Lesson 5: Objectives and Endpoints

Overview Section

The objectives of a trial must be stated in specific terms. Achieving objectives should not depend on observing a particular outcome of the trial, e.g. finding a difference in mean weight loss of exactly 2 kg, but in obtaining a valid result. For example, a randomized trial of 4 diets had as its objective, “To assess adherence rates and the effectiveness of 4 popular diets for weight loss and cardiac risk factor reduction.” (Dansinger et al. 2005).

The endpoints (or outcomes), determined for each study participant, are the quantitative measurements required by the objectives. In the Dansinger weight loss study, the primary endpoint was identified to be mean absolute change from baseline weight at 1 year. In a cancer chemotherapy trial, the clinical objective is usually improved survival. Survival time is recorded for each patient; the primary outcome reported may be median survival time or it could be five-year survival.

Clinical trials typically have a primary objective or endpoint. Additional objectives and endpoints are secondary. The sample size calculation is based on the primary endpoint. Analysis involving a secondary objective has statistical power that is calculated based on the sample size for the primary objective.

"Hard" endpoints are well-defined in the study protocol, definitive with respect to the disease process, and require no subjectivity. "Soft" endpoints are those that do not relate strongly to the disease process or require subjective assessments by investigators and/or patients. Some endpoints fall between these two classifications. For example the grading of x-rays by radiologists and the grading of cell and tissue lesions/tumors by pathologists. There is some degree of subjectivity, but they are valid and reliable endpoints in most settings.

This lesson will help to differentiate between these types of objectives and endpoints. Ready, let's get started!


Upon completion of this lesson, you should be able to:

  • Identify outcomes that are continuous, binary, event times, counts, ordered or unordered categories and repeated measurements.
  • State the merits and problems of using a surrogate outcome.
  • Recognize types of censoring that can occur in studies of time-to-event outcomes.
  • State the components of a typical dose-finding design.