Opinion
Editorials represent the opinions of the authors and JAMA and not those of the American Medical Association.
EDITORIAL
Clinical Application of Whole-Genome Sequencing Proceed With Care William Gregory Feero, MD, PhD
Stunning advances have been made over the last 5 years in the ability to rapidly and inexpensively detect variation in the human genome. In the mid-2000s massively parallel detection of single-nucleotide polymorphisms (SNPs) on gene chips (genotyping) burst on to the Related article page 1035 scene, launching the era of genome-wide association studies and high-profile direct-toconsumer marketing of genetic testing of questionable clinical value.1 More recently, substantial credible evidence has been accumulating for the research and clinical value of wholeexome sequencing (WES) for conditions ranging from cancer to developmental delay to mendelian disorders.2-5 Wholeexome sequencing uses high-throughput sequencing technologies to determine the arrangement of DNA base pairs specifying the protein coding regions of an individual’s genome, also known as the exome. As remarkable as SNP genotyping and WES technologies are, they are both interim methods for detecting DNA variation. Assuming perfect technical accuracy, both are limited in the extent of variation that they can discover in a patient. In the case of SNP genotyping, this is because of the type of known variations the platforms can detect and in WES because the exome comprises about 1% of the entire genome. Clinical application of whole-genome sequencing (WGS) represents the next step in the progression to complete elucidation of the genomic determinants of a patient’s heritable make-up. Using ever-evolving technologies, WGS can provide insights into known and unknown variations in approximately 95% of the individual patient’s genome. Until very recently, the time, cost, and technical expertise required to generate and analyze WGS data largely precluded serious consideration of its use outside of research settings. This can no longer be assumed to be the case.6,7 Ideally, uncertainty in medical decision making would be reduced and clinical outcomes improved by making interpreted genome-sequence information available to patients, physicians, and other health care practitioners. This is a major premise of the movement toward personalized or precision medicine. In this issue of JAMA, the descriptive study by Dewey and colleagues8 critically explores several of the myriad issues confronting the integration of WGS into patient care at a major academic medical center. The authors report data from a cohort of 12 patient volunteers, without obvious manifest heritable disease, who had their genomes sequenced, interpreted, and reported back to a panel of potential treating physicians not involved in the analysis
pipeline. There are several notable aspects to this article, the 2 most outstanding of which are that the participants underwent clinical WGS rather than WES and the level of selfrevelatory reporting by the authors regarding potential sources of error in the pipeline. The most obvious feature of WGS is that it substantially increases the volume of detected variants per individual. In contrast to WES, WGS captures genomic variations within and outside of the exome. To date, only a comparatively small subset of these variations have demonstrated health consequences. In the study by Dewey et al, the median number of unique variations identified per individual on the reference sequencing platform—slightly less than 3 million—is absolutely staggering. Collating and tracking this number of variations is technically daunting and interpretation requires sophisticated bioinformatics analysis. Importantly, current WGS technologies likely underestimate the full extent of potentially meaningful variation present in an individual’s genome. For example, WES/WGS technologies have difficulty accurately measuring the number of elements in stretches of dinucleotide or trinucleotide repeats.9 Complicating the picture further, Dewey et al present sobering data regarding the analytic performance of 2 commercially available WGS platforms used in their study. With these 2 platforms, medians of 9% and 17% of 56 genes recently identified as having potentially high clinical importance were not covered by sufficient numbers of repeated sequencing reads (depth or fold coverage) to achieve clinical grade variant detection. Looking across all variations detected, the authors present disturbingly high levels of disagreement between platform variant detection ability (“calls”), particularly for small insertions and deletions (66% concordance) in protein coding regions and variants that were candidates for disease risk (33% concordance). As the clinical implications of these variants become more evident, variation in results based on platform will become more important. The ability to successfully identify potentially clinically relevant variants from the much larger pool of all detected variants depends in part on the availability of high-quality, accessible reference databases and prediction models that correlate variation to clinical phenotypes, changes in biological function, and evolutionary conservation. Dewey et al report consulting nearly 50 different databases or prediction models through their pipeline. A particular challenge facing the clinical use of WGS lies in making sense of the plethora of novel or very rare variants occurring in potentially important regions
jama.com
JAMA March 12, 2014 Volume 311, Number 10
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Nanyang Technological University User on 05/31/2015
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Opinion Editorial
