Table 3.

Odds Ratios of Surgical Complications Using Doubly Robust Logistic Regression^*

	Type of Complication
	30-Day Surgical	Late Urinary	Long-Term Incontinence
Urologist change
No change	1.00	1.00	1.00
Urologist change	0.82 (0.76–0.89)	0.94 (0.87–1.01)	0.97 (0.89–1.05)
Urologist volume of treating urologist
Low	1.00	1.00	1.00
High	0.86 (0.77–0.97)	0.83 (0.76–0.91)	0.82 (0.73–0.93)
Years since medical school graduation for treating urologist†
Top quartile (oldest)	1.00	1.00	1.00
Middle top quartile	0.99 (0.89–1.12)	0.86 (0.77–0.95)	1.03 (0.91–1.17)
Middle bottom quartile	0.97 (0.86–1.10)	1.00 (0.90–1.11)	1.08 (0.95–1.22)
Lowest quartile (youngest)	1.07 (0.91–1.26)	1.06 (0.92–1.21)	1.37 (1.15–1.62)
Board certification of treating urologist
No	1.00	1.00	1.00
Yes	1.11 (1.01–1.24)	1.23 (1.13–1.37)	1.12 (1.00–1.25)
Type of procedure
Open prostatectomy	1.00	1.00	1.00
Minimally invasive prostatectomy	0.68 (0.50–0.93)	1.15 (0.88–1.50)	0.69 (0.44–1.08)

Notes. The “doubly robust” models include all variables used in generating the propensity score as well as the variables listed in the table. The odds ratios for the covariates included in the propensity score model are not interpretable in the outcome model and therefore not listed above. Bold entries are statistically significant.

^*Propensity score weighted models adjust for age, race, comorbidities, marital status, income, t-stage, grade, SEER-site, diagnosing urologist volume, laparoscopic or robotic prostatectomy experience of the treating physician, type of procedure, SEER-site, and year of diagnosis.

^†Years since medical school graduation was calculated as the number of years between 2005 and graduation year. This variable was then categorized into quartiles based on the physician distribution.