The latent tuberculosis cascade-of-care among people living with HIV: A systematic review and meta-analysis

Mayara Lisboa Bastos; Luca Melnychuk; Jonathon R Campbell; Olivia Oxlade; Dick Menzies

doi:10.1371/journal.pmed.1003703

. 2021 Sep 7;18(9):e1003703. doi: 10.1371/journal.pmed.1003703

The latent tuberculosis cascade-of-care among people living with HIV: A systematic review and meta-analysis

Mayara Lisboa Bastos ^1,^2,^3,⁴, Luca Melnychuk ³, Jonathon R Campbell ^1,^3,^4,⁵, Olivia Oxlade ⁴, Dick Menzies ^1,^3,^4,^5,^*

Editor: Amitabh Bipin Suthar⁶

PMCID: PMC8439450 PMID: 34492003

Abstract

Background

Tuberculosis preventive therapy (TPT) reduces TB-related morbidity and mortality in people living with HIV (PLHIV). Cascade-of-care analyses help identify gaps and barriers in care and develop targeted solutions. A previous latent tuberculosis infection (LTBI) cascade-of-care analysis showed only 18% of persons in at-risk populations complete TPT, but a similar analysis for TPT among PLHIV has not been completed. We conducted a meta-analysis to provide this evidence.

Methods and findings

We first screened potential articles from a LTBI cascade-of-care systematic review published in 2016. From this study, we included cohorts that reported a minimum of 25 PLHIV. To identify new cohorts, we used a similar search strategy restricted to PLHIV. The search was conducted in Medline, Embase, Health Star, and LILACS, from January 2014 to February 2021. Two authors independently screened titles and full text and assessed risk of bias using the Newcastle–Ottawa Scale for cohorts and Cochrane Risk of Bias for cluster randomized trials. We meta-analyzed the proportion of PLHIV completing each step of the LTBI cascade-of-care and estimated the cumulative proportion retained. These results were stratified based on cascades-of-care that used or did not use LTBI testing to determine eligibility for TPT. We also performed a narrative synthesis of enablers and barriers of the cascade-of-care identified at different steps of the cascade.

A total of 71 cohorts were included, and 70 were meta-analyzed, comprising 94,011 PLHIV. Among the PLHIV included, 35.3% (33,139/94,011) were from the Americas and 29.2% (27,460/94,011) from Africa. Overall, 49.9% (46,903/94,011) from low- and middle-income countries, median age was 38.0 [interquartile range (IQR) 34.0;43.6], and 65.9% (46,328/70,297) were men, 43.6% (29,629/67,947) were treated with antiretroviral therapy (ART), and the median CD4 count was 390 cell/mm3 (IQR 312;458). Among the cohorts that did not use LTBI tests, the cumulative proportion of PLHIV starting and completing TPT were 40.9% (95% CI: 39.3% to 42.7%) and 33.2% (95% CI: 31.6% to 34.9%). Among cohorts that used LTBI tests, the cumulative proportions of PLHIV starting and completing TPT were 60.4% (95% CI: 58.1% to 62.6%) and 41.9% (95% CI:39.6% to 44.2%), respectively. Completion of TPT was not significantly different in high- compared to low- and middle-income countries. Regardless of LTBI test use, substantial losses in the cascade-of-care occurred before treatment initiation. The integration of HIV and TB care was considered an enabler of the cascade-of-care in multiple cohorts. Key limitations of this systematic review are the observational nature of the included studies, potential selection bias in the population selection, only 14 cohorts reported all steps of the cascade-of-care, and barriers/facilitators were not systematically reported in all cohorts.

Conclusions

Although substantial losses were seen in multiple stages of the cascade-of-care, the cumulative proportion of PLHIV completing TPT was higher than previously reported among other at-risk populations. The use of LTBI testing in PLHIV in low- and middle-income countries was associated with higher proportion of the cohorts initiating TPT and with similar rates of completion of TPT.

Mayara Lisboa Bastos and co-workers report on cascades of care for tuberculosis preventive therapy in people with HIV infection.

Author summary

Why was this study done?

Tuberculosis (TB) remains as one of the main causes of deaths among people living with HIV (PLHIV).
Tuberculosis preventive therapy (TPT) reduces TB-related morbidity and mortality PLHIV.
Previous meta-analysis has shown that many losses occurred in the TPT cascade-of-care. However, a similar analysis has not been conducted in PLHIV.

What did the researchers do and find?

We conducted a systematic review and meta-analysis evaluating the TPT cascade-of-care among PLHIV. We constructed 2 cascade-of-care frameworks: (1) studies that did not use LTBI tests to determinate TPT eligibility; and (2) studies that used LTBI tests to determinate TPT eligibility.
We performed stratified analyses by income setting (high-income versus low- and middle-income countries) and type of clinics where patients were followed (HIV clinics versus other clinics). We also performed meta-regression using adjusting these 2 variables.
Among the cohorts that did not use LTBI tests, the cumulative proportion of PLHIV completing TPT was 33.2% and 41.9% among cohorts that used LTBI tests. This was not statistically significant when we performed meta-regression by income and type of clinics.

What do these findings mean?

The cumulative proportion of PLHIV completing TPT was higher than was previously reported among other at-risk populations.
Recommendation and initiation of TPT was higher, and completion similar among cohorts that used LTBI tests, compared to cohorts offered TPT without LTBI testing.
The use of LTBI test was not an important barrier for TPT.
Substation losses remained in the TPT cascade-of-care, and continuous efforts are necessary to improve TPT care among PLHIV.

Introduction

Tuberculosis (TB) remains a significant public health problem, particularly among people living with HIV (PLHIV). In 2019 alone, nearly 25% of PLHIV with TB disease died [1]. Tuberculosis preventive therapy (TPT) works synergistically with, and independently of, antiretroviral therapy (ART) to reduce TB incidence among PLHIV [2–4].

To scale up TPT in PLHIV, WHO has simplified its algorithm for TPT initiation by not requiring latent tuberculosis infection (LTBI) tests prior to initiation [4]. Either a tuberculin skin test (TST) or interferon gamma release assay (IGRA) can identify people who have LTBI, but these tests have reduced sensitivity among PLHIV due to impaired T-cell immunity. While PLHIV with a positive LTBI test are at substantially increased risk for active TB compared to PLHIV with a negative test, those with a negative test still experience TB disease at rates about 5 times higher than the general population [5]. For this reason, WHO recommendations permit TPT without the requirement of LTBI testing.

In 2019, 50% (3.5 million) of PLHIV newly enrolled in care initiated TPT compared to 1.5 million initiating TPT in 2018 [1]. However, these figures fail to capture the complete picture. Half of individuals eligible for TPT never initiated it, and it is uncertain how many of those initiated TPT completed it [1]. Thus, important barriers other than LTBI testing remain to be elucidated.

Cascade-of-care frameworks are increasingly used to identify gaps and barriers in care in order to develop targeted solutions [6–9]. These frameworks describe population-level engagement in the sequential steps of healthcare delivery systems in which patients must pass through multiple interventions to reach a desired outcome. Such cascades have been invaluable in highlighting gaps in HIV diagnosis and treatment implementation [10] and more recently have been used to broadly assess TPT uptake [11].

To help identify care gaps and potential targeted solutions, we conducted a systematic review and meta-analysis evaluating the LTBI cascade-of-care for TPT among PLHIV.

Methods

Objectives, search strategy, and selection criteria

Our systematic review and meta-analysis is reported according to PRISMA guidelines (S1 PRISMA Checklist) [12], and its protocol was registered in PROSPERO (CRD42020190264). The overall objective of this present systematic review was to quantify the cumulative proportion of PLHIV completing each step of the LTBI cascade-of-care and to summarize health systems barriers and interventions to overcome those barriers identified for each step.

We first screened potential titles from a previous systematic review on the LTBI cascade-of-care published in 2016 [11]. This review had screened articles in 3 databases (Medline, Health Star, Embase) from 1946 to April 12, 2015, and it included different populations at risk of developing active TB, including PLHIV. For the identification of new cohorts, we updated the search, rerunning the search strategy using similar search terms, but with a focus in PLHIV (S1 Search Strategy) in the abovementioned databases, from January 1, 2014, to February 17, 2021. To expand our search to non-English publications, we searched one additional database, LILACS, from the inception date to February 17, 2021. For this database, we used a combination of English, Spanish, and Portuguese terms (strategy available in S1 Search Strategy). We also identified additional relevant articles from the reference list of the included studies and from another published systematic review [5].

