Reporting and Methods in Clinical Prediction Research: A Systematic Review
Publication Date
May 22, 2012
Journal
PLOS Medicine
Authors
Walter Bouwmeester, Nicolaas P. A. Zuithoff, Susan Mallett, Mirjam I. Geerlings, et al
Volume
9
Issue
5
Pages
e1001221
DOI
https://dx.plos.org/10.1371/journal.pmed.1001221
Publisher URL
http://journals.plos.org/plosmedicine/article?id=10.1371%2Fjournal.pmed.1001221
PubMed
http://www.ncbi.nlm.nih.gov/pubmed/22629234
PubMed Central
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3358324
Europe PMC
http://europepmc.org/abstract/MED/22629234
Web of Science
000304757300011
Scopus
84861556816
Mendeley
http://www.mendeley.com/research/reporting-methods-clinical-prediction-research-systematic-review-5
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{"title"=>"Reporting and methods in clinical prediction research: A systematic review", "type"=>"journal", "authors"=>[{"first_name"=>"Walter", "last_name"=>"Bouwmeester", "scopus_author_id"=>"35483006500"}, {"first_name"=>"Nicolaas P.A.", "last_name"=>"Zuithoff", "scopus_author_id"=>"12764394100"}, {"first_name"=>"Susan", "last_name"=>"Mallett", "scopus_author_id"=>"57189234864"}, {"first_name"=>"Mirjam I.", "last_name"=>"Geerlings", "scopus_author_id"=>"7003527469"}, {"first_name"=>"Yvonne", "last_name"=>"Vergouwe", "scopus_author_id"=>"8917677200"}, {"first_name"=>"Ewout W.", "last_name"=>"Steyerberg", "scopus_author_id"=>"7006417148"}, {"first_name"=>"Douglas G.", "last_name"=>"Altman", "scopus_author_id"=>"7201380947"}, {"first_name"=>"Karel G.M.", "last_name"=>"Moons", "scopus_author_id"=>"7004546169"}], "year"=>2012, "source"=>"PLoS Medicine", "identifiers"=>{"scopus"=>"2-s2.0-84861556816", "doi"=>"10.1371/journal.pmed.1001221", "sgr"=>"84861556816", "isbn"=>"1549-1676 (Electronic)\\r1549-1277 (Linking)", "pmid"=>"22629234", "issn"=>"15491277", "pui"=>"364901024"}, "id"=>"bdfa809b-4974-3630-9ff6-f0518b5545cc", "abstract"=>"BACKGROUND We investigated the reporting and methods of prediction studies, focusing on aims, designs, participant selection, outcomes, predictors, statistical power, statistical methods, and predictive performance measures. METHODS AND FINDINGS We used a full hand search to identify all prediction studies published in 2008 in six high impact general medical journals. We developed a comprehensive item list to systematically score conduct and reporting of the studies, based on recent recommendations for prediction research. Two reviewers independently scored the studies. We retrieved 71 papers for full text review: 51 were predictor finding studies, 14 were prediction model development studies, three addressed an external validation of a previously developed model, and three reported on a model's impact on participant outcome. Study design was unclear in 15% of studies, and a prospective cohort was used in most studies (60%). Descriptions of the participants and definitions of predictor and outcome were generally good. Despite many recommendations against doing so, continuous predictors were often dichotomized (32% of studies). The number of events per predictor as a measure of statistical power could not be determined in 67% of the studies; of the remainder, 53% had fewer than the commonly recommended value of ten events per predictor. Methods for a priori selection of candidate predictors were described in most studies (68%). A substantial number of studies relied on a p-value cut-off of p<0.05 to select predictors in the multivariable analyses (29%). Predictive model performance measures, i.e., calibration and discrimination, were reported in 12% and 27% of studies, respectively. CONCLUSIONS The majority of prediction studies in high impact journals do not follow current methodological recommendations, limiting their reliability and applicability.", "link"=>"http://www.mendeley.com/research/reporting-methods-clinical-prediction-research-systematic-review-5", "reader_count"=>10, "reader_count_by_academic_status"=>{"Unspecified"=>2, "Researcher"=>1, "Student > Ph. D. Student"=>3, "Student > Master"=>3, "Professor"=>1}, "reader_count_by_user_role"=>{"Unspecified"=>2, "Researcher"=>1, "Student > Ph. D. Student"=>3, "Student > Master"=>3, "Professor"=>1}, "reader_count_by_subject_area"=>{"Unspecified"=>3, "Engineering"=>1, "Nursing and Health Professions"=>1, "Mathematics"=>1, "Medicine and Dentistry"=>2, "Psychology"=>1, "Social Sciences"=>1}, "reader_count_by_subdiscipline"=>{"Engineering"=>{"Engineering"=>1}, "Medicine and Dentistry"=>{"Medicine and Dentistry"=>2}, "Social Sciences"=>{"Social Sciences"=>1}, "Psychology"=>{"Psychology"=>1}, "Nursing and Health Professions"=>{"Nursing and Health Professions"=>1}, "Mathematics"=>{"Mathematics"=>1}, "Unspecified"=>{"Unspecified"=>3}}, "group_count"=>1}

