Modelling relative survival in the presence of incomplete data: a tutorial
Modelling relative survival in the presence of incomplete data: a tutorial
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DOI：
10.1093/ije/dyp309
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发表时间：
2010-02-01
影响因子：
7.7
通讯作者：
Coleman, Michel P.
中科院分区：
文献类型：
--
作者：
Nur, Ula;Shack, Lorraine G.;Coleman, Michel P.
方法我们估计了1997年至2004年间诊断并在西北癌症情报服务中心登记的29563例结直肠癌患者的相对生存率。在随机缺失（MAR）假设下，多重插补（MI）方法用于解释诊断时不完整分期的常见示例。多变量回归与广义线性模型和泊松误差结构，然后使用估计的过度风险的结直肠癌患者的死亡，超过和以上的背景死亡率，调整的显着预测mortality.Results不完整的信息阶段，形态和等级意味着只有55%的数据可以被列入“完整的情况下”分析。所有病例均可采用指标法（IM）或MI法纳入。与完整病例分析的结果相比，MI处理缺失数据产生了显著较低的分期、形态学和分级的超额死亡率估计值，晚期和高级别肿瘤的死亡率降低幅度最大。所有阶段缺失值的记录被合并为一个“缺失”类别。我们发现，MI方法大大提高了利用所有的信息在不完整的记录的结果。这种方法也有助于确保从多变量回归分析中对生存率进行有效的推断。
Methods We estimated relative survival for 29 563 colorectal cancer patients who were diagnosed between 1997 and 2004 and registered in the North West Cancer Intelligence Service. The method of multiple imputation (MI) was applied to account for the common example of incomplete stage at diagnosis, under the missing at random (MAR) assumption. Multivariable regression with a generalized linear model and Poisson error structure was then used to estimate the excess hazard of death of the colorectal cancer patients, over and above the background mortality, adjusting for significant predictors of mortality.Results Incomplete information on stage, morphology and grade meant that only 55% of the data could be included in the 'complete-case' analysis. All cases could be included after indicator method (IM) or MI method. Handling missing data by MI produced a significantly lower estimate of the excess mortality for stage, morphology and grade, with the largest reductions occurring for late-stage and high-grade tumours, when compared with the results of complete-case analysis.Conclusion In complete-case analysis, almost 50% of the information could not be included, and with the IM, all records with missing values for stage were combined into a single 'missing' category. We show that MI methods greatly improved the results by exploiting all the information in the incomplete records. This method also helped to ensure efficient inferences about survival were made from the multivariate regression analyses.