Two reviewers (MLB and LM) independently screened titles, abstracts, and full text. When a consensus was not achieved, a third reviewer was consulted (DM).

Studies published in English, French, Portuguese, Spanish, and Chinese were eligible for inclusion. The studies had to report at least 2 consecutive steps of the cascade-of-care (defined in data extraction session and in Figs 1 and 2), have at least 25 PLHIV in the first step reported in that study, and report the use or not of LTBI tests (either TST or IGRA) to determine TPT eligibility. If the population was not exclusively PLHIV, the steps of the cascade-of-care had to be stratified by HIV status. We excluded studies which the objective was focused only on active TB case finding in PLHIV, and they did not investigate outcomes related to LTBI treatment. We excluded individual-level randomized clinical trials (RCTs) that evaluated efficacy of LTBI regimens. Editorials, opinion letters, and conference abstracts were also excluded.

Fig 1 — LTBI, latent tuberculosis infection; TPT, tuberculosis preventive therapy.

Fig 2 — LTBI, latent tuberculosis infection; TPT, tuberculosis preventive therapy.

Data extraction

Two reviewers (MLB and LM) extracted 20% of the data using a standardized data form, then findings were checked for concordance. The agreement was high (95%), thus, a single reviewer (MLB) extracted the remaining data. Data extracted included study design, country, level of care (primary, secondary, or tertiary), type of service (TB, HIV, and other services), if an LTBI test was used or not, and the type of LTBI test used (IGRA or TST), if applicable. We collected information on the characteristics of the population including age, sex, ART, CD4 cells count, and LTBI regimen prescribed. We accepted the definition of a positive LTBI test (either IGRA or TST) as reported by the original studies. Within each cohort, we extracted the number of persons reaching each of the following steps of the cascade-of-care: (i) initially identified; (ii) tested for LTBI; (iii) LTBI test result available (TST read, or valid IGRA result received by providers); (iv) completed medical evaluation (including chest X-ray); (v) TPT recommended by providers; (vi) TPT accepted and started; and (vii) LTBI treatment completed (Figs 1 and 2). We considered TPT to have been recommended, if the study explicitly described a step as “providers recommendation,” or if the study provided eligibility criteria for patients to receive TPT. In these studies, we assumed that the patients that met the center’s eligibility criteria, they had received a provider recommendation for TPT. Finally, narrative comments related to barriers and enablers at each of these steps were collected from each study.

Quality assessment

Two reviewers (MLB and LM) independently assessed risks of bias, and any disagreements were solved through consensus. For observational studies, we adapted the Newcastle–Ottawa Scale for cohorts [13], which included questions related to the ascertainment of exposure and the outcome assessments. We included an additional question related to population selection (S1 Table). For cluster randomized trials, we assessed the risk of bias using the most relevant questions from the Cochrane Risk of Bias tool [14] (S2 Table).

Data analyses

For the quantitative analyses of the cascade-of-care, we considered 2 LTBI management approaches, following WHO algorithms, depending on whether or not programs used LTBI tests to guide treatment [4]. For the first approach, we restricted our analysis to cohorts that did not use LTBI tests to determine TPT eligibility, while in the second approach, we included only cohorts that used LTBI tests (either TST or IGRA). Figs 1 and 2 provide the framework for both approaches and the steps of the cascade-of-care that were analyzed within each.

Meta-analyses

To understand where the losses occurred in both cascade-of-care strategies, we meta-analyzed the proportions of PLHIV completing each step of the cascade-of-care. All proportions were meta-analyzed in R in the package meta (version 4.10–0) [15], using metaprop function. We meta-analyzed using generalized linear mixed models with fixed or random effects with a binomial distribution and logit link; pooled estimates were back transformed into proportions. The cumulative proportion retained in the cascade-of-care was estimated by multiplying the pooled estimated proportion completing each step by the pooled estimated proportion completing the preceding step. The same method was used for the confidence intervals, i.e., the inferior limit of each step was multiplied by the inferior limit of the preceding step, and the superior limit of each step was multiplied by the preceding superior limit. The choice of presenting our main analyses using fixed effect method was due to this method of calculating cascade confidence intervals for cumulative proportions and clearer visual presentation in graphic displays. However, all main meta-analyses using random effect models are presented in the supporting information tables (S1–S11 Tables).

To visually explore the variability of proportion within the cohorts, we generated forest plots of each proportion. As in our primary analyses, we stratified the forest plots by the use or not of LTBI tests.

Stratified analyses

We performed 4 stratified meta-analyses: (1) stratified one the World Bank classification of the countries where the study was performed (high-income versus low- and middle-income) [16]; (2) stratified into cohorts followed in HIV clinics, or followed in any other type of clinic; (3) we restricted to only cohorts that reported data in all steps of the cascade-of-care; and (4) in cohorts that used LTBI tests, we stratified according to the type of LTBI tests used (TST versus IGRA).

Meta-regression

We first meta-analyzed the number of PLHIV completing TPT divided by the number of PLHIV considered eligible for TPT (this was the total number identified if LTBI tests were not used, or the number of PLHIV identified multiplied by the prevalence of positive LTBI test in that cohort). A random effect meta-analysis was performed by fitting generalized linear mixed models with a binomial distribution and logit link; pooled estimates were back transformed into proportions. We used the package meta in R (version 4.10–0) [15], using metaprop function.

We then conducted 3 meta-regression models, each with one of the following 3 variables: (i) use of LTBI tests (used or not); (ii) income setting (high-income versus low- and middle-income); and (iii) type of service offering TPT (HIV-specific services versus other services). We interpreted the variable as significantly associated with TPT completion if the p-value was less than 0.05. We used the package meta in R (version 4.10–0) [15], using metareg function.

Narrative synthesis

Finally, to understand why losses and retentions occurred in different steps of the cascade-of care, we extracted from the included papers the enablers and barriers of the cascade-of-care. We linked these barriers/facilitators to each step of the cascade as they were reported by the original manuscripts. If a manuscript reported several steps of the cascade and did not specify in which step the facilitator/barrier were important, we classified as multistage.

Results

As shown in Fig 3, 2,649 titles were identified in our updated search. Among them, 271 full texts were screened for eligibility, and we included 51 studies. In addition, we identified 6 studies from the previous cascade-of-care systematic review, and 12 more studies were identified from other systematic reviews or reference lists of included studies. No manuscript was excluded on the basis of language criteria. In total, 69 studies [17–85] were included. Of the 69 studies, 2 reported more than one cohort [17,76], yielding 71 cohorts. Among those, 70 cohorts were meta-analyzed, comprising 94,011 PLHIV. One manuscript [85] not included in the meta-analyses reported national data from 16 low- and middle-income countries, supported by the US President’s Emergency Plan for AIDS Relief (PEPFAR). Due to the particularity of financial support (which might not reflect the reality of the other cohorts), the large study populations (over 1.8 million PLHIV starting TPT), and limited other information to characterize these cohorts, we summarized the PEPFAR outcomes separately.

Table 1 summarizes the main characteristics of the cohorts included in the meta-analyses. Sixty-eight (97%) cohorts were observational studies, and the 2 remaining cohorts were derived from an RCT [76]. Sixty-two cohorts reported the type of clinic where PLHIV were evaluated for TPT, and 40 (64%) of these cohorts were seen in HIV clinics. Twenty-one cohorts [17,66–79] did not use LTBI tests, while 49 cohorts [17–55] used LTBI tests; 22 used only TST, 12 used only IGRA, and 15 used either IGRA or TST. Among the 56 (80%) studies that reported the type of TPT regimen, mono-isoniazid regimens were the primary regimen prescribed in 50 cohorts (89%), and only one (2%) of the included cohorts primarily prescribed rifamycin-based short regimens (3 to 4 months of rifampicin and isoniazid) [29]. Additional details on the included studies are reported in S3–S5 Tables.

Table 1. Summary of cohorts included in the meta-analyses (N = 70)¹.

