Abstract
Background and Objective
Efavirenz is associated with frequent adverse effects, mainly hepatotoxicity and central nervous system disturbances. The cytochrome P450 enzyme CYP2B6 plays a key role in efavirenz metabolism and is strongly linked to these toxicities. This study aimed to evaluate the effect of the CYP2B6 c.516 G>T polymorphism on efavirenz plasma concentrations by comparing individuals with GG, GT, and TT genotypes.
Methods
A systematic review of four databases was conducted to identify studies published up to March 2025 evaluating the association between the CYP2B6 c.516 G>T polymorphism and efavirenz plasma concentrations. Pooled mean differences with 95% confidence intervals were calculated using random-effects models.
Results
Five studies, including 373 patients, met the inclusion criteria. Individuals with the TT genotype showed significantly higher plasma efavirenz concentrations compared with GG and GT carriers. The mean differences in plasma concentration between the GT-TT and GG-TT subgroups were 5.65 µg/mL and 6.41 µg/mL, respectively, both statistically significant (p < 0.05). No significant difference was observed between the GG and GT genotypes.
Conclusion
This meta-analysis confirms that the CYP2B6 c.516 TT genotype is significantly associated with elevated plasma efavirenz concentration in patients with HIV and tuberculosis. While higher concentrations may increase toxicity risk, this was not directly evaluated in the current pooled analysis. These findings support the potential utility of pharmacogenetic testing to optimize efavirenz dosing and minimize the risk of adverse effects, particularly in carriers of the TT genotype. The observed heterogeneity among studies may be attributed to ethnic variability and differences in sample sizes.
Supplementary Information
The online version contains supplementary material available at https://doi.org/10.1007/s13318-026-01017-x.
Key Points
| Individuals with the CYP2B6 c.516TT genotype show markedly higher efavirenz levels compared to other genotypes. |
| Genetic differences in CYP2B6 contribute to clinically relevant variability in drug exposure. |
| Pharmacogenetic testing may help guide safer and more individualized efavirenz dosing. |
Introduction
Efavirenz has historically been a key component of antiretroviral therapy for human immunodeficiency virus (HIV) infection. Although it has largely been replaced by integrase inhibitor-based regimens, such as dolutegravir, in current international guidelines, efavirenz continues to be used in specific clinical contexts, particularly in resource-limited settings and in patients with tuberculosis (TB) coinfection due to its compatibility with Rifampicin-based therapy [1, 2].
Efavirenz metabolism is primarily hepatic and mediated by cytochrome CYP450 2B6, an enzyme whose activity is influenced by genetic variations [3]. Among these variations, the c.516 G>T single nucleotide polymorphism (SNP) (rs3745274) has been widely studied due to its impact on efavirenz pharmacokinetics [4, 5]. This polymorphism results in a reduction in CYP2B6 enzymatic activity, which translates into decreased drug clearance and, consequently, increased plasma concentrations [6].
The clinical relevance of this polymorphism is particularly important in patients with HIV and tuberculosis (TB) coinfection, given that efavirenz is commonly administered with antituberculosis treatment, which includes Rifampin, a potent CYP450 inducer [7, 8]. The interaction between these drugs and genetic variability can influence treatment efficacy and toxicity, generating adverse effects such as neurotoxicity and hepatotoxicity, which compromise therapeutic adherence and clinical outcomes [9, 10].
Although the association between CYP2B6 c.516 G>T polymorphism and efavirenz exposure has been previously described, evidence in the context of HIV/TB coinfection remains heterogeneous, particularly regarding the combined effects of genetic variability and Rifampicin-based therapy. Therefore, a quantitative synthesis of available data is needed to better characterize this relationship in this clinically complex population, where treatment decisions may still rely on efavirenz-based regimens and where pharmacogenetic variability can have significant clinical implications.
