Jonas Subelack

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Subelack
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Jonas
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jonas.subelack@unisg.ch
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    Item type:Publication,
    Risk factors for interval breast cancer: insights from a decade of a mammography screening program
    (Springer Science and Business Media LLC, 2025-02-12)
    Jonas Subelack  
    ;
    Rudolf Morant
    ;
    Marcel Blum  
    ;
    Alena Eichenberger
    ;
    Alexander Geissler  
    Purpose Breast cancer remains a major global health issue, with mammography screening programs (MSPs) being critical for early detection to improve survival. Interval breast cancers (IBC) are an important quality criterion and have been linked with increased mortality. We aimed to identify risk factors for IBC diagnoses, based on MSP data. Methods In this retrospective cohort study, we merged data from the Swiss MSP “donna” with data from cancer registries from 2010 to 2019 to categorize cases as IBC or screen-detected breast cancer (SBC). We compared the incidence, tumor characteristics, and survival proportions of women with IBC versus SBC. We used a multivariable Poisson regression with robust errors to identify risk factors for IBC diagnoses. Results We identified 1134 breast cancer cases, specifically 251 IBC and 883 SBC. The 7-year survival proportions significantly deviated with 92.9% for women with IBC and 96.4% for women with SBC (p < 0.05). Women with IBC are diagnosed with significantly higher tumor stages (p < 0.05) and have a worse tumor biology in multiple dimensions e.g. larger tumor size or more often triple negative (p < 0.05). Higher breast density (BI-RADS d risk ratio (RR): 3.293), certain age groups (55–59 years RR: 1.345), and a family breast cancer history (RR: 1.299) were identified as significant (p < 0.05) risk factors for IBC diagnoses. Conclusions Women with IBC had lower overall survival proportions than women with SBC, possibly due to higher stages at diagnosis. Increased breast density and a positive family history of breast cancer could encourage MSPs to personalize their screening process (e.g. additional diagnostics).
    Type:journal article
    Journal:Breast Cancer Research and Treatment
    DOI:10.1007/s10549-025-07619-4
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/121984
    Scopus© Citations 2
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    Item type:Publication,
    The possible benefit of artificial intelligence in an organized population-related screening program : Initial results and perspective
    (2024-07-17)
    Morant, R
    ;
    Gräwingholt, A
    ;
    Jonas Subelack  
    ;
    David Kuklinski  
    ;
    Justus Vogel  
    Mammography screening programs (MSP) have shown that breast cancer can be detected at an earlier stage enabling less invasive treatment and leading to a better survival rate. The considerable numbers of interval breast cancer (IBC) and the additional examinations required, the majority of which turn out not to be cancer, are critically assessed. In recent years companies and universities have used machine learning (ML) to develop powerful algorithms that demonstrate astonishing abilities to read mammograms. Can such algorithms be used to improve the quality of MSP? The original screening mammographies of 251 cases with IBC were retrospectively analyzed using the software ProFound AI® (iCAD) and the results were compared (case score, risk score) with a control group. The relevant current literature was also studied. The distributions of the case scores and the risk scores were markedly shifted to higher risks compared to the control group, comparable to the results of other studies. Retrospective studies as well as our own data show that artificial intelligence (AI) could change our approach to MSP in the future in the direction of personalized screening and could enable a significant reduction in the workload of radiologists, fewer additional examinations and a reduced number of IBCs; however, the results of prospective studies are needed before implementation
    Type:journal article
    Journal:Die Radiologie
    DOI:10.1007/s00117-024-01345-6
    URI:https://www.alexandria.unisg.ch/handle/20.500.14171/120596
    Scopus© Citations 2