Factor/Parameter	Cohorts, (N, %)	Participants (N, %)²
Overall	70 (100.0%)	94,011 (100.0%)
Population
Children	3 (4.3%)	53,538 (56.9%)
Adults	35 (50.0%)	24,431 (26.0%)
Both	20 (28.6%)	1,048 (1.1%)
Unclear	12 (17.1%)	14,994 (15.9%)
Study design
Cluster RCT³	2 (2.9%)	3,024 (3.2%)
Cross-sectional	7 (10.0%)	17,955 (19.1%)
Pre-post study	1 (1.4%)	1,395 (1.5%)
Prospective cohort	38 (54.3%)	38,518 (41.0%)
Retrospective cohort	22 (31.4%)	33,119 (35.2%)
Country by World Bank definition⁴
High-income	25 (35.7%)	46,340 (49.3%)
Low- and middle-income	44 (62.9%)	46,903 (49.9%)
WHO regions	(100.0%)
Africa	21 (30.0%)	27,460 (29.2%)
America	18 (25.7%)	33,139 (35.3%)
Europe	13 (18.6%)	21,198 (22.5%)
Southeast Asia	4 (5.7%)	1,905 (2.0%)
Western Pacific	14 (20.0%)	10,309 (11.0%)
Type of care
HIV clinic	40 (57.2%)	67,176 (71.5%)
TB clinic	4 (5.7%)	408 (0.4%)
Mixed HIV/TB care (majority primary clinics offering TB/HIV services)	10 (14.3%)	12,645 (13.5%)
Other (specific population, e.g., prisons, PWID users)	8 (11.4%)	8,558 (9.1%)
Unclear	8 (11.4%)	5,224 (5.6%)
Used LTBI tests (N = 49)
IGRA or TST	15 (30.6%)	24,000 (36.2%)
Only IGRA	12 (24.5%)	6,497 (9.8%)
Only TST	22 (44.9%)	35,722 (53.9%)
Did not use LTBI tests (N = 21)
Only symptoms screen	16 (76.2%)	22,757 (81.9%)
Symptoms screened AND chest X-ray (or other diagnostic tests)⁵ for eligibility of TPT	2 (9.5%)	1,813 (6.5%)
Not clear if used additional tests	3 (14.3%)	3,222 (11.6%)
LTBI regimen used
Isoniazid regimen	50 (71.4%)	76,547 (81.4%)
3 months of rifampin and isoniazid⁶	1 (1.5%)	304 (0.3%)
Mainly isoniazid regimen but fewer patients used other regimens (RBT-PZA, Rif-PZA, RIF-INH-PZA)⁷	5 (7.1%)	8,973 (9.5%)
Not specified	14 (20.0%)	8,187 (8.7%)

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¹PEPFAR report [85] not included in this table.

²Denominator is the overall population; N = 94,011.

³One RCT stratified in 2 cohorts.

⁴One multicenter study, in different countries, with different income classification, not included here.

⁵One study used Xpert regardless the presence of symptoms, and other study used chest X-ray regardless the symptoms.

⁶92% cohort used 3 months of isoniazid and rifampin.

⁷More than 80% of patients of these cohorts used isoniazid regimen.

IGRA, interferon release gamma assay; INH, isoniazid; LTBI, latent tuberculosis infection; N, Number; PEPFAR, President’s Emergency Plan for AIDS Relief; PWID, persons who inject drugs; PZA, pyrazinamide; RBT, rifabutin; RCT, randomized clinical trial; RIF, rifampin; TB, tuberculosis; TPT, tuberculosis preventive therapy; TST, tuberculin skin test; WHO, World Health Organization.

Demographic and clinical information by cohort is shown in S5 Table. Age was reported in 37 (52%) cohorts, and the median age was 38.0 [interquartile range (IQR), 34.0;43.6]. Sex was reported in 59 (84%) cohorts, and 65.9% (46,328 /70,297) were men. CD4 cell count was reported in 31 (44%) cohorts, and the median count was 390 cell/mm3 (IQR 312;458). Fifty-three (76%) cohorts reported the use of ART with 43.6% (29,629/67,947) of PLHIV being treated with ART.

S1A Fig shows the quality assessment, and S1B Fig lists the evaluation of the 68 observational studies. For population selection, 67% (46/68) of studies were classified as high risk of bias, most (41/68; 60%) due to the use of convenience sampling or because the sampling method was not described. For outcome ascertainment, 16% (11/68) of studies were classified as either high or unclear risk of bias. For exposure ascertainment, 13% (9/68) of studies did not report this information. Only one study was a cluster RCT [76], and in all domains evaluated, it was classified as low risk of bias.

In the cascade-of-care analyses, all the cohorts that did not use LTBI tests prior to treatment initiation were in low- and middle-income countries (Tables 2 and S6). Out of all PLHIV identified, the cumulative proportion starting and completing TPT was 40.9% (95% CI: 39.3% to 42.7%) and 33.2% (95% CI: 31.6% to 34.9%), respectively. The main losses occurred at the step of provider recommendation of TPT (pooled estimate of 66.2%, representing a loss of 33.8%). Among cohorts that used LTBI tests (Tables 2 and S7), the cumulative proportion of PLHIV starting and completing TPT was 60.4% (95% CI: 58.1% to 62.6%) and 41.9% (95% CI:39.6% to 44.2%), respectively. For these cohorts, the main losses were in the provider recommendation of TPT and completion of TPT. Using random effect model, the main losses (S8 Table) remained in the same steps; however, the cumulative proportion of patient completing TPT was 54.0% (95% CI: 12.6% to 76.9%) among cohorts that did not receive LTBI tests and 60.3% (95% CI:37.7% to 75.0%) among cohorts that received LTBI tests.

Table 2. Pooled estimate for each step of the cascade-of-care¹ (pooled using fixed effect model).

	All cohorts				Cohorts that reported all cascade-of-care steps
Steps	Cohorts	n/N	Pooled estimate (95 CI%)	Pooled estimate (95 CI%) of cumulative percentage retained in the cascade	Cohorts	Calculated cumulative percentage retained in the cascade (95 CI%)²
Did not use LTBI tests (n = 21 cohorts) ³
Proportion 1: Had a medical evaluation/Identified	15	10,806/13,552	79.7% (95% CI: 79.1% to 80.4%)	79.7% (95% CI: 79.1% to 80.4%)	6	76.1% (95% CI: 75.0% to 77.2%)
Proportion 2: Recommended TPT/med evaluation	10	5,464/7,040	77.6% (95% CI: 76.6% to 78.6%)	61.8% (95% CI: 60.6% to 63.2%)	6	59.1% (95% CI: 57.3% to 60.9%)
Proportion 3: Started TPT/Recommended TPT	10	3,259/4,922	66.2% (95% CI: 64.9% to 67.5%)	40.9% (95% CI: 39.3% to 42.7%)	6	44.3% (95% CI: 42.1% to 46.6%)
Proportion 4: Completed TPT treatment/Started TPT	13	8,064/9,937	81.2% (95% CI: 80.4% to 81.9%)	33.2% (95% CI: 31.6% to 34.9%)	6	32.4% (95% CI: 30.0% to 34.9%)
Used LTBI tests (n = 49 cohorts)
Proportion 1: Initiated LTBI testing/Identified	34	30,813/35,201	87.5% (95% CI: 87.2% to 87.9%)	87.5% (95% CI: 87.2% to 87.9%)	8	68.8% (95% CI: 67.7% to 70.0%)
Proportion 2: Completed LTBI testing/initiated LTBI test	37	32,899/34,447	95.5% (95% CI: 95.3% to 95.7%)	83.6% (95% CI: 83.1% to 84.1%)	8	63.6% (95% CI: 62.0% to 65.2%)
Prevalence of LTBI positive: Tests positive/completed test	47⁴	10,131/55,587	18.2% (95% CI: 17.9% to 18.5%)	-		-
Proportion 3: Medical evaluation completed/Needed medical evaluation	31	2,839/2,881	98.5% (95% CI: 98.0% to 98.9%)	82.3% (95% CI: 81.4% to 83.2%)	8	63.6% (95% CI: 61.0% to 65.1%)⁵
Proportion 4: Recommended TPT/Medical evaluation completed	24	2,308/2,714	85.0% (95% CI: 83.6% to 86.3%)	70.0% (95% CI: 68.1% to 71.8%)	8	54.3% (95% CI: 50.8% to 56.8%)
Proportion 5: Started TPT/Recommended LTBI treatment	23	4,583/5,313	86.3% (95% CI: 85.3% to 87.2%)	60.4% (95% CI: 58.1% to 62.6%)	8	49.5% (95% CI: 48.2% to 55.2%)
Proportion 6: Completed TPT/Started TPT treatment	23	3,762/5,419	69.4% (95% CI: 68.2% to 70.6%)	41.9% (95% CI:39.6% to 44.2%)	8	35.0% (95% CI: 32.8% to 40.6%)

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¹Pooled using fixed effect model.

