Wang Jiaqiang, Ye Chengwei, Zhang Chaoyang, Wang Kaiming, Hong Furong, Peng Qingqin, Chen Zilong
Department of Radiation Oncology, The First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, China.
Department of Gastrointestinal Surgery, The First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, China.
Front Surg. 2022 Jul 29;9:989204. doi: 10.3389/fsurg.2022.989204. eCollection 2022.
Neoadjuvant chemoradiotherapy (nCRT) is the recommended standard treatment for locally advanced esophageal cancer (LA-EC). This study aimed to determine whether sex makes a difference in cancer-specific survival (CSS) and construct a novel nomogram model to predict CSS for LA-EC after nCRT based on the SEER database.
Patients coded by 04-15 were identified from the SEER database. Patients with systemic treatment and radiotherapy before surgery were defined as nCRT. We further divided this population into a training group and a verification group at a ratio of 7:3. Univariate and multivariate cox analyses were applied to determine the prognostic risk factors based on the training cohort, and then the Nomogram model was established. The area under the curve (AUC) was used to evaluate the predictive ability of the model. We used the calibration curve to evaluate the consistency between the predicted status and actual status and decision curve analysis (DCA) to evaluate the clinical value. We used X-tile software to determine the best cut-off value of nomogram scores and divided the population into low-risk, medium-risk, and high-risk groups, and Kaplan-Meier analysis was applied to compare the CSS.
A total of 2096 LA-EC patients were included for further analysis, with 1,540 in the training cohort and 656 in the validation group. Male (HR: 1.29, 95% CI, 1.04 -1.58), T stage, N stage, and M stage were identified as independent risk factors of CSS based on the training cohort. A Nomogram model was constructed to predict the 3-, 5- and 7-years CSS. ROC curve and AUC confirmed that this nomogram has median discrimination ability. The calibration curve showed good agreement between predicted status and actual status. The DCA curves confirmed the clinical value. Kaplan-Meier analysis indicated that patients in the high-risk subgroup had poorer CSS in both the training cohort and validation cohort ( < 0.001).
Male patients had poorer CSS in LA-EC patients after nCRT. A nomogram model composed of sex, T stage, N stage, and M stage was constructed to identify the high-risk population and provide a personalized follow-up plan.
新辅助放化疗(nCRT)是局部晚期食管癌(LA-EC)推荐的标准治疗方法。本研究旨在确定性别是否会对癌症特异性生存(CSS)产生影响,并基于监测、流行病学和最终结果(SEER)数据库构建一种新型列线图模型,以预测nCRT后LA-EC患者的CSS。
从SEER数据库中识别出编码为04-15的患者。术前接受全身治疗和放疗的患者被定义为nCRT。我们进一步将该人群以7:3的比例分为训练组和验证组。应用单因素和多因素Cox分析,基于训练队列确定预后危险因素,然后建立列线图模型。曲线下面积(AUC)用于评估模型的预测能力。我们使用校准曲线评估预测状态与实际状态之间的一致性,并使用决策曲线分析(DCA)评估临床价值。我们使用X-tile软件确定列线图评分的最佳截断值,并将人群分为低风险、中风险和高风险组,应用Kaplan-Meier分析比较CSS。
共纳入2096例LA-EC患者进行进一步分析,其中训练队列1540例,验证组656例。基于训练队列,男性(风险比:1.29,95%置信区间,1.04-1.58)、T分期、N分期和M分期被确定为CSS的独立危险因素。构建了列线图模型以预测3年、5年和7年CSS。受试者工作特征(ROC)曲线和AUC证实该列线图具有中等辨别能力。校准曲线显示预测状态与实际状态之间具有良好的一致性。DCA曲线证实了临床价值。Kaplan-Meier分析表明,高风险亚组患者在训练队列和验证队列中的CSS均较差(P<0.001)。
nCRT后LA-EC患者中男性患者的CSS较差。构建了一个由性别、T分期、N分期和M分期组成的列线图模型,以识别高风险人群并提供个性化的随访计划。