Incidence and predictors of mortality among persons receiving second-line tuberculosis treatment in sub-Saharan Africa: A meta-analysis of 43 cohort studies.

BACKGROUND: Drug resistance remains from among the most feared public health threats that commonly challenges tuberculosis treatment success. Since 2010, there have been rapid evolution and advances to second-line anti-tuberculosis treatments (SLD). However, evidence on impacts of these advances on incidence of mortality are scarce and conflicting. Estimating the number of people died from any cause during the follow-up period of SLD as the incidence proportion of all-cause mortality is the most informative way of appraising the drug-resistant tuberculosis treatment outcome. We thus aimed to estimate the pooled incidence of mortality and its predictors among persons receiving the SLD in sub-Saharan Africa.
METHODS: We systematically identified relevant studies published between January, 2010 and March, 2020, by searching PubMed/MEDLINE, EMBASE, SCOPUS, Cochrane library, Google scholar, and Health Technology Assessment. Eligible English-language publications reported on death and/or its predictors among persons receiving SLD, but those publications that reported death among persons treated for extensively drug-resistant tuberculosis were excluded. Study features, patients' clinical characteristics, and incidence and/or predictors of mortality were extracted and pooled for effect sizes employing a random-effects model. The pooled incidence of mortality was estimated as percentage rate while risks of the individual predictors were appraised based on their independent associations with the mortality outcome.
RESULTS: A total of 43 studies were reviewed that revealed 31,525 patients and 4,976 deaths. The pooled incidence of mortality was 17% (95% CI: 15%-18%; I2 = 91.40; P = 0.00). The studies used varied models in identifying predictors of mortality. They found diagnoses of clinical conditions (RR: 2.36; 95% CI: 1.82-3.05); excessive substance use (RR: 2.56; 95% CI: 1.78-3.67); HIV and other comorbidities (RR: 1.96; 95% CI: 1.65-2.32); resistance to SLD (RR: 1.75; 95% CI: 1.37-2.23); and male sex (RR: 1.82; 95% CI: 1.35-2.44) as consistent predictors of the mortality. Few individual studies also reported an increased incidence of mortality among persons initiated with the SLD after a month delay (RR: 1.59; 95% CI: 0.98-2.60) and those persons with history of tuberculosis (RR: 1.21; 95% CI: 1.12-1.32).
CONCLUSIONS: We found about one in six persons who received SLD in sub-Saharan Africa had died in the last decade. This incidence of mortality among the drug-resistant tuberculosis patients in the sub-Saharan Africa mirrors the global average. Nevertheless, it was considerably high among the patients who had comorbidities; who were diagnosed with other clinical conditions; who had resistance to SLD; who were males and substance users. Therefore, modified measures involving shorter SLD regimens fortified with newer or repurposed drugs, differentiated care approaches, and support of substance use rehabilitation programs can help improve the treatment outcome of persons with the drug-resistant tuberculosis. TRIAL REGISTRATION NUMBER: CRD42020160473; PROSPERO.

Introduction

Antimicrobial resistance to mycobacterium tuberculosis (TB) remains from among the most feared public health threats that commonly challenges the TB treatment success [1]. In 2019, a total of 206,030 people across the world were detected and notified to have drug-resistant TB (DR-TB), with 177,099 of them enrolled for receiving treatments [2]. According to the World Health Organization’s (WHO) global estimate in 2017, from among the 558,000 people predicted to be infected with DR-TB, only 186,883 them were detected [2, 3]. This indicated that more than half of the DR-TB cases are left undetected, and a large number of these missed cases are likely to be in resource-limited settings. On top of this, treatment regimens received by persons with DR-TB are relatively complex, prolonged, costly, and associated with multiple toxicities that may lead to difficulties to complete the entire dosages [4]. The Global TB report of 2020 pertaining to a 2017 cohort of DR-TB patients indicated that 57% them completed the treatments successfully while 15% of them died, 16% of them lost from the follow-up, and 7% of them failed treatment [2]. In addition to the large number of missed DR-TB cases in Africa, the high proportion of unsuccessful outcomes linked with DR-TB patients will threaten the prospect of achieving the set target for the EndTB Strategy by 2035 [2, 5]. Accordingly, measuring the number of people who died from any cause during the follow-up period of standardized second-line anti-tuberculosis drugs (SLD) as the incidence of all-cause mortality and its predictors are the most informative ways of assessing the DR-TB treatment outcomes [6].

The mortality commonly occurs among the persons receiving SLD [7, 8]. Patient characteristics like older age, male sex, underweight, comorbid conditions including HIV-coinfection, and extra-pulmonary involvement are the frequent explanations to contribute to the increased incidence of mortality among the persons receiving SLD [9, 10]. Besides, a high incidence of mortality was also reported among the DR-TB patients with previous history of TB and those patients with features involving undernutrition and excessive alcohol use [11, 12].

Since 2010, there has been a rapid evolution on the better use of more effective DR-TB treatment regimens, mainly in African and Asian patients [2]. There have also been progress in discovering novel drugs and approaches to the use of repurposed drugs, and some of the world countries have begun adding these medicines to the standardized SLD regimen [13-17]. Again, there have been advances with respect to rapid testing, detection, and effective treatment with shorter regimens for the DR-TB patients [18-22]. In line to these changes, the average annual all-cause mortality rate in resource-limited settings looked to mirror the global average, but it remained unacceptably high and reaches up to 30 percent or above for some of the resource-limited countries including sub-Saharan Africa (SSA) [2, 8, 23]. Indeed, a reduction in the mortality rate has been predicted in line with the various changes implemented in these countries as part of the EndTB Strategy target set for 2035 [2]. Accordingly, there appears to be other factors than the treatment features that could influence the all-cause mortality among persons receiving the SLD therapy. Understanding such potential factors can inform a policy priority for the SLD therapy alongside its fortifications with novel or repurposed drugs. As such, a focused evidence that considers the combined risks of behavioral, sociodemographic, and clinical features of patients with proven and consistent influences on the high incidence of mortality among persons receiving the SLD therapy is mandatory. This evidence can inform an appropriate and a context-led approach with the potential to contribute to the DR-TB treatment successes. We thus aimed to estimate a pooled incidence proportion of all-cause mortality and its predictors among the persons receiving SLD treatments in SSA.

Methods

A methodological protocol for this review was prepared according to a statement recommendation made by the Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols (PRISMA-P) in 2015 [24]. The International Prospective Register of Systematic Reviews (PROSPERO) has registered the protocol with a trial registration number of CRD42020160473. Besides, we strictly followed the PRISMA flow diagram during the process of study selection [25].

Search strategy

We identified publications by systematic searches of PubMed/Medline, Embase, Scopus, Google Scholar, Heath Technology assessment and Cochrane Library, from February to March 15, 2020. The identified records were downloaded with an appropriate format and linked to the Endnote. The terms used for our search strategy included: second-line*, rifampicin-resistant, multidrug-resistant, tuberculosis, treatment outcome, unfavorable*, death, factor, and Africa, South of the Sahara. During the searches, we employed Boolean operators (AND, OR) and truncations as appropriate to identify and include more publications. A PubMed search strategy is added to the supporting information section as a (S1 Table).

