ArticleJournal of inflammation research2021
Models Based on Dynamic Clinicopathological Indices for Predicting Prognosis During the Perioperative Period for Patients with Colorectal Cancer.
Article in Journal of inflammation research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Prognostic prediction model of colorectal cancer based on preoperative serum tumor markers.World journal of gastrointestinal surgery · 2024Article
- Prediction models of colorectal cancer prognosis incorporating perioperative longitudinal serum tumor markers: a retrospective longitudinal cohort study.BMC medicine · 2023Article
- A Nomogram Model for Predicting Recurrence of Stage I-III Endometrial Cancer Based on Inflammation-Immunity-Nutrition Score (IINS) and Traditional Classical Predictors.Journal of inflammation research · 2022Article
- Predicting the Recurrence of Operable Cervical Cancer Patients Based on Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score and Classical Clinicopathological Parameters.Journal of inflammation research · 2022Article
- Predictive Nomogram for the Prediction of Early Recurrence of Colorectal Cancer.International journal of general medicine · 2021Article
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Abstract
backgroundRecent studies have found that clinicopathological indices, such as inflammatory and biochemical indices, play a significant role in the prognosis of colorectal cancer (CRC) patients. However, few studies have focused on the effect of dynamic changes in these indicators. In our study, we studied the influence of dynamic changes in inflammatory and biochemical indices on patient outcomes during the perioperative period.
methodsWe enrolled 551 patients from Hubei Cancer Hospital who had undergone radical resection of CRC and collected the results of laboratory examinations performed within 1 week before surgery and at the first admission after surgery. The whole population was randomly divided into the training (386) and testing (185) cohorts. We used postoperative inflammatory and biochemical indices/preoperative inflammatory and biochemical indices (ΔX) to reflect the dynamic changes. Chi-square tests, Kaplan-Meier survival analyses, and univariate and multivariate Cox regression analyses were used to evaluate the prognosis. The prediction accuracies of models for overall survival (OS) and disease-free survival (DFS) were estimated through Harrell's concordance index (the C-index) and Brier scores. Nomograms of the prognostic models were plotted for evaluations of individualized outcomes.
resultsThe median follow-up time of the 551 patients was 35.6 (range: 1.1-73.8) months. Ultimately, the prognostic models based on age, sex, TNM stage, pathological conditions, inflammatory and biochemical indices, CEA, and CA199 were found to have exceptional performance for OS and DFS. The C-index of the nomogram for OS was 0.806 (95% CI, 0.75-0.86) in the training cohort and 0.921 (95% CI, 0.87-0.96) in the testing cohort. The C-index of the nomogram for DFS was 0.781 (95% CI, 0.74-0.82) in the training cohort and 0.835 (95% CI, 0.78-0.88) in the testing cohort.
conclusionWe successfully established a novel model based on inflammatory and biochemical indices to guide clinical decision-making for CRC.
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