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Simple methods for the estimation and sensitivity analysis of principal strata effects using marginal structural models: Application to a bone fracture prevention trial
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- Yukari Uemura
- Biostatistics Section Department of Data Science Center for Clinical Sciences National Center for Global Health and Medicine Shinjyuku‐ku Tokyo Japan
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- Masataka Taguri
- Department of Science Yokohama City University School of Data Science Kanazawa‐ku Yokohama Japan
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- Takuya Kawahara
- Biostatistics Division Clinical Research Support Center The University of Tokyo Hospital Bunkyo‐ku Tokyo Japan
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- Yasutaka Chiba
- Clinical Research Center Kindai University Hospital Osakasayama Osaka Japan
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Description
<jats:title>Abstract</jats:title><jats:p>In randomized clinical trials, it is often of interest to estimate the effect of treatment on quality of life (QOL), in addition to those on the event itself. When an event occurs in some patients prior to QOL score assessment, investigators may compare QOL scores between patient subgroups defined by the event after randomization. However, owing to postrandomization selection bias, this analysis can mislead investigators about treatment efficacy and result in paradoxical findings. The recent Japanese Osteoporosis Intervention Trial (JOINT‐02), which compared the benefits of a combination therapy for fracture prevention with those of a monotherapy, exemplifies the case in point; the average QOL score was higher in the combination therapy arm for the unfractured subgroup but was lower for the fractured subgroup. To address this issue, principal strata effects (PSEs), which are treatment effects estimated within subgroups of individuals stratified by potential intermediate variable, have been discussed in the literature. In this paper, we describe a simple procedure for estimating the PSEs using marginal structural models. This procedure utilizes SAS code for the estimation. In addition, we present a simple sensitivity analysis method for examining the resulting estimates. The analyses of JOINT‐02 data using these methods revealed that QOL scores were higher in the combination therapy arm than in the monotherapy arm for both subgroups.</jats:p>
Journal
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- Biometrical Journal
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Biometrical Journal 61 (6), 1448-1461, 2019-07-17
Wiley