TY - JOUR
T1 - Development of a Preoperative Predictive Model for Reaching the Oswestry Disability Index Minimal Clinically Important Difference for Adult Spinal Deformity Patients
AU - International Spine Study Group
AU - Scheer, Justin K.
AU - Osorio, Joseph A.
AU - Smith, Justin S.
AU - Schwab, Frank
AU - Hart, Robert A.
AU - Hostin, Richard
AU - Lafage, Virginie
AU - Jain, Amit
AU - Burton, Douglas C.
AU - Bess, Shay
AU - Ailon, Tamir
AU - Protopsaltis, Themistocles S.
AU - Klineberg, Eric O.
AU - Shaffrey, Christopher I.
AU - Ames, Christopher P.
N1 - Publisher Copyright:
© 2018 Scoliosis Research Society
PY - 2018/9/1
Y1 - 2018/9/1
N2 - Study Design: Retrospective review of prospective multicenter adult spinal deformity (ASD) database. Objective: To create a model based on baseline demographic, radiographic, health-related quality of life (HRQOL), and surgical factors that can predict patients meeting the Oswestry Disability Index (ODI) minimal clinically important difference (MCID) at the two-year postoperative follow-up. Summary of Background Data: Surgical correction of ASD can result in significant improvement in disability as measured by ODI, with the goal of reaching at least one MCID. However, a predictive model for reaching MCID following ASD correction does not exist. Methods: ASD patients ≥18 years and baseline ODI ≥ 30 were included. Initial training of the model comprised forty-three variables including demographic data, comorbidities, modifiable surgical variables, baseline HRQOL, and coronal/sagittal radiographic parameters. Patients were grouped by whether or not they reached at least one ODI MCID at two-year follow-up. Decision trees were constructed using the C5.0 algorithm with five different bootstrapped models. Internal validation was accomplished via a 70:30 data split for training and testing each model, respectively. Final predictions from the models were chosen by voting with random selection for tied votes. Overall accuracy, and the area under a receiver operating characteristic curve (AUC) were calculated. Results: 198 patients were included (MCID: 109, No-MCID: 89). Overall model accuracy was 86.0%, with an AUC of 0.94. The top 11 predictors of reaching MCID were gender, Scoliosis Research Society (SRS) activity subscore, back pain, sagittal vertical axis (SVA), pelvic incidence–lumbar lordosis mismatch (PI-LL), primary version revision, T1 spinopelvic inclination angle (T1SPI), American Society of Anesthesiologists (ASA) grade, T1 pelvic angle (T1PA), SRS pain, SRS total. Conclusions: A successful model was built predicting ODI MCID. Most important predictors were not modifiable surgical parameters, indicating that baseline clinical and radiographic status is a critical factor for reaching ODI MCID. Level of Evidence: Level II.
AB - Study Design: Retrospective review of prospective multicenter adult spinal deformity (ASD) database. Objective: To create a model based on baseline demographic, radiographic, health-related quality of life (HRQOL), and surgical factors that can predict patients meeting the Oswestry Disability Index (ODI) minimal clinically important difference (MCID) at the two-year postoperative follow-up. Summary of Background Data: Surgical correction of ASD can result in significant improvement in disability as measured by ODI, with the goal of reaching at least one MCID. However, a predictive model for reaching MCID following ASD correction does not exist. Methods: ASD patients ≥18 years and baseline ODI ≥ 30 were included. Initial training of the model comprised forty-three variables including demographic data, comorbidities, modifiable surgical variables, baseline HRQOL, and coronal/sagittal radiographic parameters. Patients were grouped by whether or not they reached at least one ODI MCID at two-year follow-up. Decision trees were constructed using the C5.0 algorithm with five different bootstrapped models. Internal validation was accomplished via a 70:30 data split for training and testing each model, respectively. Final predictions from the models were chosen by voting with random selection for tied votes. Overall accuracy, and the area under a receiver operating characteristic curve (AUC) were calculated. Results: 198 patients were included (MCID: 109, No-MCID: 89). Overall model accuracy was 86.0%, with an AUC of 0.94. The top 11 predictors of reaching MCID were gender, Scoliosis Research Society (SRS) activity subscore, back pain, sagittal vertical axis (SVA), pelvic incidence–lumbar lordosis mismatch (PI-LL), primary version revision, T1 spinopelvic inclination angle (T1SPI), American Society of Anesthesiologists (ASA) grade, T1 pelvic angle (T1PA), SRS pain, SRS total. Conclusions: A successful model was built predicting ODI MCID. Most important predictors were not modifiable surgical parameters, indicating that baseline clinical and radiographic status is a critical factor for reaching ODI MCID. Level of Evidence: Level II.
KW - Adult spinal deformity
KW - Minimum clinically important difference
KW - Oswestry Disability Index
KW - Predictive modeling
KW - Scoliosis
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U2 - 10.1016/j.jspd.2018.02.010
DO - 10.1016/j.jspd.2018.02.010
M3 - Article
C2 - 30122396
AN - SCOPUS:85045214176
SN - 2212-134X
VL - 6
SP - 593
EP - 599
JO - Spine Deformity
JF - Spine Deformity
IS - 5
ER -