Impact of Isoniazid Preventive Therapy on Tuberculosis incidence among people living with HIV: A secondary data analysis using Inverse Probability Weighting of individuals attending HIV care and treatment clinics in Tanzania

Werner M Maokola; Bernard J Ngowi; Michael J Mahande; Jim Todd; Masanja Robert; Sia E Msuya

doi:10.1371/journal.pone.0254082

. 2021 Jul 13;16(7):e0254082. doi: 10.1371/journal.pone.0254082

Impact of Isoniazid Preventive Therapy on Tuberculosis incidence among people living with HIV: A secondary data analysis using Inverse Probability Weighting of individuals attending HIV care and treatment clinics in Tanzania

Werner M Maokola ^1,^2,^*, Bernard J Ngowi ³, Michael J Mahande ², Jim Todd ^4,⁵, Masanja Robert ⁶, Sia E Msuya ²

Editor: Katalin Andrea Wilkinson⁷

PMCID: PMC8277069 PMID: 34255776

Abstract

Background

Information on how well Isoniazid Preventive Therapy (IPT) works on reducing TB incidence among people living with HIV (PLHIV) in routine settings using robust statistical methods to establish causality in observational studies is scarce.

Objectives

To evaluate the effectiveness of IPT in routine clinical settings by comparing TB incidence between IPT and non-IPT groups.

Methods

We used data from PLHIV enrolled in 315 HIV care and treatment clinic from January 2012 to December 2016. We used Inverse Probability of Treatment Weighting to adjust for the probability of receiving IPT; balancing the baseline covariates between IPT and non-IPT groups. The effectiveness of IPT on TB incidence was estimated using Cox regression using the weighted sample.

Results

Of 171,743 PLHIV enrolled in the clinics over the five years, 10,326 (6.01%) were excluded leaving 161,417 available for the analysis. Of the 24,800 who received IPT, 1.00% developed TB disease whereas of the 136,617 who never received IPT 6,085 (4.98%) developed TB disease. In 278,545.90 person-years of follow up, a total 7,052 new TB cases were diagnosed. Using the weighted sample, the overall TB incidence was 11.57 (95% CI: 11.09–12.07) per 1,000 person-years. The TB incidence among PLHIV who received IPT was 10.49 (95% CI: 9.11–12.15) per 1,000 person-years and 12.00 (95% CI: 11.69–12.33) per 1,000 person-years in those who never received IPT. After adjusting for other covariates there was 52% lower risk of developing TB disease among those who received IPT compared to those who never received IPT: aHR = 0.48 (95% CI: 0.40–0.58, P<0.001).

Conclusion

IPT reduced TB incidence by 52% in PLHIV attending routine CTC in Tanzania. IPTW adjusted the groups for imbalances in the covariates associated with receiving IPT to achieve comparable groups of IPT and non-IPT. This study has added evidence on the effectiveness of IPT in routine clinical settings and on the use of IPTW to determine impact of interventions in observational studies.

Background

Tuberculosis (TB) is a common opportunistic infection among people living with HIV (PLHIV) [1, 2]. Despite strategies for control and prevention of TB among PLHIV, co-infection of TB and HIV (TBHIV) is still a public health concern [3–5]. Worldwide in 2018, 862,000 (2.3%) of all PLHIV had TB disease and 30% of all HIV deaths occurred in individuals with TBHIV co-infection [6, 7]. The African continent accounted for 24% of all TB cases diagnosed and was second to Asia in the number of TB cases. Tanzania was ranked among 30 countries in the World with high TB burden [7]. HIV is a known risk for TB especially in the absence of antiretroviral therapy (ART). The burden of TB among PLHIV in Tanzania was reported to 16.7 cases per 1000 person-years [8].

Tanzania adopted World Health Organization (WHO) three I’s strategy which comprises of intensified TB Case Finding (ICF), Isoniazid Preventive Therapy (IPT) and Infection control and prevention in all clinical settings since 2010 [9]. IPT entails giving an anti-TB drug to eligible PLHIV for at least 6 months to treat latent TB infection (LTBI); individuals infected with TB but without TB disease [10, 11]. IPT integration into HIV care and treatment services in Tanzania started in 2011 starting with high level health facilities as a phased implementation to lower level health facilities in 2012, so that 50% of care and treatment clinics (CTC) was implementing IPT by the end of December 2018 [12]. However, routine data from PLHIV attending CTC in 3 regions in Tanzania documented14% had initiated IPT from 2012–2016 [13] whereas the target was to cover a minimum of 50% of clinic attendees [14].

IPT is a proven public health intervention to reduce TB among PLHIV by treating LTBI, thus preventing LTBI from developing into TB disease. A systematic review and meta-analysis from clinical trials have demonstrated a reduction in TB incidence among PLHIV following IPT ranging from 30% to 74% [4, 15–17].

Moreover, in routine clinical settings have shown a reduction in TB incidence of between 48% and 76% in PLHIV receiving IPT [18–21]. These studies conducted in Ethiopia, Tanzania and Brazil but did not address the challenges of using observational studies to establish cause-effect relationship between IPT and TB incidence when IPT is rolled out in routine clinical settings, the baseline characteristics of those initiated on IPT may differ from those who are not initiated on IPT. Propensity scores are one way to obtain an unbiased estimate of the effectiveness of IPT in preventing TB incidence using observational data from routine clinical settings [22]. This paper reports a secondary analysis of a cohort of PLHIV enrolled in CTC from January 2012 to December 2016 in the three regions in Tanzania. We applied Inverse-Probability for Treatment Weighting (IPTW)-one of the propensity score approaches to the data in order to balance baseline characteristics of PLHIV who received and those who never received IPT [23]. This approach obtained an objective estimate of the impact of IPT intervention on TB incidence in using observational data from routine clinical settings where randomization of the intervention is not done.

Methods

Study design and study population

This analysis used routine data from PLHIV enrolled in 315 CTC in three regions of Tanzania from January 2012 to December 2016.

Study setting

More information regarding the HIV care and treatment program in Tanzania, including the integration of the TB services in HIV clinics, has been previously Published [24]. Tanzania has 26 regions and the three regions chosen were among those with the highest HIV prevalence [25]. Since 2012, all health facilities with CTC in Tanzania have implemented ICF and TB infection control and prevention, with IPT incrementally rolled out across Tanzania. During every clinic visit, PLHIV were screened for the presence of TB symptoms and signs as part of ICF. In health facilities where IPT was available, PLHIV who screened TB negative and fulfill other clinical criteria were initiated on IPT for 6 months to treat latent TB. Those who screened positive for TB underwent further TB disease diagnosis using diagnostic tests according the TB diagnosis algorithm [26]. TB infection control and prevention was another intervention to reduced TB among PLHIV and was implemented in all health facilities in the country.

Data collection

Detailed information regarding the demographic and clinical data collected in the Tanzania CTC has been described elsewhere [13, 24, 27]. At every visit to the CTC data were entered into an electronic database which was collated on a central server at national level. Independent variables used in the study namely sex, age, WHO clinical stage, Antiretroviral Therapy (ART) status, nutritional status, weight, height, enrolment year, health facility type and ownership and region where the client was registered were routinely recorded in the database. The database also recorded information on IPT initiation and completion dates and on TB screening and management. This study extracted those demographic and clinical information including those of TB services using the unique patient identification number for linking clinic visits. Any PLHIV who had any evidence of LTBI on the first visit to CTC were excluded from the analysis.

All PLHIV attending CTCs which never implemented IPT throughout the study period was also excluded from the analysis.

Data analysis

The primary exposure was IPT (IPT and non-IPT) use and TB disease incidence was the outcome of interest. “IPT” were individuals who were ever initiated on IPT and outcome of interest “non-IPT” were those who were never initiated on IPT throughout the study period. Sex, age, WHO clinical stage, ART status, Body Mass Index (BMI), functional status, health facility type, health facility ownership, enrolment year and region and were the covariates needed to be adjusted for in the analysis. Characteristics of PLHIV who received IPT and those who never received IPT during the study duration were expressed using unweighted sample. To balance for measured covariates between those who received IPT and those who never received IPT, IPTW was applied. The following steps were followed in creating weighted dataset: (1) Selection of covariates which are potential confounders (affecting both IPT initiation and TB disease diagnosis): Sex, age, functional status, ART status, Body Mass Index (BMI), nutritional status, health facility type, region and health facility ownership (12,19,28) were selected for propensity score model. (2) Creating Propensity scores (probability of receiving IPT condition to covariates): As these covariates differed between those who received IPT and those who never received IPT. Logistic regression was used to calculate propensity score to estimate the odds of receiving IPT. From the propensity scores, IPTW was created for each PLHIV to make a synthetic sample in which IPT and non-IPT groups were balanced.

The treatment effect to be calculated is Average Treatment Effect (ATE). ATE refers to the treatment effect to the entire target population (3) Checking for balance after weighting: The balance between the two groups was determined quantitatively by comparing standardized means and variances of the 2 groups. Weighted sample had standardized difference of closer to zero whereas the variance in the weighted group was closer to 1 compared to unweighted sample, showing covariate balance in the weighted sample [28, 29]. (4) Calculating Propensity Scores weights: From the propensity scores an IPTW was created for each PLHIV and this weight was used to make a synthetic sample in which IPT and non-IPT groups were Balanced. The weighted sample was then used to determine the TB incidence rates and risk factors for developing TB disease. The weighted dataset was used for the survival analysis using TB disease diagnosis as the failure variable. Entry time was the first date seen in the CTC (after 1^st January 2012) and exit time out was TB diagnosis date, or the last clinic visit recorded. TB incidence rates and corresponding 95% Confidence Intervals were calculated by dividing the sum of all TB episodes occurring during follow up and total time contributed by each of the study participant. For individuals who received IPT the time before receipt of IPT was considered “not on IPT” and the time following initiation of IPT considered “on IPT”. Risk factors for developing TB disease among PLHIV were analyzed using regression model. The univariate Cox-regression model contained covariates either known to influence TB diagnosis from previous studies or from clinical experience of the authors. Multivariate regression included covariates with P-values less than 0.2 to obtain adjusted Hazard Ratios (HR) and 95% confidence intervals (95% CI). Multivariate analysis was done to control for possible residual confounding despite IPTW [30]. Cluster effect at the health facility level was checked in the regression model and were not significant. Kaplan Meier graphs for the effect of IPT on TB incidence were drawn to show comparison of TB disease probabilities between those who received IPT and those who did not receive IPT. Stata version 14 (College Station, TX: Stata Corp LP) was used for analysis.

Ethical consideration

To maintain participants’ confidentiality. the study used de-identified routinely collected HIV data. The data was fully de-identified before made accessible. Ethical review and approval was granted by Kilimanjaro Christian Medical College (KCMUCo) Institutional Review Board (IRB) which granted the ethical clearance certificate number 2287. The parent project known as SEARCH was given ethical approval by NIMR with approval number National Institute of Medical Research (NIMR)/HQ/R.8c/Vol.II/961. The submitted manuscript is part of Doctor of Philosophy work within the main project. As the study used de-identified secondary data from routine clinical visits, the need for informed consent from the study participants was waived by both KCMUCo IRB and NIMR ethical approval. Data used for the study can be available for public use in the research repository of London School of Hygiene and Tropical Medicine, United Kingdom. The data can be accessed using the following link: https://www.lshtm.ac.uk/sites/default/files/201706/Tanzania%20CTC%20Documentation.pdf.

Results

(1) Baseline characteristics of study participants

A total of 171,743 PLHIV enrolled in 315 health facilities in Dar es Salaam, Iringa and Njombe regions from January 2012-December 2016. A total of 10,326 (6.01%) study participants were excluded from the analysis as they either had TB disease before CTC enrolment or had TB diagnosed at CTC before follow up or they were from clinics which never implemented IPT throughout the study period. Of the 161,417 who were involved in the analysis, only 1.00% of PLHIV developed TB disease among those who received IPT and 4.98% among those who never received IPT (Fig 1).

Fig 1 — The figure showed only 15.36% of the PLHIV in the study were initiated on Isoniazid Preventive Therapy. When compared, less PLHIV who ever used IPT developed TB disease (1.00%) than those who did not use IPT (4.98%).

Majority of individuals who received IPT were females (71.60%), aged 25–49 years (77.19%), with working functional status (97.51%), in WHO clinical stage III (33.61%) not on ART (72.11%), in individuals with normal BMI (57.76%) and in PLHIV with normal nutritional status (93.81%). IPT initiation was also higher among those enrolled in 2014 (22.75%) Dar es Salaam region (74.72%, enrolled in hospital (49.27%) and enrolled in public health facilities (83.88%) (Table 1).

