Adaptive Treatment Strategies with Survival Outcomes: An Application to the Treatment of Type 2 Diabetes using a Large Observational Database.
|アブストラクト||Sequences of treatments that adapt to a patient's changing condition over time are often needed for the management of chronic diseases. An adaptive treatment strategy (ATS) consists of personalized treatment rules to be applied through the course of a disease that input the patient's characteristics at the time of decision-making and output a recommended treatment. An optimal ATS is the sequence of tailored treatments that yields the best clinical outcome for patients sharing similar characteristics. Methods to estimate optimal adaptive treatment strategies, which must disentangle short- and long-term treatment e_ects, can be theoretically involved and hard to explain to clinicians, especially when the outcome to optimize is a survival time subject to right-censoring. In this paper, we describe dynamic weighted survival modeling, a method to estimate an optimal ATS with survival outcomes. We illustrate how it can answer an important clinical question about the treatment of type 2 diabetes using data from the Clinical Practice Research Datalink, a large primary care database. We identify an ATS about which drug add-ons to recommend when metformin in monotherapy does not achieve the therapeutic goals.|
|ジャーナル名||American journal of epidemiology|
|投稿者||Simoneau, Gabrielle; Moodie, Erica E M; Azoulay, Laurent; Platt, Robert W|
|組織名||Department of Epidemiology, Biostatistics and Occupational Health, McGill;University, Quebec, Canada.;Centre for Clinical Epidemiology, Lady Davis Institute, Jewish General Hospital,;Quebec, Canada.;Department of Oncology, McGill University, Quebec, Canada.;Department of Pediatrics, McGill University, Quebec, Canada.|