Multivariate logistic regression analysis of the clinical factors influencing locally advanced prostate cancer

对影响局部晚期前列腺癌的临床因素进行多因素logistic回归分析

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Abstract

BACKGROUND: Locally advanced prostate cancer (PCa) carries a high risk of recurrence and metastasis after surgery, and the prognosis is poor. We explored the risk factors for locally advanced PCa among clinical factors (neutrophil: lymphocyte ratio, lymphocyte: monocyte ratio) and indicators of systemic inflammation [prostate-specific antigen (PSA) level, Gleason score, body mass index (BMI)] through retrospective evaluation of patients with PCa diagnosed at our center. The pathologic T stage was a key indicator of locally advanced PCa. METHODS: Data from patients with pathologically confirmed PCa at our center from 1 January 2015 to 1 May 2020 were collected in strict accordance with inclusion and exclusion criteria. Clinical data were collected and the relationship between the indicators and the pathologic T stage was explored. First, Spearman rank correlation analysis was used to find the correlates of the pathologic T stage. Then, logistic ordered multiple regression analysis was used to identify independent risk factors. Finally, receiver operating characteristic (ROC) curves were used to assess the diagnostic accuracy for the T stage of PCa. RESULTS: After rigorous screening, the data of 177 patients were obtained. Spearman correlation analysis showed that BMI, the PSA level, Gleason score, hypertension, N stage, and M stage were significantly correlated with the T stage (P<0.05), suggesting that these factors may be involved in locally advanced PCa. Analyses of ROC curves showed that the PSA level [area under the ROC curve (AUC) =0.802] had greater value than BMI (0.675) for the diagnosis of the pathologic T stage PCa, and that a combination of BMI and PSA (combined AUC =0.822) could improve locally advanced PCa diagnosis. CONCLUSIONS: BMI and PSA are independent risk factors for locally advanced PCa. They may play a key part in locally advanced PCa.

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