Table 1. Baseline characteristics of study participants, N = 161,417.

Variable	IPT status
Variable	Never on IPT n = 136,617	Ever on IPT n = 24,800	Total	P-value
Sex
Male	42,409 (31.04%)	7,044 (28.40%)	49,453 (30.63%)	P<0.001
Female	94,208 (68.96%)	17,756 (71.60%)	111,964 (69.36%)	P<0.001
Baseline age	Mean: 33.64 years, SD = 12.44 years, Range: 0–95 years
0–9	6,741(4.93%)	567 (2.29%)	7,308 (4.53%)	P<0.001
10–19	6,458 (4.73%)	739 (2.98%)	7,197 (4.46%)
20–24	13,977 (10.23%)	1,808 (7.29%)	15.785 (9.78%)
25–49	96,848 (70.89%)	19,143 (77.19%)	115, 991 (71.86%)
+ 50	12,593 (9.22%)	2,543 (10.25%)	15,136 (9.38%)
Baseline functional status
Ambulatory	4,222 (3.10%)	475 (1.92%)	4,697 (2.92%)	P<0.001
Bedridden	1,143 (0.84%)	139 (0.56%)	1,282 (0.80%)
Working	130,642 (96.06%)	24,069 (97.51%)	154,711 (96.28%)
Baseline WHO clinical stage
I	52,176 38.70%	8,175 (33.39%)	60,351 (37.89%)	P<0.001
II	32,513 24.12%	6,684 (27.30%)	39,197 (24.61%)
III	40,051 29.71%	8,230 (33.61%)	48,281 (30.21%)
IV	10,073 7.47%	1,398 (5. 71%)	11,471 (7.20%)
Baseline ART status
No ART	85,297 (62.90%)	17,749 (72.11%)	103,046 (64.31%)	P<0.001
ART	50,321 (37.10%)	6,865 (27.89%)	57,186 (35.69%)	P<0.001
Baseline BMI
Underweight	14,806 (17.13%)	2,584 (14.18%)	17,390 (16.61%)	P<0.001
Normal	48,697 (56.33%)	10,524 (57.76%)	59,221 (6.57%)
Overweight	15,598 (18.04%)	3,465 (19.02%)	19,063 (18.21%)
Obesity	7,356 (8.51%)	1,648 (9.04%)	9,004 (8.60%)
Baseline nutritional status
Normal	120,051 (92.35%)	22,438 (93.81%)	142,489 (92.58%)	P<0.001
Moderate	8,501 (6.54%)	1,335 (5.58%)	9,836 (6.39%)
Severe	1,445 (1.11%)	146 (0.61%)	1,591 (1.03%)
CTC enrolment year
2012	24,364 (17.83%)	4,378 (17.65%)	28,742 (17.81%)	P<0.001
2013	26,603 (19.47%)	5,017 (20.23%)	31.620 (19.59%)
2014	28,491 (20.85%)	5,643 (22.75%)	34,134 (21.15%)
2015	26,215 (19,19%)	5,031 (20.29%)	31,246 (19.36%)
2016	30,944 (22.65%)	4,731 (19.08%)	35,675 (22.10%)
Region at enrolment
Dar es Salaam	96,524 (70.65%)	18,556 (74.82%)	115,080 (71.29%)	P<0.001
Iringa	17,216 (12.60%)	1,238 (4.99%)	18.454 (11.43%)
Njombe	22,877 (16.75%)	5,006 (20.19%)	27,883 (17.27%)
Health Facility Type at enrolment
Dispensary	55,932 (40.94%)	6,232 (25.13%)	62,164 (38.51%)	P<0.001
Health Center	36,619 (26.80%)	6,348 (25.60%)	42,967 (26.62%)
Hospital	44,066 (32.26%)	12,220 (49.27%)	56,286 (34.87%)
Health Facility ownership at enrolment
Public	96,211 (70.42%)	20,803 (83.88%)	117,014 (72.49%)	P<0.001
Private	40,406 (29.58%)	3,997 (16.12%)	44.403 (27.51%)	P<0.001

Open in a new tab

95% CI = 95% Confidence Interval, ART = Antiretroviral Treatment, BMI-Body Mass Index, Care and Treatment Clinic, IPT = Isoniazid Preventive Therapy, TB = Tuberculosis, SD = Standard Deviation, WHO = World Health Organization.

(2) Balance of covariates after IPTW

After IPTW, the standardized differences for the weighted sample were closer to zero compared to the unweighted sample. The variances of the different covariates were closer to 1 compared to the variance in the unweighted sample.

(Table 2).

Table 2. Balance between unweighted and weighted samples after Inverse Probability of Treatment Weighting.

Covariate	Standardized Difference		Variance
Covariate	Unweighted sample	Weighted sample	Unweighted sample	Weighted sample
Sex	0.03721	-0.01170	0. 9636	1.0162
Baseline age	0.1489	0.0108	0.7395	0.8963
Baseline functional status	0.8073	-0.0034	0.5981	1.0154
Baseline ART status	-0.2385	-0.0019	0.8344	0.9989
Baseline BMI	0.0559	-0.0130	0.9685	0.9502
Baseline nutritional status	-0.0736	0.0003	0.7400	0.9962
Health Facility type at enrolment	0.3583	0.0056	0.9118	0. 9695
Region at enrolment	0.0147	0.0123	1.2120	1.1355
Health Facility ownership at enrolment	0.2935	-0.0134	0.5677	1.0206

Open in a new tab

ART = Antiretroviral Therapy, BMI-Body Mass Index.

(3) TB cases, follow up time and TB incidence rate

During follow up, a total of 7,052 new TB cases were diagnosed with a total of 278,545.90 person years giving an overall TB incidence rate of 25.32 (95% CI: 21.43–30.31) per 1,000 person-years. Using the weighted sample, an overall TB incidence of 11.57 (95% Confidence Interval (CI): 11.09–12.07) per 1,000 person-years was obtained. PLHIV who received IPT had lower TB incidence rate compared with those who never received IPT: 10.49 (95% CI: 9.11–12.15) per1,000 person-years versus 12.00 per 1,000 (95% CI: 11.69–12.33) per 1,000 person-years respectively. TB incidence rate was also lower higher among females; 9.27(95% CI: 8.76–9.82 per 1,000 person-years compared to males, in PLHIV aged 20–24 years: 6.10 (95% CI: 4.92–7.66) compared to other age groups, in PLHIV with working functional status; 11.27 (95% CI: 10.78–11.78) per 1,000 person-years than in other functional statuses and in those who were on ART: 8.38 (95% CI: 7.45–9.47) per 1,000 person-years compared with those not on ART. TB incidence was also decreased in those with WHO clinical stage I; 6.05 (95% CI:5.34–6.82) per 1,000 person-years compared to higher WHO clinical stages in those who were obese: 4.71 (95% CI: 3.59–6.32) per 1,000 person-years compared to those with other weights, in those with normal nutritional status: 10.83 (95% CI: 10.32–11.37) per 1,000 person-years compared to other groups. TB incidence rate was also decreased in PLHIV enrolled in dispensaries: 10.35 (95% CI: 9.44–11.37) per 1,000 person-years compared to those in other health facility levels, in PLHIV enrolled in care in 2012: 9.20 (95% CI: 8.42–10.06) per 1,000 person-years compared to those in the following years, in those enrolled in Njombe region: 6.45 (95% CI: 5.77–7.25) per 1,000 person-years compared to those registered in other regions and in those enrolled in private health facilities: 10.37 (5% CI:9.24–11.67–10.29) per 1,000 person-years compared to those enrolled in public health facilities (Table 3).

Table 3. The incidence of TB cases, total person-year and TB rates among 24,800 PLHIV who received IPT and a weighted sample of those who did not receive IPT.

Variable	Number of TB cases	Total person-years (Years)	Rate/1,000 (95% CI)
Overall	1,037	89,661	11.57 (11.09–12.07)
IPT status
Never on IPT	765	63,739	12.00 (11.69–12.33)
Ever on IPT	272	25,922	10.49 (9.11–12.15)
Sex
Male	450	26,335	17.10 (16.05–18.23)
Female	587	63,327	9.27 (8.76–9.82)
Baseline age
0–19	105	7,442	14.17 (11.68–17.37)
20–24	45	7,427	6.10 (4.92–7.66)
25–49	764	66,226	11.54 (11.03–12.07)
+50	122	8,566	14.27 (12.69–16.11)
Baseline functional status
Ambulatory	54	2,545	21.06 (18.25–24.35)
Bedridden	9	606	14.68 (9.72–23.05)
Working	975	86,511	11.27 (10.78–11.78)
ART status
No on ART	824	64,279	12.82 (12.28–13.40)
ART initiated	209	24,937	8.38 (7.45–9.47)
Baseline WHO clinical stage
Stage I	194	32,060	6.05 (5.34–6.82)
Stage II	232	24,647	6.40 (8.58–10.39)
Stage III	485	26,317	18.43 (17.54–19.39)
Stage IV	119	5,678	21.91 (17.99–24.43)
Baseline Body Mass Index
Underweight	208	9,349	20.25 (20.81–23.81)
Normal	398	33,280	11.95 (11.29–12.36)
Overweight	75	10,888	6.84 (5.94–7.92)
Obesity	25	5,221	4.71 (3.59–6.32)
Baseline nutritional status
Normal	859	79,304	10.83(10.32–11.37)
Moderate	116	5,270	21.95 (19.99–24.14)
Severe	23	784	29.59 (22.58–39.03)
Health Facility type at enrolment
Dispensary	338	32,666	10.35 (9.44–11.37)
Health center	253	23,661	10.70 (9.95–11.02)
Hospital	446	33,334	13.38 (12.66–14.14)
CTC enrolment year
2012	227	24,631	9.20 (8.42–10.06)
2013	230	23,720	9.69 (8.89–10.60)
2014	216	20,767	10.42 (9.55–11.40)
2015	188	13,014	14.45 (13.04–16.06)
2016	176	7,530	23.38 (21.01–26.10)
Region at enrolment
Dar es Salaam	850	62,545	13.60 (13.00–14.23)
Iringa	78	10,323	7.58 (6.08–9.57)
Njombe	108	16,793	6.45 (5.77–7.25)
Health Facility ownership at enrolment
Private	274	26,420	10.37 (9.24–11.67)
Public	763	63,241	12.07 (11.75–12.79)

Open in a new tab

95% CI = 95% Confidence Interval, ART = Antiretroviral Treatment, CTC = Care and Treatment Clinic, IPT = Isoniazid Preventive Therapy, TB = Tuberculosis, WHO = World Health Organization.

Kaplan-Meier graph comparing TB disease between those who received IPT and those who did not use IPT was fitted. With increasing time of follow up cumulative incidence of TB disease increased in both groups. However, the incidence was higher among those who did not receive IPT compared with those who received the intervention (Fig 2).

Fig 2 — Throughout the follow up, those who ever received IPT had less cumulative Tuberculosis incidence than those who did not receive the intervention.

(4) Risk factors for TB disease

In multivariate analysis of unweighted sample, the risk of developing TB disease was less by 13% among those who ever received IPT: adjusted Hazard Ratio (aHR) = 0.87 (95% CI:0.76–1.01; P>0.05) compared to those who never used IPT. Using weighted sample, after adjusting for other covariates the risk of TB incidence was reduced by 52% in the IPT group compared to non-IPT; aHR = 0.48 (95% CI: 0.40–0.58; P<0.001). In the weighted sample, the risk of developing TB disease was also lower among females: aHR = 0.55 (95% CI: 0.50–0.61), P<0.001, in those who were obese: aHR = 0.36 (0.26–0.48), P<0.05, in those on ART: aHR = 0.61 (95% CI:0.53–0.70), P<0.001, and in those enrolled in Njombe region: aHR = 0.28 (95% CI:0.23–0.33), P<0.001. The risk of TB disease was increased in individual with WHO clinical stage IV; aHR = 3.44 (95% CI: 2.84–4.17), P<0.001 (Table 4).

Table 4. Risk factors for TB disease using weighted sample.

