Evidence map›Paper›PMID 41612656›Full record

ArticleJournal of breast cancer2026

Investigating Time-Varying Predictor Effects on Cardiovascular Outcomes in Breast Cancer Survivors.

Ingunn Fride Tvete, Marianne Klemp

Abstract read
In one paragraph

Article in Journal of breast cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

2 authors.

Ingunn Fride TveteDepartment of Statistical Modelling and Machine Learning, Norwegian Computing Center, Oslo, Norway. Ingunn.fride.tvete@nr.no.ORCID https://orcid.org/0000-0001-5798-5486
Marianne KlempDepartment of Pharmacology, The University of Oslo, Oslo, Norway.ORCID https://orcid.org/0000-0002-9530-8344

Funding

Regional Committees for Medical and Health Research Ethics 245944
6 · The paper itself

Abstract

purposeRelevant factors can have shifting prognostic impacts on cardiovascular disease (CVD) occurrences among in patients with breast cancer (BC) over time. CVD incidence and its driving factors vary among different CVDs. We examined the time to the first occurrence of heart attack, atrial fibrillation, embolic stroke, angina pectoris, embolism, peripheral vascular disease, and heart failure (HF). We particularly focused on the influence of molecular subtype, adjusting for age, tumor stage, and radiation therapy.

methodsThe 36,605 women diagnosed with BC from the Norwegian Cancer Registry were included. Cox regression analyses were performed for the first time for six CVDs, with death treated as a competing risk. The association between the time to first CVD diagnosis and the patient's molecular subtype was calculated. Because the Cox proportional hazard assumption was not met, a random survival forest (RSF) analysis was conducted.

resultsThe association between the time to the first CVD and the patient's molecular subtype differed for each CVD and was non-linear for HF. The time-varying cardiovascular risk in human epidermal growth factor receptor 2 (HER2)-positive versus HER2-negative breast cancer patients reflects differences in treatment, biology, and patient profiles. HER2-positive patients face early cardiotoxicity due to targeted therapies and are closely monitored, while HER2-negative patients, often older with higher baseline CVD risk, may experience delayed detection due to less routine cardiac surveillance. In ranking the factors with respect to their predictive importance for time to first HF, molecular subtype emerged as the second most important factor, followed by age.

conclusionTime to HF depends on the molecular subtype in a time-dependent manner. RSF analyses can identify complex relationships between predictors and survival without the Cox proportional hazard assumption, providing important insights into how patient and treatment factors are associated with time to CVD.

Indexed as

Breast NeoplasmsCardiovascular DiseasesDecision TreesMachine LearningSurvival Analysis

Identifiers

PMID41612656
PMCPMC12961319

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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.