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利用阳性淋巴结的联合对数优势比开发和验证预测同步结直肠癌患者预后的预测模型:一项 SEER 数据库研究。

Developing and validation a prognostic model for predicting prognosis among synchronous colorectal cancers patients using combined log odds ratio of positive lymph nodes: a SEER database study.

机构信息

Department of Gastrointestinal Surgery, Northern Jiangsu People's Hospital, Clinical Teaching Medical School of Nanjing University, No.98 Nantong West Road, Yangzhou, Jiangsu Province, 225001, China.

Medical College of Yangzhou University, Yangzhou, 225001, China.

出版信息

BMC Gastroenterol. 2024 Nov 25;24(1):427. doi: 10.1186/s12876-024-03393-7.


DOI:10.1186/s12876-024-03393-7
PMID:39587468
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11587701/
Abstract

PURPOSE: The aim of the study is to identify risk factors for the prognosis and survival of synchronous colorectal cancer and to create and validate a functional Nomogram for predicting cancer-specific survival in patients with synchronous colorectal cancer. METHODS: Synchronous colorectal cancers cases were retrieved from the Surveillance, Epidemiology, and End Results database retrospectively, then they were randomly divided into training (n = 3371) and internal validation (n = 1440) sets, and a set of 100 patients from our group was used as external validation. Risk factors for synchronous colorectal cancer were determined using univariate and multivariate Cox regression analyses, and two Nomograms were established to forecast the overall survival and cancer-specific survival, respectively. We assessed the Nomogram performance in terms of discrimination and calibration. Bootstrap resampling was used as an internal verification method, and we select external data from our hospital as independent validation sets. RESULTS: Two Nomograms are established to predict the overall survival and cancer-specific survival. In OS Nomogram, sex, age, marital status, ttumor pathological grade, AJCC TNM stage, preoperative serum CEA level, LODDS, radiotherapy and chemotherapy were determined as prognostic factors. In CSS Nomogram, age and marital status, AJCC TNM stage, tumor pathological grade, preoperative serum CEA level, LODDS, radiotherapy and chemotherapy were determined as prognostic factors.The C-indexes for the forecast of overall survival were 0.70, and the C-index was 0.68 for the training and internal validation cohort, respectively. The C-indexes for the forecast of cancer-specific survival were 0.75, and the C-index was 0.74 for the training and internal validation cohort, respectively. The Nomogram calibration curves showed no significant deviation from the reference line, indicating a good level of calibration. Both C-index and calibration curves indicated noticeable performance of newly established Nomograms. CONCLUSIONS: Those Nomograms with risk rating system can identify high risk patients who require more aggressive therapeutic intervention and longer and more frequent follow-up scheme, demonstrated prognostic efficiency.

摘要

目的:本研究旨在确定影响同步结直肠癌预后和生存的因素,并建立和验证一个用于预测同步结直肠癌患者癌症特异性生存的功能诺莫图。

方法:本研究回顾性地从监测、流行病学和最终结果数据库中检索到同步结直肠癌病例,然后将其随机分为训练集(n=3371)和内部验证集(n=1440),并从我们的小组中选择了 100 名患者作为外部验证集。使用单因素和多因素 Cox 回归分析确定同步结直肠癌的危险因素,并建立了两个诺莫图,分别用于预测总生存期和癌症特异性生存期。我们根据区分度和校准度评估了诺莫图的性能。Bootstrap 重采样作为内部验证方法,我们选择来自我们医院的外部数据作为独立验证集。

结果:建立了两个诺莫图来预测总生存期和癌症特异性生存期。在 OS 诺莫图中,性别、年龄、婚姻状况、肿瘤病理分级、AJCC TNM 分期、术前血清 CEA 水平、LODDS、放疗和化疗被确定为预后因素。在 CSS 诺莫图中,年龄和婚姻状况、AJCC TNM 分期、肿瘤病理分级、术前血清 CEA 水平、LODDS、放疗和化疗被确定为预后因素。预测总生存期的 C 指数为 0.70,训练集和内部验证队列的 C 指数分别为 0.68。预测癌症特异性生存期的 C 指数为 0.75,训练集和内部验证队列的 C 指数分别为 0.74。诺莫图校准曲线显示与参考线无显著偏差,表明校准水平良好。C 指数和校准曲线均表明新建立的诺莫图具有显著性能。

结论:这些具有风险评分系统的诺莫图可以识别需要更积极治疗干预和更长、更频繁随访方案的高危患者,表现出良好的预后效率。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/6930e66a0746/12876_2024_3393_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/1b69fc7097f7/12876_2024_3393_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/0a80ad935111/12876_2024_3393_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/0568532a460e/12876_2024_3393_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/8676cde08649/12876_2024_3393_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/3fa65022f6bb/12876_2024_3393_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/919c58e12128/12876_2024_3393_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/6930e66a0746/12876_2024_3393_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/1b69fc7097f7/12876_2024_3393_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/0a80ad935111/12876_2024_3393_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/0568532a460e/12876_2024_3393_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/8676cde08649/12876_2024_3393_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/3fa65022f6bb/12876_2024_3393_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/919c58e12128/12876_2024_3393_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c399/11587701/6930e66a0746/12876_2024_3393_Fig7_HTML.jpg

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