Abstract

Bruzzi et al have evaluated objective response rate (ORR) as a potential surrogate end point for survival in metastatic breast cancer patients. Throughout oncology, many biomarkers have been evaluated. Examples include direct measures of the tumor burden process, such as ORR or progression-free survival (PFS), or inherently less reliable indirect measures, such as carcinoembryonic antigen or prostate-specific antigen. Biomarkers can serve several useful purposes. These purposes include the following: (1) detecting disease or assessing prognosis, and to serve this purpose, biomarkers, such as carcinoembryonic antigen or prostate-specific antigen, only need to be correlated with disease presence or prognosis, rather than being the causal mechanism through which the disease process induces effects on true clinical end points like survival or disease-related symptoms (in oncology, this causal mechanism usually is the tumor burden process); (2) targeting those patients who will benefit from treatment, and to be truly useful in this context, the biomarker needs to be known before initiation of treatment, such as assessing the level of overexpression of human epidermal growth factor receptor 2 in deciding whether to use trastuzumab; and (3) as a surrogate (or replacement) end point in trials designed to provide conclusive evidence about the benefit-to-risk profile of an intervention. How useful is ORR regarding purposes 2 and 3? Although it is a direct measure of the tumor burden process, ORR could underestimate treatment effects on clinical end points, such as survival, by failing to adequately capture the magnitude, breadth, and, in particular, the duration of effects on tumor burden. Conversely, ORR could overestimate impact on survival or other clinical end points if response is brief or if this measure fails to capture unintended harmful mechanisms of action of treatment. How does one validate a biomarker in general? In particular, in the context of metastatic breast cancer in which survival is the clinical end point, is ORR reliable in addressing the useful purposes identified earlier? Three levels of statistical evidence should be considered. First, is the biomarker correlated with the clinical end point? Such correlation is a necessary but not sufficient condition to establish the validity of a surrogate end point. Simply showing that responders live longer than nonresponders does not rule out the possibility that achievement of response is merely putting a label on those who already would have lived longer, independent of treatment. Second, does evidence suggest that ORR fully captures the effect of treatment on survival, when conducting a Cox regression analysis using ORR as a time varying covariate or when generating survival curves by tumor response using the landmark method? Although these statistical analyses provide evidence concerning the plausibility that ORR is a useful surrogate end point, one must use considerable caution in interpreting these results. The conclusion by Bruzzi et al from such analyses that the “survival difference was entirely a result of the effect of experimental FU regimens on response rate” seems to be an overstatement because of several limitations. The first limitation is that these analyses only address whether ORR is capturing the net effect of treatment on survival. For example, suppose that the treatment provides a 6% reduction in death rate and that that is exactly what would be expected from the identified effect on ORR. In such settings, treatment might also be providing additional beneficial effects on survival through mechanisms other than induction of response, but these additional benefits may be offset by the treatment’s unintended adverse effects on survival that are not captured by ORR. (It also follows that it is unwise to generalize the relationship between effects on ORR and effects on survival found with one class of agents to other classes.) The second limitation is JOURNAL OF CLINICAL ONCOLOGY E D I T O R I A L VOLUME 23 NUMBER 22 AUGUST 1 2005

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