of DNA that do not code for proteins and appear in no accessible database. To date, there is no easy remedy for this issue. The authors’ ability to winnow down the detected variations to a set that could be manageably reviewed by experts relied on a complex data analysis program developed by the authors (Sequence to Medical Phenotype) as a prefilter for variations that might be of biological interest. Others have developed similar bioinformatics approaches to aid in variant detection. However, to date, no widely clinically validated program exists for paring down the thousands of novel variations to a short list amenable to manual interpretation by a panel of experts. Furthermore, as reported by Dewey et al, experts can differ in their conclusions regarding the potential clinical significance of potential risk variants. For example, the reported κ (kappa) values indicated only moderate agreement for predicted pathogenicity for 18 variants potentially important for mendelian disease risk or carrier status in study participants. Any analysis of WGS (or WES) sequence information is dependent on the quality of the available reference information, the robustness of the design of interpretive bioinformatics systems, and the level of expertise in the group manually reviewing the short list of variations identified by the bioinformatics step. Within the genomics community, there is recognition of the limitations of currently available databases such as the Human Gene Mutation Database (HGMD) for clinical sequence interpretation, and a major US federal effort to create a centralized repository of maintained (curated), machine readable data on genotype/phenotype correlations has been launched.10,11 Clinicians should recognize that determining the biological consequences of very rare and novel variations found in a genome, especially outside of the exome, remains arduous, tenuous, and costly even in highly experienced hands. A number of concerns have been raised regarding the downstream consequences of providing clinicians with interpreted genome sc ale data in an other w ise healthy individual.12-14 One of the most pressing in an era of health care cost containment is the concern that flagging potential risks in patients would lead to resource intensive secondary testing and interventions of unclear benefit. The yield of potentially clinically significant variations related to inherited disease reported by Dewey et al for each participant was fairly substantial (as reported in Table 2 of the article8). To explore the clinical consequences of returning the results defined by the research team as reportable from their 12 participants, the authors shared technical summary reports (online supplemental material “Sample Report”8) to a small group of volunteer clinicians (3 primary care clinicians and 2 medical geneticists) not involved in the process of genome interpretation and analyzed their suggested action steps. That the clinicians could
ARTICLE INFORMATION Author Affiliations: Maine Dartmouth Family Medicine Residency, Augusta, Maine; Associate Editor, JAMA. 1018
make much sense of the variant reports likely indicates a higher level of genomics expertise than their average peer clinicians. The findings suggest, at least superficially, that concerns about expensive immediate downstream clinical actions in every sequenced individual may be unfounded. On average, the panelists suggested an estimated 1 to 3 initial additional diagnostic tests or referrals per individual at a cost of US $351 to US $776; clearly those next steps could result in a cascade of interventions of unclear costs. Despite the apparently reasonable hypothetical initial cost estimates, an important finding was the fair to poor levels of agreement among physicians regarding what variations should be acted on, as well as the diversity of next steps recommended. Admittedly, both the patient and clinician sample size is small. However, lack of agreement regarding clinical actions raises the credible possibility that introducing WGS information into clinical encounters at this time may be premature. Significant work is needed to develop evidence-linked guidelines for clinical action. Education of physicians and other health care practitioners regarding the potential risks and benefits of obtaining WGS seems of paramount importance. Medical decision making in the setting of an incomplete understanding of human biology has been a part of caring for patients for thousands of years. For better or worse, clinicians have developed skills to cope reasonably effectively with substantial lacunae in knowledge. Complete elucidation of the human genome sequence will undoubtedly be recorded in the annals of medical science as a major step toward filling voids in understanding the biological underpinnings of health and disease. In the near term, however, genome sequencing has unmasked substantial additional fragments of the complexity underlying health and disease. Medical application of genomic and personalized medicine technologies hold out the real promise of improved decision making and patient outcomes by providing an increased knowledge of the determinants of health and disease at the level of the individual patient. Like the personal computer, Internet, smartphones, and electronic health records, turning back now from the use of genomic technologies in health care is inconceivable.15 Studies like that of Dewey et al provide a glimpse of what is possible but demonstrate that much remains to be learned about previously assumed to be “known” information as well as myriad “known unknowns” and “unknown unknowns” before truly successful widespread integration can occur. A question facing potential early adopters of genome sequencing as an adjunct to patient care is whether or not having WGS data, at this time, will decrease uncertainty and improve outcomes or merely exponentially increase the complexity of clinical care.
