Author(s): Gamel JW, Vogel RL, Valagussa P, Bonadonna G
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Abstract BACKGROUND: Standard, nonparametric statistical methods estimate only the impact of therapy on survival rate up to a selected follow-up interval. In contrast, parametric methods can estimate the impact of treatment on the two cardinal parameters of malignancy: likelihood of cure and recurrence free survival time among uncured patients. METHODS: The authors screened a total of six parametric survival models. Three of these, including the log normal model, were applied to survival data from five clinical trials of adjuvant therapy for Stage II breast cancer. For comparison, the log rank test, a standard nonparametric method, was also applied to the same data. RESULTS: Both parametric and nonparametric methods identified a significant therapeutic in three of the five trials. In only one of these three trials, however, did parametric analysis identify a significant difference in the likelihood of cure between treatment groups. In the remaining two trials, a significant difference was found in recurrence free survival time among uncured patients. The three parametric survival models gave similar results. CONCLUSION: These findings suggest that parametric analysis may warrant further study as a method for measuring the long term clinical impact of adjuvant therapy on Stage II breast cancer.
This article was published in Cancer
and referenced in Journal of Biometrics & Biostatistics