Nomogram predicting severe adverse events after musculoskeletal tumor surgery: analysis of a national administrative database.

BACKGROUND: There have been no nationwide surveys of postoperative adverse events (AEs) after musculoskeletal tumor surgery focusing on their severity. Therefore, we developed a nomogram to predict severe AEs after musculoskeletal tumor surgery.
METHODS: We identified patients in the Diagnosis Procedure Combination database who underwent musculoskeletal tumor surgery during 2007-2012, and defined severe AEs as follows: (i) in-hospital mortality; (ii) postoperative medications including massive transfusion (≥1,400 mL), catecholamines, γ-globulin products, protease inhibitors, and medications for disseminated intravascular coagulation; and (iii) postoperative interventions consisting of mechanical ventilation, dialysis support, and cardiac support. Logistic regression models were used to address the occurrence of severe AEs.
RESULTS: Of 5,716 patients identified, 613 patients (10.7 %) had severe AEs. Multivariate analyses showed an inverse relationship between body mass index (BMI) and severe AEs (odds ratio 1.80 for BMI <18.50; p < 0.001) after adjustment for other significant factors, including sex, age, tumor location, Charlson comorbidity index, type of surgery, and duration of anesthesia. A nomogram and a calibration plot based on these results were well-fitted to predict the probability of severe AEs after musculoskeletal tumor surgery (concordance index 0.781).
CONCLUSIONS: We developed a nomogram predicting the probability of severe AEs after musculoskeletal tumor surgery. In addition, we clarified that underweight, but not overweight or obese, status was significantly associated with increased severe AEs after adjusting for patient background characteristics.