Biotechnology Healthcare - June 2008 - (Page 23) UNDERSTANDING CANCER TRIAL ENDPOINTS Ideally, when reviewing an oncology agent for coverage, a payer should augment the review of safety and efficacy data with a thorough cost/benefit analysis, weighing the costs of the agent against the benefits to payers, healthcare providers, and patients. Such an analysis, however, often is not possible because of a paucity of supporting data. Payers, therefore, should have a clear understanding of oncology clinical trial endpoints to make accurate decisions about the value of various treatments. According to the FDA’s Guidance for Industry: Clinical Trial Endpoints for the Approval of Cancer Drugs and Biologics (FDA 2007), several endpoints are commonly used to measure the efficacy of oncology agents in clinical trials (Table 1, page 25). These endpoints are discussed below. Calculating survival benefit. When reviewing cancer treatments, the key benefit for all stakeholders is the ability to extend survival. FIGURE 1 The two most common methods of calculating survival rates are the Kaplan-Meier method and life table analysis. The Kaplan-Meier method is preferred because survival is calculated using each event (patient death) as an interval; life table analysis, by contrast, uses a fixedtime interval. With Kaplan-Meier, survival is recalculated every time any patient dies. Survival is calculated by dividing the number of patients alive at the end of a day by the number alive at the beginning of that day. Censored patients (those who were alive at the end of the trial but not followed for the entire length of the trial) are excluded from both the numerator and the denominator. To calculate the number of patients who survive from day 0 until a predetermined measurement point (such as the end of the study), the number of patients who survive day 1 is multiplied by the number of patients who survive day 2, and this calculation is done for each succeeding day included in the study. Figure 1 shows a sim- ple survival curve with censored data compared with a curve without censored data. Two terms that are frequently confused when evaluating survival data are median survival time and mean survival time. Understanding the nuances of each of these metrics is crucial if payers are to be able to assess how efficacious an oncologic agent may be. Median survival time is the point at which half of the patients are alive and half are dead (Figure 2, next page). Mean survival time is the point at which individuals in the study stayed alive divided by the length of the study, also referred to as the area under the curve. Mean survival time includes data from censored patients, so the median survival time is less likely to be skewed. Overall survival. Overall survival (OS) represents the time from clinical trial randomization until death from any cause, and is measured in the intent-to-treat population. OS remains the preferred endpoint for clinical trials as it has the greatest Comparison of simple survival curve to one with censored data removed 100 Percent still alive 75 50 25 0 0 12 24 Time in months 36 Percent still alive 100 75 50 25 0 0 12 24 Time in months 36 Survival curve with censored subjects. A subject is censored at a certain time for one of two reasons: (1) The subject stopped following the study protocol at that time, or (2) the trial ended with the subject still alive. In the left panel, censored subjects are shown as upward blips. In the right panel, censored subjects are shown as solid circles in a horizontal portion of the curve. Source: Motulsky 1995; reprinted with permission MAY/JUNE 2008 · BIOTECHNOLOGY HEALTHCARE 23
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