Eligibility criteria

We applied several inclusion and exclusion criteria that were defined a priori to the records identified. Publications eligible for inclusion reported on the incidence of mortality and/or its predictors among individual patients treated for DR-TB (i.e., rifampicin-resistant TB (RR-TB) or multidrug-resistant TB (MDR-TB)) as a primary outcome, or secondary outcome. The mortality outcomes considered were those encounters reported following SLD therapy initiation that also included interim reports [26]. Again, publications of studies conducted in Africa, South of the Sahara and published from January 2010 to March 15, 2020, were included. We excluded abstracts with unrelated data, non–English language studies, publications without original data (reviews, correspondence, guidelines, letters, and editorials), and original articles that reported insufficient or irrelevant information. We also excluded studies that reported results from a case series or case report, qualitative data, and mixed findings from pre-extensively or extensively drug-resistant (pre-XDR or XDR) TB and MDR-TB patients that did not separately report outcomes for the MDR-TB. The studies with treatment outcomes for the patients with XDR-TB were excluded to avoid confusions in observed outcomes of the standardized SLD therapy, for complicated cases of the XDR-TB were assumed as different conditions from the other forms of DR-TB [27].

Study selection procedure

Initially, we removed duplicates from the identified publications by the use of Endnote, version 8.2 (Thomson Reuters, Stamford, CT, USA) and manual screening. Next, two of us (BH and MS) independently appraised the titles and abstracts of the retained publications and selected relevant articles for possible inclusion in the review. Accordingly, the RR/MDR-TB studies with reported mortality outcome and/or its predicting factors were kept. With this, the RR-TB was defined as any resistance to rifampicin, in the form of mono-resistance, poly-resistance, or MDR but not XDR [27]. This definition included the MDR-TB [2] which is a resistance to both isoniazid and rifampicin [27]. We also considered studies that reported retreatment TB cases managed with SLD regimens among patients with failed treatment or defaulted. Finally, two of the authors (DE and FA) independently collected and evaluated full-text details of the remained articles for quality and eligibility assessment.

Quality assessment

Methodological quality of the retained publications were appraised by two independent authors using the Joanna Briggs Institute’s (JBI’s) checklist for cohort studies [28]. A third author’s appraisal score was considered in cases of disagreement between scores of the two authors. Finally, all studies that fulfilled at least 50% of the quality requirement as per the average positive score of the appraisers were considered for this review.

Data extraction

A data abstraction format prepared in a Microsoft excel sheet was employed to extract all relevant information for the systematic review and meta-analysis. Two non-blinded investigators (DE and FA) extracted the data independently, reviewed it for discrepancies, and finally reached a consensus through discussion. The following variables were extracted: name of the first author; year of the publication; number of deaths reported during the SLD therapy; the total number of patients treated with the SLD; median duration of the standardized SLD therapy; design of the studies; settings; age category of patients (children, adults, children and adults); the WHO group of the SLD regimen used (group A, group B, group C); and details of the specific drugs used in the SLD regimen. We also extracted the number of persons exposed to the predictors of mortality, and the number died from those exposed and unexposed while receiving the SLD therapy. Additionally, predictors of mortality were extracted for studies that linked patient characteristics with this outcome. For detailed extraction of the drugs used, we abstracted the standardized SLD regimens that were fortified with a later generation fluoroquinolone, bedaquiline and linezolid as group A while the regimens that added cycloserine or terizidone and/or clofazimine were abstracted as group B. Likewise, regimens that included injectable aminoglycosides (kanamycin, capreomycin, or amikacin), ethambutol, pyrazinamide, ethionamide, para-aminosalicylic acid, delamanid, etc. (i.e., to complete the therapy) were extracted as group C [29].

Outcome definitions

The definition we considered for mortality was in line with the WHO outcomes definition among the patients with DR-TB [26]. Accordingly, the sum of cure and treatment completion was considered as a successful outcome while failed treatment, death, lost to follow-up and unevaluated outcomes were assumed as unsuccessful. In this respect, the death outcome from any cause during the time period of SLD therapy was considered as the all-cause mortality and this was the primary outcome of interest [26].

Data analysis and synthesis

Statistical pooling for incidence proportion estimates was performed according to the random-effects model with generic inverse-variance methods, using Stata 15.0 (StataCorp. 2017, Stata Statistical Software: Release 15; College Station, TX: StataCorp LLC). The random-effects model of analysis was assumed since the studies identified were observational in nature and they had both clinical and methodological variabilities. The percentage rates of the mortality incidences were presented using forest plots. In this analysis, however, risk estimates for predictors were not pooled from individual studies as this approach would have not been feasible and valid given the high risk for bias [30]. To this end, we considered an approach suggested by Ross et al. and evaluated a given predictor with proven significant and independent association with the outcome of interest [31]. In determining the risk ratios, incidences of mortality among patients with HIV-coinfection and other comorbidities such as diabetes mellitus, myocardial infraction, congestive heart failure, asthma, hypertension, chronic pulmonary insufficiency, depression, epilepsy, etc. were pooled together. Again, the mortality incidence among persons diagnosed with anemia, underweight, pneumonia, pneumothorax, hemoptysis, nutritional problems, etc. were combined together as other clinical conditions. The forest plots were employed to present the pooled risk ratio of the factors associated with the incidence of mortality. The degree of heterogeneity for effect sizes among the studies was appraised using chi2 (I2) statistics. In line with this, subgroup analyses were carried out to explain few patient features with the potential to account for the differences in the effect sizes of the mortality incidence. Publication bias (or small-study effects) was assessed by a graphical inspection of funnel plot. Next, Egger’s regression and Begg’s correlation tests were performed to test the presence of publication bias. Lastly, all statistical tests were considered as significant for P-values less than 0.05.

Results

Study selection

There were 4,255 publications identified and eligibility appraised for this review. From among these 4,255 records we identified, 422 duplicates and 3,619 unrelated studies (i.e., 1,554 of them by screening titles and 2,065 of them by screening abstracts) were excluded. Next, 171 publications were excluded with reasons from among the 214 full-text details we appraised for quality and eligibility. Finally, 43 publications that met the priori eligibility and quality requirements for the review were included in the study (Fig 1 and S2 Table).

Fig 1

PRISMA flow diagram depicting the selection process.

