Inverse probability weighting to estimate causal effect of a singular phase in a multiphase randomized clinical trial for multiple myeloma

Annalisa Pezzi, Michele Cavo, Annibale Biggeri, Elena Zamagni, Oriana Nanni

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Background: Randomization procedure in randomized controlled trials (RCTs) permits an unbiased estimation of causal effects. However, in clinical practice, differential compliance between arms may cause a strong violation of randomization balance and biased treatment effect among those who comply. We evaluated the effect of the consolidation phase on disease-free survival of patients with multiple myeloma in an RCT designed for another purpose, adjusting for potential selection bias due to different compliance to previous treatment phases. Methods: We computed two propensity scores (PS) to model two different selection processes: the first to undergo autologous stem cell transplantation, the second to begin consolidation therapy. Combined stabilized inverse probability treatment weights were then introduced in the Cox model to estimate the causal effect of consolidation therapy miming an ad hoc RCT protocol. Results: We found that the effect of consolidation therapy was restricted to the first 18 months of the phase (HR: 0.40, robust 95 % CI: 0.17-0.96), after which it disappeared. Conclusions: PS-based methods could be a complementary approach within an RCT context to evaluate the effect of the last phase of a complex therapeutic strategy, adjusting for potential selection bias caused by different compliance to the previous phases of the therapeutic scheme, in order to simulate an ad hoc randomization procedure.

Original languageEnglish
Pages (from-to)1-10
Number of pages10
JournalBMC Medical Research Methodology
Volume16
Issue number1
DOIs
Publication statusPublished - Nov 9 2016

Fingerprint

Multiple Myeloma
Randomized Controlled Trials
Random Allocation
Propensity Score
Selection Bias
Therapeutics
Stem Cell Transplantation
Clinical Protocols
Proportional Hazards Models
Compliance
Disease-Free Survival
Weights and Measures

Keywords

  • Causal effect
  • Compliance
  • Propensity score
  • RCT
  • Selection bias
  • Weighting sample

ASJC Scopus subject areas

  • Epidemiology
  • Health Informatics

Cite this

Inverse probability weighting to estimate causal effect of a singular phase in a multiphase randomized clinical trial for multiple myeloma. / Pezzi, Annalisa; Cavo, Michele; Biggeri, Annibale; Zamagni, Elena; Nanni, Oriana.

In: BMC Medical Research Methodology, Vol. 16, No. 1, 09.11.2016, p. 1-10.

Research output: Contribution to journalArticle

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