Damaged Masculinity: How Honor Endorsement Can Influence Prostate Cancer Screening Decision-Making and Prostate Cancer Mortality Rates

Prior research has established factors that contribute to the likelihood that men seek out prostate cancer screenings. The current study addresses how endorsing the ideology found in cultures of honor may serve as a barrier to prostate cancer screenings. Two studies were conducted which analyzed the impact of stigma on men’s decisions to seek out prostate cancer screenings (Study 1) as well as how prostate cancer deaths may be higher in the culture of honor regions due to men’s reticence to seek out screenings (Study 2). Results suggest that older, honor-endorsing men are less likely to have ever sought out a prostate cancer screening due to screening stigma and that an honor-oriented region (southern and western United States) displays higher rates of prostate cancer death than a non-honor-oriented region (northern United States). These findings suggest that honor may be a cultural framework to consider when practitioners address patients’ screening-related concerns.

The prostate tissue-based telomere biomarker as a prognostic tool for metastasis and death from prostate cancer after prostatectomy

ABSTRACTPurposeCurrent biomarkers are inadequate prognostic predictors in localized prostate cancer making treatment decision-making challenging. Previously, we observed that the combination of more variable telomere length among prostate cancer cells and shorter telomere length in prostate cancer-associated stromal cells – the telomere biomarker – is strongly associated with progression to metastasis and prostate cancer death after prostatectomy independent of currently used pathologic indicators.Experimental DesignWe optimized our method allowing for semi-automated telomere length determination in single cells in fixed tissue, and tested the telomere biomarker in tissue microarrays from five cohort studies of men surgically treated for clinically localized disease (N=2,255). We estimated the relative risk (RR) of progression to metastasis (N=311) and prostate cancer death (N=85) using models appropriate to each study’s design adjusting for age, prostatectomy stage, and tumor grade, which then we meta-analyzed using inverse variance weights.ResultsCompared with men who had less variable telomere length among prostate cancer cells and longer telomere length in prostate cancer-associated stromal cells, men with the combination of more variable and shorter telomere length, had 3.76-times the risk of prostate cancer death (95% CI 1.37-10.3; p=0.01) and had 2.23-times the risk of progression to metastasis (95% CI 0.99-5.02, P=0.05). The telomere biomarker was associated with prostate cancer death in men with intermediate risk disease (Grade Groups 2/3: RR=9.18, 95% CI 1.14- 74.0, p=0.037) and with PTEN intact tumors (RR=6.74, 95% CI 1.46-37.6, p=0.015).ConclusionsThe telomere biomarker is robust and associated with poor outcome independent of current pathologic indicators in surgically-treated men.Translational RelevanceCurrent prognostic biomarkers in localized prostate cancer are inadequate imperfect predictors; therefore, new biomarkers are needed to improve the prognostic classification and management of these patients. In a five-cohort study, we confirmed that the tissue-based telomere biomarker – the combination of more variable telomere length among prostate cancer cells and shorter telomere length in prostate cancer-associated stromal cells – was associated with progression to metastasis and prostate cancer death independent of currently used prognostic indicators after prostatectomy for clinically-localized disease. Importantly, the telomere biomarker was associated with poor outcome in men with intermediate risk disease, as well as in men with intact PTEN tumors. Thus, this tissue-based telomere biomarker has the translational potential to improve treatment and surveillance decision-making.

Adiposity and risk of prostate cancer death: a prospective analysis in UK Biobank and meta-analysis of published studies