Corresponding Author: William Gregory Feero, MD, PhD, Maine Dartmouth Family Medicine Residency, 4 Sheridan Dr, Ste 2, Fairfield, ME 04937 ([email protected]).
Conflict of Interest Disclosures: The author has completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
JAMA March 12, 2014 Volume 311, Number 10
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Nanyang Technological University User on 05/31/2015
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Editorial Opinion
REFERENCES 1. Manolio TA, Green ED. Genomics reaches the clinic: from basic discoveries to clinical impact. Cell. 2011;147(1):14-16. 2. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61-70. 3. Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330-337. 4. de Ligt J, Willemsen MH, van Bon BW, et al. Diagnostic exome sequencing in persons with severe intellectual disability. N Engl J Med. 2012;367(20):1921-1929. 5. Yang Y, Muzny DM, Reid JG, et al. Clinical whole-exome sequencing for the diagnosis of mendelian disorders. N Engl J Med. 2013;369(16):1502-1511. 6. Jiang YH, Yuen RK, Jin X, et al. Detection of clinically relevant genetic variants in autism
spectrum disorder by whole-genome sequencing. Am J Hum Genet. 2013;93(2):249-263. 7. Hayden EC. Is the $1,000 genome for real? http://www.nature.com/news/is-the -1-000-genome-for-real-1.14530, Accessed January 15, 2014. 8. Dewey FE, Grove ME, Pan C, et al. Clinical interpretation and implications of whole-genome sequencing. JAMA. doi:10.1001/jama.2014.1717. 9. Metzker ML. Sequencing technologies—the next generation. Nat Rev Genet. 2010;11(1):31-46. 10. The Human Gene Mutation Database. http://www.hgmd.cf.ac.uk/ac/index.php. Accessed January 14, 2014. 11. Benowitz S. New NIH-funded resource focuses on use of genomic variants in medical care [news release]. Bethesda, MD: NIH News; September 25, 2013. http://www.genome.gov/27555151. Accessed Februrary 16, 2014.
12. McGuire AL, Burke W. An unwelcome side effect of direct-to-consumer personal genome testing: raiding the medical commons. JAMA. 2008;300(22):2669-2671. 13. Johansen Taber KA, Dickinson BD, Wilson M. The promise and challenges of next-generation genome sequencing for clinical care. JAMA Intern Med. 2014;174(2):275-280. 14. Caulfield T, Evans J, McGuire A, et al. Reflections on the cost of “low-cost” whole genome sequencing: framing the health policy debate. PLoS Biol. 2013;11(11):e1001699. 15. Green ED, Guyer MS; National Human Genome Research Institute. Charting a course for genomic medicine from base pairs to bedside. Nature. 2011;470(7333):204-213.
Research on Peer Review and Biomedical Publication Furthering the Quest to Improve the Quality of Reporting Drummond Rennie, MD; Annette Flanagin, RN, MA
This issue of JAMA includes 3 reports1-3 first presented at the Seventh International Congress on Peer Review and Biomedical Publication in September 2013.4 At the first congress, held in 1989, the most common topic of the presented abstracts was editorial peer review.5 Since then, the research presented and discussed has substantially broadened to include all aspects of biomedical publication—from research proposals to sharing data after publication.4 In this issue of JAMA, Malički and colleagues1 report their findings from an analysis of the 614 abstracts presented at the 7 congresses held from 1989 through 2013. Of these abstracts, overall, 76% were observational studies, 16% were studies of interventions aimed at improving peer review and sciRelated articles pages 1045, entific reporting, and 8% were 1063 and 1065 opinion papers. At the most recent congress, 27% of the 110 presented studies were interventional, including 5 randomized trials. The authors also found that 305 (61%) of the presentations from the first 6 congresses were eventually published and that 265 articles had received at least 1 citation (with a median of 20 citations per article), with the most-cited articles focusing on reporting guidelines, synthesis of evidence, and publication bias. Of the articles published after presentation at the first 6 congresses (N = 294), 36% reported being funded, whereas of the 110 abstracts presented at the 2013 congress, 41% reported being funded. The authors point out that interventional studies aimed at improving peer review and scientific reporting are still underrepresented, and, echoing previous calls for research for these congresses,6 they suggest that systematic approaches and funding schemes are still needed to further improve research into peer review and biomedical publication.
