Evidence map›Paper›PMID 28651567›Full record

ArticleBMC public health2017

Benefits and harms of prostate cancer screening - predictions of the ONCOTYROL prostate cancer outcome and policy model.

Nikolai Mühlberger, Kristijan Boskovic, Murray D Krahn, Karen E Bremner, Willi Oberaigner, Helmut Klocker, Wolfgang Horninger, Gaby Sroczynski, Uwe Siebert

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.6field-weighted citation impact, top 16% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 12 citations in OpenAlex.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Review
  7. Article
  8. Prostate cancer screening-when to start and how to screen?Translational andrology and urology · 2018
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Nikolai MühlbergerInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall i.T, Austria.
Kristijan BoskovicInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall i.T, Austria.
Murray D KrahnToronto Health Economics and Technology Assessment (THETA) Collaborative, University of Toronto, Toronto, ON, Canada.
Karen E BremnerToronto General Research Institute, Toronto General Hospital, Toronto, ON, Canada.
Willi OberaignerCancer Registry of Tyrol, Tirol Kliniken GmbH, Innsbruck, Austria.
Helmut KlockerDepartment of Urology, Medical University of Innsbruck, Innsbruck, Austria.
Wolfgang HorningerDepartment of Urology, Medical University of Innsbruck, Innsbruck, Austria.
Gaby SroczynskiInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall i.T, Austria.
Uwe SiebertInstitute of Public Health, Medical Decision Making and Health Technology Assessment, Department of Public Health, Health Services Research and Health Technology Assessment, UMIT - University for Health Sciences, Medical Informatics and Technology, Eduard-Wallnoefer-Zentrum 1, A-6060, Hall i.T, Austria. public-health@umit.at.
Innsbruck Medical University · ATToronto General Hospital · CATirol Kliniken · AT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundA recent recalibration of the ONCOTYROL Prostate Cancer Outcome and Policy (PCOP) Model, assuming that latent prostate cancer (PCa) detectable at autopsy might be detectable by screening as well, resulted in considerable worsening of the benefit-harm balance of screening. In this study, we used the recalibrated model to assess the effects of familial risk, quality of life (QoL) preferences, age, and active surveillance.

methodsMen with average and elevated familial PCa risk were simulated in separate models, differing in familial risk parameters. Familial risk was assumed to affect PCa onset and progression simultaneously in the base-case, and separately in scenario analyses. Evaluated screening strategies included one-time screening at different ages, and screening at different intervals and age ranges. Optimal screening strategies were identified depending on age and individual QoL preferences. Strategies were additionally evaluated with active surveillance by biennial re-biopsy delaying treatment of localized cancer until grade progression to Gleason score ≥ 7.

resultsScreening men with average PCa risk reduced quality-adjusted life expectancy (QALE) even under favorable assumptions. Men with elevated familial risk, depending on age and disutilities, gained QALE. While for men with familial risk aged 55 and 60 years annual screening to age 69 was the optimal strategy over most disutility ranges, no screening was the preferred option for 65 year-old men with average and above disutilities. Active surveillance greatly reduced overtreatment, but QALE gains by averted adverse events were opposed by losses due to delayed treatment and additional biopsies. The effect of active surveillance on the benefit-harm balance of screening differed between populations, as net losses and gains in QALE predicted for screening without active surveillance in men with average and familial PCa risk, respectively, were both reduced.

conclusionsAssumptions about PCa risk and screen-detectable prevalence significantly affect the benefit-harm balance of screening. Based on the assumptions of our model, PCa screening should focus on candidates with familial predisposition with consideration of individual QoL preferences and age. Active surveillance may require treatment initiation before Gleason score progression to 7. Alternative active surveillance strategies should be evaluated in further modeling studies.

Indexed as

Quality-Adjusted Life YearsQuality of LifeAgedAge FactorsBiopsyDisease ProgressionDisease SusceptibilityEarly Detection of CancerFamilyHumansLife ExpectancyMaleMass ScreeningMiddle AgedModels, BiologicalNeoplasm Grading

Identifiers

PMID28651567
PMCPMC5485506
OpenAlexW2720883134

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.