Evidence map›Paper›PMID 41129144›Full record

ArticleJAMA oncology2025

Risk Prediction Model for Development of Heart Failure or Cardiomyopathy After Breast Cancer Treatment.

Ana Barac, Jiling Chou, Nawar Shara, Lie H Chen, Jiaxiao Shi, Rowan T Chlebowski, Amrita Mukherjee, Reina Haque, Arnold L Potosky

Abstract read
In one paragraph

Article in JAMA oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors.

Ana BaracInova Schar Heart and Vascular, Fairfax, Virginia.
Jiling ChouMedStar Health Research Institute, Columbia, Maryland.
Nawar SharaMedStar Health Research Institute, Columbia, Maryland.
Lie H ChenDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena.
Jiaxiao ShiDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena.
Rowan T ChlebowskiThe Lundquist Institute, Torrance, California.
Amrita MukherjeeDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena.
Reina HaqueDepartment of Research & Evaluation, Kaiser Permanente Southern California, Pasadena.
Arnold L PotoskyCancer Prevention and Control Program, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.

Funding

Tissue Culture Shared ResourceP30CA051008 · NCI · GEORGETOWN UNIVERSITY · PI Louis M Weiner · 1990 to 2026
$71.5M
Risk prediction of breast cancer treatment-related cardiotoxicity to guide clinical decision makingR01HL154319 · NHLBI · KAISER FOUNDATION RESEARCH INSTITUTE · PI HAQUE, REINA, POTOSKY, ARNOLD L · 2020 to 2023
$1.5M
NCI NIH HHS P30 CA051008NHLBI NIH HHS R01 HL154319
6 · The paper itself

Abstract

Importance: Women receiving breast cancer (BC) treatment are at risk for heart failure or cardiomyopathy (HF/CM). No standard method exists to identify women at risk who might benefit from preventive cardiac strategies and surveillance during and after treatment. Objective: To develop and validate a model predicting the 10-year risk of developing HF/CM in women receiving systemic treatment for invasive early-stage BC to inform cardiac risk management. Design, Setting, and Participants: This longitudinal cohort study of patients cared for in Kaiser Permanente Southern California, a vertically integrated health care system. The goal of the study was to predict the 10-year HF/CM risk using multivariable elastic-net Cox proportional hazards models. Women aged 18 to 79 years with newly diagnosed invasive local or regional BC from 2008 to 2020, with a median follow-up of 5.2 years, were included. The cohort was randomly split into derivation (60%) and validation (40%) cohorts. Data were analyzed from April 2024 to May 2025. Exposures: HF/CM risk predictors included age at BC diagnosis, race and ethnicity, area-level socioeconomic status, local and systemic BC treatments, cancer stage, obesity, and history of hypertension, diabetes, hyperlipidemia, smoking, and other CV conditions. Main Outcome and Measures: Incident HF/CM events. Women were categorized into low-, moderate-, and high-risk groups based on the tertiles of the risk score in the derivation cohort. Results: Of 26 044 women included in the total cohort, the median (IQR) age was 61 (52-68) years. The risk model had good calibration and high accuracy in predicting HF/CM risk in the 3 subgroups, with HF/CM risk in the validation cohort matching the estimates from the derivation for identifying women at low risk (1.7%; 95% CI, 1.1%-2.4%) and high risk (19.4%; 95% CI. 17.3%-21.5%) of HF/CM at 10 years. The model's discrimination ability was good, based on the time-dependent area under the curve of 0.79 at 10 years in the validation cohort. Conclusions and Relevance: This risk prediction model among women with early-stage BC was able to prospectively identify those at risk of HF/CM over a 10-year period based on the selected BC treatment and clinical variables available at BC diagnosis. The model can be used to inform risk-guided cardiac management for these women.

Indexed as

Breast NeoplasmsCardiomyopathiesHeart FailureAdolescentAdultAgedFemaleHumansLongitudinal StudiesMiddle AgedProportional Hazards ModelsRisk AssessmentRisk FactorsYoung Adult

Identifiers

PMID41129144
PMCPMC12550738

What OpenQuestion 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 OpenQuestion graph.