Evidence Hub

The role of Silodosin as a new medical expulsive therapy for ureteral stones: a meta-analysis

Hui Ding, Zhongyun Ning, Yu Dai, Panfeng Shang, Li Yang

Renal Failure, 2016

1,035 participants · 13 citations

Abstract

To evaluate the efficacy of Silodosin as a medical expulsive therapy of ureteral stones, we searched PubMed, EMBASE, the Cochrane Library, and CBM up to June 2015. All randomized controlled trials (RCTs) were identified in which patients were randomized to receive Silodosin versus placebo or other therapies for ureteral stones. Outcome measures assessed were overall stone expulsion rate (primary) and expulsion time, analgesics times, and the incidence of additional treatment and regarding treatment complications (secondary). Two authors independently assessed study quality and extracted data. All data were analyzed using RevMan 5.3. Seven RCTs with a total of 1035 patients met the inclusion criteria. The pooled meta-analysis showed a significant improvement in stone clearance with Silodosin (Silodosin versus placebo, OR =1.69, 95% CI [1.19-2.40], p = 0.003; Silodosin versus tamsulosin, OR =2.82, 95% CI [1.79-4.44], p < 0.00001). According to the size and location of ureteral stone, the pooling effects of Silodosin were analyzed, with a meaningful expulsion rate in distal ureteral stone when the size was 5-10 mm. In addition, a shorter expulsion time, fewer analgesics times, and additional treatments were observed. The common side effect was retrograde ejaculation. In summary, Silodosin appears to be more effective than either placebo or tamsulosin. Within the limits of available data, high-quality multicenter RCTs are needed to thoroughly evaluate the outcome in the future.

How strong is the evidence?

Evidence Hub reads this as a meta-analysis, done in people. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 1,035 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free