Poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis: A systematic review and meta-analysis

Ayinalem Alemu; Zebenay Workneh Bitew; Getu Diriba; Getachew Seid; Shewki Moga; Saro Abdella; Emebet Gashu; Kirubel Eshetu; Getachew Tollera; Mesay Hailu Dangisso; Balako Gumi

doi:10.1371/journal.pone.0286194

. 2023 Jul 19;18(7):e0286194. doi: 10.1371/journal.pone.0286194

Poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis: A systematic review and meta-analysis

Ayinalem Alemu ^1,^2,^*, Zebenay Workneh Bitew ³, Getu Diriba ¹, Getachew Seid ^1,², Shewki Moga ¹, Saro Abdella ¹, Emebet Gashu ⁴, Kirubel Eshetu ⁵, Getachew Tollera ¹, Mesay Hailu Dangisso ¹, Balako Gumi ²

Editor: Frederick Quinn⁶

PMCID: PMC10355410 PMID: 37467275

Abstract

Background

To date, isoniazid mono-resistant tuberculosis (TB) is becoming an emerging global public health problem. It is associated with poor treatment outcome. Different studies have assessed the treatment outcome of isoniazid mono-resistant TB cases, however, the findings are inconsistent and there is limited global comprehensive report. Thus, this study aimed to assess the poor treatment outcome and its associated risk factors among patients with isoniazid mono-resistant TB.

Methods

Studies that reported the treatment outcomes and associated factors among isoniazid mono-resistant TB were searched from electronic databases and other sources. We used Joana Briggs Institute critical appraisal tool to assess the study’s quality. We assessed publication bias through visual inspection of the funnel plot and confirmed by Egger’s regression test. We used STATA version 17 for statistical analysis.

Results

Among 347 studies identified from the whole search, data were extracted from 25 studies reported from 47 countries. The pooled successful and poor treatment outcomes were 78% (95%CI; 74%-83%) and 22% (95%CI; 17%-26%), respectively. Specifically, complete, cure, treatment failure, mortality, loss to follow-up and relapse rates were 34%(95%CI; 17%-52%), 62% (95%CI; 50%-73%), 5% (95%CI; 3%-7%), 6% (95%CI; 4%-8%), 12% (95%CI; 8%-17%), and 1.7% (95%CI; 0.4%-3.1%), respectively. Higher prevalence of pooled poor treatment outcome was found in the South East Asian Region (estimate; 40%, 95%C; 34%-45%), and African Region (estimate; 33%, 95%CI; 24%-42%). Previous TB treatment (OR; 1.74, 95%CI; 1.15–2.33), having cancer (OR; 3.53, 95%CI; 1.43–5.62), and being initially smear positive (OR; 1.26, 95%CI; 1.08–1.43) were associated with poor treatment outcome. While those patients who took rifampicin in the continuation phase (OR; 0.22, 95%CI; 0.04–0.41), had extrapulmonary TB (OR; 0.70, 95%CI; 0.55–0.85), and took second-line injectable drugs (OR; 0.54, 95%CI; 0.33–0.75) had reduced risk of poor treatment outcome.

Conclusion

Isoniazid mono-resistant TB patients had high poor treatment outcome. Thus, determination of isoniazid resistance pattern for all bacteriologically confirmed TB cases is critical for successful treatment outcome.

PROSPERO registration number: CRD42022372367

Introduction

Tuberculosis (TB) is causing a huge public health impact being the second cause of mortality among infectious diseases. There were 9.9 million TB cases and more than 1.5 million deaths due to TB in 2020 [1]. The efforts for the prevention and control of TB becomes challenging due to the emergence of drug resistant TB mainly with respect to treatment outcome. Drug-resistant TB is associated with poor treatment outcome [1, 2]. Based on the 2021 global TB report, the global successful treatment outcome among drug susceptible and Multi-drug resistant TB (MDR-TB)/ Rifampicin resistant TB (RR-TB) cases were 86% and 59%, respectively [1]. Drug resistant TB have different categories including mono-resistant TB. When TB is caused by Mycobacterium tuberculosis strains which are resistant only to one anti-TB drug it is called mono-resistant TB and isoniazid mono-resistant TB is among the categories [1, 2].

The world health organization (WHO) through the END TB Strategic document recommends calls for the early TB diagnosis drug sensitivity testing (DST) [3]. The drug resistance pattern should be determined for all bacteriologically confirmed TB cases to put patients on the right treatment for successful treatment outcome and to prevent the emergence of additional drug-resistance. Even though, there are improvements in the recent years, this becomes difficult in many TB endemic low and middle-income countries having resource limitations. To date, due to the implementation of Xpert MTB/RIF assay many countries reported RR-TB to the WHO [1, 2]. In this assay, the resistance profile for the other potent anti-TB drug isoniazid is unknown that might have made the isoniazid mono-resistant TB cases to be less reported and be treated as drug susceptible TB [2]. However, about 11% of TB patients worldwide are estimated to have isoniazid resistant, rifampicin susceptible TB [2].

Studies conducted in different settings indicated that isoniazid mono-resistant TB is a problem in different countries [4–8]. The incidence of isoniazid mono-resistant TB is increasing and it is higher than RR-TB globally [9]. In addition, studies revealed that those isoniazid mono-resistant TB cases had higher rate of poor treatment outcome compared to the drug-susceptible TB cases [10–13]. There are studies that assessed the treatment outcome of isoniazid mono-resistant TB cases [4–7, 10–30], however, the findings are inconsistent. In addition, there is no comprehensive report at the global level. Thus, this study aimed to assess the poor treatment outcome and the associated risk factors among patients with isoniazid mono-resistant TB.

Methods

Protocol registration

The protocol for this study is registered on the international prospective register of systematic reviews (PROSPERO) with a registration number CRD42022372367.

Information source and search strategy

This study was developed following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) reporting checklist [31] (S1 Table). Article searching was conducted systematically from the electronic databases including PubMed, CINAHL, Global Health, Global Health Medicus and Environment Index. In addition, our search extends to other grey literature sources such as Google and Google Scholar. The search was conducted up to 20 November 2022 for studies published in English language. Two authors (AA, EG) have conducted the article searching independently. The third author (ZWB) managed the inconsistencies arose between the two authors. The search was conducted using the keywords; isoniazid mono-resistant tuberculosis, treatment outcome and risk factors/determinants. The Boolean operators OR and AND were used accordingly. The search string for PubMed was ("Treatment Outcome"[MeSH Terms] OR (("poverty"[MeSH Terms] OR "poverty"[All Fields] OR "poor"[All Fields]) AND ("Treatment Outcome"[MeSH Terms] OR ("treatment"[All Fields] AND "outcome"[All Fields]) OR "Treatment Outcome"[All Fields])) OR ("Treatment Outcome"[MeSH Terms] OR ("treatment"[All Fields] AND "outcome"[All Fields]) OR "Treatment Outcome"[All Fields])) AND (("isoniazid"[MeSH Terms] OR "isoniazid"[All Fields] OR "isoniazide"[All Fields]) AND "mono-resistant"[All Fields]) (S2 Table).

Study selection procedure

We have followed a step-wise approach to select the eligible studies. Primarily, all the studies identified from the whole search were exported to EndNote X8 citation manager, and we have removed the duplicates. In the next step, we have screened the articles by title and abstract. Then, full-text assessment was conducted for the remaining articles. Finally, we have included the articles that passed the full-text review in the final analysis. The article selection procedure was conducted by two independent authors (GD, GS) using pre-defined criteria that considered study subjects, study designs, quality, and outcome (Fig 1).

PICOS criteria

Participants: Isoniazid mono-resistant tuberculosis patients

Intervention: Anti-TB treatment

Comparator: Successful treatment outcome

Outcome: Poor treatment outcome

Study design: Observational studies.

Study setting: Any setting in any country across the globe

Inclusion and exclusion criteria

Studies that reported either TB treatment outcome or risk factors of poor treatment outcome or both in patients with isoniazid mono-resistant TB were included in the study. There was no restriction on entering the study in terms of sample size. The exclusion criteria were review studies, and not differentiated the target population.

Data extraction

Data were extracted from the articles included in the final analysis using Microsoft Excel 2016 spreadsheet. The extracted data included; primary author name, publication year, country, data collection period, study design, data collection time (prospective vs retrospective), study setting/place, age of study participants, number of study participants, number having successful (completed, cured) and poor treatment outcomes (mortality, treatment failure, loss to follow-up), number of relapse in successfully treated cases, and factors associated with poor treatment outcomes. Data were extracted by two independent authors (AA, ZWB), and the third author (GD) managed the inconsistencies that arose between the two authors.