Study characteristics

From among the 43 studies that were included, a total of 31,525 persons receiving SLD were followed-up and 4,976 of them encountered the incidence of mortality. The study participants for four of these studies were children [32-35]; for 20 of the studies were adults [23, 36–54]; and for 19 of the studies were both adults and children [55-73]. Methodological design for nine of the studies was prospective cohort [23, 39, 42–46, 50, 63] while it was retrospective cohort for 34 of the remaining studies [32–38, 40, 41, 47–49, 51–62, 64–73]. In terms of regions of the SSA from where the data were originated, 25 of the studies were from the southern region [23, 32–34, 36–39, 41, 43, 45–47, 49, 51–56, 63, 66, 68, 71, 72]; 14 of the studies were from the eastern region [35, 40, 44, 48, 57, 58, 60–62, 65, 67, 69, 70, 73]; two of the studies were from the central region [42, 64]; one of the study was from the western region [59]; and the remaining one study was from multi-sites in different SSA regions [50]. A total of 23 studies out of the 43 publications identified had reported the predictors of mortality among the persons receiving SLD therapy [23, 32, 34, 35, 37–41, 44, 47, 49, 52, 54, 55, 57, 59–61, 64, 67, 69, 71]. However, varied analytic models of analyses were used by these studies in their attempt to identify the potential predictors of mortality (Table 1 and S3 Table).

Table 1

Characteristics of identified publications and their analytic models of factor prediction for the SLD treatment outcomes.

Study	# died	Total size	Follow-up period	Design	Setting	Age category	Analytic model	Group of SLD regimen	Details of the drugs used
Adewumi (2012)	44	336	24 months	RFU	South Africa	Adults and Children	χ2 test	Group B	kanamycin, ethionamide, ofloxacin, cycloserine, pyrazinamide
Alakaye (2018)	83	343	18 months	RFU	Lesotho	Adults and Children	Cox proportional hazards regression	Group C	Amikacin, kanamycin, Capreomycin or any fluoroquinolone
Alene (2017)	31	242	20 months	RFU	Ethiopia	Adults and Children	Cox proportional hazards regression	Group B	Pyrazinamide, capreomycin, levofloxacin, ethionamide, cycloserine
Ali (2019)	22	156	18 months	RFU	Sudan	Adults and Children	Cox proportional hazards regression	Group B	pyrazinamide, capreomycin, levofloxacin, ethionamide and cycloserine
Bajehson (2019)	38	147	20 months	RFU	Nigeria	Adults and Children	Cox proportional hazards regression	Group B	Capreomycin, levofloxacin, cycloserine, prothionamide and pyrazinamide
Borisov (2017)	17	113	18 months	RFU	South Africa	Adults	χ2 test	Group A	Bedaquiline, linezolid, moxifloxacin, clofazimine and carbapenems
Brust (2010)	223	1209	24 months	RFU	South Africa	Adults	Multivariate logistic regression	Group B	Kanamycin, ofloxacin, pyrazinamide, ethambutol or cycloserine and thionamide
Brust (2018)	22	191	32 months	RFU	South Africa	Adults	Cox proportional hazards regression	Group B	Kanamycin, moxifloxacin ethionamide, terizidone, ethambutol and pyrazinamide
Cox (2014)	128	718	24 months	RFU	South Africa	Adults/Adolescents	Cox proportional hazards regression	Group C	Ofloxacin, kanamycin, ethambutol, ethionamide and pyrazinamide
Fantaw (2018)	30	164	13 months	RFU	Ethiopia	Adults and Children	Cox proportional hazards regression	NS	Standardized SLD
Farley (2011)	177	757	24 months	FU	South Africa	Adults	Cox proportional hazards regression	Group C	Pyrazinamide, ethambutol, ethionamide, ofloxacin, and either amikacin or kanamycin.
Getachew (2013)	29	188	14 months	RFU	Ethiopia	Adults and Children	Cox proportional hazards regression	NS	Standardized SLD
Girum (2017)	13	154	24 months	RFU	Ethiopia	Adults	Cox proportional hazards regression	Group B	Capreomycin, amikacin, ethionamide, levofloxacin and cycloserine
Hall (2017)	69	423	24 months	RFU	South Africa	Children	Cox proportional hazards regression	Group C	A fluoroquilone and second-line injectables
Hicks (2014)	8	68	18 months	RFU	South Africa	Children	Multivariate logistic regression	Group B	pyrazinamide, ethambutol, terizidone, kapromycin, ofloxacin and ethambutol
Hirasen (2018)	37	240	12 months	FU	South Africa	Adults	Cox proportional hazards regression	NS	Standardized SLD
Huerga (2017)	21	145	24 months	RFU	Kenya	Adults and Children	Multivariate logistic regression	Group B	kanamycin or capreomycin, levofloxacin, prothionamide, cycloserine, para-aminosalicylic acid
Jikijela (2018)	147	332	24 months	RFU	South Africa	Adults	Multivariate logistic regression	NS	Standardized SLD
Kapata (2017)	12	71	20 months	FU	Zambia	Adults and Children	Cox proportional hazards regression	Group B	kanamycin, levofloxacin, ethionamide, cycloserine and pyrazinamide
Kashongwe (2017)	18	199	6 months	RFU	Congo	Adults and Children	Multivariate logistic regression	NS	Standardized SLD
Kuaban (2015)	10	150	12 months	FU	Cameroon	Adults	Multivariate logistic regression	Group B	gatifloxacin, clofazimine, prothionamide, ethambutol and pyrazinamide
Leveri (2019)	56	332	24 months	RFU	Tanzania	Adults and Children	Multivariate logistic regression	Group B	Amikacin or kanamycin, ofloxacin or levofloxacin, pyrazinamide, ethionamide, cycloserine, and ethambutol
Loveday (2015)	223	1549	24 months	FU	South Africa	Adults	Cox proportional hazards regression	Group B	Kanamycin, pyrazinamide, ethambutol, ethionamide, ofloxacin and cycloserine
Marais (2013)	65	324	24 months	RFU	South Africa	Adults and Children	Multivariate logistic regression	Group B	kanamycin, pyrazinamide, ofloxacin, ethionamide and terizidone or ethambutol
Meressa (2015)	85	612	24 months	FU	Ethiopia	Adults	Cox proportional hazards regression	Group B	Three of levofloxacin, ethionamide, cycloserine or para-aminosalicyclic acid, pyrazinamide and amikacin or kanamycin or capreomycin
Mibei (2016)	18	205	20 months	RFU	Kenya	Adults and Children	Multivariate logistic regression	Group B	kanamycin, levofloxacin, cycloserine, ethionamide and pyrazinamide
Mohr (2015)	123	757	18 months	RFU	South Africa	Adults and Children	Multivariate logistic regression	NS	second-line anti-TB drugs
Mollalign (2015)	37	342	16 months	RFU	Ethiopia	Adults and Children	Cox proportional hazards regression	Group C	Ethambutol, streptomycin, kanamycin, amikacin and capreomycin
Mollel (2019)	29	201	20 months	RFU	Tanzania	Adults and Children	Multivariate logistic regression	Group B	amikacin or kanamycin, ofloxacin, cycloserine, ethionamide, pyrazinamide and ethambutol
Ndjeka (2018)	25	200	24 months	FU	South Africa	Adults	Multivariate logistic regression	Group A	Bedaquiline, clofazimine, levofloxacin, linezolid, kanamycin
Padayatchi (2014)	7	23	18 months	FU	South Africa	Adults	Multivariate Poison regression	Group C	kanamycin, ofloxacin, pyrazinamide, ethambutol or cycloserine and ethionamide
Satti (2012)	46	134	24 months	RFU	Lesotho	Adults	Cox proportional hazards regression	Group B	fluoroquinolone, prothionamide or ethionamide, cycloserine, pyrazinamide, para-aminosalicylic acid, etc.
Schnippel (2015)	2165	15339	24 months	RFU	South Africa	Adults and Children	Multivariate Poison regression	Group B	Kanamycin or amikacin, ofloxacin, ethambutol or ethionamide, terizidone, and pyrazinamide
Seddon (2012)	13	111	24 months	RFU	South Africa	Children	Multivariate logistic regression	Group B	Amikacin, capreomycin, ofloxacin, ethionamide, para-aminosalicylic acid, terizidone, linezolid, etc.
Shibabaw (2018)	19	235	24 months	RFU	Ethiopia	Adults	Cox proportional hazards regression	Group B	At least three of oral agents (pyrazinamide, levofloxacin, ethionamide, protonamide, cycloserine or para-aminosalicyclic acid) and an injectable agent (amikacin, kanamycin, capreomycin)
Shin (2017)	118	588	24 months	RFU	Botswana	Adults	Multivariate Poison regression	Group B	amikacin, levofloxacin, ethionamide, cycloserine, and pyrazinamide
Tola (2020)	18	155	36 months	RFU	Ethiopia	Children	Cox proportional hazards regression	Group B	levofloxacin, ethionamide, cycloserine, para-aminosalicyclic acid, pyrazinamide, prothionamide, linezolid, clofazimine, amikacin, kanamycin and capreomycin
Trebucq (2018)	78	1006	24 months	FU	9 Africa countries	Adults	Multivariate logistic regression	Group B	moxifloxacin, clofazimine, ethambutol, pyrazinamide, kanamycin, prothionamide and high-dose isoniazid
Umanah (2015a)	181	947	24 months	RFU	South Africa	Adults	Multivariate logistic regression	Group B	Kanamycin/Amikacin, Moxifloxacin, Ethionamide, Terizidone, Ethambutol and/or pyrazinamide
Umanah (2015b)	258	1137	24 months	RFU	South Africa	Adults	Multivariate Poison regression	Group B	kanamycin/amikacin, moxifloxicin, ethionamide, terizidone, and pyrazinamide
Van der Walt (2016)	123	393	24 months	RFU	South Africa	Adults and Children	χ2 test	NS	Standardized SLD
Verdecchia (2018)	37	174	18 months	RFU	Eswatini	Adults	Cox proportional hazards regression	Group B	Levofloxacin, ethionamide, terizidone or cycloserine, pyrazinamide, kanamycin/amikacin with/without para-aminosalicylic acid
Woldeyohannes (2019)	73	415	20 months	RFU	Ethiopia	Adults and Children	Cox proportional hazards regression	Group B	Pyrazinamide, Ethambutol, Capreomycin, Levofloxacin, Ehionamide, Cycloserine; and others
Total	4,976	31,525

