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Purpose: To describe a statistically valid method for analyzing cause-specific failure data based on simple proportions, that is easy to understand and apply, and outline under what conditions its implementation is well-suited., Methods and Materials: In the comparison of treatment groups, time to first failure (in any site) was analyzed first, followed by an analysis of the pattern of first failure, preferably at the latest complete follow-up time common to each group., Results: A retrospective analysis of time to contralateral breast cancer in 777 early breast cancer patients was undertaken. Patients previously treated by mastectomy plus radiation therapy to the chest wall and regional nodal areas were randomized to receive further radiation and prednisone (R+P), radiation alone (R), or no further treatment (NT). Those randomized to R+P had a statistically significantly delayed time to first failure compared to the group randomized to NT (p = 0.0008). Patients randomized to R also experienced a delayed time to first failure compared to NT, but the difference was not statistically significant (p = 0.14). At 14 years from the date of surgery (the latest common complete follow-up time) the distribution of first failures was statistically significantly different between R+P and NT (p = 0.005), but not between R and NT (p = 0.09). The contralateral breast cancer first failure rate at 14 years from surgery was 7.2% for NT, 4.6% for R, and 3.7% for R+P. The corresponding Kaplan-Meier estimates were 13.2%, 8.2%, and 5.4%, respectively., Conclusion: Analyzing cause-specific failure data using methods developed for survival endpoints is problematic. We encourage the use of the two-step analysis strategy described when, as in the example presented, competing causes of failure are not likely to be statistically independent, and when a treatment comparison at a single time-point is clinically relevant and feasible; that is, all patients have complete follow-up to this point.