Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute Shenyang, Shenyang, People's Republic of China.
Cancer Sci. 2023 Mar;114(3):1131-1141. doi: 10.1111/cas.15624. Epub 2022 Dec 23.
This study aimed to build a comprehensive model for predicting the overall survival (OS) of cervical cancer patients who received standard treatments and to build a series of new stages based on the International Federation of Gynecologists and Obstetricians (FIGO) stages for better such predictions. We collected the cervical cancer patients diagnosed since the year 2000 from the Surveillance, Epidemiology, and End Results (SEER) database. Cervical cancer patients who received radiotherapy or surgery were included. Log-rank tests and Cox regression were used to identify potential factors of OS. Bayesian networks (BNs) were built to predict 3- and 5-year survival. We also grouped the patients into new stages by clustering their 5-year survival probabilities based on FIGO stage, age, and tumor differentiation. Cox regression suggested black ethnicity, adenocarcinoma, and single status as risks for poorer prognosis, in addition to age and stage. A total of 43,749 and 39,333 cases were finally eligible for the 3- and 5-year BNs, respectively, with 11 variables included. Cluster analysis and Kaplan-Meier curves indicated that it was best to divide the patients into nine modified stages. The BNs had excellent performance, with area under the curve and maximum accuracy of 0.855 and 0.804 for 3-year survival, and 0.851 and 0.787 for 5-year survival, respectively. Thus, BNs are excellent candidates for predicting cervical cancer survival. It is necessary to consider age and tumor differentiation when estimating the prognosis of cervical cancer using FIGO stages.
本研究旨在建立一个综合模型，用于预测接受标准治疗的宫颈癌患者的总生存期（OS），并基于国际妇产科联合会（FIGO）分期建立一系列新的分期，以更好地进行此类预测。我们从监测、流行病学和最终结果（SEER）数据库中收集了自 2000 年以来诊断的宫颈癌患者。纳入接受放疗或手术的宫颈癌患者。采用对数秩检验和 Cox 回归来识别 OS 的潜在因素。建立贝叶斯网络（BNs）来预测 3 年和 5 年生存率。我们还根据 FIGO 分期、年龄和肿瘤分化，通过聚类患者的 5 年生存率，将患者分为新的分期。Cox 回归表明，除了年龄和分期外，黑种人、腺癌和单身状态也是预后较差的危险因素。最终共有 43749 例和 39333 例病例分别适合 3 年和 5 年 BNs，分别包含 11 个变量。聚类分析和 Kaplan-Meier 曲线表明，最好将患者分为九个改良分期。BNs 的性能非常出色，对于 3 年生存率的曲线下面积和最大准确率分别为 0.855 和 0.804，对于 5 年生存率的曲线下面积和最大准确率分别为 0.851 和 0.787。因此，BNs 是预测宫颈癌生存的优秀候选者。在使用 FIGO 分期估计宫颈癌预后时，需要考虑年龄和肿瘤分化。
