Optimized OF-Score– Therapy Prediction in Successfully Treated Patients With Osteoporotic Spine Fractures Using Minimal Clinically Important Difference

Study DesignMulticenter study with prospective collected data.ObjectivesThis study investigates the relationship between individual score components and treatment success, defined by achieving Minimal Clinically Important Difference (MCID) thresholds in functional outcomes, using multicenter prospectively collected data. This work aimed to optimize the OF-Score while maintaining its original structure. By using outcome-oriented data, we refined this established decision-support tool to improve its predictive accuracy for successful clinical outcomes.MethodsData from 518 patients from the EOFTT study with osteoporotic vertebral fractures were analyzed. Only patients with clinically successful outcomes, defined by improvement beyond MCID thresholds in functional scores after conservative or surgical treatment, were selected from this cohort. Optimization was performed using a data-driven reweighting approach combined with structured clinical expert evaluation, adjusting variable weights within predefined limits to improve alignment with successful therapies.ResultsThe subset data of 374 successfully treated patients were analyzed. Before optimization, the OF-Score showed an accuracy of 73%, with pain and mobilization being the most important parameters. After optimization, the OF-Score showed an accuracy of 80.7% (sensitivity 85.2%, specificity 71.2%). The number of nonapplicable (indifferent) therapy recommendations dropped from 144 (37%) to 72 (19%). A threshold of 5 points provided optimal discrimination between conservative treatment (≤5) and surgical treatment (>5).DiscussionThe optimized OF-Score, targeted weight adjustments, improves the alignment between clinical recommendations and treatment success. This refinement enhances the score's predictive accuracy for treatment responders while maintaining the simple, practical structure.