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Uncertainty in the Relationship Between Sagittal Alignment and Patient-Reported Outcomes
Peter D Angevine1, David Bray2, Michael Cloney3
1Department of Neurological Surgery, Columbia University Vagelos College of Physicians and Surgeons, New York, New York.
Neurosurgery
|July 3, 2019
Summary
The relationship between spinal sagittal alignment and quality of life is uncertain. Predicting patient outcomes based on alignment is unreliable, necessitating advanced modeling for better accuracy.
Area of Science:
- Spine surgery
- Orthopedics
- Radiographic analysis
Background:
- Previous studies show correlations between spinal sagittal alignment and health-related quality of life (HRQOL).
- The extent of uncertainty in these established relationships has not been quantified.
- Accurate assessment of spinal alignment's impact on patient outcomes is crucial.
Purpose of the Study:
- To quantify the uncertainty in the relationship between spinal sagittal alignment and HRQOL.
- To assess the uncertainty in predicting individual patient pain and disability based on alignment.
- To provide a more precise understanding of the variability in patient outcomes.
Main Methods:
- Retrospective analysis of 134 adult patients with complete radiographic and HRQOL data (2012-2014).
- Bayesian linear regression models were used to analyze relationships.
- High-density probability intervals were calculated to determine the range of uncertainty.
Main Results:
- Significant uncertainty was found in the relationship between Oswestry Disability Index (ODI) and both pelvic incidence-lumbar lordosis (LL) and sagittal vertical axis.
- The magnitude and direction of the association between spinal alignment parameters and ODI were uncertain.
- Predicting individual patient scores demonstrated wide regions of uncertainty.
Conclusions:
- The degree of uncertainty in the quantitative relationships between radiographic sagittal alignment and patient-reported outcomes is significant and previously unreported.
- Establishing treatment thresholds or predicting individual outcomes based on current alignment data is unreliable.
- Future research should focus on multilevel hierarchical models to incorporate parameter uncertainty and heterogeneous effects for improved outcome prediction.
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