Contemporary Rates and Predictors of Open Conversion During Minimally Invasive Radical Prostatectomy for Nonmetastatic Prostate Cancer

Background: To test contemporary rates and predictors of open conversion at minimally invasive (laparoscopic or robotic) radical prostatectomy (MIRP). Materials and Methods: Within the National Inpatient Sample database (2008-2015), we identified all MIRP patients and patients who underwent open conversion at MIRP. First, estimated annual percentage changes (EAPCs) tested temporal trends of open conversion. Second, multivariable logistic regression models predicted open conversion at MIRP. All models were weighted and adjusted for clustering, as well as all available patient and hospital characteristics. Results: Of 57,078 MIRP patients, 368 (0.6%) underwent open conversion. The rates of open conversion decreased over time (from 1.80% to 0.38%; EAPC: -26.0%; p = 0.003). In multivariable logistic regression models predicting open conversion, patient obesity (odds ratio [OR]: 2.10; p < 0.001), frailty (OR: 1.45; p = 0.005), and Charlson comorbidity index (CCI) >= 2 (OR: 1.57; p = 0.03) achieved independent predictor status. Moreover, compared with high-volume hospitals, medium-volume (OR: 2.03; p < 0.001) and low-volume hospitals (OR: 3.86; p < 0.001) were associated with higher rates of open conversion. Last but not least, when the interaction between the number of patient risk factors (obesity and/or frailty and/or CCI >= 2) and hospital volume was tested, a dose-response effect was observed. Specifically, the rates of open conversion ranged from 0.3% (patients with zero risk factors treated at high-volume hospitals) to 2.2% (patients with two to three risk factors treated at low-volume hospitals). Conclusion: Overall contemporary (2008-2015) rate of open conversion at MIRP was 0.6% and it was strongly associated with patient obesity, frailty, CCI >= 2, and hospital surgical volume. In consequence, these parameters should be taken into account during preoperative patients counseling, as well as in clinical and administrative decision making.