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Development and validation of a prediction model for the probability of responding to placebo in antidepressant trials: a pooled analysis of individual patient data
  1. Kiyomi Shinohara1,
  2. Shiro Tanaka2,
  3. Hissei Imai1,
  4. Hisashi Noma3,
  5. Kazushi Maruo4,
  6. Andrea Cipriani5,6,
  7. Shigeto Yamawaki7,
  8. Toshi A Furukawa1
  1. 1 Department of Health Promotion and Human Behavior and of Clinical Epidemiology, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto, Japan
  2. 2 Department of Clinical Biostatistics, Kyoto University Graduate School of Medicine, Kyoto, Japan
  3. 3 Department of Data Science, The Institute of Statistical Mathematics, Tokyo, Japan
  4. 4 Department of Biostatistics, Faculty of Medicine, University of Tsukuba, Tsukuba, Japan
  5. 5 Department of Psychiatry, University of Oxford, Oxford, UK
  6. 6 Oxford Health NHS Foundation Trust, Warneford Hospital, Oxford, UK
  7. 7 Academic-Industrial Cooperation Office, Hiroshima University, Hiroshima, Japan
  1. Correspondence to Dr Kiyomi Shinohara, Departments of Health Promotion and Human Behavior and of Clinical Epidemiology, Kyoto University Graduate School of Medicine/School of Public Health, Kyoto 606-8501, Japan; kiyomi.wb3{at}gmail.com

Abstract

Background Identifying potential placebo responders among apparent drug responders is critical to dissect drug-specific and nonspecific effects in depression.

Objective This project aimed to develop and test a prediction model for the probability of responding to placebo in antidepressant trials. Such a model will allow us to estimate the probability of placebo response among drug responders in antidepressants trials.

Methods We identified all placebo-controlled, double-blind randomised controlled trials (RCTs) of second generation antidepressants for major depressive disorder conducted in Japan and requested their individual patient data (IPD) to pharmaceutical companies. We obtained IPD (n=1493) from four phase II/III RCTs comparing mirtazapine, escitalopram, duloxetine, paroxetine and placebo. Out of 1493 participants in the four clinical trials, 440 participants allocated to placebo were included in the analyses. Our primary outcome was response, defined as 50% or greater reduction on Hamilton Rating Scale for Depression at study endpoint. We used multivariable logistic regression to develop a prediction model. All available candidate of predictor variables were tested through a backward variable selection and covariates were selected for the prediction model. The performance of the model was assessed by using Hosmer-Lemeshow test for calibration and the area under the ROC curve for discrimination.

Findings Placebo response rates differed between 31% and 59% (grand average: 43%) among four trials. Four variables were selected from all candidate variables and included in the final model: age at onset, age at baseline, bodily symptoms, and study-level difference. The final model performed satisfactorily in terms of calibration (Hosmer-Lemeshow p=0.92) and discrimination (the area under the ROC curve (AUC): 0.70).

Conclusions Our model is expected to help researchers discriminate individuals who are more likely to respond to placebo from those who are less likely so.

Clinical implications A larger sample and more precise individual participant information should be collected for better performance. Examination of external validity in independent datasets is warranted.

Trial registration number CRD42017055912.

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Footnotes

  • Contributors KS, ST, AC and TAF designed this study. KS, ST, HI, HN, KM, TAF and SY managed the data collection, and ST analysed the data. KS wrote the first draft of the manuscript under the supervision of ST, TAF and AC. All authors contributed to an have approved the final manuscript.

  • Funding This study was supported in part by a grant-in-aid from Japan Agency for Medical Research and Development (AMED) to SY (grant number 16dm0107093h0001: Strategic Research Program for Brain Sciences) and TAF (grant number 18dk0307072h0002). This study was also supported in part by the Project Promoting Clinical Trials for Development of New Drugs (18lk0201061t0003) from the AMED to ST.

  • Disclaimer These entities had no role in study design, data collection, data analysis, data interpretation or writing of the report. The views expressed are those of the authors and not necessarily those of the UK National Health Service, the NIHR, or the UK Department of Health.

  • Competing interests TAF has received lecture fees from Janssen, Meiji, Mitsubishi-Tanabe, MSD and Pfizer and research support from Mitsubishi-Tanabe; HN has received lecture fees from Boehringer Ingelheim and Kyowa Hakko Kirin, and research support from Kyowa Hakko Kirin and GSK. HI reports lecture fees from Mitsubishi-Tanabe, personal fees from Medical Science International publisher. ST has received lecture fees from Astra-Zeneca, Taiho and Ono. He has received consultation fees from DeNA Life Science and CanBus. He has received outsourcing fees from Satt and Asahi Kasei Pharma. His wife has been engaged in a research project of Bayer. AC is the Editor for BMJ Evidence-Based Medicine.

  • Patient consent Not required.

  • Provenance and peer review Not commissioned; internally peer reviewed.

  • Data sharing statement The individual participant data from phase II and III trials have been provided to us by respective pharmaceutical companies under the Non-disclosure Agreement.

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