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COVID-19 in children: New cases down for third straight week
New COVID-19 cases in children dropped for the third consecutive week, even as children continue to make up a larger share of all cases, according to a report from the American Academy of Pediatrics and the Children’s Hospital Association.
New child cases totaled almost 118,000 for the week of Jan. 29-Feb. 4, continuing the decline that began right after the United States topped 200,000 cases for the only time Jan. 8-14, the AAP and the CHA said in their weekly COVID-19 report.
For the latest week, however, children represented 16.0% of all new COVID-19 cases, continuing a 5-week increase that began in early December 2020, after the proportion had dropped to 12.6%, based on data collected from the health departments of 49 states (excluding New York), the District of Columbia, New York City, Puerto Rico, and Guam. During the week of Sept. 11-17, children made up 16.9% of all cases, the highest level seen during the pandemic.
The 2.93 million cases that have been reported in children make up 12.9% of all cases since the pandemic began, and the overall rate of pediatric coronavirus infection is 3,899 cases per 100,000 children in the population. Taking a step down from the national level, 30 states are above that rate and 18 are below it, along with D.C., New York City, Puerto Rico, and Guam (New York and Texas are excluded), the AAP and CHA reported.
There were 12 new COVID-19–related child deaths in the 43 states, along with New York City and Guam, that are reporting such data, bringing the total to 227. Nationally, 0.06% of all deaths have occurred in children, with rates ranging from 0.00% (11 states) to 0.26% (Nebraska) in the 45 jurisdictions, the AAP/CHA report shows.
Child hospitalizations rose to 1.9% of all hospitalizations after holding at 1.8% since mid-November in 25 reporting jurisdictions (24 states and New York City), but the hospitalization rate among children with COVID held at 0.8%, where it has been for the last 4 weeks. Hospitalization rates as high as 3.8% were recorded early in the pandemic, the AAP and CHA noted.
New COVID-19 cases in children dropped for the third consecutive week, even as children continue to make up a larger share of all cases, according to a report from the American Academy of Pediatrics and the Children’s Hospital Association.
New child cases totaled almost 118,000 for the week of Jan. 29-Feb. 4, continuing the decline that began right after the United States topped 200,000 cases for the only time Jan. 8-14, the AAP and the CHA said in their weekly COVID-19 report.
For the latest week, however, children represented 16.0% of all new COVID-19 cases, continuing a 5-week increase that began in early December 2020, after the proportion had dropped to 12.6%, based on data collected from the health departments of 49 states (excluding New York), the District of Columbia, New York City, Puerto Rico, and Guam. During the week of Sept. 11-17, children made up 16.9% of all cases, the highest level seen during the pandemic.
The 2.93 million cases that have been reported in children make up 12.9% of all cases since the pandemic began, and the overall rate of pediatric coronavirus infection is 3,899 cases per 100,000 children in the population. Taking a step down from the national level, 30 states are above that rate and 18 are below it, along with D.C., New York City, Puerto Rico, and Guam (New York and Texas are excluded), the AAP and CHA reported.
There were 12 new COVID-19–related child deaths in the 43 states, along with New York City and Guam, that are reporting such data, bringing the total to 227. Nationally, 0.06% of all deaths have occurred in children, with rates ranging from 0.00% (11 states) to 0.26% (Nebraska) in the 45 jurisdictions, the AAP/CHA report shows.
Child hospitalizations rose to 1.9% of all hospitalizations after holding at 1.8% since mid-November in 25 reporting jurisdictions (24 states and New York City), but the hospitalization rate among children with COVID held at 0.8%, where it has been for the last 4 weeks. Hospitalization rates as high as 3.8% were recorded early in the pandemic, the AAP and CHA noted.
New COVID-19 cases in children dropped for the third consecutive week, even as children continue to make up a larger share of all cases, according to a report from the American Academy of Pediatrics and the Children’s Hospital Association.
New child cases totaled almost 118,000 for the week of Jan. 29-Feb. 4, continuing the decline that began right after the United States topped 200,000 cases for the only time Jan. 8-14, the AAP and the CHA said in their weekly COVID-19 report.
For the latest week, however, children represented 16.0% of all new COVID-19 cases, continuing a 5-week increase that began in early December 2020, after the proportion had dropped to 12.6%, based on data collected from the health departments of 49 states (excluding New York), the District of Columbia, New York City, Puerto Rico, and Guam. During the week of Sept. 11-17, children made up 16.9% of all cases, the highest level seen during the pandemic.
The 2.93 million cases that have been reported in children make up 12.9% of all cases since the pandemic began, and the overall rate of pediatric coronavirus infection is 3,899 cases per 100,000 children in the population. Taking a step down from the national level, 30 states are above that rate and 18 are below it, along with D.C., New York City, Puerto Rico, and Guam (New York and Texas are excluded), the AAP and CHA reported.
There were 12 new COVID-19–related child deaths in the 43 states, along with New York City and Guam, that are reporting such data, bringing the total to 227. Nationally, 0.06% of all deaths have occurred in children, with rates ranging from 0.00% (11 states) to 0.26% (Nebraska) in the 45 jurisdictions, the AAP/CHA report shows.
Child hospitalizations rose to 1.9% of all hospitalizations after holding at 1.8% since mid-November in 25 reporting jurisdictions (24 states and New York City), but the hospitalization rate among children with COVID held at 0.8%, where it has been for the last 4 weeks. Hospitalization rates as high as 3.8% were recorded early in the pandemic, the AAP and CHA noted.
Study tests ways to increase autism screening and referrals
To improve autism screening rates, researchers in Utah tried a range of interventions.
They added automatic reminders to the electronic health record (EHR). They started using a shorter, more sensitive screening instrument. And they trained clinicians to perform autism-specific evaluations in a primary care clinic.
The researchers found that these interventions were associated with increased rates of autism screening and referrals.
At the same time, they looked at screening and referral rates at other community clinics in their health care system. These clinics incorporated EHR reminders but not all of the other changes.
“The community clinics had an increase in screening frequency with only automatic reminders,” the researchers reported. At the two intervention clinics, however, screening rates increased more than they did at the community clinics. Referrals did not significantly increase at the community clinics.
Kathleen Campbell, MD, MHSc, a pediatric resident at the University of Utah in Salt Lake City, and colleagues described their research in a study published in Pediatrics.
Three phases
They examined more than 12,000 well-child visits for children aged 16-30 months between July 2017 and June 2019.
In all, 4,155 visits occurred at the 2 intervention clinics, and 8,078 visits occurred at the 27 community clinics in the University of Utah health care system.
From baseline through the interventions, the proportion of visits with screening increased by 51% in the intervention clinics (from 58.6% to 88.8%), and by 21% in the community clinics (from 43.4% to 52.4%). The proportion of referrals increased 1.5-fold in intervention clinics, from 1.3% to 3.3%, the authors said.
The American Academy of Pediatrics (AAP) supports screening for autism in all children starting at age 18 months, but “only 44% of children with autism have had a comprehensive autism evaluation before age 36 months,” Dr. Campbell and colleagues wrote.
In their system, about half of the children were being screened for autism, and 0.5% had autism diagnosed.
In an effort to increase the proportion of visits with screening for autism and the proportion of visits with referrals for autism evaluation, Dr. Campbell and colleagues designed a quality improvement study.
Following a baseline period, they implemented interventions in three phases.
Initially, all clinics used the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) for autism screening. For the first phase starting in July 2018, the researchers changed the screening instrument at the two intervention clinics to the Parent’s Observation of Social Interaction (POSI). This instrument “is embedded in a broadband developmental screen, is shorter than the M-CHAT-R, and includes questions about the consistency of the child’s behavior,” the authors said. “The POSI has greater sensitivity than the M-CHAT-R ... and similar, although somewhat lower, specificity.”
In intervention phase 2 starting in November 2018, the researchers “added an automatic reminder for autism screening to the EHR health maintenance screen.” Both the intervention clinics and the community clinics received the automatic reminders.
In intervention phase 3 starting in February 2019, they “added a referral option that clinicians could use for rapid access to autism-specific evaluation ... for children who had a POSI result suggestive of autism and for whom the clinician had sufficient concerns about autism that would indicate the need for referral for autism evaluation,” the researchers said.
“Using an online tutorial, we trained three clinicians in the intervention clinics to administer an observational assessment known as the Screening Tool for Autism in Toddlers (STAT),” which requires a 30-minute visit, they said. “Children who had a STAT result suggestive of autism were referred for expedited autism diagnostic evaluation, which was performed by a multidisciplinary team in our university-based developmental assessment clinic. Children who had a STAT result that did not suggest autism did not receive further autism evaluations unless the clinician felt they still needed further evaluation at the developmental clinic.”
After the switch to POSI, the percentage of visits with a positive screen result increased from 4.7% to 13.5% in the intervention clinics.
Furthermore, referrals were 3.4 times more frequent for visits during phase 3 in the intervention clinics, relative to the baseline period.
Potential to overwhelm
“The change to a more sensitive screening instrument increased the frequency of screening results suggestive of autism and informed our improvement team of the need to implement autism evaluation in primary care to avoid overwhelming our referral system,” Dr. Campbell and coauthors reported.
Future studies may assess whether increased screening and referrals speed the time to diagnosis and treatment and improve long-term functional abilities of children with autism. Some children in the study have received an autism diagnosis, while others have not yet been evaluated.
The use of STAT in primary care may be limited by “the barriers of training providers and purchasing materials,” the authors noted. “However, the time-based billing for lengthier appointments and billing for developmental testing help to cover cost.”
The intervention clinics and community clinics were staffed by pediatric providers, including residents and attendings, said Dr. Campbell.
“The staffing is similar at the community and intervention clinics, with mostly pediatricians and some nurse practitioners,” Dr. Campbell said. “One difference is that there are a few family medicine physicians in the community clinics, but we did not study whether that made a difference in screening. At the beginning of the study the approach to screening was the same.”
From the start, the community clinics were screening for autism and referring for further autism evaluation less often than the intervention clinics. “I don’t know why they were screening less, but they did improve with the automatic reminders,” said Dr. Campbell. “We didn’t examine type of provider or type of practice in this study, but the literature suggests that family physicians do not screen for autism as often as pediatricians.”
Payment and referral challenges
In theory, the approach in the study is a great idea, but it may not be feasible to implement for many private practices, said Herschel Lessin, MD. Dr. Lessin is a senior partner of the Children’s Medical Group in New York.
“We desperately need autism screening in a primary care setting,” Dr. Lessin said. “These authors found that wasn’t being done as recommended by the AAP Bright Futures, which is a problem.”
However, the researchers incorporated the interventions in a health care system with “far more resources than most people in practice would ever have” and substituted a less familiar screening tool.
In addition, the ability to use confirmatory STAT for primary care evaluations may be limited. “Unless you can find pediatricians willing to commit 30 to 45 minutes on one of these evaluations ... few are going to do that,” he said.
“The whole problem is that there are no referrals available or very few referrals available, and that insurance payments so underpay for developmental screening and evaluation that it does not justify the time doing it, so a lot of doctors are unable to do it,” said Dr. Lessin. When a referral is warranted, developmental pediatricians may have 6- to 12-month waiting lists, he said.
“For people in clinical practice, this is not news,” Dr. Lessin said. “We know we should screen for autism. The problem is it’s time consuming. Nobody pays for it. We have no place to send them even when we are suspicious.”
From screening to diagnosis to treatment
“Autism screen approaches vary but with educational efforts on the part of the AAP, CDC, and family organizations the rates for autism screening have dramatically improved,” said Susan L. Hyman, MD, professor of pediatrics at the University of Rochester in New York. “I do not know if screening rates have been impacted by COVID.”
Dr. Hyman and coauthors wrote an AAP clinical report on the identification, evaluation, and management of children with autism spectrum disorder. The report was published in the January 2020 issue of Pediatrics.
After screening and diagnostic testing, patients most importantly need to be able to access “timely and equitable evidence-based intervention,” which should be available, said Dr. Hyman.
Although researchers have proposed training primary care providers in autism diagnostics, “older, more complex patients with co-occurring behavioral health or other developmental disorders may need more specialized diagnostic assessment than could be accomplished in a primary care setting,” Dr. Hyman added.
“However, it is very important to identify children with therapeutic needs as early as possible and move them through the continuum from screening to diagnosis to treatment in a timely fashion. It would be wonderful if symptoms could be addressed without the need for diagnosis in the very youngest children,” Dr. Hyman said. “Early symptoms, even if not autism, are likely to be appropriate for intervention – whether it is speech therapy, attention to food selectivity, sleep problems – things that impact quality of life and potential future symptoms.”
The research was supported by the Utah Stimulating Access to Research in Residency Transition Scholar award, which is funded by the National Institutes of Health.
Dr. Campbell is an inventor on a patent related to screening for autism. The study authors otherwise had no disclosures. Dr. Lessin is on the editorial advisory board for Pediatric News and is on an advisory board for Cognoa, which is developing a medical device to diagnose autism and he is also the co-editor of the AAP's current ADHD Toolkit. Dr. Hyman had no relevant financial disclosures.
*This story was updated on Feb. 11, 2021.
To improve autism screening rates, researchers in Utah tried a range of interventions.
They added automatic reminders to the electronic health record (EHR). They started using a shorter, more sensitive screening instrument. And they trained clinicians to perform autism-specific evaluations in a primary care clinic.
The researchers found that these interventions were associated with increased rates of autism screening and referrals.
At the same time, they looked at screening and referral rates at other community clinics in their health care system. These clinics incorporated EHR reminders but not all of the other changes.
“The community clinics had an increase in screening frequency with only automatic reminders,” the researchers reported. At the two intervention clinics, however, screening rates increased more than they did at the community clinics. Referrals did not significantly increase at the community clinics.