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Scopus | Further Information

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Figshare

  • {"files"=>["https://ndownloader.figshare.com/files/634981"], "description"=>"<p>Impact studies were excluded from this table because these studies had outcomes of a different type (e.g., costs). Hence, the total number of studies is 68.</p>a<p>Not applicable in 11/68 studies, because all cause death was the outcome.</p>b<p>Types of outcomes and how they were analysed (unclear for five studies). The sum 6+23+8+30 is higher than 63 because some outcomes were analysed in more than one way (e.g., a time-to-event outcome that was analysed as time to event and as a binary outcome neglecting time). If a study analysed two binary outcomes, it was here counted as one binary outcome.</p>c<p>After dichotomization of a continuous outcome.</p>d<p>One study used the Cochran–Mantel–Haenszel procedure, another calculated odds ratios.</p><p>CART, classification and regression tree.</p>", "links"=>[], "tags"=>["public health and epidemiology"], "article_id"=>305470, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t003", "stats"=>{"downloads"=>0, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Reporting_of_outcomes_/305470", "title"=>"Reporting of outcomes.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:31:10"}
  • {"files"=>["https://ndownloader.figshare.com/files/634898"], "description"=>"<p>Numbers are column percentages, with absolute numbers in parentheses. For continuous outcomes, the effective sample size is the number of participants divided by the number of predictors; for dichotomous outcomes, the effective sample size is the number of participants in the smallest category divided by the number of predictors; for time-to-event outcomes, the effective sample size is the number of events divided by the number of predictors.</p>a<p>Excluding impact and external validation studies, because they require very different statistical power calculations.</p>b<p>The number of candidate predictors was the total number of degrees of freedom (i.e., the sum of all candidate predictors, interactions, and dummy variables).</p>", "links"=>[], "tags"=>["included", "studies"], "article_id"=>305388, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t005", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Effective_sample_size_of_the_included_studies_reflecting_statistical_power_/305388", "title"=>"Effective sample size of the included studies (reflecting statistical power).", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:29:48"}
  • {"files"=>["https://ndownloader.figshare.com/files/634707"], "description"=>"<p><sup>a</sup>The hand search included only studies with an abstract, published in 2008 in <i>The New England Journal of Medicine</i>, <i>The Lancet</i>, <i>JAMA: the Journal of the American Medical Association</i>, <i>Annals of Internal Medicine</i>, <i>BMJ</i>, and <i>PLoS Medicine</i>. The following publication types were excluded beforehand: editorials, bibliographies, biographies, comments, dictionaries, directories, festschrifts, interviews, letters, news, and periodical indexes. <sup>b</sup>Studies, generally conducted in a yet healthy population, aimed at quantifying a causal relationship between a particular determinant or risk factor and an outcome, adjusting for other risk factors (i.e., confounders). <sup>c</sup>For example, see <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001221#pmed.1001221-Pletcher1\" target=\"_blank\">[72]</a>.</p>", "links"=>[], "tags"=>["included"], "article_id"=>305193, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.g001", "stats"=>{"downloads"=>1, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Flowchart_of_included_studies_/305193", "title"=>"Flowchart of included studies.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2012-05-22 01:26:33"}
