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Comparison of treatments with ordinal responses in trials with sequential monitoring and response-adaptive randomization.
Yu, Yian; Xu, Cong; Zhong, Junjiang; Cheung, Siu Hung.
Affiliation
  • Yu Y; Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China.
  • Xu C; Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China.
  • Zhong J; School of Mathematics and Statistics, Xiamen University of Technology, Xiamen, China.
  • Cheung SH; Department of Statistics, The Chinese University of Hong Kong, Hong Kong, China.
Stat Med ; 41(25): 5061-5083, 2022 11 10.
Article in En | MEDLINE | ID: mdl-35973712
In clinical trials, comparisons of treatments with ordinal responses are frequently conducted using the proportional odds model. However, the use of this model necessitates the adoption of the proportional odds assumption, which may not be appropriate. In particular, when responses are skewed, the use of the proportional odds model may result in a markedly inflated type I error rate. The latent Weibull distribution has recently been proposed to remedy this problem, and it has been demonstrated to be superior to the proportional odds model, especially when response-adaptive randomization is incorporated. However, there are several drawbacks associated with the latent Weibull model and the previously suggested response-adaptive treatment randomization scheme. In this paper, we propose the modified latent Weibull model to address these issues. Based on the modified latent Weibull model, the original response-adaptive design was also revised. In addition, the group sequential monitoring mechanism was included to enable interim analyses to be performed to determine, during a trial, whether a specific treatment is significantly more effective than another. If so, this will enable the trial to be terminated at a much earlier stage than a trial based on a fixed sample size. We performed a simulation study that clearly demonstrated the merits of our proposed framework. Furthermore, we redesigned a clinical study to further illustrate the advantages of our response-adaptive approach.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Research Design Type of study: Clinical_trials / Prognostic_studies Limits: Humans Language: En Journal: Stat Med Year: 2022 Document type: Article Affiliation country: China Country of publication: United kingdom

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Research Design Type of study: Clinical_trials / Prognostic_studies Limits: Humans Language: En Journal: Stat Med Year: 2022 Document type: Article Affiliation country: China Country of publication: United kingdom