Risk Stratification in Colorectal Cancer: Nomograms Utilizing Inflammatory Factors and Immunological Hematological Indicators

Author:

Tang Jiadai1,Xiang Mengying1,Xiong Guangrui2,Liao Yedan1,Shen Xin1,Li Rong1,Zhang Ke3,Li Zhengting1,Xia Tingrong1,Xie Lin1

Affiliation:

1. The Third Affiliated Hospital of Kunming Medical University, Yunnan Cancer Hospital, Pekin University Cancer Hospital Yunnan

2. Lincang People's Hospital

3. Baoshan People's Hospital

Abstract

Abstract

Background Cancer-associate inflammation and immunological hematological indicators could regard as contributing factors to promote for the progression of solid tumors. Methods This study aimed to construct nomograms with inflammatory factors and immunological hematological parameters to predict the prognosis of colorectal cancer (CRC). Results The training cohort had a 66.25% prediction rate for distant metastasis. Nomograms were created to predict distant metastasis, overall survival (OS), and progression-free survival (PFS) using clinicopathologic features, inflammatory factors, and immunologic hematological indicators as baseline, and the consistency index (C index) scores of the three nomograms were 0.791 (95% CI, 0.745–0.838), 0.752 (95% CI, 0.699–0.806), and 0.687 (95% CI, 0.647–0.726) respectively. The consistency index (C index) scores for the three nomograms were 0.791 (95% CI, 0.745–0.838), 0.752 (95% CI, 0.699–0.806), and 0.687 (95% CI, 0.647–0.726), respectively. Calibration graphs demonstrated a good correlation between predicted and actual prognostic rates. Decision curve analysis (DCA) curves demonstrated that the predictive models had potential for clinical application. Subgroup analyses showed that the nomograms were favorable prognostic indicators for stage I-IV CRC patients(P < 0.05). Conclusion Single or combined hematological indicators are easy to obtain, feasible, and of high prognostic predictive values, so the nomograms constructed on the basis of cancer-associate inflammatory factors and immunological hematological indicators had good accuracies in predicting distant metastasis, OS and PFS in CRC patients, which could help clinicians to conduct risk stratification in CRC patients and assist in treatment decision-making, achieve better oncological outcomes ultimately.

Publisher

Springer Science and Business Media LLC

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