Risk of hepatitis with various reintroduction regimens of anti-tubercular therapy: a systematic review and network meta-analysis.
Hariom SoniPraveen Kumar-MShubhra MishraBalaji L BellamHarjeet SinghHarshal S MandavdhareBikash MedhiUsha DuttaNavneet SharmaPublished in: Expert review of anti-infective therapy (2020)
Objective: To compare risk of hepatotoxicity between various regimens for reintroduction of antitubercular therapy (ATT) in patients with previous episode of ATT hepatitis.Methods: We searched various databases (PubMed, Embase, CENTRAL, Scopus, WoS and LILACS) for studies comparing ATT reintroduction regimens using terms 'drug-induced liver injury' and 'antitubercular drugs' AND 'reintroduction'. The reintroduction regimens i.e concomitant (all drugs introduced together), sequential (reintroduction of one drug in full dose followed by another) or incremental (one drug in a low dose and then higher dose followed by next drug) were compared using Bayesian approach for network meta-analysis with random-effect model. Cochrane revised tool was used to assess risk of bias in included studies (RoB 2.0).Results: Four randomized studies with 577 patients were eligible for analysis. Compared with concomitant regimen (baseline comparator), incremental regimen appeared to have lower risk of ATT hepatitis (odds ratio [OR] 0.24; 95% CrI 0.017, 1.2) as also the sequential regimen (OR 0.33; 95% CrI 0.033, 1.7). Rifampicin first and isoniazid first reintroduction regimens were similar via-a-vis recurrence of hepatotoxicity.Conclusion: The sequential and incremental regimen may be better than concomitant regimen in reducing risk of ATT hepatitis although the odds did not achieve statistical significance.
Keyphrases
- drug induced
- low dose
- case control
- systematic review
- mycobacterium tuberculosis
- end stage renal disease
- adverse drug
- randomized controlled trial
- ejection fraction
- chronic kidney disease
- emergency department
- open label
- prognostic factors
- stem cells
- high dose
- patient reported outcomes
- big data
- electronic health record
- data analysis