Kathleen Campbell, MD, MHSc, a pediatric resident at the University of Utah in Salt Lake City, and colleagues described their research in a study published in Pediatrics.
Three phases
They examined more than 12,000 well-child visits for children aged 16-30 months between July 2017 and June 2019.
In all, 4,155 visits occurred at the 2 intervention clinics, and 8,078 visits occurred at the 27 community clinics in the University of Utah health care system.
From baseline through the interventions, the proportion of visits with screening increased by 51% in the intervention clinics (from 58.6% to 88.8%), and by 21% in the community clinics (from 43.4% to 52.4%). The proportion of referrals increased 1.5-fold in intervention clinics, from 1.3% to 3.3%, the authors said.
The American Academy of Pediatrics (AAP) supports screening for autism in all children starting at age 18 months, but “only 44% of children with autism have had a comprehensive autism evaluation before age 36 months,” Dr. Campbell and colleagues wrote.
In their system, about half of the children were being screened for autism, and 0.5% had autism diagnosed.
In an effort to increase the proportion of visits with screening for autism and the proportion of visits with referrals for autism evaluation, Dr. Campbell and colleagues designed a quality improvement study.
Following a baseline period, they implemented interventions in three phases.
Initially, all clinics used the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) for autism screening. For the first phase starting in July 2018, the researchers changed the screening instrument at the two intervention clinics to the Parent’s Observation of Social Interaction (POSI). This instrument “is embedded in a broadband developmental screen, is shorter than the M-CHAT-R, and includes questions about the consistency of the child’s behavior,” the authors said. “The POSI has greater sensitivity than the M-CHAT-R ... and similar, although somewhat lower, specificity.”
In intervention phase 2 starting in November 2018, the researchers “added an automatic reminder for autism screening to the EHR health maintenance screen.” Both the intervention clinics and the community clinics received the automatic reminders.
In intervention phase 3 starting in February 2019, they “added a referral option that clinicians could use for rapid access to autism-specific evaluation ... for children who had a POSI result suggestive of autism and for whom the clinician had sufficient concerns about autism that would indicate the need for referral for autism evaluation,” the researchers said.
“Using an online tutorial, we trained three clinicians in the intervention clinics to administer an observational assessment known as the Screening Tool for Autism in Toddlers (STAT),” which requires a 30-minute visit, they said. “Children who had a STAT result suggestive of autism were referred for expedited autism diagnostic evaluation, which was performed by a multidisciplinary team in our university-based developmental assessment clinic. Children who had a STAT result that did not suggest autism did not receive further autism evaluations unless the clinician felt they still needed further evaluation at the developmental clinic.”
After the switch to POSI, the percentage of visits with a positive screen result increased from 4.7% to 13.5% in the intervention clinics.
Furthermore, referrals were 3.4 times more frequent for visits during phase 3 in the intervention clinics, relative to the baseline period.
Potential to overwhelm
“The change to a more sensitive screening instrument increased the frequency of screening results suggestive of autism and informed our improvement team of the need to implement autism evaluation in primary care to avoid overwhelming our referral system,” Dr. Campbell and coauthors reported.
Future studies may assess whether increased screening and referrals speed the time to diagnosis and treatment and improve long-term functional abilities of children with autism. Some children in the study have received an autism diagnosis, while others have not yet been evaluated.
The use of STAT in primary care may be limited by “the barriers of training providers and purchasing materials,” the authors noted. “However, the time-based billing for lengthier appointments and billing for developmental testing help to cover cost.”
The intervention clinics and community clinics were staffed by pediatric providers, including residents and attendings, said Dr. Campbell.
“The staffing is similar at the community and intervention clinics, with mostly pediatricians and some nurse practitioners,” Dr. Campbell said. “One difference is that there are a few family medicine physicians in the community clinics, but we did not study whether that made a difference in screening. At the beginning of the study the approach to screening was the same.”
From the start, the community clinics were screening for autism and referring for further autism evaluation less often than the intervention clinics. “I don’t know why they were screening less, but they did improve with the automatic reminders,” said Dr. Campbell. “We didn’t examine type of provider or type of practice in this study, but the literature suggests that family physicians do not screen for autism as often as pediatricians.”
Payment and referral challenges
In theory, the approach in the study is a great idea, but it may not be feasible to implement for many private practices, said Herschel Lessin, MD. Dr. Lessin is a senior partner of the Children’s Medical Group in New York.
“We desperately need autism screening in a primary care setting,” Dr. Lessin said. “These authors found that wasn’t being done as recommended by the AAP Bright Futures, which is a problem.”
However, the researchers incorporated the interventions in a health care system with “far more resources than most people in practice would ever have” and substituted a less familiar screening tool.
In addition, the ability to use confirmatory STAT for primary care evaluations may be limited. “Unless you can find pediatricians willing to commit 30 to 45 minutes on one of these evaluations ... few are going to do that,” he said.
“The whole problem is that there are no referrals available or very few referrals available, and that insurance payments so underpay for developmental screening and evaluation that it does not justify the time doing it, so a lot of doctors are unable to do it,” said Dr. Lessin. When a referral is warranted, developmental pediatricians may have 6- to 12-month waiting lists, he said.
“For people in clinical practice, this is not news,” Dr. Lessin said. “We know we should screen for autism. The problem is it’s time consuming. Nobody pays for it. We have no place to send them even when we are suspicious.”
From screening to diagnosis to treatment
“Autism screen approaches vary but with educational efforts on the part of the AAP, CDC, and family organizations the rates for autism screening have dramatically improved,” said Susan L. Hyman, MD, professor of pediatrics at the University of Rochester in New York. “I do not know if screening rates have been impacted by COVID.”
Dr. Hyman and coauthors wrote an AAP clinical report on the identification, evaluation, and management of children with autism spectrum disorder. The report was published in the January 2020 issue of Pediatrics.
After screening and diagnostic testing, patients most importantly need to be able to access “timely and equitable evidence-based intervention,” which should be available, said Dr. Hyman.
Although researchers have proposed training primary care providers in autism diagnostics, “older, more complex patients with co-occurring behavioral health or other developmental disorders may need more specialized diagnostic assessment than could be accomplished in a primary care setting,” Dr. Hyman added.
“However, it is very important to identify children with therapeutic needs as early as possible and move them through the continuum from screening to diagnosis to treatment in a timely fashion. It would be wonderful if symptoms could be addressed without the need for diagnosis in the very youngest children,” Dr. Hyman said. “Early symptoms, even if not autism, are likely to be appropriate for intervention – whether it is speech therapy, attention to food selectivity, sleep problems – things that impact quality of life and potential future symptoms.”
The research was supported by the Utah Stimulating Access to Research in Residency Transition Scholar award, which is funded by the National Institutes of Health.
Dr. Campbell is an inventor on a patent related to screening for autism. The study authors otherwise had no disclosures. Dr. Lessin is on the editorial advisory board for Pediatric News and is on an advisory board for Cognoa, which is developing a medical device to diagnose autism and he is also the co-editor of the AAP's current ADHD Toolkit. Dr. Hyman had no relevant financial disclosures.
*This story was updated on Feb. 11, 2021.
To improve autism screening rates, researchers in Utah tried a range of interventions.
They added automatic reminders to the electronic health record (EHR). They started using a shorter, more sensitive screening instrument. And they trained clinicians to perform autism-specific evaluations in a primary care clinic.
The researchers found that these interventions were associated with increased rates of autism screening and referrals.
At the same time, they looked at screening and referral rates at other community clinics in their health care system. These clinics incorporated EHR reminders but not all of the other changes.
“The community clinics had an increase in screening frequency with only automatic reminders,” the researchers reported. At the two intervention clinics, however, screening rates increased more than they did at the community clinics. Referrals did not significantly increase at the community clinics.
Kathleen Campbell, MD, MHSc, a pediatric resident at the University of Utah in Salt Lake City, and colleagues described their research in a study published in Pediatrics.
Three phases
They examined more than 12,000 well-child visits for children aged 16-30 months between July 2017 and June 2019.
In all, 4,155 visits occurred at the 2 intervention clinics, and 8,078 visits occurred at the 27 community clinics in the University of Utah health care system.
From baseline through the interventions, the proportion of visits with screening increased by 51% in the intervention clinics (from 58.6% to 88.8%), and by 21% in the community clinics (from 43.4% to 52.4%). The proportion of referrals increased 1.5-fold in intervention clinics, from 1.3% to 3.3%, the authors said.
The American Academy of Pediatrics (AAP) supports screening for autism in all children starting at age 18 months, but “only 44% of children with autism have had a comprehensive autism evaluation before age 36 months,” Dr. Campbell and colleagues wrote.
In their system, about half of the children were being screened for autism, and 0.5% had autism diagnosed.
In an effort to increase the proportion of visits with screening for autism and the proportion of visits with referrals for autism evaluation, Dr. Campbell and colleagues designed a quality improvement study.
Following a baseline period, they implemented interventions in three phases.
Initially, all clinics used the Modified Checklist for Autism in Toddlers, Revised (M-CHAT-R) for autism screening. For the first phase starting in July 2018, the researchers changed the screening instrument at the two intervention clinics to the Parent’s Observation of Social Interaction (POSI). This instrument “is embedded in a broadband developmental screen, is shorter than the M-CHAT-R, and includes questions about the consistency of the child’s behavior,” the authors said. “The POSI has greater sensitivity than the M-CHAT-R ... and similar, although somewhat lower, specificity.”
In intervention phase 2 starting in November 2018, the researchers “added an automatic reminder for autism screening to the EHR health maintenance screen.” Both the intervention clinics and the community clinics received the automatic reminders.
In intervention phase 3 starting in February 2019, they “added a referral option that clinicians could use for rapid access to autism-specific evaluation ... for children who had a POSI result suggestive of autism and for whom the clinician had sufficient concerns about autism that would indicate the need for referral for autism evaluation,” the researchers said.
“Using an online tutorial, we trained three clinicians in the intervention clinics to administer an observational assessment known as the Screening Tool for Autism in Toddlers (STAT),” which requires a 30-minute visit, they said. “Children who had a STAT result suggestive of autism were referred for expedited autism diagnostic evaluation, which was performed by a multidisciplinary team in our university-based developmental assessment clinic. Children who had a STAT result that did not suggest autism did not receive further autism evaluations unless the clinician felt they still needed further evaluation at the developmental clinic.”
After the switch to POSI, the percentage of visits with a positive screen result increased from 4.7% to 13.5% in the intervention clinics.
Furthermore, referrals were 3.4 times more frequent for visits during phase 3 in the intervention clinics, relative to the baseline period.
Potential to overwhelm
“The change to a more sensitive screening instrument increased the frequency of screening results suggestive of autism and informed our improvement team of the need to implement autism evaluation in primary care to avoid overwhelming our referral system,” Dr. Campbell and coauthors reported.
Future studies may assess whether increased screening and referrals speed the time to diagnosis and treatment and improve long-term functional abilities of children with autism. Some children in the study have received an autism diagnosis, while others have not yet been evaluated.
The use of STAT in primary care may be limited by “the barriers of training providers and purchasing materials,” the authors noted. “However, the time-based billing for lengthier appointments and billing for developmental testing help to cover cost.”
The intervention clinics and community clinics were staffed by pediatric providers, including residents and attendings, said Dr. Campbell.
“The staffing is similar at the community and intervention clinics, with mostly pediatricians and some nurse practitioners,” Dr. Campbell said. “One difference is that there are a few family medicine physicians in the community clinics, but we did not study whether that made a difference in screening. At the beginning of the study the approach to screening was the same.”
From the start, the community clinics were screening for autism and referring for further autism evaluation less often than the intervention clinics. “I don’t know why they were screening less, but they did improve with the automatic reminders,” said Dr. Campbell. “We didn’t examine type of provider or type of practice in this study, but the literature suggests that family physicians do not screen for autism as often as pediatricians.”
Payment and referral challenges
In theory, the approach in the study is a great idea, but it may not be feasible to implement for many private practices, said Herschel Lessin, MD. Dr. Lessin is a senior partner of the Children’s Medical Group in New York.
“We desperately need autism screening in a primary care setting,” Dr. Lessin said. “These authors found that wasn’t being done as recommended by the AAP Bright Futures, which is a problem.”
However, the researchers incorporated the interventions in a health care system with “far more resources than most people in practice would ever have” and substituted a less familiar screening tool.
In addition, the ability to use confirmatory STAT for primary care evaluations may be limited. “Unless you can find pediatricians willing to commit 30 to 45 minutes on one of these evaluations ... few are going to do that,” he said.
“The whole problem is that there are no referrals available or very few referrals available, and that insurance payments so underpay for developmental screening and evaluation that it does not justify the time doing it, so a lot of doctors are unable to do it,” said Dr. Lessin. When a referral is warranted, developmental pediatricians may have 6- to 12-month waiting lists, he said.
“For people in clinical practice, this is not news,” Dr. Lessin said. “We know we should screen for autism. The problem is it’s time consuming. Nobody pays for it. We have no place to send them even when we are suspicious.”
From screening to diagnosis to treatment
“Autism screen approaches vary but with educational efforts on the part of the AAP, CDC, and family organizations the rates for autism screening have dramatically improved,” said Susan L. Hyman, MD, professor of pediatrics at the University of Rochester in New York. “I do not know if screening rates have been impacted by COVID.”
Dr. Hyman and coauthors wrote an AAP clinical report on the identification, evaluation, and management of children with autism spectrum disorder. The report was published in the January 2020 issue of Pediatrics.
After screening and diagnostic testing, patients most importantly need to be able to access “timely and equitable evidence-based intervention,” which should be available, said Dr. Hyman.
