The precision interventions for severe and/or exacerbation-prone asthma (PrecISE) adaptive platform trial: statistical considerations

Anastasia Ivanova*, Elliot Israel, Lisa M. LaVange, Michael C. Peters, Loren C. Denlinger, Wendy C. Moore, Leonard B. Bacharier, M. Alison Marquis, Nathan M. Gotman, Michael R. Kosorok, Chalmer Tomlinson, David T. Mauger, Steve N. Georas, Rosalind J. Wright, Patricia Noel, Gary L. Rosner, Praveen Akuthota, Dean Billheimer, Eugene R. Bleecker, Juan Carlos CardetMario Castro, Emily A. DiMango, Serpil C. Erzurum, John V. Fahy, Merritt L. Fajt, Benjamin M. Gaston, Fernando Holguin, Sonia Jain, Nicholas J. Kenyon, Jerry A. Krishnan, Monica Kraft, Rajesh Kumar, Mark C. Liu, Ngoc P. Ly, James N. Moy, Wanda Phipatanakul, Kristie Ross, Lewis J. Smith, Stanley J. Szefler, W. Gerald Teague, Michael E. Wechsler, Sally E. Wenzel, Steven R. White

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

The Precision Interventions for Severe and/or Exacerbation-prone Asthma (PrecISE) study is an adaptive platform trial designed to investigate novel interventions to severe asthma. The study is conducted under a master protocol and utilizes a crossover design with each participant receiving up to five interventions and at least one placebo. Treatment assignments are based on the patients’ biomarker profiles and precision health methods are incorporated into the interim and final analyses. We describe key elements of the PrecISE study including the multistage adaptive enrichment strategy, early stopping of an intervention for futility, power calculations, and the primary analysis strategy.

Original languageEnglish (US)
Pages (from-to)1026-1037
Number of pages12
JournalJournal of Biopharmaceutical Statistics
Volume30
Issue number6
DOIs
StatePublished - 2020
Externally publishedYes

Keywords

  • Master protocol
  • adaptive enrichment
  • compex
  • covariate adaptive randomization
  • platform trial
  • severe asthma

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmacology
  • Pharmacology (medical)

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