Controversial (Unresolved) Issues in Noninferiority Trials

2014 ◽  
pp. 97-114
Author(s):  
Brian Wiens
Keyword(s):  
Noninferiority Trials

A systematic review of noninferiority margins in oncology clinical trials

2021 ◽  
Vol 10 (6) ◽  
pp. 443-455
Author(s):  
Mahmoud Hashim ◽  
Talitha Vincken ◽  
Florint Kroi ◽  
Samron Gebregergish ◽  
Mike Spencer ◽  
...  
Keyword(s):  
Systematic Review ◽  
Clinical Trials ◽  
Absolute Rate ◽  
Time To Event ◽  
End Points ◽  
Patients With Cancer ◽  
Randomized Controlled ◽  
Noninferiority Trials ◽  
Oncology Clinical Trials ◽  
Noninferiority Margin

Aim: A systematic literature review was conducted to identify and characterize noninferiority margins for relevant end points in oncology clinical trials. Materials & methods: Randomized, controlled, noninferiority trials of patients with cancer were identified in PubMed and Embase. Results: Of 2284 publications identified, 285 oncology noninferiority clinical trials were analyzed. The median noninferiority margin was a hazard ratio of 1.29 (mean: 1.32; range: 1.05–2.05) for studies that reported time-to-event end points (n = 192). The median noninferiority margin was 13.0% (mean: 12.7%; range: 5.0–20.0%) for studies that reported response end points as absolute rate differences (n = 31). Conclusion: Although there was consistency in the noninferiority margins’ scale, variability was evident in noninferiority margins across trials. Increased transparency may improve consistency in noninferiority margin application in oncology clinical trials.

Noninferiority Trials

JAMA ◽  
2015 ◽  
Vol 313 (23) ◽  
pp. 2371 ◽  
Author(s):  
Amy H. Kaji ◽  
Roger J. Lewis
Keyword(s):  
Noninferiority Trials

scholarly journals Excess Deaths Associated With Tigecycline After Approval Based on Noninferiority Trials

2012 ◽  
Vol 54 (12) ◽  
pp. 1699-1709 ◽  
Author(s):  
P. Prasad ◽  
J. Sun ◽  
R. L. Danner ◽  
C. Natanson
Keyword(s):  
Noninferiority Trials ◽  
Excess Deaths

Assessing treatment efficacy in noninferiority trials

2003 ◽  
Vol 24 (2) ◽  
pp. 147-155 ◽  
Author(s):  
Sue-Jane Wang ◽  
H.M.James Hung
Keyword(s):  
Treatment Efficacy ◽  
Noninferiority Trials

Noninferiority trials with nonadherence to the assigned randomized treatment

2019 ◽  
Vol 16 (6) ◽  
pp. 673-681 ◽  
Author(s):  
Edward L Korn ◽  
Robert J Gray ◽  
Boris Freidlin
Keyword(s):  
Sensitivity Analysis ◽  
Sample Size ◽  
Risk Score ◽  
Standard Therapy ◽  
Error Probability ◽  
Experimental Therapy ◽  
Random Assignment ◽  
Type 1 Error ◽  
Noninferiority Trials

Background: Nonadherence to treatment assignment in a noninferiority randomized trial is especially problematic because it attenuates observed differences between the treatment arms, possibly leading one to conclude erroneously that a truly inferior experimental therapy is noninferior to a standard therapy (inflated type 1 error probability). The Lachin–Foulkes adjustment is an increase in the sample size to account for random nonadherence for the design of a superiority trial with a time-to-event outcome; it has not been explored in the noninferiority trial setting nor with nonrandom nonadherence. Noninferiority trials where patients have knowledge of a personal prognostic risk score may lead to nonrandom nonadherence, as patients with a relatively high risk may be more likely to not adhere to the random assignment to the (reduced) experimental therapy, and patients with a relatively low risk score may be more likely to not adhere to the random assignment to the (more aggressive) standard therapy. Methods: We investigated via simulations the properties of the Lachin–Foulkes adjustment in the noninferiority setting. We considered nonrandom in addition to random nonadherence to the treatment assignment. For nonrandom nonadherence, we used the scenario where a risk score, potentially associated with the between-arm treatment difference, influences patients’ nonadherence. A sensitivity analysis is proposed for addressing the nonrandom nonadherence for this scenario. The noninferiority TAILORx adjuvant breast cancer trial, where eligibility was based on a genomic risk score, is used as an example throughout. Results: The Lachin–Foulkes adjustment to the sample size improves the operating characteristics of noninferiority trials with random nonadherence. However, to maintain type 1 error probability, it is critical to adjust the noninferiorty margin as well as the sample size. With nonrandom nonadherence that is associated with a prognostic risk score, the type 1 error probability of the Lachin–Foulkes adjustment can be inflated (e.g. doubled) when the nonadherence is larger in the experimental arm than the standard arm. The proposed sensitivity analysis lessens the inflation in this situation. Conclusion: The Lachin–Foulkes adjustment to the sample size and noninferiority margin is a useful simple technique for attenuating the effects of random nonadherence in the noninferiority setting. With nonrandom nonadherence associated with a risk score known to the patients, the type 1 error probability can be inflated in certain situations. A proposed sensitivity analysis for these situations can attenuate the inflation.

Incorporating Patient Preferences in Noninferiority Trials

JAMA ◽  
2019 ◽  
Vol 322 (4) ◽  
pp. 305 ◽  
Author(s):  
Sergio A. Acuna ◽  
Tyler R. Chesney ◽  
Nancy N. Baxter
Keyword(s):  
Patient Preferences ◽  
Noninferiority Trials
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