Although researchers have proposed training primary care providers in autism diagnostics, “older, more complex patients with co-occurring behavioral health or other developmental disorders may need more specialized diagnostic assessment than could be accomplished in a primary care setting,” Dr. Hyman added.
“However, it is very important to identify children with therapeutic needs as early as possible and move them through the continuum from screening to diagnosis to treatment in a timely fashion. It would be wonderful if symptoms could be addressed without the need for diagnosis in the very youngest children,” Dr. Hyman said. “Early symptoms, even if not autism, are likely to be appropriate for intervention – whether it is speech therapy, attention to food selectivity, sleep problems – things that impact quality of life and potential future symptoms.”
The research was supported by the Utah Stimulating Access to Research in Residency Transition Scholar award, which is funded by the National Institutes of Health.
Dr. Campbell is an inventor on a patent related to screening for autism. The study authors otherwise had no disclosures. Dr. Lessin is on the editorial advisory board for Pediatric News and is on an advisory board for Cognoa, which is developing a medical device to diagnose autism and he is also the co-editor of the AAP's current ADHD Toolkit. Dr. Hyman had no relevant financial disclosures.
*This story was updated on Feb. 11, 2021.
FROM PEDIATRICS
Coffee lowers heart failure risk in unique study
Higher coffee consumption is associated with a lower risk of heart failure, according to a machine learning–based algorithm that analyzed data from three large observational trials.
“Coffee consumption actually was predictive on top of known risk factors originally identified from those three trials.” The study is significant because it underscores the potential of big data for individualizing patient management, lead investigator David Kao, MD, said in an interview. “We in fact adjusted for the scores that are commonly used to predict heart disease, and coffee consumption remained a predictor even on top of that.”
The study used supervised machine learning to analyze data on diet and other variables from three well-known observational studies: Framingham Heart Study (FHS), Cardiovascular Heart Study (CHS), and ARIC (Atherosclerosis Risk in Communities). The goal of the study, published online on Feb. 9, 2021*, was to identify potential novel risk factors for incident coronary heart disease, stroke, and heart failure.
“The main difference of the relationship between coffee and heart disease, compared with prior analyses, is that we’re able to find it in these well-known and well-accepted studies that have helped us find risk factors before,” Dr. Kao said
The study included 2,732 FHS participants aged 30-62 years, 3,704 CHS patients aged 65 and older, and 14,925 ARIC subjects aged 45-64, all of whom had no history of cardiovascular disease events when they enrolled. Primary outcomes for the machine-learning study were times to incident coronary heart disease, heart failure, and stroke.
Mathematics, not hypotheses
To compensate for variations in methodologies between the three observational trials, the study used 204 data measurements collected at the first FHS exam, including 16 dietary variables and for which similar data were collected for the other two studies.
The machine-learning model used what’s known as a random forest analysis to identify the leading potential risk factors from among the 204 variables. To confirm findings between studies, the authors used a technique called “data harmonization” to smooth variations in the methodologies of the trials, not only with participant age and duration and date of the trials, but also in how data on coffee consumption were gathered. For example, FHS collected that data as cups per day, whereas CHS and ARIC collected that as monthly, weekly, and daily consumption. The study converted the coffee consumption data from CHS and ARIC to cups per day to conform to FHS data.
Random forest analysis is a type of machine learning that randomly creates a cluster of decision trees – the “forest” – to determine which variables, such as dietary factors, are important in predicting a result. The analysis uses mathematics, not hypotheses, to identify important variables.
Heart failure and risk reduced
In this study, the analysis determined that each cup of caffeinated coffee daily was linked with a 5% reduction in the risk of heart failure (hazard ratio, 0.95; P = .02) and 6% reduction in stroke risk (HR, 0.94; P = .02), but had no significant impact on risk for coronary heart disease or cardiovascular disease.
When the data were adjusted for the FHS CVD risk score, increasing coffee consumption remained significantly associated with an identical lower risk of heart failure (P = .03) but not stroke (P = .33).
While the study supports an association between coffee consumption and heart failure risk, it doesn’t establish causation, noted Alice H. Lichtenstein, DSc, director and senior scientist at the Cardiovascular Nutrition Laboratory at Tufts University, Boston. “The authors could not rule out the possibility that caffeinated coffee intake was a proxy for other heart-healthy lifestyle behaviors,” Dr. Lichtenstein said. “Perhaps the best message from the study is that there appears to be no adverse effects of drinking moderate amounts of caffeinated coffee, and there may be benefits.”
She added a note of caution. “This result does not suggest coffee intake should be increased, nor does it give license to increasing coffee drinks with a lot of added cream and sugar.”
Machine learning mines observational trials
Dr. Kao explained the rationale for applying a machine-learning algorithm to the three observational trials. “When these trials were designed in general, they had an idea of what they were looking for in terms of what might be a risk factor,” said Dr. Kao, of the University of Colorado at Denver, Aurora. “What we were interested in doing was to look for risk factors that nobody really thought about ahead of time and let the data show us what might be a predictor without any bias of what we imagined to be true.”
He described the role of machine learning in extracting and “filtering” data from the trials. “Machine learning allows us to look at a very large number of factors or variables and identify the most important ones in predicting a specific outcome,” he said. This study evaluated the 204 variables and focused on dietary factors because they’re modifiable.
“We looked at them in these different studies where we could, and coffee was the one that was reproducible in all of them,” he said. “Machine learning helped filter down these very large numbers of variables in ways you can’t do with traditional statistics. It’s useful in studies like this because they gather thousands and thousands of variables that generally nobody uses, but these methods allow you to actually do something with them – to determine which ones are most important.”
He added: “These methods I think will take us toward personalized medicine where you’re really individualizing a plan for keeping a patient healthy. We still have a lot of work to do, but there’s a lot of promise for really helping each of us to figure out the ways we can become the healthiest that we can be.”
The study was supported with funding from the National Heart, Lung, and Blood Institute and the American Heart Association. Dr. Kao and coauthors, as well as Dr. Lichtenstein, had no relevant financial relationships to disclose.
*Correction, 2/10/21: An earlier version of this article misstated the study's publication date.
Higher coffee consumption is associated with a lower risk of heart failure, according to a machine learning–based algorithm that analyzed data from three large observational trials.
“Coffee consumption actually was predictive on top of known risk factors originally identified from those three trials.” The study is significant because it underscores the potential of big data for individualizing patient management, lead investigator David Kao, MD, said in an interview. “We in fact adjusted for the scores that are commonly used to predict heart disease, and coffee consumption remained a predictor even on top of that.”
The study used supervised machine learning to analyze data on diet and other variables from three well-known observational studies: Framingham Heart Study (FHS), Cardiovascular Heart Study (CHS), and ARIC (Atherosclerosis Risk in Communities). The goal of the study, published online on Feb. 9, 2021*, was to identify potential novel risk factors for incident coronary heart disease, stroke, and heart failure.
“The main difference of the relationship between coffee and heart disease, compared with prior analyses, is that we’re able to find it in these well-known and well-accepted studies that have helped us find risk factors before,” Dr. Kao said
The study included 2,732 FHS participants aged 30-62 years, 3,704 CHS patients aged 65 and older, and 14,925 ARIC subjects aged 45-64, all of whom had no history of cardiovascular disease events when they enrolled. Primary outcomes for the machine-learning study were times to incident coronary heart disease, heart failure, and stroke.
Mathematics, not hypotheses
To compensate for variations in methodologies between the three observational trials, the study used 204 data measurements collected at the first FHS exam, including 16 dietary variables and for which similar data were collected for the other two studies.
The machine-learning model used what’s known as a random forest analysis to identify the leading potential risk factors from among the 204 variables. To confirm findings between studies, the authors used a technique called “data harmonization” to smooth variations in the methodologies of the trials, not only with participant age and duration and date of the trials, but also in how data on coffee consumption were gathered. For example, FHS collected that data as cups per day, whereas CHS and ARIC collected that as monthly, weekly, and daily consumption. The study converted the coffee consumption data from CHS and ARIC to cups per day to conform to FHS data.
Random forest analysis is a type of machine learning that randomly creates a cluster of decision trees – the “forest” – to determine which variables, such as dietary factors, are important in predicting a result. The analysis uses mathematics, not hypotheses, to identify important variables.
Heart failure and risk reduced
In this study, the analysis determined that each cup of caffeinated coffee daily was linked with a 5% reduction in the risk of heart failure (hazard ratio, 0.95; P = .02) and 6% reduction in stroke risk (HR, 0.94; P = .02), but had no significant impact on risk for coronary heart disease or cardiovascular disease.
When the data were adjusted for the FHS CVD risk score, increasing coffee consumption remained significantly associated with an identical lower risk of heart failure (P = .03) but not stroke (P = .33).
While the study supports an association between coffee consumption and heart failure risk, it doesn’t establish causation, noted Alice H. Lichtenstein, DSc, director and senior scientist at the Cardiovascular Nutrition Laboratory at Tufts University, Boston. “The authors could not rule out the possibility that caffeinated coffee intake was a proxy for other heart-healthy lifestyle behaviors,” Dr. Lichtenstein said. “Perhaps the best message from the study is that there appears to be no adverse effects of drinking moderate amounts of caffeinated coffee, and there may be benefits.”
She added a note of caution. “This result does not suggest coffee intake should be increased, nor does it give license to increasing coffee drinks with a lot of added cream and sugar.”
Machine learning mines observational trials
Dr. Kao explained the rationale for applying a machine-learning algorithm to the three observational trials. “When these trials were designed in general, they had an idea of what they were looking for in terms of what might be a risk factor,” said Dr. Kao, of the University of Colorado at Denver, Aurora. “What we were interested in doing was to look for risk factors that nobody really thought about ahead of time and let the data show us what might be a predictor without any bias of what we imagined to be true.”
He described the role of machine learning in extracting and “filtering” data from the trials. “Machine learning allows us to look at a very large number of factors or variables and identify the most important ones in predicting a specific outcome,” he said. This study evaluated the 204 variables and focused on dietary factors because they’re modifiable.
“We looked at them in these different studies where we could, and coffee was the one that was reproducible in all of them,” he said. “Machine learning helped filter down these very large numbers of variables in ways you can’t do with traditional statistics. It’s useful in studies like this because they gather thousands and thousands of variables that generally nobody uses, but these methods allow you to actually do something with them – to determine which ones are most important.”
He added: “These methods I think will take us toward personalized medicine where you’re really individualizing a plan for keeping a patient healthy. We still have a lot of work to do, but there’s a lot of promise for really helping each of us to figure out the ways we can become the healthiest that we can be.”
The study was supported with funding from the National Heart, Lung, and Blood Institute and the American Heart Association. Dr. Kao and coauthors, as well as Dr. Lichtenstein, had no relevant financial relationships to disclose.
*Correction, 2/10/21: An earlier version of this article misstated the study's publication date.
Higher coffee consumption is associated with a lower risk of heart failure, according to a machine learning–based algorithm that analyzed data from three large observational trials.
“Coffee consumption actually was predictive on top of known risk factors originally identified from those three trials.” The study is significant because it underscores the potential of big data for individualizing patient management, lead investigator David Kao, MD, said in an interview. “We in fact adjusted for the scores that are commonly used to predict heart disease, and coffee consumption remained a predictor even on top of that.”
The study used supervised machine learning to analyze data on diet and other variables from three well-known observational studies: Framingham Heart Study (FHS), Cardiovascular Heart Study (CHS), and ARIC (Atherosclerosis Risk in Communities). The goal of the study, published online on Feb. 9, 2021*, was to identify potential novel risk factors for incident coronary heart disease, stroke, and heart failure.
“The main difference of the relationship between coffee and heart disease, compared with prior analyses, is that we’re able to find it in these well-known and well-accepted studies that have helped us find risk factors before,” Dr. Kao said
The study included 2,732 FHS participants aged 30-62 years, 3,704 CHS patients aged 65 and older, and 14,925 ARIC subjects aged 45-64, all of whom had no history of cardiovascular disease events when they enrolled. Primary outcomes for the machine-learning study were times to incident coronary heart disease, heart failure, and stroke.
Mathematics, not hypotheses
To compensate for variations in methodologies between the three observational trials, the study used 204 data measurements collected at the first FHS exam, including 16 dietary variables and for which similar data were collected for the other two studies.
The machine-learning model used what’s known as a random forest analysis to identify the leading potential risk factors from among the 204 variables. To confirm findings between studies, the authors used a technique called “data harmonization” to smooth variations in the methodologies of the trials, not only with participant age and duration and date of the trials, but also in how data on coffee consumption were gathered. For example, FHS collected that data as cups per day, whereas CHS and ARIC collected that as monthly, weekly, and daily consumption. The study converted the coffee consumption data from CHS and ARIC to cups per day to conform to FHS data.
Random forest analysis is a type of machine learning that randomly creates a cluster of decision trees – the “forest” – to determine which variables, such as dietary factors, are important in predicting a result. The analysis uses mathematics, not hypotheses, to identify important variables.
Heart failure and risk reduced
In this study, the analysis determined that each cup of caffeinated coffee daily was linked with a 5% reduction in the risk of heart failure (hazard ratio, 0.95; P = .02) and 6% reduction in stroke risk (HR, 0.94; P = .02), but had no significant impact on risk for coronary heart disease or cardiovascular disease.
When the data were adjusted for the FHS CVD risk score, increasing coffee consumption remained significantly associated with an identical lower risk of heart failure (P = .03) but not stroke (P = .33).
