External validation of a prediction model for pain and functional outcome after elective lumbar spinal fusion

European spine journal

article

Ayesha Quddusi¹  Hubert A. J. Eversdijk²  Anita M. Klukowska²  Marlies P. de Wispelaere⁴  Julius M. Kernbach⁵  Marc L. Schröder²  Victor E. Staartjes² 

[1] Center for Neuroscience, Queens University;Department of Neurosurgery, Bergman Clinics;School of Medicine, University of Nottingham;Department of Clinical Informatics, Bergman Clinics;Department of Neurosurgery, Faculty of Medicine, RWTH Aachen University;Amsterdam Movement Sciences, Vrije Universiteit Amsterdam;Machine Intelligence in Clinical Neuroscience Lab, Department of Neurosurgery, University Hospital Zurich, Clinical Neuroscience Centre, University of Zurich

关键词: Outcome prediction;    Lumbar fusion;    Patient-reported outcome;    External validation;    Predictive analytics;   

DOI  :  10.1007/s00586-019-06189-6

来源: Springer

【 摘 要 】

Patient-reported outcome measures following elective lumbar fusion surgery demonstrate major heterogeneity. Individualized prediction tools can provide valuable insights for shared decision-making. We externally validated the spine surgical care and outcomes assessment programme/comparative effectiveness translational network (SCOAP-CERTAIN) model for prediction of 12-month minimum clinically important difference in Oswestry Disability Index (ODI) and in numeric rating scales for back (NRS-BP) and leg pain (NRS-LP) after elective lumbar fusion. Data from a prospective registry were obtained. We calculated the area under the curve (AUC), calibration slope and intercept, and Hosmer–Lemeshow values to estimate discrimination and calibration of the models. We included 100 patients, with average age of 50.4 ± 11.4 years. For 12-month ODI, AUC was 0.71 while the calibration intercept and slope were 1.08 and 0.95, respectively. For NRS-BP, AUC was 0.72, with a calibration intercept of 1.02, and slope of 0.74. For NRS-LP, AUC was 0.83, with a calibration intercept of 1.08, and slope of 0.95. Sensitivity ranged from 0.64 to 1.00, while specificity ranged from 0.38 to 0.65. A lack of fit was found for all three models based on Hosmer–Lemeshow testing. The SCOAP-CERTAIN tool can accurately predict which patients will achieve favourable outcomes. However, the predicted probabilities—which are the most valuable in clinical practice—reported by the tool do not correspond well to the true probability of a favourable outcome. We suggest that any prediction tool should first be externally validated before it is applied in routine clinical practice. These slides can be retrieved under Electronic Supplementary Material.

【 授权许可】

Unknown