Development and Validation of Nomograms to Predict the Overall Survival and Progression-Free Survival in Patients with Advanced Unresectable Intrahepatic Cholangiocarcinoma.

IF 2.5 4区医学 Q3 ONCOLOGY

Cancer Management and Research Pub Date : 2024-12-18 eCollection Date: 2024-01-01 DOI:10.2147/CMAR.S489960

Feng Xian, Xuewu Song, Jun Bie, Guohui Xu

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引用次数: 0

Abstract

Purpose: This study aimed to develop and validate clinical nomograms for predicting progression-free survival (PFS) and overall survival (OS) in unresectable ICC patients.

Patients and methods: Patients with ICC between 1 January 2018 and 31 May 2023 were selected and randomized into a training set and an internal validation set as a 7:3 ratio. Data analysis and modeling were conducted through R software. The univariate and multivariate Cox regression models were used to analyze the prognosis factors affecting OS and PFS. Survival analysis was conducted using the Kaplan-Meier (KM) method, and comparisons were made using the Log rank test. Then, two nomogram models were constructed to predict OS and PFS, respectively. The nomogram was evaluated and calibrated using the Harrell's C-index, receiver operating characteristic curve (ROC), and calibration plots, and the decision curve analysis (DCA) was conducted to assess its clinical utility.

Results: A total of 110 patients were enrolled in this study, with 77 to the training set and 33 to the validation set. In the entire population, the OS rates at 6 and 12 months were 75.5% and 35.5%, respectively, while the PFS rates at 6 and 12 months were 47.3% and 20%, respectively. Cox regression analyses showed that ECOG, Tumor volume, HBsAg and AFP were the prognosis factors of OS, and the predictors in the model of PFS included Gender, Stage of tumor, CDC20 expression and AFP. The nomograms were constructed based on the predictors above. The C-index for predicting OS was 0.802 (0.755, 0.849) in the training set, 0.813 (0.764, 0.862) in the internal validation set; the C-index for predicting PFS was 0.658 (0.568, 0.748) in the training set, and 0.795 (0.705, 0.885) in the internal validation set. Finally, calibration curves and DCA indicated that two nomograms showed favorable performance.

Conclusion: Two practical and effective prognostic nomograms were developed to assist clinicians in evaluating OS and PFS in patients with unresectable ICC.

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nomogram预测晚期不可切除肝内胆管癌患者总生存期和无进展生存期的发展和验证。

目的：本研究旨在开发和验证用于预测不可切除ICC患者无进展生存期（PFS）和总生存期（OS）的临床图。患者和方法：选择2018年1月1日至2023年5月31日之间的ICC患者，并按7:3的比例随机分为训练集和内部验证集。通过R软件进行数据分析和建模。采用单因素和多因素Cox回归模型分析影响OS和PFS的预后因素。生存分析采用Kaplan-Meier （KM）法，比较采用Log rank检验。然后，分别构建两个nomogram模型来预测OS和PFS。采用Harrell’s c指数、受试者工作特征曲线（ROC）和校准图对nomogram进行评估和校准，并进行决策曲线分析（DCA）来评估其临床应用价值。结果：共有110例患者入组，其中77例进入训练集，33例进入验证集。在整个人群中，6个月和12个月的OS率分别为75.5%和35.5%，而6和12个月的PFS率分别为47.3%和20%。Cox回归分析显示ECOG、Tumor volume、HBsAg、AFP是OS的预后因素，PFS模型的预测因子包括性别、肿瘤分期、CDC20表达、AFP。在上述预测因子的基础上构建了模态图。预测OS的c指数在训练集中为0.802(0.755,0.849)，在内部验证集中为0.813 (0.764,0.862)；预测PFS的c指数在训练集为0.658(0.568,0.748)，在内部验证集为0.795（0.705,0.885）。最后，标定曲线和DCA结果表明，两种模态图具有良好的性能。结论：开发了两种实用有效的预后图，以帮助临床医生评估不可切除ICC患者的OS和PFS。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Cancer Management and Research Medicine-Oncology

CiteScore

7.40

自引率

0.00%

发文量

448

审稿时长

16 weeks

期刊介绍： Cancer Management and Research is an international, peer reviewed, open access journal focusing on cancer research and the optimal use of preventative and integrated treatment interventions to achieve improved outcomes, enhanced survival, and quality of life for cancer patients. Specific topics covered in the journal include: ◦Epidemiology, detection and screening ◦Cellular research and biomarkers ◦Identification of biotargets and agents with novel mechanisms of action ◦Optimal clinical use of existing anticancer agents, including combination therapies ◦Radiation and surgery ◦Palliative care ◦Patient adherence, quality of life, satisfaction The journal welcomes submitted papers covering original research, basic science, clinical & epidemiological studies, reviews & evaluations, guidelines, expert opinion and commentary, and case series that shed novel insights on a disease or disease subtype.