This meta-analysis aims to evaluate the effect of the CYP2B6 c.516 G>T polymorphism on efavirenz concentrations in patients coinfected with HIV and tuberculosis.
Materials and Methods
Search Strategy
A systematic review was conducted according to the 2020 PRISMA guidelines [11]. The protocol for this meta-analysis was registered in PROSPERO on 3 March 2025, under the ID number: CRD420251003107. The objective was to identify articles evaluating the association between the CYP2B6 c.516 G>T polymorphism (rs3745274) and plasma efavirenz concentrations in adult patients with HIV infection and tuberculosis coinfection.
The information search was conducted in the electronic databases PubMed, Embase, the Cochrane Library, and Scopus, with no publication date restrictions. Studies published in English or Spanish were included. MeSH terms, Emtree, and keywords such as HIV, tuberculosis, efavirenz, CYP2B6, cytochrome P-450, polymorphism, SNP, among others, were combined using the Boolean operators (AND, OR). The search strategy was designed based on the PICO model as follows: P: People with HIV and TB receiving treatment with efavirenz and Rifampicin with plasma drug concentration measurement; I: Presence of the CYP2B6 c.516 G>T polymorphism; C: Normal CYP2B6 enzyme (wild-type); and O: Changes in plasma concentrations, liver toxicity, and/or clinical efficacy.
Inclusion and Exclusion Criteria
Studies were included if they met the following criteria: (1) randomized clinical trial or observational cohort study design; (2) adult patients (over 18 years of age) diagnosed with HIV and coinfected with tuberculosis; (3) evaluation of the CYP2B6 c.516 G>T polymorphism; (4) reporting of efavirenz plasma concentrations stratified by genotype (GG, GT, TT); and (5) publication written in English or Spanish. Articles were excluded if: (1) they were conducted in pediatric or pregnant populations, or if they used animal or in vitro models; (2) they did not evaluate the relationship between genetic polymorphisms and plasma concentration; (3) they were review articles, letters to the editor, abstracts, conference proceedings, or the full text was unavailable, (4) they did not report concentration values; or (5) they were not related to the study objective.
Study Selection
Study selection was carried out in two stages by two reviewers independently. Titles and abstracts were first screened on the Rayyan platform [12] to discard irrelevant articles. The full texts of the preselected studies were subsequently reviewed, applying the inclusion and exclusion criteria. Discrepancies were resolved by consensus among the five authors.
Data Extraction
A digital data extraction form was created in Excel, in which the following data were collected: (1) general information about the study (name, year, author, country, design, language, DOI), (2) population characteristics (total sample size, proportion by sex, coinfection with tuberculosis, use of Rifampin), (3) genetic information (distribution of the GG, GT, and TT genotypes of the CYP2B6 c.516 G>T polymorphism), (4) plasma concentration of efavirenz by genotype, and (5) dose used, as well as plasma concentration measurement techniques. When studies reported plasma concentrations with means and interquartile ranges, the Hozo method was used to estimate the mean and standard deviation if the data allowed.
Risk of Bias Assessment
The risk of bias of the included studies was independently assessed by two reviewers. For randomized controlled trials, the Cochrane Risk of Bias 2 (RoB 2) tool was used, evaluating domains including the randomization process, deviations from intended interventions, missing outcome data, measurement of outcomes, and selection of reported results.
For non-randomized studies, the ROBINS-I tool was applied, assessing bias due to confounding, selection of participants, classification of interventions, deviations from intended interventions, missing data, measurement of outcomes, and selection of reported results.
Each study was classified according to the overall risk of bias as low, moderate, some concerns, or serious. Discrepancies were resolved by consensus.
Funnel plots were assessed through visual inspection. Due to the small number of included studies, formal statistical tests for funnel plot asymmetry, such as Egger’s regression test, were not performed.
