Revisiting the effectiveness of interventions to decrease surgical site infections in colorectal surgery: A Bayesian perspective.

OBJECTIVE

To evaluate the evidence for interventions to decrease surgical site infections (SSIs) in colorectal operations using Bayesian meta-analysis.

BACKGROUND

Interventions other than appropriate administration of prophylactic antibiotics to prevent SSIs have not been adopted widely, in part because of lack of recommendations for these interventions based on traditional meta-analyses. Bayesian methods can provide probabilities of specific thresholds of benefit, which may be more useful in guiding clinical decision making. We hypothesized that Bayesian meta-analytic methods would complement the interpretation of traditional analyses regarding the effectiveness of interventions to decrease SSIs.

METHODS

We conducted a systematic search of the Cochrane database for reviews of interventions to decrease SSIs after colorectal surgery other than prophylactic antibiotics. Traditional and Bayesian meta-analyses were performed using RevMan (Nordic Cochrane Center, Copenhagen, Denmark) and WinBUGS (MRC Biostatistics Unit, Cambridge, UK). Bayesian posterior probabilities of any benefit, defined as a relative risk of <1, were calculated using skeptical, neutral, and enthusiastic prior probabilities. Probabilities were also calculated that interventions decreased SSIs by ≥10%, and ≥20% using neutral prior probability distributions.

RESULTS

A total of 9 Cochrane reviews met the search criteria. Using traditional meta-analysis methods, only laparoscopic colorectal surgery resulted in a significant reduction in SSIs and a recommendation for use of the intervention. Using Bayesian analysis, several interventions that did not result in "significant" decreases in SSIs using traditional analytic methods had a >85% probability of benefit. Also, nonuse of 2 interventions (mechanical bowel preparation and adhesive drapes) had a high probability of decreasing SSIs compared with their use.

CONCLUSION

Bayesian probabilities and traditional point estimates of treatment effect yield similar information in terms of potential effectiveness. Bayesian meta-analysis, however, provides complementary information on the probability of a large magnitude of effect. The clinical impact of using Bayesian methods to inform decisions about which interventions to institute first or which interventions to combine requires further study.