Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Mar-Apr;24(2):e2455.
doi: 10.1002/pst.2455. Epub 2024 Nov 17.

Subgroup Identification Based on Quantitative Objectives

Affiliations

Subgroup Identification Based on Quantitative Objectives

Yan Sun et al. Pharm Stat. 2025 Mar-Apr.

Abstract

Precision medicine is the future of drug development, and subgroup identification plays a critical role in achieving the goal. In this paper, we propose a powerful end-to-end solution squant (available on CRAN) that explores a sequence of quantitative objectives. The method converts the original study to an artificial 1:1 randomized trial, and features a flexible objective function, a stable signature with good interpretability, and an embedded false discovery rate (FDR) control. We demonstrate its performance through simulation and provide a real data example.

Keywords: biomarker; precision medicine; subgroup identification.

PubMed Disclaimer

References

    1. M. Reck , D. Rodríguez‐Abreu , A. G. Robinson , et al., “Pembrolizumab Versus Chemotherapy for PD‐L1‐Positive Non‐Small‐Cell Lung Cancer,” New England Journal of Medicine 375, no. 19 (2016): 1823–1833, https://doi.org/10.1056/NEJMoa1606774.
    1. M. Bonetti and R. D. Gelber , “Patterns of Treatment Effects in Subsets of Patients in Clinical Trials,” Biostatistics 5, no. 3 (2004): 465–481, https://doi.org/10.1093/biostatistics/5.3.465.
    1. W. Sauerbrei , P. Royston , and K. Zapien , “Detecting an Interaction Between Treatment and a Continuous Covariate: A Comparison of Two Approaches,” Computational Statistics & Data Analysis 51, no. 8 (2007): 4054–4063.
    1. E. O. Bayman , K. Chaloner , and M. K. Cowles , “Detecting Qualitative Interaction: A Bayesian Approach,” Statistics in Medicine 29, no. 4 (2010): 455–463, https://doi.org/10.1002/sim.3787.
    1. S. Sivaganesan , P. W. Laud , and P. Müller , “A Bayesian Subgroup Analysis With a Zero‐Enriched Polya Urn Scheme,” Statistics in Medicine 30, no. 4 (2011): 312–323, https://doi.org/10.1002/sim.4108.

MeSH terms

LinkOut - more resources