Variable	Univariate		Multivariate
Variable	cHR, 95% CI	P-Value	aHR, 95% CI	P-Value
IPT status
Never on IPT	1	P>0.05	1	P<0.001
Ever on IPT	0.87 (0.76–1.01)	P>0.05	0.48 (0.40–0.58)	P<0.001
Sex
Male	1	P<0.001	1	P<0.001
Female	0.54 (0.50–0.53)	P<0.001	0.55 (0.50–0.61)	P<0.001
Baseline age
0–19	1	P>0.05
20–24	0.43 (0.32–0.58)
25–49	0.81 (0.67–0.99)
+50	1.00 (0.80–1.27
Baseline BMI
Underweight	1	P<0.001	1	P<0.001
Normal	0.54 (0.49–0.59)		0.71 (0.64–0.79)
Overweight	0.31 (0.26–0.36)		0.46 (0.38–0.54)
Obesity	0.21 (0.16–0.28)		0.36 (0.26–0.48)
Baseline functional status
Ambulatory	1	P>0.05
Bedridden	0.70 (0.45–1.08)
Working	0.54 (0.46–0.63)
Baseline ART status
ART not initiated	1	P<0.001	1	P<0.001
ART initiated	0.65 (0.58–0.74)	P<0.001	0.61 (0.53–0.70)	P<0.001
Baseline WHO clinical stage
Stage one	1	P<0.001	1	P<0.001
Stage two	1.55 (1.33–1.81)		1.51 (1.28–1.78)
Stage three	3.04 (2.68–3.46)		3.03 (2.64–3.48)
Stage four	3.45 (2.85–4.18)		3.44 (2.84–4.17)
Nutritional status
Normal	1		1
Moderate	2.03 (1.82–2.26)	P<0.001	1.19 (1.05–1.35)	P>0.05
Severe	2.73 (2.05–3.65)	P<0.001	1.22 (0.87–1.72)
Health Facility type
Dispensary	1	P>0.05
Health center	0.98 (0.86–1.11)
Hospital	1.14 (1.00–1.28)
CTC enrolment Year
2012	1
2013	1.05 (0.93–1.19)	P>0.05
2014	1.13 (1.00–1.29)
2015	1.57 (1.37–1.80)
2016	2.54 (2.21–2.93)
Region
Dar es Salaam	1		1	P<0.001
Iringa	0.56 (0.44–0.70)	P<0.001	0.33 (0.25–0.42)
Njombe	0.47 (0.42–0.54)		0.28 (0.23–0.33)
Health facility ownership
Private	1		1	P>0.05
Public	1.16 (1.03–1.32)	P<0.001	0.89 (0.75–1.11)	P>0.05

Open in a new tab

95% CI = 95% Confidence Interval, aHR = Adjusted Hazard Ratio, ART = Antiretroviral Treatment, BMI-Body Mass Index, Care and Treatment Clinic, cHR = Crude Hazard Ratio, CTC = Care and Treatment Clinic, IPT = Isoniazid Preventive Therapy, TB = Tuberculosis, WHO = World Health Organization.

Discussion

We set out to determine impact of IPT on TB incidence among PLHIV as well show case the application of IPTW to minimize selection bias in observational studies in order to establish causal relationship between IPT and TB incidence among PLHIV in routine clinical settings.

These results show that in the implementation of IPT the risk of developing TB Disease was reduced by a half (52%) in those who received IPT in the studied cohort when compared to those who never received IPT after applying IPTW and adjusting for confounding from other factors. The results also show lower TB disease incidence among those who received IPT in comparison with those who never received IPT. Both lower rates of TB among those who ever used IPT and reduced TB risk among IPT users consolidates evidence of effectiveness of IPT on TB incidence among PLHIV. Lower TB incidence among IPT users has also been documented in other studies where PLHIV who ever used IPT had lower rates of TB incidence than those who never used IPT [4, 18, 31–34], however, unlike many of these studies in real life, the current study applied IPTW to minimize bias associated with non-experimental study designs. Protective effect of IPT on TB incidence among PLHIV in non-research, routine HIV care settings have also been determined in other studies when those who used IPT were compared with those who did not use in routine settings in Tanzania [20], Ethiopia [4, 18, 34–36] and a systematic review [16], and it ranged from 48% to 94%. The various studies showed that the protective effect of IPT is stretched over a long range. These studies were conducted in different routine settings with varying degrees of data quality together with different approaches in controlling for possible biases during data analysis level. Hence, the range of IPT effectiveness in these studies could be due to different study settings and different statistical manipulations done to make those who received IPT and those who did not receive comparable groups.

Overall this population had a relatively lower TB incidence reduction compared to other similar studies in Sub-Saharan Africa including the study in Tanzania [20]. The discrepancy between our study and other studies could also be due to lack of application of statistical techniques like propensity scores to minimize selection bias associated with observational studies [23, 29]. Lack of use of such techniques to minimize selection bias in establishing causal inference in observation studies may result in erroneous estimation of the outcome of interest [37].

The results from the analysis of the weighted data also showed that the risk of TB disease was also lower among females, those on ART, obese individuals and those enrolled in Njombe region. The risk of TB disease was higher in PLHIV with baseline WHO clinical stage IV. Other studies have also shown a low TB risk among females in comparison with Males [38, 39]. Difference in health seeking behavior between males and females [38] and the role of biological difference between the two sexes playing a role in immune responses in resisting Mycobacterium Tuberculosis have been attributed to the differences [39]. ART use is a known public health tool in reducing the risk of developing TB disease among PLHIV [2, 40, 41]. ART restores immune responses to Mycobacterium Tuberculosis through lowering of HIV viral load and hence, prevents HIV-associated TB [41]. Lower TB disease risk among individuals with higher BMI (overweight and obese) in comparison with normal nutritional status has also been reported by others [42, 43]. Overweight or obese people may have increased intake of protein and energy containing food as well as micronutrients which may be protective of TB diseases [43]. However, a thorough mechanism of the association between nutritional status and TB disease may be needed. Different TB risk according to regions could be attributed to health system components which were beyond the scope of this study. Regional variations in TB disease in Tanzania has also been reported by others [44]. The risk of TB disease in individuals with advanced WHO clinical stages (stage 3 and 4) is also reported in other studies [45, 46]. Advanced HIV affects both cellular and hormonal immune responses required to control TB, thus increasing TB disease susceptibility in individuals with advanced HIV disease [47].

ICF and IPT in Tanzania were scaled up from 2011. The observed increased TB notification with increasing years from 2012 could be due to scaling up of these interventions which result into increased TB case notification [48]. TB diagnosis especially by using Florescent Light Emitting Diode (LED) microscopy and Gene-Xpert has been improved over time. Use of these diagnostic tests which perform better than conventional light microscopy lead to increased TB case notification [49, 50]. Moreover, the fact that advancement in TB diagnosis happened as years go, this may explain the increased TB notification from 2012 to 2016. Differences in TB burden among regions in Tanzania was also documented by others [51]. Different TB burden among regions together with differences in TB diagnosis among regions in the country may explain different TB incidence found in this study. Lower TB notification in private health facilities reported in the current research is similar to those reported by others [52]. This may be due to less engagement of private health facilities in TB disease management [53].

This study has an implication on practice and policy in preventing TB. The findings of this study have added information on how IPT works in reducing TB diseases among PLHIV in routine real-world settings. Such findings encourage policy makers to continue safeguarding policies on TB preventive strategy. The findings also encourage health care providers to continue scaling up IPT such that it is accessed by all eligible PLHIV in the country.

The strength of this analysis is that the data are taken from routine visits by PLHIV attending CTC and hence the results represent the effect of IPT under routine settings. The data came from three regions representing a cross section of Tanzania where the prevalence was high [25]. The analysis used IPTW to adjust for the characteristics of study participants [23].

The main limitation of the study as a result of its being a retrospective design, is its inability to include other variables which could be included as possible confounders for IPT initiation. These are such as availability of Isoniazid tablets in the health facilities which may affect IPT initiation. Another limitation of the study is its inability to complete quantitative data with qualitative data to understand context of IPT delivery. Moreover, the study may result into overestimating TB among non-IPT recipients because much TB may have been diagnosed more at the beginning of follow up.

Conclusion

The study found that IPT reduced TB disease in routine HIV care and treatment settings in Tanzania to the same extent as other studies in routine settings. This study has also shown the possibility of applying IPTW to determine causality in observational studies.

Supporting information

S1 Dataset

(ZIP)

Click here for additional data file.^{(1.6MB, zip)}

Acknowledgments

We would like to acknowledge active participation of health care providers and clinic clients in the participating health facilities for their involvement in the study. The authors would also like to thank staff from National AIDS Control Program Tanzania for their support throughout the study.

Abbreviations

ART: Antiretroviral Treatment
ARV: Antiretroviral Therapy
ATE: Average Treatment Effect
BMI: Body Mass Index
CI: Confidence Interval
CTC: Care and Treatment Clinic
HR: Hazard Ratio
ICF: Intensified TB Case Finding
IPT: Isoniazid Preventive Therapy
IPTW: Inverse Probability of Treatment Weighting
NIMR: National Institute of Medical Research
PLHIV: People Living with HIV
TB: Tuberculosis
WHO: World Health Organization

Data Availability

All relevant data are within the paper and its S1 Dataset.

Funding Statement

The study was funded through SEARCH (Sustainable Evaluation through Analysis of Routinely Collected HIV data) Project under Bill and Melinda Gates Foundation grant number OPP1084472 entitled “Using routinely collected public facility data for program improvement in Tanzania, Malawi and Zambia.”. Routine HIV data management is Tanzania is managed collaboratively by the Government of the Republic of Tanzania and the Government of the United States of America through President’s Emergency Plan for AIDS Relief.

