ArticleCancers2024
Implementation and Evaluation of a Breast Cancer Disease Model Using Real-World Claims Data in Germany from 2010 to 2020.
Article in Cancers, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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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.
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Who cites it
6 citing papers in PubMed, 6 citations in OpenAlex.
- MMBCFNet: multi modal hybrid deep learning framework for breast cancer detection using MRI, mammography, and ultrasound images.Journal of ultrasound · 2026Article
- Real-world evidence from Germany: representativeness analysis and mortality endpoint validation in electronic health record-derived oncology cohorts.BMC cancer · 2026Article
- High Adherence to Adjuvant Endocrine Therapy Improves Outcome in Early Breast Cancer - Results from a Large Real-World Claims Data Analysis in Germany.Geburtshilfe und Frauenheilkunde · 2026Article
- Impact of adjuvant endocrine therapy utilization in male patients with early breast cancer: results from a large German real-world claims data analysis.Archives of gynecology and obstetrics · 2025Article
- Breast Cancer and Mental Health: Incidence and Influencing Factors-A Claims Data Analysis from Germany.Cancers · 2024Article
- Adverse Obstetric Outcomes after Breast Cancer Diagnosis: An Observational Database Study in Germany.Cancers · 2024Article
Corrections and comments
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Authors and funding
17 authors at 3 institutions in 1 country.
Funding
Abstract
Breast cancer is the leading cause of cancer-related mortality among women in Germany and worldwide. This retrospective claims data analysis utilizing data from AOK Baden-Wuerttemberg, a major statutory German health insurance provider, aimed to construct and assess a real-world data breast cancer disease model. The study included 27,869 female breast cancer patients and 55,738 age-matched controls, analyzing data from 2010 to 2020. Three distinct breast cancer stages were analyzed: Stage A (early breast cancer without lymph node involvement), Stage B (early breast cancer with lymph node involvement), and Stage C (primary distant metastatic breast cancer). Tumor subtypes were estimated based on the prescription of antihormonal or HER2-targeted therapy. The study established that 77.9% of patients had HR+ breast cancer and 9.8% HER2+; HR+/HER2- was the most common subtype (70.9%). Overall survival (OS) analysis demonstrated significantly lower survival rates for stages B and C than for controls, with 5-year OS rates ranging from 79.3% for stage B to 35.4% for stage C. OS rates were further stratified by tumor subtype and stage, revealing varying prognoses. Distant recurrence-free survival (DRFS) analysis showed higher recurrence rates in stage B than in stage A, with HR-/HER2- displaying the worst DRFS. This study, the first to model breast cancer subtypes, stages, and outcomes using German claims data, provides valuable insights into real-world breast cancer epidemiology and demonstrates that this breast cancer disease model has the potential to be representative of treatment outcomes.
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Registered trials
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