Risk of bias (quality) assessment of included studies

We have evaluated the methodological reputability and quality of the findings of the included studies using the Joanna Briggs Institute (JBI) critical appraisal tools for observational studies [32]. Two independent authors (GS, KE) conducted the quality assessment, and the third author (ZWB) resolved the inconsistencies. The checklist for cross-sectional, case control and cohort studies consists of 8, 10, and 11 indicators, respectively. Each indicator was equally scored and summed up to give 100%. The quality of the studies was scored to have high, medium and low quality if the overall quality score was >80%, 60–80% and <60%, respectively (S3

Table). The presence of publication bias was explored through visual evaluation of the funnel plot such that asymmetry of the funnel plot indicated the presence of publication bias. Furthermore, we have conducted egger’s regression test to confirm the presence of publication bias (P<0.05).

Outcomes

The primary outcome of this study was the treatment outcomes such as the successful and poor treatment outcomes along with different categories among patients with isoniazid mono-resistant tuberculosis. The secondary outcomes were the factors that associated with poor treatment outcomes in those patients.

Operational definition

The operational definition for isoniazid mono-resistant tuberculosis was based on the WHO definition. This type of tuberculosis is caused by Mycobacterium tuberculosis strains that are resistant to isoniazid but susceptible to rifampicin confirmed in vitro [33]. The definitions for the treatment outcomes is based on the WHO classification of TB treatment outcomes as described in the guideline [34].

Ethical approval and consent to participate

Since this study is based on a review of published articles, ethical approval is not mandatory. The protocol is registered on PROSPERO.

Data synthesis and statistical analysis

The pooled estimates of successful and poor treatment outcomes among patients with isoniazid mono-resistant TB was determined with its 95%CI by assuming the true effect size varies between studies. The pooled estimate for successful and poor treatment outcomes were determined as the ratio of numbers of isoniazid mono-resistant TB patients with successful and poor treatment outcomes to the total treated isoniazid mono-resistant TB patients, respectively. Besides, the pooled OR along with 95%CI was estimated for each factor to determine the factors associated with poor treatment outcomes. We have also performed a stratified analysis. We presented the data using the forest plot. The heterogeneity among the studies was assessed using the I² heterogeneity test and a value above 50% indicated the presence of substantial heterogeneity among studies [35, 36]. We have performed bi-variable and multi-variable meta-regression to assess the association of study year and sample size on poor treatment outcome. To assess the presence of publication bias, the funnel plot was inspected visually and Egger’s regression test was conducted. For those parameters that had a publication bias (P<0.05) in the Egger’s regression test [37, 38], we have performed a trim and fill analysis to adjust the publication bias. The statistical analysis was conducted using STATA version 17.

Results

Characteristics of included studies

From the whole search, we identified 347 studies and after removing 129 duplicates, 218 were screened by title and abstract. At this stage, 189 studies were excluded and the remaining 29 studies were screened by full text review. Finally, 25 studies were included in this study [4–7, 10–30]. These studies were reported from five continents and from all the six WHO regions. Accordingly, the most frequent number of studies were reported from Asia with 11 studies followed by North America (5 studies), Africa (4 studies), Europe (3 studies), and South America (2 studies). Per WHO regional classification, relatively higher number of studies were reported from the Region of Americas (AMR) with 7 studies. The frequencies of studies in the other regions were; West Pacific Region (WPR) (5 studies), African Region (AFR) (4 studies), European Region (EUR) (4 studies), South Eastern Asian Region (SEAR) (3 studies), and Eastern Mediterranean Region (EMR) (2 studies). The studies were reported from 47 countries and a maximum of two studies were reported from a single country (South Africa, Taiwan, China, Portugal, USA, Canada, India, and Peru). A single study conducted in Europe comprises data collected from 31 countries [20] that made the number of countries included in the current systematic review and meta-analysis study to be 47 in number.

The studies were published from 2009 [15, 29] to 2022 [28]. The data collection period for most of the studies were after 2000 except two studies where the data collection period was from October 1992 to October 2005 for one study [15] and from 1995 to 2010 for the other study [11]. In the majority of the studies (88%, 22), data were collected retrospectively. The data in these studies were collected either from a health facility or from the national surveillance data registry database (Table 1).

Table 1. Characteristics of individual studies on the poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis included in the current systematic review and meta-analysis.

Author year	Publication year	Country	Study period	Study design	Data collection time	Study setting	Age group	Sample size	Successful outcome		Poor outcome
Author year	Publication year	Country	Study period	Study design	Data collection time	Study setting	Age group	Sample size	N	%	N	%
Chien et al., 2014	2014	Taiwan	January 2004 to October 2011	Retrospective cohort study	Retrospectively	Four hospitals in northern, central, southern and eastern Taiwan	All age groups (Median age was 64 years)	395	328	83.04	67	16.96
Bachir et al., 2021	2021	France	January 1, 2016 to December 31, 2017	Multicenter case-control study	Retrospectively	University hospitals of Paris, Lille, Caen and Strasbourg	Median age was 35 years	97	75	77.32	22	22.68
Cattamanchi et al., 2009*	2009	USA	October 1992 to October 2005	Retrospective cohort study	Retrospectively	San Francisco Department of Public Health Tuberculosis Control Section	Median age was 47 years	137	-	-	-	-
Kwak et al., 2020	2020	South Korea	January 2005 to December 2018	Retrospective record review	Retrospectively	South Korean tertiary referral hospital	≥18 years	195	164	84.10	31	15.90
Binkhamis et al., 2021	2021	Saudi Arabia	May 2015 and April 2019	Cross-sectional analytical study	Retrospectively	King Khalid University Hospital	All age groups (range:1–90 years)	9	5	55.56	4	44.44
Murwira, et al., 2020	2020	Zimbabwe	March 2017 and December 2018	Retrospective cohort study	Retrospectively	National TB Reference Laboratory (NTBRL) in Bulawayo City and National TB programme	All age groups (Median age was 36 years, Interquartile range, was 29–45 years)	31	25	80.65	6	19.35
Chierakul et al., 2014	2014	Thailand	July 2009 and July 2011	Retrospective cohort study	Retrospectively	Siriraj Hospital	> 15 years	28	20	71.43	-	-
Jacobson et al., 2011	2011	South Africa	28 November 2000 to 28 May 2009	Retrospective cohort study	Retrospectively	22 clinics in the rural Cape Winelands East and Overberg Districts, Western Cape Province	All age groups (range:11–67 years)	151	101	66.89	50	33.11
Garcia et al., 2018	2018	Peru	January 2012 and December 2014	Cross-sectional study	Retrospectively	National registry of drug-resistant tuberculosis	All age groups	947	731	77.19	216	22.81
Karo et al., 2018	2018	31 European countries	2002 to 2014	Observational study	Retrospectively	European Surveillance System (TESSy)	All age groups (Median age was 41 years)	6796	5611	82.56	1185	17.44
Saldaña et al., 2016	2016	Mexico	1995 to 2010	Prospective cohort study	Prospectively	12 municipalities in the Orizaba Health Jurisdiction in Veracruz State	> 15 years	85	64	75.29	21	24.71
Villegas et al., 2016	2016	Peru	March 2010 to December 2011	Prospective cohort study	Prospectively	34 health facilities in a northern district of Lima	All age groups	82	63	76.83	19	23.17
Edwards et al., 2020	2020	Canada	2007 to 2017	Retrospective cohort study	Retrospectively	One of three centralized comprehensive clinics in the province of Alberta	Median age was 37 years	98	90	91.84	8	8.16
Wang et al., 2014	2014	Taiwan	2006 January to 2007 December	Retrospective cohort study	Retrospectively	Chang Gung Memorial Hospital	All age groups	134	114	85.07	20	14.93
Sayfutdinov et al., 2021	2021	Uzbekistan	2017 to 2018	Retrospective cohort study	Retrospectively	Two regions of Uzbekistan (Fergana and Bukhara)	All age groups	132	105	79.55	27	20.45
der Heijden et al., 2017	2017	South Africa	2000 to 2012	Longitudinal study	Retrospectively	Prince Cyril Zulu Communicable Diseases Centre (PCZCDC)	All age groups (Median age was 34 years)	405	235	58.02	170	41.98
Romanowski et al., 2017	2017	Canada	2002 to 2014	Retrospective record review	Retrospectively	BC Centre for Disease Control (BCCDC)	All age groups (Median age was 46 years)	152	140	92.11	12	7.89
Santos et al., 2018	2018	Portugal	01 January 2008 to 31 December 2014	Retrospective record review	Retrospectively	National-Tuberculosis-Surveillance-System (SVIG-TB)	All age groups (Median age was 44 years)	232	210	90.52	22	9.48
Shao et al., 2020	2020	China	2013 to 2018	Retrospective cohort study	Retrospectively	Four national DR-TB surveillance sites of Jiangsu Province	All age groups (Median age was 48 years)	63	52	82.54	11	17.46
Kuaban et al., 2020	2020	Cameroon	January 2012 to March 2015	Retrospective record review	Retrospectively	In all the TB diagnostic and treatment centres (DTCs) in four regions of Cameroon namely the North West, South West, West, and Littoral regions	All age groups (range: 17–79 years)	45	32	71.11	13	28.89
Salindri et al., 2018	2018	USA	2009 to 2014	Retrospective cohort study	Retrospectively	Georgia State Electronic Notifiable Disease Surveillance System (SENDSS)	≥15 years	140	124	88.57	16	11.43
Nagar et al., 2022	2022	India	January 2019 to December 2020	Retrospective record review	Retrospectively	Ahmedabad city from Ni-kshay, an online web-based portal	≥18 years	243	144	59.26	99	40.74
Tabarsi et al., 2009	2009	Iran	2003 to 2005	Prospective cohort study	Prospectively	Masih Daneshvari Hospital	All age groups	42	37	88.10	5	11.90
Chunrong et al., 2020	2020	China	January 2016 to January 2019	Retrospective record review	Retrospectively	Shenzhen’s drug-resistant TB project	All age groups (17–75 years)	144	102	70.83	42	29.17
Garg et al., 2019	2019	India	January 1 to December 31, 2017	Retrospective record review	Retrospectively	At the nodal DRTB centre, Department of Pulmonary Medicine, Government Medical College and Hospital, Chandigarh	All age groups	52	34	65.38	18	34.62