  • {"files"=>["https://ndownloader.figshare.com/files/634871"], "description"=>"<p>Numbers are column percentages, with absolute numbers in parentheses. Impact and external validation studies (<i>n</i> = 6) were excluded from this table as these issues are not applicable for these type of studies. Hence, <i>n</i> = 65.</p>a<p>More than one method may be used within a study; percentages do not add up to 100%.</p>b<p>Percentage (number) of studies that reported the applied method for selecting which predictors were included in the multivariable analyses, if it was not based on statistical analysis (i.e., univariable predictor–outcome associations).</p>c<p>Predictor inclusion in multivariable model was pre-specified, as the specific aim was to quantify the added value of a new predictor to existing predictors.</p>d<p>For example, systolic and diasystolic blood pressure combined to mean blood pressure.</p>e<p>For the items below, two percentages are given. The first percentage includes all studies (i.e., 48 predictor finding studies, 17 model development studies, or 65 total); the second is the percentage of all studies that applied some type of predictor selection in the multivariable analysis (35 predictor finding studies, 11 model development studies, and 46 total; the excluded studies did not apply any predictor selection in the multivariable analysis but simply pre-specified the final model).</p>", "links"=>[], "tags"=>["predictor", "stratified", "was"], "article_id"=>305352, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t006", "stats"=>{"downloads"=>0, "page_views"=>12, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Method_of_predictor_selection_stratified_by_whether_prediction_was_the_primary_or_secondary_study_aim_/305352", "title"=>"Method of predictor selection, stratified by whether prediction was the primary or secondary study aim.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:29:12"}
  • {"files"=>["https://ndownloader.figshare.com/files/327886", "https://ndownloader.figshare.com/files/327929", "https://ndownloader.figshare.com/files/328009"], "description"=>"<div><h3>Background</h3><p>We investigated the reporting and methods of prediction studies, focusing on aims, designs, participant selection, outcomes, predictors, statistical power, statistical methods, and predictive performance measures.</p> <h3>Methods and Findings</h3><p>We used a full hand search to identify all prediction studies published in 2008 in six high impact general medical journals. We developed a comprehensive item list to systematically score conduct and reporting of the studies, based on recent recommendations for prediction research. Two reviewers independently scored the studies. We retrieved 71 papers for full text review: 51 were predictor finding studies, 14 were prediction model development studies, three addressed an external validation of a previously developed model, and three reported on a model's impact on participant outcome. Study design was unclear in 15% of studies, and a prospective cohort was used in most studies (60%). Descriptions of the participants and definitions of predictor and outcome were generally good. Despite many recommendations against doing so, continuous predictors were often dichotomized (32% of studies). The number of events per predictor as a measure of statistical power could not be determined in 67% of the studies; of the remainder, 53% had fewer than the commonly recommended value of ten events per predictor. <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001221#s2\">Methods</a> for a priori selection of candidate predictors were described in most studies (68%). A substantial number of studies relied on a <em>p</em>-value cut-off of <em>p</em><0.05 to select predictors in the multivariable analyses (29%). Predictive model performance measures, i.e., calibration and discrimination, were reported in 12% and 27% of studies, respectively.</p> <h3>Conclusions</h3><p>The majority of prediction studies in high impact journals do not follow current methodological recommendations, limiting their reliability and applicability.</p> <h3></h3><p> <em>Please see later in the article for the Editors' Summary</em></p> </div>", "links"=>[], "tags"=>["methods", "systematic"], "article_id"=>124725, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>["https://dx.doi.org/10.1371/journal.pmed.1001221.s001", "https://dx.doi.org/10.1371/journal.pmed.1001221.s002", "https://dx.doi.org/10.1371/journal.pmed.1001221.s003"], "stats"=>{"downloads"=>12, "page_views"=>19, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/Reporting_and_Methods_in_Clinical_Prediction_Research_A_Systematic_Review/124725", "title"=>"Reporting and Methods in Clinical Prediction Research: A Systematic Review", "pos_in_sequence"=>0, "defined_type"=>4, "published_date"=>"2012-05-22 01:18:45"}