While the study supports an association between coffee consumption and heart failure risk, it doesn’t establish causation, noted Alice H. Lichtenstein, DSc, director and senior scientist at the Cardiovascular Nutrition Laboratory at Tufts University, Boston. “The authors could not rule out the possibility that caffeinated coffee intake was a proxy for other heart-healthy lifestyle behaviors,” Dr. Lichtenstein said. “Perhaps the best message from the study is that there appears to be no adverse effects of drinking moderate amounts of caffeinated coffee, and there may be benefits.”
She added a note of caution. “This result does not suggest coffee intake should be increased, nor does it give license to increasing coffee drinks with a lot of added cream and sugar.”
Machine learning mines observational trials
Dr. Kao explained the rationale for applying a machine-learning algorithm to the three observational trials. “When these trials were designed in general, they had an idea of what they were looking for in terms of what might be a risk factor,” said Dr. Kao, of the University of Colorado at Denver, Aurora. “What we were interested in doing was to look for risk factors that nobody really thought about ahead of time and let the data show us what might be a predictor without any bias of what we imagined to be true.”
He described the role of machine learning in extracting and “filtering” data from the trials. “Machine learning allows us to look at a very large number of factors or variables and identify the most important ones in predicting a specific outcome,” he said. This study evaluated the 204 variables and focused on dietary factors because they’re modifiable.
“We looked at them in these different studies where we could, and coffee was the one that was reproducible in all of them,” he said. “Machine learning helped filter down these very large numbers of variables in ways you can’t do with traditional statistics. It’s useful in studies like this because they gather thousands and thousands of variables that generally nobody uses, but these methods allow you to actually do something with them – to determine which ones are most important.”
He added: “These methods I think will take us toward personalized medicine where you’re really individualizing a plan for keeping a patient healthy. We still have a lot of work to do, but there’s a lot of promise for really helping each of us to figure out the ways we can become the healthiest that we can be.”
The study was supported with funding from the National Heart, Lung, and Blood Institute and the American Heart Association. Dr. Kao and coauthors, as well as Dr. Lichtenstein, had no relevant financial relationships to disclose.
*Correction, 2/10/21: An earlier version of this article misstated the study's publication date.
FROM CIRCULATION: HEART FAILURE
Customized chemotherapy did not improve survival in early NSCLC
The patients were randomized to receive investigator’s choice of platinum-based chemotherapy or treatment tailored according to messenger RNA (mRNA) expression of two molecular markers – excision repair cross complementation 1 (ERCC1) and thymidylate synthase (TS).
There was no significant difference in overall survival or recurrence-free survival between the treatment approaches. However, toxicity was less common among patients who received customized treatment.
These results, from the phase 3 ITACA trial, were presented at the 2020 World Conference on Lung Cancer (Abstract 1820), which was rescheduled to January 2021.
“There is a clear need to define patients most likely to derive survival benefit from adjuvant therapy and spare patients who do not need adjuvant chemotherapy due to the toxicity of such therapy,” said presenter Silvia Novello, MD, PhD, of the University of Turin in Italy. “mRNA expression of different genes has been correlated with the sensitivity or resistance to specific anticancer agents.”
With this in mind, Dr. Novello and colleagues conducted the ITACA trial. The researchers’ primary goal was to determine whether an adjuvant pharmacogenomic-driven approach was able to improve overall survival in completely resected NSCLC.
Patients and treatment
The researchers randomized 773 NSCLC patients within 5-8 weeks after radical surgery. Genomic analyses were performed soon after surgery, and patients were randomly assigned to investigator’s choice of platinum-based chemotherapy or to tailored treatments defined by mRNA levels of ERCC1 and TS.
Patients with high ERCC1 mRNA expression who were randomized to tailored treatment received single-agent docetaxel if their TS level was high or pemetrexed monotherapy if their TS level was low.
Patients with low ERCC1 mRNA expression who were randomized to tailored treatment received cisplatin-gemcitabine if their TS level was high or cisplatin-pemetrexed if their TS was low.
The most frequent doublets used in control patients were cisplatin-gemcitabine and cisplatin-vinorelbine.
The demographic characteristics of the 384 patients randomized to tailored therapy and the 389 control subjects were well-balanced, Dr. Novello said. Two-thirds of patients had stage II disease, 11% were never smokers, and the vast majority had a lobectomy as the resection method.
Results
At a median follow-up of 28.2 months, the median overall survival was 96.4 months in the tailored therapy arm and 83.5 months in the control arm. The median recurrence-free survival was 64.4 months and 41.5 months, respectively.
“Adjuvant chemotherapy customization based on the primary tumor tissue mRNA expression of ERCC1 and TS did not significantly improve overall survival or recurrence-free survival,” Dr. Novello said. “There was a non–statistically significant trend for overall survival favoring the customized arm.”
Dr. Novello noted that, when the final analysis was performed, the study was underpowered, as only 46% of expected events were collected. Assuming the same hazard ratio point estimate and that the expected 336 events were collected, the hazard ratio estimate would be 0.76 (P = .012).
Grade 3/4 toxicities occurred in 32.6% of patients in the tailored therapy arm and 45.9% of those in the control arm (P < .001).
“It is important to underline that the treatment customization significantly improved the toxicity profile without compromising the efficacy,” Dr. Novello said.
She added that “more comprehensive and high-throughput diagnostic techniques will be needed in order to tailor adjuvant chemotherapy, with or without immunotherapy, in completely resected NSCLC.”
“The ITACA study is the largest adjuvant study tailored to ERCC1/TS status, and the results have been long-awaited,” said Tetsuya Mitsudomi, MD, a professor at Kindai University in Japan and president of the International Association for the Study of Lung Cancer.
“This trial should be praised for the mandated genomic analysis that was accomplished within a reasonably short time frame before random assignment. In addition, this trial confirmed that there is no biomarker strong enough to predict the efficacy of cytotoxic chemotherapy. However, the concept of customizing adjuvant therapy according to the genomic status of patients’ tumors is valid, leading to the recent demonstration in the ADAURA study of the superiority of osimertinib in delaying the postoperative recurrence of disease in patients with EGFR-mutated NSCLC.”
The ITACA study was funded by University of Turin and Eli Lilly. Dr. Novello disclosed relationships with Eli Lilly, Amgen, AstraZeneca, Bohringer Ingelheim, Beigene, Pfizer, Roche, Merck, Bristol-Myers Squibb, Takeda, and Sanofi. Dr. Mitsudomi disclosed relationships with Eli Lilly, AstraZeneca, Boehringer-Ingelheim, Chugai, Pfizer, Merck, Ono Pharmaceutical, Bristol-Myers Squibb, Novartis, ThermoFisher, Guardant, Eisai, Amgen, and Johnson & Johnson.
The patients were randomized to receive investigator’s choice of platinum-based chemotherapy or treatment tailored according to messenger RNA (mRNA) expression of two molecular markers – excision repair cross complementation 1 (ERCC1) and thymidylate synthase (TS).
There was no significant difference in overall survival or recurrence-free survival between the treatment approaches. However, toxicity was less common among patients who received customized treatment.
These results, from the phase 3 ITACA trial, were presented at the 2020 World Conference on Lung Cancer (Abstract 1820), which was rescheduled to January 2021.
“There is a clear need to define patients most likely to derive survival benefit from adjuvant therapy and spare patients who do not need adjuvant chemotherapy due to the toxicity of such therapy,” said presenter Silvia Novello, MD, PhD, of the University of Turin in Italy. “mRNA expression of different genes has been correlated with the sensitivity or resistance to specific anticancer agents.”
With this in mind, Dr. Novello and colleagues conducted the ITACA trial. The researchers’ primary goal was to determine whether an adjuvant pharmacogenomic-driven approach was able to improve overall survival in completely resected NSCLC.
Patients and treatment
The researchers randomized 773 NSCLC patients within 5-8 weeks after radical surgery. Genomic analyses were performed soon after surgery, and patients were randomly assigned to investigator’s choice of platinum-based chemotherapy or to tailored treatments defined by mRNA levels of ERCC1 and TS.
Patients with high ERCC1 mRNA expression who were randomized to tailored treatment received single-agent docetaxel if their TS level was high or pemetrexed monotherapy if their TS level was low.
Patients with low ERCC1 mRNA expression who were randomized to tailored treatment received cisplatin-gemcitabine if their TS level was high or cisplatin-pemetrexed if their TS was low.
The most frequent doublets used in control patients were cisplatin-gemcitabine and cisplatin-vinorelbine.
The demographic characteristics of the 384 patients randomized to tailored therapy and the 389 control subjects were well-balanced, Dr. Novello said. Two-thirds of patients had stage II disease, 11% were never smokers, and the vast majority had a lobectomy as the resection method.
Results
At a median follow-up of 28.2 months, the median overall survival was 96.4 months in the tailored therapy arm and 83.5 months in the control arm. The median recurrence-free survival was 64.4 months and 41.5 months, respectively.
“Adjuvant chemotherapy customization based on the primary tumor tissue mRNA expression of ERCC1 and TS did not significantly improve overall survival or recurrence-free survival,” Dr. Novello said. “There was a non–statistically significant trend for overall survival favoring the customized arm.”
Dr. Novello noted that, when the final analysis was performed, the study was underpowered, as only 46% of expected events were collected. Assuming the same hazard ratio point estimate and that the expected 336 events were collected, the hazard ratio estimate would be 0.76 (P = .012).
Grade 3/4 toxicities occurred in 32.6% of patients in the tailored therapy arm and 45.9% of those in the control arm (P < .001).
“It is important to underline that the treatment customization significantly improved the toxicity profile without compromising the efficacy,” Dr. Novello said.
She added that “more comprehensive and high-throughput diagnostic techniques will be needed in order to tailor adjuvant chemotherapy, with or without immunotherapy, in completely resected NSCLC.”
“The ITACA study is the largest adjuvant study tailored to ERCC1/TS status, and the results have been long-awaited,” said Tetsuya Mitsudomi, MD, a professor at Kindai University in Japan and president of the International Association for the Study of Lung Cancer.
“This trial should be praised for the mandated genomic analysis that was accomplished within a reasonably short time frame before random assignment. In addition, this trial confirmed that there is no biomarker strong enough to predict the efficacy of cytotoxic chemotherapy. However, the concept of customizing adjuvant therapy according to the genomic status of patients’ tumors is valid, leading to the recent demonstration in the ADAURA study of the superiority of osimertinib in delaying the postoperative recurrence of disease in patients with EGFR-mutated NSCLC.”
The ITACA study was funded by University of Turin and Eli Lilly. Dr. Novello disclosed relationships with Eli Lilly, Amgen, AstraZeneca, Bohringer Ingelheim, Beigene, Pfizer, Roche, Merck, Bristol-Myers Squibb, Takeda, and Sanofi. Dr. Mitsudomi disclosed relationships with Eli Lilly, AstraZeneca, Boehringer-Ingelheim, Chugai, Pfizer, Merck, Ono Pharmaceutical, Bristol-Myers Squibb, Novartis, ThermoFisher, Guardant, Eisai, Amgen, and Johnson & Johnson.
The patients were randomized to receive investigator’s choice of platinum-based chemotherapy or treatment tailored according to messenger RNA (mRNA) expression of two molecular markers – excision repair cross complementation 1 (ERCC1) and thymidylate synthase (TS).
There was no significant difference in overall survival or recurrence-free survival between the treatment approaches. However, toxicity was less common among patients who received customized treatment.
These results, from the phase 3 ITACA trial, were presented at the 2020 World Conference on Lung Cancer (Abstract 1820), which was rescheduled to January 2021.
“There is a clear need to define patients most likely to derive survival benefit from adjuvant therapy and spare patients who do not need adjuvant chemotherapy due to the toxicity of such therapy,” said presenter Silvia Novello, MD, PhD, of the University of Turin in Italy. “mRNA expression of different genes has been correlated with the sensitivity or resistance to specific anticancer agents.”
With this in mind, Dr. Novello and colleagues conducted the ITACA trial. The researchers’ primary goal was to determine whether an adjuvant pharmacogenomic-driven approach was able to improve overall survival in completely resected NSCLC.
Patients and treatment
The researchers randomized 773 NSCLC patients within 5-8 weeks after radical surgery. Genomic analyses were performed soon after surgery, and patients were randomly assigned to investigator’s choice of platinum-based chemotherapy or to tailored treatments defined by mRNA levels of ERCC1 and TS.
Patients with high ERCC1 mRNA expression who were randomized to tailored treatment received single-agent docetaxel if their TS level was high or pemetrexed monotherapy if their TS level was low.
Patients with low ERCC1 mRNA expression who were randomized to tailored treatment received cisplatin-gemcitabine if their TS level was high or cisplatin-pemetrexed if their TS was low.
The most frequent doublets used in control patients were cisplatin-gemcitabine and cisplatin-vinorelbine.
The demographic characteristics of the 384 patients randomized to tailored therapy and the 389 control subjects were well-balanced, Dr. Novello said. Two-thirds of patients had stage II disease, 11% were never smokers, and the vast majority had a lobectomy as the resection method.
Results
At a median follow-up of 28.2 months, the median overall survival was 96.4 months in the tailored therapy arm and 83.5 months in the control arm. The median recurrence-free survival was 64.4 months and 41.5 months, respectively.
“Adjuvant chemotherapy customization based on the primary tumor tissue mRNA expression of ERCC1 and TS did not significantly improve overall survival or recurrence-free survival,” Dr. Novello said. “There was a non–statistically significant trend for overall survival favoring the customized arm.”
Dr. Novello noted that, when the final analysis was performed, the study was underpowered, as only 46% of expected events were collected. Assuming the same hazard ratio point estimate and that the expected 336 events were collected, the hazard ratio estimate would be 0.76 (P = .012).
Grade 3/4 toxicities occurred in 32.6% of patients in the tailored therapy arm and 45.9% of those in the control arm (P < .001).
“It is important to underline that the treatment customization significantly improved the toxicity profile without compromising the efficacy,” Dr. Novello said.