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“-“; Not specifically indicated

* the study only indicated the treatment completion rate the total successful treatment outcome including the cured cases and the poor treatment outcome (failure, death and lost to follow-up) are not indicated in the study.

Pooled treatment outcomes among isoniazid mono-resistant tuberculosis patients

In the current study, we extracted data to estimate the pooled prevalence of successful treatment outcome including cure rate and treatment completion rate, poor treatment outcome including death rate, treatment failure rate and loss to follow-up, relapse after successful treatment outcome, and factors associated with poor treatment outcome among patients with isoniazid mono-resistant tuberculosis.

Data were extracted from 24 and 23 studies to estimate the pooled prevalence of successful treatment outcome and poor treatment outcome, respectively. The largest sample size was 6796 in a study that comprises 31 European countries [20], while the smallest sample size was 9 in a study conducted in Saudi Arabia [21]. Among the studies, 11 studies had a sample size below 100 while the remaining studies had a sample size of 132 and above.

Based on data collected from 24 studies comprising 10, 698 isoniazid mono-resistant TB patients, 8606 had successful treatment outcome that gave a pooled estimate of 78% (95%CI; 74–83, I²; 94.02%) (Fig 2). The symmetry of the funnel plot (Fig 3) and the statistical insignificance of the egger’s regression test showed there is no publication bias (P = 0.080). Specifically, the pooled treatment completed and cured rate among isoniazid mono-resistant TB patients were 34% (95%CI; 17–52, I²; 99.26%) (S1 and S2 Figs) and 62% (95%CI; 50–73, I²; 96.91%) (S3 and S4 Figs), respectively. Based on the WHO regional classification, the pooled prevalence of successful treatment outcome from the highest to lowest pooled estimate were; AMR (estimate; 84%; 95%CI; 78–90, I²; 87.66%), EUR (estimate; 84%; 95%CI; 77–91, I²; 91.21%), WPR (estimate; 82%; 95%CI; 77–86, I²; 64.67%), EMR (estimate; 75%; 95%CI; 44–106, I²; 73.41%), AFR (estimate; 67%; 95%CI; 58–76, I²; 74.28%), and SEAR (estimate; 62%; 95%CI; 56–69, I²; 13.74%) (Fig 2) (Table 2).

Table 2. The summary of the pooled on the poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis per different categories.

Indicators	Number of studies	Pooled estimates
		Estimate (prevalence/OR), 95%CI	Heterogeneity
		Estimate (prevalence/OR), 95%CI	I²
Successful treatment outcome
Over all	24	78% (74–83)	94.02%
AFR	4	67% (58–76)	74.28%
AMR	6	84% (78–90)	87.66%
EMR	2	75% (44–106)	73.41%
EUR	4	84% (77–91)	91.21%
SEAR	3	62% (56–69)	13.74%
WPR	5	82% (77–86)	64.67%
Cure rate	15	62% (50–73)	96.91%
Complete rate	14	34% (17–52)	99.26%
Poor treatment outcome
Over all	23	22% (17–26)	94.08%
AFR	4	33% (24–42)	74.28%
AMR	6	16%(10–22)	87.75%
EMR	2	25% (-6-56)	73.41%
EUR	4	17% (11–22)	85.06%
SEAR	2	40% (34–45)	0.00%
WPR	5	18% (14–23)	64.63%
Treatment failure	16	5% (3–7)	93.97%
Loss to follow-up	18	12% (8–17)	96.58%
Mortality	23	6% (4–8)	88.73%
Relapse after successful outcome	8	1.7% (0.4–3.1)	n33.58%
Risk factors of poor treatment outcome
Previous anti-TB treatment	9	1.74 (1.15–2.33)	45.10%
Male sex	9	1.34 (0.90–1.77)	43.67%
Older age	9	0.97 (0.62, 1.32)	87.56%
Had HIV co-infection	6	2.26 (0.60–3.91)	43.47%
Smoking	2	2.54 (0.89–4.20)	13.69%
Had diabetes	3	1.16 (0.70–1.63)	0.00%
Had cancer	2	3.53 (1.43–5.62)	0.00%
Had end stage renal disease	2	3.15 (-0.07–6.38)	0.00%
Being smear positive initially	7	1.26 (1.08–1.43)	2.13%
Had high level INH resistance	6	0.79 (0.38–1.21)	28.22%
Took INH in the initiation phase	2	0.72(0.33–1.11)	0.00%
Took STR in the initiation phase	2	0.76 (0.15–1.37)	0.00%
Took FLQ in the initiation phase	3	0.94 (0.48–1.39)	0.00%
Took RIF in the continuation phase	2	0.22 (0.04–0.41)	0.00%
Took PZA in the continuation phase	2	0.87 (0.27–1.47)	0.005
Had extrapulmonary tuberculosis	4	0.70 (0.55–0.85)	0.00%
Not culture converted after 2 months of treatment	4	1.30 (0.59–2.00)	0.00%
Took SLIDs	2	0.54 (0.33–0.75)	0.00%
Had cavity lesion on the chest radiograph	3	1.23 (0.62–1.84)	0.00%

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AFR; African region, AMR; Region of the Americas, EMR; Eastern Mediterranean Region, EUR; European Region, SEAR; South Eastern region, WPR; West Pacific Region, HIV; Human Immunodeficiency Virus, INH; Isoniazid, RIF; Rifampicin, STR; Streptomycin; FLQ; Fluoroquinolones, PZA; Pyrazinamide; SLIDs; Second Line Injectable Drugs, OR; Odds Ratio

The poor treatment outcome was estimated from 23 studies having 10,670 isoniazid mono-resistant TB patients. From these individuals, 2084 had poor treatment outcome that yield a pooled estimate of 22% (95%CI; 17–26, I²; 94.08%) (Fig 4). The egger’s regression test showed there is no publication bias (P = 0.107) (Fig 5). Specifically, the pooled treatment failure, mortality and loss to follow-up rates were 5% (95%CI; 3–7, I²; 93.97%) (S5 and S6 Figs), 6% (95%CI; 4–8, I²; 88.73%) (S7 and S9 Figs), and 12% (95%CI; 8–17, I²; 96.58%) (S9 and S10 Figs), respectively. Based on the WHO regional classification, the pooled prevalence of poor treatment outcome from the highest to lowest pooled estimate was; SEAR (estimate; 40%; 95%C; I34-45, I²; 0.00%), AFR (estimate; 33%; 95%CI; 24–42, I²; 74.28%), EMR (estimate; 25%; 95%CI; -0.06–56, I²; 73.41%), WPR (estimate; 18%; 95%CI; 14–23, I²; 64.63%), EUR (estimate; 17%; 95%CI; 11–22, I²; 85.06%), and AMR (estimate; 16%; 95%CI; 10–22, I²; 87.75%) (Fig 4) (Table 2).

Pooled prevalence of relapse among successfully treated isoniazid mono-resistant tuberculosis patients

In this study, we have also assessed the relapse rate among isoniazid mono-resistant TB patients who had successful treatment outcome. We extracted data from eight studies comprising 970 successfully treated isoniazid mono-resistant TB cases. From these individuals, 28 developed relapse. The relapse period started from treatment completion and extends up to two years after treatment. Based on the random-effects model, the pooled prevalence of relapse among successfully treated isoniazid mono-resistant TB cases was 1.7% (95%CI; 0.4–3.1, I²; 44.58%) (Fig 6).

Meta-regression

Besides, we have conducted a meta-regression analysis to assess the effect of sample size and publication year on the heterogeneity among studies that reported poor treatment outcome among isoniazid mono-resistant TB patients. The multivariable meta-regression model revealed that sample size (P = 0.713) and publication year (P = 0.464) did not significantly affected heterogeneity among studies (Table 3).

