The prognostic value of the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in colorectal cancer and colorectal anastomotic leakage patients: a retrospective study.
摘要:
The purpose of this study was to investigate the influence and predictive value of preoperative peripheral blood neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) index on the prognosis of colorectal anastomotic leakage (CAL) patients. This study retrospectively analyzed the clinical data of 1016 patients who underwent radical resection for colorectal cancer at a single center between January 1, 2007 and December 31, 2023. In this study, NLR and PLR were analyzed before surgery. Kaplan-Meier survival analysis was performed according to the postoperative survival status of the patients. Nomogram and calibration curve were established by proportional hazards model (COX) to verify its predictive value. A total of 890 patients with colorectal cancer, 102 patients with CAL, and 788 patients with non- anastomotic leakage (AL) colorectal cancer were enrolled for a median follow-up of 96 months (quartile range 33-133). In this study, COX regression analysis showed that preoperative NLR and PLR could predict the prognosis of CAL patients, and the optimal cut-off points of NLR and PLR were 2.89 and 157.62, respectively. Kaplan-Meier survival curve results showed that 5-year overall survival (OS) and disease-free survival (DFS) in the low NLR and PLR group were significantly higher than those in the high NLR and PLR group. OS and DFS were divided into high, low NLR and PLR groups. Finally, based on COX model, a nomogram analysis was conducted to analyze the risk factors affecting OS and DFS, and the accuracy and practicality of the model were verified by calibration curve and decision curve. Preoperative NLR and PLR can predict the long-term prognosis of colorectal cancer (CRC) and CAL patients, and patients with NLR ≥ 2.89 and PLR ≥ 157.62 have poor survival prognosis. Nomogram and calibration curve analysis will further improve the accuracy of OS and DFS prediction.
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DOI:
10.1186/s12893-024-02708-5
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年份:
1970


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