A predictive model for identifying patients with colorectal cancer from benign polyps based on the serum PLR and PLR-CEA-CA199 score

Author:

Cai Lulu1,Chen Ni1,Qiu Xinze1,Zeng Xinya1,Huang Jiean1,Liu Shiquan1

Affiliation:

1. The Second Affiliated Hospital of Guangxi Medical University

Abstract

Abstract Background Inflammatory responses play an important role in tumor initiation, invasion and metastasis. Platelet-to-lymphocyte ratio (PLR) can reflect systemic inflammation of colorectal cancer (CRC), CEA and CA199 have been known as the simple diagnostic tumor biomarkers for CRC. This study aims to investigate the diagnostic values of PLR, construct a novel PLR-CEA-CA199 (PCC) score, and develop a predictive model for identifying patients with CRC from benign polyps. Methods A total of 333 patients with CRC and 461 patients with benign polyps were selected as subjects retrospectively. The diagnostic performances of PLR and PCC score were estimated by receiver operating characteristic curve (ROC). Univariate and multivariate logistic regression analyses were used to determine risk predictors for the identification of CRC. Finally, a predictive model was established, and whose predictive efficacy was evaluated. Results Results showed that PLR levels and PCC score were significantly different between CRC and benign polyps (P < 0.05). ROC curve analysis showed the diagnostic predictive efficacy of PCC score (AUC = 0.735) was superior to PLR, CEA, CA199, CEA-CA199 (CCI) and PLR-CEA(PCI) score. Multivariate logistic regression analysis showed that four valid parameters including age, maximum tumor size, white blood cell counts (WBC) and PCC score, were suitable to construct a diagnostic predictive model for the identification of CRC (AUC = 0.970, Sen = 90.0%, and Spe = 96.6%). Moreover, the predictive efficacy is also remarkable in distinguishing the advanced CRC from early-stage CRC (AUC = 0.892, Se = 91.0%, and Sp = 78.6%). Conclusions PCC score is an effective indicator to distinguish CRC from benign polyps. Additionally, the predictive model based on four parameters (Age, Maximum tumor size, WBC and PPC score) shows excellent accuracy in identifying patients with CRC from benign polyps, and patients with the advanced CRC from early-stage CRC.

Publisher

Research Square Platform LLC

Reference39 articles.

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