²This value is the product of the cumulative percentage from the preceding step, multiplied by the pooled estimate from this step.

³All cohorts from low- to middle-income countries.

⁴Among 49 cohorts, 47 reported the positivity rates of LTBI tests.

⁵Confidence intervals estimated using inverse method.

CI, confidence interval; LTBI, latent tuberculosis infection; N, Number; TPT, tuberculosis preventive therapy.

To explore possible reporting bias among studies reporting only a limited number of steps of the cascade-of-care, we analyzed the cohorts that reported data for all steps. Similar results were found with a cumulative TPT completion rate of 32.4% (95% CI: 30.0% to 34.9%) among cohorts that did not use LTBI tests to determine TPT eligibility and 35.0% (95% CI: 32.8% to 40.6%) among cohorts that used these tests (Table 2). Using random effect model among cohorts that reported all steps, the cumulative proportion of patients completing TPT was 42.6% (95% CI: 2.6% to 74.5%) among cohorts that did not receive LTBI tests and 53.1% (95% CI: 18.4% to 79.9%) among cohorts that received LTBI tests (S8 Table).

To explore the variability in the estimates of losses at different steps, we generated forest plots (S2 and S3 Figs). The variability between studies was high in all proportions presented, regardless of the use of LTBI tests.

Among the cohorts that used LTBI tests, 25 cohorts were from high-income countries, 23 were from low- and middle-income countries, and one multicenter cohort included sites from both settings [40]. The pooled prevalence of LTBI was 13.2% in cohorts from high-income countries, and 26.2% within low- and middle-income countries. When comparing the 2 settings, the losses occurred in different steps over the cascade-of care, but, consistently, the step with the greatest losses was TPT completion (Table 3). The cumulative proportion of patients completing TPT were similar in high- and low- and middle-income countries, 37.9% (95% CI: 34.1% to 41.2%) and 42.9% (95% CI: 39.8% to 45.9%), respectively (Table 3). Using random effect model (S9 Table), the cumulative proportion of patients completing TPT in high- and low- and middle-income countries were 43.7% (95% CI: 17.6% to 66.0%) and 72.4% (95% CI: 9.2% to 89.1%), respectively.

Table 3. Pooled estimate for each step of the cascade in cohorts that used LTBI tests, stratified by country income level¹ (pooled using fixed effect model).

Steps	Cohorts	n/N	Pooled estimate	Calculated cumulative percentage retained in the cascade (95 CI%)²
High-income countries (N = 25 cohorts)
Proportion 1: Initiated LTBI testing/Identified	19	23,239/26,288	88.4% (95% CI: 88.0% to 88.8%)	88.4% (95% CI: 88.0% to 88.8%)
Proportion 2: Completed LTBI testing/initiated LTBI test	19	22,778/23,239	98.0% (95% CI: 97.8% to 98.2%)	86.9% (95% CI: 86.1%. to 87.2%)
Prevalence of LTBI test positive: Positive/completed test	24	4,551/34,506	13.2% (95% CI: 12.8% to 13.6%)	-
Proportion 3: Medical evaluation completed/Needed medical evaluation	17	750/763	98.3% (95% CI: 97.1% to 99.0%)	85.4% (95% CI: 83.6% to 86.2%)
Proportion 4: Recommended TPT/Medical evaluation completed	11	570/641	88.9% (95% CI: 86.3% to 91.1%)	75.9% (95% CI: 72.1% to 78.6%)
Proportion 5: Started TPT/Recommended LTBI treatment	11	1,486/1,666	89.2% (95% CI: 87.6% to 90.6%)	67.7% (95% CI: 63.2% to 71.3%)
Proportion 6: Completed TPT/Started TPT	12	1,375/2,461	55.9% (95% CI: 53.9% to 57.8%)	37.9% (95% CI: 34.1% to 41.2%)
Low- and middle-income countries (N = 23 cohorts)
Proportion 1: Initiated LTBI testing/Identified	14	6,806/8,145	83.6% (95% CI: 82.7% to 84.3%)	83.6% (95% CI: 82.7% to 84.3%)
Proportion 2: Completed LTBI testing/initiated LTBI test	17	9,463/10,440	90.6% (95% CI: 90.1% to 91.2%)	75.7% (95% CI: 74.5% to 76.9%)
Prevalence of LTBI test positive: Positive/completed test	22	5,341/20,423	26.2% (95% CI: 25.6% to 26.8%)	-
Proportion 3: Medical evaluation completed/Needed medical evaluation	14	2,089/2,118	98.6% (95% CI: 98.0% to 99.0%)	74.7% (95% CI: 73.0% to 76.1%)
Proportion 4: Recommended TPT/Medical evaluation completed	13	1,738/2,073	83.8% (95% CI: 82.2% to 85.4%)	62.6% (95% CI: 60.0% to 65.0%)
Proportion 5: Started TPT/Recommended LTBI treatment	12	3,097/3,647	84.9% (95% CI: 83.7% to 86.0%)	53.1% (95% CI: 50.2% to 55.9%)
Proportion 6: Completed TPT/Started TPT	11	2,387/2,958	80.7% (95% CI: 79.2% to 82.1%)	42.9% (95% CI: 39.8% to 45.9%)

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¹Pooled using fixed effect model. One multicenter study, in different countries with different income classification, not included in these analyses since the cascade steps were not reported by center (Sester and colleagues [40]).

²This value is the product of the cumulative percentage from the preceding step, multiplied by the pooled estimate from this step.

CI, confidence interval; LTBI, latent tuberculosis infection; N, Number; TPT, tuberculosis preventive therapy.

In the stratified analysis by type of LTBI test performed, the losses in the different steps of the cascade were variable between the cohorts that used TST or IGRA. But, at the end of the cascade-of-care, the cumulative proportion of patients completing TPT was similar as seen in S4 Fig.

Among cohorts that did not receive LTBI tests, the cumulative TPT initiation and completion were similar if PLHIV were followed at HIV clinics or other clinics (S5 Fig). However, among the cohorts that received LTBI tests (S6 Fig), TPT completion was higher among PLHIV that were followed in HIV clinics, compared to other clinics [54.4% (95% CI: 29.1% to 71.5%) versus 52.3% (95% CI 1.3% to 82.9%)].

S10 Table summarizes the results of the PEPFAR program results during the years of 2017 to 2019, in 14 African countries, plus Haiti and Vietnam. All PLHIV that started TPT were receiving ART. A total of 1,805,145 PLHIV started TPT, of whom 59.8% completed it. Kenya, Nigeria, South Africa, and Tanzania were the countries with higher number of PLHIV starting and completing TPT.

As shown in S11 Table, the overall pooled proportion of PLHIV eligible for TPT who completed treatment was 26.5% (95% CI: 18.9% to 35.9%). Use of LTBI tests, country-level income, and type of service were not significantly associated with this outcome, in meta-regression.

Table 4 summarizes enablers reported in 17 studies [18,21,24,38,51,58,66,70–76,78,79,82]. The most common facilitators were related to the initial steps (identification, initial LTBI testing, and completing LTBI testing) and to initiation and completion of TPT. Regardless of the steps, most facilitators were from the health system perspective and included activities such as training healthcare workers about the importance of TPT in PLHIV and proper techniques for injection and reading of TST. Integration of HIV and TPT care was a facilitator for multiple steps in 7 studies [18,38,72,74,76,79,82]. Barriers were reported by 12 studies [18,21,24,34,58,66,70,72,74,78,80,81], primarily at the initial steps of identification and testing and the final steps of initiating and completing TPT. Nonintegrated TB and HIV care was a barrier for at multiple steps [34,81]. Pill burden, fear of adverse events, and stocks out of LTBI drugs were also reported as barriers for starting and completing TPT [18,34,72,74,78].

