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Updated: Sep 25, 2026
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Cardiovascular events and mortality after breast cancer diagnosis: multistate models in a nationwide cohort study
Ingunn Fride Tvete1, Marianne Klemp2
1Statistical Modelling and Machine Learning, Norwegian Computing Center, Oslo, Norway ingunn.fride.tvete@nr.no.
Objective:
To study the progression of newly diagnosed breast cancer patients towards cardioembolic disorders (CDs) and ischaemic or structural heart disease (ISH) within a multistate framework that includes death as an absorbing state, in order to evaluate long-term cardiovascular burden and to examine whether the observed patterns may reflect short-term acute events or longer-term effects potentially associated with treatment. CD and ISH occurrences following breast cancer treatment may have different underlying biological mechanisms, potentially leading to different survival patterns across patient groups defined by breast cancer characteristics, and we sought to explore this.
Design:
Two continuous-time multistate Markov models described patients' transitions among three states: time of breast cancer diagnosis, first occurrence of CD or ISH, and death, depending on patients' molecular subtype, tumour stage, age and radiation treatment status.
Participants:
Altogether 36 778 patients from the Norwegian Cancer Registry, linked with information on cardiovascular events from the Norwegian Patient Registry, diagnosed earliest in 2006, followed until their first cardiovascular event and/or death or throughout 2020.
Results:
HR-/HER2- patients had the highest HR for a first CD event compared with HR+/HER2- patients (HR 1.51, 95% CI 1.39 to 1.65), with no significant differences observed between the remaining groups. For first ISH event, HR-/HER2+, HR+/HER2+ and HR-/HER2- patients had HRs of 1.91 (95% CI 1.61 to 2.27), 1.64 (95% CI 1.43 to 1.88) and 1.56 (95% CI 1.44 to 1.69), respectively, compared with HR+/HER2- patients.
Conclusions:
Long-term cardiovascular burden for patients with breast cancer may be more strongly influenced by chronic vascular and myocardial damage, likely driven by treatment-related cardiotoxicity and cumulative exposure compared with acute thromboembolic mechanisms. A multistate Markov modelling approach proved valuable for capturing the dynamics for patients to move between the states breast cancer diagnosis, CD or ISH event and death, and may guide more tailored follow-up and use of cardioprotective strategies.
