Development And Validation Of A Nomogram Including Lymphocyte-to-monocyte Ratio For Prostate Cancer Risk

Objective: Lymphocyte-to-monocyte ratio(LMR),one of the systemic inflammatory biomarkers,is reported to be involved in cancer detection and prognosis.Hence,we investigated the diagnostic value of LMR in initial prostate biopsy.A prostate cancer(PCa)risk nomogram including LMR was developed,and internal and external validation were furtherly conducted.Methods: 2509 patients from Fudan University Shanghai Cancer Center(the training set: 70%;internal verification set: 30%)and the Affiliated Hospital of Qingdao University(external verification set)who underwent initial prostate biopsy were enrolled in the study.WBC and differential leukocyte count,PSA and other clinicopathologic characteristics were collected.A PCa prediction model was developed on the training set.Significant risk factors with P<0.10 in multivariate logistic regression models were used to generate a nomogram.Discrimination,calibration and clinical usefulness of the model were assessed using Cindex,calibration plot and decision curve analysis(DCA).The nomogram was re-examined with the internal validation set and external validation set.Similarly,to explore the diagnostic value of LMR in clinically significant PCa(csPCa)and in patients with PSA 4-10 ng/ml,a nomogram was developed and furtherly validated.Results: Predictors in the PCa risk nomogram included age,PSA,digital rectal examination(DRE),abnormal imaging signals,PSA density(PSAD)and LMR.The model displayed good discrimination and calibration with C-index 0.830 [95% confidence interval(CI): 0.812-0.852],and the nomogram was furtherly validated by the internal and the independent external validation sets.The nomogram exhibited better performance compared to the nomogram with PSA only and the nomogram with LMR excluded.Similarly,the nomogram for csPCa risk included six predictors: age,PSA,DRE,abnormal imaging signals,PSAD and LMR.The model displayed good calibration and discrimination with C-index 0.828 [95% CI: 0.829-0.867].The model can provide individualized cs PCa risk prediction.The nomogram predicting PCa risk in patients with PSA 4-10 ng/ml included 4 predictors: age,DRE,f/t PSA and LMR.The nomogram also displayed good prediction performance(C-index: 0.734,95% CI: 0.708-0.760).The model can assess the PCa risk for patients in the grey zone and provide precise plan in individualized treatment.Conclusions: Here we conducted a double center retrospective study.This nomogram incorporating age,PSA,DRE,abnormal imaging signals,PSAD and LMR could be used to facilitate individual PCa and csPCa risk prediction in initial prostate biopsy.In addition,a nomogram incorporating age,f/t PSA,DRE and LMR was developed for PCa detection in patients with PSA 4-10 ng/ml.These nomograms exhibit good discrimination,calibration and clinical usefulness.This is the first nomogram including LMR,one of the systemic inflammatory biomarkers.This nomogram will help to predict cancer risk and make clinical decisions with suspicious PCa.