ArticleEuropean spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society2020
External validation of a prediction model for pain and functional outcome after elective lumbar spinal fusion.
Article in European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Generalisable prediction models for outcomes after lumbar spinal stenosis surgery: a model development and external validation study.EClinicalMedicine · 2026Article
- Predicting pediatric patient rehabilitation outcomes after spinal deformity surgery with artificial intelligence.Communications medicine · 2025Article
- Validity and accuracy of a machine learning predictive model in the exploitation of patient-related outcomes in spine surgery.Frontiers in surgery · 2025Article
- Multicenter external validation of prediction models for clinical outcomes after spinal fusion for lumbar degenerative disease.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2024Article
- Clinical Decision Support System Used in Spinal Disorders: Scoping Review.Journal of medical Internet research · 2024Article
- Development and temporal validation of clinical prediction models for 1-year disability and pain after lumbar decompressive surgery. The Norwich Lumbar Surgery Predictor (development version).European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2023Article
- Predictors of poor outcome following lumbar spinal fusion surgery: a prospective observational study to derive two clinical prediction rules using British Spine Registry data.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2023Observational
- Predicting patient-reported outcomes following lumbar spine surgery: development and external validation of multivariable prediction models.BMC musculoskeletal disorders · 2023Article
- Development of a machine-learning based model for predicting multidimensional outcome after surgery for degenerative disorders of the spine.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2022Article
- Prediction of outcome after spinal surgery-using The Dialogue Support based on the Swedish national quality register.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2022Article
- Validation of the ACS-NSQIP Risk Calculator: A Machine-Learning Risk Tool for Predicting Complications and Mortality Following Adult Spinal Deformity Corrective Surgery.International journal of spine surgery · 2021Article
- Prediction Models in Degenerative Spine Surgery: A Systematic Review.Global spine journal · 2021Article
- Robot-Guided Transforaminal Versus Robot-Guided Posterior Lumbar Interbody Fusion for Lumbar Degenerative Disease.Neurospine · 2021Article
- Machine learning in neurosurgery: a global survey.Acta neurochirurgica · 2020Article
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectivePatient-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.
methodsData 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.
resultsWe 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.
conclusionsThe 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.
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