Shen Weidong, Sakamoto Naoko, Yang Limin
Department of Otolaryngology - Head and Neck Surgery, Chinese PLA General Hospital, The Institute of Otolaryngology, 28 Fuxing Road, Beijing, 100853, People's Republic of China.
Department of Epidemiology Research, Toho University, 4-16-20, Omori-Nishi Ota-ku, Tokyo, 143-0015, Japan.
BMC Cancer. 2016 Jul 7;16:413. doi: 10.1186/s12885-016-2438-3.
The objectives of this study were to evaluate and model the probability of melanoma-specific death and competing causes of death for patients with melanoma by competing risk analysis, and to build competing risk nomograms to provide individualized and accurate predictive tools.
Melanoma data were obtained from the Surveillance Epidemiology and End Results program. All patients diagnosed with primary non-metastatic melanoma during the years 2004-2007 were potentially eligible for inclusion. The cumulative incidence function (CIF) was used to describe the probability of melanoma mortality and competing risk mortality. We used Gray's test to compare differences in CIF between groups. The proportional subdistribution hazard approach by Fine and Gray was used to model CIF. We built competing risk nomograms based on the models that we developed.
The 5-year cumulative incidence of melanoma death was 7.1 %, and the cumulative incidence of other causes of death was 7.4 %. We identified that variables associated with an elevated probability of melanoma-specific mortality included older age, male sex, thick melanoma, ulcerated cancer, and positive lymph nodes. The nomograms were well calibrated. C-indexes were 0.85 and 0.83 for nomograms predicting the probability of melanoma mortality and competing risk mortality, which suggests good discriminative ability.
This large study cohort enabled us to build a reliable competing risk model and nomogram for predicting melanoma prognosis. Model performance proved to be good. This individualized predictive tool can be used in clinical practice to help treatment-related decision making.
本研究的目的是通过竞争风险分析评估和建立黑色素瘤患者黑色素瘤特异性死亡及其他死因的概率模型,并构建竞争风险列线图以提供个体化且准确的预测工具。
黑色素瘤数据来自监测、流行病学和最终结果计划。2004年至2007年期间所有诊断为原发性非转移性黑色素瘤的患者均有可能被纳入。累积发病率函数(CIF)用于描述黑色素瘤死亡率和竞争风险死亡率的概率。我们使用Gray检验比较组间CIF的差异。采用Fine和Gray的比例子分布风险方法对CIF进行建模。我们基于所开发的模型构建了竞争风险列线图。
黑色素瘤死亡的5年累积发病率为7.1%,其他死因的累积发病率为7.4%。我们确定与黑色素瘤特异性死亡概率升高相关的变量包括年龄较大、男性、黑色素瘤厚度大、溃疡型癌症和阳性淋巴结。列线图校准良好。预测黑色素瘤死亡率和竞争风险死亡率概率的列线图的C指数分别为0.85和0.83,表明具有良好的判别能力。
这个大型研究队列使我们能够构建一个可靠的竞争风险模型和列线图来预测黑色素瘤预后。模型表现良好。这种个体化预测工具可用于临床实践,以帮助进行与治疗相关的决策。