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Multicenter external validation of prediction models for clinical outcomes after spinal fusion for lumbar degenerative disease.

Authors :
Grob, Alexandra
Rohr, Jonas
Stumpo, Vittorio
Vieli, Moira
Ciobanu-Caraus, Olga
Ricciardi, Luca
Maldaner, Nicolai
Raco, Antonino
Miscusi, Massimo
Perna, Andrea
Proietti, Luca
Lofrese, Giorgio
Dughiero, Michele
Cultrera, Francesco
D'Andrea, Marcello
An, Seong Bae
Ha, Yoon
Amelot, Aymeric
Bedia Cadelo, Jorge
Viñuela-Prieto, Jose M.
Source :
European Spine Journal. Sep2024, Vol. 33 Issue 9, p3534-3544. 11p.
Publication Year :
2024

Abstract

Background: Clinical prediction models (CPM), such as the SCOAP-CERTAIN tool, can be utilized to enhance decision-making for lumbar spinal fusion surgery by providing quantitative estimates of outcomes, aiding surgeons in assessing potential benefits and risks for each individual patient. External validation is crucial in CPM to assess generalizability beyond the initial dataset. This ensures performance in diverse populations, reliability and real-world applicability of the results. Therefore, we externally validated the tool for predictability of improvement in oswestry disability index (ODI), back and leg pain (BP, LP). Methods: Prospective and retrospective data from multicenter registry was obtained. As outcome measure minimum clinically important change was chosen for ODI with ≥ 15-point and ≥ 2-point reduction for numeric rating scales (NRS) for BP and LP 12 months after lumbar fusion for degenerative disease. We externally validate this tool by calculating discrimination and calibration metrics such as intercept, slope, Brier Score, expected/observed ratio, Hosmer–Lemeshow (HL), AUC, sensitivity and specificity. Results: We included 1115 patients, average age 60.8 ± 12.5 years. For 12-month ODI, area-under-the-curve (AUC) was 0.70, the calibration intercept and slope were 1.01 and 0.84, respectively. For NRS BP, AUC was 0.72, with calibration intercept of 0.97 and slope of 0.87. For NRS LP, AUC was 0.70, with calibration intercept of 0.04 and slope of 0.72. Sensitivity ranged from 0.63 to 0.96, while specificity ranged from 0.15 to 0.68. Lack of fit was found for all three models based on HL testing. Conclusions: Utilizing data from a multinational registry, we externally validate the SCOAP-CERTAIN prediction tool. The model demonstrated fair discrimination and calibration of predicted probabilities, necessitating caution in applying it in clinical practice. We suggest that future CPMs focus on predicting longer-term prognosis for this patient population, emphasizing the significance of robust calibration and thorough reporting. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
09406719
Volume :
33
Issue :
9
Database :
Academic Search Index
Journal :
European Spine Journal
Publication Type :
Academic Journal
Accession number :
179772312
Full Text :
https://doi.org/10.1007/s00586-024-08395-3