IntroductionThe association of adiposity with prostate cancer specific mortality remains unclear. We examined how adiposity and its distribution relates to fatal prostate cancer by analysing data from UK Biobank, and conducting a dose-response meta-analysis to integrate existing prospective evidence. We also described the cross-sectional associations in UK Biobank of commonly used adiposity measurements with indices of adiposity estimated by imaging.Methods218,246 men from UK Biobank who were free from cancer at baseline were included and participants were followed-up via linkage to health administrative datasets. Body mass index (BMI), total body fat percentage (using bioimpedance), waist circumference (WC) and waist-to-hip ratio (WHR) were collected at recruitment. Risk of dying from prostate cancer (primary cause) by the different adiposity measurements was estimated using multivariable-adjusted Cox proportional hazards models. Results from this and other prospective cohort studies were combined in a dose-response meta-analysis.ResultsIn UK Biobank, 631 men died from prostate cancer over a mean follow-up of 11.5 years. The hazard ratios (HR) for prostate cancer death were 1.10 (95% confidence interval=1.00-1.21) per 5 kg/m2 higher BMI, 1.03 (0.96-1.11) per 5% increase in total body fat percentage, 1.09 (1.02-1.18) per 10 cm increase in WC, and 1.09 (1.02-1.16) per 0.05 increase in WHR. Our meta-analyses of prospective studies included 22,106 prostate cancer deaths for BMI, 642 for body fat percentage, 3,153 for WC and 1,611 for WHR, and the combined HRs for dying from prostate cancer for the increments above were 1.10 (1.08-1.13), 1.03 (0.96-1.11), 1.08 (1.04-1.12), and 1.07 (1.02-1.12), respectively. In up to 4,800 UK Biobank participants with magnetic resonance imaging and dual-energy X-ray absorptiometry, BMI and WC were strongly associated with imaging estimations of total and central adiposity (e.g. visceral fat, trunk fat), with associations marginally larger for WC. There might be ∼1000 fewer prostate cancer deaths per year in the UK if the mean BMI in men was reduced by 5 kg/m2.ConclusionOverall, we found that men with higher total and central adiposity had similarly higher risks of prostate cancer death, which may be biologically driven or due to differences in detection. In either case, these findings provide further reasons for men to maintain a healthy body weight.

Predicting cause of death from free-text health summaries: development of an interpretable machine learning tool

Purpose: Accurately assigning cause of death is vital to understanding health outcomes in the population and improving health care provision. Cancer-specific cause of death is a key outcome in clinical trials, but assignment of cause of death from death certification is prone to misattribution, therefore can have an impact on cancer-specific trial mortality outcome measures. Methods: We developed an interpretable machine learning classifier to predict prostate cancer death from free-text summaries of medical history for prostate cancer patients (CAP). We developed visualisations to highlight the predictive elements of the free-text summaries. These were used by the project analysts to gain an insight of how the predictions were made. Results: Compared to independent human expert assignment, the classifier showed >90% accuracy in predicting prostate cancer death in test subset of the CAP dataset. Informal feedback suggested that these visualisations would require adaptation to be useful to clinical experts when assessing the appropriateness of these ML predictions in a clinical setting. Notably, key features used by the classifier to predict prostate cancer death and emphasised in the visualisations, were considered to be clinically important signs of progressing prostate cancer based on prior knowledge of the dataset. Conclusion: The results suggest that our interpretability approach improve analyst confidence in the tool, and reveal how the approach could be developed to produce a decision-support tool that would be useful to health care reviewers. As such, we have published the code on GitHub to allow others to apply our methodology to their data (https://zenodo.org/badge/latestdoi/294910364).

Active surveillance of postradical prostatectomy biochemical recurrence: Long-term assessment of outcomes.

5081 Background: Biochemical recurrence (BCR) following radical prostatectomy (RP) is an unreliable predictor of distant metastatic progression/prostate cancer death, resulting in potential complications & expenses of overtreatment. Little has been published on management decisions & outcomes of active surveillance (AS). We characterize our long term experience with AS following post-RP BCR without radiation/androgen deprivation therapy. Methods: From June 2002 - September 2019, 1865 men underwent RP. 406 experienced BCR; of these, 138 (34%) were observed without treatment intervention. BCR defined as PSA>0.2 ng/dl, x2. PSAs checked every 1-3 months and entered into a PSADT graph. Men were considered to be formally AS after 3+ years of increasing DT following RP. Men with decreasing DT were treated and censored. Results: The table depicts demographics of the AS patients; median follow-up was 7.3 years (IQR: 4.6-10.6) post-RP. Of patients on AS, average age was 63.7 +/- 7.2 years and 86%, 48%, 40%, 51% and 14% were GG 1 through 5, respectively. Current DT of AS patients averages 20 months, with 0% PCSM. Only 10% of patients with decreasing DT began treatment after average 4 years following BCR. Conclusions: Of 406 patients experiencing post-RP BCR, 34% of patients are effectively managed with AS, with 0% PCSM across all GG. Presently 69 (50%) AS men have been under observation for 7.3 to 18 years. This suggests that significant portion of patients display benign recurrence, characterized by increasing DT following BCR and can be managed safely with observation alone.[Table: see text]

Prostate cancer prognosis after initiation of androgen deprivation therapy among statin users. A population-based cohort study

