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多名信息提供者:一种评估乳腺癌患者合并症的新方法。

Multiple informants: a new method to assess breast cancer patients' comorbidity.

作者信息

Lash Timothy L, Thwin Soe Soe, Horton Nicholas J, Guadagnoli Edward, Silliman Rebecca A

机构信息

Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA.

出版信息

Am J Epidemiol. 2003 Feb 1;157(3):249-57. doi: 10.1093/aje/kwf193.

Abstract

Past assessments of comorbidity indices have sought to recommend a single index that performs better than others. The authors used a multiple informants approach as an alternative method to simultaneously assess five indices of comorbidity. This approach provides a single estimate of the overall effect of comorbidity and evaluates the relation any individual index has to the outcomes of interest. Association of comorbidity with definitive primary therapy, discussion of tamoxifen, and receipt of tamoxifen was evaluated in a cohort of 830 older breast cancer patients enrolled at four geographically distinct centers in the United States from 1996 to 1999. The estimated adjusted effect of a unit increase in comorbidity on the odds of discussing tamoxifen therapy was 0.70 (95% confidence interval: 0.56, 0.88). An increase in comorbidity was not associated with receipt of definitive primary therapy (odds ratio = 0.94, 95% confidence interval: 0.79, 1.13) or receipt of tamoxifen (odds ratio = 0.96, 95% confidence interval: 0.72, 1.27). The multiple informants regression proved superior to separate regression models that included only one index. In analyses that require comorbidity adjustment and for which no single index is expected to be ideal, the multiple informants approach is an attractive alternative to selecting a single index and to other methods of using multiple indices.

摘要

过去对共病指数的评估一直试图推荐一种比其他指数表现更好的单一指数。作者采用了多信息源方法作为一种替代方法,以同时评估五个共病指数。这种方法提供了对共病总体影响的单一估计,并评估了任何单个指数与感兴趣的结果之间的关系。在1996年至1999年期间在美国四个地理位置不同的中心招募的830名老年乳腺癌患者队列中,评估了共病与确定性初级治疗、他莫昔芬的讨论以及他莫昔芬的使用之间的关联。共病单位增加对讨论他莫昔芬治疗几率的估计调整效应为0.70(95%置信区间:0.56,0.88)。共病增加与接受确定性初级治疗(比值比 = 0.94,95%置信区间:0.79,1.13)或接受他莫昔芬(比值比 = 0.96,95%置信区间:0.72,1.27)无关。多信息源回归被证明优于仅包含一个指数的单独回归模型。在需要进行共病调整且预计没有单一指数是理想的分析中,多信息源方法是选择单一指数和使用多个指数的其他方法的一种有吸引力的替代方法。

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