A novel equation and nomogram including body weight for estimating prostate volumes in men with biopsy-proven benign prostatic hyperplasia

Correlation between body mass index and prostate volume in benign prostatic hyperplasia patients undergoing holmium enucleation of the prostate surgery

Background

Benign prostatic obstruction (BPO) due to benign prostatic hyperplasia (BPH) is a leading cause of morbidity in men over the age of 40. This study examined whether there was an association between body mass index (BMI) and pre-operative prostate volume and whether expression of two genes, alpha-2-macroglobulin (A2M) and transforming growth factor beta 3 (TGFB3), was correlated with BMI, pre-operative prostate volume, and age at surgery.

Methods

Medical records of patients who underwent holmium enucleation of the prostate surgery for treatment of BPO were retrospectively reviewed. Surgical specimens were obtained from formalin-fixed paraffin-embedded blocks, and expression of the targeted genes was quantified using a real time PCR approach. Linear regression analysis was performed to assess association between BMI and prostate volume adjusting for demographic characteristics and co-morbidity. Spearman’s correlation was used to examine whether gene expression was correlated with BMI, prostate volume, and age at surgery.

Results

A total of 278 patients were identified, including 62.9% European Americans (n = 175) and 27.7% Hispanic Americans (n = 77). BMI was significantly correlated with prostate volume (Spearman’s rho = 0.123, P = 0.045). In linear regression analysis, BMI was positively associated with prostate volume (β = 0.01, P = 0.004), while hyperlipidemia was negatively associated with prostate volume (β = −0.08, P = 0.02). A trend for a positive association was also observed for diabetes (β = 0.07, P = 0.099). In the race/ethnicity stratified analysis, age at surgery showed a trend for significantly positive association with prostate volume in European Americans (β = 0.005, P = 0.08), but not in Hispanic Americans. Expression of the A2M gene in the stroma was negatively correlated with age at surgery (P = 0.006). A2M expression in the gland was positively correlated with prostate volume among older men (Age ≥ 70, P = 0.01) and overweight men (BMI 25–30, P = 0.04). TGFB3 expression in the gland was positively correlated with BMI (P = 0.007) among older men.

Conclusions

This study demonstrated the positive correlation between BMI and prostate volume. Expression of TGFB3 and A2M was correlated with BMI, prostate volume, and age at surgery.

Supplementary information

Supplementary information accompanies this paper at 10.1186/s12894-020-00753-9.

A Novel Calculator for Estimating Prostate Volume in Daily Urology Services

OBJECTIVES

To develop a simple prostate volume (PV) calculator that can aid in managing patients with lower urinary tract symptoms (LUTS) secondary to benign prostatic enlargement at daily urology services in developing Asian countries.

MATERIALS AND METHODS

We conducted a cross-sectional study of men aged above 40 years with no history of prostate cancer, prostate surgery, or 5α-reductase inhibitor treatment. Serum prostate-specific antigen (PSA) and total PV were measured in each subject. Potential sociodemographic and clinical variables including age, weight, comorbidities, and International Prostate Symptom Score (IPSS) were collected. Of 1034 subjects, 837 were used in building the PV calculator using regression analysis. The remaining 1/5 (n = 197) was used for model validation.

RESULTS

There were 1034 multiethnic Asian men (Chinese 52.9%, Malay 35.4%, and Indian 11.7%) with mean age of 60 ± 7.6 years. Average PV was 29.4 ± 13.0 mL while the overall mean of PSA was 1.7 ± 1.7 ng/mL. We identified age, IPSS, weight, and PSA (all P <.05) in the PV regression model. Using the validation set, the coefficient of determination (R²) of this PV calculator was 0.47 where PV = 20.6 + (age - 60) × 0.1 + (IPSS score) × 0.1 + (Weight - 70) × 0.3 + (history of alpha-blocker treatment for LUTS) × 9.6 + PSA × 3.7. The area under curve of this model in predicting PV above 30 mL and 40 mL were 0.82 (95% confidence interval, 0.75-0.88) and 0.91 (95% confidence interval, 0.87-0.96), respectively.

CONCLUSION

We develop a PV calculator that is simple and accurate to be used in routine clinical consultation for patients with LUTS. A separate study is important to confirm and to validate the findings in other populations.

Predicting the resected tissue weight from a digital rectal examination and total prostate specific antigen level before transurethral resection of the prostate

OBJECTIVE

To determine the use of the prostate specific antigen (PSA) level and digital rectal examination (DRE) findings to estimate the resected tissue weight (RTW) before transurethral resection of the prostate (TURP).

PATIENTS AND METHODS

We retrospectively analysed 983 patients who underwent TURP between December 2006 and December 2012. The primary outcome was the RTW required for clinical improvement, and was not associated with re-intervention. Age, PSA level, body mass index (BMI) and DRE findings were correlated and modelled with the RTW. The DRE result was defined as DREa (small vs. large) or DREb (small vs. moderate vs. large) according to the surgeon's report. Equations to calculate RTW were developed and tested using receiver operating characteristic (ROC) curve analyses.

RESULTS

There were significant correlations between PSA level (r = 0.4, P < 0.001) and RTW, whilst BMI and age showed weak correlations. The median (range) RTW was 45 (7-60) vs. 15 (6-60) g for small vs. large prostates (DREa) (P < 0.001), respectively. Similarly, the median (range) RTW was 11 (6-59) vs. 26.2 (6-60) vs. 42 (7-60) g in small vs. moderate vs. large prostates (DREb) (P < 0.001), respectively. Using PSA level and DREb (model 3) there was a significantly better ability to estimate RTW than using PSA and DREa (model 2) or PSA alone (model 1) based on ROC curve analyses. The equation developed by model 3 (RTW = 1.2 + (1.13 × PSA) + (DREb × 9.5)) had a sensitivity and specificity of 82% and 71% for estimating a RTW of >30 g, and 84% and 63% for estimating a RTW of >40 g, respectively.

CONCLUSIONS

The PSA level and DRE findings can be used to predict the RTW before TURP.