References

1.Solomon F. B., Angore B. N., Koyra H. C., Tufa E. G., Berheto T. M., and Admasu M., “Spectrum of opportunistic infections and associated factors among people living with HIV/AIDS in the era of highly active anti-retroviral treatment in Dawro Zone hospital: A retrospective study,” BMC Res. Notes, vol. 11, no. 1, pp. 1–7, 2018. doi: 10.1186/s13104-018-3707-9 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.Dravid A. et al., “Incidence of tuberculosis among HIV infected individuals on long term antiretroviral therapy in private healthcare sector in Pune, Western India,” BMC Infect. Dis., vol. 19, no. 1, pp. 1–12, 2019. doi: 10.1186/s12879-019-4361-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.Pape J. W., Jean S. S., Ho J. L., Hafner A., and Johnson W. D., “Effect of isoniazid prophylaxis on incidence of active tuberculosis and progression of HIV infection,” Lancet, vol. 342, no. 8866, pp. 268–272, Jul. 1993. doi: 10.1016/0140-6736(93)91817-6 [DOI] [PubMed] [Google Scholar]
4.Geremew D., Endalamaw A., Negash M., Eshetie S., and Tessema B., “The protective effect of isoniazid preventive therapy on tuberculosis incidence among HIV positive patients receiving ART in Ethiopian settings: A meta-analysis,” BMC Infect. Dis., vol. 19, no. 1, pp. 1–9, 2019. doi: 10.1186/s12879-019-4031-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Sulis G., Roggi A., Matteelli A., and Raviglione M. C., “Tuberculosis: Epidemiology and control,” Mediterr. J. Hematol. Infect. Dis., vol. 6, no. 1, 2014. doi: 10.4084/MJHID.2014.070 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.WHO, “HIV-Associated Tuberculosis,” World Health Organization@2019, 2019. [Online]. https://www.who.int/tb/areas-of-work/tb-hiv/tbhiv_factsheet.pd. [Accessed: 18-Apr-2020]. [Google Scholar]
7.UNAIDS, “UNAIDS DATA. The Joint United Nations Programme on HIV/AIDS,” 2019. [PubMed] [Google Scholar]
8.Majigo M. et al., “Prevalence and incidence rate of tuberculosis among HIV-infected patients enrolled in HIV care, treatment, and support program in mainland Tanzania,” Trop. Med. Health, vol. 48, no. 1, 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]
9.WHO, “WHO policy on collaborative TB / HIV activities Guidelines for national programmes and other stakeholders. World Health Organization,” p. 36, 2004. [PubMed] [Google Scholar]
10.WHO, “WHO Three I’s Meeting Intensified Case Finding (ICF), Isoniazid Preventive Therapy (IPT) and TB Infection Control (IC) for people living with HIV,” 2008.
11.WHO, “Guidelines for intensified tuberculosis case-finding and isoniazid preventive therapy for people living with HIV in resource- constrained settings,” World Health Organization, vol. 66. pp. 37–39, 2012. [Google Scholar]
12.NACP, “HIV care and treatment. National AIDS Control Program, Tanzania,” 2019. [Google Scholar]
13.Maokola W. et al., “Coverage of isoniazid preventive therapy among people living with HIV; A retrospective cohort study in Tanzania (2012–2016),” Int. J. Infect. Dis., vol. 103, pp. 562–567, 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]
14.MoHCDEC, United Republic of Tanzania Ministry of Health, community, gender, elderly and children National AIDS Control Programme (HSHSP IV) 2017–2022, no. July. 2017. [Google Scholar]
15.Akolo C., Adetifa I., Shepperd S., and Volmink J., “Treatment of latent tuberculosis infection in HIV infected persons (Review),” Cochrane Database Syst. Rev., no. 1, 2010. [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Melissa B., Courtney E., Surbhi M., Taylor K. N., and Anand D., “Use of isoniazid preventive therapy for TB among PLHIV,” HHS Public Access, vol. 155, no. 12, pp. 3007–3024, 2015. [Google Scholar]
17.Rangaka M. X. et al., “Isoniazid plus antiretroviral therapy to prevent tuberculosis: A randomised double-blind, placebo-controlled trial,” Lancet, vol. 384, no. 9944, pp. 682–690, 2014. doi: 10.1016/S0140-6736(14)60162-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Tiruneh G., Getahun A., and Adeba E., “Assessing the Impact of Isoniazid Preventive Therapy (IPT) on Tuberculosis Incidence and Predictors of Tuberculosis among Adult Patients Enrolled on ART in Nekemte Town, Western Ethiopia: A Retrospective Cohort Study,” Interdiscip. Perspect. Infect. Dis., vol. 2019, 2019. doi: 10.1155/2019/1413427 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Ayele A. A. et al., “Self-reported adherence and associated factors to isoniazid preventive therapy for latent tuberculosis among people living with HIV/AIDS at health centers in Gondar town, North West Ethiopia,” Patient Prefer. Adherence, vol. 11, pp. 743–749, 2017. doi: 10.2147/PPA.S131314 [DOI] [PMC free article] [PubMed] [Google Scholar]
20.Sabasaba A., Mwambi H., Somi G., Ramadhani A., and Mahande M. J., “Effect of isoniazid preventive therapy on tuberculosis incidence and associated risk factors among HIV infected adults in Tanzania: A retrospective cohort study 11 Medical and Health Sciences 1117 Public Health and Health Services,” BMC Infect. Dis., vol. 19, no. 1, pp. 1–8, 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Golub J. E. et al., “The impact of antiretroviral therapy and isoniazid preventive therapy on tuberculosis incidence in HIV-infected patients in Rio de Janeiro, Brazil,” no. February, 2007. [DOI] [PMC free article] [PubMed] [Google Scholar]
22.Singal A. G., Higgins P. D. R., and Waljee A. K., “A primer on effectiveness and efficacy trials,” Clin. Transl. Gastroenterol., vol. 5, no. 2, pp. e45–4, 2014. doi: 10.1038/ctg.2013.13 [DOI] [PMC free article] [PubMed] [Google Scholar]
23.Austin P. C. and Stuart E. A., “Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies,” Stat. Med., vol. 34, no. 28, pp. 3661–3679, 2015. doi: 10.1002/sim.6607 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Maokola W., Ngowi B., Lawson L., Mahande M., Todd J., and Msuya S., “Performance of and Factors Associated With Tuberculosis Screening and Diagnosis Among People Living With HIV: Analysis of 2012–2016 Routine HIV Data in Tanzania,” Front. Public Heal., vol. 7, no. 404, Feb. 2020. doi: 10.3389/fpubh.2019.00404 [DOI] [PMC free article] [PubMed] [Google Scholar]
25.NBS, “Tanzania Hiv Impact Survey (This) 2016–2017,” Tanzania HIV Impact Surv. 2016–2017, no. December 2017, pp. 2016–2017, 2018. [Google Scholar]
26.NTLP, “Manual for the Management of Tuberculosis and Leprosy. Sixth Edition 2013,” 2013. [Google Scholar]
27.Hazlett C., Maokola W., and Wulf D. A., “Inference without randomization or ignorability: A stability-controlled quasi-experiment on the prevention of tuberculosis,” no. July, pp. 1–18, 2020. [DOI] [PubMed] [Google Scholar]
28.Garrido M. M. et al., “Methods for constructing and assessing propensity scores,” Health Serv. Res., vol. 49, no. 5, pp. 1701–1720, 2014. doi: 10.1111/1475-6773.12182 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Austin P. C., “An introduction to propensity score methods for reducing the effects of confounding in observational studies,” Multivariate Behav. Res., vol. 46, no. 3, pp. 399–424, 2011. doi: 10.1080/00273171.2011.568786 [DOI] [PMC free article] [PubMed] [Google Scholar]
30.Alan B., Wyss R., Layton B., and Til S., “Propensity Score Methods for Confounding Control in NonExperimental Research,” Circ Cardiovasc Qual Outcomes, vol. 6, no. 5, pp. 604–611, 2013. [DOI] [PMC free article] [PubMed] [Google Scholar]
31.Yirdaw K. D. et al., “Beneficial effect of isoniazid preventive therapy and antiretroviral therapy on the incidence of tuberculosis in people living with HIV in Ethiopia,” PLoS One, vol. 9, no. 8, 2014. doi: 10.1371/journal.pone.0104557 [DOI] [PMC free article] [PubMed] [Google Scholar]
32.Atey T. M., Bitew H., Asgedom S. W., Endrias A., and Berhe D. F., “Does Isoniazid Preventive Therapy Provide Better Treatment Outcomes in HIV-Infected Individuals in Northern Ethiopia? A Retrospective Cohort Study,” AIDS Res. Treat., vol. 2020, 2020. doi: 10.1155/2020/7025738 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Juszkiewicz K., Jarosz M. J., Włoszczak-Szubzda A., and Głowacka M., “Comparative analysis of the effectiveness of tuberculosis prophylaxis in patients with HIV/AIDS treated with isoniazid,” Ann. Agric. Environ. Med., vol. 26, no. 3, pp. 462–467, 2019. doi: 10.26444/aaem/106765 [DOI] [PubMed] [Google Scholar]
34.Golub J. et al., “Isoniazid preventive therapy, HAART and tuberculosis risk in HIV-infected adults in South Africa: a prospective cohort,” AIDS, vol. 23, no. 5, pp. 631–636, 2009. doi: 10.1097/QAD.0b013e328327964f [DOI] [PMC free article] [PubMed] [Google Scholar]
35.Semu M., Fenta T. G., Medhin G., and Assefa D., “Effectiveness of isoniazid preventative therapy in reducing incidence of active tuberculosis among people living with HIV / AIDS in public health facilities of Addis Ababa, Ethiopia: a historical cohort study,” BMC Infect. Dis., pp. 1–8, 2017. [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Chang C. et al., “Tuberculosis Incidence and Risk Factors Among Human Immunodeficiency Virus (HIV)-Infected Adults Receiving Antiretroviral Therapy in a Large HIV Program in Nigeria,” OFID, 2015. [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Pandis N., “Bias in observational studies,” Am. J. Orthod. Dentofac. Orthop., vol. 145, no. 4, pp. 542–543, 2014. doi: 10.1016/j.ajodo.2014.01.008 [DOI] [PubMed] [Google Scholar]
38.Horton K. C., Macpherson P., Houben R. M. G. J., White G., and Corbett E. L., “Sex Differences in Tuberculosis Burden and Notifications in Low- and Middle-Income Countries: A Systematic Review and Meta- analysis,” vol. 21, pp. 1–23, 2016. [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Nhamoyebonde S. and Leslie A., “Biological differences between the sexes and susceptibility to tuberculosis,” J. Infect. Dis., vol. 209, no. SUPPL. 3, 2014. doi: 10.1093/infdis/jiu147 [DOI] [PubMed] [Google Scholar]
40.Lawn S. D., Kranzer K., and Wood R., “Antiretroviral Therapy for Control of the HIV-associated Tuberculosis Epidemic in Resource-Limited Settings,” Clin. Chest Med., vol. 30, no. 4, pp. 685–699, 2009. doi: 10.1016/j.ccm.2009.08.010 [DOI] [PMC free article] [PubMed] [Google Scholar]
41.Suthar A. B. et al., “Antiretroviral therapy for prevention of tuberculosis in adults with hiv: A systematic review and meta-analysis,” PLoS Med., vol. 9, no. 7, 2012. doi: 10.1371/journal.pmed.1001270 [DOI] [PMC free article] [PubMed] [Google Scholar]
42.Hanrahan C. F. et al., “Body mass index and risk of tuberculosis and death,” Aids, vol. 24, no. 10, pp. 1501–1508, 2010. doi: 10.1097/QAD.0b013e32833a2a4a [DOI] [PMC free article] [PubMed] [Google Scholar]
43.Pednekar M. S., Hakama M., Hebert J. R., and Gupta P. C., “Association of body mass index with all-cause and cause-specific mortality: Findings from a prospective cohort study in Mumbai (Bombay), India,” Int. J. Epidemiol., vol. 37, no. 3, pp. 524–535, 2008. doi: 10.1093/ije/dyn001 [DOI] [PubMed] [Google Scholar]
44.Mpagama S. G. et al., “Gridlock from diagnosis to treatment of multidrug-resistant tuberculosis in Tanzania: Low accessibility of molecular diagnostic services and lack of healthcare worker empowerment in 28 districts of 5 high burden TB regions with mixed methods evaluation,” BMC Public Health, vol. 19, no. 1, pp. 1–11, 2019. doi: 10.1186/s12889-019-6720-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
45.Gunda D. W. et al., “Prevalence and risk factors of active TB among Adult HIV Patients Receiving ART in Northwestern Tanzania: A Retrospective Cohort Study,” Can. J. Infect. Dis. Med. Microbiol., vol. 2018, 2018. doi: 10.1155/2018/1346104 [DOI] [PMC free article] [PubMed] [Google Scholar]
46.Lawn S. D., Badri M., and Wood R., “Tuberculosis among HIV-infected patients receiving HAART: Long term incidence and risk factors in a South African cohort,” Aids, vol. 19, no. 18, pp. 2109–2116, 2005. [DOI] [PubMed] [Google Scholar]
47.Zuiga J., Torres-García D., Santos-Mendoza T., Rodriguez-Reyna T. S., Granados J., and Yunis E. J., “Cellular and humoral mechanisms involved in the control of tuberculosis,” Clin. Dev. Immunol., vol. 2012, 2012. [DOI] [PMC free article] [PubMed] [Google Scholar]
48.Corbett E. and MacPherson P., “Tuberculosis screening in high human immunodeficiency virus prevalence settings: turning promise into reality,” Int J Tuberc Lung Dis, vol. 17, no. 9, pp. 1125–1138, 2013. doi: 10.5588/ijtld.13.0117 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Gelalcha A. G., Kebede A., and Mamo H., “Light-emitting diode fluorescent microscopy and Xpert MTB/RIF^® assay for diagnosis of pulmonary tuberculosis among patients attending Ambo hospital, west-central Ethiopia,” BMC Infect. Dis., vol. 17, no. 1, pp. 1–9, 2017. doi: 10.1186/s12879-017-2701-5 [DOI] [PMC free article] [PubMed] [Google Scholar]
50.Steingart K. R. et al., “Fluorescence versus conventional sputum smear microscopy for tuberculosis: a systematic review,” Lancet Infect. Dis., vol. 6, no. 9, pp. 570–581, 2006. doi: 10.1016/S1473-3099(06)70578-3 [DOI] [PubMed] [Google Scholar]
51.NTLP, “Tubeculosis Prevalence in Tanzania,” National Tuberculosis and Leprosy Program Tanzania, 2012. [Online]. https://ntlp.go.tz/tuberculosis/tb-prevalence/. [Accessed: 20-May-2021].
52.Siddaiah A. et al., “Tuberculosis notification in a private tertiary care teaching hospital in South India: A mixed-methods study,” BMJ Open, vol. 9, no. 2, pp. 1–13, 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]
53.Stallworthy G., Dias H. M., and Pai M., “Quality of tuberculosis care in the private health sector,” J. Clin. Tuberc. Other Mycobact. Dis., vol. 20, p. 100171, 2020. doi: 10.1016/j.jctube.2020.100171 [DOI] [PMC free article] [PubMed] [Google Scholar]

PLoS One. 2021 Jul 13;16(7):e0254082. doi: 10.1371/journal.pone.0254082.r001

Author response to previous submission

2 Dec 2020

Attachment

Submitted filename: Responses to the editor.docx

Click here for additional data file.^{(15.5KB, docx)}

PLoS One. doi: 10.1371/journal.pone.0254082.r002

Decision Letter 0

Katalin Andrea Wilkinson

20 Jan 2021

PONE-D-20-37236

Impact of Isoniazid Preventive Therapy on Tuberculosis incidence among people living with HIV; a secondary data analysis using Inverse Probability Weighting of patients attending HIV care and treatment clinics in Tanzania.

PLOS ONE

Dear Dr. Maokola,

Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but 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.

Please submit your revised manuscript by Feb 14 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:

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'.

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.

We look forward to receiving your revised manuscript.

