RESUMO
BACKGROUND: Colorectal cancer is the third most prevalent malignancy globally and ranks second in cancer-related mortality, with the liver being the primary organ of metastasis. Preoperative chemotherapy is widely recommended for initially or potentially resectable colorectal liver metastases (CRLMs). Tumour pathological response serves as the most important and intuitive indicator for assessing the efficacy of chemotherapy. However, the postoperative pathological results reveal that a considerable number of patients exhibit a poor response to preoperative chemotherapy. Body mass index (BMI) is one of the factors affecting the tumorigenesis and progression of colorectal cancer as well as prognosis after various antitumour therapies. Several studies have indicated that overweight and obese patients with metastatic colorectal cancer experience worse prognoses than those with normal weight, particularly when receiving first-line chemotherapy regimens in combination with bevacizumab. AIM: To explore the predictive value of BMI regarding the pathologic response following preoperative chemotherapy for CRLMs. METHODS: A retrospective analysis was performed in 126 consecutive patients with CRLM who underwent hepatectomy following preoperative chemotherapy at four different hospitals from October 2019 to July 2023. Univariate and multivariate logistic regression models were applied to analyse potential predictors of tumour pathological response. The Kaplan-Meier method with log rank test was used to compare progression-free survival (PFS) between patients with high and low BMI. BMI < 24.0 kg/m2 was defined as low BMI, and tumour regression grade 1-2 was defined as complete tumour response. RESULTS: Low BMI was observed in 74 (58.7%) patients and complete tumour response was found in 27 (21.4%) patients. The rate of complete tumour response was significantly higher in patients with low BMI (29.7% vs 9.6%, P = 0.007). Multivariate analysis revealed that low BMI [odds ratio (OR) = 4.56, 95% confidence interval (CI): 1.42-14.63, P = 0.011], targeted therapy with bevacizumab (OR = 3.02, 95%CI: 1.10-8.33, P = 0.033), preoperative carcinoembryonic antigen level < 10 ng/mL (OR = 3.84, 95%CI: 1.19-12.44, P = 0.025) and severe sinusoidal dilatation (OR = 0.17, 95%CI: 0.03-0.90, P = 0.037) were independent predictive factors for complete tumour response. The low BMI group exhibited a significantly longer median PFS than the high BMI group (10.7 mo vs 4.7 mo, P = 0.011). CONCLUSION: In CRLM patients receiving preoperative chemotherapy, a low BMI may be associated with better tumour response and longer PFS.
RESUMO
BACKGROUND: Colorectal cancer (CRC) has one of the highest morbidity and mortality rates among digestive tract tumors. Intra-abdominal infection (IAI) is a common postoperative complication that affects the clinical outcomes of patients with CRC and hinders their rehabilitation process. However, the factors influencing abdominal infection after CRC surgery remain unclear; further, prediction models are rarely used to analyze preoperative laboratory indicators and postoperative complications. AIM: To explore the predictive value of preoperative blood markers for IAI after radical resection of CRC. METHODS: The data of 80 patients who underwent radical resection of CRC in the Anorectal Surgery Department of Suzhou Hospital affiliated with Anhui Medical University were analyzed. These patients were categorized into IAI (n = 15) and non-IAI groups (n = 65) based on whether IAI occurred. Influencing factors were compared; general data and laboratory indices of both groups were identified. The relationship between the indicators was assessed. Further, a nomogram prediction model was developed and evaluated; its utility and clinical applicability were assessed. RESULTS: The risk factors for IAI after radical resection of CRC were neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and carcinoembryonic antigen (CEA) levels. NLR was correlated with PLR and SII (r = 0.604, 0.925, and 0.305, respectively), while PLR was correlated with SII (r = 0.787). The nomogram prediction model demonstrated an area under the curve of 0.968 [95% confidence interval (CI): 0.948-0.988] in the training set (n = 60) and 0.926 (95%CI: 0.906-0.980) in the validation set (n = 20). The average absolute errors of the calibration curves for the training and validation sets were 0.032 and 0.048, respectively, indicating a good model fit. The decision curve analysis curves demonstrated high net income above the 5% threshold, indicating the clinical practicality of the model. CONCLUSION: The nomogram model constructed using NLR, PLR, SII, and CEA levels had good accuracy and reliability in predicting IAI after radical resection of CRC, potentially aiding clinical treatment decision-making.
