Value of a diagnostic model based on composite inflammatory and nutritional indicators in predicting early colorectal cancer

Objective To construct a diagnostic model based on composite inflammatory and nutritional indicators for early colorectal cancer, and to evaluate the predictive value of the model. Methods The patients who underwent colonoscopy and received treatment in The Affiliated Hospital of Qingdao University from January 2019 to April 2021 were enrolled as the training set, and according to their lesions, they were divided into early colorectal cancer group with 106 patients and precancerous lesion group with 244 patients. The patients who underwent colonoscopy and received treatment in The Affiliated Hospital of Qingdao University from May to October 2021 were enrolled as the validation set and were divided into early colorectal cancer group with 22 patients and precancerous lesion group with 30 patients. The two groups of patients in the training set were compared in terms of clinical features, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), fibrinogen-to-prealbumin ratio (FPR), fibrinogen-to-albumin ratio (FAR), and prognostic nutritional index (PNI), and the independent risk factors for early colorectal cancer were analyzed. A diagnostic model for early colorectal cancer was constructed, and the receiver operating characteristic (ROC) curve was used to assess the diagnostic efficacy of the model. The Hosmer-Lemeshow test was used to assess the degree of fitting of the model, and the model was assessed in the validation set. ResultsIn the training set, the early colorectal cancer group had significantly higher NLR, PLR, MLR, and FPR than the precancerous lesion group (Z=-5.269--2.917,P<0.05). The multivariate logistic regression analysis showed that NLR>1.71, PLR>169.47, and FPR>11.25 were independent risk factors for early colorectal cancer (P<0.05). The diagnostic model constructed for the diagnosis of early colorectal cancer in the training set had an area under the ROC curve (AUC) of 0.697, and the Hosmer-Lemeshow test showed that the model had a good degree of fitting (P>0.05). In the validation set, the diagnostic model had an AUC of 0.727 in the diagnosis of patients with early colorectal cancer, and the Hosmer-Lemeshow test showed that the model had a good degree of fitting (P>0.05). Conclusion NLR>1.71, PLR>169.47, and FPR>11.25 are independent risk factors for early colorectal cancer, and the diagnostic model for early colorectal cancer based on NLR, PLR, and FPR has a relatively high predictive value.