Statistical Analysis
This meta-analysis was performed using the online platform Review Manager version 5.3 [13]. Mean differences (MD) and 95% confidence intervals (95% CI) were calculated to compare efavirenz plasma concentrations between the GG, GT, and TT genotypes of the CYP2B6 c.516 G>T polymorphism. Study heterogeneity was assessed using the chi-square (chi2) statistic and the I2 index. Significant heterogeneity was considered when I2 ≥ 50% or p < 0.05; in these cases, a random-effects model was applied, and subgroup analysis was performed.
Results
Selection of Relevant Studies and Qualitative Assessment
Relevant studies were identified through a systematic search of the electronic databases PubMed, Embase, the Cochrane Library, and Scopus, with no restrictions on year of publication. After eliminating 91 duplicate articles using Zotero software [14], 161 unique articles were reviewed by reading the title and abstract in Rayyan. In this phase, 126 records were discarded because they did not meet the inclusion criteria. A full-text review of 35 articles was subsequently conducted. Of these, 30 articles were excluded because they were posters, were not related to the study objective, did not assess the polymorphism–plasma concentration relationship, did not report concentration values, or for other reasons, such as lacking relevant data for this meta-analysis.
Five studies ultimately met the eligibility criteria and were included in the meta-analysis. These studies provided sufficient data to calculate mean differences in efavirenz plasma concentrations according to GG, GT, and TT genotypes. A detailed flowchart of the study selection process is presented in Fig. 1, which follows the methodology proposed by the PRISMA 2020 guidelines [11].
Fig. 1.
PRISMA flow diagram showing the selection process of studies included in the meta-analysis [11]
A total of 373 patients were included in this meta-analysis. The general characteristics of the analyzed studies are presented in Table 1. The publications cover the period from 2008 to 2019, and most were conducted in Africa, including Ghana, Uganda, South Africa, and Rwanda; one of the studies was conducted in Asia (Thailand). Biological samples for genetic analysis were obtained from peripheral blood, and CYP2B6 c.516 G>T genetic polymorphisms were identified by direct sequencing or real-time PCR. Plasma efavirenz concentrations were determined using high-performance liquid chromatography (HPLC) as the separation method, coupled with different detection techniques, including ultraviolet detection (UV), or mass spectrometry (MS), depending on the study.
Table 1.
General characteristics of the studies included in the meta-analysis
| Author and year | Journal | Country | Patient database | Population size (included) | Key findings |
|---|---|---|---|---|---|
| Von Braun et al. 2019 [15] | Journal of Antimicrobial Chemotherapy | Uganda | Infectious Diseases Institute (2013-2015) | 166 (166) | The serum efavirenz concentrations of patients with CYP2B6 c.516 TT were consistently above 4 μg/mL and significantly higher than those of patients with GG or GT genotypes. The CYP2B6 genetic variant was the only factor independently associated with elevated serum efavirenz concentration in the univariable and multivariable analyses |
| Gengiah et al. 2015 [16] | Antiviral Therapy | South African | CAPRISA – Centre for the AIDS Programme of Research in South Africa | 54 (54) | High efavirenz levels (> 4 μg/ml) were predicted by composite mutant genotypes of each of CYP2B6 c.516 GT and TT, as well as by RIF-based TB treatment. 800 mg efavirenz dose appeared to be well tolerated; small sample size may have accounted for the limited number of adverse event reports (patients ≥ 50 kg) |
| Bienvenu et al. 2014 [17] | Antiviral Research | Rwanda | National Ethics Committee of the Ministry of Health in Rwanda (2009-2010) | 80 (62) | CYP2B6 c.516TT was associated with high efavirenz levels compared to others in presence and absence of Rifampicin-based TB treatment. This TB treatment was also shown to affect the positive predictive value of CYP2B6 SNPs, and to lower efavirenz plasma levels significantly, but did not affect the significant reduction of HIV-RNA copies |
| Uttayamakul et al. 2010 [18] | AIDS Research and Therapy | Thailand |
Bamrasnaradura Infectious Diseases Institute (2006-2009) |
124 (65) | The mean 12-hour post-dose plasma efavirenz concentration in patients with TT genotype at weeks 6 and 12 of ART and 1 month after Rifampicin discontinuation were significantly higher. efavirenz levels by Rifampicin was much smaller than that by CYP2B6 c.516 TT genotype |
| Kwara et al. 2008 [19] | Journal of Clinical Pharmacology | Ghana | Lifespan Hospitals (2005-2007) | 26 (26) | Mean plasma efavirenz area under the curve was significantly higher in patients with CYP2B6 c.516 TT. Rifampin treatment does not fully reverse the poor metabolizer phenotype in this genotype group |
Table 2 shows the clinical and demographic characteristics of the patients included in each study. The mean age ranged from 32 to 39 years, with a variable proportion of men and women. In the studies that reported this information, an expected distribution of genotypes (GG, GT, and TT) and variable plasma concentrations were observed between each genotype.
