RESUMEN
OBJECTIVE: To emulate three target trials: single treatment vs. no treatment, joint treatment vs. no treatment, and head-to-head comparison of two treatments, we explain how to estimate the observational analogs of intention-to-treat and per-protocol effects, using hazard ratios and survival curves. For per-protocol effects, we describe two methods for adherence adjustment via inverse-probability weighting. STUDY DESIGN AND SETTING: Prospective observational study using electronic medical records of individuals aged 55-84 with coronary heart disease from >500 practices in the United Kingdom between 2000 and 2010. RESULTS: The intention-to-treat mortality hazard ratio (95% confidence interval) was 0.90 (0.84, 0.97) for statins vs. no treatment, 0.88 (0.73, 1.06) for statins plus antihypertensives vs. no treatment, and 0.91 (0.77, 1.06) for atorvastatin vs. simvastatin. When censoring nonadherent person-times, the per-protocol mortality hazard ratio was 0.74 (0.64, 0.85) for statins vs. no treatment, 0.55 (0.35, 0.87) for statins plus antihypertensives vs. no treatment, and 1.13 (0.88, 1.45) for atorvastatin vs. simvastatin. We estimated per-protocol hazard ratios for a 5-year treatment using different dose-response marginal structural models and standardized survival curves for each target trial using intention-to-treat and per-protocol analyses. CONCLUSION: When randomized trials are not available or feasible, observational analyses can emulate a variety of target trials.
Asunto(s)
Antihipertensivos/uso terapéutico , Enfermedad Coronaria/tratamiento farmacológico , Inhibidores de Hidroximetilglutaril-CoA Reductasas/uso terapéutico , Anciano , Anciano de 80 o más Años , Enfermedad Coronaria/mortalidad , Registros Electrónicos de Salud , Femenino , Humanos , Análisis de Intención de Tratar , Masculino , Persona de Mediana Edad , Cooperación del Paciente/estadística & datos numéricos , Estudios Prospectivos , Análisis de Supervivencia , Resultado del Tratamiento , Reino UnidoRESUMEN
This article reviews methods for comparative effectiveness research using observational data. The basic idea is using an observational study to emulate a hypothetical randomised trial by comparing initiators versus non-initiators of treatment. After adjustment for measured baseline confounders, one can then conduct the observational analogue of an intention-to-treat analysis. We also explain two approaches to conduct the analogues of per-protocol and as-treated analyses after further adjusting for measured time-varying confounding and selection bias using inverse-probability weighting. As an example, we implemented these methods to estimate the effect of statins for primary prevention of coronary heart disease (CHD) using data from electronic medical records in the UK. Despite strong confounding by indication, our approach detected a potential benefit of statin therapy. The analogue of the intention-to-treat hazard ratio (HR) of CHD was 0.89 (0.73, 1.09) for statin initiators versus non-initiators. The HR of CHD was 0.84 (0.54, 1.30) in the per-protocol analysis and 0.79 (0.41, 1.41) in the as-treated analysis for 2 years of use versus no use. In contrast, a conventional comparison of current users versus never users of statin therapy resulted in a HR of 1.31 (1.04, 1.66). We provide a flexible and annotated SAS program to implement the proposed analyses.