Krongrad A, Lai H, Lai S
Department of Urology, and Sylvester Comprehensive Cancer Center, University of Miami School of Medicine, Florida, USA.
J Urol. 1997 Oct;158(4):1487-90.
Traditional survival analytical tools do not reveal the ability of significant prognostic factors to predict (that is, explain variation in) survival. We used survival data in patients with prostate cancer to illustrate how the association of factors with survival diverges from their ability to explain variation in survival; bladder cancer was included as a point of general comparison.
We used the 1973 to 1990 records of the Surveillance Epidemiology and End Results program. Multivariate proportional hazards models were used to identify factors that significantly associated with survival. The proportion of variation explained by these factors was estimated with the Schemper method.
The dataset included 10,636 patients with prostate cancer and 1,070 with bladder cancer. Median survival was significantly longer in prostate than bladder cancer; other characteristics were similarly distributed. Age, stage and marital status were associated with survival in both cancers (p value range 0.0001 to 0.0009). The total proportion of variation explained was 7.1% and 32.1% for prostate and bladder cancer, respectively. In prostate cancer, age, stage and marital status explained 0.6, 5.5 and 0.4%, of the adjusted proportion of variation explained, respectively, and in bladder cancer, they explained 14.7, 8.9 and 0.6%, respectively.
Proportional hazards models identified but did not reveal the ability of significant prognostic factors to explain variations in survival. The proportion of variation explained analyses illustrate why predicting survival is so difficult, especially in prostate cancer. The prognostic factors used do not possess the ability to explain variation in survival; new prognostic factors must be identified.
传统的生存分析工具无法揭示显著预后因素预测（即解释）生存情况的能力。我们使用前列腺癌患者的生存数据来说明因素与生存之间的关联如何与其解释生存差异的能力相背离；将膀胱癌纳入作为一般比较的对象。
我们使用了监测、流行病学和最终结果计划1973年至1990年的记录。采用多变量比例风险模型来识别与生存显著相关的因素。用施佩尔方法估计这些因素所解释的变异比例。
数据集包括10636例前列腺癌患者和1070例膀胱癌患者。前列腺癌患者的中位生存期明显长于膀胱癌患者；其他特征分布相似。年龄、分期和婚姻状况在两种癌症中均与生存相关（P值范围为0.0001至0.0009）。前列腺癌和膀胱癌所解释的变异总比例分别为7.1%和32.1%。在前列腺癌中，年龄、分期和婚姻状况分别解释了调整后变异比例的0.6%、5.5%和0.4%，在膀胱癌中，它们分别解释了14.7%、8.9%和0.6%。
比例风险模型识别出了显著预后因素，但未揭示其解释生存差异的能力。所解释变异比例的分析说明了预测生存为何如此困难，尤其是在前列腺癌中。所使用的预后因素不具备解释生存差异的能力；必须识别新的预后因素。