Table 2.
Clinical and demographic characteristics of the participants included in the studies analyzed
| Baseline clinical and demographic population | |||||||
|---|---|---|---|---|---|---|---|
| Author and year | Sex | Frequency genotype | Mean efavirenz plasma concentration (μg/mL) (SD) | AST, U/L, mean (SD) | ALT, U/L Mean (SD) | Genotyping | EPSM and EPDM |
| Von Braun et al.2019 [15] |
F: 67 M: 99 |
GG: 60 GT: 81 TT: 25 |
GG: 2,63 (2,05) GT: 3,53 (2,26) TT: 10,06 (4,71) |
– | – | Real-time PCR | UV-HPLC method |
| Gengiah et al. 2015 [16] |
F: 10 M: 19 |
GG: 27 GT: 21 TT: 6 |
GG: 3 (0,62) GT: 4,66 (6,2) TT: 9,1 (4,09) |
31.1 (16.6) | 24.7 (18.4) | TaqMan genotyping assays | LC-MS/MS |
| Bienvenu et al. 2014 [17] |
F: 37 M: 39 |
GG: 28 GT: 28 TT: 6 |
GG: 1,43 (0,78) GT: 1,9 (1,01) TT: 5,36 (5,33) |
Results not shown | Results not shown | PCR KASP | HPLC-UV |
| Uttayamakul et al. 2010 [18] |
F: 23 M:42 |
GG: 25 GT: 31 TT: 9 |
GG: 2.45 (0.26) GT: 3.35 (0.27) TT: 13.62 (4.21) |
GG: 32.8 (2.35) GT: 40.48 (3.32) TT: 43.22 (10.21) |
GG: 27.0 (3.05) GT: 28.55 (2.89) TT: 31.22 (8.89) |
Real-time PCR | Reverse-phase (HPLC) method |
| Kwara et al. 2008 [19] |
F: 8 M: 18 |
GG: 7 GT: 12 TT: 7 |
GG: 1,08 (0,68) GT: 1,2 (0,75) TT: 4,05 (3,07) |
GG: 57 (31) GT: 33 (11) TT: 49 (29) |
GG: 35 (23) GT: 24 (12) TT: 35 (22) |
Direct sequence chromatograms | Modified reverse HPLC-UV |
AST aspartate aminotransferase, ALT alanine aminotransferase, EPCM efavirenz plasma separation method, EPDM efavirenz plasma detection method, HPLC high-performance liquid chromatography, LC liquid chromatography, MS mass spectrometry, PCR KASP kompetitive allele specific PCR, UV ultraviolet detection
Table 1 summarizes the general characteristics and key findings of the five studies included in the meta-analysis assessing the relationship between CYP2B6 c.516 G>T genotypes and plasma efavirenz concentrations. Each row corresponds to one study, providing details on the author, year, journal, country, study population, and main findings. Overall, these studies collectively demonstrate that the CYP2B6 c.516 TT genotype is strongly associated with higher plasma efavirenz concentrations, independent of Rifampicin-based TB therapy or other clinical covariates.
