دورية أكاديمية
أعرض في EDS

Group sequential design with maximin efficiency robust test for immunotherapy with generalized delayed treatment effect.

التفاصيل البيبلوغرافية
العنوان: Group sequential design with maximin efficiency robust test for immunotherapy with generalized delayed treatment effect.
المؤلفون: Li B; Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China., Zhang J; Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China., Yang W; Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China., Su L; Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China., Yan F; Research Center of Biostatistics and Computational Pharmacy, China Pharmaceutical University, Nanjing, China.
المصدر: Pharmaceutical statistics [Pharm Stat] 2024 Jan-Feb; Vol. 23 (1), pp. 107-133. Date of Electronic Publication: 2023 Oct 19.
نوع المنشور: Clinical Trial; Journal Article; Research Support, Non-U.S. Gov't
اللغة: English
بيانات الدورية: Publisher: Wiley Country of Publication: England NLM ID: 101201192 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1539-1612 (Electronic) Linking ISSN: 15391604 NLM ISO Abbreviation: Pharm Stat Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Chichester, UK : Wiley, c2002-
مواضيع طبية MeSH: Immunotherapy*/methods , Treatment Delay*, Humans ; Computer Simulation ; Research Design ; Sample Size
مستخلص: The delayed treatment effect is a common feature of immunotherapy, characterized by a gradual onset of action ranging from no effect to full effect. In this study, we propose a generalized delayed treatment effect function to depict the delayed effective process precisely and flexibly. To reduce potential power loss caused by the delayed treatment effect in a group sequential trial, we employ the maximin efficiency robust test, which enhances power robustness across a range of possible delays. We present novel approaches based on the Markov chain method for determining group sequential boundaries, calculating the power function, and estimating the maximum sample size through iterative regressions between the square root of the maximum sample size and the normal quantile of power. Extensive simulation studies validate the effectiveness of our approaches, particularly in balanced trials, demonstrating the validity of group sequential boundaries and the accuracy of maximum sample size estimations. Additionally, we utilize a real trial as an example to compare our considered trial with group sequential trials using the log-rank and generalized piecewise weighted log-rank tests. The results show significantly reduced maximum sample sizes, highlighting the economic advantage of our approach.
(© 2023 John Wiley & Sons Ltd.)
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معلومات مُعتمدة: 81973145 National Natural Science Foundation of China; 82273735 National Natural Science Foundation of China; 82304252 National Natural Science Foundation of China
فهرسة مساهمة: Keywords: general lag model; group sequential boundaries; maximum sample size; statistical power; type 1 error rate
تواريخ الأحداث: Date Created: 20231020 Date Completed: 20240205 Latest Revision: 20240509
رمز التحديث: 20240510
DOI: 10.1002/pst.2341
PMID: 37859531
قاعدة البيانات: MEDLINE
الوصف
تدمد:1539-1612
DOI:10.1002/pst.2341