Literature DB >> 35028720

Clinical and pharmacoeconomic impact of subgroup analysis in onco-hematological patients.

Manuel David Gil-Sierra1,2, Maria Del Pilar Briceño-Casado3, Marina Sánchez-Hidalgo4.   

Abstract

Subgroup analysis evaluates a health intervention in subpopulations according to a characteristic or factor. It can be useful for generating new hypotheses or conducting new studies. However, subgroup analysis presents several limitations and it should be considered cautiously. The development of new onco-hematological drugs is accelerating in recent years and the impact of subgroup analysis on clinical decision-making is increasing. The interpretation of subgroup analyses can be controversial in some cases, negatively affecting patients and healthcare systems. This work is a review of the clinical and pharmacoeconomic impact of subgroup analysis in onco-hematological patients. The study describes some illustrative examples of inadequate interpretations about subset analysis: combination of pembrolizumab plus chemotherapy in lung cancer, inhibitors of cyclin-dependent kinases in breast cancer, daratumumab-based regimens in newly diagnosed multiple myeloma, combination of nivolumab with ipilimumab in melanoma and docetaxel in prostate cancer. Subgroup analysis can have a significant impact on the data selection for the development of studies; efficacy, safety, and convenience of treatments in onco-hematological patients; efficiency of therapies in health systems; and therapeutic positioning of antineoplastic drugs. There is a strong need to establish homogeneous criteria for the assessment of subgroup analysis and to develop new tools for its consideration.
© 2022. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Drug evaluation studies; Evidence-based medicine; Hematology; Oncology; Subgroup analysis; medical

Mesh:

Substances:

Year:  2022        PMID: 35028720     DOI: 10.1007/s00520-022-06823-y

Source DB:  PubMed          Journal:  Support Care Cancer        ISSN: 0941-4355            Impact factor:   3.359


  35 in total

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Authors:  Helen Barraclough; Ramaswamy Govindan
Journal:  J Thorac Oncol       Date:  2010-05       Impact factor: 15.609

2.  Statistics in medicine--reporting of subgroup analyses in clinical trials.

Authors:  Rui Wang; Stephen W Lagakos; James H Ware; David J Hunter; Jeffrey M Drazen
Journal:  N Engl J Med       Date:  2007-11-22       Impact factor: 91.245

3.  Evaluation of Evidence of Statistical Support and Corroboration of Subgroup Claims in Randomized Clinical Trials.

Authors:  Joshua D Wallach; Patrick G Sullivan; John F Trepanowski; Kristin L Sainani; Ewout W Steyerberg; John P A Ioannidis
Journal:  JAMA Intern Med       Date:  2017-04-01       Impact factor: 21.873

4.  Interaction 3: How to examine heterogeneity.

Authors:  J N Matthews; D G Altman
Journal:  BMJ       Date:  1996-10-05

Review 5.  What's wrong with Bonferroni adjustments.

Authors:  T V Perneger
Journal:  BMJ       Date:  1998-04-18

6.  How to use a subgroup analysis: users' guide to the medical literature.

Authors:  Xin Sun; John P A Ioannidis; Thomas Agoritsas; Ana C Alba; Gordon Guyatt
Journal:  JAMA       Date:  2014 Jan 22-29       Impact factor: 56.272

7.  Subgroup Analyses in Reporting of Phase III Clinical Trials in Solid Tumors.

Authors:  Sheng Zhang; Fei Liang; Wenfeng Li; Xichun Hu
Journal:  J Clin Oncol       Date:  2015-04-20       Impact factor: 44.544

8.  Checklist for clinical applicability of subgroup analysis.

Authors:  Manuel David Gil-Sierra; Silvia Fénix-Caballero; Laila Abdel Kader-Martin; Maria Dolores Fraga-Fuentes; Marina Sánchez-Hidalgo; Catalina Alarcón de la Lastra-Romero; Emilio Jesús Alegre-Del Rey
Journal:  J Clin Pharm Ther       Date:  2019-12-18       Impact factor: 2.512

9.  Clinical Decision-making About Neoadjuvant Nivolumab Plus Ipilimumab.

Authors:  Manuel David Gil-Sierra; Marina Sánchez-Hidalgo; Catalina Alarcón de la Lastra-Romero
Journal:  JAMA Oncol       Date:  2021-02-01       Impact factor: 31.777

10.  Subgroup analyses of randomized clinical trials in heart failure: facts and numbers.

Authors:  Andrija Vidic; John T Chibnall; Niharika Goparaju; Paul J Hauptman
Journal:  ESC Heart Fail       Date:  2016-06-22
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