Table 2 presents the baseline demographic and clinical characteristics of participants from the five studies included in the meta-analysis, highlighting genotype distribution, efavirenz plasma concentrations, immunologic and hepatic parameters, genotyping techniques and separation/detection method. The data consistently demonstrate higher mean efavirenz concentrations in participants carrying the CYP2B6 c.516 TT genotype across all studies, often exceeding therapeutic thresholds, while hepatic enzyme levels and tolerance varied among cohorts.
Comparison of CYP2B6 c.516 G>T Polymorphism Genotypes
Data from five studies reporting efavirenz plasma concentrations stratified by CYP2B6 c.516 G>T polymorphism genotype were analyzed. Pairwise comparisons were made between the GG-GT, GG-TT, and GT-TT genotypes by determining the mean difference.
GG versus GT Comparison
The pooled analysis included 320 patients (147 with the GG genotype and 173 with the GT genotype). The mean difference in efavirenz plasma concentrations between the GG and GT genotypes was − 0.68 μg/mL (95% CI − 1.02 to − 0.34), favoring the GG group. This difference was statistically significant with a Z value of 3.89 and a p value < 0.0001. Heterogeneity between studies was moderate (I2 = 50%, p =0.09), so a random-effects model was used (Fig. 2a).
Fig. 2.
Forest plots showing pooled mean differences in efavirenz plasma concentrations among CYP2B6 c.516 G>T genotypes. a Comparison between GG and GT genotypes showed a non-significant difference. b Comparison between GG and TT genotypes revealed significantly higher plasma concentrations in TT carriers. c Comparison between GT and TT genotypes also showed significantly elevated levels in TT carriers. Random-effects models were applied in all analyses
GG versus TT Comparison
This comparison included 200 patients (147 with the GG genotype and 53 with the TT genotype). A mean difference of − 6.41 μg/mL (95% CI − 9.30 to − 3.52) was observed, indicating that patients with the TT genotype had significantly higher plasma efavirenz concentrations than patients with the GG genotype (Z = 4.35, p < 0.0001). Heterogeneity was high (I2 = 82%, p = 0.0002), so a random-effects model was also used (Fig. 2b).
GT versus TT Comparison
A total of 226 patients were included (173 with GT genotype and 53 with TT). A mean difference of − 5.65 μg/mL (95% CI − 8.40 to − 2.90) was observed, with plasma concentrations being significantly higher in the TT group (Z = 4.03, p < 0.0001). Heterogeneity was considerable (I2 = 78%, p = 0.001), so a random-effects model was also used (Fig. 2c).
Individuals with the TT genotype exhibited significantly higher plasma efavirenz concentrations, with a pooled mean difference of − 6.41 μg/mL (95% CI − 9.30 to − 3.52) compared to the GG genotype and − 5.65 μg/mL (95% CI − 8.40 to − 2.90) compared to the GT genotype.
These absolute differences are clinically significant, as the elevated concentration in TT carriers (ranging from 4.05 to 13.62 μg/mL in the included studies) frequently exceed the established therapeutic range of 1–4 μg/mL), potentially increasing the risk of toxicity.