Table 3. Meta-regression analysis of heterogeneity using sample size and publication year on poor treatment outcome.

Variable	Unadjusted model		Adjusted model
Variable	Coefficient (95%CI)	P-value	Coefficient (95%CI)	P-value
Sample size	-5.76e-06 (-0.000035, 0.0000241)	0.719	-5.64e-06 (-0.0000357, 0.0000244)	0.713
Publication year	0.0051572 (-0.0085616, 0.0188759)	0.461	.0052476 (-0.0087989, 0.0192942)	0.464

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Risk factors of poor treatment outcome in isoniazid mono-resistant tuberculosis patients

In the current study, we assessed the risk factors associated with poor treatment outcome in isoniazid mono-resistant TB patients. We have performed the pooled estimate for the factors reported at least by two studies. We have estimated the pooled OR for 19 variables. The risk factors analyzed included demographic (sex, age group), smoking status, clinical factors such as having co-morbidities including diabetes, cancer, end-stage renal failure, and HIV, presence of cavity lesion in the chest radiograph, type of TB (extra-pulmonary vs pulmonary), initial smear status (smear positive vs smear negative), culture conversion after 2 months, drug-resistance level of isoniazid (high level vs low-level), and per taking different anti-TB drugs during initiation phase isoniazid (INH), streptomycin (STR), fluoroquinolones (FLQ), second-line injectable drugs (SLIDs) and continuation phase (rifampicin (RIF), (pyrazinamide (PZA)).

Statistically significant association was found for previous TB history (pooled OR; 1.74; 95%CI; 1.15–2.33, I²; 45.10%) (Fig 7), having cancer, (pooled OR; 3.53; 95%CI; 1.43–5.62, I²; 0.00%) (S11 Fig), initially smear positive (pooled OR; 1.26, 95%CI; 1.08–1.43, I²; 2.13%) (Fig 8), taking RIF in the continuation phase (pooled OR; 0.22, 95%CI; 0.04–0.41, I²; 0.00%) (S12 Fig), having EPTB (pooled OR; 0.70, 95%CI; 0.55–0.85, I²; 0.00%) (S13 Fig), and taking SLIDs (pooled OR; 0.54, 95%CI; 0.33–0.75, I²; 0.00%) (S14 Fig). Accordingly, individuals with previous TB treatment history had 1.74 times the odds to had poor treatment outcome compared to new patients. Those patients who had cancer had 3.53 times the odds to develop poor treatment outcome compared to the counterparts. In addition, those patients who were smear positive initially had 1.26 times the odds to develop poor treatment outcome compared to those having smear negative TB initially. Patients who took RIF in the continuation phase had 78% reduced risk to have poor treatment outcome compared to their counterparts. Furthermore, those who took SLIDs had 45% reduced risk to have poor treatment outcome compared to their counterparts. Besides, those patients with EPTB had 30% reduced risk of poor treatment outcomes compared to those who had pulmonary TB (Table 2).

Statistically significant association was not found for being male (pooled OR; 1.34, 95%CI; 0.90–1.77, I²; 43.67%) (S15 Fig), older age (pooled OR; 0.97, 95%CI; 0.62–1,32, I²;85.56%) (S16 Fig), being smoker (pooled OR; 95%CI; 0.89–4.20, I²; 13.69%) (S17 Fig), having DM (pooled OR; 1.16, 95%CI; 0.70–1.63, I²; 0.00%) (S18 Fig), having end-stage renal failure (pooled OR; 3.15, 95%CI; -0.07–6.38, I²; 0.00%) (S19 Fig), being HIV positive (pooled OR; 2.26, 95%CI; 0.60–3.91, I²; 43.47%) (S20 Fig), being high level INH resistance (pooled OR; 0.79, 5%CI; 0.36–1.21, I²; 28.22%) (S21 Fig), taking INH in the initiation phase (pooled OR; 0.72, 95%CI; 0.33–1.11, I²; 0.00%) (S22 Fig), taking STR in the initiation phase (pooled OR; 0.76, 95%CI; 0.15–1.37, I²; 0.00%) (S23 Fig), taking FLQ in the initiation phase (pooled OR; 0.94, 95%CI; 0.48–1.39, I²; 0.00%) (S24 Fig), taking PZA in the continuation phase (pooled OR; 0.87, 95%CI; 0.27–1.47, I²; 0.00%) (S25 Fig), not culture converted after 2 months (pooled OR; 1.30, 95%CI; 0.59–2.00, I²; 0.00%) (S26 Fig), and the presence cavity lesion in the chest radiograph (pooled OR; 1.23, 95%CI; 0.62–1.84, I²; 0.00%) (S27 Fig) (Table 2).

Discussion

Based on the pooled estimates, about one fifth of isoniazid mono-resistant TB patients had poor treatment outcomes and different factors are associated with this. The study findings of this study revealed that the successful treatment rate among isoniazid mono-resistant TB patients was 79%. This finding is lower than the global average of the successful treatment outcome among drug-susceptible TB cases which was 85% and 86% for people newly enrolled on treatment in 2018 and in 2019, respectively [1, 2]. However, this is higher than MDR/RR-TB cases which was 59% based on the latest cohort [1], thus determining isoniazid resistant status for all bacteriologically confirmed TB cases may contribute for better treatment outcome and prevention of additional drug resistance. The successful treatment outcome among isoniazid mono-resistant TB cases had regional disparities, where better treatment success rate was noted from AMR, EUR, and WPR having a successful treatment outcome above 80%, while lower treatment outcome was noted in AFR and SEAR having 71% and 62%, respectively. This revealed the importance of taking regional and country specific interventions.

The pooled poor treatment outcome among isoniazid-mono resistant TB patients estimated in this study is higher compared to drug-susceptible TB patients at the global level [1, 2]. Thus, determining isoniazid resistance level for all bacteriologically confirmed TB cases is important. In developing countries there is a gap in addressing the universal access to DST. Besides, most of the countries are using GeneXpert for the simultaneous detection of TB and rifampicin resistance. This test determines only the drug resistance pattern to rifampicin. Thus, the isoniazid resistance level may be underestimated and may be treated as drug susceptible TB. This might have resulted with poor treatment outcomes and increasing drug resistance [2]. Based on the sub-group analysis, higher poor treatment outcome is noted in the SEAR. Likewise, based on the 2020 global TB report, lower MDR/RR-TB treatment success rate was noted in SEAR [2].

We have estimated the pooled proportion of relapse among successfully treated isoniazid mono-resistant TB cases. The finding revealed that two percent of those patients had a relapse that extends up to two years after treatment completion. This relapse rate is relatively lower than the 3.7% relapse rate in a pooled estimate among patients enrolled on DOTs program [39]. The pooled estimate in our study might be affected because the time of follow-up was different among the studies.

In the current study, we have conducted a pooled estimate to assess the factors associated with poor treatment outcome in isoniazid mono-resistant TB cases. The study findings revealed that, those patients who had a previous TB treatment history had 1.74 times the odds to develop poor treatment outcome compared to new cases. Association of previous TB treatment history for developing unsuccessful treatment outcome in TB patients for both drug-susceptible and drug-resistant TB was reported in different studies [40–44]. This risk factor is not specific to isoniazid mono-resistant TB, rather it is associated with unfavorable TB treatment outcome in general. The other identified risk factor is being smear positive initially. Initially smear positive patients had 1.26 times the odds to develop poor treatment outcome compared to smear negatives. Smear positive TB patients had higher bacterial load in their sputum reflecting the severity of the disease. Likewise, a global pooled estimate revealed that drug-resistant TB patients who were smear positive at the baseline had 1.58 times the risk to die [41]. Besides, those isoniazid mono-resistant TB cases who had cancer comorbid had 3.53 times the odds to had poor treatment outcome compared to the counter parts. Similarly, in a previous study it was reported that the 12-months all-cause mortality during TB in patients with malignancy was as high as 20.56% [45]. Thus, those patients with comorbid conditions should be critically followed during treatment.

The findings of this study also revealed that those patients who took rifampicin in the continuation phase had lower risk to develop poor treatment outcome. Including rifampicin for treatment of isoniazid-mono resistant TB cases is important to shorten the treatment duration. Our study also revealed that taking SLIDs lowered the risk of poor treatment outcome. However, in patients with confirmed rifampicin-susceptible and isoniazid-resistant TB, it is not recommended to add injectable agents to the treatment regimen [46]. In addition, compared to PTB cases EPTB cases had 45% reduced risk to develop poor treatment outcome which needs further studies. It is difficult to document treatment cure in EPTB cases. In two studies conducted in Ethiopia, EPTB was reported as the risk factor for unsuccessful treatment outcome [47, 48].