She added that “more comprehensive and high-throughput diagnostic techniques will be needed in order to tailor adjuvant chemotherapy, with or without immunotherapy, in completely resected NSCLC.”
“The ITACA study is the largest adjuvant study tailored to ERCC1/TS status, and the results have been long-awaited,” said Tetsuya Mitsudomi, MD, a professor at Kindai University in Japan and president of the International Association for the Study of Lung Cancer.
“This trial should be praised for the mandated genomic analysis that was accomplished within a reasonably short time frame before random assignment. In addition, this trial confirmed that there is no biomarker strong enough to predict the efficacy of cytotoxic chemotherapy. However, the concept of customizing adjuvant therapy according to the genomic status of patients’ tumors is valid, leading to the recent demonstration in the ADAURA study of the superiority of osimertinib in delaying the postoperative recurrence of disease in patients with EGFR-mutated NSCLC.”
The ITACA study was funded by University of Turin and Eli Lilly. Dr. Novello disclosed relationships with Eli Lilly, Amgen, AstraZeneca, Bohringer Ingelheim, Beigene, Pfizer, Roche, Merck, Bristol-Myers Squibb, Takeda, and Sanofi. Dr. Mitsudomi disclosed relationships with Eli Lilly, AstraZeneca, Boehringer-Ingelheim, Chugai, Pfizer, Merck, Ono Pharmaceutical, Bristol-Myers Squibb, Novartis, ThermoFisher, Guardant, Eisai, Amgen, and Johnson & Johnson.
FROM WCLC 2020
CXR-Net: An AI-based diagnostic tool for COVID-19
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
The system, called CXR-Net, was trained to differentiate SARS-CoV-2 chest x-rays (CXRs) from CXRs that are either normal or non–COVID-19 lung pathologies, explained Abdulah Haikal, an MD candidate at Wayne State University, Detroit.
Mr. Haikal described CXR-Net at the AACR Virtual Meeting: COVID-19 and Cancer (Abstract S11-04).
CXR-Net is a two-module pipeline, Mr. Haikal explained. Module I is based on Res-CR-Net, a type of neural network originally designed for the semantic segmentation of microscopy images, with the ability to retain the original resolution of the input images in the feature maps of all layers and in the final output.
Module II is a hybrid convolutional neural network in which the first convolutional layer with learned coefficients is replaced by a layer with fixed coefficients provided by the Wavelet Scattering Transform. Module II inputs patients’ CXRs and corresponding lung masks quantified by Module I, and generates as outputs a class assignment (COVID-19 or non–COVID-19) and high-resolution heat maps that detect the severe acute respiratory syndrome–-associated lung regions.
“The system is trained to differentiate COVID and non-COVID pathologies and produces a highly discriminative heat map to point to lung regions where COVID is suspected,” Mr. Haikal said. “The Wavelet Scattering Transform allows for fast determination of COVID versus non-COVID CXRs.”
Preliminary results and implications
CXR-Net was piloted on a small dataset of CXRs from non–COVID-19 and polymerase chain reaction–confirmed COVID-19 patients acquired at a single center in Detroit.
Upon fivefold cross validation of the training set with 2,265 images, 90% accuracy was observed when the training set was tested against the validation set. However, once 1,532 new images were introduced, a 76% accuracy rate was observed.
The F1 scores were 0.81 and 0.70 for the training and test sets, respectively.
“I’m really excited about this new approach, and I think AI will allow us to do more with less, which is exciting,” said Ross L. Levine, MD, of Memorial Sloan Kettering Cancer Center in New York, who led a discussion session with Mr. Haikal about CXR-Net.
One question raised during the discussion was whether the technology will help health care providers be more thoughtful about when and how they image COVID-19 patients.
“The more data you feed into the system, the stronger and more accurate it becomes,” Mr. Haikal said. “However, until we have data sharing from multiple centers, we won’t see improved accuracy results.”
Another question was whether this technology could be integrated with more clinical parameters.
“Some individuals are afraid that AI will replace the job of a professional, but it will only make it better for us,” Mr. Haikal said. “We don’t rely on current imaging techniques to make a definitive diagnosis, but rather have a specificity and sensitivity to establish a diagnosis, and AI can be used in the same way as a diagnostic tool.”
Mr. Haikal and Dr. Levine disclosed no conflicts of interest. No funding sources were reported in the presentation.
FROM AACR: COVID-19 AND CANCER 2021
Cisplatin tops cetuximab for advanced head and neck cancer
Concurrent cisplatin should remain the standard treatment over cetuximab for patients with locoregionally advanced head and neck squamous cell carcinoma, according to a large comparative phase 3 trial.
Based on the results of an interim analysis of the ARTSCAN III clinical trial, the independent safety data monitoring committee recommended early closure of the study because the results of the study suggest that cetuximab may be inferior to cisplatin.
“This study supports previous retrospective and prospective studies that suggest that concurrent cisplatin with radiation is superior to regimens with concurrent cetuximab in locally advanced head and neck cancers,” commented Sachin Jhawar, MD, MSCI, assistant professor in the department of radiation oncology at Ohio State University Comprehensive Cancer Center, Columbus. “While the previous studies De-ESCALaTE HPV and RTOG 1016 were specific to HPV [human papillomavirus]-positive cancers, this study allowed non–virally mediated tumors, though the majority of cases were HPV related.”
The new study also used a lower-dose weekly regimen of cisplatin than the other two studies, noted Dr. Jhawar. Early trials used a cisplatin dose of 100 mg/m2 every 3 weeks, but “the field is moving toward a dose of 40 mg/m2 weekly, the dose use in the Swedish study. This study had an interesting second randomization of radiation dose-escalation for more advanced primary T stage tumors, but because the study ended early it is difficult to fully interpret those results.”
Swedish researchers, led by Maria Gebre-Medhin, MD, PhD, department of hematology, oncology, and radiation physics, Skåne University Hospital, Lund, Sweden, performed an open-label, randomized, controlled, phase 3 study of patients with locoregionally advanced head and neck squamous cell carcinoma. The patients received IV cetuximab 400 mg/m2 1 week before the start of radiation therapy followed by 250 mg/m2 per week, or weekly IV cisplatin 40 mg/m2 during radiation therapy.
The study results were published in the Journal of Clinical Oncology.
The study was prematurely closed after an unplanned interim analysis when 298 patients had been randomly assigned. The cumulative incidence of locoregional failures at 3 years was more than twice as high in the cetuximab group (23%), compared with the cisplatin group (9%; P = .0036). At 3 years, overall survival was higher in the cisplatin (88%) group than in the cetuximab group (78%), but the difference was not significant (P = .086). The cumulative incidence of distant failures did not differ between the treatment groups, and the toxicity burden was similar.
“Concurrent cisplatin led to improved locoregional control and event-free survival with a trend toward improved overall survival. The types of toxicity were different, as would be expected with the different drug mechanisms, but the rate of toxicity was not,” said Dr. Dr. Jhawar. “Interestingly, the benefit of cisplatin seemed to be limited to patients with p16-positive oropharyngeal cancer. There was clinical equipoise in the p16-negative oropharyngeal cancer group and in the non–oropharyngeal cancer group. The numbers were small, but this is intriguing and suggests that there is more work to be done in this group of patients to tease out if we can escalate or use alternative therapy.”
Cisplatin has been repeatedly proven to be superior in selected populations. The next steps, said Dr. Jhawar, include defining “optimal regimens in cisplatin-ineligible populations based on age, performance status, kidney function, hearing loss, neuropathy, and HIV/AIDS; improvements with new targeted therapies and immunotherapies; and deescalation of systemic and/or radiation regimens in the best outcome groups, such as low-risk HPV-positive patients. And we are going to see more personalized medicine with genetic testing of tumors.”
When patients are ineligible for cisplatin, no optimal regimens have been defined as yet. At Ohio State, Dr. Jhawar and colleagues use carboplatin therapy.
For practicing oncologists, Dr. Jhawar said the bottom line is “patients who are eligible should receive concurrent cisplatin therapy for locoregionally advanced head and neck cancer.”
The ARTSCAN III study was funded by the Swedish Cancer Society and the Mrs. Berta Kamprad Cancer Foundation. One of the study’s coauthors reported a leadership role in ScandiDos. The other authors reported they had no conflicts. Dr. Jhawar reported he had no conflicts of interest.
Concurrent cisplatin should remain the standard treatment over cetuximab for patients with locoregionally advanced head and neck squamous cell carcinoma, according to a large comparative phase 3 trial.
Based on the results of an interim analysis of the ARTSCAN III clinical trial, the independent safety data monitoring committee recommended early closure of the study because the results of the study suggest that cetuximab may be inferior to cisplatin.
“This study supports previous retrospective and prospective studies that suggest that concurrent cisplatin with radiation is superior to regimens with concurrent cetuximab in locally advanced head and neck cancers,” commented Sachin Jhawar, MD, MSCI, assistant professor in the department of radiation oncology at Ohio State University Comprehensive Cancer Center, Columbus. “While the previous studies De-ESCALaTE HPV and RTOG 1016 were specific to HPV [human papillomavirus]-positive cancers, this study allowed non–virally mediated tumors, though the majority of cases were HPV related.”
The new study also used a lower-dose weekly regimen of cisplatin than the other two studies, noted Dr. Jhawar. Early trials used a cisplatin dose of 100 mg/m2 every 3 weeks, but “the field is moving toward a dose of 40 mg/m2 weekly, the dose use in the Swedish study. This study had an interesting second randomization of radiation dose-escalation for more advanced primary T stage tumors, but because the study ended early it is difficult to fully interpret those results.”
Swedish researchers, led by Maria Gebre-Medhin, MD, PhD, department of hematology, oncology, and radiation physics, Skåne University Hospital, Lund, Sweden, performed an open-label, randomized, controlled, phase 3 study of patients with locoregionally advanced head and neck squamous cell carcinoma. The patients received IV cetuximab 400 mg/m2 1 week before the start of radiation therapy followed by 250 mg/m2 per week, or weekly IV cisplatin 40 mg/m2 during radiation therapy.
The study results were published in the Journal of Clinical Oncology.
The study was prematurely closed after an unplanned interim analysis when 298 patients had been randomly assigned. The cumulative incidence of locoregional failures at 3 years was more than twice as high in the cetuximab group (23%), compared with the cisplatin group (9%; P = .0036). At 3 years, overall survival was higher in the cisplatin (88%) group than in the cetuximab group (78%), but the difference was not significant (P = .086). The cumulative incidence of distant failures did not differ between the treatment groups, and the toxicity burden was similar.
“Concurrent cisplatin led to improved locoregional control and event-free survival with a trend toward improved overall survival. The types of toxicity were different, as would be expected with the different drug mechanisms, but the rate of toxicity was not,” said Dr. Dr. Jhawar. “Interestingly, the benefit of cisplatin seemed to be limited to patients with p16-positive oropharyngeal cancer. There was clinical equipoise in the p16-negative oropharyngeal cancer group and in the non–oropharyngeal cancer group. The numbers were small, but this is intriguing and suggests that there is more work to be done in this group of patients to tease out if we can escalate or use alternative therapy.”
Cisplatin has been repeatedly proven to be superior in selected populations. The next steps, said Dr. Jhawar, include defining “optimal regimens in cisplatin-ineligible populations based on age, performance status, kidney function, hearing loss, neuropathy, and HIV/AIDS; improvements with new targeted therapies and immunotherapies; and deescalation of systemic and/or radiation regimens in the best outcome groups, such as low-risk HPV-positive patients. And we are going to see more personalized medicine with genetic testing of tumors.”
When patients are ineligible for cisplatin, no optimal regimens have been defined as yet. At Ohio State, Dr. Jhawar and colleagues use carboplatin therapy.
For practicing oncologists, Dr. Jhawar said the bottom line is “patients who are eligible should receive concurrent cisplatin therapy for locoregionally advanced head and neck cancer.”
The ARTSCAN III study was funded by the Swedish Cancer Society and the Mrs. Berta Kamprad Cancer Foundation. One of the study’s coauthors reported a leadership role in ScandiDos. The other authors reported they had no conflicts. Dr. Jhawar reported he had no conflicts of interest.
Concurrent cisplatin should remain the standard treatment over cetuximab for patients with locoregionally advanced head and neck squamous cell carcinoma, according to a large comparative phase 3 trial.
Based on the results of an interim analysis of the ARTSCAN III clinical trial, the independent safety data monitoring committee recommended early closure of the study because the results of the study suggest that cetuximab may be inferior to cisplatin.
“This study supports previous retrospective and prospective studies that suggest that concurrent cisplatin with radiation is superior to regimens with concurrent cetuximab in locally advanced head and neck cancers,” commented Sachin Jhawar, MD, MSCI, assistant professor in the department of radiation oncology at Ohio State University Comprehensive Cancer Center, Columbus. “While the previous studies De-ESCALaTE HPV and RTOG 1016 were specific to HPV [human papillomavirus]-positive cancers, this study allowed non–virally mediated tumors, though the majority of cases were HPV related.”
The new study also used a lower-dose weekly regimen of cisplatin than the other two studies, noted Dr. Jhawar. Early trials used a cisplatin dose of 100 mg/m2 every 3 weeks, but “the field is moving toward a dose of 40 mg/m2 weekly, the dose use in the Swedish study. This study had an interesting second randomization of radiation dose-escalation for more advanced primary T stage tumors, but because the study ended early it is difficult to fully interpret those results.”