  • {"files"=>["https://ndownloader.figshare.com/files/635053"], "description"=>"<p>Numbers are column percentages, with absolute numbers in parentheses.</p>a<p>Including studies from infectious diseases (<i>n</i> = 7), diabetes (<i>n</i> = 5), neonatology and child health (<i>n</i> = 6), mental disorders (e.g., dementia) (<i>n</i> = 4), and musculoskeletal disorders (e.g., lower back pain) (<i>n</i> = 4).</p>b<p>There were no external validation studies of a previously published model that also updated the model after poor validation.</p>", "links"=>[], "tags"=>["included", "multivariable", "subdivided"], "article_id"=>305539, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t001", "stats"=>{"downloads"=>1, "page_views"=>3, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Aim_of_the_included_multivariable_prediction_studies_subdivided_by_clinical_domains_/305539", "title"=>"Aim of the included multivariable prediction studies, subdivided by clinical domains.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:32:19"}
  • {"files"=>["https://ndownloader.figshare.com/files/635090"], "description"=>"<p>Numbers are column percentages, with absolute numbers in parentheses. The percentages sometimes do not add up to 100% because development studies commonly reported more than one performance measure or validity assessment.</p>a<p>Impact studies (<i>n</i> = 3) were excluded since all items were not applicable. Additionally, two external validation studies were excluded because they evaluated risk stratification tools that did not provide predicted probabilities (the Manchester triage system <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001221#pmed.1001221-VanVeen1\" target=\"_blank\">[74]</a> and predictive life support tools <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001221#pmed.1001221-Sasson1\" target=\"_blank\">[75]</a>). Hence, almost all items were not applicable. Hence, for this table total <i>n</i> = 66 studies.</p>b<p>The predictive performance (e.g., <i>C</i>-statistic, calibration, or net reclassification index) of the prediction model as estimated from the same data from which the model was developed.</p><p>AUC-ROC, area under the receiver operation characteristic curve; NRI, net reclassification index.</p>", "links"=>[], "tags"=>["stratified"], "article_id"=>305579, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t009", "stats"=>{"downloads"=>0, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Model_performance_measures_stratified_by_type_of_prediction_study_/305579", "title"=>"Model performance measures, stratified by type of prediction study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:32:59"}
  • {"files"=>["https://ndownloader.figshare.com/files/634941"], "description"=>"<p>Impact studies (<i>n</i> = 3) were excluded from this table as their aim is not to develop or validate a prediction model, but rather to quantify the effect or impact of using a prediction model on physicians' behaviour, patient outcome, or cost-effectiveness of care relative to not using the model or usual care. Hence, for this table total <i>n</i> = 68.</p>a<p>Not applicable for the three external validation studies. Hence, <i>n</i> = 65.</p>b<p>Not applicable in four studies, because one studied no continuous predictors, and the others were the three external validation studies. Hence, <i>n</i> = 64. Of these, handling was unclear in 19 studies, not described in two studies. The sum 43+12+30+21+2 is more than 43 because some studies handled continuous predictors in two ways (e.g., dichotomizing blood pressure and categorising body mass index into four categories).</p>", "links"=>[], "tags"=>["public health and epidemiology"], "article_id"=>305431, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t004", "stats"=>{"downloads"=>2, "page_views"=>7, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Reporting_of_candidate_predictors_/305431", "title"=>"Reporting of candidate predictors.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:30:31"}