Table 4. Enablers and barriers for different steps of the cascade-of-care identified in the studies included in the review.

	Enablers (N = 17 cohorts)	Barriers (N = 12 cohorts)
Multistage	• HIV and TPT care integrated [18,38,72,74,76,79,82]	• Fragmentation of care of HIV and TB patients [34,81] • Testing and TPT were implemented by TB programs that were not familiar with the care of HIV patients [66] • Stigma of HIV patients receiving care in TB clinics [72,74] • Lack of information, motivation, and support to HCW [21,80,81] • Too much workload [81]
Identification	• Participation of staff in the design of TPT implementations strategy [70] • Patient education material [70] • HIV testing for household contacts of infectious TB disease [38,71] • Community HCWs initiating contact [71] • TB/HIV care in antenatal care services [73,75] • Creation of a TB/HIV integration officer and a TB screening officer [76] • Task shifting TB screening to primary care [76]	• None Identified
Initial testing	• Theoretical training on TST [18,24] • TST training [18,24,70] • Extra consultation room [18] • TB screening by “lay counselor” [18] • TB screening done by physicians [24] • TB nurse dedicated for administration of TST [24] • TB counseling at the moment of HIV diagnosis [21] • Socials workers who traced and visited patients who missed appointments [21]	• Gaps in infection control: absence of N95 masks and training for HCW not conducted regularly [72] • Establishing a cold chain for TST [24] • HCW confusion between TST and BCG vaccine [24] • HCW has no time to perform TST [70] • HIV test councilors who had limited familiarity with LTBI [21]
Received test results	• Calling patients to return for TST reading [18] • HCW explained when and why patients need to return [58] • Skin tested interpreted in closer facility or at patient’s home or work [58]	• Difficult to motivate patients to return for TST reading [70] • TST that could not be interpreted [34] • Long wait time for patients or inconvenient clinic hours [58] • Travel costs to return to clinics [58] • Absence of work or family duties [58] • Patient not told or did not understand that had to return [58]
Needed medical evaluation	• None identified	• None identified
Medical evaluation	• None identified	• None identified
Recommended TPT treatment	• None identified	• None identified
Started TPT	• Staff training about TPT [51,66] • Patients were informed about adverse event of IPT and disadvantages of stopping treatment [66] • TPT paper tool to facilitate HCWs in charge to prescribe TPT [74] • Clinic received list of patients eligible for TPT [51]	• Counseling patients about TPT is difficult and time consuming [70] • Patients not knowledgeable about TPT [70] • Poor adherence to ART and follow-up [74] • Pill burden [34,74] • Lack of liver function tests at baseline [74] • Fear of side effects [74]
Completed TPT	• Supervision of children who required TPT [79] • Patients could choose model for TPT delivery coordinated with ART refills [78,82]	• Adverse drug reactions—hepatotoxicity in the context of hepatitis B infection and alcohol use [18] • Neuropathy developing in the context of INH use and vitamin B6 not being prescribed [18] • Supply chain and drug stockouts [72,78] • Follow-up of patients on TPT is difficult and time consuming [70]

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BCG, Bacillus Calmette–Guerin; HCW, health care workers; INH, isoniazid; LFT, liver functions tests; TB, tuberculosis; TPT, tuberculosis preventive therapy; TST, tuberculosis skin test.

Discussion

In this meta-analysis exclusively in PLHIV, we found that cumulative TPT completion was similar in studies that used or did not use LTBI tests and also similar in studies from high- or low- and middle-income income settings, regardless of use of LTBI tests. Despite the losses in multiples stages, overall TPT completion was better than overall completion observed in an earlier review that included multiple at-risk populations [11]. Health system facilitators included training of healthcare workers for TPT, and integration of TB and HIV care, while barriers included fear of adverse events, pill burden, and lack of knowledge among healthcare workers and patients.

Our study has several public health implications. Despite major losses in the cascade-of-care found in our analyses, the overall initiation and completion of TPT among PLHIV was higher than described in a previous systematic review [11]—which evaluated multiple at-risk populations. The differences in the study populations included in these 2 systematic reviews might explain the difference in findings. Our systematic review was exclusively in PLHIV, who are usually already linked to the healthcare system. In the previous systematic review, the main loss (approximately 28%) occurred in the initial identification and linkage to healthcare step [11], likely because the populations in that review were mainly contacts and immigrants, who were not already linked to the healthcare system.

The important losses in the cascade found might be explained by the fragmentation of TB and HIV care. Multiple studies reported that integration of TB and HIV care was an important enabler of TPT [18,38,72,74,76,79,82], while fragmentation of TB and HIV care was identified as an important barrier [34,81]. This suggests that policymakers should work to close the gap between HIV and TB care.

An important finding in our review was that the use of LTBI tests was not a barrier to TPT initiation or completion among cohorts that used them. Cohorts that used IGRA, compared to cohorts tested with TST, had a higher percentage of population in initiating (87% versus 73%) and completing (99% and 89%) these tests, but overall TPT initiation and completion was similar, regardless of type of test used.

Despite the possible lower sensitivity of IGRAs and TST in PLHIV, previous trials and systematic reviews [2,3,5] have shown that PLHIV with positive LTBI tests benefitted most from TPT, since the risk of TB in PLHIV with a positive LTBI test (TST or IGRA) is 11-fold higher than in PLHIV with a negative LTBI test [5]. Interestingly, TPT recommendation and initiation was higher among cohorts that used LTBI tests; this may reflect providers and patients’ beliefs in prescribing and accepting treatment with evidence of a positive test. For these reasons, we suggest that the use of LTBI tests should be encouraged, not only in high-income countries where it is already part of care, but also in low- and middle-income countries, where this review found numerous reports of its successful use. TPT may provide some benefit in high TB incidence settings if all PLHIV are treated without use of LTBI testing [86,87]. However, the use of LTBI tests can identify those most likely to benefit [5], and treatment without prior LTBI testing might expose PLHIV without TB infection to a nontrivial risk of adverse events [88,89]. Furthermore, the healthcare expenditures for drugs, follow-up visits, and tests including those related to AE, to provide TPT to PLHIV who may not benefit from this could be redirected to strengthening the LTBI cascade-of-care in those (with positive LTBI tests) who will benefit more from TPT.

Completing the medical evaluation was considered an important barrier in cohorts that did not use LTBI testing. These cohorts used diagnostic algorithm strategies [4] that rely on symptom screening. However, in the presence of symptoms and/or if the patient is receiving ART, a chest X-ray is recommended before TPT initiation [4]. All these cohorts were from low- and middle-income countries, where chest X-ray services are not commonly accessible. Even where the test is available, the cost often falls on the patient and their family [90] and can be prohibitively expensive. Therefore, the elimination of the financial burden of chest X-rays is essential for TPT scale-up or alternative algorithms using other diagnostic tests to exclude active TB [91,92].

Finally, among the 50 cohorts that provided information on the TPT regimen prescribed, 49 used isoniazid, even though short rifamycin regimens have been available for over 2 decades. TPT completion was low in primary and all stratified analyses, and pill burden and fear of adverse event were reported as barriers for TPT initiation and completion. Certain ART regimens may present drug–drug interactions with rifamycin regimen, especially protease inhibitors. This could explain the lower prescription of rifamycin short regimens by the providers. However, non-nucleoside reverse transcriptase inhibitors (such as efavirenz) and the integrase inhibitors—such as raltegravir or dolutegravir (doubling the dose)—can be coadministered with rifamycins [14]. Increase use of shorter rifamycin-based regimens should be considered, as these may improve TPT completion and are safer, cheaper, and at least as effective as isoniazid regimens [93–99].

This systematic review has a number of limitations. Only 14 of the included cohorts reported all the steps of the cascade-of-care. To include a greater diversity of study settings, we included all 71 cohorts in which at least 2 consecutive cascade steps were reported. This allowed us to calculate the proportion of PLHIV retained in multiple steps of the cascade-of-care from a much larger number of studies, enhancing generalizability. When we compared results of analysis of all cohorts with the 14 studies that included all the steps of the cascade-of-care, results were very similar. Barriers and facilitators were not systematically reported in all included cohorts, so we could not fully understand why the losses and/or retention occurred at each cascade step. All but one of the studies were observational and mostly used convenience sampling or did not describe the population selection. Hence, the majority of studies were judged to have potential selection bias. As a result, we consider the overall quality of evidence to be low, limiting inferences from our findings. Only 3 studies focused exclusively on children, so the pediatric TPT cascade-of-care could not be assessed.

