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Excretory urography could be performed less frequently if some combinations of genitourinary signs and symptoms were found to be predictive of either a specific disease or normality. To explore this possibility, the authors conducted a prospective study involving more than 3,000 patients at three institutions (a teaching hospital, a community hospital, and a health maintenance organization). Predictive algorithms were obtained by application of a polychotomous logistic regression model but did poorly at differentiating normal from abnormal patients or arriving at a specific diagnosis. Selection of patients on the basis of the logistic model would have required testing 90% of all patients in order to detect 95% of those with abnormal urograms. These results suggest that current clinical selection criteria for excretory urography are effective, and that present frequency of utilization is appropriate.
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