ArticleEuropean radiology2026
Diagnostic accuracy of a 'stage-gated' approach for reporting prostate screening MRI: "Is less more?"
Article in European radiology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03702439 (Prostate Cancer Screening Trial Using A Group of Radiological Approaches Including MRI and Ultrasound), which is not on this map. Not yet cited in PubMed.
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.
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.
Prostate Cancer Screening Trial Using A Group of Radiological Approaches Including MRI and Ultrasound
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
- Commented on by
Authors and funding
17 authors.
Funding
Abstract
objectivesTo evaluate whether a two-step, 'stage-gated' reporting approach could improve the positive predictive value (PPV) of biparametric (bp)MRI for prostate cancer (PCa) screening compared to conventional Likert/PI-RADS scoring. MATERIALS AND
methodsThis retrospective secondary analysis utilised data from IP1-PROSTAGRAM-a prospective, population-based study of men aged 50-69 years who underwent PCa screening with bpMRI, ultrasound and prostate-specific antigen (PSA) testing between October 2018 and May 2019 at two centres (NCT03702439). MRI scans from IP1-PROSTAGRAM were retrospectively evaluated using the 'stage-gated' approach: three radiologists independently reviewed limited MRI sequences (axial T2-weighted and b1500 diffusion-weighted images) and classified scans as positive or negative; if positive, the remaining bpMRI images were reviewed and a hypothetical "decision-to-biopsy" made. The PPV of 'stage-gated' reading was compared to PI-RADS and Likert scores ≥ 4 from the original IP1-PROSTAGRAM bpMRI reports. The reference standard was IP1-PROSTAGRAM biopsy results with grade group (GG) ≥ 2 cancer considered significant.
resultsOf 408 participants (median age 57 years [IQR 53, 61]), 405 had MRI scans available for secondary analysis. The prevalence of GG ≥ 2 cancer was 4% (17/405). The 'stage-gated' reporting approach achieved a PPV of 53% (95% CI: 30, 75; 8/15), compared to 29% (95% CI: 15, 47; 8/28) and 30% (95% CI: 17, 46; 11/37) for Likert and PI-RADS ≥ 4 pathways, respectively. The 'stage-gated' approach halved the number of recommended biopsies while maintaining similar cancer detection rates.
conclusionThe 'stage-gated' reporting approach, using limited sequences for the initial read, may improve the PPV and benefit-to-harm ratio of MRI-based screening. KEY POINTS: Question The PPV of MRI in PCa screening is low, likely because conventional assessment systems are not optimised for low disease prevalence populations. Findings A two-step, 'stage-gated' reading approach achieved a PPV of 53% (8/15), compared to 29% (8/28) for Likert and 30% (11/37) for PI-RADS scores ≥ 4. Clinical relevance The 'stage-gated' reporting approach, which uses limited sequences for the initial read, may improve the PPV and benefit-to-harm ratio of MRI-based screening by reducing unnecessary biopsies. Prospective evaluation is needed to confirm these findings in real-world screening settings.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.