建立并验证转移性肺大细胞神经内分泌癌患者的预后提名图

IF 2.5 4区 医学 Q3 ONCOLOGY
Xiaoyun Chen, Xingyue Lai, Yedong Huang, Chaosheng Deng
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引用次数: 0

摘要

目的:转移性肺大细胞神经内分泌癌(LCNEC)是一种侵袭性癌症,预后普遍较差。需要有效的方法来预测转移性 LCNEC 患者的生存率。本研究旨在确定独立的生存预测因素,并制定预测转移性 LCNEC 患者生存期的提名图:我们利用监测、流行病学和最终结果(SEER)数据库进行了一项回顾性分析,确定了在 2010 年至 2017 年期间确诊的转移性 LCNEC 患者。为了找到癌症特异性生存率(CSS)的独立预测因素,我们进行了 Cox 回归分析。我们绘制了一个提名图来预测转移性LCNEC患者6个月、12个月和18个月的CSS率。我们采用了一致性指数(C-index)、接收者操作特征曲线(ROC)下面积(AUC)和校准曲线,以评估该模型是否具有鉴别性和可靠性。决策曲线分析(DCA)用于从临床角度评估该模型的实用性和优势:这项研究共招募了 616 名患者,其中 432 人被分配到训练队列,184 人被分配到验证队列。根据多变量考克斯回归分析结果,年龄、T分期、N分期、转移部位、放疗和化疗被确定为转移性LCNEC患者的独立预后因素。提名图显示出很强的性能,训练组和验证组的 C 指数值分别为 0.733 和 0.728。ROC曲线显示该模型具有良好的预测性能,在预测转移性LCNEC患者6个月、12个月和18个月的CSS率时,训练队列的AUC值分别为0.796、0.735和0.736,在验证队列中分别为0.795、0.801和0.780。校准曲线和DCA证实了提名图的可靠性和临床实用性:新的提名图用于预测转移性 LCNEC 患者的 CSS,提供了个性化的风险评估并有助于临床决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Establishment and Validation of Prognostic Nomograms for Patients with Metastatic Pulmonary Large Cell Neuroendocrine Carcinoma.

Purpose: Metastatic pulmonary large cell neuroendocrine carcinoma (LCNEC) is an aggressive cancer with generally poor outcomes. Effective methods for predicting survival in patients with metastatic LCNEC are needed. This study aimed to identify independent survival predictors and develop nomograms for predicting survival in patients with metastatic LCNEC.

Patients and methods: We conducted a retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database, identifying patients with metastatic LCNEC diagnosed between 2010 and 2017. To find independent predictors of cancer-specific survival (CSS), we performed Cox regression analysis. A nomogram was developed to predict the 6-, 12-, and 18-month CSS rates of patients with metastatic LCNEC. The concordance index (C-index), area under the receiver operating characteristic (ROC) curves (AUC), and calibration curves were adopted with the aim of assessing whether the model can be discriminative and reliable. Decision curve analyses (DCAs) were used to assess the model's utility and benefits from a clinical perspective.

Results: This study enrolled a total of 616 patients, of whom 432 were allocated to the training cohort and 184 to the validation cohort. Age, T staging, N staging, metastatic sites, radiotherapy, and chemotherapy were identified as independent prognostic factors for patients with metastatic LCNEC based on multivariable Cox regression analysis results. The nomogram showed strong performance with C-index values of 0.733 and 0.728 for the training and validation cohorts, respectively. ROC curves indicated good predictive performance of the model, with AUC values of 0.796, 0.735, and 0.736 for predicting the 6-, 12-, and 18-month CSS rates of patients with metastatic LCNEC in the training cohort, and 0.795, 0.801, and 0.780 in the validation cohort, respectively. Calibration curves and DCAs confirmed the nomogram's reliability and clinical utility.

Conclusion: The new nomogram was developed for predicting CSS in patients with metastatic LCNEC, providing personalized risk evaluation and aiding clinical decision-making.

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来源期刊
Cancer Control
Cancer Control ONCOLOGY-
CiteScore
3.80
自引率
0.00%
发文量
148
审稿时长
>12 weeks
期刊介绍: Cancer Control is a JCR-ranked, peer-reviewed open access journal whose mission is to advance the prevention, detection, diagnosis, treatment, and palliative care of cancer by enabling researchers, doctors, policymakers, and other healthcare professionals to freely share research along the cancer control continuum. Our vision is a world where gold-standard cancer care is the norm, not the exception.
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