Heterogeneity Assessment
Heterogeneity was assessed using the chi-square test and the I2 statistic. As described above, the GG versus GT comparison presented moderate heterogeneity (I2 = 50%), while the GG versus TT and GT versus TT comparisons presented high and considerable heterogeneity, respectively (I2 82% and 78%). Based on these findings, a subgroup analysis was performed to explore potential sources of variability among the included studies. They were grouped into two categories according to the geographic region in which they were conducted: Africa and Asia. The analysis was performed excluding the study by Uttayamakul et al. [18], the only study conducted in Asia (Thailand), to assess whether the exclusion of a geographically distinct population influenced the heterogeneity of the results. After eliminating the Asian study, heterogeneity in the GG versus GT comparison decreased to I2 = 40%, and the mean difference remained significant at − 0.72 μg/mL (95% CI − 1.10 to − 0.34). In the GG versus TT comparison, it decreased to I2 = 70%, with a mean difference of − 6.50 μg/mL (95% CI − 9.50 to − 3.50). In the GT versus TT comparison, it decreased to I2 = 65%, and the mean difference was − 5.75 μg/mL (95% CI − 8.50 to − 3.00). The reduction in heterogeneity suggests that the geographic origin of the population is a relevant factor that may influence variability between studies. This finding could be explained by differences in the allele frequency of the CYP2B6 c.516 G>T polymorphism in enzyme expression patterns across different regions of the world. In addition, a subgroup analysis of patients with HIV infection only and no concomitant tuberculosis treatment was performed in three of the studies. In this subgroup, the TT genotype was also associated with significantly higher efavirenz concentrations, suggesting that the effect of the CYP2B6 c.516 G>T polymorphism is significant even in the absence of Rifampin.
Assessment of Risk of Bias and Publication Bias
The risk of bias of the included studies was assessed using the RoB-2 [20] and ROBINS-I [21] tools, depending on the study design. For randomized controlled trials, the studies conducted by Gengiah et al. [16] and Uttayamakul et al. [18] were classified as having an overall risk of bias of “some concerns.” Gengiah et al. [16] showed potential bias in the selection of reported outcomes, while Uttayamakul et al. [18] raised concerns regarding intervention bias and outcome measurement. However, the randomization process and missing data handling were adequate in both cases, reducing the impact of these limitations on the validity of the meta-analysis.
For non-randomized studies, the ROBINS-I tool indicated that the studies by Von Braun et al. [15] and Bienvenu et al. [17] presented a moderate risk of bias, while Kwara et al. [19] was classified as having a serious risk due to the presence of significant uncontrolled confounding. The main source of bias in observational studies was confounding, followed by concerns about outcome measurement. A funnel plot analysis of the primary outcome showed a relatively symmetrical distribution of studies in the GG-GT, GG-TT, and GT-TT comparisons, suggesting a low likelihood of publication bias. The dispersion of studies followed an expected pattern, with the largest studies near the pooled effect and smaller studies more dispersed at the bottom. These findings indicate that the results of the meta-analysis are robust and reliable, with no clear evidence of systematic bias, as shown in the corresponding figure (see complementary material).
Discussion
The results of our meta-analysis confirm a significant association between the CYP2B6 c.516 G>T polymorphism and efavirenz plasma concentrations, with a clear pattern: patients with the TT genotype present significantly higher levels than GT and GG carriers [14–18]. This effect of the T allele has already been described in previous studies [22, 23], which documented increased efavirenz exposure in T allele carriers, associated with lower CYP2B6 enzyme activity. Additionally, a recent study analyzed the relationship between the CYP2B6 *1/*6 and *6/*6 genotypes and an increased risk of efavirenz- and nevirapine-induced hepatotoxicity [24]. This complements our findings from a clinical perspective, demonstrating that the presence of the T allele not only alters plasma concentrations but may also predispose to adverse events related to liver toxicity.
The main finding of our study was that the effect of the c.516 G>T polymorphism is maintained and may even be intensified in patients coinfected with tuberculosis receiving combination therapy with Rifampin and Isoniazid. Although Rifampin is a potent enzyme inducer, our results show that it fails to counteract the reduction in efavirenz metabolism in patients with the TT genotype. This phenomenon may be explained by the concentration-dependent inhibition of CYP2B6 induced by Isoniazid, as reported in previous studies [16], which also highlighted the possible role of NAT2 (N-acetyltransferase 2) polymorphisms in efavirenz clearance during combination therapy. Thus, efavirenz metabolism in coinfected patients appears to be modulated by a complex interaction between genetic and pharmacological factors.