Purpose Statins’ cholesterol-lowering efficacy is well-known. Recent epidemiological studies have found that inhibition of cholesterol synthesis may have beneficial effects on prostate cancer (PCa) patients, especially patients treated with androgen deprivation therapy (ADT). We evaluated statins’ effect on prostate cancer prognosis among patients treated with ADT. Materials and methods Our study population consisted of 8253 PCa patients detected among the study population of the Finnish randomized study of screening for prostate cancer. These were limited to 4428 men who initiated ADT during the follow-up. Cox proportional regression model adjusted for tumor clinical characteristics and comorbidities was used to estimate hazard ratios for risk of PSA relapse after ADT initiation and prostate cancer death. Results During the median follow-up of 6.3 years after the ADT initiation, there were 834 PCa deaths and 1565 PSA relapses in a study cohort. Statin use after ADT was associated with a decreased risk of PSA relapse (HR 0.73, 95% CI 0.65–0.82) and prostate cancer death (HR 0.82; 95% CI 0.69–0.96). In contrast, statin use defined with a one-year lag (HR 0.89, 95% CI 0.76–1.04), statin use before ADT initiation (HR 1.12, 95% CI 0.96–1.31), and use in the first year on ADT (HR 1.02, 95% CI 0.85–1.24) were not associated with prostate cancer death, without dose dependency. Conclusion Statin use after initiation of ADT, but not before, was associated with improved prostate cancer prognosis.

Common genetic and clinical risk factors: Association with fatal prostate cancer in the Cohort of Swedish Men.

65 Background: Clinical variables (age, family history, and genetics) are commonly used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores, including PHS, are associated with all prostate cancer and are not specific for fatal cancers, PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to available clinical variables improves associations with prostate cancer death. Methods: Genotype and phenotype data were obtained from a nested case-control subset (n=3,279; 2,163 were diagnosed with prostate cancer, 278 died of prostate cancer) of the longitudinal, population-based Cohort of Swedish Men. PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes history, and body mass index) were independently tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models were constructed with clinical variables and PHS. Log-likelihood tests compared models. Results: Median age at last follow-up and at prostate cancer death were 78.0 (IQR: 72.3-84.1) and 81.4 (75.4-86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95% CI 2.78-4.17]), family history (HR 1.72 [1.46-2.03]), alcohol intake (HR 1.74 [1.40-2.15]), and diabetes (HR 0.53 [0.37-0.75]) were each associated with prostate cancer death. A multivariable clinical model including PHS46 improved associations for fatal disease ( p<10−15). On multivariable analysis, PHS46 (HR 2.45 [1.99-2.97]), family history (HR 1.73 [1.48-2.03]), alcohol intake (HR 1.45 [1.19-1.76]), and diabetes (HR 0.62 [0.42-0.90]) all remained associated with prostate cancer death. Similar results were found using the newer PHS166. Conclusions: PHS had the most robust association with fatal prostate cancer in a multivariable model with common clinical risk factors, including family history. Adding PHS to clinical variables may improve individualized prostate cancer risk stratification strategies.

Common genetic and clinical risk factors: Association with fatal prostate cancer in the Cohort of Swedish Men

Background: Clinical variables--age, family history, genetics--are used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores are associated with all prostate cancer (not specific for fatal cancers), PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to clinical variables improves associations with prostate cancer death. Methods: Genotype/phenotype data were obtained from a nested case-control Cohort of Swedish Men (n=3,279; 2,163 with prostate cancer, 278 prostate cancer deaths). PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes, body mass index) were tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models with/without PHS were compared with log-likelihood tests. Results: Median age at last follow-up/prostate cancer death were 78.0 (IQR: 72.3-84.1) and 81.4 (75.4-86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95%CI 2.78-4.17]), family history (HR 1.72 [1.46-2.03]), alcohol (HR 1.74 [1.40-2.15]), diabetes (HR 0.53 [0.37-0.75]) were each associated with prostate cancer death. On multivariable analysis, PHS46 (HR 2.45 [1.99-2.97]), family history (HR 1.73 [1.48-2.03]), alcohol (HR 1.45 [1.19-1.76]), diabetes (HR 0.62 [0.42-0.90]) all remained associated with fatal disease. Including PHS46 or PHS166 improved multivariable models for fatal prostate cancer (p<10-15). Conclusions: PHS had the most robust association with fatal prostate cancer in a multivariable model with common risk factors, including family history. Impact: Adding PHS to clinical variables may improve prostate cancer risk stratification strategies.