Swedish researchers, led by Maria Gebre-Medhin, MD, PhD, department of hematology, oncology, and radiation physics, Skåne University Hospital, Lund, Sweden, performed an open-label, randomized, controlled, phase 3 study of patients with locoregionally advanced head and neck squamous cell carcinoma. The patients received IV cetuximab 400 mg/m2 1 week before the start of radiation therapy followed by 250 mg/m2 per week, or weekly IV cisplatin 40 mg/m2 during radiation therapy.
The study results were published in the Journal of Clinical Oncology.
The study was prematurely closed after an unplanned interim analysis when 298 patients had been randomly assigned. The cumulative incidence of locoregional failures at 3 years was more than twice as high in the cetuximab group (23%), compared with the cisplatin group (9%; P = .0036). At 3 years, overall survival was higher in the cisplatin (88%) group than in the cetuximab group (78%), but the difference was not significant (P = .086). The cumulative incidence of distant failures did not differ between the treatment groups, and the toxicity burden was similar.
“Concurrent cisplatin led to improved locoregional control and event-free survival with a trend toward improved overall survival. The types of toxicity were different, as would be expected with the different drug mechanisms, but the rate of toxicity was not,” said Dr. Dr. Jhawar. “Interestingly, the benefit of cisplatin seemed to be limited to patients with p16-positive oropharyngeal cancer. There was clinical equipoise in the p16-negative oropharyngeal cancer group and in the non–oropharyngeal cancer group. The numbers were small, but this is intriguing and suggests that there is more work to be done in this group of patients to tease out if we can escalate or use alternative therapy.”
Cisplatin has been repeatedly proven to be superior in selected populations. The next steps, said Dr. Jhawar, include defining “optimal regimens in cisplatin-ineligible populations based on age, performance status, kidney function, hearing loss, neuropathy, and HIV/AIDS; improvements with new targeted therapies and immunotherapies; and deescalation of systemic and/or radiation regimens in the best outcome groups, such as low-risk HPV-positive patients. And we are going to see more personalized medicine with genetic testing of tumors.”
When patients are ineligible for cisplatin, no optimal regimens have been defined as yet. At Ohio State, Dr. Jhawar and colleagues use carboplatin therapy.
For practicing oncologists, Dr. Jhawar said the bottom line is “patients who are eligible should receive concurrent cisplatin therapy for locoregionally advanced head and neck cancer.”
The ARTSCAN III study was funded by the Swedish Cancer Society and the Mrs. Berta Kamprad Cancer Foundation. One of the study’s coauthors reported a leadership role in ScandiDos. The other authors reported they had no conflicts. Dr. Jhawar reported he had no conflicts of interest.
FROM THE JOURNAL OF CLINICAL ONCOLOGY
U.K. COVID-19 variant doubling every 10 days in the U.S.: Study
The SARS-CoV-2 variant first detected in the United Kingdom is rapidly becoming the dominant strain in several countries and is doubling every 10 days in the United States, according to new data.
The findings by Nicole L. Washington, PhD, associate director of research at the genomics company Helix, and colleagues were posted Feb. 7, 2021, on the preprint server medRxiv. The paper has not been peer-reviewed in a scientific journal.
The researchers also found that the transmission rate in the United States of the variant, labeled B.1.1.7, is 30%-40% higher than that of more common lineages.
While clinical outcomes initially were thought to be similar to those of other SARS-CoV-2 variants, early reports suggest that infection with the B.1.1.7 variant may increase death risk by about 30%.
A coauthor of the current study, Kristian Andersen, PhD, told the New York Times , “Nothing in this paper is surprising, but people need to see it.”
Dr. Andersen, a virologist at the Scripps Research Institute in La Jolla, Calif., added that “we should probably prepare for this being the predominant lineage in most places in the United States by March.”
The study of the B.1.1.7 variant adds support for the Centers for Disease Control and Prevention prediction in January that it would dominate by March.
“Our study shows that the U.S. is on a similar trajectory as other countries where B.1.1.7 rapidly became the dominant SARS-CoV-2 variant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality,” the researchers wrote.
The authors pointed out that the B.1.1.7 variant became the dominant SARS-CoV-2 strain in the United Kingdom within a couple of months of its detection.
“Since then, the variant has been increasingly observed across many European countries, including Portugal and Ireland, which, like the U.K., observed devastating waves of COVID-19 after B.1.1.7 became dominant,” the authors wrote.
“Category 5” storm
The B.1.1.7 variant has likely been spreading between U.S. states since at least December, they wrote.
This news organization reported on Jan. 15 that, as of Jan. 13, the B.1.1.7 variant was seen in 76 cases across 12 U.S. states, according to an early release of the CDC’s Morbidity and Mortality Weekly Report.
As of Feb. 7, there were 690 cases of the B.1.1.7 variant in the US in 33 states, according to the CDC.
Dr. Washington and colleagues examined more than 500,000 coronavirus test samples from cases across the United States that were tested at San Mateo, Calif.–based Helix facilities since July.
In the study, they found inconsistent prevalence of the variant across states. By the last week in January, the researchers estimated the proportion of B.1.1.7 in the U.S. population to be about 2.1% of all COVID-19 cases, though they found it made up about 2% of all COVID-19 cases in California and about 4.5% of cases in Florida. The authors acknowledged that their data is less robust outside of those two states.
Though that seems a relatively low frequency, “our estimates show that its growth rate is at least 35%-45% increased and doubling every week and a half,” the authors wrote.
“Because laboratories in the U.S. are only sequencing a small subset of SARS-CoV-2 samples, the true sequence diversity of SARS-CoV-2 in this country is still unknown,” they noted.
Michael Osterholm, PhD, MPH, director of the Center for Infectious Disease Research and Policy at the University of Minnesota, Minneapolis, said last week that the United States is facing a “Category 5” storm with the spread of the B.1.1.7 variant as well as the variants first identified in South Africa and Brazil.
“We are going to see something like we have not seen yet in this country,” Dr. Osterholm said recently on NBC’s Meet the Press.
Lead author Nicole L. Washington and many of the coauthors are employees of Helix. Other coauthors are employees of Illumina. Three coauthors own stock in ILMN. The work was funded by Illumina, Helix, the Innovative Genomics Institute, and the New Frontiers in Research Fund provided by the Canadian Institutes of Health Research.
A version of this article first appeared on Medscape.com.
The SARS-CoV-2 variant first detected in the United Kingdom is rapidly becoming the dominant strain in several countries and is doubling every 10 days in the United States, according to new data.
The findings by Nicole L. Washington, PhD, associate director of research at the genomics company Helix, and colleagues were posted Feb. 7, 2021, on the preprint server medRxiv. The paper has not been peer-reviewed in a scientific journal.
The researchers also found that the transmission rate in the United States of the variant, labeled B.1.1.7, is 30%-40% higher than that of more common lineages.
While clinical outcomes initially were thought to be similar to those of other SARS-CoV-2 variants, early reports suggest that infection with the B.1.1.7 variant may increase death risk by about 30%.
A coauthor of the current study, Kristian Andersen, PhD, told the New York Times , “Nothing in this paper is surprising, but people need to see it.”
Dr. Andersen, a virologist at the Scripps Research Institute in La Jolla, Calif., added that “we should probably prepare for this being the predominant lineage in most places in the United States by March.”
The study of the B.1.1.7 variant adds support for the Centers for Disease Control and Prevention prediction in January that it would dominate by March.
“Our study shows that the U.S. is on a similar trajectory as other countries where B.1.1.7 rapidly became the dominant SARS-CoV-2 variant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality,” the researchers wrote.
The authors pointed out that the B.1.1.7 variant became the dominant SARS-CoV-2 strain in the United Kingdom within a couple of months of its detection.
“Since then, the variant has been increasingly observed across many European countries, including Portugal and Ireland, which, like the U.K., observed devastating waves of COVID-19 after B.1.1.7 became dominant,” the authors wrote.
“Category 5” storm
The B.1.1.7 variant has likely been spreading between U.S. states since at least December, they wrote.
This news organization reported on Jan. 15 that, as of Jan. 13, the B.1.1.7 variant was seen in 76 cases across 12 U.S. states, according to an early release of the CDC’s Morbidity and Mortality Weekly Report.
As of Feb. 7, there were 690 cases of the B.1.1.7 variant in the US in 33 states, according to the CDC.
Dr. Washington and colleagues examined more than 500,000 coronavirus test samples from cases across the United States that were tested at San Mateo, Calif.–based Helix facilities since July.
In the study, they found inconsistent prevalence of the variant across states. By the last week in January, the researchers estimated the proportion of B.1.1.7 in the U.S. population to be about 2.1% of all COVID-19 cases, though they found it made up about 2% of all COVID-19 cases in California and about 4.5% of cases in Florida. The authors acknowledged that their data is less robust outside of those two states.
Though that seems a relatively low frequency, “our estimates show that its growth rate is at least 35%-45% increased and doubling every week and a half,” the authors wrote.
“Because laboratories in the U.S. are only sequencing a small subset of SARS-CoV-2 samples, the true sequence diversity of SARS-CoV-2 in this country is still unknown,” they noted.
Michael Osterholm, PhD, MPH, director of the Center for Infectious Disease Research and Policy at the University of Minnesota, Minneapolis, said last week that the United States is facing a “Category 5” storm with the spread of the B.1.1.7 variant as well as the variants first identified in South Africa and Brazil.
“We are going to see something like we have not seen yet in this country,” Dr. Osterholm said recently on NBC’s Meet the Press.
Lead author Nicole L. Washington and many of the coauthors are employees of Helix. Other coauthors are employees of Illumina. Three coauthors own stock in ILMN. The work was funded by Illumina, Helix, the Innovative Genomics Institute, and the New Frontiers in Research Fund provided by the Canadian Institutes of Health Research.
A version of this article first appeared on Medscape.com.
The SARS-CoV-2 variant first detected in the United Kingdom is rapidly becoming the dominant strain in several countries and is doubling every 10 days in the United States, according to new data.
The findings by Nicole L. Washington, PhD, associate director of research at the genomics company Helix, and colleagues were posted Feb. 7, 2021, on the preprint server medRxiv. The paper has not been peer-reviewed in a scientific journal.
The researchers also found that the transmission rate in the United States of the variant, labeled B.1.1.7, is 30%-40% higher than that of more common lineages.
While clinical outcomes initially were thought to be similar to those of other SARS-CoV-2 variants, early reports suggest that infection with the B.1.1.7 variant may increase death risk by about 30%.
A coauthor of the current study, Kristian Andersen, PhD, told the New York Times , “Nothing in this paper is surprising, but people need to see it.”
Dr. Andersen, a virologist at the Scripps Research Institute in La Jolla, Calif., added that “we should probably prepare for this being the predominant lineage in most places in the United States by March.”
The study of the B.1.1.7 variant adds support for the Centers for Disease Control and Prevention prediction in January that it would dominate by March.
“Our study shows that the U.S. is on a similar trajectory as other countries where B.1.1.7 rapidly became the dominant SARS-CoV-2 variant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality,” the researchers wrote.
The authors pointed out that the B.1.1.7 variant became the dominant SARS-CoV-2 strain in the United Kingdom within a couple of months of its detection.
“Since then, the variant has been increasingly observed across many European countries, including Portugal and Ireland, which, like the U.K., observed devastating waves of COVID-19 after B.1.1.7 became dominant,” the authors wrote.
“Category 5” storm
The B.1.1.7 variant has likely been spreading between U.S. states since at least December, they wrote.
This news organization reported on Jan. 15 that, as of Jan. 13, the B.1.1.7 variant was seen in 76 cases across 12 U.S. states, according to an early release of the CDC’s Morbidity and Mortality Weekly Report.
As of Feb. 7, there were 690 cases of the B.1.1.7 variant in the US in 33 states, according to the CDC.
Dr. Washington and colleagues examined more than 500,000 coronavirus test samples from cases across the United States that were tested at San Mateo, Calif.–based Helix facilities since July.
In the study, they found inconsistent prevalence of the variant across states. By the last week in January, the researchers estimated the proportion of B.1.1.7 in the U.S. population to be about 2.1% of all COVID-19 cases, though they found it made up about 2% of all COVID-19 cases in California and about 4.5% of cases in Florida. The authors acknowledged that their data is less robust outside of those two states.
Though that seems a relatively low frequency, “our estimates show that its growth rate is at least 35%-45% increased and doubling every week and a half,” the authors wrote.
“Because laboratories in the U.S. are only sequencing a small subset of SARS-CoV-2 samples, the true sequence diversity of SARS-CoV-2 in this country is still unknown,” they noted.
Michael Osterholm, PhD, MPH, director of the Center for Infectious Disease Research and Policy at the University of Minnesota, Minneapolis, said last week that the United States is facing a “Category 5” storm with the spread of the B.1.1.7 variant as well as the variants first identified in South Africa and Brazil.
“We are going to see something like we have not seen yet in this country,” Dr. Osterholm said recently on NBC’s Meet the Press.
Lead author Nicole L. Washington and many of the coauthors are employees of Helix. Other coauthors are employees of Illumina. Three coauthors own stock in ILMN. The work was funded by Illumina, Helix, the Innovative Genomics Institute, and the New Frontiers in Research Fund provided by the Canadian Institutes of Health Research.
A version of this article first appeared on Medscape.com.
Are diagnosticians chasing COVID-linked zebras and missing horses?
The emergence of multiple inflammatory syndrome in children (MIS-C) in association with COVID-19 may be complicating the investigation and diagnosis of more common viral and bacterial infections, potentially delaying treatment and prolonging hospital stays.
Two recent articles published online in Hospital Pediatrics provide evidence of this phenomenon. The articles outlined case studies of children who underwent extensive investigation for MIS-C when in fact they had less severe and more common infections. MIS-C is a severe but rare syndrome that involves systemic hyperinflammation with fever and multisystem organ dysfunction similar to that of Kawasaki disease (KD).
