ArticleFrontiers in oncology2023
Prognostic nomograms integrating preoperative serum lipid derivative and systemic inflammatory marker of patients with non-metastatic colorectal cancer undergoing curative resection.
Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
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Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 5 citations in OpenAlex.
- Blood lipid metabolic biomarkers are emerging as significant prognostic indicators for survival in cancer patients.BMC cancer · 2024Pooled it
- Albumin and neutrophil combined prognostic grade for predicting overall survival in colorectal cancer: a retrospective cohort study.Frontiers in oncology · 2026Article
- Preoperative malnutrition predicts poor early immune recovery following gynecologic cancer surgery: a retrospective cohort study and risk nomogram development.Frontiers in immunology · 2025Article
- Significance of prothrombin, activated partial thromboplastin, and thrombin times in early rehabilitation after tibial fracture surgery.American journal of translational research · 2024Article
- Analysis of Baseline Serum Lipid Profile for Predicting Clinical Outcomes of Patients with Extensive-Stage Small Cell Lung Cancer.Cancer management and research · 2023Article
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Authors and funding
7 authors at 3 institutions in 1 country.
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Abstract
Background: Lipid metabolism and cancer-related inflammation are closely related to the progression and prognosis of colorectal cancer (CRC). Therefore, this study aims to establish novel nomograms based on the combined detection of preoperative blood lipids and systemic inflammatory indicators to predict the overall survival (OS) and cancer-specific survival (CCS) of CRC patients. Methods: A total of 523 patients with stage I-III CRC in our institute were collected from 2014 to 2018. The independent predictors for OS and CCS were determined by forward stepwise Cox regression for the establishment of prognostic models. The superiorities of different models were compared by concordance index (C-index), Akaike information criterion (AIC) and integrated discrimination improvement analysis. The performance of the nomograms based on the optimal models was measured by the plotting time-dependent receiver operating characteristic curves, calibration curves, and decision curves, and compared with the tumor-node-metastasis (TNM) staging system. The cohort was categorized into low-risk, medium-risk and high-risk groups according to the risk points of the nomogram, and analyzed using Kaplan-Meier curves and log-rank test. Results: Preoperative TG/HDL-C ratio (THR) ≥ 1.93 and prognostic nutritional index (PNI) ≥ 42.55 were independently associated with favorable outcomes in CRC patients. Six (pT stage, pN stage, histological subtype, perineural invasion, THR and PNI) and seven (pT stage, pN stage, histological subtype, perineural invasion, gross appearance, THR and PNI) variables were chosen to develop the optimal models and construct nomograms for the prediction of OS and CCS. The models had lower AIC and larger C-indexes than other models lacking either or both of THR and PNI, and improved those integrated discrimination ability significantly. The nomograms showed better discrimination ability, calibration ability and clinical effectiveness than TNM system in predicting OS and CCS, and these results were reproducible in the validation cohort. The three risk stratifications based on the nomograms presented significant discrepancies in prognosis. Conclusion: Preoperative THR and PNI have distinct prognostic value in stage I-III CRC patients. The nomograms incorporated the two indexes provide an intuitive and reliable approach for predicting the prognosis and optimizing individualized therapy of non-metastatic CRC patients, which may be a complement to the TNM staging system.
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