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. 2022 Oct;13(5):2269-2281.
doi: 10.21037/jgo-22-410.

Development and validation of a nomogram based on neutrophil-to-lymphocyte ratio and fibrinogen-to-lymphocyte ratio for predicting recurrence of colorectal adenoma

Qijin He #  1 , Sanjun Du #  1 , Xu Wang #  1 , Jiani Liu  1 , Xin Xu  1 , Wentian Liu  1 , Jie Zhang  1 , Kui Jiang  1
Affiliations

Development and validation of a nomogram based on neutrophil-to-lymphocyte ratio and fibrinogen-to-lymphocyte ratio for predicting recurrence of colorectal adenoma

Qijin He et al. J Gastrointest Oncol. 2022 Oct.

Abstract

Background: There are many risk factors for the recurrence of colorectal adenoma (CRA). The purpose of this study was to explore the predictive performance of fibrinogen-to-lymphocyte ratio (FLR) and neutrophil-to-lymphocyte ratio (NLR) on the recurrence of CRA and to construct a predictive model.

Methods: This study analyzed the clinicopathological features of 421 CRA patients who underwent colonoscopy and adenectomy, and evaluated the recurrence of polyps under colonoscopy. Among them, 301 were training cohort and 120 were validation cohort. Multivariate logistic regression was used to identify independent risk factors associated with CRA recurrence. Established a nomogram model to predict the risk of recurrence in CRA patients using independent risk factors. The receiver operating characteristic (ROC) curves were used to verify the nomogram model discrimination. Calibration curves were used to verify the model calibration degree. The decision curve analysis (DCA) curves were used to verify the clinical efficacy of the nomogram model.

Results: Totally, six independent predictors, including smoking, diabetes, adenoma number, adenoma size, NLR, and FLR, were enrolled in the nomogram. In the training cohort and validation cohort, the area under the curve (AUC) of the nomogram for predicting the risk of CRA recurrence was 0.846 and 0.841, respectively. The calibration curves displayed a good agreement. DCA curves showed that this model had a high net clinical benefit.

Conclusions: Smoking, diabetes, adenoma number, adenoma size, NLR, and FLR were influencing factors for CRA recurrence.

Keywords: Colorectal adenoma (CRA); nomogram; recurrence; risk factors.

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Conflict of interest statement

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jgo.amegroups.com/article/view/10.21037/jgo-22-410/coif). The authors have no conflicts of interest to declare.

Figures

Figure 1
Figure 1
The ROC curve of markers for predicting recurrence of CRA. AUC, the area under the curve; NLR, neutrophil-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; LMR, lymphocyte-to-monocyte ratio; PNI, prognostic nutritional index; FLR, fibrinogen-to-lymphocyte ratio; ROC, receiver operating characteristic; CRA, colorectal adenoma.
Figure 2
Figure 2
Nomogram model for the prediction of recurrence after CRAs removed by colonoscopy. NLR, neutrophil-to-lymphocyte ratio; FLR, fibrinogen-to-lymphocyte ratio; CRA, colorectal adenoma.
Figure 3
Figure 3
ROC curves of nomogram model. (A) ROC curve of the model in the training cohort. (B) ROC curve of the model in the validation cohort. ROC, receiver operating characteristic; AUC, the area under the curve.
Figure 4
Figure 4
Calibration curves of the nomogram model. (A) Calibration curve of the model in the training cohort. (B) Calibration curve of the model in the validation cohort.
Figure 5
Figure 5
DCA for the nomogram model. The x-axis and y-axis represent the threshold probability and net benefit, respectively. The “Nomo” line represents the net benefit of nomogram model predicting the risk of adenoma recurrence. (A) DCA of the nomogram model for predicting the risk of adenoma recurrence in the training cohort. (B) DCA of the nomogram model for predicting the risk of adenoma recurrence in the validation cohort. DCA, decision curve analysis.
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