The strengths of this review include the large number of cohorts meta-analyzed (N = 70) and the large population of PLHIV (N = 94,011), which allowed us to perform more detailed stratified analyses including country income level, use of LTBI tests, type of LTBI test, and type of clinic. We also evaluated cohorts from different countries, with a wide range of socioeconomic status and resource availability, enhancing the generalizability of our findings.

Conclusions

In conclusion, TPT initiation and completion were higher in PLHIV than previously reported for other at-risk populations. Linkage to the health system, clear and consistent evidence from multiple randomized trials of the benefits of TPT, and consistent recommendations by international and national public health authorities might explain this degree of relative success. These lessons should be applied in other groups, particularly in household contacts. Despite this, our analysis of the LTBI cascade-of-care among PLHIV reveals continued important losses. Only 40% of PLHIV eligible for TPT completed this, which is much lower than other care targets in HIV, such as the famous “90-90-90” [100]. Therefore, continued efforts are needed to further improve the LTBI cascade-of-care in this population.

Supporting information

S1 PRISMA Checklist. PRISMA checklist for reporting systematic reviews and meta-analyses.

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Click here for additional data file.^{(28.9KB, docx)}

S1 Search Strategy. Search Strategy (Medline Ovid and LILACS).

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S1 Table. Quality assessment tool used in review for observational studies (adapted from Newcastle–Ottawa Scale).

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S2 Table. Quality assessment tool used in review for cluster randomized trials (adapted from Cochrane RoB tool).

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S3 Table. Summary of design features of the studies included in the review.

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Click here for additional data file.^{(157KB, docx)}

S4 Table. Characteristics of participants in the studies included in the review.

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S5 Table. Number and clinical characteristics of participants in the studies included in the review.

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S6 Table. Number of participants in each step of the cascade-of-care among studies that did not use LTBI tests.

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S7 Table. Number of participants in each step of the cascade-of-care among studies that used LTBI tests.

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S8 Table. Sensitivity analysis.

Pooled estimate for each step of the cascade-of-care, using random effect model.

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S9 Table. Sensitivity analysis table.

Pooled estimate for each step of the cascade in cohorts that used LTBI tests, stratified by country income level¹ random effect model.

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S10 Table. Summary results of the report US President’s Emergency Plan for AIDS Relief, 2017–2019 (PEPFAR) Tuberculosis Preventive Treatment Scale-Up Among Antiretroviral Therapy Patients.

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S11 Table. Meta-regression of patients completing TPT over PLHIV identified.

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S1 Fig. Quality assessment of the studies included in the review.

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S2 Fig. Forest plots among studies that did not use LTBI tests.

LTBI, latent tuberculosis infection; TPT, tuberculosis preventive therapy.

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S3 Fig. Forest plots among studies that used LTBI tests.

LTBI, latent tuberculosis infection; TPT, tuberculosis preventive therapy.

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S4 Fig. Cumulative proportion of each step of the cascade among cohorts that did not use LTBI test stratified by type of clinic where PLHIV were evaluate.

Pooled using fixed effect model. IGRA, interferon gamma release assay; LTBI, latent tuberculosis infection; PLHIV, people living with HIV; TPT, tuberculosis preventive therapy; TST, tuberculin skin test.

(DOCX)

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S5 Fig. Cumulative proportion of each step of the cascade among cohorts that used LTBI test stratified by type of clinic where PLHIV were evaluated.

Pooled using fixed effect model. LTBI, latent tuberculosis infection; PLHIV, people living with HIV.

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S6 Fig. Cumulative proportion of each step of the cascade among cohorts that used LTBI test stratified by type of clinic where PLHIV were evaluated (N = 49 cohorts).

Pooled using fixed effect model. LTBI, latent tuberculosis infection; PLHIV, people living with HIV; TPT, tuberculosis preventive therapy.

(DOCX)

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S1 Data. Data used to perform the meta-analyses.

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Abbreviations

ART: antiretroviral therapy
IGRA: interferon gamma release assay
IQR: interquartile range
LTBI: latent tuberculosis infection
PEPFAR: President’s Emergency Plan for AIDS Relief
PLHIV: people living with HIV
RCT: randomized clinical trial
TB: tuberculosis
TPT: tuberculosis preventive therapy
TST: tuberculin skin test

Data Availability

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

Funding Statement

This work was funded by the Bill & Melinda Gates Foundation (Grant Number INV-003634). The initial study questions for the papers included in the PLOS Collection were drafted together with input from staff of the Bill & Melinda Gates Foundation, but they had no further role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS Med. doi: 10.1371/journal.pmed.1003703.r001

Decision Letter 0

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6 Jan 2021

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PLoS Med. doi: 10.1371/journal.pmed.1003703.r002

Decision Letter 1

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17 Feb 2021

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Requests from the editors:

Please resubmit your article as a "Research article" (which is standard for systematic reviews and meta-analyses at PLOS Medicine), and we will assign an academic editor to the paper upon resubmission.

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Comments from the reviewers:

*** Reviewer #1:

[See attachment]

Michael Dewey

*** Reviewer #2:

PMEDICINE-D-20-06012R1

Overall summary of critique

Bastos et al. present a well conducted systematic review and meta-analysis evaluating the cascade of latent TB (LTBI) care in PLHIV. This is provides important data to quantify the gaps in care with additional nuance regarding the outcomes with and without the use of LTBI tests. My main points of critique are that the authors should provide more information regarding how they collected data to include in the narrative review (as this could be a separate topic) and about the framing of the conclusion as emphasizing that the outcomes for PLHIV were better than for other high-risk populations because these outcomes remain below target and this risks an implicit judgement that detracts from the need to emphasize the need to close these gaps in this high risk population as well as others. The discussion should also include some of the nuances regarding the imperfect sensitivity of current LTBI testing in PLHIV and limited knowledge re: ART drug interactions with newer shorter regimens.

Reviewer comments by section

Abstract

Line 55-56 - I think this second conclusion sentence should be split in two as think you are saying the use of LTBI testing did not reduce the proportion of eligible PLHIV who completed TPT?

Introduction

Line 77 - please clarify 'never received it' - does this mean did not receive a course of TPT or did not actually initiate TPT?

Methods

Lines 147-148: narrative synthesis methodology requires further information. Currently this appears to be a throwaway comment but it is important to understand how the authors approached data collection to answer this question.

Results

Line 160 - were TST thresholds consistent i.e. always <5mm and were IGRA results always classified as positive only according to the manufacturer's recommendations?

Line 180 - re: main loss being provider recommendation for TPT- did studies always actually measure this/refer to this in the same way? Where does the 31.1% come from (don't see it in Table 2)?

Lines 197-199 - please review phrasing here re: clarity around despite where the losses occurred?

Discussion

Line 222- would include HIV in first sentence and currently it is a bit vague - do you mean better than the overall rate observed as per the Alsdurf review or for the subgroup with HIV? I think this refers to the former but see comment re: overall conclusion. I think framing should be although considerably better than for other high risk groups, analysis of the LTBI cascade of care for PLHIV reveals large gaps at multiple stages. This is important because there is generally greater consensus and support for TPT in PLHIV and despite this the outcomes do not reach targets.

Lines 227- suggest more discussion of the study findings prior to discussing limitations i.e. would bring other paragraphs (from line 249 onwards) earlier

Lines 224-226- while these findings are important, should clarify that this was not the primary purpose of the review (or was this in the protocol)? Would suggest having some additional context by first citing data from your quantitative findings first to highlight major gaps being TPT being recommended and then completed.

Line 242- again here you are comparing PLHIV to the entire population offered TPT in the earlier review so language should be clear about this as PLHIV are more likely to have additional support services/counseling re: importance of TPT (as you specify in the next sentence) so important to clarify that you are not referring to a comparison between the same populations.

Lines 262-267 - need to acknowledge the limitations (imperfect sensitivity) of these tests in PLHIV given reliance on immune response

Lines 268-270 - this contradicts what you say in the abstract re: use of LTBI testing did not reduce proportion of people who completed TPT?