Note

#, number; NS, not specified; and χ2, chi-squared.

Proportion of patients with the incidence of mortality

The pooled estimate for the incidence of mortality as a percentage rate was 17% (95% CI: 15% - 18%; I2 = 91.40; P = 0.00). The effect sizes estimated for the individual studies ranged from 7% (95% CI: 3% - 16%) to 44% (95% CI: 39% - 50%) (Fig 2).

Fig 2

Forest plot for the incidence proportion of mortality.

Sensitivity analysis

To explore the source of heterogeneity among the included studies, we performed a sensitivity analysis by excluding two of the outliers [41, 42]. However, this resulted in a slight reduction to the degree of heterogeneity with a percentage decrease to the incidence of mortality that was already estimated (effect size: 16%; 95% CI: 15% - 18%; I2 = 88.75%; P = 0.00) (Fig 3).

Fig 3

Forest plot for incidence proportion of mortality by excluding outliers.

Subgroup analyses

Since the variability among studies remained high even after the sensitivity analysis, we performed subgroup analyses to further explore the source of heterogeneity. We categorized the studies by groups of the SLD regimen, median duration of follow-up for the SLD therapy, and regions of the SSA as the key observational features. However, none of these subgroups appeared homogenous except the slight variabilities in the group-specific mortality estimates which were not statistically significant. The incidence proportion of mortality ranged from 13% (95% CI: 8%-17%) for studies with the median follow-up of less than 15 months to 18% (95% CI: 13%-19%) for studies with the median follow-up of 16–20 months. This was 13% (95% CI: 10%-17%) for group A, 15% (95% CI: 13%-17%) for group B, 19% (95% CI: 14%-24%) for group C and 21% (95% CI: 13%-29%) for non-specific SLD regimens. Again, the incidence proportion of mortality was 19% (95% CI: 17%– 22%) for studies from the southern SSA region, 13% (95% CI: 11% - 15%) for studies from the eastern SSA region, and 11% (95% CI: 6% -17%) for studies from mixed SSA regions (S1–S3 Figs).

Predictors of mortality

A total of 23 studies had reported at least one predictor linked with the incidence of mortality among persons receiving the SLD therapy. Nineteen (19) of these studies reported HIV-coinfection and other comorbidities (i.e., diabetes mellitus, myocardial infractions, hypertension, congestive heart failure, asthma, epilepsy, depression, chronic pulmonary insufficiency and pulmonary fibrosis) [32, 34, 35, 37–41, 44, 49, 52, 54, 55, 59–61, 64, 67, 71] while ten of the studies reported diagnoses of clinical conditions such as anemia, underweight (BMI < 18.5 Kg/m2), pneumothorax, pneumonia, hemoptysis, opportunistic infections, cavitary changes and nutritional problems [23, 32, 34, 44, 47, 51, 52, 57, 64, 69] as the key predictors of all-cause mortality. Besides, three of the studies specific to each feature had reported resistance to SLD [54, 69, 71]; male sex [32, 49, 67]; and excessive substance use [61, 64, 69] as the predictors of all-cause mortality. Moreover, two of the studies reported delays (i.e., more than a month) in initiating SLD therapy [59, 61]; encounters of adverse drug events (ADEs) [40, 41], and extra-pulmonary involvement [34, 41] as the predictors of the mortality outcome. Reports of individual studies also indicated multiple other drugs than SLD [41]; previous episode of TB [71]; previous history of failed treatment [23], and under five aged children [35] as the predictors of mortality.

We combined risk ratio estimates for at least three of the studies that reported similar predictors of all-cause mortality and found its significant increases among persons receiving the SLD and with certain characteristics. These features included diagnoses of newer clinical conditions (RR: 2.36; 95% CI: 2.82–3. 05); substance use (RR: 2.56; 95% CI: 1.78–3.67); presence of HIV-coinfection and other comorbidities (RR: 1.96; 95% CI: 1. 65–2.32); resistance to SLD (RR: 1.75; 95% CI: 1.37–2.23); and male sex (RR: 1.82; 95% CI: 1.35–2.44) (Fig 4). The resistance to SLD regimen was defined by the studies as any resistance to fluoroquinolones or at least one injectable aminoglycoside (i.e., capreomycin, kanamycin, amikacin) [54, 69, 71].

