Gamel J W, Vogel R L, Valagussa P, Bonadonna G
Veterans Administration Medical Center.
Cancer. 1994 Nov 1;74(9):2483-90. doi: 10.1002/1097-0142(19941101)74:9<2483::aid-cncr2820740915>3.0.co;2-3.
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.
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.
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.
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.
标准的非参数统计方法仅能估计治疗对选定随访期内生存率的影响。相比之下，参数方法能够估计治疗对恶性肿瘤两个主要参数的影响：治愈可能性以及未治愈患者的无复发生存时间。
作者总共筛选了六种参数生存模型。其中三种，包括对数正态模型，被应用于II期乳腺癌辅助治疗的五项临床试验的生存数据。为作比较，标准非参数方法对数秩检验也被应用于相同数据。
参数和非参数方法均在五项试验中的三项试验里确定了显著的治疗效果。然而，在这三项试验中只有一项试验，参数分析确定了治疗组之间在治愈可能性上存在显著差异。在其余两项试验中，未治愈患者的无复发生存时间存在显著差异。三种参数生存模型给出了相似的结果。
这些发现表明，作为一种衡量辅助治疗对II期乳腺癌长期临床影响的方法，参数分析可能值得进一步研究。