Lines 279-284- need to comment on ART drug interactions that may limit use of rifamycins and highlight that clinician training is needed re: safety of shorter regimens with certain ART regimens

Lines 286-287 - Is this really the conclusion the authors want to draw? Average 50% treatment initiation is still not high and below treatment targets. Suggest instead that conclusion should be along the lines of 'TPT initiation and completion in PLHIV fall short of global targets but are higher than observed for other high-risk populations'? We need to be more ambitious as a TB community so drawing the comparison to other data that demonstrates massive unacceptable gaps does not help to drive our ambition to do better.

Table 1

Replace IDU with PWID

Table 4

Re: staff training (enabler) and counseling as time consuming (barrier) - to confirm, this was for TPT initiation but did not pertain to TPT recommendation?

*** Reviewer #3:

Thank you for the opportunity to read this submission.

1. This piece was a remarkable compilation of data. The analysis of bias was remarkable for the effort but not clear how it eliminated or improved your ability to improve a programs impact.

2. The inability to understand who was excluded in the studies dilutes your ability to understand the external validity of your findings.

3. The "care cascade" has its greatest utility at the individual level (single patient), at the clinic site or system level where you can take the findings of your cascade and identify where you need to strengthen your system, i.e, identification, entry and retention. If it is not applied to specific sites it has limited utility as a management tool to direct resources to problems that are contributing to your outcome. As you move into provincial and national data aggregation you dilute the ability to apply corrective interventions along the cascade because your data is aggregated. With aggregated data the ability to locate the barriers to ID, Testing, Initiation TPT, Completion of TPT etc, are precluded and remain disarticulated facts with no place to point the corrective action, to strengthen the cascade.

4. the Rif vs INH discussion seemed disconnected from data presented and conclusions

*** Reviewer #4:

In this article the author evaluates the proportion of people living with HIV completing the tuberculosis preventive therapy, assessing the cascade of care, as well as the use of tests to detect the presence of latent tuberculosis infection as part of the cascade and compared similarities in high and low-middle income countries, identifying barriers and facilitators for retention.

This review to be the first specifically looking at the cascade of TPT in PLHIV, and the use of the network meta-analysis methodology is also novel, as prior reviews have conducted more traditional meta-analyses. A major advantage of the network meta-analysis is that this methodology exploits all available direct and indirect evidence. It yields more precise estimates of the intervention effects in comparison with a single direct or indirect estimate and can provide information for comparisons between pairs of interventions that have not been compared directly within an individual randomized trial (indirect comparisons). This method uses the intervention effects from each group of randomized trials and therefore preserves within-trial randomization. Also, the simultaneous comparison of all interventions of interest in the same analysis enables the estimation of their relative ranking for a given outcome. As such, this is an important strength of the manuscript. The manuscript is very well organized and clearly written.

A few points need revision:

1- In abstract, line 54, conclusion: Please rephrase for clarity: "Completion was similar in high and low-middle countries, and in low-middle income countries and the use of LTBI testing did not reduce the proportion of eligible PLHIV who completed TPT."

2- In order to most properly follow the PRISMA statement, the objective of the systematic review needs further revision, to include the cascade of care participants, interventions, comparisons, and specific outcomes of interest used to identify the articles of interest.

3- In Results, page 160, the sentence "either IGRA or TST (IGRA or TST)" is redundant, please check.

4- Despite results reported in this meta-analysis that by design is restricted to PLHIV are better than those reported for the broader population, it is very important to highlight these results in the context of a still fragmented TB-treatment and prevention service provision, which certainly negatively impact these results, despite the fact that the authors cite that PLHIV are already linked to care.

5- In Table 2, there is a typo ("cohor") that needs correction.In the Discussion, please consider including the strength of evidence for each recommendation or outcome.

6- In the discussion, the authors mention that an important finding in this review was that the use of LTBI tests was not a barrier to TPT initiation or completion among cohorts that used them, and that TPT recommendation and initiation was higher among cohorts that used LTBI tests, and suggest that the use of LTBI tests should be encouraged, not only in high income country where it is already part of care, but also in low and middle-income countries, where this review found numerous reports of its successful use. They also mention that LTBI treatment without prior LTBI testing will expose a substantial proportion of PLHIV to a nontrivial risk of adverse events without evidence of the benefit of TPT. These points need to be put in context considering that published manuscripts not necessarily translate programmatic data. Therefore, taking into account the great utility this review will have from a public health perspective, it is recommended the review of this statement, not to bring the impression that we are currently following guidance that may be harmful to patients, what isn't at all the case.

7- I suggest to include a paragraph on the most recent trials with shortened course LTBI which will most probably impact the later stages of the cascade, with higher % of finishing the prophylaxis course, although the earlier cascade steps are under the same constrains.

***

Any attachments provided with reviews can be seen via the following link:

[LINK]

Attachment

Submitted filename: bastos.pdf

Click here for additional data file.^{(65KB, pdf)}

PLoS Med. 2021 Sep 7;18(9):e1003703. doi: 10.1371/journal.pmed.1003703.r003

Author response to Decision Letter 1

31 Mar 2021

Attachment

Submitted filename: Cascade TPTinHIV ResponsetoReviewers.docx

Click here for additional data file.^{(39.9KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1003703.r004

Decision Letter 2

Richard Turner

11 Jun 2021

Dear Dr. Menzies,

Thank you very much for re-submitting your manuscript "The Latent Tuberculosis Cascade-of-Care Among People Living with HIV: A Systematic Review and Meta-Analysis" (PMEDICINE-D-20-06012R2) for consideration at PLOS Medicine.

I have discussed the paper with editorial colleagues and our academic editor, and it was also seen again by two reviewers. I am pleased to tell you that, provided the remaining editorial and production issues are fully dealt with, we expect to be able to accept the paper for publication in the journal.

The remaining issues that need to be addressed are listed at the end of this email. Any accompanying reviewer attachments can be seen via the link below. Please take these into account before resubmitting your manuscript:

[LINK]

In revising the manuscript for further consideration here, please ensure you address the specific points made by each reviewer and the editors. In your rebuttal letter you should indicate your response to the reviewers' and editors' comments and the changes you have made in the manuscript. Please submit a clean version of the paper as the main article file. A version with changes marked must also be uploaded as a marked up manuscript file.

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Please let me know if you have any questions, and we look forward to receiving the revised manuscript shortly.

Sincerely,

Richard Turner, PhD

Senior Editor, PLOS Medicine

rturner@plos.org

------------------------------------------------------------

Requests from Editors:

Please resubmit your paper as a research article.

Please quote the date(s) of the new search in the abstract.

To the abstract, we suggest adding a sentence, say, quoting the proportion of participants in low- and middle-income countries, and broken down by WHO region.

We also suggest adding a sentence to summarize participants' age, sex, and CD4 and ART status.

In the abstract and throughout the text, please quote p values alongside 95% CI, where available.

Please remove the information about study funding from the abstract. In the event of publication, this information will appear in the article metadata, via entries in the submission form.

At lines 80/81, we suggest quoting both numbers to one decimal place.

At line 221, please make that "1.8 million".

Please use the style "low- and middle-income" throughout.

Please use the journal name abbreviation "PLoS ONE" consistently in the reference list.

Are references 14 and 57-65 missing journal names?

Please rename the attached PRISMA checklist "S1_PRISMA_Checklist" or similar and refer to it by this label at line 116.

Comments from Reviewers:

*** Reviewer #1:

The authors have addressed all my points.

Michael Dewey

*** Reviewer #2:

PMEDICINE-D-20-06012_R2

The authors have responded thoughtfully and appropriately to the critiques I and the other reviewers raised and accordingly present a strengthened manuscript, which includes an updated search and additional studies as well as revisions that have improved the clarity and messaging of the manuscript. I thus do not have major recommendations to offer at this stage. I would however suggest that the authors consider adding text in the abstract and author summary conclusions that note that TPT recommendation and initiation was higher among cohorts that used LTBI tests. For example, they could add something to the effect of the following clause (in bold) in the author's conclusion: 'Although TPT recommendation and initiation was higher among cohorts that used LTBI tests, the use of LTBI testing did not reduce the proportion of eligible PLHIV who completed TPT.' The rationale for this suggestion is that this paper may have important policy implications and it is otherwise possible that it could be interpreted that LTBI testing should not be scaled up in LMICs, which is not in accordance with the author's suggested recommendations. Otherwise, the manuscript needs a careful review by the authors to correct a few minor typos but overall represents an important addition to the literature on this topic.

