Christopher P Ames1, Justin S Smith2, Ferran Pellisé3, Michael P Kelly4, Jeffrey L Gum5, Ahmet Alanay6, Emre Acaroğlu7, Francisco Javier Sánchez Pérez-Grueso8, Frank S Kleinstück9, Ibrahim Obeid10, Alba Vila-Casademunt11, Douglas C Burton12, Virginie Lafage13, Frank J Schwab13, Christopher I Shaffrey2, Shay Bess14, Miquel Serra-Burriel15. 1. Department of Neurosurgery, University of California San Francisco, San Francisco, CA. 2. Department of Neurosurgery, University of Virginia Medical Center, Charlottesville, VA. 3. Spine Surgery Unit, Hospital Vall d'Hebron, Barcelona, Spain. 4. Department of Orthopaedic Surgery, Washington University, St Louis, MO. 5. Norton Leatherman Spine Center, Louisville, KY. 6. Department of Orthopedics and Traumatology, Acibadem University, Büyükdere cad, Istanbul, Turkey. 7. Ankara ARTES Spine Center, Ankara, Turkey. 8. Spine Surgery Unit, Hospital Universitario La Paz, Paseo de la Castellana, Madrid, Spain. 9. Spine Center Division, Department of Orthopedics and Neurosurgery, Schulthess Klinik, Zürich, Switzerland. 10. Spine Surgery Unit, Bordeaux University Hospital, Bordeaux, France. 11. Vall d'Hebron Institute of Research (VHIR) Barcelona, Spain. 12. Department of Orthopaedic Surgery, University of Kansas Medical Center, Kansas City, KS. 13. Department of Orthopaedic Surgery, Hospital for Special Surgery, New York, NY. 14. Denver International Spine Center, Presbyterian St. Luke's/Rocky Mountain Hospital for Children, Denver, CO. 15. Center for Research in Health and Economics, Universitat Pompeu Fabra, Barcelona, Spain.
Abstract
STUDY DESIGN: Retrospective analysis of prospectively-collected, multicenter adult spinal deformity (ASD) databases. OBJECTIVE: To predict the likelihood of reaching minimum clinically important differences in patient-reported outcomes after ASD surgery. SUMMARY OF BACKGROUND DATA: ASD surgeries are costly procedures that do not always provide the desired benefit. In some series only 50% of patients achieve minimum clinically important differences in patient-reported outcomes (PROs). Predictive modeling may be useful in shared-decision making and surgical planning processes. The goal of this study was to model the probability of achieving minimum clinically important differences change in PROs at 1 and 2 years after surgery. METHODS: Two prospective observational ASD cohorts were queried. Patients with Scoliosis Research Society-22, Oswestry Disability Index , and Short Form-36 data at preoperative baseline and at 1 and 2 years after surgery were included. Seventy-five variables were used in the training of the models including demographics, baseline PROs, and modifiable surgical parameters. Eight predictive algorithms were trained at four-time horizons: preoperative or postoperative baseline to 1 year and preoperative or postoperative baseline to 2 years. External validation was accomplished via an 80%/20% random split. Five-fold cross validation within the training sample was performed. Precision was measured as the mean average error (MAE) and R values. RESULTS: Five hundred seventy patients were included in the analysis. Models with the lowest MAE were selected; R values ranged from 20% to 45% and MAE ranged from 8% to 15% depending upon the predicted outcome. Patients with worse preoperative baseline PROs achieved the greatest mean improvements. Surgeon and site were not important components of the models, explaining little variance in the predicted 1- and 2-year PROs. CONCLUSION: We present an accurate and consistent way of predicting the probability for achieving clinically relevant improvement after ASD surgery in the largest-to-date prospective operative multicenter cohort with 2-year follow-up. This study has significant clinical implications for shared decision making, surgical planning, and postoperative counseling. LEVEL OF EVIDENCE: 4.
STUDY DESIGN: Retrospective analysis of prospectively-collected, multicenter adult spinal deformity (ASD) databases. OBJECTIVE: To predict the likelihood of reaching minimum clinically important differences in patient-reported outcomes after ASD surgery. SUMMARY OF BACKGROUND DATA: ASD surgeries are costly procedures that do not always provide the desired benefit. In some series only 50% of patients achieve minimum clinically important differences in patient-reported outcomes (PROs). Predictive modeling may be useful in shared-decision making and surgical planning processes. The goal of this study was to model the probability of achieving minimum clinically important differences change in PROs at 1 and 2 years after surgery. METHODS: Two prospective observational ASD cohorts were queried. Patients with Scoliosis Research Society-22, Oswestry Disability Index , and Short Form-36 data at preoperative baseline and at 1 and 2 years after surgery were included. Seventy-five variables were used in the training of the models including demographics, baseline PROs, and modifiable surgical parameters. Eight predictive algorithms were trained at four-time horizons: preoperative or postoperative baseline to 1 year and preoperative or postoperative baseline to 2 years. External validation was accomplished via an 80%/20% random split. Five-fold cross validation within the training sample was performed. Precision was measured as the mean average error (MAE) and R values. RESULTS: Five hundred seventy patients were included in the analysis. Models with the lowest MAE were selected; R values ranged from 20% to 45% and MAE ranged from 8% to 15% depending upon the predicted outcome. Patients with worse preoperative baseline PROs achieved the greatest mean improvements. Surgeon and site were not important components of the models, explaining little variance in the predicted 1- and 2-year PROs. CONCLUSION: We present an accurate and consistent way of predicting the probability for achieving clinically relevant improvement after ASD surgery in the largest-to-date prospective operative multicenter cohort with 2-year follow-up. This study has significant clinical implications for shared decision making, surgical planning, and postoperative counseling. LEVEL OF EVIDENCE: 4.
Authors: Ferran Pellisé; Alba Vila-Casademunt; Susana Núñez-Pereira; Sleiman Haddad; Justin S Smith; Michael P Kelly; Ahmet Alanay; Christopher Shaffrey; Javier Pizones; Çaglar Yilgor; Ibrahim Obeid; Douglas Burton; Frank Kleinstück; Tamas Fekete; Shay Bess; Munish Gupta; Markus Loibl; Eric O Klineberg; Francisco J Sánchez Pérez-Grueso; Miquel Serra-Burriel; Christopher P Ames Journal: Eur Spine J Date: 2022-03-28 Impact factor: 2.721
Authors: Carl Laverdière; Miltiadis Georgiopoulos; Christopher P Ames; Jason Corban; Pouyan Ahangar; Khaled Awadhi; Michael H Weber Journal: Global Spine J Date: 2021-03-26
Authors: Rushikesh S Joshi; Darryl Lau; Justin K Scheer; Miquel Serra-Burriel; Alba Vila-Casademunt; Shay Bess; Justin S Smith; Ferran Pellise; Christopher P Ames Journal: Spine Deform Date: 2021-05-18