Kind regards,

Katalin Andrea Wilkinson, PhD

Academic Editor

PLOS ONE

Journal Requirements:

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

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

2. Please include additional information regarding the data extraction tool used in the study and ensure that you have provided sufficient details that others could replicate the analyses. For instance, if you developed a data extraction tool as part of this study and it is not under a copyright more restrictive than CC-BY, please include a copy, in both the original language and English, as Supporting Information, or include a citation if it has been published previously.

3. Thank you for stating the following in the Competing Interests section:

"The study was funded through SEARCH Project under Bill and Melinda Gates Foundation. Routine HIV data management is Tanzania is managed collaboratively by the Government of the Republic of Tanzania and the Government of the United States of America through President’s Emergency Plan for AIDS Relief."

Please confirm that this does not alter your adherence to all PLOS ONE policies on sharing data and materials, by including the following statement: "This does not alter our adherence to PLOS ONE policies on sharing data and materials.” (as detailed online in our guide for authors http://journals.plos.org/plosone/s/competing-interests). If there are restrictions on sharing of data and/or materials, please state these. Please note that we cannot proceed with consideration of your article until this information has been declared.

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

Please know it is PLOS ONE policy for corresponding authors to declare, on behalf of all authors, all potential competing interests for the purposes of transparency. PLOS defines a competing interest as anything that interferes with, or could reasonably be perceived as interfering with, the full and objective presentation, peer review, editorial decision-making, or publication of research or non-research articles submitted to one of the journals. Competing interests can be financial or non-financial, professional, or personal. Competing interests can arise in relationship to an organization or another person. Please follow this link to our website for more details on competing interests: http://journals.plos.org/plosone/s/competing-interests

4. We note that you have indicated that data from this study are available upon request. PLOS only allows data to be available upon request if there are legal or ethical restrictions on sharing data publicly. For information on unacceptable data access restrictions, please see http://journals.plos.org/plosone/s/data-availability#loc-unacceptable-data-access-restrictions.

In your revised cover letter, please address the following prompts:

a) If there are ethical or legal restrictions on sharing a de-identified data set, please explain them in detail (e.g., data contain potentially identifying or sensitive patient information) and who has imposed them (e.g., an ethics committee). Please also provide contact information for a data access committee, ethics committee, or other institutional body to which data requests may be sent.

b) If there are no restrictions, please upload the minimal anonymized data set necessary to replicate your study findings as either Supporting Information files or to a stable, public repository and provide us with the relevant URLs, DOIs, or accession numbers. Please see http://www.bmj.com/content/340/bmj.c181.long for guidelines on how to de-identify and prepare clinical data for publication. For a list of acceptable repositories, please see http://journals.plos.org/plosone/s/data-availability#loc-recommended-repositories.

We will update your Data Availability statement on your behalf to reflect the information you provide.

5. Your ethics statement should only appear in the Methods section of your manuscript. If your ethics statement is written in any section besides the Methods, please move it to the Methods section and delete it from any other section. Please ensure that your ethics statement is included in your manuscript, as the ethics statement entered into the online submission form will not be published alongside your manuscript.

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

1. 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 #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

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

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

**********

3. 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: No

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: No

**********

4. 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: Yes

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: Yes

**********

5. 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: In this manuscript, the authors make use of a national dataset to explore the effects of IPT on incident TB among people living with HIV in Tanzania. To address confounding in such an observational dataset, they use an inverse probability of treatment weighting to balance certain confounders between treated and untreated groups. The large size of the dataset and the appropriately chosen method for causal inference are promising, but there are several weaknesses of the analysis as currently presented:

1. The 4 variables adjusted for are not sufficient to balance the IPT and non-IPT groups. IPTW requires balancing all confounders that independently influence both IPT initiation and TB risk. In this dataset, there are a number of other measured but unadjusted confounders that appear to have been associated with IPT initiation (Table 1) and that are also likely to influence TB diagnosis outside of the IPT causal pathway. These include, for example, ART status, BMI and/or nutritional status, and type of health facility. The IPTW analysis is not valid unless all confounders are both measured and included in the weighting, and the authors cannot just assert that “after weighting, the two exposure groups were comparable.”

The authors also note in the introduction that IPT tended to be introduced sooner at larger facilities, and larger facilities may also be associated with differences in care that influence either risk of developing TB or probability of being diagnosed with TB (e.g. because of different TB diagnostics available), making this another potential confounder.

2. The authors need to do more to describe the motivation and context for their study. While Plos One does not select papers for publication based on “impact”, it is still important to accurately describe the existing literature and what the current analysis adds. The authors start from the assertion that “IPT reduces TB incidence” (abstract), and they cite a number of observational studies demonstrating effectiveness of IPT in reducing TB incidence in routine care settings including Tanzania. They say that the current study will help to inform scale-up, but it is not clear what aspects of scale-up this study informs. Is there clinically important uncertainty in the size of effect based on prior literature? Is there something different about this setting that might lead to a different effect? Are there particular covariates of interest that this analysis is intended to explore?

Similarly, it seems contradictory in the introduction to state that “a number of studies … in routine public health settings… have also shown benefits of IPT on TB incidence ”,but then assert in the next paragraph that “effectiveness [of IPT] in these settings has not been adequately and properly evaluated.” More exploration is needed of what the gaps in current data are and how this study addresses them.

3. I note in Figure 2 that a lot of the divergence between the IPT and no-IPT groups occurs within the first two months of follow up. This makes me think that much of the difference is not an effect of the IPT, but rather a difference in the suspicion of existing TB: Clinicians may have been disinclined to start IPT when they suspected that a patient already had active TB, even if an initial diagnostic test was negative or they were still waiting for a diagnostic result. Or, it could be that patients who were going to start IPT got a more thorough evaluation to rule out active TB at baseline, making those with early, undiagnosed TB disease less likely to be included in the IPT group than in the no-IPT group. More information about TB screening and diagnostic practices during the study period might help to clarify this, and it is also a limitation that needs to be explored in the discussion.

Minor:

Introduction:

- It’s potentially misleading to cite the % of PLHIV who have TB infection at time of death. Would be more useful to cite the % of PLHIV who have TB disease at time of death.

Methods:

- Please state how incidence rates (and their confidence intervals) were calculated.

- How was the multivariable model (Table 3) developed? Why this set of covariates?

Results:

- Too many significant digits are included, making results both overly precise and difficult to read.

- Person-years do not make sense as reported. Should these be thousands of person years?

- What is the difference between “ambulatory” and “walking” functional status? To me, these seem synonymous.

- Sentences containing lists are difficult to follow due to inconsistent grammar and punctuation.

- Several numerical results seem to be incorrectly typed. For example, incidences by ART status differ between text and table, some confidence intervals are concerningly asymmetric, some column percentages in tables do not add to 100%, and some reported p values seem incorrect based on the point estimates and Cis presented.

- TB incidence seems to increase over time from 2012 to 2016. What there a change in diagnostic practice during this period (e.g. introduction of Xpert or change in screening practices), and if so, how is that likely to affect your results? Should calendar year or clinic-level diagnostic availability be adjusted for?

Discussion:

- I suggest presenting results in the context of follow-up period. IPT reduced TB incidence by xx% over what median duration of follow up? Effects are likely to wane with time, as reinfection increasingly predominates over reactivation as the source of incident TB.

- The main limitation cited is the “inability to include other [confounding] variables”, but they in fact have data on many more potentially-confounding variables that they do have the ability to include if they choose.

- Much more exploration of the study’s limitations is needed.

Author contributions:

- All authors should review and approve the final manuscript.

Reviewer #2: Thank you very much for allowing me to review this interesting manuscript.

The manuscript adds to the existing evidence on the effectiveness of IPT in reducing TB incidence based on analysis of a large number of participants in Tanzania. The papers showed durable protection against TB for 6 years. The manuscript is generally well written but lacks some details. Please consider suggestions below to improve clarity.

1. The definition of the IPT group and the control group is not clear to me. The authors conducted the survival analysis by defining entry time as the data of enrolment. Were participants classified into either IPT group or the control group depending on whether they started IPT at the time of enrolment? I presume that most of PLHIV started at IPT the time enrolment but some might have initiated it later (e.g. after investigation for TB). How did you account for those who started IPT later? For example, if they started IPT one month later, were they then transferred into the IPT group? If they remained in the control group, then the control group is not “those who never received IPT”.

2. What is the definition of TB disease? Only bacteriologically confirmed? Does this include TB diagnosed regardless of the timing after the follow-up? (e.g. TB diagnosed within one week after the enrolment.)

3. Figure 2 shows a sharp increase in TB very early in the follow-up. If I understand correctly, participants who screened positive didn’t start immediately upon enrolment and were included in the control group. Among those who screened positive, prevalent TB may have been found after investigation and inflated the number of TB cases in the control group in the initial period.

4. The authors claim that baseline characteristics were balanced after IPTW. However, I seem to find some imbalances, for example:

ART 29.02% vs 36.09%

Private facility 17% vs 29%

Underweight 15% vs 18%

Is this the reason why the authors conducted multivariable cox-regression after IPTW?

I wonder if the authors conducted balance diagnostics. Presenting results may be helpful. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626409/

I would also suggest presenting the distribution of the weights.

Minor points

Introduction

Suggest mentioning the coverage of IPT among PLHIV not only the proportion of CTC providing TPT.

Also, suggest to briefly summarize the durability of efficacy reported in high TB burden countries and discuss how the present research adds to the evidence.

Method:

Is TST recommended at all?

If I remember correctly, the TB guidelines in Tanzania recommend repeating IPT after 2 years. Is there any chance that some of the participants repeated IPT?

Data collection

How did you assess nutritional status? What is the definition of each category?

How is ambulatory different from walking?

Do you have information on the previous history of TB?

Analysis

Please justly the use of p-values less than 0.05 as a criterion to select covariates included in the final model. This may miss important variables associated with exposure and outcome. Have you considered a higher threshold? https://pubmed.ncbi.nlm.nih.gov/8256780/

How did you handle missing data?

How were the weights given? Was it simple inverse or did you use stabilized weights?

Result

Paragraph 2

“from private health facilities (84.36%).” This is not consistent with Table 1. 84.36% is from public facilities.

Paragraph 3

Suggest reporting the median duration of follow-up in the two groups. The person-years reported don’t seem to correct. Only 134.56 person-year? Is this for all participants or 2309 TB patients? Either way, the number is too small, corresponding to a very short period of follow-up. Person-years in Table 2 are also too small.

Did you find any difference in the number of people who were lost to follow-up or died between the two groups? How could that impact the analysis?

Discussion

Paragraphs 2 and 3 seem repetitive.

The discussion could also mention the durability of protection.

Table 1.

Proportions of the weighted sample enrolled by year in the IPT group do not sum up to 100%.

Reviewer #3: There is no statement on the ethical consideration that explains how to keep the confidentiality of the participants.try to include a statement. It also needs some grammatical error corrections. both on the introduction and discussion.

Reviewer #4: ‘Impact of Isoniazid Preventive Therapy on Tuberculosis incidence among people living with HIV; a secondary data analysis using Inverse Probability Weighting of patients attending HIV care and treatment clinics in Tanzania.

This manuscript is intended to describe the use of inverse probability weighting (IPW) to determine the effectiveness of IPT in preventing active TB among PLHIV attending health facilities in Tanzania. The manuscript is good addition to scientific literature as it demonstrates the benefit of using IPW and its results. Previous studies on impact of TB prevention and TB Incidence in Tanzania has been done but the uniqueness of this paper is that it has included children, more regions in addition to Dar es Salaam and use of IPW to determine TB incidence among those on TB Prevention. The author needs to define and clearly state the objective of this study.

The abstract section is well written and reflecting on the manuscript. However, the author has indicated 171,672 as the study participants but this is not reflected in the results section which indicates 166,709 can this be clarified. The background section seems to be missing the objective and the statement on routine settings should be clear they should consider routine care setting. The conclusion should be aligned to the study objectives.

In the background section, in the 2nd paragraph the author has indicated Tanzania adopting WHO 3 I's in 2011 , can this be expounded was it in the form of guidelines or policy directive from the ministry ? and further expound on the scale up was it phased from higher level to lower level .The author has indicated > 50% scale up in the CTCs can this indicated in patient numbers as well .The policy on IPT uptake is it once in a lifetime or repeated after a certain duration of time in Tanzania .The fourth paragraph should read limited information on effectiveness of IPT on TB incidence as there has a study published on this (Sabasaba et al. BMC Infectious Diseases)

The manuscript would have benefitted from a clearer ,detailed and a logical methodology section for the readers to understand .The authors should consider to elaborate on the study design , clearly describe the study setting or a brief on the 3 regions .A brief explanation on the TB/HIV service delivery in particular IPT services in the health facilities in this 3 regions , the TB screening process , diagnosis , treatment and follow up .The authors needs to be clear on the study population .In the data analysis section the author needs to clearly indicate how the 4 variables ( Age,sex, region WHO staging ) was achieved at, justify why IPW .A clear explanation on the propensity scores used and how this was achieved .There should be a step wise approach with clear formulae and outcomes .

