Development and validation of a prediction tool for pain reduction in adult patients undergoing elective lumbar spinal fusion: a multicentre cohort study

Esther R. C. Janssen*, Ilona M. Punt, Sander M. J. van Kuijk, Eric A. Hoebink, Nico L. U. van Meeteren, Paul C. Willems

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Web of Science)


Purpose On average, 56% of patients report a clinically relevant reduction in pain after lumbar spinal fusion (LSF). Preoperatively identifying which patient will benefit from LSF is paramount to improve clinical decision making, expectation management and treatment selection. Therefore, this multicentre study aimed to develop and validate a clinical prediction tool for a clinically relevant reduction in pain 1 to 2 years after elective LSF. Methods The outcomes were defined as a clinically relevant reduction in predominant (worst reported pain in back or legs) pain 1 to 2 years after LSF. Patient-reported outcome measures and patient characteristics from 202 patients were used to develop a prediction model by logistic regression. Data from 251 patients were used to validate the model. Results Nonsmokers (odds ratio = 0.41 [95% confidence interval = 0.19-0.87]), with lower Body Mass Index (0.93 [0.85-1.01]), shorter pain duration (0.49 [0.20-1.19]), lower American Society of Anaesthesiologists score (4.82 [1.35-17.25]), higher Visual Analogue Scale score for predominant pain (1.05 [1.02-1.08]), lower Oswestry Disability Index (0.96 [0.93-1.00]) and higher RAND-36 mental component score (1.03 [0.10-1.06]) preoperatively had a higher chance of a clinically relevant reduction in predominant pain. The area under the curve of the externally validated model yielded 0.68. A nomogram was developed to aid clinical decision making. Conclusions Using the developed nomogram surgeons can estimate the probability of achieving a clinically relevant pain reduction 1 to 2 years after LSF and consequently inform patients on expected outcomes when considering treatment.

Original languageEnglish
Pages (from-to)1909-1916
Number of pages8
JournalEuropean Spine Journal
Issue number8
Publication statusPublished - Aug 2020


  • Clinical prediction model
  • Decision aid
  • External validation
  • Patient-reported outcomes
  • Risk factors

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