To validate a claims-based algorithm for detecting severe rectal and urinary adverse effects (AEs) of radiotherapy (RT) to inform the design and interpretation of outcomes studies, using administrative datasets to detect such RT AEs.

An institutional billing analysis was performed to identify patients managed with RT for prostate or cervical cancer at the University of Minnesota, between 2000 and 2006. A priori, we identified Current Procedural Terminology procedural codes consistent with treatment for severe RT AEs. A retrospective chart review and a billing (ie “claims”) analysis were performed to detect the procedures used to treat RT AEs. The accuracy of the claims-based algorithm was compared with chart review (the reference standard).

On chart review, 31 patients (7.6%) with severe rectal and urinary RT AEs were detected among 406 patients with nonmetastatic cancer at diagnosis. The most common AE was ureteral stenosis (25% of all AEs). The sensitivity and specificity of the claims-based analysis were 75% and 100% respectively for urethral stricture, 100% and 99% respectively for ureteral stricture, 60% and 100% respectively for radiation cystitis, 88% and 100% respectively for rectal or urinary fistula, and 88% and 100% respectively for radiation proctitis.

We demonstrated an excellent specificity and yet fairly good sensitivity of our claims-based algorithm for detecting treatment of urethral stricture, rectal or urinary fistulas, radiation proctitis, and ureteral stricture. These data might inform the design and interpretation of studies using claims-based methods for the detection of severe urinary AEs of pelvic RT.