In the result section, the authors need to have a clearly structured sub section of the results. There needs to be clarification on the actual number of study participants analyzed (171,743 or 171,672 or 166,709?) and let it be uniform throughout the document. Table 1 is not uniform and a brief explanation on the age stratification from 0-9 then 10 – 19 then 20 – 24 then 25- 29. There needs to a clear write up of the highlight summary findings of the 3 tables in the result section and revision of the 3 tables as they appear overcrowded .

In the discussion section, in the first paragraph the aspect of using IPTW to determine effectiveness of public health intervention has been previously used refer to the NIH study (Sheri A. Lippman et al .NIH ) it’s more of use of TB prevention and in this country setting that is limited .The author seems to have duplicate information on ‘IPT lowering TB incidence by 70% ‘ in the 2nd and 4th paragraph can this be revised .From the commencement of TB prevention in the HIV facilities from 2011 has the national TB program seen some changes like reduction in the TB/HIV co-infection rate ? . Can the author expound on the association of higher TB incidence in the variables: Male; not on ART ; aging population ; Nutrition status ; higher numbers in 2016 and in the Dar es salaam region and the public health facilities of TB incidence .Basically the authors need to further expound on the findings of the current study in line with the results they got.

Finally, perhaps the authors can strengthen the conclusion in line with the objective of the study perhaps inclusion on use of IPW in evaluating effectiveness of a public health intervention.

**********

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

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

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

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: Dr. Muthoni E. Karanja

[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.

Attachment

Submitted filename: Peer review comments PONE-D-20-37236.docx

Click here for additional data file.^{(20.9KB, docx)}

Attachment

Submitted filename: plos one comments.docx

Click here for additional data file.^{(13KB, docx)}

PLoS One. 2021 Jul 13;16(7):e0254082. doi: 10.1371/journal.pone.0254082.r003

Author response to Decision Letter 0

8 Apr 2021

PONE-D-20-37236

Journal Requirements:

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

1. Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at

https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and

https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Response: Thank you very much for the comment. PLOS ONE style has been adopted in the revised manuscript (Lines 1-326).

Response: Thank you very much for the comment. The study used secondary data collected as part of HIV care and treatment services in the country. Details on how data extraction has been explained in details under methods section (Lines 90-103). The variables to be extracted was guided by planned dummy tables for the manuscript.

3. Thank you for stating the following in the Competing Interests section:

Please include your updated Competing Interests statement in your cover letter; we will change the online submission form on your behalf.

Response: Thank you very much for the comment. An updated Competing interests statement has been included in the cover letter as directed.

Response: Thank you very much for the comment. We have visited the link and read the contents.

In your revised cover letter, please address the following prompts:

Response: Thank you very much for the comment. Detailed explanation regarding data sharing and contact person have been included in the cover letter.

We will update your Data Availability statement on your behalf to reflect the information you provide.

Response: Thanks for the comment. As stated earlier, the permission for data sharing needs to be requested from the Principal Secretary-Health. Upon request, the data set will be made available. The statement regarding data availability has been included in the ethical consideration section (162-164).

Response: Thank you very much for the comment. Ethics statement has been moved into the Methods section (Lines: 152-164).

[Note: HTML markup is below. Please do not edit.]

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #1: Partly

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

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

Reviewer #1: No

Reviewer #2: Yes

Reviewer #3: Yes

Reviewer #4: Yes

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

Reviewer #1: No

Reviewer #2: No

Reviewer #3: Yes

Reviewer #4: No

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

Reviewer #1: Yes

Reviewer #2: Yes

Reviewer #3: No

Reviewer #4: Yes

5. Review Comments to the Author

Response: Thank you very much for the comment. The aim of IPTW is to balance covariates which are more likely to affect treatment selection (in this case is IPT) as well the outcome of interest (in this case is TB incidence). The propensity score model now contains all covariates that are potential confounders; they affect the outcome of interest as well as determine whether a client will be given IPT or not. After weighting the balance of covariates between weighted and original sample was shown quantitatively by using standard differences and variances. (Line 114-134)

Response: Thank you very much for the comment. The potential confounding effect due to health facility type was checked. This was checked by including “Type of Health Facility” as one of the covariates. Furthermore, the effect of Type of Health Facility” on TB disease was also checked by carrying out multilevel analysis to check for cluster effect of health facility types. There was no cluster effect detected (Line 147-148).

Response: Thanks for the comment. Sabasaba et al conducted a study to determine effect of IPT in one region in Tanzania. The current study has widened the scope by including three regions. Moreover, the current study unlike most studies before, used IPTW to determine causality between an interventions (IPT) and an outcome or impact of interest (TB incidence). Hence, the study intended to show effectiveness of IPT in routine clinical settings as well as advocate the use of statistical methods to infer causality in observational studies. The motivation and the context of the study has been added in the abstract (Lines 11-12) as well as in the background (Line: 57-69).

Similarly, it seems contradictory in the introduction to state that “a number of studies … in routine public health settings… have also shown benefits of IPT on TB incidence”, but then assert in the next paragraph that “effectiveness [of IPT] in these settings has not been adequately and properly evaluated.” More exploration is needed of what the gaps in current data are and how this study addresses them.

Response: Thank you very much for the comment. The gap was mainly referring to Tanzanian context. Effectiveness of IPT in routine settings has not been extensively conducted. As pointed earlier, Sabasaba et al determined effect of IPT on TB incidence in one region in Tanzania. In other countries like Ethiopia, Brazil and Zimbabwe where IPT implementation has been evaluated, the analysis method was not rigorous as the analysis did not consider the bias introduced by self-selection which is common in observational studies as well as indication bias (confounding by indication) introduced by clinician’s decision as to who to treat and who not to. Hence, the study intended to produce local evidence for Tanzania by involving more regions as well as to show case the use of propensity scores to minimize biases in observational studies for causal inference (Line: 57-69).

Response: Thank you very much for the comment. We agree with you the possibilities of overestimating TB for PLHIV not on IPT during the first days of follow up. This will be included as one of the study limitations (Line: 293-295).

Minor:

Introduction:

- It’s potentially misleading to cite the % of PLHIV who have TB infection at time of death. Would be more useful to cite the % of PLHIV who have TB disease at time of death.

Response: Thank you very much for the comment. The correction has been done (Line 43-46).

Methods:

- Please state how incidence rates (and their confidence intervals) were calculated.

- How was the multivariable model (Table 3) developed? Why this set of covariates?

Response: Thank you very much for the comment. How incidence rates were calculated and multivariable model was developed has been included in the method section of the manuscript (lines 137-139).

Results:

- Too many significant digits are included, making results both overly precise and difficult to read.

- Person-years do not make sense as reported. Should these be thousands of person years?

- What is the difference between “ambulatory” and “walking” functional status? To me, these seem synonymous.

- Sentences containing lists are difficult to follow due to inconsistent grammar and punctuation.

- Several numerical results seem to be incorrectly typed. For example, incidences by ART status differ between text and table, some confidence intervals are concerning asymmetric, some column percentages in tables do not add to 100%, and some reported p values seem incorrect based on the point estimates and Cis presented.

Response: Thank you very much for the comment. Relevant corrections raised have been done. Both calendar year and clinic level were included in the multivariate analysis. Moreover, clinic level associated cluster effect was also checked and had no effect on TB incidence (Lines 145-148).

Discussion:

- Much more exploration of the study’s limitations is needed.

Response: Thank you very much for the comment. The result section has been reviewed; presentation of results has been changed (Lines 165-222) and study limitations have been reviewed and written as suggested. The limitation was referring to covariates which potentially would be helpful if collected. These were such as health system issues e.g. availability of Isoniazid which is used for IPT (Line 289-295).

Author contributions:

- All authors should review and approve the final manuscript.

Response: Thank you very much for the comment. Contribution of authors has been reviewed (Lines: 316-320).

Reviewer #2: Thank you very much for allowing me to review this interesting manuscript.

1.The definition of the IPT group and the control group is not clear to me. The authors conducted the survival analysis by defining entry time as the data of enrolment. Were participants classified into either IPT group or the control group depending on whether they started IPT at the time of enrolment? I presume that most of PLHIV started at IPT the time enrolment but some might have initiated it later (e.g. after investigation for TB). How did you account for those who started IPT later? For example, if they started IPT one month later, were they then transferred into the IPT group? If they remained in the control group, then the control group is not “those who never received IPT”.

Response: Thank you very much for requesting clarification. The study involved People living with HIV (PLHIV) enrolled from January 2012 to December 2016. The IPT group were those who ever received IPT and the control group constituted those who never received IPT during any time of study duration. For individuals who received IPT the time before receipt of IPT was considered “not on IPT” and the time following initiation of IPT considered “on IPT” (Lines: 105-107) and (Lines: 139-141).

Response: Thank you very much for asking. TB disease diagnosis was either bacteriological or radiological or symptomatic as decided by the clinician. Only PLHIV who were diagnosed with TB before being enrolled into HIV clinics were excluded from follow up.

Response: Thank you very much for the comment. We agree with you TB at the start of follow up may overestimate TB disease among non-IPT group. This has been admitted as a limitation (Lines: 293-295).

4. The authors claim that baseline characteristics were balanced after IPTW. However, I seem to find some imbalances, for example:

ART 29.02% vs 36.09%

Private facility 17% vs 29%

Underweight 15% vs 18%

Is this the reason why the authors conducted multivariable cox-regression after IPTW?

I wonder if the authors conducted balance diagnostics. Presenting results may be helpful. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4626409/

I would also suggest presenting the distribution of the weights.

Response: Thank you very much for the comment. Balance between the 2 groups (Intervention and control groups) has been quantitatively tested after weighting by using standardized difference and variance between unweighted and weighted samples (Line 125-129).

Minor points

Introduction

Suggest mentioning the coverage of IPT among PLHIV not only the proportion of CTC providing TPT.

Also, suggest to briefly summarize the durability of efficacy reported in high TB burden countries and discuss how the present research adds to the evidence.

Response: Thank you very much for the comment. IPT coverage in Tanzania has also been incorporated (Line 55-56). Efficacy and effectiveness of IPT in other countries have been included (Lines: 57-65).

Method:

Is TST recommended at all?

Response: Thank you very much for requesting clarification. TST is not mandatory for IPT in Tanzania

If I remember correctly, the TB guidelines in Tanzania recommend repeating IPT after 2 years. Is there any chance that some of the participants repeated IPT?

Response: Thank you very much for the comment. Yes, before April 2018 IPT was repeated in every 2 years. However, this analysis did not consider repeated IPT. Individuals were in IPT group if ever received IPT and non-IPT for those who never received IPT (Lines: 105-107).

Data collection

How did you assess nutritional status? What is the definition of each category?

How is ambulatory different from walking?

Do you have information on the previous history of TB?

Response: Thanks for the comment. Nutrition was obtained by calculating Body Mass Index (BMI) from weights and heights of clients.). The definitions were according to World Health Organization as follows: Underweight (<18.5kg/m2) Normal (18.5kg/m2), overweight (25 kg/m2) and obese (>30 kg/m2).

The study participants were newly enrolled PLHIV from January 2012 to December 2016. Those with TB before enrolment in HIV clinics were excluded from the cohort. Prior TB apart from TB with which a client reported to HIV clinic was not known.

The right categories are bedridden, ambulatory and working. The right correction has been done.

Analysis

Response:

How did you handle missing data?

Response: Thanks for the comment. The threshold for including a covariate into a multivariate model was lifted to P-value of a maximum of 0.2 (Lines 144-145) to include more covariates as suggested in the article given for reference. The distribution of missing was checked. Missing data had no effect on the outcome of interest; they were at random. If they were systematic we would apply manipulations such as imputation. Hence, the data analysis was done using the whole dataset.

How were the weights given? Was it simple inverse or did you use stabilized weights?

Response: Thanks for the comment. The weights were given using simple inverse (Line 129-134).

Result

Paragraph 2

“from private health facilities (84.36%).” This is not consistent with Table 1. 84.36% is from public facilities.

Response: Thank you very much for the comment. This has been rectified.

Paragraph 3

Did you find any difference in the number of people who were lost to follow-up or died between the two groups? How could that impact the analysis?

Response: Thank you very much for the response. The follow up duration in each of the group has been shown in the result section. Lost to follow up was not considered in this analysis.

Discussion

Paragraphs 2 and 3 seem repetitive. The discussion could also mention the durability of protection.

