Evidence map›Paper›PMID 41991871›Full record

ArticleBreast cancer research and treatment2026

External validation of PREDICT Breast v3.1 for overall survival in international cohorts, including young and invasive lobular subgroups.

Elfi M Verheul, Frank Doornkamp, Iurii Petrov, Sabine Siesling, Hester F Lingsma, Linetta B Koppert, Lara W A Vreven, Adri C Voogd, Maria Margarete Karsten, Lea Doppelbauer and 8 more

Abstract readValidation Study
In one paragraph

Article in Breast cancer research and treatment, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Elfi M VerheulCenter for Medical Decision Making, Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands. e.verheul@erasmusmc.nl.
Frank DoornkampBiomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
Iurii PetrovMicrobiology, Tumour- and Cell Biology Department, Karolinska Institutet, Stockholm, Sweden.
Sabine SieslingDepartment of Research, Netherlands Comprehensive Cancer Organization (IKNL), Utrecht, The Netherlands.
Hester F LingsmaCenter for Medical Decision Making, Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands.
Linetta B KoppertDepartment of Surgery, Erasmus MC Cancer Institute, Rotterdam, The Netherlands.
Lara W A VrevenDepartment of Epidemiology, Maastricht University, Maastricht, The Netherlands.
Adri C VoogdDepartment of Epidemiology, Maastricht University, Maastricht, The Netherlands.
Maria Margarete KarstenDepartment of Gynecology with Breast Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Lea DoppelbauerDepartment of Gynecology with Breast Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.
Pimrapat GebertBerlin Institute of Health at Charité -Universitätsmedizin Berlin, Berlin, Germany.
Narsis KianiDepartment of Oncology-Pathology, Center for Molecular Medicine, Karolinska Institutet, Solna, Sweden.
Simona BorstnarDepartment of Medical Oncology, Institute of Oncology Ljubljana, Ljubljana, Slovenia.
Paul D P PharoahDepartment of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
Elham HedayatiDepartment of Oncology-Pathology, Center for Molecular Medicine, Karolinska Institutet, Solna, Sweden.
Ewout W SteyerbergBiomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands.
David van KlaverenCenter for Medical Decision Making, Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands.
4D PICTURE Consortium

Funding

HORIZON EUROPE European Research Council 101057332
6 · The paper itself

Abstract

purposePREDICT Breast is an online tool that provides survival predictions for patients with early-stage breast cancer, for different treatments after surgery. External validation is essential to assess model performance across populations and healthcare settings. We aimed to externally validate PREDICT using clinical practice data from the Netherlands, Sweden, and Slovenia.

methodsWe validated PREDICT in national populations (Netherlands, N = 221,636; Sweden, N = 84,928) and in two specific subgroups: patients with invasive lobular breast cancer (ILC) (Netherlands, N = 26,834; Sweden, N = 10,563; Slovenia, N = 341) and patients aged ≤ 40 years (Netherlands, N = 9995; Sweden, N = 2694). We assessed discrimination with the 10-year area under the curve (AUC) and calibration of 10-year mortality predictions through calibration plots, intercepts and slopes.

resultsPREDICT v3.1 discriminated well in the national populations (Netherlands AUC 0.75, 95% CI 0.75-0.76; Sweden 0.75, 95% CI 0.75-0.76), with similar discrimination in ILC patients (Netherlands 0.76, 95% CI 0.74-0.76; Sweden 0.75, 95% CI 0.73-0.77; Slovenia 0.78, 95% CI 0.71-0.83). Calibration showed slight underestimation of mortality risk in the Netherlands (intercept 0.13; slope 1.01), and was near perfect in the Swedish population (intercept 0.04; slope 1.05). Amongst ILC patients, we observed some underestimation of mortality (Netherlands intercept 0.20; Sweden intercept 0.10; Slovenia intercept 0.02). In young patients, miscalibration was observed (Netherlands, intercept 0.21, slope 0.79; Sweden, intercept 0.08, slope 0.85).

conclusionPREDICT v3.1 is generally well calibrated and suitable for clinical use in the evaluated European populations. Efforts to improve PREDICT should focus on more accurate predictions for younger patients.

Indexed as

Breast NeoplasmsCarcinoma, LobularAdultAgedFemaleHumansMiddle AgedNeoplasm StagingNetherlandsPrognosisSloveniaSwedenBreast cancerExternal validationOverall survivalPREDICT breastPrediction model

Identifiers

PMID41991871
PMCPMC13086695

What Socratic holds

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Registered trials

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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 Socratic graph.