  • {"files"=>["https://ndownloader.figshare.com/files/635126"], "description"=>"<p>Numbers are column percentages, with absolute numbers in parentheses. Impact and external validation studies (<i>n</i> = 6) were excluded from this table as these items were not applicable. Hence, total <i>n</i> = 65.</p>a<p>The percentages do not add up to 100%, because studies reported univariable and multivariable models. Further, all studies reporting the full model also reported the final model.</p>", "links"=>[], "tags"=>["stratified"], "article_id"=>305612, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t008", "stats"=>{"downloads"=>0, "page_views"=>1, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Presentation_of_the_results_stratified_by_type_of_prediction_study_/305612", "title"=>"Presentation of the results, stratified by type of prediction study.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:33:32"}
  • {"files"=>["https://ndownloader.figshare.com/files/634827"], "description"=>"<p>Numbers are column percentages, with absolute numbers in parentheses.</p>a<p>Some studies reported more than one item. Hence, percentages do not add up to 100%.</p>b<p>Cross-sectional studies were excluded for this item (item not applicable).</p>c<p>More than one method could be applied. Hence, the percentages do not add up to 100%. Items were not applicable for two primary-aim studies that had no missing values. Hence, total <i>n</i> = 69.</p>d<p>Only participants with completely observed data were analysed.</p>e<p>For example: in a diagnostic study <a href=\"http://www.plosmedicine.org/article/info:doi/10.1371/journal.pmed.1001221#pmed.1001221-Imperiale1\" target=\"_blank\">[73]</a>, the investigators assumed that among participants who did not undergo follow-up colonoscopy, the detection rates for any adenoma and for an advanced adenoma ranged from half to twice the rates among participants who did undergo follow-up colonoscopy.</p>", "links"=>[], "tags"=>["stratified", "was"], "article_id"=>305316, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t007", "stats"=>{"downloads"=>1, "page_views"=>10, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Handling_of_missing_values_stratified_by_whether_prediction_was_the_primary_or_secondary_study_aim_/305316", "title"=>"Handling of missing values, stratified by whether prediction was the primary or secondary study aim.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:28:36"}
  • {"files"=>["https://ndownloader.figshare.com/files/635014"], "description"=>"<p>Numbers are column percentages, with absolute numbers in parentheses, except for the column “Specifications”, which includes only absolute numbers.</p>a<p>Some cohort studies had a cross-sectional cohort design, which was possible because the predictor values did not change (gender, genes, etc.) or because the study involved a diagnostic prediction model study.</p>b<p>Of the 13 studies that used randomized trial data, 11 were predictor finding or model development studies. Of these 11 studies, five adjusted for the treatment effect, three did not adjust because there was no treatment effect, one did not adjust despite an effective treatment, and in two studies reporting and adjustment for treatment effects was entirely missing.</p>c<p>One study used two designs: a cross-sectional case-cohort and a cross-sectional nested case-control (here both scored as nested case-control).</p>", "links"=>[], "tags"=>["public health and epidemiology"], "article_id"=>305503, "categories"=>["Biotechnology"], "users"=>["Walter Bouwmeester", "Nicolaas P. A. Zuithoff", "Susan Mallett", "Mirjam I. Geerlings", "Yvonne Vergouwe", "Ewout W. Steyerberg", "Douglas G. Altman", "Karel G. M. Moons"], "doi"=>"https://dx.doi.org/10.1371/journal.pmed.1001221.t002", "stats"=>{"downloads"=>0, "page_views"=>6, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Study_design_in_relation_to_study_aim_/305503", "title"=>"Study design in relation to study aim.", "pos_in_sequence"=>0, "defined_type"=>3, "published_date"=>"2012-05-22 01:31:43"}

PMC Usage Stats | Further Information

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Relative Metric

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