Response: Thank you very much for the comment. This has been corrected. In the discussion section.

Table 1.

Proportions of the weighted sample enrolled by year in the IPT group do not sum up to 100%.

Response: Thank you very much for the comment. This has been corrected

Reviewer #3: There is no statement on the ethical consideration that explains how to keep the confidentiality of the participants. Try to include a statement. It also needs some grammatical error corrections. both on the introduction and discussion.

Response: Thank you very much for the comments. Ethical consideration kept participants’ confidentiality by using only unique identification instead of their names. Ethical clearance has been reviewed to reflect the comment (Line 152-164).

Response: Thank you very much for the comment. The objective of the manuscript has been revised Back (Lines 14-15, 71-74).

Response: Thank you very much for the comment. Abstract, background, result, discussion and conclusion sections are aligned.

Response: Thank you very much for the comment. We have worked on the above (Lines 37-74). Tanzania started implementing 3Is in 2011. IPT uptake was repeated in every 2 years before April 2018. After April 2018, IPT was given only once.

.An explanation on the TB/HIV service delivery in particular IPT services in the health facilities in this 3 regions including TB screening process , diagnosis , treatment and follow up has also been included in the manuscript .The authors needs to be clear on the study population .In the data analysis section the author needs to clearly indicate how the 4 variables ( Age,sex, region WHO staging ) was achieved at, justify why IPW .A clear explanation on the propensity scores used and how this was achieved .There should be a step wise approach with clear formulae and outcomes .

Response: Thank you very much for the comment. A brief explanation on the TB/HIV service delivery in particular IPT services in the health facilities in this 3 regions, the TB screening process, diagnosis, treatment and follow up has been included in the manuscript (Lines: 78-89). The study population has been clearly stated (Lines: 105-107). How the propensity score model was constructed has been explained (Lines: 114-134). Justification for using IPTW has been given (Lines 69-74). Steps involved in the IPTW have been included in the manuscript (Lines:114-134). Formulae and outcomes used are shown below:

1. Notations for logistic regression for selection of covariates:

Logit(IPT)=a+b(Sex)+b(Age)+b(Functionalstatus)+b(ART)+b(BMI)+b(Nutrition)+b(HealthFacilitytype)+b(Region)+b(Health Facility ownership)+e

Logit(TB disease)= a+b(Sex)+b(Age)+b(Functional status)+b(ART)+b(BMI)+b(Nutrition)+b(Health Facility type)+b(Region)+b(Health Facility ownership)+e

Where a=Outcome at baseline, b=co-efficient of covariates, e=error term

2. Notations for propensity scores:

ATE=Expected ((IPT)-(Non-IPT))

Propensity Score (Probability of receiving IPT given a certain covariate), PS=Prob(IPT/Covariate)

3. Notations for model balance:

D=Prop(IPT)-Prop(Non-IPT)/√(PropIPT(1-PropIPT)+PropNon-IPT(1-Non-IPT))/2

4. Notations for propensity score weights:

PS weights=1/PS + 1(1-PS)

Where, 1/PS=Weight for IPT group, 1/(1-PS) =Weight for Non-IPT group

Response: Thank you very much for the comment. The result section has been revised to accommodate the suggested comments

In the discussion section, in the first paragraph the aspect of using IPTW to determine effectiveness of public health intervention has been previously used refer to the NIH study (Sheri A. Lippman et al .NIH ) it’s more of use of TB prevention and in this country setting that is limited .The author seems to have duplicate information on ‘IPT lowering TB incidence by 70% ‘ in the 2nd and 4th paragraph can this be revised .From the commencement of TB prevention in the HIV facilities from 2011 has the national TB program seen some changes like reduction in the TB/HIV co-infection rate ? . Can the author expound on the association of higher TB incidence in the variables: Male; not on ART; aging population; Nutrition status; higher numbers in 2016 and in the Dar es salaam region and the public health facilities of TB incidence. Basically the authors need to further expound on the findings of the current study in line with the results they got.

Thank you very much for the comment. Relevant corrections have been done in the discussion section.

Finally, perhaps the authors can strengthen the conclusion in line with the objective of the study perhaps inclusion on use of IPW in evaluating effectiveness of a public health intervention.

Thank you very much for the comment. The conclusion section has been revised (Lines: 296-299).

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

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

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

Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

Reviewer #4: Yes: Dr. Muthoni E. Karanja

Thank you very much for the comment. Figures have been uploaded in PACE.

Comments on the Plos One paper:

The paper attempted to study a very important question, well done for the initiative. Please find my following comments regarding the article below.

Response: Thank you very for the comment.

Abstract

Background: there is no statement that explains the magnitude of the problem (statement of the problem).

Response: Thank you very much for the comment. The magnitude of TB among people living with HIV has been included (Line 43-46)

Methods:

study setting and design not included on the methods section of the abstract, when are you going to say the IPT has no effect, reduces the effect or increases the effect, the decision criteria is not set on this section. Or the cutoff point is not placed here. Try to include it. In the methods of the abstract, some of the sections of the method of the abstract does not make sense it needs revision.

In the result of the abstract, one change that should be made revolves around the Results sections on the "incidence" is that incidence or prevalence??

Response: Thank you very much for the comment: The conclusion of effectiveness of IPT on reducing TB disease among PLHIV has been drawn in comparison with studies from other settings. There is no cutoff point. Relevant changes have been made in the abstract section to include study setting and design.

Data collection: the data collection technique is not included on the data collection section try to include it there.

Response: Thank you very much for the comment. Data collection technique is included (Lines 90-103).

Methods section:

Please clearly elaborate the following procedures: inclusion and exclusion criteria, sampling, methods for data capture and quality control. Any attempt to reduce internal and external biases, which confounders were considered? There is missing of eligibility criteria, Data collection, Handling and Tracking of Missing data, and Quality control.

Response: Thank you very much for the comment. The study included PLHIV enrolled in HIV clinics from January 2012 to December 2016 in 3 regions in Tanzania. The study excluded from analysis, PLHIV who had existing TB disease (on treatment) before HIV clinic enrolment (Lines 100-103).

The regions were conveniently sampled as they had high HIV and TB incidence. As data used for analysis were those of routine practices, there are mechanisms to make sure that routine data are of quality at routine program level. These include training of staff and ongoing capacity building through mentorship, supportive supervision and data quality assessment. Different measures have been taken to minimize biases. These include propensity score weighting and multivariate analysis. Missing data were examined and were not found to have significant effect and thus analysis was done for the whole sample.

Ethical consideration

There is no statement on the ethical consideration that explains how to keep the confidentiality of the participants. Try to include a statement.

Response: Thank you very much for the comment. A statement on study participant confidentiality has been added in the ethical consideration section (Line 153-164).

Discussion

You should include a paragraph in the discussion about the significance of your results and how this will inform preventative strategies in the future.

Response: Thank you very much for the comment. A sentence on the implication of study findings on the practice/policy on TBHIV prevention has been included (Line 278-283).

Attachment

Submitted filename: Responses)_Werner.pdf

Click here for additional data file.^{(426.3KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0254082.r004

Decision Letter 1

Katalin Andrea Wilkinson

26 Apr 2021

PONE-D-20-37236R1

Impact of Isoniazid Preventive Therapy on Tuberculosis incidence among people living with HIV; a secondary data analysis using Inverse Probability Weighting of individuals attending HIV care and treatment clinics in Tanzania.

PLOS ONE

Dear Dr. Maokola,

Please submit your revised manuscript by Jun 10 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:

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'.

If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.

We look forward to receiving your revised manuscript.

Kind regards,

Katalin Andrea Wilkinson, PhD

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.

[Note: HTML markup is below. Please do not edit.]

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 #2: (No Response)

Reviewer #4: (No Response)

**********

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

Reviewer #2: Yes

Reviewer #4: Yes

**********

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

Reviewer #2: Yes

Reviewer #4: Yes

**********

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

Reviewer #2: No

Reviewer #4: Yes

**********

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

Reviewer #2: Yes

Reviewer #4: Yes

**********

6. Review Comments to the Author

Reviewer #2: Thank you very much for revising the manuscript.

I only have a few minor comments below.

Line 100: “TB infection” usually refers to LTBI in the context of TB prevention and thus confusing.

Line 106: What do you mean by “at least one cycle”. Do you mean completion of 6-month? Isn’t all who started IPT included?

Lines 121-123 and Lines 130-132.

Reviewer #4: I appreciate the opportunity to review this manuscript which describes the use of Inverse Probability for Treatment Weighting (IPTW) to determine the relationship between IPT and TB incidence among PLHIV attending care. This will be a great addition especially in minimizing bias in non-experimental studies. The authors have addressed a number of corrections and suggestions which is very commendable. A few considerations to be looked into by the authors are as summarized below:

Abstract

The authors need to consider revising the background section its more of a statement rather a recommendation. The objectives are not smart as well. Line 33-34 is not necessary can the authors consider revision of that sentence.

Discussion

The authors should consider revising line 239 -244 a bit of repetition. They have explained some of the results as written in line 257 – 270 however, they need to further expound on the TB incidence rate why it is lower in private health facilities as depicted in the results section as well as the reason it is lowest in 2012 and increasing throughout the study.

Minor

The authors need to work on the grammatical errors and omissions throughout the whole document.

**********

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 #2: No

Reviewer #4: No

PLoS One. 2021 Jul 13;16(7):e0254082. doi: 10.1371/journal.pone.0254082.r005

Author response to Decision Letter 1

14 Jun 2021

Response to reviewers addressing all the comments has been attached in this submission as suggested and labelled "Response to reviewers"

Attachment

Submitted filename: Rebuttal Letter_Response to Reviewers.pdf

Click here for additional data file.^{(294.6KB, pdf)}

PLoS One. doi: 10.1371/journal.pone.0254082.r006

Decision Letter 2

Katalin Andrea Wilkinson

21 Jun 2021

PONE-D-20-37236R2

Dear Dr. Maokola,

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,

Katalin Andrea Wilkinson, PhD

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

PLoS One. doi: 10.1371/journal.pone.0254082.r007

Acceptance letter

Katalin Andrea Wilkinson

28 Jun 2021

PONE-D-20-37236R2

Dear Dr. Maokola:

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

Associate Professor Katalin Andrea Wilkinson

Academic Editor

PLOS ONE

Associated Data

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

Supplementary Materials

S1 Dataset

(ZIP)

Click here for additional data file.^{(1.6MB, zip)}

Attachment

Submitted filename: Responses to the editor.docx

Click here for additional data file.^{(15.5KB, docx)}

Attachment

Submitted filename: Peer review comments PONE-D-20-37236.docx

Click here for additional data file.^{(20.9KB, docx)}

Attachment

Submitted filename: plos one comments.docx

Click here for additional data file.^{(13KB, docx)}

Attachment

Submitted filename: Responses)_Werner.pdf

Click here for additional data file.^{(426.3KB, pdf)}

Attachment

Submitted filename: Rebuttal Letter_Response to Reviewers.pdf

Click here for additional data file.^{(294.6KB, pdf)}

Data Availability Statement

All relevant data are within the paper and its S1 Dataset.

[pone.0254082.ref001] 1.Solomon F. B., Angore B. N., Koyra H. C., Tufa E. G., Berheto T. M., and Admasu M., “Spectrum of opportunistic infections and associated factors among people living with HIV/AIDS in the era of highly active anti-retroviral treatment in Dawro Zone hospital: A retrospective study,” BMC Res. Notes, vol. 11, no. 1, pp. 1–7, 2018. doi: 10.1186/s13104-018-3707-9 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref002] 2.Dravid A. et al., “Incidence of tuberculosis among HIV infected individuals on long term antiretroviral therapy in private healthcare sector in Pune, Western India,” BMC Infect. Dis., vol. 19, no. 1, pp. 1–12, 2019. doi: 10.1186/s12879-019-4361-0 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref003] 3.Pape J. W., Jean S. S., Ho J. L., Hafner A., and Johnson W. D., “Effect of isoniazid prophylaxis on incidence of active tuberculosis and progression of HIV infection,” Lancet, vol. 342, no. 8866, pp. 268–272, Jul. 1993. doi: 10.1016/0140-6736(93)91817-6 [DOI] [PubMed] [Google Scholar]

[pone.0254082.ref004] 4.Geremew D., Endalamaw A., Negash M., Eshetie S., and Tessema B., “The protective effect of isoniazid preventive therapy on tuberculosis incidence among HIV positive patients receiving ART in Ethiopian settings: A meta-analysis,” BMC Infect. Dis., vol. 19, no. 1, pp. 1–9, 2019. doi: 10.1186/s12879-019-4031-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref005] 5.Sulis G., Roggi A., Matteelli A., and Raviglione M. C., “Tuberculosis: Epidemiology and control,” Mediterr. J. Hematol. Infect. Dis., vol. 6, no. 1, 2014. doi: 10.4084/MJHID.2014.070 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref006] 6.WHO, “HIV-Associated Tuberculosis,” World Health Organization@2019, 2019. [Online]. https://www.who.int/tb/areas-of-work/tb-hiv/tbhiv_factsheet.pd. [Accessed: 18-Apr-2020]. [Google Scholar]

[pone.0254082.ref007] 7.UNAIDS, “UNAIDS DATA. The Joint United Nations Programme on HIV/AIDS,” 2019. [PubMed] [Google Scholar]

[pone.0254082.ref008] 8.Majigo M. et al., “Prevalence and incidence rate of tuberculosis among HIV-infected patients enrolled in HIV care, treatment, and support program in mainland Tanzania,” Trop. Med. Health, vol. 48, no. 1, 2020. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref009] 9.WHO, “WHO policy on collaborative TB / HIV activities Guidelines for national programmes and other stakeholders. World Health Organization,” p. 36, 2004. [PubMed] [Google Scholar]

[pone.0254082.ref010] 10.WHO, “WHO Three I’s Meeting Intensified Case Finding (ICF), Isoniazid Preventive Therapy (IPT) and TB Infection Control (IC) for people living with HIV,” 2008.