Finally, the findings of this study should be interpreted by considering the limitations. The study findings of this study was based on a limited number of studies (24 studies) with small sample size for the majority that might affected the pooled estimates. In addition, in the majority of the primary studies data were collected retrospectively that might have introduced selection bias. Besides, there is high heterogeneity and publication bias was detected for some parameters that might affect the true estimates. However, we have performed a stratified analysis and we also performed a trim and fill analysis for those pooled estimates that had a publication bias that validated the findings of this study.

Conclusion

The findings of this study revealed that isoniazid mono-resistant TB patients had higher poor treatment outcome. The pooled estimates vary per geographical locations. Previous anti-TB treatment history, being smear positive initially, and having cancer were associated with poor treatment outcome in isoniazid mono-resistant TB patients. While, taking rifampicin in the continuation phase, taking SLIDs and having EPTB were associated with reduced risk of poor treatment outcome compared to their counter parts. Thus, determination of isoniazid resistance pattern for all bacteriological TB cases is critical to have successful treatment outcome.

Supporting information

S1 Table. Completed PRISMA 2009 checklist.

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S2 Table. Search engines.

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S3 Table. Quality assessment for the included studies in meta-analysis.

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S1 Fig. Forest plot for the complete rate among isoniazid mono-resistant tuberculosis patients.

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S2 Fig. Funnel plot for the complete rate among isoniazid mono-resistant tuberculosis patients.

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S3 Fig. Forest plot for the cure rate among isoniazid mono-resistant tuberculosis patients.

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S4 Fig. Funnel plot for the cure rate among isoniazid mono-resistant tuberculosis patients.

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S5 Fig. Forest plot for the treatment failure rate among isoniazid mono-resistant tuberculosis patients.

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S6 Fig. Funnel plot for the treatment failure rate among isoniazid mono-resistant tuberculosis patients.

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S7 Fig. Forest plot for the mortality rate among isoniazid mono-resistant tuberculosis patients.

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S8 Fig. Funnel plot for the mortality rate among isoniazid mono-resistant tuberculosis patients.

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S9 Fig. Forest plot for the lost to follow-up rate among isoniazid mono-resistant tuberculosis patients.

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S10 Fig. Funnel plot for the lost to follow-up rate among isoniazid mono-resistant tuberculosis patients.

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S11 Fig. Forest plot for the association of having cancer with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S12 Fig. Forest plot for the association of taking rifampicin in the continuation phase with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S13 Fig. Forest plot for the association of having extrapulmonary tuberculosis with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S14 Fig. Forest plot for the association of taking second-line injectable drugs with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S15 Fig. Forest plot for the association of being male with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S16 Fig. Forest plot for the association of older age with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S17 Fig. Forest plot for the association of smoking with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S18 Fig. Forest plot for the association of having diabetes with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S19 Fig. Forest plot for the association of having end stage renal disease with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S20 Fig. Forest plot for the association of being HIV positive with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S21 Fig. Forest plot for the association of having high-level isoniazid resistance with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S22 Fig. Forest plot for the association of taking isoniazid in the initiation phase with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S23 Fig. Forest plot for the association of taking streptomycin in the initiation phase with poor outcome among isoniazid mono-resistant tuberculosis patients.

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S24 Fig. Forest plot for the association of taking fluoroquinolones in the initiation phase with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S25 Fig. Forest plot for the association of taking pyrazinamide in the continuation phase with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S26 Fig. Forest plot for the association of not culture converted after 2 months’ treatment of the initiation phase with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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S27 Fig. Forest plot for the association of having cavity during chest radiograph with poor treatment outcome among isoniazid mono-resistant tuberculosis patients.

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Acknowledgments

We acknowledged the authors of the primary studies. We also acknowledge the Ethiopian Public Health Institute for access to internet searching.

Data Availability

All relevant data are within the paper and its Supporting Information files.

Funding Statement

The author(s) received no specific funding for this work.

