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Quantile Effect on Duration of Response: A Zero-Inflated Censored Regression Approach.

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Bibliographic Details
Title: Quantile Effect on Duration of Response: A Zero-Inflated Censored Regression Approach.
Authors: Sun N; BeOne Medicines, Shanghai, China., Wang J; Bristol Myers Squibb, Boudry, Switzerland., Tiwari R; Global StatSolutions, Reston, Virginia, USA.
Source: Pharmaceutical statistics [Pharm Stat] 2025 Nov-Dec; Vol. 24 (6), pp. e70053.
Publication Type: Journal Article
Language: English
Journal Info: Publisher: Wiley Country of Publication: England NLM ID: 101201192 Publication Model: Print Cited Medium: Internet ISSN: 1539-1612 (Electronic) Linking ISSN: 15391604 NLM ISO Abbreviation: Pharm Stat Subsets: MEDLINE
Imprint Name(s): Original Publication: Chichester, UK : Wiley, c2002-
MeSH Terms: Randomized Controlled Trials as Topic*/methods , Randomized Controlled Trials as Topic*/statistics & numerical data , Models, Statistical*, Humans ; Regression Analysis ; Computer Simulation ; Time Factors ; Leukemia, Myeloid, Acute/drug therapy ; Treatment Outcome ; Data Interpretation, Statistical
Abstract: Duration of response (DOR) has been increasingly used as a useful measure of response to treatments in randomized clinical trials (RCT). Some estimands for DOR, such as the restricted mean DOR, although simple to use, may be sensitive to outliers and may not correctly measure treatment effects on the quantiles of DOR, such as the proportion of patients with DOR of at least 3 months. Quantile regression for survival data has been well developed. However, it is not directly applicable to DOR data in RCTs, due to the presence of non-responders for whom DOR is not defined. Although they can be treated as having zero DOR in a standard quantile regression, such an approach may not be flexible to model these subset of patients. To mitigate this issue, we propose an approach similar to the two-parts zero-inflated models, for example, for count data, so that the nonresponders are modeled as a part of the model, while DOR is modeled using quantile regression. A simulation study is conducted to examine the performance of the proposed approach. For illustration, we apply our approach to a simulated dataset of an acute myeloid leukemia trial, since the true dataset cannot be used due to confidentiality. The asymptotic properties of the proposed approach are also derived.
(© 2025 John Wiley & Sons Ltd.)
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Contributed Indexing: Keywords: duration of response; logistic regression; quantile regression; time to response; zero‐inflated models
Entry Date(s): Date Created: 20251118 Date Completed: 20251118 Latest Revision: 20251118
Update Code: 20251118
DOI: 10.1002/pst.70053
PMID: 41249872
Database: MEDLINE
Description
Abstract:Duration of response (DOR) has been increasingly used as a useful measure of response to treatments in randomized clinical trials (RCT). Some estimands for DOR, such as the restricted mean DOR, although simple to use, may be sensitive to outliers and may not correctly measure treatment effects on the quantiles of DOR, such as the proportion of patients with DOR of at least 3 months. Quantile regression for survival data has been well developed. However, it is not directly applicable to DOR data in RCTs, due to the presence of non-responders for whom DOR is not defined. Although they can be treated as having zero DOR in a standard quantile regression, such an approach may not be flexible to model these subset of patients. To mitigate this issue, we propose an approach similar to the two-parts zero-inflated models, for example, for count data, so that the nonresponders are modeled as a part of the model, while DOR is modeled using quantile regression. A simulation study is conducted to examine the performance of the proposed approach. For illustration, we apply our approach to a simulated dataset of an acute myeloid leukemia trial, since the true dataset cannot be used due to confidentiality. The asymptotic properties of the proposed approach are also derived.<br /> (© 2025 John Wiley & Sons Ltd.)
ISSN:1539-1612
DOI:10.1002/pst.70053