Historically, the term 'co-primary endpoints' was used for different meanings in different clinical trial protocols, statistical analysis plans, and journal articles. In many cases, the term 'co-primary endpoints' was inappropriately used for really 'multiple primary endpoints'.
Co-primary endpoints should only be used when there are more than one primary endpoint and declare the study success only if both primary endpoints are statistically significant in favor of the experimental treatment. When co-primary endpoints are used, each primary endpoint is tested at significant level of 0.05. There is no multiplicity issue involved.
In contrary, the term 'multiple primary endpoints' should be used if there are more than one primary endpoint and declare the study success if either one of the primary endpoints is statistically significant in favor of the experimental treatment. In this case, each primary endpoint is tested at a significant level determined by the method for multiplicity adjustment or simply by the partition of the alpha levels.
Here is what EMA guidance 'guideline on multiplicity issues in clinical trials' says:
If more than one primary endpoint is used to define study success, this success could be defined by a positive outcome in all endpoints or it may be considered sufficient, if one out of a number of endpoints has a positive outcome. Whereas in the first definition the primary endpoints are designated as co-primary endpoints, the latter case is different and would require appropriate adjustment for multiplicity. More generally, in case of more than two primary endpoints, adjustment is needed if not all endpoints need to be significant to define study success, and the inability to exclude deteriorations in other primary endpoints would have to be considered in the overall benefit/risk assessment.In FDA's guidance 'multiple endpoints in clinical trials', the term 'co-primary endpoints' was extensively discussed and the examples of co-primary endpoints were provided. In section C of the guidance, it says:
For some disorders, there are two or more different features that are so critically important to the disease under study that a drug will not be considered effective without demonstration of a treatment effect on all of these disease features. The term used in this guidance to describe this circumstance of multiple primary endpoints is co-primary endpoints. Multiple primary endpoints become co-primary endpoints when it is necessary to demonstrate an effect on each of the endpoints to conclude that a drug is effective.The guidance provided the following examples of co-primary endpoints where both co-primary endpoints needed to be statistically significant in order to declare the trial success:
- A recent approach to studying treatments is to consider a drug effective for migraines only if pain and an individually-specified most bothersome second feature are both shown to be improved by the drug treatment.
- Drugs for Alzheimer’s disease have generally been expected to show an effect on both the defining feature of the disease, decreased cognitive function, and on some measure of the clinical impact of that effect. Because there is no single endpoint able to provide convincing evidence of both, co-primary endpoints are used. One primary endpoint is the effect on a measure of cognition in Alzheimer’s disease (e.g., the Alzheimer’s Disease Assessment Scale-Cognitive Component), and the second is the effect on a clinically interpretable measure of function, such as a clinician’s global assessment or an Activities of Daily Living Assessment.
In an article by Kantarjian et al “Decitabine improves patients outcome in myelodysplastic syndromes: results of a phase III randomized study”, the term ‘coprimary endpoints’ was incorrectly used for ‘multiple endpoints’ even though the multiplicity adjustment method (Bonferroni correction) was appropriately applied.
The coprimary endpoints in the current study were ORR and time to AML transformation or death. Response was assessed according to the International Working group (IWG) criteria……Two analyses, one interim and one final, were planned using the stopping rules of O’Brien and Fleming. The overall type 1 error rate was maintained at a maximum of 5% by applying a Bonferroni correction for the coprimary endpoints at the final analysis. A maximum P value of .024 was required to establish statistical significance using a 2-sided analysis for either of the coprimary endpoints (ORR or time to AML or Death).
The initial assumptions for the primary end-point were an annual rate of 21% on placebo with a risk reduced by 36% (hazard ratio (HR) 0.64) with bosentan and a negligible annual attrition rate. In addition, it was planned to conduct a single final analysis at 0.04 (two-sided), taking into account the existence of a co-primary end-point (change in 6MWD at 16 weeks) planned to be tested at 0.01 (two-sided). Over the course of the study, a number of amendments were introduced based on the evolution of knowledge in the field of PAH, as well as the rate of enrolment and blinded evaluation of the overall event rate. On implementation of an amendment in 2007, the 6MWD end-point was changed from a co-primary end-point to a secondary endpoint and the Type I error associated with the single remaining primary end-point was increased to 0.05 (two-sided).