A scoping review on patient heterogeneity in economic evaluations of precision medicine based on basket trials

ABSTRACT

Introduction

Considerable challenges in the economic evaluation of precision medicines have been mentioned in previous studies. However, they have not addressed how an economic assessment would be conducted based on basket trials (novel studies for evaluation of precision medicine effects) in which the included populations have specific biomarkers and various cancers. Since basket trial populations have remarkable heterogeneity, this study aims to investigate the concept of heterogeneity and specific method(s) for considering it in economic evaluations through guidelines and studies that could be applicable in economic evaluation based on basket trials.

Area covered

We searched PubMed, Web of Science, Scopus, Google Scholar, and Google to find studies and pharmacoeconomics guidelines. The inclusion criteria included subjects of patient heterogeneity and suggested explicit method(s). Thirty-nine guidelines and 43 studies were included and evaluated. None of these materials mentioned disease types in a target population as a factor causing heterogeneity. Moreover, in economic evaluations, patient heterogeneity has been considered with four general approaches subgroup analysis, individual-based models, sensitivity analysis, and regression models.

Expert opinion

Type of disease is not considered a contributing factor in population heterogeneity, and the probable appropriate method for this issue could be individual-based models.

KEYWORDS:

• Basket trial
• cost-effectiveness
• economic evaluation
• patient heterogeneity
• personalized medicine
• precision medicine

Article highlights

• Investigation of the concept of patient heterogeneity in guidelines and studies revealed that demographic factors (e.g. age and gender) and clinical factors (such as the risk of developing a disease, its progression, or responding to treatment) were considered the main factors engendering heterogeneity.

• Four general approaches have been suggested for considering patient heterogeneity in economic evaluation in reviewed guidelines and studies: subgroup analysis (the most highly proposed method), individual-based models, sensitivity analysis, and regression models.

• Regarding the subject of this study, the type of disease is not listed as a contributing factor in population heterogeneity in economic evaluations. Therefore, it is strongly recommended that the type of disease be considered a contributing factor in population heterogeneity in economic evaluation guidelines.

• The general approach of precision medicine is selecting the treatment strategies based on the type of biomarkers or genetic features rather than the type of diseases. Therefore, the specific method(s) for calculating the cost effectiveness of studies of precision medicine interventions in the target population with a specific biomarker and various diseases must be considered.

Acknowledgments

This scoping review is a part of PhD thesis titled “economic evaluation based on basket trial” in the Department of Pharmacoeconomics and pharmaceutical administration, School of Pharmacy, Tehran University of Medical Sciences. It is an in-house, financially non-supported study. All authors have contributed to doing the study and preparing the article. All have read and approved the final version of the article. This research received no external funding, and the authors declare no conflict of interest. All the figures and tables are original and have not previously been published. The authors wish to thank Prof Dr Mohammad Abdollahi, who made a final English language edit of the article.

Declaration of interest

The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

Reviewer disclosures

Peer reviewers on this manuscript have no relevant financial or other relationships to disclose.

Author contributions

S Nikfar and M Nosrati contributed to study conception. Some major contribution to study design was provided by S Nikfar, M Nosrati and M Hasanzad. Data analysis was conducted by M Nosrati, and S Nikfar M Nosrati contributed to manuscript writing. S Nikfar and M Hasanzad provided valuable advice on manuscript and gave final approval of the version for publication. All authors agree for the final version of the manuscript to be published.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/14737167.2022.2108408

Additional information

Funding

This paper was not funded.