Background: Prurigo nodularis (PN) is a rare chronic inflammatory skin disease with a high disease burden, but data on clinical and economic burden are still scarce.
Objective: To describe the real-world epidemiologic, clinical and therapeutic characteristics and related economic burden of patients with PN compared to a benchmark population in Germany.
Methods: This retrospective study was based on an excerpt of German Statutory Health Insurance data of patients with an initial PN diagnosis between 2012 and 2016. PN cohort contained no record of PN in eight quarters before the index quarter and was followed up for eight quarters (unless deceased). Benchmark cohort without PN was calculated using direct standardization and 1:1 matching to PN cohort.
Results: Out of 4,536,002 insured patients, 2309 incident patients with PN were identified and matched to the benchmark cohort out of 3,018,382 patients without PN. Patients were mostly between 45 and 80 years when diagnosed with PN. Higher comorbidity rates were reported for PN than benchmark, with a rising disease burden at follow-up. Most patients with PN (91.3%) were diagnosed outpatient and had >50% more outpatient visits than the benchmark cohort. Hospitalization rates were higher in PN (53.9%) versus benchmark (35.1%), yielding twice longer mean hospital stays for PN (12 days) compared to benchmark (6 days) (p < 0.001). The most common initial therapy for patients with PN was topical corticosteroids (47.6%); ≥10% of patients were treated with antidepressants, antihistamines or systemic corticosteroids. Therapy rates were higher for PN compared to benchmark (p < 0.001). Mean initial costs were twofold higher in PN versus benchmark for outpatient, inpatient and drugs. During follow-up, an increase of >70% in mean PN costs compared to benchmark was identified for outpatient, inpatient and concomitant treatments (p < 0.001).
Conclusion: This study highlights the significantly higher clinical and economic burden incurred by PN compared to benchmark patients in Germany, reflecting the unmet medical need for PN.
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http://dx.doi.org/10.1111/jdv.19700 | DOI Listing |
Brief Bioinform
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College of Computer Science and Electronic Engineering, Hunan University, Changsha 410082, China.
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November 2024
Department of Electronic Engineering, Tsinghua University, 100084 Beijing, China.
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December 2024
Analytical Chemistry Group, Van 't Hoff Institute for Molecular Sciences, Science Park 904, the Netherlands; Centre for Analytical Sciences Amsterdam (CASA), Amsterdam, the Netherlands; AI4Science Lab, Informatics Institute, University of Amsterdam, Science Park 904, the Netherlands. Electronic address:
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January 2025
College of Artificial Intelligence, Nanjing Agricultural University, Weigang No.1, Nanjing, 210095, Jiangsu, China.
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View Article and Find Full Text PDFSci Rep
January 2025
School of Electromechanical Engineering, Guangdong University of Technology, Guangzhou, 510006, China.
Multi-objective and multi-stage decision-making problems require balancing multiple objectives at each stage and making optimal decision in multi-dimensional control variables, where the commonly used intelligent optimization algorithms suffer from low solving efficiency. To this end, this paper proposes an efficient algorithm named non-dominated sorting dynamic programming (NSDP), which incorporates non-dominated sorting into the traditional dynamic programming method. To improve the solving efficiency and solution diversity, two fast non-dominated sorting methods and a dynamic-crowding-distance based elitism strategy are integrated into the NSDP algorithm.
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