***

Any attachments provided with reviews can be seen via the following link:

[LINK]

PLoS Med. 2021 Sep 7;18(9):e1003703. doi: 10.1371/journal.pmed.1003703.r005

Author response to Decision Letter 2

16 Jun 2021

Attachment

Submitted filename: Cascade TPTinHIV ResponsetoReviewers_R2.docx

Click here for additional data file.^{(17KB, docx)}

PLoS Med. doi: 10.1371/journal.pmed.1003703.r006

Decision Letter 3

Richard Turner

20 Jun 2021

Dear Dr Menzies,

On behalf of my colleagues and our Academic Editor, I am pleased to inform you that we have agreed to publish your manuscript "The Latent Tuberculosis Cascade-of-Care Among People Living with HIV: A Systematic Review and Meta-Analysis" (PMEDICINE-D-20-06012R3) in PLOS Medicine.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. Please be aware that it may take several days for you to receive this email; during this time no action is required by you. Once you have received these formatting requests, please note that your manuscript will not be scheduled for publication until you have made the required changes.

Prior to final acceptance, please check numbers for consistency throughout the paper - we think that the proportion of participants on ART is quoted as 46.3% in the abstract and 44% early in the Results section (the denominators appear to be different).

In the meantime, please log into Editorial Manager at http://www.editorialmanager.com/pmedicine/, click the "Update My Information" link at the top of the page, and update your user information to ensure an efficient production process.

PRESS

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To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. Additionally, PLOS ONE offers an option to publish peer-reviewed clinical study protocols. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols

Thank you again for submitting to PLOS Medicine. We look forward to publishing your paper.

Sincerely,

Richard Turner, PhD

Senior Editor, PLOS Medicine

rturner@plos.org

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

S1 PRISMA Checklist. PRISMA checklist for reporting systematic reviews and meta-analyses.

(DOCX)

Click here for additional data file.^{(28.9KB, docx)}

S1 Search Strategy. Search Strategy (Medline Ovid and LILACS).

(DOCX)

Click here for additional data file.^{(14.2KB, docx)}

S1 Table. Quality assessment tool used in review for observational studies (adapted from Newcastle–Ottawa Scale).

(DOCX)

Click here for additional data file.^{(14.2KB, docx)}

S2 Table. Quality assessment tool used in review for cluster randomized trials (adapted from Cochrane RoB tool).

(DOCX)

Click here for additional data file.^{(14.3KB, docx)}

S3 Table. Summary of design features of the studies included in the review.

(DOCX)

Click here for additional data file.^{(157KB, docx)}

S4 Table. Characteristics of participants in the studies included in the review.

(DOCX)

Click here for additional data file.^{(148.8KB, docx)}

S5 Table. Number and clinical characteristics of participants in the studies included in the review.

(DOCX)

Click here for additional data file.^{(146.3KB, docx)}

S6 Table. Number of participants in each step of the cascade-of-care among studies that did not use LTBI tests.

(DOCX)

Click here for additional data file.^{(50.4KB, docx)}

S7 Table. Number of participants in each step of the cascade-of-care among studies that used LTBI tests.

(DOCX)

Click here for additional data file.^{(117.2KB, docx)}

S8 Table. Sensitivity analysis.

Pooled estimate for each step of the cascade-of-care, using random effect model.

(DOCX)

Click here for additional data file.^{(16.7KB, docx)}

S9 Table. Sensitivity analysis table.

Pooled estimate for each step of the cascade in cohorts that used LTBI tests, stratified by country income level¹ random effect model.

(DOCX)

Click here for additional data file.^{(21.8KB, docx)}

S10 Table. Summary results of the report US President’s Emergency Plan for AIDS Relief, 2017–2019 (PEPFAR) Tuberculosis Preventive Treatment Scale-Up Among Antiretroviral Therapy Patients.

(DOCX)

Click here for additional data file.^{(18.1KB, docx)}

S11 Table. Meta-regression of patients completing TPT over PLHIV identified.

(DOCX)

Click here for additional data file.^{(14.3KB, docx)}

S1 Fig. Quality assessment of the studies included in the review.

(DOCX)

Click here for additional data file.^{(68.7KB, docx)}

S2 Fig. Forest plots among studies that did not use LTBI tests.

LTBI, latent tuberculosis infection; TPT, tuberculosis preventive therapy.

(DOCX)

Click here for additional data file.^{(407.5KB, docx)}

S3 Fig. Forest plots among studies that used LTBI tests.

LTBI, latent tuberculosis infection; TPT, tuberculosis preventive therapy.

(DOCX)

Click here for additional data file.^{(1MB, docx)}

S4 Fig. Cumulative proportion of each step of the cascade among cohorts that did not use LTBI test stratified by type of clinic where PLHIV were evaluate.

(DOCX)

Click here for additional data file.^{(48.5KB, docx)}

S5 Fig. Cumulative proportion of each step of the cascade among cohorts that used LTBI test stratified by type of clinic where PLHIV were evaluated.

Pooled using fixed effect model. LTBI, latent tuberculosis infection; PLHIV, people living with HIV.

(DOCX)

Click here for additional data file.^{(47.6KB, docx)}

S6 Fig. Cumulative proportion of each step of the cascade among cohorts that used LTBI test stratified by type of clinic where PLHIV were evaluated (N = 49 cohorts).

Pooled using fixed effect model. LTBI, latent tuberculosis infection; PLHIV, people living with HIV; TPT, tuberculosis preventive therapy.

(DOCX)

Click here for additional data file.^{(63KB, docx)}

S1 Data. Data used to perform the meta-analyses.

(XLSX)

Click here for additional data file.^{(16KB, xlsx)}

Attachment

Submitted filename: bastos.pdf

Click here for additional data file.^{(65KB, pdf)}

Attachment

Submitted filename: Cascade TPTinHIV ResponsetoReviewers.docx

Click here for additional data file.^{(39.9KB, docx)}

Attachment

Submitted filename: Cascade TPTinHIV ResponsetoReviewers_R2.docx

Click here for additional data file.^{(17KB, docx)}

Data Availability Statement

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

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PERMALINK

The latent tuberculosis cascade-of-care among people living with HIV: A systematic review and meta-analysis

Mayara Lisboa Bastos

Luca Melnychuk

Jonathon R Campbell

Olivia Oxlade

Dick Menzies

Roles

Abstract

Background

Methods and findings

Conclusions

Author summary

Why was this study done?

What did the researchers do and find?

What do these findings mean?

Introduction

Methods

Objectives, search strategy, and selection criteria

Fig 1. Cascade framework used for analysis of cohorts that did not use LTBI tests (N = 21 cohorts).

Fig 2. Cascade framework for analysis of cohorts that used LTBI tests (N = 49 cohorts).

Data extraction

Quality assessment

Data analyses

Meta-analyses

Stratified analyses

Meta-regression

Narrative synthesis

Results

Fig 3. PRISMA flow diagram.

Table 1. Summary of cohorts included in the meta-analyses (N = 70)1.

Table 2. Pooled estimate for each step of the cascade-of-care1 (pooled using fixed effect model).

Table 3. Pooled estimate for each step of the cascade in cohorts that used LTBI tests, stratified by country income level1 (pooled using fixed effect model).

Table 4. Enablers and barriers for different steps of the cascade-of-care identified in the studies included in the review.

Discussion

Conclusions

Supporting information

Abbreviations

Data Availability

Funding Statement

References

Decision Letter 0

Thomas J McBride

Roles

Decision Letter 1

Richard Turner

Roles

Author response to Decision Letter 1

Decision Letter 2

Richard Turner

Roles

Author response to Decision Letter 2

Decision Letter 3

Richard Turner

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Table 1. Summary of cohorts included in the meta-analyses (N = 70)¹.

Table 2. Pooled estimate for each step of the cascade-of-care¹ (pooled using fixed effect model).

Table 3. Pooled estimate for each step of the cascade in cohorts that used LTBI tests, stratified by country income level¹ (pooled using fixed effect model).