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Updated: May 29, 2026

A Modified Surgical Technique for Kidney Transplantation in Mice
Published on: July 22, 2022
Designing a non-inferiority study in kidney transplantation: a case study
Steffen Witte1, Heinz Schmidli, Anthony O'Hagan
1Novartis Pharma AG, Basel, Switzerland. steffen.witte@novartis.com
Abstract:
In organ transplantation, placebo-controlled clinical trials are not possible for ethical reasons, and hence non-inferiority trials are used to evaluate new drugs. Patients with a transplanted kidney typically receive three to four immunosuppressant drugs to prevent organ rejection. In the described case of a non-inferiority trial for one of these immunosuppressants, the dose is changed, and another is replaced by an investigational drug. This test regimen is compared with the active control regimen. Justification for the non-inferiority margin is challenging as the putative placebo has never been studied in a clinical trial. We propose the use of a random-effect meta-regression, where each immunosuppressant component of the regimen enters as a covariate. This allows us to make inference on the difference between the putative placebo and the active control. From this, various methods can then be used to derive the non-inferiority margin. A hybrid of the 95/95 and synthesis approach is suggested. Data from 51 trials with a total of 17,002 patients were used in the meta-regression. Our approach was motivated by a recent large confirmatory trial in kidney transplantation. The results and the methodological documents of this evaluation were submitted to the Food and Drug Administration. The Food and Drug Administration accepted our proposed non-inferiority margin and our rationale.
Insights
Establishing ethical non-inferiority margins for immunosuppressant drugs in kidney transplantation is crucial. A novel meta-regression approach successfully derived an acceptable margin for a new investigational drug, ensuring patient safety and therapeutic equivalence.
Area of Science:
- Immunology
- Pharmacology
- Clinical Trials
Background:
- Placebo-controlled trials are ethically unfeasible for organ transplant immunosuppressants.
- Non-inferiority trials are standard for evaluating new immunosuppressive drugs in kidney transplant recipients.
- Determining appropriate non-inferiority margins is challenging due to the lack of placebo data for established regimens.
Purpose of the Study:
- To propose and validate a method for deriving non-inferiority margins in immunosuppressant drug trials.
- To address the ethical and methodological challenges in establishing margins when a true placebo has not been studied.
Main Methods:
- Utilized a random-effect meta-regression analysis incorporating individual immunosuppressant components as covariates.
- Inferred the difference between a hypothetical placebo and the active control regimen.
- Derived the non-inferiority margin using a hybrid approach combining 95/95 and synthesis methods, applied to data from 51 trials (17,002 patients).
Main Results:
- The proposed meta-regression approach successfully derived a non-inferiority margin.
- The methodology was motivated by a large kidney transplant trial and submitted to the Food and Drug Administration (FDA).
- The FDA accepted the proposed non-inferiority margin and the underlying rationale.
Conclusions:
- The developed meta-regression framework provides a robust method for establishing non-inferiority margins in ethically constrained clinical trial settings.
- This approach ensures rigorous evaluation of new immunosuppressants while maintaining patient safety in organ transplantation.
- The FDA's acceptance validates the method's utility and reliability for regulatory submissions.
Related Concept Videos
Kidney Transplant I: Introduction
Kidney Transplant II: Surgical Procedure
Kidney Transplant III: Nursing Management
Bioequivalence Experimental Study Designs: Repeated Measures, Cross-Over, Carry-Over, and Latin Square Designs
Study Designs in Epidemiology
Observational studies are those where the researcher does not intervene but rather observes natural variations. They include cross-sectional, cohort, and case-control studies.

