Shen Weidong, Sakamoto Naoko, Yang Limin
Institute of Otolaryngology, Department of Otolaryngology - Head and Neck Surgery, Chinese PLA General Hospital, Beijing, 100853, China.
Department of Epidemiology Research, Toho University, Tokyo, 143-0015, Japan.
Ann Surg Oncol. 2017 Aug;24(8):2129-2136. doi: 10.1245/s10434-017-5861-z. Epub 2017 Apr 19.
The main objective of this study was to evaluate the cumulative incidence of cause-specific death and other causes of death for patients with head and neck adenoid cystic carcinoma (ACC). The secondary aim was to model the probability of cause-specific death and build a competing risk nomogram to predict cause-specific mortality for this disease.
Data were extracted from the US National Cancer Institute's Surveillance Epidemiology, and End Results (SEER)-18 dataset. The study cohort included patients with a diagnosis of primary head and neck ACC during the period 2004-2013. We calculated the cumulative incidence function (CIF) for cause-specific death and other causes of death, and constructed the Fine and Gray's proportional subdistribution hazard model, as well as a competing-risk nomogram based on Fine and Gray's model, to predict the probability of cause-specific death for patients with head and neck ACC.
After data selection, 1435 cases were included for analysis. Five-year cumulative incidence of cause-specific death was 17.4% (95% confidence interval [CI] 15.1-19.8%) and cumulative incidence of other causes of death was 5.8% (95% CI 4.4-7.4%). Predictors of cause-specific death for head and neck ACC included age, tumor size, advanced T stage, positive lymph node, distant metastasis, and surgery. The nomogram was well-calibrated, and had good discriminative ability.
The large sample allowed us to construct a reliable predictive model for rare malignancy. The model performance was good, with a concordance index of 0.79, and the nomogram can provide useful individualized predictive information for patients with head and neck ACC.
本研究的主要目的是评估头颈部腺样囊性癌（ACC）患者特定病因死亡及其他死因的累积发生率。次要目的是建立特定病因死亡概率模型，并构建竞争风险列线图以预测该疾病的特定病因死亡率。
数据取自美国国立癌症研究所的监测、流行病学和最终结果（SEER）-18数据集。研究队列包括2004年至2013年期间诊断为原发性头颈部ACC的患者。我们计算了特定病因死亡及其他死因的累积发生率函数（CIF），并构建了Fine和Gray的比例亚分布风险模型以及基于该模型的竞争风险列线图，以预测头颈部ACC患者特定病因死亡的概率。
经过数据筛选，纳入1435例病例进行分析。特定病因死亡的5年累积发生率为17.4%（95%置信区间[CI] 15.1 - 19.8%），其他死因的累积发生率为5.8%（95% CI 4.4 - 7.4%）。头颈部ACC特定病因死亡的预测因素包括年龄、肿瘤大小、T分期晚期、淋巴结阳性、远处转移和手术。列线图校准良好，具有良好的鉴别能力。
大样本量使我们能够为罕见恶性肿瘤构建可靠的预测模型。模型性能良好，一致性指数为0.79，列线图可为头颈部ACC患者提供有用的个体化预测信息。
