Literature DB >> 34117032

Subgroup Analyses in Oncology Trials: Regulatory Considerations and Case Examples.

Anup K Amatya1, Mallorie H Fiero2, Erik W Bloomquist2, Arup K Sinha2, Steven J Lemery3,4, Harpreet Singh3,4, Amna Ibrahim3,4, Martha Donoghue3,4, Lola A Fashoyin-Aje3,4, R Angelo de Claro3,4, Nicole J Gormley3,4, Laleh Amiri-Kordestani3,4, Rajeshwari Sridhara4, Marc R Theoret3,4, Paul G Kluetz3,4, Richard Pazdur3,4, Julia A Beaver3,4, Shenghui Tang2.   

Abstract

Subgroup analyses are assessments of treatment effects based on certain patient characteristics out of the total study population and are important for interpretation of pivotal oncology trials. However, appropriate use of subgroup analyses results for regulatory decision-making and product labeling is challenging. Typically, drugs approved by the FDA are indicated for use in the total patient population studied; however, there are examples of restriction to a subgroup of patients despite positive study results in the entire study population and also extension of an indication to the entire study population despite positive results appearing primarily in one or more subgroups. In this article, we summarize key issues related to subgroup analyses in the benefit-risk assessment of cancer drugs and provide case examples to illustrate approaches that the FDA Oncology Center of Excellence has taken when considering the appropriate patient population for cancer drug approval. In general, if a subgroup is of interest, the subgroup analysis should be hypothesis-driven and have adequate sample size to demonstrate evidence of a treatment effect. In addition to statistical efficacy considerations, the decision on what subgroups to include in labeling relies on the pathophysiology of the disease, mechanistic justification, safety data, and external information available. The oncology drug review takes the totality of the data into consideration during the decision-making process to ensure the indication granted and product labeling appropriately reflect the scientific evidence to support patient population for whom the drug is safe and effective. ©2021 American Association for Cancer Research.

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Year:  2021        PMID: 34117032      PMCID: PMC8563387          DOI: 10.1158/1078-0432.CCR-20-4912

Source DB:  PubMed          Journal:  Clin Cancer Res        ISSN: 1078-0432            Impact factor:   13.801


  9 in total

Review 1.  General guidance on exploratory and confirmatory subgroup analysis in late-stage clinical trials.

Authors:  Alex Dmitrienko; Christoph Muysers; Arno Fritsch; Ilya Lipkovich
Journal:  J Biopharm Stat       Date:  2016       Impact factor: 1.051

2.  Bayesian models for subgroup analysis in clinical trials.

Authors:  Hayley E Jones; David I Ohlssen; Beat Neuenschwander; Amy Racine; Michael Branson
Journal:  Clin Trials       Date:  2011-01-31       Impact factor: 2.486

3.  Subgroup analysis and interpretation for phase 3 confirmatory trials: White paper of the EFSPI/PSI working group on subgroup analysis.

Authors:  Aaron Dane; Amy Spencer; Gerd Rosenkranz; Ilya Lipkovich; Tom Parke
Journal:  Pharm Stat       Date:  2018-12-27       Impact factor: 1.894

4.  FDA Approval Summary: Atezolizumab Plus Paclitaxel Protein-bound for the Treatment of Patients with Advanced or Metastatic TNBC Whose Tumors Express PD-L1.

Authors:  Preeti Narayan; Sakar Wahby; Jennifer J Gao; Laleh Amiri-Kordestani; Amna Ibrahim; Erik Bloomquist; Shenghui Tang; Yuan Xu; Jiang Liu; Wentao Fu; Pengfei Song; Bellinda L King-Kallimanis; Sherry Hou; Yutao Gong; Shyam Kalavar; Soma Ghosh; Reena Philip; Kirsten B Goldberg; Marc R Theoret; Gideon M Blumenthal; Paul G Kluetz; Rajeshwari Sridhara; Richard Pazdur; Julia A Beaver
Journal:  Clin Cancer Res       Date:  2020-01-30       Impact factor: 12.531

5.  Tutorial on statistical considerations on subgroup analysis in confirmatory clinical trials.

Authors:  Mohamed Alosh; Mohammad F Huque; Frank Bretz; Ralph B D'Agostino
Journal:  Stat Med       Date:  2016-11-28       Impact factor: 2.373

6.  FDA Approval Summary: Eribulin for Patients with Unresectable or Metastatic Liposarcoma Who Have Received a Prior Anthracycline-Containing Regimen.