In one of the articles, Matthew Molloy, MD, MPH, of the division of pediatric hospital medicine at Cincinnati Children’s Hospital Medical Center, and colleagues aptly asked: “What are we missing in our search for MIS-C?”
E. coli, not SARS-CoV-2
That question arose from a case involving a 3-year-old boy who had a 6-day history of fever and fatigue. Three days earlier, he had tested negative for strep antigen and COVID-19. He had a persistent, high fever, reduced appetite, and reduced urine output and was taken to the ED. On physical examination, there was no rash, skin peeling, redness of the eye or oral mucosa, congestion, rhinorrhea, cough, shortness of breath, chest pain, abdominal pain, nausea, vomiting, or diarrhea.
Urinalysis results and exam findings were suspicious for pyelonephritis. Other findings from an extensive laboratory workup raised the alarm that the boy was suffering from MIS-C as opposed to incomplete KD. After admission to hospital medicine, the cardiology, rheumatology, and infectious disease teams were called in to consult.
Repeat labs were planned for the following day before initiating therapy. On day 2, the child’s urine culture was positive for gram-negative rods, later identified as Escherichia coli. The boy was started on ceftriaxone. Left renal scarring was apparent on ultrasound. The patient’s condition resolved after 36 hours, and he was discharged home with antibiotics.
‘Diagnosis derailed’
Calling this a case of “diagnosis derailed,” the authors noted that, in the pre-COVID era, this child’s signs and symptoms would likely have triggered a more targeted and less costly evaluation for more common infectious and noninfectious causes, including pyelonephritis, absent any physical exam findings consistent with KD.
“However, the patient presented in the midst of the COVID-19 pandemic with growing awareness of a new clinical entity,” Dr. Molloy and colleagues wrote. “Anchored to the patient’s persistent fever, the medical team initiated an extensive, costly, and ultimately unnecessary workup to avoid missing the diagnosis of MIS-C; a not yet well-described diagnosis with potentially severe morbidity.”
Confirmation bias and diagnostic momentum likely contributed to the early focus on MIS-C rather than more common alternatives, the authors acknowledged. The addition of mildly abnormal laboratory data not typically obtained in the evaluation of fever led the team astray. “The diagnosis and definitive treatment may have been made earlier had the focus on concern for MIS-C not been present,” Dr. Molloy said in an interview.
Keeping value in care
The authors recognized that their initial approach to evaluating for MIS-C provided low-value care. “In our desire to not ‘miss’ MIS-C, we were performing costly evaluations that at times produced mildly abnormal, nonspecific results,” they wrote. That triggered a cascade of specialty consultations, follow-up testing, and an unwarranted diagnostic preoccupation with MIS-C.
Determining the extra price tag for the child’s workup would be complex and difficult because there is a difference in the cost to the hospital and the cost to the family, Dr. Molloy said. “However, there are potential cost savings that would be related to making a correct diagnosis in a timely manner in terms of preventing downstream effects from delayed diagnoses.”
Even as clinicians struggle with the challenging SARS-CoV-2 learning curve, Dr. Molloy and associates urged them to continue to strive for high-value care, with an unwavering focus on using only necessary resources, a stewardship the pandemic has shown to be critical.
“The COVID-19 pandemic has been an incredibly stressful time for physicians and for families,” Dr. Molloy said. “COVID-19 and related conditions like MIS-C are new, and we are learning more and more about them every week. These diagnoses are understandably on the minds of physicians and families when children present with fever.” Notwithstanding, the boy’s case underscores the need for clinicians to consider alternate diagnoses and the value of the care provided.
Impact of bias
Dr. Molloy’s group brings home the cognitive biases practitioners often suffer from, including anchoring and confirmation bias and diagnostic momentum, according to J. Howard Smart, MD, chief of pediatrics at Sharp Mary Birch Hospital for Women and Newborns, San Diego, and an assistant clinical professor of pediatrics at University of California, San Diego.
“But it is one thing to recognize these in retrospect and quite another to consider whether they may be happening to you yourself in real time,” he said in an interview. “It is almost as if we need to have a ‘time out,’ where we stop and ask ourselves whether there is something else that could be explaining our patient’s presentation, something that would be more common and more likely to be occurring.”
According to Dr. Smart, who was not involved in Dr. Molloy’s study, the team’s premature diagnostic focus on MIS-C was almost the inverse of what typically happens with KD. “It is usually the case that Kawasaki disease does not enter the differential diagnosis until late in the course of the fever, typically on day 5 or later, when it may have been better to think of it earlier,” he said.
In the second article, Andrea Dean, MD, of the department of pediatrics at Baylor College of Medicine and Texas Children’s Hospital, both in Houston, and colleagues outlined the cases of five patients aged 8-17 years who were hospitalized in May 2020 for suspected MIS-C. They exhibited inflammatory and other concerning indicators but were eventually discharged with a diagnosis of murine typhus.
This flea-borne infection, most commonly reported in the United States in the southeastern Gulf Coast region, Hawaii, and California, is often associated with a triad of fever, rash, and headache.
Cases have been rising in southern Texas, and Dr. Dean and colleagues postulated that school closures and social distancing may have increased exposure as a result of children spending more time outdoors or with pets. “Alternatively, parental concern for SARS-CoV-2 infection could mean children with symptoms are presenting to care and being referred or admitted to the hospital more frequently due to provider concern for MIS-C,” they wrote.
Cardiac involvement
The most concerning of the five cases in terms of possible MIS-C, Dr. Dean said in an interview, was that of a 12-year-old boy who had fever for 6 days in association with headache, eczematous rash, dry lips, and conjunctivitis. Laboratory tests showed a mildly elevated C-reactive protein level, hyponatremia, and thrombocytopenia, as well as sterile pyuria and mildly elevated prothrombin time. He was treated empirically with doxycycline, and his fever resolved over the next 24 hours.
An echocardiogram at initial evaluation, however, revealed mild dilation of the left anterior descending and right coronary arteries, which led to the administration of intravenous immunoglobulin and aspirin for atypical KD, in contrast to MIS-C. The authors postulated that mild cardiac involvement in disorders other than MIS-C and KD may be underrecognized.
The lesson from these cases, Dr. Dean and associates concluded, is that hospitalists must maintain a wide differential diagnosis when assessing a child with prolonged fever and evidence of systemic inflammation. The CDC stipulates that a diagnosis of MIS-C requires the absence of a plausible alternative diagnosis.
In addition to common viral, bacterial, and noninfectious disorders, a range of regional endemic rickettsial and parasitic infections must be considered as alternative diagnoses to MIS-C. “Many of these diseases cannot be reliably differentiated from MIS-C on presentation, and as community exposure to SARS-CoV-2 grows, hospitalists should be prepared to admit febrile children with evidence of systemic inflammation for brief observation periods to evaluate for MIS-C,” Dr. Dean’s group wrote. In this context, however, empiric treatment for common or even uncommon infectious diseases may avoid overdiagnosis and overtreatment of MIS-C as well as improve patient outcomes.
“We do have specific MIS-C guidelines at our institution,” Dr. Dean said, “but like all institutions, we are dealing with the broad definition of MIS-C according to the World Health Organization and the CDC, which is really the takeaway from this paper.”
More difficult differentiation
Both groups of authors pointed out that, as SARS-CoV-2 spreads throughout a community, a higher percentage of the population will have positive results on antibody testing, and such results will become less useful for differentiating between MIS-C and other conditions.
Despite these series’ cautionary lessons, other experts point to the critical importance of including MIS-C early on in the interest of efficient diagnosis and therapy. “In the cases cited, other pathologies were evaluated for and treated accordingly,” said Kara Gross Margolis, MD, AGAF, an associate professor of pediatrics in the division of pediatric gastroenterology, hepatology, and nutrition at Morgan Stanley Children’s Hospital,New York. “These papers stress the need for a balance that is important, and all potential diagnoses need to be considered, but MIS-C, due to its potential severe consequences, also needs to be on our differential now.”
In her view, as this new high-morbidity entity becomes more widespread during the pandemic, it will be increasingly important to keep this condition on the diagnostic radar.
Interestingly, in a converse example of diagnostic clouding, Dr. Gross Margolis’s group reported (Gastroenterology. 2020 Oct;159[4]:1571-4.e2) last year on a pediatric case series in which the presence of gastrointestinal symptoms in children with COVID-19–related MIS-C muddied the diagnosis by confusing this potentially severe syndrome with more common and less toxic gastrointestinal infections.
According to Dr. Smart, although the two reports don’t offer evidence for a particular diagnostic practice, they can inform the decision-making process. “It may be that we will have enough evidence shortly to say what the best practice is regarding diagnostic evaluation of possible MIS-C cases,” he said. “Until then, we must remember that common things occur commonly, even during a global pandemic.”
Neither of the two reports received any specific funding. The authors disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
The emergence of multiple inflammatory syndrome in children (MIS-C) in association with COVID-19 may be complicating the investigation and diagnosis of more common viral and bacterial infections, potentially delaying treatment and prolonging hospital stays.
Two recent articles published online in Hospital Pediatrics provide evidence of this phenomenon. The articles outlined case studies of children who underwent extensive investigation for MIS-C when in fact they had less severe and more common infections. MIS-C is a severe but rare syndrome that involves systemic hyperinflammation with fever and multisystem organ dysfunction similar to that of Kawasaki disease (KD).
In one of the articles, Matthew Molloy, MD, MPH, of the division of pediatric hospital medicine at Cincinnati Children’s Hospital Medical Center, and colleagues aptly asked: “What are we missing in our search for MIS-C?”
E. coli, not SARS-CoV-2
That question arose from a case involving a 3-year-old boy who had a 6-day history of fever and fatigue. Three days earlier, he had tested negative for strep antigen and COVID-19. He had a persistent, high fever, reduced appetite, and reduced urine output and was taken to the ED. On physical examination, there was no rash, skin peeling, redness of the eye or oral mucosa, congestion, rhinorrhea, cough, shortness of breath, chest pain, abdominal pain, nausea, vomiting, or diarrhea.
Urinalysis results and exam findings were suspicious for pyelonephritis. Other findings from an extensive laboratory workup raised the alarm that the boy was suffering from MIS-C as opposed to incomplete KD. After admission to hospital medicine, the cardiology, rheumatology, and infectious disease teams were called in to consult.
Repeat labs were planned for the following day before initiating therapy. On day 2, the child’s urine culture was positive for gram-negative rods, later identified as Escherichia coli. The boy was started on ceftriaxone. Left renal scarring was apparent on ultrasound. The patient’s condition resolved after 36 hours, and he was discharged home with antibiotics.
‘Diagnosis derailed’
Calling this a case of “diagnosis derailed,” the authors noted that, in the pre-COVID era, this child’s signs and symptoms would likely have triggered a more targeted and less costly evaluation for more common infectious and noninfectious causes, including pyelonephritis, absent any physical exam findings consistent with KD.
“However, the patient presented in the midst of the COVID-19 pandemic with growing awareness of a new clinical entity,” Dr. Molloy and colleagues wrote. “Anchored to the patient’s persistent fever, the medical team initiated an extensive, costly, and ultimately unnecessary workup to avoid missing the diagnosis of MIS-C; a not yet well-described diagnosis with potentially severe morbidity.”
Confirmation bias and diagnostic momentum likely contributed to the early focus on MIS-C rather than more common alternatives, the authors acknowledged. The addition of mildly abnormal laboratory data not typically obtained in the evaluation of fever led the team astray. “The diagnosis and definitive treatment may have been made earlier had the focus on concern for MIS-C not been present,” Dr. Molloy said in an interview.
Keeping value in care
The authors recognized that their initial approach to evaluating for MIS-C provided low-value care. “In our desire to not ‘miss’ MIS-C, we were performing costly evaluations that at times produced mildly abnormal, nonspecific results,” they wrote. That triggered a cascade of specialty consultations, follow-up testing, and an unwarranted diagnostic preoccupation with MIS-C.
Determining the extra price tag for the child’s workup would be complex and difficult because there is a difference in the cost to the hospital and the cost to the family, Dr. Molloy said. “However, there are potential cost savings that would be related to making a correct diagnosis in a timely manner in terms of preventing downstream effects from delayed diagnoses.”
Even as clinicians struggle with the challenging SARS-CoV-2 learning curve, Dr. Molloy and associates urged them to continue to strive for high-value care, with an unwavering focus on using only necessary resources, a stewardship the pandemic has shown to be critical.
“The COVID-19 pandemic has been an incredibly stressful time for physicians and for families,” Dr. Molloy said. “COVID-19 and related conditions like MIS-C are new, and we are learning more and more about them every week. These diagnoses are understandably on the minds of physicians and families when children present with fever.” Notwithstanding, the boy’s case underscores the need for clinicians to consider alternate diagnoses and the value of the care provided.
Impact of bias
Dr. Molloy’s group brings home the cognitive biases practitioners often suffer from, including anchoring and confirmation bias and diagnostic momentum, according to J. Howard Smart, MD, chief of pediatrics at Sharp Mary Birch Hospital for Women and Newborns, San Diego, and an assistant clinical professor of pediatrics at University of California, San Diego.
“But it is one thing to recognize these in retrospect and quite another to consider whether they may be happening to you yourself in real time,” he said in an interview. “It is almost as if we need to have a ‘time out,’ where we stop and ask ourselves whether there is something else that could be explaining our patient’s presentation, something that would be more common and more likely to be occurring.”
According to Dr. Smart, who was not involved in Dr. Molloy’s study, the team’s premature diagnostic focus on MIS-C was almost the inverse of what typically happens with KD. “It is usually the case that Kawasaki disease does not enter the differential diagnosis until late in the course of the fever, typically on day 5 or later, when it may have been better to think of it earlier,” he said.