Fig 4

Predictors of mortality among persons receiving SLD in SSA.

(a) Forest plot describing presence of HIV and other comorbidities as the predictors of mortality. (b) Forest plot describing male sex as a predictor of mortality. (c) Forest plot describing diagnoses of clinical conditions as the predictors of mortality. (d) Forest plot describing resistance to SLD as a predictor of mortality. (e) Forest plot describing substance uses as the predictors of mortality.

Publication bias

Graphical visualization of the funnel plot found its symmetrical appearance which gave us hint about absence of the publication bias. This visual inspection was further tested by using Egger’s regression and it also showed no evidence of the small-study effects (effect estimate: 1.40; 95% CI: -0.14–2.94; P = 0.073). Additionally, Begg’s correlation test revealed no evidence of the publication bias (Z = 0.96; P = 0.34) (Fig 5).

Fig 5

Funnel plot of standard error by effect size for publication bias.

Discussion

More than one-sixths of the persons receiving SLD for DR-TB managements in SSA had died during the last decade. A relatively lower incidence proportion of the mortality was found among the DR-TB patients treated with group A or B regimens compared with those patients treated with group C regimens. The pooled risk ratio estimate for the identified predictors found increased incidences of mortality among persons with features of established comorbidities, diagnoses of newer clinical conditions, resistance to SLD, substance use, and male sex.

The pooled incidence proportion of mortality among the DR-TB patients treated with SLD in SSA was 17%. No significant differences were found by subgroup analyses that considered the median time period of treatment follow-up, specific regimen groups for SLD and regions of the SSA. However, the pooled estimate of mortality was as high as 19% in southern SSA and as low as 13% among the patients treated with group A SLD. It was also estimated to be 15% among the patients treated with group B regimens. Essentially, these estimates are promising and can hint as though this setting is on a right track to achieving the EndTB strategy target of 90% mortality reduction by 2030 [2]. A study report also revealed similar benefits of using SLD regimens that contained linezolid, a later generation fluoroquinolones (levofloxacin or moxifloxacin), bedaquiline, clofazimine, or capreomycin [74]. Most of these drugs are the essential medicines that are usually added to groups A, B, or shorter SLD regimens. A similar meta-analysis also reported that there have been no significant differences in survival benefits with respect to specific drugs used and the time period of the treatment follow-up [75]. Again, most of the specific drugs added to group A, B or C regimens were part of the DR-TB treatment advances in the last decade [76]. Similar benefits were reported by the use of repurposed drugs, newer drugs, later generation fluoroquinolones, ethionamide or prothionamide, four or more effective drugs in intensive phase, and three or more likely effective drugs in continuation phase of the DR-TB treatment [76]. Most of the DR-TB patients included in this review also used SLD regimens that added the later generation fluoroquinolones, repurposed agents, newer drugs, and injectable aminoglycosides. Besides, these drugs had appeared to have strong association with treatment success and survival benefits [77].

Moreover, most of the DR-TB patients in SSA had already initiated newer agents and shorter SLD regimens as part of the response to EndTB Strategy and WHO recommendation [76]. These shorter regimens appeared to be effective in treating MDR-TB [78]. With this, the type of drug added to the SLD regimen is considerable for optimal benefits [79]. To this end, the global average mortality of 15% among the cohort of DR-TB patients treated with SLD mirrors the percentage rate this study found (17%) for a similar setting (i.e., SSA) [2]. About half of countries (n = 21) from among 48 countries with high burden of DR-TB patients included in the cohort were from SSA, for which the estimated treatment successes ranged from zero percent (in Angola) to 88% (in Congo). For this cohort, majorities of the SSA countries achieved a success rate of around 65% [2]. Individual studies that participated DR-TB patients during their SLD therapy follow-up in India, Malaysia, and Pakistan also found 16%, 15.3%, and 17.4% mortality rates, respectively [80-82].

HIV and other comorbidities were the most common predictors of mortality which were frequently reported among persons receiving SLD therapy. The mortality was 1.96 times higher among the patients with comorbidities than those patients free of these conditions. Similarly, in reference to patients free of comorbidities, the risk of mortality among the patients with various comorbid conditions while on SLD therapy was variably increased by 1.96 (95% CI: 1.35–3.85), 2.33 (95% CI: 1.34–4.05), 2.6 (95% CI: 1.82–3.70), 5.42 (95% CI: 2.66–11.04), and 6.82 (95% CI: 2.16–21.50) folds [9, 12, 80, 83]. Again, several other studies indicated a varied but increased likelihood of mortality by 1.46 (95% CI: 1.05–1.96), 1.50 (95% CI: 1.20–1.90), 1.70 (95% CI: 1.20–3.10), 1.89 (95% CI: 1.02–3.52), 2.97 (95% CI: 1.41–6.24), 3.18 (95% CI: 1.05–9.69), 3.47 (95% CI: 1.02–11.64), 4.22 (95% CI: 2.65–6.72), and 5.6 (95% CI: 3.2–9.7) times higher among the HIV-infected patients than HIV-uninfected ones [83-91]. A meta-analysis also reported 1·8 (95% CI: 1·5–2·2) times higher odds of mortality among the HIV-positive patients on antiretroviral therapy (ART) than those who did not receive the ART [92], but majorities of the studies included in our review did not report mortality by the ART status and we were unable to explore this difference by the ART treatment. Another meta-analysis also stressed on a closer link between HIV-infection and MDR-TB and found that the MDR-TB was 2.28 times more likely in HIV-infected people than those people who were HIV-uninfected [93]. In the current review, the risk of mortality was somewhat lower than the likely risks reported by several of the previous studies. Unarguably, the MDR-TB management approach of countries (in the last decade) had involved early and rapid diagnosis with genotype testing; prompt treatment with appropriate regimens based on drug-susceptibility testing; preference for shorter regimens by using newer or repurposed drugs; a patient-centered approach; and strong infection-control measures. All these strategies might have helped the mortality reduction among the DR-TB patients with comorbidities including HIV-coinfection [94]. Also, the use of a differentiated care approach, the demand created for effective TB/HIV service delivery, the establishment of HIV/TB coordination mechanisms, the rapid scale-up of facilities with decentralization of treatment services, the regular joint supervision, and monitoring might have contributed to the successes [95, 96].

In another way round, CD4 values lower than 50 cells/mm3 (HR, 4.64; P = 0.01) and 51–200 cells/mm3 (HR, 4.17; P = 0.008) among the treated DR-TB patients were found as the independent risk factors of mortality compared with those patients with CD4 values >200 cells/mm3 [97]. A higher susceptibility to opportunistic infections (OIs) due to the lower immune status (indicated by the low CD4 levels) can justify this finding. Previous OIs among patients treated with SLD therapy were also related to a 3.13 (95% CI: 1.64–5.96) times higher hazards of mortality than those without the OIs episode [90]. Again, patients with previous TB history and treated with SLD for about 2–6 months had 1.46 times higher risks of mortality compared to the patients without previous TB episodes [98]. In addition, history of previous TB increased the risk of death by 1.61 fold among patients with the episode compared to those patients free of the episode [12]. A study finding also implicated numbers of the previous TB episodes to have direct links with the increased risks of death [83].