Authors:  Christy L Osgood; Meredith K Chuk; Marc R Theoret; Lan Huang; Kun He; Leah Her; Patricia Keegan; Richard Pazdur
Journal:  Clin Cancer Res       Date:  2017-02-27       Impact factor: 12.531

7.  PARP inhibitors in ovarian cancer.

Authors:  J A Ledermann
Journal:  Ann Oncol       Date:  2016-04       Impact factor: 32.976

8.  FDA Approval Summary: Nivolumab for the Treatment of Metastatic Non-Small Cell Lung Cancer With Progression On or After Platinum-Based Chemotherapy.

Authors:  Dickran Kazandjian; Daniel L Suzman; Gideon Blumenthal; Sirisha Mushti; Kun He; Meredith Libeg; Patricia Keegan; Richard Pazdur
Journal:  Oncologist       Date:  2016-03-16

9.  FDA Approval Summary: Olaparib Monotherapy or in Combination with Bevacizumab for the Maintenance Treatment of Patients with Advanced Ovarian Cancer.

Authors:  Shaily Arora; Sanjeeve Balasubramaniam; Hui Zhang; Tara Berman; Preeti Narayan; Daniel Suzman; Erik Bloomquist; Shenghui Tang; Yutao Gong; Rajeshwari Sridhara; Francisca Reyes Turcu; Deb Chatterjee; Banu Saritas-Yildirim; Soma Ghosh; Reena Philip; Anand Pathak; Jennifer J Gao; Laleh Amiri-Kordestani; Richard Pazdur; Julia A Beaver
Journal:  Oncologist       Date:  2020-10-20
  9 in total
  4 in total

Review 1.  Clinical Benefit Scales and Trial Design: Some Statistical Issues.

Authors:  Edward L Korn; Carmen J Allegra; Boris Freidlin
Journal:  J Natl Cancer Inst       Date:  2022-09-09       Impact factor: 11.816

2.  Significant Improvement of Prognosis After the Advent of Immune Checkpoint Inhibitors in Patients with Advanced, Unresectable, or Metastatic Urothelial Carcinoma: A Propensity Score Matching and Inverse Probability of Treatment Weighting Analysis on Real-World Data.

Authors:  Makito Miyake; Nobutaka Nishimura; Takuto Shimizu; Mikiko Ohnishi; Masaomi Kuwada; Yoshitaka Itami; Takeshi Inoue; Kenta Ohnishi; Yoshihiro Matsumoto; Takanori Yoshida; Yoshihiro Tatsumi; Masatake Shinohara; Shunta Hori; Yosuke Morizawa; Daisuke Gotoh; Yasushi Nakai; Satoshi Anai; Kazumasa Torimoto; Katsuya Aoki; Tomomi Fujii; Nobumichi Tanaka; Kiyohide Fujimoto
Journal:  Cancer Manag Res       Date:  2022-02-16       Impact factor: 3.989

3.  KMSubtraction: reconstruction of unreported subgroup survival data utilizing published Kaplan-Meier survival curves.

Authors:  Joseph J Zhao; Nicholas L Syn; Benjamin Kye Jyn Tan; Dominic Wei Ting Yap; Chong Boon Teo; Yiong Huak Chan; Raghav Sundar
Journal:  BMC Med Res Methodol       Date:  2022-04-03       Impact factor: 4.615

4.  Efficacy of acupuncture in subpopulations with functional constipation: A protocol for a systematic review and individual patient data meta-analysis.

Authors:  Chao Chen; Jia Liu; Baoyan Liu; Xue Cao; Zhishun Liu; Tianyi Zhao; Xiaoying Lv; Shengnan Guo; Yang Li; Liyun He; Yanke Ai
Journal:  PLoS One       Date:  2022-04-12       Impact factor: 3.240

  4 in total

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