Two other reports from the 2013 congress provide important information about the quality of reporting results from clinical trials. Becker and colleagues2 conducted a crosssectional analysis of clinical trials with primary results published in high-impact journals between July 2010 and June 2011 and compared trial information and results reported in ClinicalTrials.gov with that reported in peer-reviewed publications. The authors found that 93 of 96 trials had at least 1 discrepancy, with the highest rates of discordance involving completion rates (22%) and trial interventions (16%). In addition, in 91 trials that described 156 primary efficacy end points, including 132 end points described in both sources, 21 trials (16%) had discordant end points and 30 end points (23%) could not be compared. These investigators suggest that further efforts are needed to ensure the accuracy of reporting results of clinical trials. In another report, Kasenda and colleagues3 describe a multinational study that examined 894 clinical trials involving patients, after approval of the relevant trial protocols by 6 research ethics committees between 2000 and 2003, with follow-up through April 2013 to determine the prevalence of and reasons for discontinuation and publication status. The investigators found that 25% of all trials approved by the 6 research ethics committees were discontinued, with poor recruitment being the most common cause. Moreover, these discontinued trials were often not reported and the ethics committees often were not informed. The results of these 2 studies2,3 highlight the need for greater transparency and efficiency in the reporting of research. Moreover, these studies are reminiscent of demonstrations at the early congresses of major defects in reporting of research, which were soon followed by the development of
jama.com
JAMA March 12, 2014 Volume 311, Number 10
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Nanyang Technological University User on 05/31/2015
1019
Editorials represent the opinions of the authors and JAMA and not those of the American Medical Association.
EDITORIAL
Clinical Application of Whole-Genome Sequencing Proceed With Care William Gregory Feero, MD, PhD
Stunning advances have been made over the last 5 years in the ability to rapidly and inexpensively detect variation in the human genome. In the mid-2000s massively parallel detection of single-nucleotide polymorphisms (SNPs) on gene chips (genotyping) burst on to the Related article page 1035 scene, launching the era of genome-wide association studies and high-profile direct-toconsumer marketing of genetic testing of questionable clinical value.1 More recently, substantial credible evidence has been accumulating for the research and clinical value of wholeexome sequencing (WES) for conditions ranging from cancer to developmental delay to mendelian disorders.2-5 Wholeexome sequencing uses high-throughput sequencing technologies to determine the arrangement of DNA base pairs specifying the protein coding regions of an individual’s genome, also known as the exome. As remarkable as SNP genotyping and WES technologies are, they are both interim methods for detecting DNA variation. Assuming perfect technical accuracy, both are limited in the extent of variation that they can discover in a patient. In the case of SNP genotyping, this is because of the type of known variations the platforms can detect and in WES because the exome comprises about 1% of the entire genome. Clinical application of whole-genome sequencing (WGS) represents the next step in the progression to complete elucidation of the genomic determinants of a patient’s heritable make-up. Using ever-evolving technologies, WGS can provide insights into known and unknown variations in approximately 95% of the individual patient’s genome. Until very recently, the time, cost, and technical expertise required to generate and analyze WGS data largely precluded serious consideration of its use outside of research settings. This can no longer be assumed to be the case.6,7 Ideally, uncertainty in medical decision making would be reduced and clinical outcomes improved by making interpreted genome-sequence information available to patients, physicians, and other health care practitioners. This is a major premise of the movement toward personalized or precision medicine. In this issue of JAMA, the descriptive study by Dewey and colleagues8 critically explores several of the myriad issues confronting the integration of WGS into patient care at a major academic medical center. The authors report data from a cohort of 12 patient volunteers, without obvious manifest heritable disease, who had their genomes sequenced, interpreted, and reported back to a panel of potential treating physicians not involved in the analysis
