Despite guidelines, routine 24-hour urine testing is completed in <10% of high-risk, recurrent stone formers. Using surrogates for metabolic testing, such as key patient characteristics, could obviate the cost and burden of this test while providing information needed for proper stone prevention counseling.
We performed a retrospective study of 392 consecutive patients from 2007 to 2014 with ≥2 lifetime stone episodes, >70% calcium oxalate by mineral analysis, and ≥1 24-hour urine collection. We compared mean 24-hour urine values by age in decades. We used logistic regression and receiver operating characteristic (ROC) curve analysis to assess the predictive ability of age, gender, body mass index (BMI), and comorbidities to detect abnormal 24-hour urine parameters.
The mean age of the cohort was 51 ± 16 years. Older age was associated with greater urinary oxalate (p-trend <0.001), lower urinary uric acid (UA) (p-trend = 0.007), and lower urinary pH (p-trend <0.001). A nonlinear association was noted between age and urinary calcium or citrate (calcium peaked at 40-49 years, p = 0.03; citrate nadired at 18-29 years, p = 0.001). ROC analysis of age, gender, and BMI to predict 24-hour urine abnormalities performed the best for hyperuricosuria (area under the curve [AUC] 0.816), hyperoxaluria (AUC 0.737), and hypocitraturia (AUC 0.740). Including diabetes mellitus or hypertension did not improve AUC significantly.
In our recurrent calcium oxalate cohort, age significantly impacted urinary calcium, oxalate, citrate, and pH. Along with gender and BMI, age can be used to predict key 24-hour urine stone risk results. These data lay the foundation for a risk prediction tool, which could be a surrogate for 24-hour urine results in recurrent stone formers, who are unwilling or unable to complete metabolic testing. Further validation of these findings is needed in other stone populations.