Cancer Clinical Trials beyond Pandemic: Report of an American Statistical Association Biopharmaceutical Section Open Forum Discussion

Rajeshwari Sridhara, Elizabeth Barksdale, Olga Marchenko, Qi Jiang, Yuki Ando, Erick Bloomquist, Michael Coory, Melissa Crouse, Evgeny Degtyarev, Theodor Framke, Boris Freidlin, David E. Gerber, Thomas Gwise, Filip Josephson, Lorenzo Hess, Paul Kluetz, Daniel Li, Sumithra Mandrekar, Martin Posch, Khadija RantellBohdana Ratitch, Andrew Raven, Kit Roes, Kaspar Rufibach, Sinan B. Sarac, Richard Simon, Harpreet Singh, Marc Theoret, Andrew Thomson, Emmanuel Zuber, Yuan Li Shen, Richard Pazdur

Research output: Contribution to journalLetterpeer-review

Abstract

This article provides a summary of discussions from the American Statistical Association (ASA) Biopharmaceutical (BIOP) Section Open Forum organized by the ASA BIOP Statistical Methods in Oncology Scientific Working Group in coordination with the US FDA Oncology Center of Excellence and LUNGevity Foundation on January 14, 2021, and February 8, 2021. Diverse stakeholders including oncologists, patient advocates, experts from international regulatory agencies, academicians, and representatives of the pharmaceutical industry engaged in a discussion on how best to incorporate lessons learned during the COVID-19 pandemic into the design of future oncology trials. While recognizing that decentralized or hybrid cancer trials may increase variability associated with measurement error and potentially increase bias in treatment effect estimation, panel discussions highlighted the importance of flexibility for decreasing patient burden, which has the potential to increase access to and retention in cancer clinical trials and may broaden the representation of real-world patients in the trial setting.

Original languageEnglish (US)
JournalStatistics in Biopharmaceutical Research
DOIs
StateAccepted/In press - 2022

Keywords

  • COVID-19 pandemic
  • Decentralized trials
  • Oncology drug development
  • Telemedicine

ASJC Scopus subject areas

  • Statistics and Probability
  • Pharmaceutical Science

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