pipeline. There are several notable aspects to this article, the 2 most outstanding of which are that the participants underwent clinical WGS rather than WES and the level of selfrevelatory reporting by the authors regarding potential sources of error in the pipeline. The most obvious feature of WGS is that it substantially increases the volume of detected variants per individual. In contrast to WES, WGS captures genomic variations within and outside of the exome. To date, only a comparatively small subset of these variations have demonstrated health consequences. In the study by Dewey et al, the median number of unique variations identified per individual on the reference sequencing platform—slightly less than 3 million—is absolutely staggering. Collating and tracking this number of variations is technically daunting and interpretation requires sophisticated bioinformatics analysis. Importantly, current WGS technologies likely underestimate the full extent of potentially meaningful variation present in an individual’s genome. For example, WES/WGS technologies have difficulty accurately measuring the number of elements in stretches of dinucleotide or trinucleotide repeats.9 Complicating the picture further, Dewey et al present sobering data regarding the analytic performance of 2 commercially available WGS platforms used in their study. With these 2 platforms, medians of 9% and 17% of 56 genes recently identified as having potentially high clinical importance were not covered by sufficient numbers of repeated sequencing reads (depth or fold coverage) to achieve clinical grade variant detection. Looking across all variations detected, the authors present disturbingly high levels of disagreement between platform variant detection ability (“calls”), particularly for small insertions and deletions (66% concordance) in protein coding regions and variants that were candidates for disease risk (33% concordance). As the clinical implications of these variants become more evident, variation in results based on platform will become more important. The ability to successfully identify potentially clinically relevant variants from the much larger pool of all detected variants depends in part on the availability of high-quality, accessible reference databases and prediction models that correlate variation to clinical phenotypes, changes in biological function, and evolutionary conservation. Dewey et al report consulting nearly 50 different databases or prediction models through their pipeline. A particular challenge facing the clinical use of WGS lies in making sense of the plethora of novel or very rare variants occurring in potentially important regions
jama.com
JAMA March 12, 2014 Volume 311, Number 10
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Nanyang Technological University User on 05/31/2015
1017
Opinion Editorial
of DNA that do not code for proteins and appear in no accessible database. To date, there is no easy remedy for this issue. The authors’ ability to winnow down the detected variations to a set that could be manageably reviewed by experts relied on a complex data analysis program developed by the authors (Sequence to Medical Phenotype) as a prefilter for variations that might be of biological interest. Others have developed similar bioinformatics approaches to aid in variant detection. However, to date, no widely clinically validated program exists for paring down the thousands of novel variations to a short list amenable to manual interpretation by a panel of experts. Furthermore, as reported by Dewey et al, experts can differ in their conclusions regarding the potential clinical significance of potential risk variants. For example, the reported κ (kappa) values indicated only moderate agreement for predicted pathogenicity for 18 variants potentially important for mendelian disease risk or carrier status in study participants. Any analysis of WGS (or WES) sequence information is dependent on the quality of the available reference information, the robustness of the design of interpretive bioinformatics systems, and the level of expertise in the group manually reviewing the short list of variations identified by the bioinformatics step. Within the genomics community, there is recognition of the limitations of currently available databases such as the Human Gene Mutation Database (HGMD) for clinical sequence interpretation, and a major US federal effort to create a centralized repository of maintained (curated), machine readable data on genotype/phenotype correlations has been launched.10,11 Clinicians should recognize that determining the biological consequences of very rare and novel variations found in a genome, especially outside of the exome, remains arduous, tenuous, and costly even in highly experienced hands. A number of concerns have been raised regarding the downstream consequences of providing clinicians with interpreted genome sc ale data in an other w ise healthy individual.12-14 One of the most pressing in an era of health care cost containment is the concern that flagging potential risks in patients would lead to resource intensive secondary testing and interventions of unclear benefit. The yield of potentially clinically significant variations related to inherited disease reported by Dewey et al for each participant was fairly substantial (as reported in Table 2 of the article8). To explore the clinical consequences of returning the results defined by the research team as reportable from their 12 participants, the authors shared technical summary reports (online supplemental material “Sample Report”8) to a small group of volunteer clinicians (3 primary care clinicians and 2 medical geneticists) not involved in the process of genome interpretation and analyzed their suggested action steps. That the clinicians could
