Predicting the Recurrence of Operable Cervical Cancer Patients Based on Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score and Classical Clinicopathological Parameters

Peng Jiang; Wei Kong; Chunxia Gong; Yanlin Chen; Fenglian Li; Lingya Xu; Yang Yang; Shikai Gou; Zhuoying Hu

doi:10.2147/JIR.S383742

Predicting the Recurrence of Operable Cervical Cancer Patients Based on Hemoglobin, Albumin, Lymphocyte, and Platelet (HALP) Score and Classical Clinicopathological Parameters

J Inflamm Res. 2022 Sep 12:15:5265-5281. doi: 10.2147/JIR.S383742. eCollection 2022.

Authors

Peng Jiang¹, Wei Kong¹, Chunxia Gong², Yanlin Chen³, Fenglian Li¹, Lingya Xu¹, Yang Yang¹, Shikai Gou¹, Zhuoying Hu¹

Affiliations

¹ Department of Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
² Department of Obstetrics and Gynecology, Women and Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.
³ Department of Pathology, Women and Children's Hospital of Chongqing Medical University, Chongqing, People's Republic of China.

Abstract

Objective: The purpose of this study was to evaluate the prognostic value of hemoglobin, albumin, lymphocyte, and platelet (HALP) score in patients with operable cervical cancer, and on this basis, combined with classical clinicopathological parameters to predict the recurrence of patients.

Methods: A total of 1580 patients with stage IA-IIA cervical cancer were randomly divided into training cohort (n=1054) and validation cohort (n=526) according to the predefined ratio of 2:1. In the training cohort, the receiver operating characteristic (ROC) curve and Youden index were used to determine the optimal threshold of HALP score for predicting cervical cancer recurrence. On this basis, the independent related factors with cervical cancer recurrence were screened through univariate and multivariate Cox regression analysis, and then a nomogram model was further established. The internal and external validation of the model was carried out in the training cohort and the validation cohort respectively through the consistency index (C-index) and calibration curve.

Results: ROC curve and Youden index showed that the optimal threshold of HALP score for predicting cervical cancer recurrence was 39.50. Multivariate analysis confirmed that HALP score and some other classic clinicopathological parameters were independently associated with cervical cancer recurrence. Based on the results of multivariate analysis, a nomogram model for predicting cervical cancer recurrence was successfully constructed. The internal and external calibration curves showed that the fitting degree of the model was good, and the C-index (the C-index of the training cohort and the validation cohort were 0.862 and 0.847, respectively) showed that the prediction accuracy of the model proposed in this study was better than other similar models.

Conclusion: HALP score may be a novel predictor for predicting the cervical cancer recurrence. Nomogram model based on HALP score and classical clinicopathological parameters can better predict the recurrence of cervical cancer.

Keywords: HALP score; cervical cancer; nomogram model; predict; recurrence.

Grants and funding

There is no funding to report.