MS, DNB, FRCS(Glasg.), FRCSEd, MNAMS, FRCSC,University of Manitoba, Head and Neck Surgical Oncologist, Cancer Care Manitoba, GF 440 A, 820 Sherbrook Street, Winnipeg, Manitoba R3A 1R9, Canada.
J Clin Endocrinol Metab. 2013 Dec;98(12):4768-75. doi: 10.1210/jc.2013-2318. Epub 2013 Oct 23.
Thyroid cancers represent a conglomerate of diverse histological types with equally variable prognosis. There is no reliable prognostic model to predict the risks of relapse and death for different types of thyroid cancers.
The purpose of this study was to build prognostic nomograms to predict individualized risks of relapse and death of thyroid cancer within 10 years of diagnosis based on patients' prognostic factors.
Competing risk subhazard models were used to develop prognostic nomograms based on the information on individual patients in a population-based thyroid cancer cohort followed up for a median period of 126 months. Analyses were conducted using R version 2.13.2. The R packages cmprsk10, Design, and QHScrnomo were used for modeling, developing, and validating the nomograms for prediction of patients' individualized risks of relapse and death of thyroid cancer.
This study was performed at CancerCare Manitoba, the sole comprehensive cancer center for a population of 1.2 million.
Participants were a population-based cohort of 2306 consecutive thyroid cancers observed in 2296 patients in the province of Manitoba, Canada, during 1970 to 2010.
Outcomes were discrimination (concordance index) and calibration curves of nomograms.
Our cohort of 570 men and 1726 women included 2155 (93.4%) differentiated thyroid cancers. On multivariable analysis, patient's age, sex, tumor histology, T, N, and M stages, and clinically or radiologically detectable posttreatment gross residual disease were independent determinants of risk of relapse and/or death. The individualized 10-year risks of relapse and death of thyroid cancer in the nomogram were predicted by the total of the weighted scores of these determinants. The concordance indices for prediction of thyroid cancer-related deaths and relapses were 0.92 and 0.76, respectively. The calibration curves were very close to the diagonals.
We have successfully developed prognostic nomograms for thyroid cancer with excellent discrimination (concordance indices) and calibration.
甲状腺癌是一组具有不同组织学类型且预后差异极大的肿瘤。目前尚无可靠的预后模型可以预测不同类型甲状腺癌的复发和死亡风险。
本研究旨在建立基于患者预后因素的预测模型，以预测甲状腺癌患者在诊断后 10 年内复发和死亡的个体化风险。
本研究使用竞争风险亚分布风险模型，基于人群甲状腺癌队列中个体患者的信息进行分析，该队列中位随访时间为 126 个月。分析使用 R 版本 2.13.2 完成，R 包 cmprsk10、Design 和 QHScrnomo 用于模型构建、预测模型的开发和验证。
本研究在加拿大马尼托巴省的癌症护理曼尼托巴省进行，该省是一个拥有 120 万人口的综合性癌症中心。
本研究参与者为 1970 年至 2010 年间在加拿大马尼托巴省观察到的 2296 例患者中的 2306 例连续甲状腺癌患者，其中 570 例为男性，1726 例为女性。
预测模型的判别能力（一致性指数）和校准曲线。
本队列包括 2155 例分化型甲状腺癌（93.4%），其中 570 例为男性，1726 例为女性。多变量分析显示，患者年龄、性别、肿瘤组织学、T、N 和 M 分期以及临床或影像学检查发现的治疗后大体残留疾病是复发和/或死亡风险的独立决定因素。该预测模型通过对这些因素的加权评分总和来预测患者 10 年内的复发和死亡风险。预测甲状腺癌相关死亡和复发的一致性指数分别为 0.92 和 0.76。校准曲线非常接近对角线。
我们成功开发了具有出色判别能力（一致性指数）和校准能力的甲状腺癌预测模型。