ARTICLE INFORMATION Author Affiliations: Maine Dartmouth Family Medicine Residency, Augusta, Maine; Associate Editor, JAMA. 1018
make much sense of the variant reports likely indicates a higher level of genomics expertise than their average peer clinicians. The findings suggest, at least superficially, that concerns about expensive immediate downstream clinical actions in every sequenced individual may be unfounded. On average, the panelists suggested an estimated 1 to 3 initial additional diagnostic tests or referrals per individual at a cost of US $351 to US $776; clearly those next steps could result in a cascade of interventions of unclear costs. Despite the apparently reasonable hypothetical initial cost estimates, an important finding was the fair to poor levels of agreement among physicians regarding what variations should be acted on, as well as the diversity of next steps recommended. Admittedly, both the patient and clinician sample size is small. However, lack of agreement regarding clinical actions raises the credible possibility that introducing WGS information into clinical encounters at this time may be premature. Significant work is needed to develop evidence-linked guidelines for clinical action. Education of physicians and other health care practitioners regarding the potential risks and benefits of obtaining WGS seems of paramount importance. Medical decision making in the setting of an incomplete understanding of human biology has been a part of caring for patients for thousands of years. For better or worse, clinicians have developed skills to cope reasonably effectively with substantial lacunae in knowledge. Complete elucidation of the human genome sequence will undoubtedly be recorded in the annals of medical science as a major step toward filling voids in understanding the biological underpinnings of health and disease. In the near term, however, genome sequencing has unmasked substantial additional fragments of the complexity underlying health and disease. Medical application of genomic and personalized medicine technologies hold out the real promise of improved decision making and patient outcomes by providing an increased knowledge of the determinants of health and disease at the level of the individual patient. Like the personal computer, Internet, smartphones, and electronic health records, turning back now from the use of genomic technologies in health care is inconceivable.15 Studies like that of Dewey et al provide a glimpse of what is possible but demonstrate that much remains to be learned about previously assumed to be “known” information as well as myriad “known unknowns” and “unknown unknowns” before truly successful widespread integration can occur. A question facing potential early adopters of genome sequencing as an adjunct to patient care is whether or not having WGS data, at this time, will decrease uncertainty and improve outcomes or merely exponentially increase the complexity of clinical care.
Corresponding Author: William Gregory Feero, MD, PhD, Maine Dartmouth Family Medicine Residency, 4 Sheridan Dr, Ste 2, Fairfield, ME 04937 ([email protected]).
Conflict of Interest Disclosures: The author has completed and submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest and none were reported.
JAMA March 12, 2014 Volume 311, Number 10
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Nanyang Technological University User on 05/31/2015
jama.com
Editorial Opinion
REFERENCES 1. Manolio TA, Green ED. Genomics reaches the clinic: from basic discoveries to clinical impact. Cell. 2011;147(1):14-16. 2. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61-70. 3. Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330-337. 4. de Ligt J, Willemsen MH, van Bon BW, et al. Diagnostic exome sequencing in persons with severe intellectual disability. N Engl J Med. 2012;367(20):1921-1929. 5. Yang Y, Muzny DM, Reid JG, et al. Clinical whole-exome sequencing for the diagnosis of mendelian disorders. N Engl J Med. 2013;369(16):1502-1511. 6. Jiang YH, Yuen RK, Jin X, et al. Detection of clinically relevant genetic variants in autism
spectrum disorder by whole-genome sequencing. Am J Hum Genet. 2013;93(2):249-263. 7. Hayden EC. Is the $1,000 genome for real? http://www.nature.com/news/is-the -1-000-genome-for-real-1.14530, Accessed January 15, 2014. 8. Dewey FE, Grove ME, Pan C, et al. Clinical interpretation and implications of whole-genome sequencing. JAMA. doi:10.1001/jama.2014.1717. 9. Metzker ML. Sequencing technologies—the next generation. Nat Rev Genet. 2010;11(1):31-46. 10. The Human Gene Mutation Database. http://www.hgmd.cf.ac.uk/ac/index.php. Accessed January 14, 2014. 11. Benowitz S. New NIH-funded resource focuses on use of genomic variants in medical care [news release]. Bethesda, MD: NIH News; September 25, 2013. http://www.genome.gov/27555151. Accessed Februrary 16, 2014.
