Intervention-related Deaths in the European Randomized Study of Screening for Prostate Cancer

Which men benefit from prostate cancer screening? Prostate cancer mortality by subgroup in the European Randomised Study of Screening for Prostate Cancer

OBJECTIVE

To evaluate whether a subgroup of men can be identified that would benefit more from screening than others.

MATERIALS AND METHODS

This retrospective cohort study was based on three European Randomised Study of Screening for Prostate Cancer (ERSPC) centres, Finland, the Netherlands and Sweden. We identified 126 827 men aged 55-69 years in the study who were followed for maximum of 16 years after randomisation. The primary outcome was prostate cancer (PCa) mortality. We analysed three age groups 55-59, 60-64 and 65-69 years and PCa cases within four European Association of Urology (EAU) risk groups: low, intermediate, high risk, and advanced disease.

RESULTS

The hazard ratio (HR) for PCa mortality in the screening arm relative to the control arm for men aged 55-59 years was 0.96 (95% confidence interval [CI] 0.75-1.24) in Finland, 0.70 (95% CI 0.44-1.12) in the Netherlands and 0.42 (95% CI 0.24-0.73) in Sweden. The HR for men aged 60-64 years was 1.03 (95% CI 0.77-1.37) in Finland, 0.76 (95% CI 0.50-1.16) in the Netherlands and 0.97 (95% CI 0.64-1.48) in Sweden. The HR for men aged 65-69 years was 0.80 (95% CI 0.62-1.03) in Finland and 0.57 (95% CI 0.38-0.83) in the Netherlands, and this age group was absent in Sweden. In the EAU risk group analysis, PCa mortality rates were materially lower for men with advanced disease at diagnosis in all three countries: 0.67 (95% CI 0.56-0.82) in Finland, 0.28 (95% CI 0.18-0.44) in the Netherlands, and 0.48 (95% CI 0.30-0.78) in Sweden.

CONCLUSION

We were unable to unequivocally identify the optimal age group for screening, as mortality reduction differed among centres and age groups. Instead, the screening effect appears to depend on screening duration, and the number and frequency of screening rounds. PCa mortality reduction by screening is largely attributable to stage shift.

Metabolic analysis using HR-MAS in prostate tissue for prostate cancer diagnosis

INTRODUCTION

In this study we used nuclear magnetic resonance spectroscopy in prostate tissue to provide new data on potential biomarkers of prostate cancer in patients eligible for prostate biopsy.

MATERIAL AND METHODS

Core needle prostate tissue samples were obtained. After acquiring all the spectra using a Bruker Avance III DRX 600 spectrometer, tissue samples were subjected to routine histology to confirm presence or absence of prostate cancer. Univariate and multivariate analyses with metabolic and clinical variables were performed to predict the occurrence of prostate cancer.

RESULTS

A total of 201 patients, were included in the study. Of all cores subjected to high-resolution magic angle spinning (HR-MAS) followed by standard histological study, 56 (27.8%) tested positive for carcinoma. According to HR-MAS probe analysis, metabolic pathways such as glycolysis, the Krebs cycle, and the metabolism of different amino acids were associated with presence of prostate cancer. Metabolites detected in tissue such as citrate or glycerol-3-phosphocholine, together with prostate volume and suspicious rectal examination, formed a predictive model for prostate cancer in tissue with an area under the curve of 0.87, a specificity of 94%, a positive predictive value of 80% and a negative predictive value of 84%.

CONCLUSIONS

Metabolomics using HR-MAS analysis can uncover a specific metabolic fingerprint of prostate cancer in prostate tissue, using a tissue core obtained by transrectal biopsy. This specific fingerprint is based on levels of citrate, glycerol-3-phosphocholine, glycine, carnitine, and 0-phosphocholine. Several clinical variables, such as suspicious digital rectal examination and prostate volume, combined with these metabolites, form a predictive model to diagnose prostate cancer that has shown encouraging results.