References

1.WHO. Global tuberculosis report. Geneva, Switzerland: World Health Organization; 2021. [Google Scholar]
2.WHO. Global tuberculosis report. Geneva, Switzerland: World Health Organization; 2020. [Google Scholar]
3.WHO. The END TB Strategy; global strategy and targets for tuberculosis prevention, care and control after 2015. Geneva, Switzerland: World Health Organization; 2014. [Google Scholar]
4.Villegas L, Otero L, Sterling TR, Huaman MA, Van der Stuyft P, Gotuzzo E, et al. Prevalence, Risk Factors, and Treatment Outcomes of Isoniazid- and Rifampicin- Mono-Resistant Pulmonary Tuberculosis in Lima, Peru. PLoS ONE. 2016; 11 (4): e0152933 doi: 10.1371/journal.pone.0152933 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Garg K, Saini V, Dhillon R, Agarwal P. Isoniazid mono-resistant tuberculosis: Time to take it seriously. The Indian journal of tuberculosis. 2019;66(2):247–52. doi: 10.1016/j.ijtb.2019.04.001 [DOI] [PubMed] [Google Scholar]
6.Bachir M, Guglielmetti L, Tunesi S, Pomares TB, Chiesi S, et al. Isoniazid-monoresistant tuberculosis in France: Risk factors, treatment outcomes and adverse events. International Journal of Infectious Diseases. 2021; 107:86–91 doi: 10.1016/j.ijid.2021.03.093 [DOI] [PubMed] [Google Scholar]
7.Binkhamis KM, Bahatheg MA, Altahan FA, Alwakeel SS, Almutairi KA, et al. Prevalence and outcome of isoniazid-monoresistant tuberculosis at a university hospital in Saudi Arabia. Saudi Med J. 2021; 42 (6): 636–642 doi: 10.15537/smj.2021.42.6.20200832 [DOI] [PMC free article] [PubMed] [Google Scholar]
8.Hoopes AJ, Kammerer JS, Harrington TA, Ijaz K, and Armstrong LR. Isoniazid-Monoresistant Tuberculosis in the United States, 1993 to 2003. Arch Intern Med. 2008;168(18):1984–1992 doi: 10.1001/archinte.168.18.1984 [DOI] [PubMed] [Google Scholar]
9.Dean AS, Zignol M, Cabibbe AM, Falzon D, Glaziou P, Cirillo DM, et al. Prevalence and genetic profiles of isoniazid resistance in tuberculosis patients: A multicountry analysis of cross-sectional data. PLoS medicine. 2020;17(1):e1003008. doi: 10.1371/journal.pmed.1003008 [DOI] [PMC free article] [PubMed] [Google Scholar]
10.Muwira BM, Takarinda KC, Thekkur P, Payera B, Mutunzi H, et al. Prevalence, risk factors and treatment outcomes of isoniazid resistant TB in Bulawayo city, Zimbabwe: A cohort study. J Infect Dev Ctries. 2020; 14(8):893–900. doi: 10.3855/jidc.12319 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Ba´ez-Saldaña R, Delgado-Sa nchez G, Garcı´a-Garcı´a L, Cruz-Hervert LP, MontesinosCastillo M, Ferreyra-Reyes L, et al. Isoniazid Mono-Resistant Tuberculosis: Impact on Treatment Outcome and Survival of Pulmonary Tuberculosis Patients in Southern Mexico 1995–2010. PLoS ONE. 2016; 11(12): e0168955. doi: 10.1371/journal.pone.0168955 [DOI] [PMC free article] [PubMed] [Google Scholar]
12.Edwards BD, Edwards J, Cooper R, Kunimoto D, Somayaji R, and Fisher D. Incidence, treatment, and outcomes of isoniazid mono-resistant Mycobacterium tuberculosis infections in Alberta, Canada from 2007–2017. PLoS ONE. 2020; 15(3): e0229691 doi: 10.1371/journal.pone.0229691 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.van der Heijden YF, Karimf, Mufamadi G, Zako l, Chinappa T, et al. Isoniazid-monoresistant tuberculosis is associated with poor treatment outcomes in Durban, South Africa. Int J Tuberc Lung Dis. 2017; 21(6):670–676. doi: 10.5588/ijtld.16.0843 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Chien JY, Chen YT, Wu SG, Lee JJ, Wang JY and Yu CJ. Treatment outcome of patients with isoniazid mono-resistant tuberculosis. Clin Microbiol Infect. 2015; 21: 59–68. doi: 10.1016/j.cmi.2014.08.008 [DOI] [PubMed] [Google Scholar]
15.Cattamanchi A, Dantes RB, Metcalfe JZ, Jarlsberg LG, Grinsdale J, et al. Clinical Characteristics and Treatment Outcomes of Patients with Isoniazid-Monoresistant Tuberculosis. Clinical Infectious Diseases. 2009;48:179–85. doi: 10.1086/595689 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Kwak SH, Choi JS, Lee EH,Lee HS, Leem AY, et al. Characteristics and Treatment Outcomes of Isoniazid Mono-Resistant Tuberculosis: A Retrospective Study. Yonsei Med J. 2020; 61(12):1034–1041 doi: 10.3349/ymj.2020.61.12.1034 [DOI] [PMC free article] [PubMed] [Google Scholar]
17.Chierakul N, Saengthongpinij V, and Foongladda S. Clinical Features and Outcomes of Isoniazid Mono-Resistant Pulmonary Tuberculosis. J Med Assoc Thai. 2014; 97 (Suppl 3): 586–590. [PubMed] [Google Scholar]
18.Jacobson KR, Theron D, Victor TC, Streicher EM, Warren RM and Murray MB. Treatment Outcomes of IsoniazidResistant Tuberculosis Patients, Western Cape Province, South Africa. CID. 2011:53 doi: 10.1093/cid/cir406 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Cornejo Garcia JG, Alarco´n Guizado VA, Mendoza Ticona A, Alarcon E, Heldal E, Moore DAJ. Treatment outcomes for isoniazidmonoresistant tuberculosis in Peru, 2012–2014. PLoS ONE. 2018; 13(12): e0206658 doi: 10.1371/journal.pone.0206658 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Karo B, Kohlenberg A, Hollo V, Duarte R, Fiebig L, Jackson S, et al. Isoniazid (INH) mono-resistance and tuberculosis (TB) treatment success: analysis of European surveillance data, 2002 to 2014. Euro surveillance: bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin. 2019;24(12). doi: 10.2807/1560-7917.ES.2019.24.12.1800392 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Wang T-Y, Lin S-M, Shie S-S, Chou P-C, Huang C-D, et al. Clinical Characteristics and Treatment Outcomes of Patients with Low- and HighConcentration Isoniazid-Monoresistant Tuberculosis. PLoS ONE. 2014; 9(1): e86316 doi: 10.1371/journal.pone.0086316 [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Sayfutdinov Z.; Kumar A.; Nabirova D.; Gadoev J.; Turaev L.; Sultanov S.; et al. Treatment Outcomes of Isoniazid-Resistant (Rifampicin Susceptible) Tuberculosis Patients in Uzbekistan, 2017–2018. Int. J. Environ. Res. Public Health. 2021, 18, 2965. doi: 10.3390/ijerph18062965 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Romanowski K, Chiang LY, Roth DZ, Krajden M, Tang P, et al. Treatment outcomes for isoniazid-resistant tuberculosis under program conditions in British Columbia, Canada. BMC Infectious Diseases. 2017; 17:604. doi: 10.1186/s12879-017-2706-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Santos G, Oliveira O, Gaio R, and Duarte R. Effect of Isoniazid Resistance on the Tuberculosis Treatment Outcome. Scientific letters / Arch Bronconeumol. 2018;54(1):43–55 doi: 10.1016/j.arbres.2017.06.009 [DOI] [PubMed] [Google Scholar]
25.Shao Y, Li Y, Song H, Li G, Li Y, et al. A retrospective cohort study of isoniazid-resistant tuberculosis treatment outcomes and isoniazid resistance-associated mutations in eastern China from 2013 to 2018. Journal of Global Antimicrobial Resistance. 2020; 22: 847–853. doi: 10.1016/j.jgar.2020.07.012 [DOI] [PubMed] [Google Scholar]
26.Kuaban Christopher et al. Treatment outcomes and factors associated with unfavourable outcome among previously treated tuberculosis patients with isoniazid resistance in four regions of Cameroon. Pan African Medical Journal. 2020;37(45). doi: 10.11604/pamj.2020.37.45.25684 [DOI] [PMC free article] [PubMed] [Google Scholar]
27.Salindri AD, Sales RF, DiMiceli L, Schechter MC, Kempker RR, et al. Isoniazid Monoresistance and Rate of Culture Conversion among Patients in the State of Georgia with Confirmed Tuberculosis, 2009–2014. AnnalsATS. 2018; 15 (3). doi: 10.1513/AnnalsATS.201702-147OC [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Nagar JG, RamKCi,. Patel MM, and Bhavsar KM. Treatment outcomes of patients with isoniazid resistant tuberculosis under National Tuberculosis Elimination Programme in Ahmedabad city: a retrospective study. Int J Res Med Sci. 2022;10(3):678–682 [Google Scholar]
29.Tabarsi P, Baghaei P, Hemmati N, Mirsaeidi M, Kazempour M, et al. Comparison of the effectiveness of 2 treatment regimens in patients with isoniazid-resistant tuberculosis. La Revue de Santé de la Méditerranée orientale. 2009; 15 (6)/ [PubMed] [Google Scholar]
30.Chunrong LU, Qingfang WU, Mingzhen LI, Xiaofei ZOU, Xiaoding LI et al. Treatment outcome of isoniazid-resistant tuberculosis in Shenzhen, 2016–2019. China Tropical Medicine. 2020: 20 (12). [Google Scholar]
31.Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gotzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ (Clinical research ed). 2009;339:b2700. doi: 10.1136/bmj.b2700 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Porritt K, Gomersall J, Lockwood C. JBI’s Systematic Reviews: Study selection and critical appraisal. AJN. Am J Nurs 2014;114:47–52. doi: 10.1097/01.NAJ.0000450430.97383.64 [DOI] [PubMed] [Google Scholar]
33.WHO treatment guidelines for isoniazid-resistant tuberculosis: Supplement to the WHO treatment guidelines for drug-resistant tuberculosis. Geneva: World Health Organization; 2018. Licence: CC BY-NC-SA 3.0 IGO. [PubMed] [Google Scholar]
34.WHO. Definitions and reporting framework for tuberculosis– 2013 revision (updated December 2014 and January 2020). Geneva, Switzerland: World Health Organization; 2013. [Google Scholar]
35.Sterne JA, Egger M. Funnel plots for detecting bias in meta-analysis: guidelines on choice of axis. J Clin Epidemiol 2001;54:1046–55. doi: 10.1016/s0895-4356(01)00377-8 [DOI] [PubMed] [Google Scholar]
36.Riley RD, Higgins JPT, Deeks JJ. Interpretation of random effects meta-analyses. BMJ 2011; 342:dS49. doi: 10.1136/bmj.d549 [DOI] [PubMed] [Google Scholar]
37.Egger M, Davey Smith G, Schneider M, Minder C. Bias in meta-analysis detected by a simple, graphical test. BMJ (Clinical research ed). 1997;315(7109):629–34. doi: 10.1136/bmj.315.7109.629 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Sterne JA, Sutton AJ, Ioannidis JP, Terrin N, Jones DR, Lau J, et al. Recommendations for examining and interpreting funnel plot asymmetry in meta-analyses of randomised controlled trials. BMJ (Clinical research ed). 2011;343:d4002. doi: 10.1136/bmj.d4002 [DOI] [PubMed] [Google Scholar]
39.Pasipanodya JG and Gumbo T. A Meta-Analysis of Self-Administered vs Directly Observed Therapy Effect on Microbiologic Failure, Relapse, and Acquired Drug Resistance in Tuberculosis Patients. CID. 2013:57 doi: 10.1093/cid/cit167 [DOI] [PMC free article] [PubMed] [Google Scholar]
40.Alemu A, Bitew ZW, Worku T. Poor treatment outcome and its predictors among drug-resistant tuberculosis patients in Ethiopia: A systematic review and meta-analysis. Int J Infect Dis. 2020;98:420–39. doi: 10.1016/j.ijid.2020.05.087 [DOI] [PubMed] [Google Scholar]
41.Alemu A, Bitew ZW, Worku T, Gamtesa DF, Alebel A. Predictors of mortality in patients with drug-resistant tuberculosis: A systematic review and meta-analysis. PLoS One. 2021;16(6):e0253848. doi: 10.1371/journal.pone.0253848 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Seid MA, Ayalew MB, Muche EA, et al. Drugsusceptible tuberculosis treatment success and associated factors in Ethiopia from 2005 to 2017: a systematic review and meta-analysis. BMJ Open. 2018;8:e022111. doi: 10.1136/bmjopen-2018-022111 [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Alene KA, Viney K, Gray DJ, McBryde ES, Xu Z, Clements ACA. Development of a risk score for prediction of poor treatment outcomes among patients with multidrug-resistant tuberculosis. PLoS One. 2020;15(1):e0227100. doi: 10.1371/journal.pone.0227100 [DOI] [PMC free article] [PubMed] [Google Scholar]
44.Teferi MY, El-Khatib Z, Boltena MT, Andualem AT, Asamoah BO, Biru M, et al. Tuberculosis Treatment Outcome and Predictors in Africa: A Systematic Review and Meta-Analysis. International journal of environmental research and public health. 2021;18(20). doi: 10.3390/ijerph182010678 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Shu CC, Liao KM, Chen YC, Wang JJ, Ho CH. The burdens of tuberculosis on patients with malignancy: incidence, mortality and relapse. Sci Rep. 2019;9(1):11901. doi: 10.1038/s41598-019-48395-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.WHO consolidated guidelines on drug-resistant tuberculosis treatment. Geneva: World Health Organization; 2019. Licence: CC BY-NC-SA 3.0 IGO. [PubMed] [Google Scholar]
47.Biruk M, Yimam B, Abrha H, Biruk S, Amdie FZ. Treatment Outcomes of Tuberculosis and Associated Factors in an Ethiopian University Hospital. Advances in Public Health. 2016;2016:1–9. [Google Scholar]
48.Fentie AM, Jorgi T, Assefa T. Tuberculosis treatment outcome among patients treated in public primary healthcare facility, Addis Ababa, Ethiopia: a retrospective study. Arch Public Health. 2020;78:12. doi: 10.1186/s13690-020-0393-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. doi: 10.1371/journal.pone.0286194.r001

Decision Letter 0

Mohammad Mehdi Feizabadi

13 Feb 2023

PONE-D-22-32583Poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis: a systematic review and meta-analysisPLOS ONE

Dear Dr. Alemu,

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Despite the significance of the subject of this review, it needs major revision concerning the points raised by the reviewers.

