Predictive modeling for score translation among patient-reported outcome measures in chronic rhinosinusitis with nasal polyps: a cross-sectional study
Predictive modeling among PRO questionnaires in CRSwNP is both feasible and clinically impactful. These models facilitate the translation of scores between instruments, thus enhancing clinical decision-making, streamlining patient assessments, and supporting data harmonization in multicentric and longitudinal studies. Future research should pursue external and longitudinal validations to ensure broader applicability and reliability of these predictive tools.
Authors
- Rafael Lomas‐Vega (ORCID: https://orcid.org/0000-0003-2546-6301)
- María Soledad Sánchez‐Torices
- Javier Modesto García‐Fernández (ORCID: https://orcid.org/0000-0002-0200-051X)
- M A Montilla-Ibáñez (ORCID: https://orcid.org/0000-0001-8997-0844)
- M A Feliz-Fernández
Institutions
- Universidad de Jaén (ES)
- Complejo Hospitalario de Jaén (ES)
Publication Details
- Journal
- European Archives of Oto-Rhino-Laryngology
- Published
- 2025-06-18
- DOI
- https://doi.org/10.1007/s00405-025-09446-1
- Citations
- 2
- Primary Topic
- Sinusitis and nasal conditions
- Type
- article
- Field-Weighted Citation Impact
- 3.70
Funders
- Universidad de Jaén