PSA screening rate and prostate cancer mortality reduction in the province of Quebec

2005 ◽  
Vol 23 (16_suppl) ◽  
pp. 1023-1023
Author(s):  
B. Candas ◽  
F. Labrie
Keyword(s):  
Prostate Cancer ◽  
Cancer Mortality ◽  
Mortality Reduction ◽  
Screening Rate ◽  
Prostate Cancer Mortality ◽  
Psa Screening

Prostate cancer mortality reduction by screening: Power and time frame with complete enrollment in the European randomised screening for prostate cancer (ERSPC) trial

2001 ◽  
Vol 98 (2) ◽  
pp. 268-273 ◽  
Author(s):  
Harry J. de Koning ◽  
Michael K. Liem ◽  
Caroline A. Baan ◽  
Rob Boer ◽  
Fritz H. Schröder ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Mortality ◽  
Time Frame ◽  
Mortality Reduction ◽  
Prostate Cancer Mortality

scholarly journals Values and preferences of men for undergoing prostate-specific antigen screening for prostate cancer: a systematic review

BMJ Open ◽  
2018 ◽  
Vol 8 (9) ◽  
pp. e025470 ◽  
Author(s):  
Robin W M Vernooij ◽  
Lyubov Lytvyn ◽  
Hector Pardo-Hernandez ◽  
Loai Albarqouni ◽  
Carlos Canelo-Aybar ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Systematic Review ◽  
Prostate Specific Antigen ◽  
Cancer Mortality ◽  
Prostate Cancer Screening ◽  
Grey Literature ◽  
Specific Antigen ◽  
Risk Of Bias ◽  
Prostate Cancer Mortality ◽  
Psa Screening

ObjectivesTo investigate men’s values and preferences regarding prostate-specific antigen (PSA)-based screening for prostate cancer.DesignSystematic review.Data sourcesWe searched MEDLINE, EMBASE, PsycINFO and grey literature up to 2 September 2017.Eligibility criteriaPrimary studies of men’s values and preferences regarding the benefits and harms of PSA screening.Data extraction and synthesisTwo independent reviewers extracted data and assessed risk of bias with a modified version of a risk of bias tool for values and preferences studies, the International Patient Decision Aid Standards instrument V.3 and the Cochrane Collaboration risk of bias tool.ResultsWe identified 4172 unique citations, of which 11 studies proved eligible. Five studies investigated PSA screening using a direct choice study design, whereas six used decisions aids displaying patient-important outcomes. The direct choice studies used different methodologies and varied considerably in the reporting of outcomes. Two studies suggested that men were willing to forego screening with a small benefit in prostate cancer mortality if it would decrease the likelihood of unnecessary treatment or biopsies. In contrast, one study reported that men were willing to accept a substantial overdiagnosis to reduce their risk of prostate cancer mortality. Among the six studies involving decision aids, willingness to undergo screening varied substantially from 37% when displaying a hypothetical reduction in mortality of 10 per 1000 men, to 44% when displaying a reduction in mortality of 7 per 1000. We found no studies that specifically investigated whether values and preferences differed among men with family history, of African descent or with lower socioeconomic levels.ConclusionThe variability of men’s values and preferences reflect that the decision to screen is highly preference sensitive. Our review highlights the need for shared decision making in men considering prostate cancer screening.Trial registration numberCRD42018095585.

scholarly journals How Does Early Detection by Screening Affect Disease Progression?

2011 ◽  
Vol 31 (4) ◽  
pp. 550-558 ◽  
Author(s):  
Elisabeth M. Wever ◽  
Gerrit Draisma ◽  
Eveline A. M. Heijnsdijk ◽  
Harry J. de Koning
Keyword(s):  
Prostate Cancer ◽  
Cancer Screening ◽  
Early Detection ◽  
Cancer Mortality ◽  
Mortality Data ◽  
Mortality Reduction ◽  
Screening Effect ◽  
Cure Model ◽  
Prostate Cancer Mortality ◽  
Shift Model