Among the limitations of this meta-analysis, only five studies were included, which limits the power of subgroup analyses. Considerable heterogeneity was also observed in comparisons that included patients with the TT genotype, possibly explained by ethnic differences, dose, body weight, quantification methods, or concomitant treatment. In the subgroup of patients without tuberculosis, differences between TT and other genotypes did not reach statistical significance, likely due to the small sample size. Finally, information on clinical effects associated with high concentrations (such as neuropsychiatric symptoms and hepatotoxicity) was not systematically available in the included studies. Additionally, non-normal distributions of efavirenz plasma concentrations may have influenced the pooled estimates; however, this could not be formally assessed due to the use of aggregated data. Furthermore, the small number of included studies limits the reliability of this assessment. Formal statistical tests for funnel plot asymmetry, such as Egger’s regression test, were not performed due to their low statistical power and potential to produce misleading results. Therefore, publication bias cannot be reliably assessed and cannot be definitively excluded.
Ethnic variability may contribute to the observed heterogeneity. The CYP2B6 c.516 G>T polymorphism is more frequent in African populations and less common in Asian and Caucasian populations, influencing efavirenz metabolism. Although only one Asian study was included, it showed high efavirenz concentrations among TT carriers, suggesting that both genetic and non-genetic factors influence drug exposure [18]. These findings underscore the need for more diverse populations in pharmacogenetic research.
Despite these limitations, the results reinforce the clinical utility of CYP2B6 genotyping, especially in the context of HIV-TB coinfection. Identifying patients with poor metabolism would allow for the implementation of personalized dosing strategies that minimize toxicity and optimize treatment adherence. As discussed in previous reviews [25], the main challenge for implementing pharmacogenetics in clinical practice is not the lack of evidence but rather the integration of this information into healthcare systems and the training of medical personnel. Evidence from prior research [24] emphasizes the need to apply pharmacogenomics in diverse and vulnerable populations, given that therapeutic efficacy can be profoundly influenced by specific genetic variants.
Conclusions
This meta-analysis demonstrates that the CYP2B6 c.516 G>T polymorphism is significantly associated with increased plasma exposure to efavirenz, especially in individuals with the homozygous TT genotype. This effect persists even under concomitant treatment with Rifampin and Isoniazid. These findings support the clinical relevance of genetic profiling in efavirenz pharmacokinetics and underscore the usefulness of incorporating CYP2B6 genotyping as a tool to optimize therapeutic regimens, reduce adverse events, and advance personalized medicine in populations with a high prevalence of HIV-tuberculosis coinfection.
Supplementary Information
Below is the link to the electronic supplementary material.
Author Contributions
AVS: Conceptualization, Methodology, Formal analysis, Investigation, Data curation, Writing – review & editing. GNR and AMRD: Methodology, Formal analysis, Investigation, Data curation, Writing – review & editing. GRU: Methodology, Supervision, Project administration, Writing – review & editing. YLB: Conceptualization, Formal analysis, Investigation, Data curation, Writing – original draft, Writing – review & editing. JRCM: Conceptualization, Methodology, Supervision, Project administration, Writing – review & editing.
Funding
The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.
Data Availability
All data analyzed in this meta-analysis were derived from previously published studies. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request
Declarations
Conflict of Interest
The authors have no relevant financial or non-financial interests to disclose
Ethical Approval
This study is a secondary analysis of previously published data. All included primary studies reported approval from their respective ethics committees or institutional review boards. No new data collection involving human participants was conducted; therefore, additional ethical approval was not required.
Consent to Participate
Not applicable.
Consent for Publication
Not applicable.
Contributor Information
Yair Lara-Blanco, Email: yair.lara91@uabc.edu.mx.
José Román Chavez-Méndez, Email: roman.chavez@uabc.edu.mx.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
All data analyzed in this meta-analysis were derived from previously published studies. The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request