Resistance to SLD was another predictor of mortality with about 75% increased risks of death among the patients who experienced drug resistance. Consistent with this finding, a study in Brazil found that MDR-TB patients who developed resistance to SLD had 74% higher risks of death than those patients who did not experience resistance [84]. Another study also reported resistance to the SLD as a key predictor of poor outcome (OR: 2.61; 95% CI: 1.61–4.21) [81]. Besides, a 31.4% incidence proportion of mortality was reported among the cohort of patients with any form of resistance to SLD therapy [99]. This mortality could reach more than 50% among under-treated patients with the resistant strains [100]. Again, MDR-TB patients with any form of resistance to SLD were found to have the lowest success rate (29.3%) [101]. In line with this, delay in initiating the SLD regimens or substituting the regimen components with resistance could be the likely reason for extending to a further resistance. About two-fold increased odds of dying was reported with the delay in starting SLD treatment [102]. Again, near to 30% increased risk of unfavorable outcome was explained with more than a month delay in initiation of SLD after the resistance detection [103]. Delay in the resistance detection was also reported to increase the probability of mortality by 8.3% among the patients treated with SLD therapy [104].

In this review, the risk of mortality was 2.36-fold increased among the cohorts of patients diagnosed with clinical conditions than those patients free of the conditions. Underweight and anemia were the most frequent diagnosis that the studies reported. Similarly, other studies also revealed underweight to be 1.30 (95% CI: 1.0–1.50), 2.50 (95% CI: 2.10–2.90), 2.50 (95% CI: 1.70–3.5), and 3.39 (95% CI: 1.20–9.45) times more likely related with unfavorable outcomes than the patients with normal body weight [11, 91, 105, 106]. Besides, there were pieces of evidence that reported findings of baseline underweight among most MDR-TB patients (i.e., up to 86.6%), in which anemia was the most common clinical condition (i.e., up to 73.83%) [107-109]. Besides, underweight patients had a 90% increased incidence of mortality than the patients with normal body weight [110]. In fact, severe anemia and malnutrition were known as the independent predictors of early mortality in TB patients [111].

The DR-TB patients who used excessive substances (cigarette and alcohol) and male patients had 2.56 and 1.82 times higher risks of mortality than the patients who did not use the substances and who were females, respectively. Consistently, patients with excessive substance uses tended to have poor MDR-TB treatment outcomes [112]. In a study report, patients with alcohol misuse had a 1.45 (95% CI: 1.21–1.75) times higher risks of unsuccessful outcomes than the patients who did not drink alcohol [113]. Again, MDR-TB patients with habits of cigarette smoking were found to have 5.44 (95% CI: 1.09–27.19) times higher odds of mortality than those patients who were non-smokers [89]. In line with this, a two-fold increased odds of substance abuse disorders were correlated with male sex [114]. And, the risk of mortality was 1.4 (95% CI: 1.1–1.7) and 2.0 (95% CI: 1.27–3.14) times higher among males than females on SLD therapy follow-up [9, 106].

Despite the large size of aggregate data pooled together for summary effects in this systematic review and meta-analysis, it is not without limitations. First, the studies considered for the meta-analysis were observational by nature. This selection might have resulted in a higher degree of heterogeneity with a range of potential biases. However, we employed a random-effects model to account for the anticipated heterogeneity. Second, there were some inconsistencies in the studies included in terms of the median time period of follow-up for the SLD therapy, but we assumed the intention-to-treat approach and considered deaths reported at any time during the follow-up period. Third, the retrospective cohort studies included in our review did not adjust for mortality in patients with lost follow-up and failed treatment. Due to the aggregate data meta-analysis approach and a limited control over the data, these deaths could not be accounted for, and this gap might have under-estimated the incidence of all-cause mortality. Fourth, we included articles written in the English language, and this restriction could have under-or over-estimated the pooled incidence of mortality and its predictors while on the SLD therapy. Fifth, there appeared some overlaps of included patients in four of the South Africa studies reporting national treatment register and community-based programs, but we were unable to avoid such overlaps for we do not have clear knowledge of the data source. Therefore, interpretations for the findings in this review need to be aligned and seen in contexts of these limitations.

Conclusions

We found about one in six persons who received SLD in SSA had died in the last decade. This pooled incidence proportion of mortality while on the SLD therapy follow-up among the patients in SSA mirrors the global average mortality. Several measures including fortification of newer or repurposed drugs and the initiation of shorter regimens were among the essential components for this acceptable mortality rate we estimated which was in line with the set target of EndTB Strategy. Nonetheless, the incidence of mortality was considerably high among DR-TB patients with comorbidities; diagnoses of other clinical conditions; resistance to SLD therapy; male sex; and excessive substance use. Therefore, modified measures involving shorter SLD regimens fortified with newer or repurposed drugs, differentiated care approaches, and support of substance use rehabilitation programs can help improve the treatment outcome of persons with the drug-resistant tuberculosis.

Forest plot of mortality proportion by median duration of SLD therapy.

(TIF)

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Forest plot of mortality proportion by group of SLD regimen.

(TIF)

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Forest plot of mortality proportion by SSA regions.

(TIF)

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PubMed search strategy and results.

(DOCX)

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Quality assessment for the included studies.

(DOCX)

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Completed PRISMA checklist.

(DOC)

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2 Mar 2021

PONE-D-20-25643

Risk factors of mortality during course of second-line tuberculosis treatment in sub-Saharan Africa: A meta-analysis of cohort studies

PLOS ONE

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Reviewer #1: Partly

Reviewer #2: Yes

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Reviewer #2: I Don't Know

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Reviewer #1: Section of the paper Comment

General

Content I think that the authors need to highlight what makes this study novel as there have been similar systematic reviews and meta-analyses investigating factors associated with ones DR-TB prognosis, including mortaltiy.

Methodology I generally think that the methodology used requires improvement. The inclusion criteria are not explicit and I think there is a possibility that patients have been included more than once in the analysis. Additionally, I think that the intent to treat methodology might have led to an underestimation of mortality. With that said I wonder how the risk can be accurately determined.

Editing The authors should pay attention to the grammar used throughout. The grammar used needs improvement. The authors might benefit from an editing service to improve the structure and flow of many of these sections.

The authors should ensure that they define all abbreviated terms upon first time use and thereafter they can use the abbreviated term (i.e. SLD).

The authors should spell out numbers less than 10 unless they are linked to a unit of measurement.

Title

Language and representativeness The English used in the title is not clear. You might want to consider an alternative title for example:

Risk factors of mortality among persons receiving second-line tuberculosis treatment in sub-Saharan Africa: A meta-analysis of cohort studies

Additionally, in the title you might want to consider including the number of studies included in the meta-analysis.

Abstract

Introduction I think that the authors need to consider highlighting what makes this study novel here.

Methods I think that the authors need to further expand on their inclusion and exclusion criteria here.

Background

General I recommend that you update the references to include the data from the WHO Global TB report from 2020.

