Heterogeneity of the baseline risk within patient populations of clinical trials: a proposed evaluation algorithm Export

@article{9850135, abstract = {In this paper, the authors present an evaluation algorithm for systematic assessment of the observed heterogeneity in disease risk within trial populations. Predictive models are used to estimate the predicted patient hazards, the odds of having an event in the upper risk quartile (ODU) and the lower risk quartile (ODL), and the odds ratio (rate ratio for time-to-event analyses) for having an event in the upper risk quartile versus the lower risk quartile (extreme quartile odds ratio (EQuOR) and extreme quartile rate ratio (EQuRR)). The ranges for these metrics depend on the extent to which predictors of the outcome of interest exist and are known and the extent to which data are collected in the trial, as well as on the eligibility criteria and the specific patients who are actually enrolled. ODU, ODL, and EQuOR values are used to systematically interpret the results for patients at different levels of risk, to evaluate generalizability, and to determine the need for subgroup analyses. Individual data for five outcomes from three trials (n = 842, 913, and 1,001, respectively) are used as examples. Observed EQuOR values ranged from 1.5 (very little predicted heterogeneity) to 59 (large heterogeneity). EQuRR values ranged from 2 to 46. ODU values ranged from 0.24 to 3.19 (generally high risk), and ODL values ranged from 0.01 (clinically negligible risk) to 0.16 (clinically meaningful risk). The algorithm may also be used for comparing diverse trials (e.g., in meta-analyses) and used prospectively for designing future trials, as shown in simulations.}, address = {HIV Research Branch, Therapeutics Research Program, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA.}, author = {Ioannidis, J. P. and Lau, J.}, citeulike-article-id = {4415770}, citeulike-linkout-0 = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=9850135%20}, comment = {0002-9262 (Print) Journal Article}, day = {1}, journal = {Am J Epidemiol}, keywords = {acquired, agentsadministration, aids-related, algorithms, analysis, anti-hiv, bias, combinationadministration, comparative, controlled, dapsoneadministration, data, design, dosage, epidemiology, failure, file-import-09-04-28, humans, immunodeficiency, infectionsdrug, meta-analysis, models, numerical, odds, opportunistic, pentamidineadministration, pneumocystisdrug, pneumonia, randomized, ratio, research, risk, statistical, study, survival, syndromedrug, therapymortality, treatment, trialsstatistics, trimethoprim-sulfamethoxazole}, month = {December}, number = {11}, pages = {1117--26}, posted-at = {2009-04-28 16:00:50}, priority = {2}, title = {Heterogeneity of the baseline risk within patient populations of clinical trials: a proposed evaluation algorithm}, url = {http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=9850135%20}, volume = {148}, year = {1998} }

TY - JOUR ID - 9850135 L3 - citeulike-article-id:4415770 N2 - In this paper, the authors present an evaluation algorithm for systematic assessment of the observed heterogeneity in disease risk within trial populations. Predictive models are used to estimate the predicted patient hazards, the odds of having an event in the upper risk quartile (ODU) and the lower risk quartile (ODL), and the odds ratio (rate ratio for time-to-event analyses) for having an event in the upper risk quartile versus the lower risk quartile (extreme quartile odds ratio (EQuOR) and extreme quartile rate ratio (EQuRR)). The ranges for these metrics depend on the extent to which predictors of the outcome of interest exist and are known and the extent to which data are collected in the trial, as well as on the eligibility criteria and the specific patients who are actually enrolled. ODU, ODL, and EQuOR values are used to systematically interpret the results for patients at different levels of risk, to evaluate generalizability, and to determine the need for subgroup analyses. Individual data for five outcomes from three trials (n = 842, 913, and 1,001, respectively) are used as examples. Observed EQuOR values ranged from 1.5 (very little predicted heterogeneity) to 59 (large heterogeneity). EQuRR values ranged from 2 to 46. ODU values ranged from 0.24 to 3.19 (generally high risk), and ODL values ranged from 0.01 (clinically negligible risk) to 0.16 (clinically meaningful risk). The algorithm may also be used for comparing diverse trials (e.g., in meta-analyses) and used prospectively for designing future trials, as shown in simulations. IS - 11 JF - Am J Epidemiol AD - HIV Research Branch, Therapeutics Research Program, National Institute of Allergy and Infectious Diseases, Bethesda, MD 20892, USA. EP - 26 TI - Heterogeneity of the baseline risk within patient populations of clinical trials: a proposed evaluation algorithm VL - 148 SP - 1117 KW - acquired KW - agentsadministration KW - aids-related KW - algorithms KW - analysis KW - anti-hiv KW - bias KW - combinationadministration KW - comparative KW - controlled KW - dapsoneadministration KW - data KW - design KW - dosage KW - epidemiology KW - failure KW - file-import-09-04-28 KW - humans KW - immunodeficiency KW - infectionsdrug KW - meta-analysis KW - models KW - numerical KW - odds KW - opportunistic KW - pentamidineadministration KW - pneumocystisdrug KW - pneumonia KW - randomized KW - ratio KW - research KW - risk KW - statistical KW - study KW - survival KW - syndromedrug KW - therapymortality KW - treatment KW - trialsstatistics KW - trimethoprim-sulfamethoxazole N1 - 0002-9262 (Print) Journal Article AU - Ioannidis, JP AU - Lau, J PY - 1998/12/01/ UR - http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&dopt=Citation&list_uids=9850135%20 ER -