Department of Integration of Western and Traditional Medicine, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
Department of Breast Surgery, Obstetrics and Gynecology Hospital of Fudan University, Shanghai, China.
Biomed Res Int. 2020 Nov 7;2020:8882576. doi: 10.1155/2020/8882576. eCollection 2020.
In the past few years, the immune system and tumor immune microenvironment are becoming increasingly popular as more work has been accomplished in this field. However, nomograms based on immune-related characteristics for prognosis prediction of cervical cancer have not been fully explored to our knowledge. We constructed a novel immune score-based nomogram to predict patients with high risk and poor prognosis.
198 patients with cervical cancer from The Cancer Genome Atlas (TCGA) database were included in our study. Immune scores were generated with Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm, and clinic-pathological characteristics were also included for subsequent analysis. Cox proportional hazards regression models were performed for univariate and multivariate analyses to screen the significant factors, and a prognostic nomogram was built. Bootstrap resampling analysis was used for internal validation. The calibration curve and concordance index (C-index) were used to assess the predictive performance of the nomogram.
Patients were split into three subgroups based on immune scores. We found that patients with high immune scores conferred significantly better overall survival (OS) compared with those with medium and low immune scores (hazard ratio (HR), 0.305; 95% confidence interval (CI), 0.108-0.869). A nomogram with a C-index of 0.720 had a favorable performance for predicting survival rate for clinical use by combining immune scores with other clinical features. The calibration curves at 3 and 5 years suggested a good consistency between the predicted OS and the actual OS probability.
Our work highlights the potential clinical application significance of immune score-based nomogram in predicting the OS of cervical cancer patients.
在过去的几年中，免疫系统和肿瘤免疫微环境越来越受到关注，因为在这一领域已经取得了更多的研究成果。然而，据我们所知，基于免疫相关特征的列线图尚未充分探索用于预测宫颈癌患者的预后。我们构建了一个新的基于免疫评分的列线图，以预测具有高风险和预后不良的患者。
本研究纳入了来自癌症基因组图谱（TCGA）数据库的 198 例宫颈癌患者。使用 ESTIMATE 算法生成免疫评分，并结合临床病理特征进行后续分析。采用 Cox 比例风险回归模型进行单因素和多因素分析，筛选出显著因素，并构建预后列线图。Bootstrap 重采样分析用于内部验证。校准曲线和一致性指数（C-index）用于评估列线图的预测性能。
根据免疫评分将患者分为三组。我们发现，高免疫评分患者的总生存（OS）显著优于中、低免疫评分患者（风险比（HR），0.305；95%置信区间（CI），0.108-0.869）。结合免疫评分和其他临床特征构建的 C-index 为 0.720 的列线图在预测生存率方面具有良好的临床应用性能。3 年和 5 年的校准曲线表明，预测 OS 与实际 OS 概率之间具有良好的一致性。
本研究强调了基于免疫评分的列线图在预测宫颈癌患者 OS 中的潜在临床应用意义。
