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结肠癌临床决策辅助工具:两种预测列线图的比较。

Clinical decision aids in colon cancer: a comparison of two predictive nomograms.

机构信息

Department of Cancer Medicine, Peter MacCallum Cancer Centre, Melbourne, Australia.

出版信息

Clin Colorectal Cancer. 2012 Jun;11(2):138-42. doi: 10.1016/j.clcc.2011.07.001. Epub 2011 Oct 22.

Abstract

BACKGROUND

The risk of recurrence of colon cancer after curative surgery can be estimated by using decision aids. These aids use pathologic and patient factors to predict recurrence risk after adjuvant chemotherapy and have been validated when using clinical trial populations; however, the performance of 2 decision aids were compared by using a cohort of patients treated at a single center.

PATIENTS AND METHODS

Patient data were used to estimate the risk of recurrence when using both the Adjuvant! for colon cancer and Memorial Sloan Kettering Cancer Center (MSKCC) decision aids. A receiver operator characteristic (ROC) curve analyzed the predicted chance of being disease free at 5 years against the actual outcome for each patient. This curve was then used to define cutoff points at a chosen sensitivity and specificity to stratify patients into risk groups, and survival curves for each group calculated.

RESULTS

Data on 134 patients were analyzed. The Pearson correlation between the 2 nomograms was 0.848 (P < .01). The ROC curve for the MSKCC nomogram had an area under the curve of 0.638. At a sensitivity and a specificity of 0.8, the MSKCC curve has a risk recurrence score of 69% and 84%, respectively. By using these cutoffs to stratify patients into 3 risk groups, a statistically significant difference in survival was found between high risk and low risk (P = .025).

CONCLUSION

Tools to predict risk or recurrence and estimate benefit from therapy may be enhanced in the future by using genetic profiling, but use of existing tools can help deliver a personalized approach to adjuvant therapy.

摘要

背景

通过使用决策辅助工具,可以评估结肠癌根治性手术后的复发风险。这些工具使用病理和患者因素来预测辅助化疗后的复发风险,并且已经在临床试验人群中得到验证;然而,通过比较单个中心治疗的患者队列,比较了 2 种决策辅助工具的性能。

患者和方法

使用 Adjuvant! for colon cancer 和 Memorial Sloan Kettering Cancer Center (MSKCC) 决策辅助工具来估计患者数据复发的风险。受试者工作特征(ROC)曲线分析了每个患者 5 年内无病的预测机会与实际结果之间的关系。然后,使用该曲线定义在选择的灵敏度和特异性下的截断点,将患者分层为风险组,并计算每个组的生存曲线。

结果

分析了 134 例患者的数据。2 个列线图之间的 Pearson 相关系数为 0.848(P<.01)。MSKCC 列线图的 ROC 曲线下面积为 0.638。在灵敏度和特异性分别为 0.8 时,MSKCC 曲线的风险复发评分分别为 69%和 84%。通过使用这些截断值将患者分为 3 个风险组,高风险和低风险之间的生存存在统计学显著差异(P=.025)。

结论

在未来,通过使用基因谱分析,预测风险或复发并估计治疗获益的工具可能会得到增强,但使用现有工具可以帮助提供辅助治疗的个性化方法。

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