The association of smoking with urinary and sexual function recovery following radical prostatectomy for localized prostate cancer: a systematic review and meta-analysis.

BACKGROUND: Urinary and sexual dysfunction after radical prostatectomy remains a major cause of morbidity, despite widespread availability of pharmacological and rehabilitative treatments. Smoking is a modifiable risk factor known to correlate with erectile and urinary dysfunction and we hypothesise that smoking cessation may improve post-prostatectomy urinary and sexual function recovery. Our objective is to systematically evaluate literature describing the association of smoking status with urinary and sexual function in men following radical prostatectomy. METHODS: In total, 310 unique records were identified through a systematic search of the MEDLINE, EMBASE, Scopus, Web of Science, CINAHL and CENTRAL databases up to February 2023. Nine studies reported smoking status and post radical prostatectomy urinary and sexual function outcomes in men with localized prostate cancer. Risk of bias was assessed and meta-analysis included six studies. RESULTS: Smokers had inferior erectile function after prostatectomy compared to non-smokers (OR 0.73, [95% CI 0.56-0.95]) during follow-up, while urinary incontinence was not statistically different between groups (OR 1.20, [95% CI 0.75-1.91]). Smoking cessation improved the EPIC-26 sexual domain score with 6.6 points on average [p = 0.03] to a clinically significant maximum of 12.5 points at 18-24 months. CONCLUSIONS: Smoking is associated with impaired sexual function recovery after radical prostatectomy and quitting may improve sexual function >18 months. Current evidence shows no such association for urinary outcomes. Further studies are needed to corroborate findings.

Predicting post-radiation genitourinary hospital admissions in patients with localised prostate cancer.

PURPOSE: The risk of treatment-related toxicity is important for patients with localised prostate cancer to consider when deciding between treatment options. We developed a model to predict hospitalisation for radiation-induced genitourinary toxicity based on patient characteristics. METHODS: The prospective South Australian Prostate Cancer Clinical Outcomes registry was used to identify men with localised prostate cancer who underwent curative intent external beam radiotherapy (EBRT) between 1998 and 2019. Multivariable Cox proportional regression was performed. Model discrimination, calibration, internal validation and utility were assessed using C-statistics and area under ROC, calibration plots, bootstrapping, and decision curve analysis, respectively. RESULTS: There were 3,243 patients treated with EBRT included, of which 644 (20%) patients had a treated-related admission. In multivariable analysis, diabetes (HR 1.35, 95% CI 1.13-1.60, p < 0.001), smoking (HR 1.78, 95% CI 1.40-2.12, p < 0.001), and bladder outlet obstruction (BOO) without transurethral resection of prostate (TURP) (HR 7.49, 95% CI 6.18-9.08 p < 0.001) followed by BOO with TURP (HR 4.96, 95% CI 4.10-5.99 p < 0.001) were strong independent predictors of hospitalisation (censor-adjusted c-statistic = 0.80). The model was well-calibrated (AUC = 0.76). The global proportional hazards were met. In internal validation through bootstrapping, the model was reasonably discriminate at five (AUC 0.75) years after radiotherapy. CONCLUSIONS: This is the first study to develop a predictive model for genitourinary toxicity requiring hospitalisation amongst men with prostate cancer treated with EBRT. Patients with localised prostate cancer and concurrent BOO may benefit from TURP before EBRT.

Evaluation of selective bone scan staging in prostate cancer - external validation of current strategies and decision-curve analysis.

BACKGROUND: Recommendations for staging newly diagnosed prostate cancer patients vary between guidelines and literature. METHODS: Our objective was to validate and compare prediction models selecting newly diagnosed prostate cancer patients for bone scan staging. To achieve this, we validated eleven models in a population-based cohort of 10,721 patients diagnosed with prostate cancer between 2005 and 2019. The primary outcome was net-benefit. This was assessed at different balances of conservatism and tolerance, represented by preference ratio and number-willing-to-test (NWT). Secondary outcomes included calibration slope, calibration-in-the-large (intercept), and discrimination measured by Area-under-the-receiver-operator-characteristics curve (AUC). RESULTS: For preference ratios less than 1:39 (NWT greater than 40), scanning everyone provided greater net-benefit than selective staging. For preference ratios 1:39 to 3:97 (NWT 33-40), the European Association of Urology (EAU) 2020 guideline recommendation was the best approach. For preference ratios 3:97-7:93 (NWT 14-33), scanning EAU high-risk patients only was preferable. For preference ratios 7:93-1:9 (NWT 10-13), scanning only Gnanapragasam Group 5 patients was best. All models had similar fair discrimination (AUCs 0.68-0.80), but most had poor calibration. CONCLUSIONS: We identified three selective staging strategies that outperformed all other approaches but did so over different ranges of conservatism and tolerance. Scanning only EAU high-risk patients provided the greatest net-benefit over the greatest range of preference ratios and scenarios, but other options may be preferable depending upon the local healthcare system's degree of conservatism and tolerance.