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Comments to the Author

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Reviewer #1: Yes

Reviewer #2: Yes

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2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: No

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Reviewer #1: No

Reviewer #2: No

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Reviewer #2: Yes

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5. Review Comments to the Author

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Reviewer #1: This study was done with the aim of "Poor treatment outcome an patients with isoniazid mono-resistant tuberculosis", which has important results, but in terms of writing, statistical analysis, the values of the tables need to be modified. Items requiring modification are available below

-METHOD : Inclusion and exclusion criteria, it should be added that there was no restriction on entering the study in terms of sample size.

-Method: To assess the presence of 174 publication bias, the funnel plot was inspected visually and Egger’s regression test was conducted 175 to ascertain the presence of publication bias.... This sentence is repeated twice in the method

-Line 176. Method: in the Egger’s regression test)….. Remove the parentheses

-Lin2 215: (P=0.1205). ..... p-values should be reported to three decimal places

-Line 270 : (INH, STR, FLQ, SLIDs) and continuation phase (RIF, PZA)….. Tb drugs that are mentioned for the first time in the text should be completed with the name

-line 302 : Based on the pooled estimates, about one fifth of isoniazid mono-resistant TB patients had poor treatment outcomes and different factors are associated with this……….

line 315: This study revealed that one among five (21%) isoniazid-mono resistant TB patients had poor…………..

These sentences are repeated twice

-TABLE 1: Cattamanchi et al., 2009 . The cells are empty

-TABLE 1: Study period....study period report should be same for some studies have reported by ‘month’ and ‘year’ while for other studies have written just ‘year’

-TABLE 1:Report of age groups should be same . For some studies have written "all" , some articles "all ( with median age )" and some other studies "median age ". it’s better that reported by min- max or mean ( sd)

-TABLE1: Chierakul: Celss are incomplete

-In table 1, the sum of the groups is not equal to the total, check again for example …

-TABLLE 1: 155 101 +50

-TABLE 1: der Heijden 407 235 +170

-Percentages check too please in table 1

-TABLE2

Treatment failure, Loss to follow-up ,Mortality= 16 18 23 … need check and correction

-TABLE 3: The writing format is not correct, while the content of the table is also ambiguous. Was the model based on linear regression? Or logistics? In this test, is the dependent variable of poor treatment with three subgroups ? (In this case, it is not possible to perform the logistic and linear regression test) or the type of outcome (poor and success). And why is the type of region or continent not included in the regression model?

-FIGURE 1: I2,H2,T2, …These indicators should be explained in the footnotes of all figures

-285 Line ant-TB treatment..... anti-TB treatment.

Reviewer #2: The subject of the research is very important and current. With the increasing need for new drugs for the treatment of tuberculosis, it is extremely important to determine the frequency of ripampicin resistance, the key of tuberculosis treatment.

The present manuscript describes a meta-analysis based on studies performed in the world.

Despite the importance of the topic addressed by the paper, many important points must be reviewed, specifically in the methodology:

1. Literature Searches and Search terms are incomplete. This is suboptimal for publication for systematic review. Search Embase is highly recommended. Please attach search terms that were used in each database as supplement for Data source and search strategies in the manuscript.

2. Quality assessment checklists are different for different types of studies, and researchers should choose the necessary checklist based on the type of article. Quality assessments for all included papers should be shown as a supplementary file.

3. The type and design of selected studies should be specified.

4. Another important issue is the considerable source of heterogeneity. High heterogeneity should be mentioned in the limitations section.

5. The method for selecting studies is not clear and needs further explanation.

6. The reasons for excluding the 7 articles (figure 1) should be stated.

7. Cohort studies cannot be combined with cross-sectional studies. All analyzes of these two types of studies should be performed separately and reported separately.

8. According to the global scale of the study, the number of included studies is very low and there are a large number of studies that should be included in the study by searching and re-screening.

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Reviewer #1: No

Reviewer #2: No

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PLoS One. 2023 Jul 19;18(7):e0286194. doi: 10.1371/journal.pone.0286194.r002

Author response to Decision Letter 0

19 Feb 2023

Revisions based on the Editor’s and the reviewers’ comments and suggestions

Title: Poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis: a systematic review and meta-analysis (PONE-D-22-32583)

Editor Comments and suggestions

We would like to thank the editor and the reviewers for giving pertinent comments and suggestions that improve the quality of the paper.

Journal Requirements:

When submitting your revision, we need you to address these additional requirements.

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming.

• Response: Thank you, we have uploaded all required documents.

Additional Editor Comments:

Despite the significance of the subject of this review, it needs major revision concerning the points raised by the reviewers.

• Response: Thank you. We have revised the manuscript based on the important comments and suggestions given by both reviewers.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

2. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: No

Reviewer #2: No

• Response: Thank you for the critical review. Now we have revised the whole manuscript and updated the statistical analysis since some numbers are changed. The statistical analysis is now reviewed by a statistician.

________________________________________

3. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: No

Reviewer #2: No

• Response: Thank you for the pertinent review. All the supporting files are available within the manuscript and the supplementary files.

________________________________________

4. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: Yes

________________________________________

5. Review Comments to the Author

-METHOD : Inclusion and exclusion criteria, it should be added that there was no restriction on entering the study in terms of sample size.

• Response: Thank you for the comment and suggestion. We included the sentence “There was no restriction on entering the study in terms of sample size.” in the revised manuscript.

• Response: Thank you for the comment. Now, we revised it and avoided the unnecessary repetitions.

-Line 176. Method: in the Egger’s regression test)….. Remove the parentheses

• Response: Thank you for the comment. Now, it is removed.

-Lin2 215: (P=0.1205). ..... p-values should be reported to three decimal places

• Response: Thank you for the comment. In the revised version, we presented the P-values in three decimal places.

-Line 270 : (INH, STR, FLQ, SLIDs) and continuation phase (RIF, PZA)….. Tb drugs that are mentioned for the first time in the text should be completed with the name

• Response: Thank you for the important comment. We presented their full name in their first presentation in the revised version.

-line 302 : Based on the pooled estimates, about one fifth of isoniazid mono-resistant TB patients had poor treatment outcomes and different factors are associated with this……….

line 315: This study revealed that one among five (21%) isoniazid-mono resistant TB patients had poor…………..

These sentences are repeated twice

• Response: Thank you for the comment. We rephrased the repeated sentence.

-TABLE 1: Cattamanchi et al., 2009 . The cells are empty

-TABLE1: Chierakul: Celss are incomplete

• Response: Thank you for the important comment. We put the sample size (137) for Cattamanchi et al., 2009 in the revised version, however the study only indicated the treatment completion rate the total successful treatment outcome including the cured cases and the poor treatment outcome (failure, death and lost to follow-up) are not indicated in the study. We mainly used this study to estimate the pooled prevalence of relapse in isoniazid mono-resistant tuberculosis patients. The Chierakul et al., 2014 didn’t specifically described the number of poor treatment outcome. In the current study, among the 25 studies, pooled treatment outcome is estimated using 23 studies excluding Cattamanchi et al., 2009 and Chierakul et al., 2014. Whereas, successful treatment outcome is estimated using 24 studies by excluding Cattamanchi et al., 2009. These are the reasons for the incomplete cells.

-TABLE 1: Study period....study period report should be same for some studies have reported by ‘month’ and ‘year’ while for other studies have written just ‘year’

• Response: Thank you for this important comment. Unfortunately, the original studies did not describe the study period in similar way, some studies described the specific date, others indicated the month and some others described only the study year. We presented the study period based on the study period described in the primary studies. Likewise, the age of the study participants was described in different ways in the original studies. Thus, we presented the age groups already described by the original studies. We tried to present what is already described in the original studies. If there is any suggestion, we are happy.

