The distinction between primary and secondary endpoints reflects the hierarchy of importance in clinical trial outcomes and the statistical framework for drawing conclusions from trial data. The primary endpoint represents the outcome most relevant to the clinical question the trial is designed to answer, and success or failure of the trial is typically determined by results on this endpoint. Sample size calculations are based on the primary endpoint, and the statistical analysis plan specifies the primary analysis with full control of Type I error.

Primary endpoint selection requires careful consideration of clinical relevance, regulatory acceptance, and practical feasibility. The endpoint should reflect an outcome meaningful to patients, such as survival, symptom improvement, or prevention of disease progression. Regulatory authorities provide guidance on acceptable endpoints for specific indications, and early engagement with regulators helps ensure that chosen endpoints will support approval. Practical considerations include the frequency of events, measurement reliability, and the duration of follow-up required for assessment.

Secondary endpoints provide additional characterization of treatment effects beyond the primary endpoint, addressing questions such as effects on symptoms, quality of life, biomarkers, or alternative efficacy measures. While secondary endpoints contribute valuable information, their analysis is typically considered exploratory or supportive unless multiplicity adjustments maintain Type I error control. Results on secondary endpoints that support primary findings strengthen the evidence for treatment benefit, while discordant results may require careful interpretation. Tertiary or exploratory endpoints address hypotheses of lower priority or generate hypotheses for future investigation.