title: Multivariate case-control study of survival following transurethral resection of prostate.
abstract: Although prevalence of perioperative mortality following transurethral resection of the prostate (TURP) has steadily declined as reported in several review studies, it has been suggested that with extended follow-up after TURP, mortality exceeds that of an age-matched population. The sample selected for this study was drawn from a data base of 2,005 men who entered a urologic health-screening program. The sample included a group of 25 patients who underwent TURP and a group of 50 age-matched control patients with symptoms of prostatism. Patients were followed for six years, a total of 450 observed person-years. Multivariate analyses based on a general linear model approach for the dependent variable of survival were used to assess gains in predictive efficiency due to combinations of TURP versus control, time, and patient variables. F-ratio hypothesis tests of coefficients of multiple determination for the models indicated that TURP did account for a significant amount of the variability of survival but only after five years of follow-up. However, a far larger proportion of the variance in survival was explained by other patient variables of age, preoperative risk, comorbidity factors, and postoperative urinary disease after all effects due to TURP, follow-up years, and operation cohort years were held constant in the survival prediction equation.
authors.affiliation: Health Care Administration Program, U.S. Army-Baylor University Graduate School, Texas.
authors.forename: M E
authors.initials: ME
authors.lastname: Hooten
authors.forename: K
authors.initials: K
authors.lastname: Finstuen
authors.forename: I M
authors.initials: IM
authors.lastname: Thompson
mesh_terms: D000368:Aged; D016022:Case-Control Studies; D016009:Chi-Square Distribution; D015331:Cohort Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D011468:Prostatectomy / Q000401:mortality*; D012307:Risk Factors; D016019:Survival Analysis