Kindly clarify the language used after reference 6. I think you are referring to the missing TB cases. You could say something like in addition to the large number of missing incident DR-TB cases,….”

I recommend that you edit the first sentence of the second paragraph. The wording is quite awkward. In fact I recommend that this whole paragraph is edited in order to improve the flow and use of English language.

In the last paragraph, I think you need to focus more on what makes your study unique and novel as there have been various systematic reviews which have investigated the various DR-TB treatment correlates associated with outcomes.

Methods

The protocol and registration This paragraph requires editing for improved English language use.

Search strategy I wonder why the authors did not use the term mortality in their search strategy?

Eligibility criteria I am not sure what you mean by this? Do you mean you excluded studies that only evaluated treatment success? All DR-TB outcomes are intertwined. Even patients who are LTFU or whom fail treatment are at increased risk of mortality.

“But, we excluded records with outcomes unrelated or irrelevant to mortality and/or its risk factors.”

What do you define as insufficient as mentioned in the below comment? Additionally I am not sure as to your intended meaning when you say mixed patients? I am not sure how patients were excluded on these bases. This requires clarification to truly understand who was vs was not enrolled.

“Again, we excluded studies which report outcomes with insufficient quality and no separate result in the case of mixed patients from both extensively drug-resistant TB and multidrug-resistant TB treatments.”

I wonder if the authors only included studies which used the WHO definitions of outcomes.

Again, were only 24 month outcomes evaluated? Or were interim outcomes evaluated in this study.

Study selection procedure If patients were retreatment cases, how did you decide which treatment episode to include in your study?

Data extraction process As you say that you used intention to treat analysis, does this mean you included studies that reported on interim outcomes. Again, this requires clarification in the eligibility criteria section of the paper.

Outcomes definition

Page 4, line 36

Page 4, line 39

Rather say “Outcome definitions”

The primary outcome in this study was the occurrence of AEs.

Results

Study characteristics I recommend that you do not say mixed-age patients. You could consider something like included both “adults and children”.

Why do you say 9 of the 34 included studies but then you also say that only 43 studies were included.

Table 1 I see that you include patients with different follow-up durations i.e. you did not evaluate end of treatment outcomes and you including interim treatment outcomes. These studies might therefore underreport mortality. How did you account for this in your analysis?

There could be the same patients from the study conducted by Schnippel et al 2015 in the other South Africa based cohort studies as the study conducted by Schnippel reviewed the national treatment register. Have you ensured that you excluded duplicate records for all of these studies.

Risk Factors of Mortality I see that the authors report on substance use as a risk factor for mortality but it would be helpful to have a better understanding of how this was quantified/classified in the included studies.

You say “experience of treatment failure” was a risk factor for mortality so did you evaluate all cause mortality in this study (i.e. mortality that also occurred after LTFU or Rx failure). This requires clarification in the methods section of the paper.

Later in this section you state the following:

“However, the risk of mortality was not significantly increased in under-five children, in patients who failed treatment and those patients who experienced ADE during course of the treatment.”

This seems to contradict the statement I mention in my above comment regarding treatment failure.

In your analysis of risk of mortality, did you look at all into the regimens received/the drugs included in the regimen and what drugs might have influenced mortality. Did you look at the cohort based on year of Rx initiation? Various factors have changed regarding policy and clinical practice from 2010-current and therefore I wonder how the authors accounted for the change in the management of the disease over time.

I wonder if there were any social factors you could assess as well in order to determine risk factors associated with mortality. i.e. household income, female led households, number of people in the household, setting/housing structure

Discussion

First paragraph I recommend that you first summarize your finding without yet making reference to other studies in detail. Additionally, I would not say that the mortality is justified because then it sounds as if we are saying that it is “OK” that the mortality for these individuals is acceptable. We might be able to explain the factors contributing to it but it is far from acceptable and no where in line with making progress towards achieving the goals outlined in the EndTB strategy.

You could just generally compare your mortality rate to that reported by the WHO for all patients enrolled on treatment globally as a baseline and then delve more specifically into country level mortality.

General I think this section requires many improvements. It seems that you just compare your findings to those from previously published studies rather than really looking into the policy and implementation factors that might be driving these risk factors. You might want to consider mentioning different models of care or approaches to TB control and management that can be employed to mitigate these risk factors, which have already been well documented in the literature. I do not think that the risk factors you point to here are different in any way from those already known and well documented in the literature.

Limitations

General comments I do not think that the intention to treat approach is realistic to procure good enough evidence in this study to inform policy regarding mortality. Without systematic follow-up for everyone mortality could be underestimated and the identified risk could therefore be less than that in reality should we have complete follow-up for this cohort of patients.

Conclusions

General comments I feel as though this section is weak. Although you have summarized your key findings and made recommendations they are very general. I think you could have better utilized the discussion section to expand on the various measures that could be employed to address high rates of mortality.

Figures

General comment Ensures that your figure quality is improved as the figures are blurry.

Reviewer #2: In this meta-analysis the authors set out to identify risk factors for mortality during treatment for RR/MDR-TB in sub-Saharan Africa. The central findings of the analysis include the following: 17% of patients died during RR/MDR-TB treatment, and risk factors included low BMI (RR 2.5), substance use (or abuse?) (RR 2.5), HIV (RR 2.2), co-morbid conditions (RR 2.0), resistance to SLD (RR 1.92), anemia (RR 1.75), male sex (RR1.8) and delayed initiation of RR/MDR treatment for > 1 month (RR1.6). The methodology appears scientifically sound however this manuscript requires professional language and grammatical editing prior to publication

Introduction

The introduction cites outdated references and incorrect statistics.

- (page 3) “As a result, only near to half of the drug-resistant TB patients are successfully treated; with approximately up to 40% of them dying during the treatment” – this statement is inaccurate. According to the WHO 2020 Global TB report, for the 2017 global cohort, 57% of RR/MDR-TB patients completed treatment successfully, 15% died, 16% were lost to follow-up and 7% failed. These figures have remained fairly stable for several years (see WHO Global TB report 2020 page 107).

- (page 3) “It (mortality) was alarmingly increased to over 30-40 percent in resource-limited settings”. This is not an accurate reflection of the WHO data on RR/MDR-TB mortality in sub-Saharan Africa where treatment success rates and mortality mirror the global averages. If the authors are including in this statement people who die without accessing treatment (undiagnosed or untreated) then they should clarify this sentence.

- Reference #2 and 5: Should cite updated statistics from the WHO 2020 global health report (introduction).

Methods:

- What search terms were used? The authors should strongly consider including a table describing the search terms used in the study in a supplementary appendix

- Was this an individual patient meta-analysis or aggregate data meta-analysis? This should be stated.

- Restrictions on studies: the authors only mention dates and English language as restrictions, however based on the final selection there must have been other restrictions. Possible restrictions that the authors don’t mention but that would have factored into their selection include:

o Exclusion of clinical trials

o Limiting the studies to patients with rifampicin-resistant and/or multi-drug-resistant TB

o Were reports of pre-XDR/XDR of FQ-R TB excluded or included?

