Biotechnology Healthcare - June 2008 - (Page 32) Time to progression of symptoms is a direct measure of clinical benefit rather than subjective factors, and can be useful in cancers with low response rates. DFS. The trial results suggest that trastuzumab significantly improved DFS (unadjusted hazard ratio of the trastuzumab group versus control was 0.54, which corresponded to an absolute benefit in DFS of 8.4 percentage points at 2 years) and reduced the risk of distant metastases with a low risk of cardiac events (Piccart-Gebhart 2005). Gill (2006) has discussed the interim results in the context of the appropriateness of using DFS as a surrogate endpoint in early-stage breast cancer. Although the authors believe this trial provided proof of concept that DFS may be an acceptable primary endpoint for adjuvant trials employing targeted therapies, they also think that a formal pooled analysis of clinical trials using DFS as a surrogate endpoint in adjuvant breast cancer treatment would be valuable. Surrogacy in cancer trials requires that the endpoint used predicts overall survival (Fleming 1996). DFS has been validated for adjuvant chemotherapy for colorectal cancer (Sargent 2005), and strong evidence exists for its validity in early-stage breast and nonresected, non-small cell lung cancer (Gill 2006). The FDA has accepted DFS as an endpoint for drug approval in adjuvant breast cancer hormonal therapy, adjuvant colon cancer, and adjuvant cytotoxic breast cancer therapy (FDA 2007). The advantages of accessing effective therapies in the adjuvant setting, where the treatment goal is a cure, cannot be underestimated. An endpoint such as DFS may allow comparison of the effectiveness of therapies in a class while waiting for data on OS to develop. When DFS is employed as a surrogate endpoint, payers need to weigh the potential benefits in improved QOL and decreased costs against the risk of assessment bias in trial results. Tumor response. The National Cancer Institute (NCI) defines response rate as the “percentage of patients whose cancer shrinks or disappears after treatment” (NCI 2007). Two types of response rates are commonly used to measure tumor response to treatment in oncology clinical trials: objective response rate (ORR) and complete response (CR) rate (also known as pathologic complete response) (FDA 2007). The FDA defines ORR as the “proportion of patients with a tumor size reduction of a predefined amount and for a minimum period of time” (FDA 2007). NCI defines CR as the “disappearance of all signs of cancer in response to treatment.” Although CR is preferred over ORR, very few drugs produce high rates of CR (FDA 2004). The use of response rate as an endpoint, especially when considering the mechanisms of action of newer cancer agents, presents several problems. Aside from the welldocumented difficulties concerning the variability of tumor measurement (Carey 2005), tumor response evaluation rests upon the theory that because anticancer agents kill cancer cells, if an agent is effective, tumor size will decrease. Unfortunately, there is not necessarily a correlation between tumor size and a patient’s overall survival. Newer targeted therapies do not work in the same cytotoxic way as older agents, and these newer agents are more likely to inhibit tumor growth rather than to decrease tumor size. It is possible for a treatment to convey clinical benefit while not creating tumor regression Evaluating surrogate endpoints Overall survival can be expensive and time consuming to calculate. Clinical trials, therefore, often use other endpoints to demonstrate a drug’s efficacy. Surrogate endpoints can accelerate the evaluation of new therapies, allowing patients to have access to, and benefit from, these therapies sooner (Gill 2006, Fleming 1996, Molenberghs 2000). According to Gill (2006), a surrogate endpoint “is selected based on a biologic rationale and may be employed when the primary endpoint of interest is difficult or expensive to measure and when an alternative, more accessible end point is sufficiently well correlated with the primary to justify its use as a substitute.” But how do you determine if the surrogate endpoint is “sufficiently well correlated?” Often, this is an area of confusion for providers and payers. Payers must understand these surrogate endpoints when making coverage decisions, and should be able to determine when their use is appropriate and how these data can be used to compare a product’s efficacy with similar treatments. 32 BIOTECHNOLOGY HEALTHCARE · MAY/JUNE 2008
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