The electronic search of selected databases using the predefined criteria identified 16 studies; of these, only 3 met inclusion and exclusion criteria on closer examination [19
]. Manual search of the references of the selected studies and review articles identified an additional 10 studies. Thus, 13 randomized clinical trials met selection criteria, comprising 6510 patients randomly assigned to receive 26 separate antituberculosis regimens that included isoniazid, between 1957 and 2003 [19
]. The selected studies plus the antituberculosis regimens are shown in Table . None of the selected studies used crossover design. Different assays were used to define acetylation status (Table ). Sputum microbiological burden at presentation and disease burden by radiological appearance were reported in all studies, but only 3 reported both measures by acetylation status [19
]. The proportion of patients with moderate or severe disease on microscopy (ie, 2-plus or higher) was 68% in rapid acetylators versus 63% in slow acetylators (P
= .03); the presence of cavitation on chest radiographs was similar between acetylation phenotypes (P
= .35). Patients were prospectively randomly assigned to antituberculosis regimens for all studies; however, 2 studies used retrospective controls to compare clinical outcomes between acetylation status groups [21
]. In all studies, patients took medications under the direct supervision of a healthcare worker; patients who failed to come to their appointments received home visits from either a social worker or a healthcare worker.
Clinical Trials and the Characteristics of Antituberculosis Regimens Selected From Meta-Analysis
All 13 studies examined for microbiological failure. Three studies (23%) combined microbiological failure and relapse as a single outcome [21
]. Of the 6510 patients enrolled in the 13 clinical trials, 3471 (53%) presented with both acetylation phenotype data and microbiological outcomes. They consisted of 1631 rapid acetylators (47%), 89 intermediate acetylators (3%), and 1751 slow acetylators (50%). Because few patients were classified as intermediate acetylators, this group was excluded from further analysis. Figure is a forest plot of studies evaluated for microbiological failure showing a significant heterogeneity of RRs for microbiological failure between rapid and slow acetylators (I2
= 39%; P
= .035). Therefore, mixed-effects modeling was used. Overall, rapid acetylators were more likely to have microbiological failure (RR, 2.0; CI, 1.5–2.7) than were slow acetylators.
Figure 1. Forest plot of studies analyzed for microbiological failure. Twenty-six antituberculosis regimens were administered, labeled regimens 1–26. Figure shows risk ratios and 95% confidence intervals for microbiological failure in fast versus slow acetylators, (more ...)
In view of the heterogeneity of studies, we performed extensive sensitivity analysis on the microbiological failure outcome. We used mixed-effects methods to combine data across trial regimens based on dosing schedule, number of drugs used in the regimens, study location, and acetylation status assays. First, microbiological failure was higher in the once-a-week dosing schedule compared with the daily or every-other-day dosing schedule (RR, 4.1; CI, 2.9–5.8). Nevertheless, the risk of microbiological failure was still significantly higher among rapid acetylators within each dosing schedule, as shown in Figure .
Figure 2. Effect of acetylation status on failure during different dosing schedules. Risk of failure among rapid acetylators compared with slow acetylators was examined for once-weekly, twice-weekly, and daily dosing schedules. “Overall” refers (more ...)
Second, because it has been noted that acetylation status is irrelevant in modern multiple-therapy regimens, we performed sensitivity analysis of the effect of monotherapy, dual therapy, and ≥3 drug regimens (Figure ). Rapid acetylators had a significantly higher risk of failure, and this risk was even more significant in the combination chemotherapy regimens compared with monotherapy (Figure ).
Figure 3. Effect of acetylation status on failure with different numbers of drugs in combination. Shown are pooled risk ratios, number of regimens combined based on the number of different drugs in each regimen, and measures of heterogeneity (I2) between the pooled (more ...)
Third, we examined the effect of different assays for acetylation status. Studies that used sulfadimidine assays (I2
= 0%) or matrix isoniazid assays (I2
= 32%) were significantly homogeneous, whereas those that used isoniazid concentration assays (I2
= 54%) were heterogeneous. The acetylation status assay did not affect RRs of failure among rapid acetylators compared with slow acetylators. However, studies that included isoniazid assays used different drug concentration levels to determine acetylation status, a possible reason for the observed heterogeneity of effect. Supplementary Figure 1
shows influence analysis data for all regimens that examined failure. Exclusion of the inferior isoniazid monotherapy regimens did not significantly influence failure. Finally, the funnel plot did not suggest any publication bias or small-study effects for microbiological failure (P
= .58). Thus, the sensitivity analysis confirmed that acetylation-defined pharmacokinetic variability was significantly associated with microbiological outcome, independent of dosing schedule, number of drugs in the regimen, or assay used to establish acetylation phenotype.
ADR was reported in a format that could be used in this meta-analysis in 5 studies, comprising 622 fast acetylators and 577 slow acetylators [25
]. Of these studies, 2 [23
] contributed 80% to the pooled RR. The studies demonstrated significant homogeneity of effect (I2
= 0%), hence, fixed-effects modeling was used. Figure shows the risk of ADR in each study. The pooled RR for ADR was 2.0 (CI, 1.1–3.4) in rapid acetylators compared with slow acetylators. However, in sensitivity analysis, when isoniazid monotherapy was excluded from computation of pooled estimates, the RR, though higher among rapid acetylators, just failed to attain statistical significance (RR, 2.3; CI, .9–6.2). The funnel plot did not suggest any publication bias or small-study effects for ADR (P
Figure 4. Forest plot for acquisition of drug resistance. Figure shows risk ratios and 95% confidence intervals, as well as the percentage of weight contributed by each regimen toward the pooled estimate obtained using fixed-effects models. Abbreviations: CI, confidence (more ...)
Relapse was assessed in 5 studies [20
]; studies that combined relapse and failure were excluded from relapse analysis. Because the studies were homogenous (I2
= 0%), fixed-effects models were used. The analysis included 557 rapid and 477 slow acetylators. Results are shown in Figure , which demonstrates that although the risk for relapse was higher among rapid acetylators, this difference did not achieve statistical significance. The funnel plot did not suggest any publication bias or small-study effects for relapse (P
Figure 5. Forest plot of studies that reported relapse. I2 demonstrates good homogeneity. Results show a higher risk of relapse (risk ratio) for fast acetylators; however, the difference did not achieve statistical significance. Abbreviations: CI, confidence interval; (more ...)