- How many investigators extracted the data? Was it done concurrently or separately and were differences in data extraction reviewed?

- What data was extracted from the reviewed studies

- How was substance abuse/use defined in the studies that evaluated this as a risk factor for mortality?

- How was second-line drug-resistance defined (i.e. resistance to aminoglycosides and/or FQs) in the studies that included this data? And what were the proportions of patients with AG vs FQ resistance in those included in the review.

- The authors should define rifampicin resistant and multi-drug resistant TB in the methods section

- The failure to include ART as a variable in the risk factor analysis for patients with HIV is problematic. If possibly I would strongly suggest that the analysis be reviewed with this risk factor as it has major implications for mortality of patients with RR/MDR-TB and HIV. ART status should be defined as on ART, not on ART or ART status not known.

- Definition of treatment outcomes should be included (i.e. how were success, lost to follow-up and failure defined in the included studies).

Results

- Table 2: Insufficient detail provided on the standard treatment regimens used in the various studies. There has been rapid evolution since 2010 in the treatment of RR/MDR-TB and modifications in the treatment regimen could result in some of the heterogeneity in the results. Consider adding this data to table 2 (for example a column with % of patients treated with AG, % of patients treated with later-generation FQ and % of patients treated with BDQ for each study, if this data is available). If this level of detail is not available or not possible to retrieve, a narrative description of the regimens used in the included studies should be added to the methods section. They could be classified according to the WHO effectiveness categories in use at the time of the study (prior to the recent major change in WHO classification of second-line TB drugs).

- Table 2: should include % HIV prevalence and % on ART in each study. The study period for each included study should also be added,

- The proportion of patients with HIV on ART is not addressed in the results section and this has major implications for mortality.

Discussion

The discussion section needs to be re-written. The purpose of the discussion section is to highlight the findings of the study and place them in the context of the literature in the field. This was not done successfully. Instead the current discussion is a re-iteration of the results of the study without much additional insight or contextualisation. Many prominent recent articles in the field and important concepts are not highlighted.

The failure to discuss the impact ART on RR/MDR-TB treatment outcomes in people living with HIV stood out. Much has been written about this in the literature that is not cited or discussed.

A brief literature review revealed several relevant and important articles in this field that are not discussed or referenced suggesting that the authors have not performed an adequate literature review which may be why they appear to have difficulty contextualising their findings in the discussion.

- Bastos et al ERS 2017 - An updated systematic review and meta-analysis for treatment of multidrug-resistant tuberculosis

- Bisson et al Lancet 2020 - Mortality in adults with multidrug-resistant tuberculosis and HIV by antiretroviral therapy and tuberculosis drug use: an individual patient data meta-analysis

- Mesfin et al Plos One 2014 - Association between HIV/AIDS and Multi-Drug Resistance Tuberculosis: A Systematic Review and Meta-Analysis

- Khan et al. ERS 2017 Effectiveness and safety of standardised shorter regimens for multidrug-resistant tuberculosis: individual patient data and aggregate data meta-analyses

- Ahmad et al. The Lancet 2018. Treatment correlates of successful outcomes in pulmonary multidrug-resistant tuberculosis: an individual patient data meta-analysis

- Isaakidis et al IJTLD 2015. Treatment outcomes for HIV and MDR-TB co-infected adults and children: systematic review and meta-analysis.

- Fox et al. ERS 2017 Group 5 drugs for multidrug-resistant tuberculosis: individual patient data meta-analysis

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Reviewer #1: No

Reviewer #2: Yes: Rebecca H Berhanu

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Submitted filename: PlosOne_Risk Factors of mortality_Review.docx

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19 Apr 2021

Authors' response to reviewers comments are attached a separate file with all files submitted.

Submitted filename: Rebuttal letter to reviewers comments.docx

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8 Oct 2021

PONE-D-20-25643R1Mortality and its risk factors among persons receiving second-line tuberculosis treatment in sub-Saharan Africa: A meta-analysis of 43 cohort studiesPLOS ONE

Dear Dr. Edessa,

Thank you for submitting your revised manuscript to PLOS ONE. After careful consideration, we feel that it has improved but still does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. In particular Reviewer #1 still has minor concerns; in addition your manuscript was reviewed by a professional statistician, who raised several concerns that should be addressed before we can accept you manuscript for publication.

Please submit your revised manuscript by Nov 22 2021 11:59PM. If you will need more time than this 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:If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter.

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'.

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We look forward to receiving your revised manuscript.

Kind regards,

Olivier Neyrolles

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.

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: (No Response)

Reviewer #3: (No Response)

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #1: Partly

Reviewer #3: Yes

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

Reviewer #1: Yes

Reviewer #3: Yes

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #1: Yes

Reviewer #3: Yes

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #1: No

Reviewer #3: Yes

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6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #1: Kindly review all of my comments in the attached file. Generally, I feel as though this manuscript still requires heavy editing for improved English language and clarity.

Reviewer #3: The present is an interesting paper.

Some issues.

Abstrct should be shortened : e.g. introduction should be more focused on resistance to tubercolosis.

Abstract>primary end point should be defined

Abstract; it should be better specified how (And if ) RRs were pooled

Abstract: some incidence or percentages should be added

Methods: due to observational design of the studies probably random effect should be used

MEthods/results: comparison between different lenght of therapy is not inferental, but just observational. this should be clearly stated

Methods: authors should evalaute if they need to pool together RR (see PMID: 22360945)

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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 #3: Yes: Fabrizio D'Ascenzo

[NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.]

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/. PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org. Please note that Supporting Information files do not need this step.

Submitted filename: PlosOne_Risk Factors of mortality_Review_v2.docx

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15 Nov 2021

A document of rebuttal letter as 'response to reviewers' comments was attached alongside the manuscript files. Please check the attachment for this section as well.

Submitted filename: Response to Reviewers.docx

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29 Nov 2021

Incidence and predictors of mortality among persons receiving second-line tuberculosis treatment in sub-Saharan Africa: A meta-analysis of 43 cohort studies

PONE-D-20-25643R2

Dear Dr. Edessa,

We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.

Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.

An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.

If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org.

Kind regards,

Olivier Neyrolles

Section Editor

PLOS ONE

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 #3: All comments have been addressed

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

The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.

Reviewer #3: (No Response)

**********

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

Reviewer #3: (No Response)

**********

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

The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.

Reviewer #3: (No Response)

**********

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

PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.

Reviewer #3: (No Response)

**********

6. Review Comments to the Author

Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters)

Reviewer #3: (No Response)

**********

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 #3: Yes: Fabrizio D'Ascenzo

2 Dec 2021

PONE-D-20-25643R2

Incidence and predictors of mortality among persons receiving second-line tuberculosis treatment in sub-Saharan Africa: A meta-analysis of 43 cohort studies

Dear Dr. Edessa:

I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department.

If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org.

If we can help with anything else, please email us at plosone@plos.org.

Thank you for submitting your work to PLOS ONE and supporting open access.

Kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Olivier Neyrolles

Section Editor

PLOS ONE