Background. Simulation models are essential tools for estimating benefits of cancer screening programs. Such models include a screening-effect model that represents how early detection by screening followed by treatment affects disease-specific survival. Two commonly used screening-effect models are the stage-shift model, where mortality benefits are explained by the shift to more favorable stages, and the cure model, where early detection enhances the chances of cure from disease. Objective. This article describes commonly used screening-effect models and analyses their predicted mortality benefit in a model for prostate cancer screening. Method. The MISCAN simulation model was used to predict the reduction of prostate cancer mortality in the European Randomized Study of Screening for Prostate Cancer (ERSPC) Rotterdam. The screening-effect models were included in the model. For each model the predictions of prostate cancer mortality reduction were calculated. The study compared 4 screening-effect models, which are versions of the stage-shift model or the cure model. Results. The stage-shift models predicted, after a follow-up of 9 years, reductions in prostate cancer mortality varying from 38% to 63% for ERSPC-Rotterdam compared with a 27% reduction observed in the ERSPC. The cure models predicted reductions in prostate cancer mortality varying from 21% to 27%. Conclusions. The differences in predicted mortality reductions show the importance of validating models to observed trial mortality data. The stage-shift models considerably overestimated the mortality reduction. Therefore, the stage-shift models should be used with care, especially when modeling the effect of screening for cancers with long lead times, such as prostate cancer.

Re: Reconsidering Prostate Cancer Mortality – The Future of PSA Screening

2020 ◽  
Vol 78 (6) ◽  
pp. 929
Author(s):  
Marco Borghesi ◽  
Nazareno Suardi ◽  
Carlo Terrone
Keyword(s):  
Prostate Cancer ◽  
Cancer Mortality ◽  
Prostate Cancer Mortality ◽  
Psa Screening ◽  
The Future

scholarly journals Quantifying the role of PSA screening in the US prostate cancer mortality decline

2007 ◽  
Vol 19 (2) ◽  
pp. 175-181 ◽  
Author(s):  
Ruth Etzioni ◽  
Alex Tsodikov ◽  
Angela Mariotto ◽  
Aniko Szabo ◽  
Seth Falcon ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Mortality ◽  
Mortality Decline ◽  
Prostate Cancer Mortality ◽  
Psa Screening ◽  
The Us

scholarly journals Design-corrected variation by centre in mortality reduction in the ERSPC randomised prostate cancer screening trial

2016 ◽  
Vol 24 (2) ◽  
pp. 98-103 ◽  
Author(s):  
Matti Hakama ◽  
Sue M Moss ◽  
Ulf-Hakan Stenman ◽  
Monique J Roobol ◽  
Marco Zappa ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Ratio ◽  
Cancer Mortality ◽  
Prostate Cancer Screening ◽  
Target Population ◽  
Mortality Reduction ◽  
Randomised Study ◽  
Prostate Cancer Mortality ◽  
Specific Variation

Objectives To calculate design-corrected estimates of the effect of screening on prostate cancer mortality by centre in the European Randomised Study of Screening for Prostate Cancer (ERSPC). Setting The ERSPC has shown a 21% reduction in prostate cancer mortality in men invited to screening with follow-up truncated at 13 years. Centres either used pre-consent randomisation (effectiveness design) or post-consent randomisation (efficacy design). Methods In six centres (three effectiveness design, three efficacy design) with follow-up until the end of 2010, or maximum 13 years, the effect of screening was estimated as both effectiveness (mortality reduction in the target population) and efficacy (reduction in those actually screened). Results The overall crude prostate cancer mortality risk ratio in the intervention arm vs control arm for the six centres was 0.79 ranging from a 14% increase to a 38% reduction. The risk ratio was 0.85 in centres with effectiveness design and 0.73 in those with efficacy design. After correcting for design, overall efficacy was 27%, 24% in pre-consent and 29% in post-consent centres, ranging between a 12% increase and a 52% reduction. Conclusion The estimated overall effect of screening in attenders (efficacy) was a 27% reduction in prostate cancer mortality at 13 years’ follow-up. The variation in efficacy between centres was greater than the range in risk ratio without correction for design. The centre-specific variation in the mortality reduction could not be accounted for by the randomisation method.

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