108. The inclusion of frailty improves predictive modeling for postoperative outcomes in the surgical management of primary and secondary lumbar spine tumors

Abstract

<h3>BACKGROUND CONTEXT</h3> Malignant spinal tumors are common, continually increasing in incidence as a function of improved survival times for patients with cancer. Until recently, age has been popularly analyzed as an independent predictor of postoperative complications. However, frailty has been shown to be superior in predicting patient outcomes in spine surgery for several indications. <h3>PURPOSE</h3> Using predictive analytics and propensity score matching, we evaluated the influence of frailty on postoperative complications compared to age in patients with malignant neoplasms of the lumbar spine. <h3>STUDY DESIGN/SETTING</h3> Retrospective cohort study. <h3>PATIENT SAMPLE</h3> A total of 533 frail patients and 538 nonfrail patients who underwent lumbar fusion with malignant spinal neoplasms within the Nationwide Readmissions Database (NRD). <h3>OUTCOME MEASURES</h3> Mortality, infection, readmission, hardware failure, increased length of stay (LOS), nonroutine discharge, increased costs. <h3>Methods</h3> Patient frailty was queried using the Johns Hopkins Adjusted Clinical Groups (JHACG) frailty-defining diagnosis indicator. Propensity score matching for age, sex, CCI, surgical approach, and number of levels fused was implemented between frail and nonfrail patients. Receiver operating characteristic (ROC) curves were created following creation of logistic regression models for relevant postoperative complications using both age and frailty status as predictor variables. The area under the curve (AUC) of each ROC served as a proxy for model performance. <h3>Results</h3> Despite matching, frail patients reported significantly higher inpatient lengths of stay (LOS), costs, infection, posthemorrhagic anemia, and urinary tract infections (p<0.05). In addition, frail patients were more often discharged to skilled nursing facilities and short-term hospitals compared to nonfrail patients (p<0.0001) when demographics and surgical variables were held constant. Regression models for mortality (AUC=0.644), nonroutine discharge (AUC=0.600), and acute infection (AUC=0.666) were all improved when using frailty as the primary predictor compared to models using age. These models were also improved using frailty when predicting 30-day readmission and 90-day hardware failure. <h3>Conclusions</h3> Frailty demonstrated a significant relationship with increased postoperative patient complications, LOS, costs, and acute complications in patients receiving fusion following resection of a malignant neoplasm of the lumbar spine region. Frailty also demonstrated better predictive validity of outcomes compared to patient age. Further investigation is warranted to obtain higher AUCs and fully optimize the prediction of perioperative complications using frailty. <h3>FDA DEVICE/DRUG STATUS</h3> This abstract does not discuss or include any applicable devices or drugs.