Abstract
Abstract Background: The relationship between neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in peripheral blood and prognosis after castration therapy for prostate cancer remains unclear. Methods: A total of 186 patients with prostate cancer treated between January 2018 and March 2021 were selected as the study subjects. All patients underwent castration therapy. Patient follow-up records for 2 years were examined to assess progression-free survival. NLR, PLR, and PSA levels were measured in the participants’ blood. Logistic regression analysis was used to identify factors affecting the occurrence of castration-resistant prostate cancer. Kaplan-Meier survival curves were plotted to analyze progression-free survival, and ROC curves were plotted to assess the predictive value of NLR and PLR for progression-free survival. Results: In the stable group, NLR, PLR, PSA levels, bone metastasis ratio, and Gleason score ≥8 were significantly lower than in the progression group. T3 stage, N0 stage, and M0 stage were significantly higher in the progression group, with statistical significance (P < 0.05). NLR, PLR, and PSA levels were all significantly linearly correlated (P < 0.05). High NLR, high PLR, high PSA, high bone metastasis, Gleason score <8, T3 stage, and N0 stage were independent risk factors for poor prognosis after castration therapy for prostate cancer, with statistical significance (P < 0.05). Patients with low NLR had significantly better progression-free survival than the high NLR group, and patients with low PLR had significantly better progression-free survival than the high PLR group, with statistical significance (P < 0.05). The area under the curve for NLR and PLR in predicting progression-free survival after castration therapy for prostate cancer was both greater than 0.90, indicating high clinical utility. Conclusion: Peripheral blood NLR and PLR after castration therapy for prostate cancer are highly correlated with patient prognosis quality and can serve as important potential indicators for predicting patient prognosis quality.
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