Evaluation of psychiatric interventions in an observational study: issues in design and analysis

Characteristics of randomized controlled clinical trials (RCTs) and observational studies of psychiatric intervention effectiveness are contrasted. Randomization drives treatment assignment in an RCT, whereas clinician and patient selection determine treatment in an observational study. Strengths and weaknesses of randomized and observational designs are considered. The propensity adjustment, a statistical approach that allows for intervention evaluation in a nonrandomized observational study, is described here. The plausibility of propensity adjustment assumptions must be carefully evaluated. This data analytic strategy is illustrated with the longitudinal observational data from the National Institute of Mental Health Collaborative Depression Study, Evaluations presented here examine acute and maintenance antidepressant effectiveness and demonstrate effectiveness of the higher categorical doses.

[1]  Donald Hedeker,et al.  Quintile stratification based on a misspecified propensity score in longitudinal treatment effectiveness analyses of ordinal doses , 2007, Comput. Stat. Data Anal..

[2]  F B Hu,et al.  Random-effects regression analysis of correlated grouped-time survival data , 2000, Statistical methods in medical research.

[3]  D. Hedeker,et al.  A comparison of mixed‐effects quantile stratification propensity adjustment strategies for longitudinal treatment effectiveness analyses of continuous outcomes , 2007, Statistics in medicine.

[4]  W. G. Cochran.  The effectiveness of adjustment by subclassification in removing bias in observational studies. , 1968, Biometrics.

[5]  R. Little.  Pattern-Mixture Models for Multivariate Incomplete Data , 1993 .

[6]  Ralph B D'Agostino,et al.  Estimating treatment effects using observational data. , 2007, JAMA.

[7]  D. Hedeker,et al.  Bias reduction in effectiveness analyses of longitudinal ordinal doses with a mixed‐effects propensity adjustment , 2007, Statistics in medicine.

[8]  D. Hedeker,et al.  Bias reduction with an adjustment for participants' intent to dropout of a randomized controlled clinical trial , 2007, Clinical trials.

[9]  M. Keller,et al.  Undertreatment of major depression. , 1988, Psychopharmacology bulletin.

[10]  D. Rubin.  The design versus the analysis of observational studies for causal effects: parallels with the design of randomized trials , 2007, Statistics in medicine.

[11]  John P. Rice,et al.  A 20-Year Longitudinal Observational Study of Somatic Antidepressant Treatment Effectiveness , 2003 .

[12]  T. Shakespeare,et al.  Observational Studies , 2003 .

[13]  A. Leon,et al.  Enhancing clinical trial design of interventions for posttraumatic stress disorder. , 2009, Journal of traumatic stress.

[14]  D. Rubin,et al.  The central role of the propensity score in observational studies for causal effects , 1983 .

[15]  A. Leon,et al.  Attrition in Randomized Controlled Clinical Trials: Methodological Issues in Psychopharmacology , 2006, Biological Psychiatry.

[16]  W. Brown,et al.  Symptom reduction and suicide risk in patients treated with placebo in antidepressant clinical trials: an analysis of the Food and Drug Administration database. , 2000, Archives of general psychiatry.

[17]  G. Klerman,et al.  Introduction: overview of the clinical studies program. , 1979, The American journal of psychiatry.

[18]  C. Drake.  Effects of misspecification of the propensity score on estimators of treatment effect , 1993 .

[19]  J M Lachin,et al.  Statistical considerations in the intent-to-treat principle. , 2000, Controlled clinical trials.

[20]  J. Ware,et al.  Random-effects models for longitudinal data. , 1982, Biometrics.

[21]  E. Robins,et al.  Research diagnostic criteria: rationale and reliability. , 1978, Archives of general psychiatry.

[22]  Donald Hedeker,et al.  A Mixed-eeects Quintile-stratiÿed Propensity Adjustment for Eeectiveness Analyses of Ordered Categorical Doses ‡ , 2022 .

[23]  N M Laird,et al.  Missing data in longitudinal studies. , 1988, Statistics in medicine.

[24]  G. Keitner,et al.  How many subjects with major depressive disorder meet eligibility requirements of an antidepressant efficacy trial? , 2003, The Journal of clinical psychiatry.

[25]  A. B. Hill,et al.  Principles of Medical Statistics , 1950, The Indian Medical Gazette.