Keith Humphreys1, Natalya C Maisel, Janet C Blodgett, John W Finney. 1. Center for Health Care Evaluation, Veterans Affairs (VA) Palo Alto Health Care System, Menlo Park, California, Department of Psychiatry & Behavioral Sciences, Stanford University School of Medicine, Stanford, California.
Abstract
OBJECTIVE: The purpose of this study was to determine whether randomized trials of treatments for substance dependence differ from those for other medical disorders on quality of enrollment information reporting and sample representativeness. METHOD: Twenty highly cited clinical trials (publication date 2002-2010) of treatments for each of 14 prevalent disorders were identified by structured literature search. The disorders were alcohol dependence, drug dependence, nicotine dependence, Alzheimer's disease, breast cancer, colorectal cancer, chronic obstructive pulmonary disease, depression, diabetes, HIV/AIDS, hypertension, ischemic heart disease, lung cancer, and schizophrenia. The 280 clinical trials were coded for number of individuals screened for eligibility, number of screened individuals meeting eligibility criteria, and number of eligible individuals refusing to participate. RESULTS: Substance-dependence treatment trials were significantly more likely to track and report enrollment information (75% vs. 45% of clinical trials for other disorders, p < .001). Substance-dependence trials did not differ from trials focused on other disorders on mean rate of non-enrollment. Across disorders, the primary driver of non-enrollment appeared to be clinical trial exclusion criteria rather than eligible patients refusing to enroll. CONCLUSIONS: Relative to other disorders, trials in the substance-dependence field do a better (although imperfect) job of tracking and reporting enrollment information. Low enrollment rates and unrepresentative samples are not challenges unique to treatment outcome studies in the substance-dependence field. Across a range of disorders, clinical trials that use eligibility criteria judiciously are more likely to produce findings that generalize to front-line clinical practice than are trials that restrict enrollment to a small and unrepresentative subset of patients.
OBJECTIVE: The purpose of this study was to determine whether randomized trials of treatments for substance dependence differ from those for other medical disorders on quality of enrollment information reporting and sample representativeness. METHOD: Twenty highly cited clinical trials (publication date 2002-2010) of treatments for each of 14 prevalent disorders were identified by structured literature search. The disorders were alcohol dependence, drug dependence, nicotine dependence, Alzheimer's disease, breast cancer, colorectal cancer, chronic obstructive pulmonary disease, depression, diabetes, HIV/AIDS, hypertension, ischemic heart disease, lung cancer, and schizophrenia. The 280 clinical trials were coded for number of individuals screened for eligibility, number of screened individuals meeting eligibility criteria, and number of eligible individuals refusing to participate. RESULTS: Substance-dependence treatment trials were significantly more likely to track and report enrollment information (75% vs. 45% of clinical trials for other disorders, p < .001). Substance-dependence trials did not differ from trials focused on other disorders on mean rate of non-enrollment. Across disorders, the primary driver of non-enrollment appeared to be clinical trial exclusion criteria rather than eligible patients refusing to enroll. CONCLUSIONS: Relative to other disorders, trials in the substance-dependence field do a better (although imperfect) job of tracking and reporting enrollment information. Low enrollment rates and unrepresentative samples are not challenges unique to treatment outcome studies in the substance-dependence field. Across a range of disorders, clinical trials that use eligibility criteria judiciously are more likely to produce findings that generalize to front-line clinical practice than are trials that restrict enrollment to a small and unrepresentative subset of patients.
Authors: Keith Humphreys; Natalya C Maisel; Janet C Blodgett; Ingrid L Fuh; John W Finney Journal: JAMA Intern Med Date: 2013-06-10 Impact factor: 21.873
Authors: Erin A McClure; Jacqueline S King; Aimee Wahle; Abigail G Matthews; Susan C Sonne; Michelle R Lofwall; Aimee L McRae-Clark; Udi E Ghitza; Melissa Martinez; Kasie Cloud; Harvir S Virk; Kevin M Gray Journal: Drug Alcohol Depend Date: 2017-05-10 Impact factor: 4.492