12. McGuire AL, Burke W. An unwelcome side effect of direct-to-consumer personal genome testing: raiding the medical commons. JAMA. 2008;300(22):2669-2671. 13. Johansen Taber KA, Dickinson BD, Wilson M. The promise and challenges of next-generation genome sequencing for clinical care. JAMA Intern Med. 2014;174(2):275-280. 14. Caulfield T, Evans J, McGuire A, et al. Reflections on the cost of “low-cost” whole genome sequencing: framing the health policy debate. PLoS Biol. 2013;11(11):e1001699. 15. Green ED, Guyer MS; National Human Genome Research Institute. Charting a course for genomic medicine from base pairs to bedside. Nature. 2011;470(7333):204-213.
Research on Peer Review and Biomedical Publication Furthering the Quest to Improve the Quality of Reporting Drummond Rennie, MD; Annette Flanagin, RN, MA
This issue of JAMA includes 3 reports1-3 first presented at the Seventh International Congress on Peer Review and Biomedical Publication in September 2013.4 At the first congress, held in 1989, the most common topic of the presented abstracts was editorial peer review.5 Since then, the research presented and discussed has substantially broadened to include all aspects of biomedical publication—from research proposals to sharing data after publication.4 In this issue of JAMA, Malički and colleagues1 report their findings from an analysis of the 614 abstracts presented at the 7 congresses held from 1989 through 2013. Of these abstracts, overall, 76% were observational studies, 16% were studies of interventions aimed at improving peer review and sciRelated articles pages 1045, entific reporting, and 8% were 1063 and 1065 opinion papers. At the most recent congress, 27% of the 110 presented studies were interventional, including 5 randomized trials. The authors also found that 305 (61%) of the presentations from the first 6 congresses were eventually published and that 265 articles had received at least 1 citation (with a median of 20 citations per article), with the most-cited articles focusing on reporting guidelines, synthesis of evidence, and publication bias. Of the articles published after presentation at the first 6 congresses (N = 294), 36% reported being funded, whereas of the 110 abstracts presented at the 2013 congress, 41% reported being funded. The authors point out that interventional studies aimed at improving peer review and scientific reporting are still underrepresented, and, echoing previous calls for research for these congresses,6 they suggest that systematic approaches and funding schemes are still needed to further improve research into peer review and biomedical publication.
Two other reports from the 2013 congress provide important information about the quality of reporting results from clinical trials. Becker and colleagues2 conducted a crosssectional analysis of clinical trials with primary results published in high-impact journals between July 2010 and June 2011 and compared trial information and results reported in ClinicalTrials.gov with that reported in peer-reviewed publications. The authors found that 93 of 96 trials had at least 1 discrepancy, with the highest rates of discordance involving completion rates (22%) and trial interventions (16%). In addition, in 91 trials that described 156 primary efficacy end points, including 132 end points described in both sources, 21 trials (16%) had discordant end points and 30 end points (23%) could not be compared. These investigators suggest that further efforts are needed to ensure the accuracy of reporting results of clinical trials. In another report, Kasenda and colleagues3 describe a multinational study that examined 894 clinical trials involving patients, after approval of the relevant trial protocols by 6 research ethics committees between 2000 and 2003, with follow-up through April 2013 to determine the prevalence of and reasons for discontinuation and publication status. The investigators found that 25% of all trials approved by the 6 research ethics committees were discontinued, with poor recruitment being the most common cause. Moreover, these discontinued trials were often not reported and the ethics committees often were not informed. The results of these 2 studies2,3 highlight the need for greater transparency and efficiency in the reporting of research. Moreover, these studies are reminiscent of demonstrations at the early congresses of major defects in reporting of research, which were soon followed by the development of
jama.com
JAMA March 12, 2014 Volume 311, Number 10
Copyright 2014 American Medical Association. All rights reserved.
Downloaded From: http://jama.jamanetwork.com/ by a Nanyang Technological University User on 05/31/2015
1019
