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Prognostic value of B-score for predicting joint replacement in the context of osteoarthritis phenotypes: Data from the osteoarthritis initiative.
Saxer, F; Demanse, D; Brett, A; Laurent, D; Mindeholm, L; Conaghan, P G; Schieker, M.
Afiliación
  • Saxer F; Novartis Biomedical Research, Novartis Campus, 4002, Basel, Switzerland.
  • Demanse D; Medical Faculty, University of Basel, 4002, Basel, Switzerland.
  • Brett A; Novartis Pharma AG, 4002, Basel, Switzerland.
  • Laurent D; Imorphics, Worthington House, Towers Business Park, Wilmslow Road, Manchester, M20 2HJ, UK.
  • Mindeholm L; Novartis Biomedical Research, Biomarker Development, 4002, Basel, Switzerland.
  • Conaghan PG; Novartis Biomedical Research, Novartis Campus, 4002, Basel, Switzerland.
  • Schieker M; Leeds Institute of Rheumatic & Musculoskeletal Medicine, University of Leeds and NIHR Leeds Biomedical Research Centre, UK.
Osteoarthr Cartil Open ; 6(2): 100458, 2024 Jun.
Article en En | MEDLINE | ID: mdl-38495348
ABSTRACT

Objective:

Developing new therapies for knee osteoarthritis (KOA) requires improved prediction of disease progression. This study evaluated the prognostic value of clinical clusters and machine-learning derived quantitative 3D bone shape B-score for predicting total and partial knee replacement (KR).

Design:

This retrospective study used longitudinal data from the Osteoarthritis Initiative. A previous study used patients' clinical profiles to delineate phenotypic clusters. For these clusters, the distribution of B-scores was assessed (employing Tukey's method). The value of both cluster allocation and B-score for KR-prediction was then evaluated using multivariable Cox regression models and Kaplan-Meier curves for time-to-event analyses. The impact of using B-score vs. cluster was evaluated using a likelihood ratio test for the multivariable Cox model; global performances were assessed by concordance statistics (Harrell's C-index) and time dependent receiver operating characteristic (ROC) curves.

Results:

B-score differed significantly for the individual clinical clusters (p â€‹< â€‹0.001). Overall, 9.4% of participants had a KR over 9 years, with a shorter time to event in clusters with high B-score at baseline. Those clusters were characterized clinically by a high rate of comorbidities and potential signs of inflammation. Both phenotype and B-score independently predicted KR, with better prediction if combined (P â€‹< â€‹0.001). B-score added predictive value in groups with less pain and radiographic severity but limited physical activity.

Conclusions:

B-scores correlated with phenotypes based on clinical patient profiles. B-score and phenotype independently predicted KR surgery, with higher predictive value if combined. This can be used for patient stratification in drug development and potentially risk prediction in clinical practice.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Osteoarthr Cartil Open Año: 2024 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Osteoarthr Cartil Open Año: 2024 Tipo del documento: Article País de afiliación: Suiza Pais de publicación: Reino Unido