Tree-Based Model for Thyroid Cancer Prognostication
Tree-Based Model for Thyroid Cancer Prognostication
复制标题
DOI：
10.1210/jc.2014-2197
复制
发表时间：
2014-10-01
影响因子：
5.8
通讯作者：
Haymart, Megan R.
中科院分区：
文献类型：
--
作者：
Banerjee, Mousumi;Muenz, Daniel G.;Haymart, Megan R.
背景：死亡在甲状腺癌患者中并不常见，并且对预测生存率的重要因素的研究还不够充分。本研究的目的是评估患者，肿瘤和治疗因素的预后影响，并确定预后组甲状腺癌survival.Methods：使用数据的监测，流行病学和最终结果计划（SEER），我们评估了整体和疾病特异性生存（DSS）在43 392例分化良好的甲状腺癌患者从1998年至2005年诊断。采用考克斯比例风险回归、生存树和随机生存森林进行多变量分析。使用国家癌症数据库数据进行了类似的分析，对1998年至2005年诊断的131484例甲状腺癌患者的总生存率（OS）进行了评价。生存的重要因素的相对重要性进行了评估的基础上随机生存forest analysis.Results：使用生存树分析，我们确定了4个不同的预后组的基础上DSS（P < .0001）。5年生存率分别为100%、98%、91%、64%，10年生存率分别为100%、96%、85%、50%。基于随机生存森林分析，DSS的最重要的因素是SEER分期和诊断年龄。对于OS，重要的预后因素是相似的，除了诊断时的年龄表现出显着的重要性相对于SEER阶段。使用国家癌症数据库data.Conclusion：这项研究确定了不同的预后组甲状腺癌，并说明了患者年龄的疾病特异性和OS的重要性。这些研究结果对患者的教育和甲状腺癌治疗的影响。
Background: Death is uncommon in thyroid cancer patients, and the factors important in predicting survival remain inadequately studied. The objective of this study was to assess prognostic effects of patient, tumor, and treatment factors and to determine prognostic groups for thyroid cancer survival.Methods: Using data from the Surveillance, Epidemiology, and End Results Program (SEER), we evaluated overall and disease-specific survival (DSS) in 43 392 well-differentiated thyroid cancer patients diagnosed from 1998 through 2005. Multivariable analyses were performed using Cox proportional hazards regression, survival trees, and random survival forest. Similar analyses were performed using National Cancer Data Base data, with overall survival (OS) evaluated in 131 484 thyroid cancer patients diagnosed from 1998 through 2005. Relative importance of factors important to survival was assessed based on the random survival forest analyses.Results: Using survival tree analyses, we identified 4 distinct prognostic groups based on DSS (P < .0001). The 5-year DSS of these prognostic groups was 100%, 98%, 91%, 64%, whereas the 10-year survival was 100%, 96%, 85%, and 50%. Based on random survival forest analyses, the most important factors for DSS were SEER stage and age at diagnosis. For OS, important prognostic factors were similar, except age at diagnosis demonstrated marked importance relative to SEER stage. Similar results for OS were found using National Cancer Data Base data.Conclusion: This study identifies distinct prognostic groups for thyroid cancer and illustrates the importance of patient age to both disease-specific and OS. These findings have implications for patient education and thyroid cancer treatment.