Evidence map›Paper›PMID 41918024›Full record

ArticleBreast cancer research : BCR2026

PREDICT v3.0 outperforms v2.2 in young (25-40 years) breast cancer patients according to real-world data from a large Swedish population-based registry.

Christine Lundgren, Irma Frediksson, Antonios Valachis, Daniel Robert Smith

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Article in Breast cancer research : BCR, 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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Christine LundgrenDepartment of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden. christine.lundgren@liu.se.
Irma FredikssonDepartment of Breast, Endocrine Tumors and Sarcoma, Karolinska University Hospital, Stockholm, Sweden.
Antonios Valachis *Department of Oncology, Faculty of Medicine and Health, Örebro University Hospital, Örebro, Sweden.
Daniel Robert Smith *Clinical Epidemiology and Biostatistics, Faculty of Medicine and Health, School of Medical Sciences, Örebro University, Örebro, Sweden.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundPREDICT is a widely used prognostic tool supporting treatment decisions in breast cancer care. As v3.0 was recently released, we performed an external validation of PREDICT v2.2 and v3.0 in young (≤ 40 years) breast cancer patients.

methodsWe included Swedish non-metastatic breast cancer patients aged ≤ 40 years, diagnosed between 2008–2019, from a registry-based research database. Outcomes were all-cause and breast cancer-specific mortality (BCSM) at 5- and 10-years, in all and in prespecified patient subgroups (by molecular subtype and nodal status). Model calibration and discrimination were evaluated by the integrated calibration index (ICI) and time dependant area under the receiver operator curve (tdAUC), respectively.

resultsIn total, 3015 patients were included. PREDICT v2.2 consistently overestimated both all-cause mortality and BCSM at 5- (ICI all-cause mortality = 5.10%, 95% confidence interval (CI) 4.93–5.27; ICIBCSM = 4.91%, 95% CI 4.71–5.13) and 10- years (ICI all-cause mortality = 9.75%, 95% CI 9.02%–10.5, ICIBCSM = 9.71%, 95% CI 8.88–10.4). In contrast, PREDICT v3.0 showed much better calibration (5 years; ICI all-cause mortality = 0.69%, 95% CI 0.60–0.78; ICIBCSM = 0.65%, 95% CI 0.57– 0.73; 10 years; ICI all-cause mortality = 5.10%, 95% CI 4.65–5.5%; ICIBCSM = 4.76%, 95% CI 4.31–5.19), although miscalibration remained in high-risk groups. Discrimination was excellent for predicting 5-year outcomes in both models but declined for 10-year predictions.

conclusionsPREDICT showed good discrimination in young patients. Although version 3.0 showed better calibration than v2.2, risk overestimation in high-risk patients may affect treatment decision-making and warrants cautious interpretation.

Indexed as

Breast NeoplasmsAdultFemaleHumansPrediction AlgorithmsPrognosisRegistriesSwedenBreast cancerPREDICT modelPrognosisYoung patients

Identifiers

PMID41918024
PMCPMC13064026

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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 OpenQuestion graph.