Effect of zoledronic acid on clinically meaningful changes in pain associated with metastatic prostate cancer.

4680 Background: Zoledronic acid (ZA) has been shown to significantly decrease skeletal-related events (SREs) in patients with prostate cancer by 11% relative to placebo. Trends were seen in pain improvement with ZA vs placebo, but there were no reliable treatment group differences. The objective of this study was to reexamine the pain outcomes using an alternative analytic framework that focuses on the frequency of clinically meaningful changes in pain scores. METHODS: Patients were randomized to ZA 4mg (n=214) or placebo (n=208). The Brief Pain Inventory Composite Score (BPI) was used to assess pain at baseline, 3 weeks, 6 weeks, and every 6 weeks for a total of 60 weeks. We determined whether clinically meaningful pain changes from baseline (+/- 2 BPI points) were related to treatment assignment using a modified non-parametric rank test. RESULTS: The rapid progression of the prostate cancer led to high rates of dropout as only 76 of 214 (35.5%) patients randomized to ZA and 62 of 208 (29.8%) patients randomized to PL completed their 60 week visit (p=0.21). At 10 of 11 assessment times, ZA patients reported more favorable clinically meaningful changes in pain scores (see table). Overall, a typical ZA patient had a 27% chance of having a favorable response (ZA>PL) compared with a typical PL patient who had an 19% chance of a favorable response (PL>ZA)-a difference that was statistically significant (95% CI: 1.1% - 15.5%). CONCLUSIONS: Patients receiving ZA were 8% more likely to have clinically beneficial changes in pain scores compared to patients receiving placebo. This is roughly consistent with the 11% difference between groups in the incidence of SREs as reported in the primary clinical analysis. Thus, ZA 4 mg significantly reduces the occurrence of skeletal-related events and the associated changes in pain they produce. [Figure: see text] [Table: see text].

Duke Scholars

Author Kevin Phillip Weinfurt Population Health Sciences

Author Kevin J. Anstrom Biostatistics & Bioinformatics, Division of Biostatistics