Cui Pengfei, Cong Xiaofeng, Chen Chen, Yang Lei, Liu Ziling
Cancer Center, The First Hospital of Jilin University, Changchun, China.
Front Oncol. 2021 Jul 22;11:652850. doi: 10.3389/fonc.2021.652850. eCollection 2021.
Due to the rarity of adenosquamous carcinoma of the cervix (ASCC), studies on the incidence, prognostic factors, and treatment outcomes of ASCC remain scarce. Therefore, we performed a retrospective population-based study to systematically investigate the characteristics of ASCC patients.
Patients with a histopathologically confirmed diagnosis of ASCC were enrolled from the Surveillance, Epidemiology, and End Results database between 1975 and 2016. Univariate and multivariate Cox regression analyses were performed to identify the potential predictors of cancer-specific survival (CSS) in patients with ASCC. Selected variables were integrated to establish a predictive nomogram and the predictive performance of the nomogram was estimated using Harrell's concordance index (C-index), calibration curve, and decision curve analysis (DCA).
A total of 1142 ASCC patients were identified and included in this study and were further randomized into the training and validation cohorts in a 7:3 ratio. The age-adjusted incidence of ASCC declined from 0.19 to 0.09 cases per 100,000 person-years between 2000 and 2017, with an annual percentage change of -4.05% (P<0.05). We identified age, tumor grade, FIGO stage, tumor size, and surgical procedure as independent predictors for CSS in ASCC patients and constructed a nomogram to predict the 3- and 5-year CSS using these prognostic factors. The calibration curve indicated an outstanding consistency between the nomogram prediction and actual observation in both the training and testing cohorts. The C-index was 0.7916 (95% CI: 0.7990-0.8042) and 0.8148 (95% CI: 0.7954-0.8342) for the training and testing cohorts, respectively, indicating an excellent discrimination ability of the nomogram. The DCA showed that the nomogram exhibited more clinical benefits than the FIGO staging system.
We established and validated an accurate predictive nomogram for ASCC patients based on several clinical characteristics. This model might serve as a useful tool for clinicians to estimate the prognosis of ASCC patients.
由于宫颈腺鳞癌（ASCC）罕见，关于ASCC的发病率、预后因素及治疗结果的研究仍然较少。因此，我们开展了一项基于人群的回顾性研究，以系统地调查ASCC患者的特征。
从监测、流行病学和最终结果数据库中纳入1975年至2016年间经组织病理学确诊为ASCC的患者。进行单因素和多因素Cox回归分析，以确定ASCC患者癌症特异性生存（CSS）的潜在预测因素。整合选定变量以建立预测列线图，并使用Harrell一致性指数（C指数）、校准曲线和决策曲线分析（DCA）评估列线图的预测性能。
本研究共纳入1142例ASCC患者，并按7:3的比例随机分为训练队列和验证队列。2000年至2017年间，ASCC的年龄调整发病率从每10万人年0.19例降至0.09例，年变化率为-4.05%（P<0.05）。我们确定年龄、肿瘤分级、国际妇产科联盟（FIGO）分期、肿瘤大小和手术方式为ASCC患者CSS的独立预测因素，并使用这些预后因素构建了一个预测3年和5年CSS的列线图。校准曲线表明，在训练队列和测试队列中，列线图预测与实际观察结果之间具有出色的一致性。训练队列和测试队列的C指数分别为0.7916（95%CI：0.7990-0.8042）和0.8148（95%CI：0.7954-0.8342），表明列线图具有出色的区分能力。DCA显示，列线图比FIGO分期系统具有更多的临床益处。
我们基于几个临床特征建立并验证了一个针对ASCC患者的准确预测列线图。该模型可能是临床医生评估ASCC患者预后的有用工具。
