Are you getting the most out of your SRD treatment?

SRD Smart Compare uses independent scientific evidence to make easy and direct comparisons between injectable antibiotics. It has been designed to help you make fact-based decisions on swine respiratory disease treatments in order to improve animal health with less antibiotic treatments.

Are you getting the most out of your SRD treatment?

The research behind:
Creating transparency on antibiotic efficacyDirectly comparing antibiotics is a scientific challenge. Due to time and resource constraints, published studies are not available for all possible antibiotic comparisons. Systematic review followed by network meta-analysis enables the assessment of comparative efficacy between antibiotics even in case no head-to-head studies are available.

O’Connor AM, Totton SC, Shane D. A systematic review and network meta-analysis of injectable antibiotic treatment options for naturally occurring swine respiratory disease. J Swine Health Prod. 2019;27(3):133-150.

Click here to view the paper

Independent review and analysis of accessible studies
Scientifically validated methods modelling probability of treatment success and assessing risk of bias
34 studies from 11 countries included in analysis (1266 records screened)
10 antibiotic molecules evaluated in model

Principles

Reference

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Click here to view the paper

What is the basis of the calculations?

O'Connor et al. used systematic review and meta-analysis to compare the efficacy of antibiotic treatments for SRD. The network of evidence contained 34 studies conducted in 11 different countries, representing 10 active ingredients. The output from the analysis provided information about the probability of treatment response and the treatment failure risk ratio comparing all possible treatments including both direct and indirect data. The SRD Smart Compare tool is built on the data published in tables 5 (page 147) & S5 (supplementary material 2) of the publication.

On which basis is the statement on superior efficacy between two antibiotics made?

The risk ratio (RR) between two antibiotics gives insights whether one antibiotic has a significantly higher risk of treatment failure than another and therefore shows lower efficacy in the meta-analysis. The upper right-hand section of the table below provides the risk ratio (RR) for treatment failure of the antibiotic in the row (nominator) compared to the antibiotic in the column (denominator) and the lower left-hand section displays the corresponding 95% confidence intervals (CI). If the CI interval for two selected antibiotics crosses 1, then there is no substantial evidence of difference in efficacy. For example, the RR between florfenicol (FLO; row = nominator) and marbofloxacin (MAR; column = denominator) is 2.55, but CI = 0.28 – 11.47, so there is no substantial evidence to say that one of them is more efficacious than the other as the CI crosses 1.

However, if the CI interval does not cross 1 and RR is different than 1, than there is substantial evidence of difference. Taking the example of amoxicillin (AMX; row = nominator) and enrofloxacin (ENF; column = denominator), RR = 10.15 and CI = 1.54 – 37.44, so one can state that there is substantial evidence of difference between the two antibiotics. The risk of treatment failure for AMX is 10.15 times higher than for ENF, meaning that AMX is less efficacious than ENF. To follow the idea, if RR is lower than 1 and CI does not cross 1, the antibiotic in the row is more effective than the antibiotic in the column. This is the case for example between enrofloxacin (ENF; row = nominator) and tildipirosin (TIL; column = denominator), where RR = 0.20 and CI = 0.04-0.53. This means that there is substantial evidence that ENF is more effective than TIL, because the risk of treatment failure for ENF is 0.20 times of TIL.

You can find the data in table 5 (page 147) in the publication.

How is the number of estimated treatment failures calculated?

Estimated treatment failures shown in SRD Smart Compare are calculated using the inverse of the mean probability of treatment response reported in the study. This is actually the mean probability of treatment failure, which is then multiplied with the SRD treatment numbers you entered as a baseline for analysis. E.g. for Amoxicillin, the mean probability of treatment response is 79%, which means a mean probability of treatment failure of 21%. If you entered that you treat 100 pigs for SRD, this would lead to a calculated estimated number of treatment failures of 21.

You can find the data in table S5 (supplementary material 2) in the publication.

Which treatment regimes have been used in the studies analysed in the meta-analysis?

Treatment regimes for antibiotic molecules reported in the model based on table 1 (page 135):

Antibiotic molecule	Treatment regimes
Non-active control	Saline, non-drug, sterile diluent, placebo
Amoxicillin	15 mg/kg, 2 doses 48 hours apart
Ceftiofur crystalline free acid (CFA)	5 mg ceftiofur equivalent/kg once
Ceftiofur hydrochloride or sodium (MD)	3-5 mg/kg SID q 3 days
Enrofloxacin	7.5 mg/kg once or 2.5-5 mg/kg SID q 3-5 days
Florfenicol	15 mg/kg, 2 doses 48 hours apart
Gamithromycin	6 mg/kg once
Marbofloxacin	8 mg/kg once or 2 mg/kg SID q 3 days
Oxytetracycline	9 mg/lb (4.1 mg/kg) once or 5-10 mg/kg once
Tildipirosin	4 mg/kg once
Tulathromycin	2.5 mg/kg once

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Last updated: 03.08.2020.