The predictive value of serum inflammatory markers for the severity of cervical lesions

Abstract Objective Exploring the predictive value of NLR, PLR, MLR, and SII for the severity of cervical cancer screening abnormalities in patients. Methods A retrospective analysis was conducted on the data of 324 patients suspected of cervical lesions due to abnormal TCT and/or HPV in our hospital from January 2023 to December 2023, who underwent colposcopy. The pathological results of colposcopic biopsy confirmed that there were 140 cases of chronic cervicitis, which classified as the group without cervical lesions. The cervical lesion group included 184 cases, including 91 cases of LSIL, 71 cases of HSIL, and 22 cases of cervical cancer. Compared the differences in preoperative peripheral blood NLR, PLR, MLR, and SII among different groups of patients, and evaluated their predictive value for the severity of cervical lesions using Receiver Operating Characteristic (ROC) curves. Results The levels of NLR, PLR, and SII in the group without cervical lesions were lower than those in the group with cervical lesions ( p 0.05). The comparison of NLR among LSIL, HSIL, and cervical cancer groups showed statistically significant differences ( p 0.05). The AUC of peripheral blood NLR, PLR, and SII for predicting cervical lesions were 0.569, 0.582, and 0.572, respectively. The optimal cutoff values were 2.3,176.48, and 603.56. The sensitivity and specificity were 38.6% and 73.6%, 28.8% and 85.7%, 37.5% and 76.4%, respectively. At the same time, the joint testing of the three had the highest efficiency, with sensitivity of 69% and specificity of 45%. Conclusion Although the peripheral blood NLR, PLR, and SII of the cervical lesions patients were higher than those without cervical lesions in cervical cancer screening abnormal patients, the predictive ROC curve discrimination was low. Therefore, it is not recommended to use preoperative peripheral blood inflammatory markers as markers for cervical cancer screening abnormal patient diversion.