Age, height, BMI and FBG predict prostate volume in ageing benign prostatic hyperplasia: Evidence from 5285 patients

Abstract

Aims Several studies have reported a potential association between prostate volume (PV) and prostate disease. Here, we classified the risk factors for PV among benign prostatic hyperplasia (BPH) patients. Methods In all, 4293 BPH patients with available clinical information were enrolled. Body mass index (BMI) was obtained as weight divided by height squared. PV was calculated as length × width × height (cm) × π/6. Mann‐Whitney U tests were used to determine the differences between PV subgroups. Univariate and multiple linear regression tests were performed to uncover the connection between clinical features and PV. The differences in the age, BMI, height and fasting blood glucose (FBG) of the subgroups were evaluated by Kruskal‐Wallis tests and adjusted with Bonferroni post hoc correction. A nomogram was created to directly illustrate the mutual interaction of amalgamator parameters. Results PV did not influence the incidence of kidney stones (P = .815), whereas prostate calculi were positively associated with an enlarged prostate (>30 mL) (P < .001). Age (adjusted R = 0.363, P < .001), height (adjusted R = 0.088, P < .001), BMI (adjusted R = 0.039, P = .013) and FBG (adjusted R = −0.034, P = .027) were the independent risk/protective factors related to enlarged PV among BPH patients. The nomogram illustrated the predictive risk of an enlarged prostate (>30 mL) in men. The area under the ROC curve value was 0.659 in the training cohort and 0.677 in an internal validation cohort. Conclusions Age, height and BMI were positive independent risk factors of enlarged PV in BPH patients, and FBG had a protective role.

Relationship between serum indirect bilirubin and prostate volume in patients with benign prostatic hyperplasia: a cross-sectional study

“…And BMI was an important confounding factor in the PV-IBIL relationship (Tables 3-5). This finding is consistent with previous reports, indicating that higher BMI is an independent risk factor for BPH (27)(28)(29). Meanwhile, OS levels increased when BMI increased (30).…”

Triglyceride to high-density lipoprotein cholesterol ratio and total cholesterol to high-density lipoprotein cholesterol ratio and risk of benign prostatic hyperplasia in Chinese male subjects

“…Expensive MRI examination has also not found an increasingly wide utilization in detecting prostate except for patients with suspected prostate cancer. Herein, the criteria for inclusion in this trial are abdominal ultrasound imaging with no suspicion of prostate cancer, and the volume of the prostate is determined by height (cm) × width (cm) × length (cm) × π/6 based on the abdominal ultrasound measurements, the normal volume is 20–30 mL, the secretion of PSA is influenced by prostate volume size, so there is no special requirement for PSA levels ( 22 ). It is noteworthy that the individuals enrolled in the group had undergone health examinations for more than 2 years, which was helpful to exclude inappropriate candidates.…”

Nomogram for predicting the overall survival of patients with early‐onset prostate cancer: A population‐based retrospective study

“…Nomograms based on the TNM classification system in conjunction with other major clinical parameters have been widely accepted as a visible and accurate model for survival prediction in several tumors 13–15 . Our previous study also applied the nomogram to predict the enlarged prostate volume in benign prostatic hyperplasia and to predict PCa patients' prognosis with clinical features and infiltrated immunocytes 16,17 . Although some prognostic models for PCa have been published, they are not suitable for assessing the survival of early‐onset PCa patients 18–21 .…”

“… 13 , 14 , 15 Our previous study also applied the nomogram to predict the enlarged prostate volume in benign prostatic hyperplasia and to predict PCa patients' prognosis with clinical features and infiltrated immunocytes. 16 , 17 Although some prognostic models for PCa have been published, they are not suitable for assessing the survival of early‐onset PCa patients. 18 , 19 , 20 , 21 To fill this research gap, we first established a predictive nomogram to predict the OS of early‐onset PCa using data in the SEER database.…”