11. Predicting disability and pain outcomes one year after elective surgery for degenerative cervical diseases: analysis from quality outcomes database

Abstract

BACKGROUND CONTEXT In the current era of value-based health care reform, engaging patients in shared decision-making for treatment planning is imperative. Predictive models capable of providing individualized predictions of patient-reported outcomes (PROs) following cervical spine surgery have the potential to be valuable tools for a shared decision-making process. PURPOSE The aim of the study is to develop and validate predictive models for 12-month postoperative disability, pain, and myelopathy outcomes in patients undergoing elective spine surgery for degenerative cervical diseases (radiculopathy and myelopathy). STUDY DESIGN/SETTING This study is a retrospective analysis of prospectively collected data from the cervical module of a national spine registry, the Quality Outcomes Database (QOD). PATIENT SAMPLE Patients undergoing cervical spine surgery for the diagnosis of radiculopathy or myelopathy with degenerative etiologies are eligible for inclusion in the QOD registry. OUTCOME MEASURES The outcomes of interest in this study were neck related disability (NDI), pain [NRS- neck pain (NP) and arm pain (AP)] and modified Japanese Orthopedic Association score for myelopathy (mJOA). METHODS Two distinct sets of multivariable proportional odds ordinal regression models were developed with the outcomes of interest of disability (NDI), pain (NRS-NP and NRS-AP) and myelopathy (mJOA) score in the myelopathy cohort and disability (NDI) and pain (NRS-NP and NRS-AP) in the radiculopathy cohort. Patient characteristics of age, gender, BMI, race, education level, smoking status, history of diabetes, anxiety and depression, symptom duration, motor deficit or numbness at presentation, preoperative imaging finding of listhesis, employment status, workers’ compensation, insurance status, and ambulatory ability, baseline PROs as well as surgery-specific variables of number of levels, arthrodesis, and surgical approach were included in the models. The models were internally validated using bootstrap resampling. RESULTS A total of 5,076 patients who underwent surgery for cervical radiculopathy and 2717 patients who underwent surgery for cervical myelopathy were included in fitting the models for the distinct set of outcomes. There was a significant improvement in all PROs at 12 months after surgery (P CONCLUSIONS These predictive models can provide individualized risk-adjusted estimates of 12-month disability, pain, and myelopathy outcomes for patients undergoing spine surgery for degenerative cervical diseases. Novel predictive models constructed with these data hold the potential to guide individualized patient discussions on postsurgical outcomes and expectations. FDA DEVICE/DRUG STATUS This abstract does not discuss or include any applicable devices or drugs.