In the second article, Andrea Dean, MD, of the department of pediatrics at Baylor College of Medicine and Texas Children’s Hospital, both in Houston, and colleagues outlined the cases of five patients aged 8-17 years who were hospitalized in May 2020 for suspected MIS-C. They exhibited inflammatory and other concerning indicators but were eventually discharged with a diagnosis of murine typhus.
This flea-borne infection, most commonly reported in the United States in the southeastern Gulf Coast region, Hawaii, and California, is often associated with a triad of fever, rash, and headache.
Cases have been rising in southern Texas, and Dr. Dean and colleagues postulated that school closures and social distancing may have increased exposure as a result of children spending more time outdoors or with pets. “Alternatively, parental concern for SARS-CoV-2 infection could mean children with symptoms are presenting to care and being referred or admitted to the hospital more frequently due to provider concern for MIS-C,” they wrote.
Cardiac involvement
The most concerning of the five cases in terms of possible MIS-C, Dr. Dean said in an interview, was that of a 12-year-old boy who had fever for 6 days in association with headache, eczematous rash, dry lips, and conjunctivitis. Laboratory tests showed a mildly elevated C-reactive protein level, hyponatremia, and thrombocytopenia, as well as sterile pyuria and mildly elevated prothrombin time. He was treated empirically with doxycycline, and his fever resolved over the next 24 hours.
An echocardiogram at initial evaluation, however, revealed mild dilation of the left anterior descending and right coronary arteries, which led to the administration of intravenous immunoglobulin and aspirin for atypical KD, in contrast to MIS-C. The authors postulated that mild cardiac involvement in disorders other than MIS-C and KD may be underrecognized.
The lesson from these cases, Dr. Dean and associates concluded, is that hospitalists must maintain a wide differential diagnosis when assessing a child with prolonged fever and evidence of systemic inflammation. The CDC stipulates that a diagnosis of MIS-C requires the absence of a plausible alternative diagnosis.
In addition to common viral, bacterial, and noninfectious disorders, a range of regional endemic rickettsial and parasitic infections must be considered as alternative diagnoses to MIS-C. “Many of these diseases cannot be reliably differentiated from MIS-C on presentation, and as community exposure to SARS-CoV-2 grows, hospitalists should be prepared to admit febrile children with evidence of systemic inflammation for brief observation periods to evaluate for MIS-C,” Dr. Dean’s group wrote. In this context, however, empiric treatment for common or even uncommon infectious diseases may avoid overdiagnosis and overtreatment of MIS-C as well as improve patient outcomes.
“We do have specific MIS-C guidelines at our institution,” Dr. Dean said, “but like all institutions, we are dealing with the broad definition of MIS-C according to the World Health Organization and the CDC, which is really the takeaway from this paper.”
More difficult differentiation
Both groups of authors pointed out that, as SARS-CoV-2 spreads throughout a community, a higher percentage of the population will have positive results on antibody testing, and such results will become less useful for differentiating between MIS-C and other conditions.
Despite these series’ cautionary lessons, other experts point to the critical importance of including MIS-C early on in the interest of efficient diagnosis and therapy. “In the cases cited, other pathologies were evaluated for and treated accordingly,” said Kara Gross Margolis, MD, AGAF, an associate professor of pediatrics in the division of pediatric gastroenterology, hepatology, and nutrition at Morgan Stanley Children’s Hospital,New York. “These papers stress the need for a balance that is important, and all potential diagnoses need to be considered, but MIS-C, due to its potential severe consequences, also needs to be on our differential now.”
In her view, as this new high-morbidity entity becomes more widespread during the pandemic, it will be increasingly important to keep this condition on the diagnostic radar.
Interestingly, in a converse example of diagnostic clouding, Dr. Gross Margolis’s group reported (Gastroenterology. 2020 Oct;159[4]:1571-4.e2) last year on a pediatric case series in which the presence of gastrointestinal symptoms in children with COVID-19–related MIS-C muddied the diagnosis by confusing this potentially severe syndrome with more common and less toxic gastrointestinal infections.
According to Dr. Smart, although the two reports don’t offer evidence for a particular diagnostic practice, they can inform the decision-making process. “It may be that we will have enough evidence shortly to say what the best practice is regarding diagnostic evaluation of possible MIS-C cases,” he said. “Until then, we must remember that common things occur commonly, even during a global pandemic.”
Neither of the two reports received any specific funding. The authors disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.
The emergence of multiple inflammatory syndrome in children (MIS-C) in association with COVID-19 may be complicating the investigation and diagnosis of more common viral and bacterial infections, potentially delaying treatment and prolonging hospital stays.
Two recent articles published online in Hospital Pediatrics provide evidence of this phenomenon. The articles outlined case studies of children who underwent extensive investigation for MIS-C when in fact they had less severe and more common infections. MIS-C is a severe but rare syndrome that involves systemic hyperinflammation with fever and multisystem organ dysfunction similar to that of Kawasaki disease (KD).
In one of the articles, Matthew Molloy, MD, MPH, of the division of pediatric hospital medicine at Cincinnati Children’s Hospital Medical Center, and colleagues aptly asked: “What are we missing in our search for MIS-C?”
E. coli, not SARS-CoV-2
That question arose from a case involving a 3-year-old boy who had a 6-day history of fever and fatigue. Three days earlier, he had tested negative for strep antigen and COVID-19. He had a persistent, high fever, reduced appetite, and reduced urine output and was taken to the ED. On physical examination, there was no rash, skin peeling, redness of the eye or oral mucosa, congestion, rhinorrhea, cough, shortness of breath, chest pain, abdominal pain, nausea, vomiting, or diarrhea.
Urinalysis results and exam findings were suspicious for pyelonephritis. Other findings from an extensive laboratory workup raised the alarm that the boy was suffering from MIS-C as opposed to incomplete KD. After admission to hospital medicine, the cardiology, rheumatology, and infectious disease teams were called in to consult.
Repeat labs were planned for the following day before initiating therapy. On day 2, the child’s urine culture was positive for gram-negative rods, later identified as Escherichia coli. The boy was started on ceftriaxone. Left renal scarring was apparent on ultrasound. The patient’s condition resolved after 36 hours, and he was discharged home with antibiotics.
‘Diagnosis derailed’
Calling this a case of “diagnosis derailed,” the authors noted that, in the pre-COVID era, this child’s signs and symptoms would likely have triggered a more targeted and less costly evaluation for more common infectious and noninfectious causes, including pyelonephritis, absent any physical exam findings consistent with KD.
“However, the patient presented in the midst of the COVID-19 pandemic with growing awareness of a new clinical entity,” Dr. Molloy and colleagues wrote. “Anchored to the patient’s persistent fever, the medical team initiated an extensive, costly, and ultimately unnecessary workup to avoid missing the diagnosis of MIS-C; a not yet well-described diagnosis with potentially severe morbidity.”
Confirmation bias and diagnostic momentum likely contributed to the early focus on MIS-C rather than more common alternatives, the authors acknowledged. The addition of mildly abnormal laboratory data not typically obtained in the evaluation of fever led the team astray. “The diagnosis and definitive treatment may have been made earlier had the focus on concern for MIS-C not been present,” Dr. Molloy said in an interview.
Keeping value in care
The authors recognized that their initial approach to evaluating for MIS-C provided low-value care. “In our desire to not ‘miss’ MIS-C, we were performing costly evaluations that at times produced mildly abnormal, nonspecific results,” they wrote. That triggered a cascade of specialty consultations, follow-up testing, and an unwarranted diagnostic preoccupation with MIS-C.
Determining the extra price tag for the child’s workup would be complex and difficult because there is a difference in the cost to the hospital and the cost to the family, Dr. Molloy said. “However, there are potential cost savings that would be related to making a correct diagnosis in a timely manner in terms of preventing downstream effects from delayed diagnoses.”
Even as clinicians struggle with the challenging SARS-CoV-2 learning curve, Dr. Molloy and associates urged them to continue to strive for high-value care, with an unwavering focus on using only necessary resources, a stewardship the pandemic has shown to be critical.
“The COVID-19 pandemic has been an incredibly stressful time for physicians and for families,” Dr. Molloy said. “COVID-19 and related conditions like MIS-C are new, and we are learning more and more about them every week. These diagnoses are understandably on the minds of physicians and families when children present with fever.” Notwithstanding, the boy’s case underscores the need for clinicians to consider alternate diagnoses and the value of the care provided.
Impact of bias
Dr. Molloy’s group brings home the cognitive biases practitioners often suffer from, including anchoring and confirmation bias and diagnostic momentum, according to J. Howard Smart, MD, chief of pediatrics at Sharp Mary Birch Hospital for Women and Newborns, San Diego, and an assistant clinical professor of pediatrics at University of California, San Diego.
“But it is one thing to recognize these in retrospect and quite another to consider whether they may be happening to you yourself in real time,” he said in an interview. “It is almost as if we need to have a ‘time out,’ where we stop and ask ourselves whether there is something else that could be explaining our patient’s presentation, something that would be more common and more likely to be occurring.”
According to Dr. Smart, who was not involved in Dr. Molloy’s study, the team’s premature diagnostic focus on MIS-C was almost the inverse of what typically happens with KD. “It is usually the case that Kawasaki disease does not enter the differential diagnosis until late in the course of the fever, typically on day 5 or later, when it may have been better to think of it earlier,” he said.
In the second article, Andrea Dean, MD, of the department of pediatrics at Baylor College of Medicine and Texas Children’s Hospital, both in Houston, and colleagues outlined the cases of five patients aged 8-17 years who were hospitalized in May 2020 for suspected MIS-C. They exhibited inflammatory and other concerning indicators but were eventually discharged with a diagnosis of murine typhus.
This flea-borne infection, most commonly reported in the United States in the southeastern Gulf Coast region, Hawaii, and California, is often associated with a triad of fever, rash, and headache.
Cases have been rising in southern Texas, and Dr. Dean and colleagues postulated that school closures and social distancing may have increased exposure as a result of children spending more time outdoors or with pets. “Alternatively, parental concern for SARS-CoV-2 infection could mean children with symptoms are presenting to care and being referred or admitted to the hospital more frequently due to provider concern for MIS-C,” they wrote.
Cardiac involvement
The most concerning of the five cases in terms of possible MIS-C, Dr. Dean said in an interview, was that of a 12-year-old boy who had fever for 6 days in association with headache, eczematous rash, dry lips, and conjunctivitis. Laboratory tests showed a mildly elevated C-reactive protein level, hyponatremia, and thrombocytopenia, as well as sterile pyuria and mildly elevated prothrombin time. He was treated empirically with doxycycline, and his fever resolved over the next 24 hours.
An echocardiogram at initial evaluation, however, revealed mild dilation of the left anterior descending and right coronary arteries, which led to the administration of intravenous immunoglobulin and aspirin for atypical KD, in contrast to MIS-C. The authors postulated that mild cardiac involvement in disorders other than MIS-C and KD may be underrecognized.
The lesson from these cases, Dr. Dean and associates concluded, is that hospitalists must maintain a wide differential diagnosis when assessing a child with prolonged fever and evidence of systemic inflammation. The CDC stipulates that a diagnosis of MIS-C requires the absence of a plausible alternative diagnosis.
In addition to common viral, bacterial, and noninfectious disorders, a range of regional endemic rickettsial and parasitic infections must be considered as alternative diagnoses to MIS-C. “Many of these diseases cannot be reliably differentiated from MIS-C on presentation, and as community exposure to SARS-CoV-2 grows, hospitalists should be prepared to admit febrile children with evidence of systemic inflammation for brief observation periods to evaluate for MIS-C,” Dr. Dean’s group wrote. In this context, however, empiric treatment for common or even uncommon infectious diseases may avoid overdiagnosis and overtreatment of MIS-C as well as improve patient outcomes.
“We do have specific MIS-C guidelines at our institution,” Dr. Dean said, “but like all institutions, we are dealing with the broad definition of MIS-C according to the World Health Organization and the CDC, which is really the takeaway from this paper.”
More difficult differentiation
Both groups of authors pointed out that, as SARS-CoV-2 spreads throughout a community, a higher percentage of the population will have positive results on antibody testing, and such results will become less useful for differentiating between MIS-C and other conditions.
Despite these series’ cautionary lessons, other experts point to the critical importance of including MIS-C early on in the interest of efficient diagnosis and therapy. “In the cases cited, other pathologies were evaluated for and treated accordingly,” said Kara Gross Margolis, MD, AGAF, an associate professor of pediatrics in the division of pediatric gastroenterology, hepatology, and nutrition at Morgan Stanley Children’s Hospital,New York. “These papers stress the need for a balance that is important, and all potential diagnoses need to be considered, but MIS-C, due to its potential severe consequences, also needs to be on our differential now.”
In her view, as this new high-morbidity entity becomes more widespread during the pandemic, it will be increasingly important to keep this condition on the diagnostic radar.
Interestingly, in a converse example of diagnostic clouding, Dr. Gross Margolis’s group reported (Gastroenterology. 2020 Oct;159[4]:1571-4.e2) last year on a pediatric case series in which the presence of gastrointestinal symptoms in children with COVID-19–related MIS-C muddied the diagnosis by confusing this potentially severe syndrome with more common and less toxic gastrointestinal infections.
According to Dr. Smart, although the two reports don’t offer evidence for a particular diagnostic practice, they can inform the decision-making process. “It may be that we will have enough evidence shortly to say what the best practice is regarding diagnostic evaluation of possible MIS-C cases,” he said. “Until then, we must remember that common things occur commonly, even during a global pandemic.”
Neither of the two reports received any specific funding. The authors disclosed no relevant financial relationships.
A version of this article first appeared on Medscape.com.