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Multicenter Study
What Factors Predict the Risk of Proximal Junctional Failure in the Long Term, Demographic, Surgical or Radiographic? Results from a Time-Dependent ROC Curve.
- Jingyan Yang, Marc Khalifé, Renaud Lafage, Han Jo Kim, Justin Smith, Christopher I Shaffrey, Douglas C Burton, Christopher P Ames, Gregory M Mundis, Richard Hostin, Shay Bess, Eric O Klineberg, Robert A A Hart, Frank J Schwab, Virginie Lafage, and International Spine Study Group (ISSG).
- Department of Orthopedic Surgery, Hospital for Special Surgery, New York, NY.
- Spine. 2019 Jun 1; 44 (11): 777-784.
Study DesignRetrospective review of prospective multicenter database.ObjectiveTo identify an optimal set of factors predicting the risk of proximal junctional failure (PJF) while taking the time dependency of PJF and those factors into account.Summary Of Background DataSurgical correction of adult spinal deformity (ASD) can be complex and therefore, may come with high revision rates due to PJF.MethodsSeven hundred sixty-three operative ASD patients with a minimum of 1-year follow-up were included. PJF was defined as any type of proximal junctional kyphosis (PJK) requiring revision surgery. Time-dependent ROC curves were estimated with corresponding Cox proportional hazard models. The predictive abilities of demographic, surgical, radiographic parameters, and their possible combinations were assessed sequentially. The area under the curve (AUC) was used to evaluate models' performance.ResultsPJF occurred in 42 patients (6%), with a median time to revision of approximately 1 year. Larger preoperative pelvic tilt (PT) (hazard ratio [HR]=1.044, P = 0.034) significantly increased the risk of PJF. With respect to changes in the radiographic parameters at 6-week postsurgery, larger differences in pelvic incidence-lumbar lordosis (PI-LL) mismatch (HR = 0.924, P = 0.002) decreased risk of PJF. The combination of demographic, surgical, and radiographic parameters has the best predictive ability for the occurrence of PJF (AUC = 0.863), followed by demographic along with radiographic parameters (AUC = 0.859). Both models' predictive ability was preserved over time.ConclusionsOver correction increased the risk of PJF. Radiographic along with demographic parameters have shown the approximately equivalent predictive ability for PJF over time as with the addition of surgical parameters. Radiographic rather than surgical factors may be of particular importance in predicting the development of PJF over time. These results set the groundwork for risk stratification and corresponding prophylactic interventions for patients undergoing ASD surgery.Level Of Evidence4.
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