-In table 1, the sum of the groups is not equal to the total, check again for example …

-TABLLE 1: 155 101 +50

-TABLE 1: der Heijden 407 235 +170

-Percentages check too please in table 1

• Response: Thank you for these critical comments and suggestions. We have revised the figures of Table 1 and the gaps were arising from counting the non-evaluated patients in the denominator of three studies. Now, we revised the numbers and the percentages. We performed an analysis including pooled estimate forest plot, funnel plot, heterogeneity, publication bias and meta-regression analysis. All the numeral figures and forest plot/funnel plot figures are revised accordingly.

-TABLE2

Treatment failure, Loss to follow-up ,Mortality= 16 18 23 … need check and correction

• Response: Thank you for the comment. The pooled treatment failure, lost to follow-up and mortality rate were estimated using 16, 18, and 23 studies, respectively. The figures described in Table 2 are correct. The forest plots are presented in the supplementary files (S5 fig for treatment failure, S9 fig for lost to follow-up and S7 fig for mortality).

• Response: Thank you for the question and the comment. In Table 3, we have conducted a meta-regression analysis to assess the effect of sample size and publication year on the heterogeneity among studies that reported poor treatment outcome among isoniazid mono-resistant TB patients. It is a linear regression analysis where the poor treatment outcome estimate (proportion) is a dependent variable and the sample size and publication year were the independent variables. Based on the multivariable meta-regression model it is revealed that sample size (P=0.713) and publication year (P=0.464) did not significantly affected heterogeneity among studies. We described it in the result section under a title “Met-regression”. In Table 3, we presented the coefficient with its 95%CI in in the bi-variable and multivariable analysis.

-FIGURE 1: I2,H2,T2, …These indicators should be explained in the footnotes of all figures

• Response: Thank you. We included the abbreviations in the footnotes of all figures.

-285 Line ant-TB treatment..... anti-TB treatment.

• Response: Thank you for the question, it was a clerical problem. We changed previous anti-TB treatment to previous TB treatment history.

The present manuscript describes a meta-analysis based on studies performed in the world.

• Response: Thank you for the review. In this study, we conducted a study titled “Poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis: a systematic review and meta-analysis”. The study mainly focused on isoniazid mono-resistant tuberculosis aimed at estimating the poor treatment outcome and its associated risk factors.

Despite the importance of the topic addressed by the paper, many important points must be reviewed, specifically in the methodology:

• Response: Thank you for the comment. Unfortunately, we don’t have access to Embase database. We have searched 5 data bases and 2 gray literature sources and we believe that relevant articles are accessed.

• The search strings for all the databases are included in the supplementary file (S2 Table). We have presented the search string for one database (PubMed) as an example in the method section of the main manuscript to limit the number of words in the manuscript. “The search string for PubMed was ("Treatment Outcome"[MeSH Terms] OR (("poverty"[MeSH Terms] OR "poverty"[All Fields] OR "poor"[All Fields]) AND ("Treatment Outcome"[MeSH Terms] OR ("treatment"[All Fields] AND "outcome"[All Fields]) OR "Treatment Outcome"[All Fields])) OR ("Treatment Outcome"[MeSH Terms] OR ("treatment"[All Fields] AND "outcome"[All Fields]) OR "Treatment Outcome"[All Fields])) AND (("isoniazid"[MeSH Terms] OR "isoniazid"[All Fields] OR "isoniazide"[All Fields]) AND "mono-resistant"[All Fields]) (S2 Table).”

• Response: Thank you for the valuable comment. We have assessed the quality of each study using the Joanna Briggs Institute (JBI) critical appraisal tools for observational studies. As shown in the supplementary file (S3 Table), we have assessed the quality of the studies separately based on the study design used in each study. We have used the JBI checklist for cross-sectional, case control and cohort studies separately.

3. The type and design of selected studies should be specified.

• Response: Thank you for the comment. The study design is specified for all studies as described in Table 1, column 5.

4. Another important issue is the considerable source of heterogeneity. High heterogeneity should be mentioned in the limitations section.

• Response: Thank you for the comment. We have mentioned the potential impact of high heterogeneity as one limitation of the study. It is described in the limitation section. “Besides, there is high heterogeneity and publication bias was detected for some parameters that might affect the true estimates.”

5. The method for selecting studies is not clear and needs further explanation.

• Response: Thank for the comment. We put this paragraph in the study selection procedure section. “We have followed a step-wise approach to select the eligible studies. Primarily, all the studies identified from the whole search were exported to EndNote X8 citation manager, and we have removed the duplicates. In the next step, we have screened the articles by title and abstract. Then, full-text assessment was conducted for the remaining articles. Finally, we have included the articles that passed the full-text review in the final analysis. The article selection procedure was conducted by two independent authors (GD, GS) using pre-defined criteria that considered study subjects, study designs, quality, and outcome (Fig 1).”

• We selected the studies using the PICOS criteria. Finally, we put an inclusion and exclusion criteria to select studies to be included in the final analysis.

6. The reasons for excluding the 7 articles (figure 1) should be stated.

• Response: Thank you for the comment. We excluded 4 studies (Fig 1). Three studies were reviews (are not primary studies) and one study was excluded because it did not describe the specific outcome.

7. Cohort studies cannot be combined with cross-sectional studies. All analyzes of these two types of studies should be performed separately and reported separately.

• Response: Thank you for the comment and suggestion. In the current study, we estimated the pooled prevalence of poor treatment outcome among isoniazid mono-resistant TB patients. Since both cross-sectional and cohort studies are observational studies, we merged together to estimate the pooled prevalence. We performed a sub-group analysis and there is no significant difference among the study designs.

8. According to the global scale of the study, the number of included studies is very low and there are a large number of studies that should be included in the study by searching and re-screening.

• Response: Thank you for the important comment. There is limited evidence that described the treatment outcome of isoniazid mono-resistant tuberculosis and associated risk factors. Since our focus is on isoniazid mono-resistant tuberculosis, we identified limited number of studies. We described the small number of studies as a limitation of the study. “The study findings of this study was based on a limited number of studies (24 studies) with small sample size for the majority that might affected the pooled estimates.”

Kind regards,

Ayinalem Alemu

Ethiopian Public Health Institute

National Tuberculosis Reference Laboratory,

P.O. Box 1242, Addis Ababa, Ethiopia.

Email: ayinalemal@gmail.com

Tell: +251912366676

Attachment

Submitted filename: Response to reviewers.docx

Click here for additional data file.^{(24.9KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0286194.r003

Decision Letter 1

Frederick Quinn

18 Apr 2023

PONE-D-22-32583R1Poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis: a systematic review and meta-analysisPLOS ONE

Dear Dr. Alemu,

Please submit your revised manuscript by Jun 02 2023 11:59PM. If you will need significantly more time to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file.

Please include the following items when submitting your revised manuscript:

A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'.
A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'.
An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'.

We look forward to receiving your revised manuscript.

Kind regards,

Frederick Quinn

Academic Editor

PLOS ONE

Journal Requirements:

Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.

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Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation.

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)

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2. Is the manuscript technically sound, and do the data support the conclusions?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

3. Has the statistical analysis been performed appropriately and rigorously?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

4. Have the authors made all data underlying the findings in their manuscript fully available?

Reviewer #1: Yes

Reviewer #2: (No Response)

**********

5. Is the manuscript presented in an intelligible fashion and written in standard English?

Reviewer #1: Yes

Reviewer #2: (No Response)

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6. Review Comments to the Author

Reviewer #1: 1. Line 270: please write ….. isoniazid (INH), streptomycin(STR), fluoroquinolones(FLQ), second-line injectable drugs (SLIDs) and continuation phase(rifampicin(RIF), pyrazinamide (PZA)).

2. Table 1 : Its need you explain in footnote of table1

Cattamanchi et al., 2009*

3.Table 1 : Chien et al., 2014 : All (Median age was 64 years) . What does "all" mean? All age groups? 64 years seems to be high for the middle age, please recheck. For all studies that include all age groups, please add the word "all age groups". For example Binkhamis et al., 202…. all age groups ( range: 1-90 years).

4.(Median zge was 41 years)……. Median age was 41 years

Reviewer #2: (No Response)

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7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: No

Reviewer #2: No

**********

PLoS One. 2023 Jul 19;18(7):e0286194. doi: 10.1371/journal.pone.0286194.r004

Author response to Decision Letter 1

19 Apr 2023

Revisions based on the Editor’s and the reviewers’ comments and suggestions

Title: Poor treatment outcome and associated risk factors among patients with isoniazid mono-resistant tuberculosis: a systematic review and meta-analysis (PONE-D-22-32583R1)

Journal Requirements:

• Response: Thank you, the reference list is complete and correct. A retracted paper is not cited.

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

Reviewer #1: All comments have been addressed

Reviewer #2: (No Response)