[pone.0254082.ref011] 11.WHO, “Guidelines for intensified tuberculosis case-finding and isoniazid preventive therapy for people living with HIV in resource- constrained settings,” World Health Organization, vol. 66. pp. 37–39, 2012. [Google Scholar]

[pone.0254082.ref012] 12.NACP, “HIV care and treatment. National AIDS Control Program, Tanzania,” 2019. [Google Scholar]

[pone.0254082.ref013] 13.Maokola W. et al., “Coverage of isoniazid preventive therapy among people living with HIV; A retrospective cohort study in Tanzania (2012–2016),” Int. J. Infect. Dis., vol. 103, pp. 562–567, 2021. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref014] 14.MoHCDEC, United Republic of Tanzania Ministry of Health, community, gender, elderly and children National AIDS Control Programme (HSHSP IV) 2017–2022, no. July. 2017. [Google Scholar]

[pone.0254082.ref015] 15.Akolo C., Adetifa I., Shepperd S., and Volmink J., “Treatment of latent tuberculosis infection in HIV infected persons (Review),” Cochrane Database Syst. Rev., no. 1, 2010. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref016] 16.Melissa B., Courtney E., Surbhi M., Taylor K. N., and Anand D., “Use of isoniazid preventive therapy for TB among PLHIV,” HHS Public Access, vol. 155, no. 12, pp. 3007–3024, 2015. [Google Scholar]

[pone.0254082.ref017] 17.Rangaka M. X. et al., “Isoniazid plus antiretroviral therapy to prevent tuberculosis: A randomised double-blind, placebo-controlled trial,” Lancet, vol. 384, no. 9944, pp. 682–690, 2014. doi: 10.1016/S0140-6736(14)60162-8 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref018] 18.Tiruneh G., Getahun A., and Adeba E., “Assessing the Impact of Isoniazid Preventive Therapy (IPT) on Tuberculosis Incidence and Predictors of Tuberculosis among Adult Patients Enrolled on ART in Nekemte Town, Western Ethiopia: A Retrospective Cohort Study,” Interdiscip. Perspect. Infect. Dis., vol. 2019, 2019. doi: 10.1155/2019/1413427 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref019] 19.Ayele A. A. et al., “Self-reported adherence and associated factors to isoniazid preventive therapy for latent tuberculosis among people living with HIV/AIDS at health centers in Gondar town, North West Ethiopia,” Patient Prefer. Adherence, vol. 11, pp. 743–749, 2017. doi: 10.2147/PPA.S131314 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref020] 20.Sabasaba A., Mwambi H., Somi G., Ramadhani A., and Mahande M. J., “Effect of isoniazid preventive therapy on tuberculosis incidence and associated risk factors among HIV infected adults in Tanzania: A retrospective cohort study 11 Medical and Health Sciences 1117 Public Health and Health Services,” BMC Infect. Dis., vol. 19, no. 1, pp. 1–8, 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref021] 21.Golub J. E. et al., “The impact of antiretroviral therapy and isoniazid preventive therapy on tuberculosis incidence in HIV-infected patients in Rio de Janeiro, Brazil,” no. February, 2007. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref022] 22.Singal A. G., Higgins P. D. R., and Waljee A. K., “A primer on effectiveness and efficacy trials,” Clin. Transl. Gastroenterol., vol. 5, no. 2, pp. e45–4, 2014. doi: 10.1038/ctg.2013.13 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref023] 23.Austin P. C. and Stuart E. A., “Moving towards best practice when using inverse probability of treatment weighting (IPTW) using the propensity score to estimate causal treatment effects in observational studies,” Stat. Med., vol. 34, no. 28, pp. 3661–3679, 2015. doi: 10.1002/sim.6607 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref024] 24.Maokola W., Ngowi B., Lawson L., Mahande M., Todd J., and Msuya S., “Performance of and Factors Associated With Tuberculosis Screening and Diagnosis Among People Living With HIV: Analysis of 2012–2016 Routine HIV Data in Tanzania,” Front. Public Heal., vol. 7, no. 404, Feb. 2020. doi: 10.3389/fpubh.2019.00404 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref025] 25.NBS, “Tanzania Hiv Impact Survey (This) 2016–2017,” Tanzania HIV Impact Surv. 2016–2017, no. December 2017, pp. 2016–2017, 2018. [Google Scholar]

[pone.0254082.ref026] 26.NTLP, “Manual for the Management of Tuberculosis and Leprosy. Sixth Edition 2013,” 2013. [Google Scholar]

[pone.0254082.ref027] 27.Hazlett C., Maokola W., and Wulf D. A., “Inference without randomization or ignorability: A stability-controlled quasi-experiment on the prevention of tuberculosis,” no. July, pp. 1–18, 2020. [DOI] [PubMed] [Google Scholar]

[pone.0254082.ref028] 28.Garrido M. M. et al., “Methods for constructing and assessing propensity scores,” Health Serv. Res., vol. 49, no. 5, pp. 1701–1720, 2014. doi: 10.1111/1475-6773.12182 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref029] 29.Austin P. C., “An introduction to propensity score methods for reducing the effects of confounding in observational studies,” Multivariate Behav. Res., vol. 46, no. 3, pp. 399–424, 2011. doi: 10.1080/00273171.2011.568786 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref030] 30.Alan B., Wyss R., Layton B., and Til S., “Propensity Score Methods for Confounding Control in NonExperimental Research,” Circ Cardiovasc Qual Outcomes, vol. 6, no. 5, pp. 604–611, 2013. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref031] 31.Yirdaw K. D. et al., “Beneficial effect of isoniazid preventive therapy and antiretroviral therapy on the incidence of tuberculosis in people living with HIV in Ethiopia,” PLoS One, vol. 9, no. 8, 2014. doi: 10.1371/journal.pone.0104557 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref032] 32.Atey T. M., Bitew H., Asgedom S. W., Endrias A., and Berhe D. F., “Does Isoniazid Preventive Therapy Provide Better Treatment Outcomes in HIV-Infected Individuals in Northern Ethiopia? A Retrospective Cohort Study,” AIDS Res. Treat., vol. 2020, 2020. doi: 10.1155/2020/7025738 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref033] 33.Juszkiewicz K., Jarosz M. J., Włoszczak-Szubzda A., and Głowacka M., “Comparative analysis of the effectiveness of tuberculosis prophylaxis in patients with HIV/AIDS treated with isoniazid,” Ann. Agric. Environ. Med., vol. 26, no. 3, pp. 462–467, 2019. doi: 10.26444/aaem/106765 [DOI] [PubMed] [Google Scholar]

[pone.0254082.ref034] 34.Golub J. et al., “Isoniazid preventive therapy, HAART and tuberculosis risk in HIV-infected adults in South Africa: a prospective cohort,” AIDS, vol. 23, no. 5, pp. 631–636, 2009. doi: 10.1097/QAD.0b013e328327964f [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref035] 35.Semu M., Fenta T. G., Medhin G., and Assefa D., “Effectiveness of isoniazid preventative therapy in reducing incidence of active tuberculosis among people living with HIV / AIDS in public health facilities of Addis Ababa, Ethiopia: a historical cohort study,” BMC Infect. Dis., pp. 1–8, 2017. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref036] 36.Chang C. et al., “Tuberculosis Incidence and Risk Factors Among Human Immunodeficiency Virus (HIV)-Infected Adults Receiving Antiretroviral Therapy in a Large HIV Program in Nigeria,” OFID, 2015. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref037] 37.Pandis N., “Bias in observational studies,” Am. J. Orthod. Dentofac. Orthop., vol. 145, no. 4, pp. 542–543, 2014. doi: 10.1016/j.ajodo.2014.01.008 [DOI] [PubMed] [Google Scholar]

[pone.0254082.ref038] 38.Horton K. C., Macpherson P., Houben R. M. G. J., White G., and Corbett E. L., “Sex Differences in Tuberculosis Burden and Notifications in Low- and Middle-Income Countries: A Systematic Review and Meta- analysis,” vol. 21, pp. 1–23, 2016. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref039] 39.Nhamoyebonde S. and Leslie A., “Biological differences between the sexes and susceptibility to tuberculosis,” J. Infect. Dis., vol. 209, no. SUPPL. 3, 2014. doi: 10.1093/infdis/jiu147 [DOI] [PubMed] [Google Scholar]

[pone.0254082.ref040] 40.Lawn S. D., Kranzer K., and Wood R., “Antiretroviral Therapy for Control of the HIV-associated Tuberculosis Epidemic in Resource-Limited Settings,” Clin. Chest Med., vol. 30, no. 4, pp. 685–699, 2009. doi: 10.1016/j.ccm.2009.08.010 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref041] 41.Suthar A. B. et al., “Antiretroviral therapy for prevention of tuberculosis in adults with hiv: A systematic review and meta-analysis,” PLoS Med., vol. 9, no. 7, 2012. doi: 10.1371/journal.pmed.1001270 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref042] 42.Hanrahan C. F. et al., “Body mass index and risk of tuberculosis and death,” Aids, vol. 24, no. 10, pp. 1501–1508, 2010. doi: 10.1097/QAD.0b013e32833a2a4a [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref043] 43.Pednekar M. S., Hakama M., Hebert J. R., and Gupta P. C., “Association of body mass index with all-cause and cause-specific mortality: Findings from a prospective cohort study in Mumbai (Bombay), India,” Int. J. Epidemiol., vol. 37, no. 3, pp. 524–535, 2008. doi: 10.1093/ije/dyn001 [DOI] [PubMed] [Google Scholar]

[pone.0254082.ref044] 44.Mpagama S. G. et al., “Gridlock from diagnosis to treatment of multidrug-resistant tuberculosis in Tanzania: Low accessibility of molecular diagnostic services and lack of healthcare worker empowerment in 28 districts of 5 high burden TB regions with mixed methods evaluation,” BMC Public Health, vol. 19, no. 1, pp. 1–11, 2019. doi: 10.1186/s12889-019-6720-6 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref045] 45.Gunda D. W. et al., “Prevalence and risk factors of active TB among Adult HIV Patients Receiving ART in Northwestern Tanzania: A Retrospective Cohort Study,” Can. J. Infect. Dis. Med. Microbiol., vol. 2018, 2018. doi: 10.1155/2018/1346104 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref046] 46.Lawn S. D., Badri M., and Wood R., “Tuberculosis among HIV-infected patients receiving HAART: Long term incidence and risk factors in a South African cohort,” Aids, vol. 19, no. 18, pp. 2109–2116, 2005. [DOI] [PubMed] [Google Scholar]

[pone.0254082.ref047] 47.Zuiga J., Torres-García D., Santos-Mendoza T., Rodriguez-Reyna T. S., Granados J., and Yunis E. J., “Cellular and humoral mechanisms involved in the control of tuberculosis,” Clin. Dev. Immunol., vol. 2012, 2012. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref048] 48.Corbett E. and MacPherson P., “Tuberculosis screening in high human immunodeficiency virus prevalence settings: turning promise into reality,” Int J Tuberc Lung Dis, vol. 17, no. 9, pp. 1125–1138, 2013. doi: 10.5588/ijtld.13.0117 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref049] 49.Gelalcha A. G., Kebede A., and Mamo H., “Light-emitting diode fluorescent microscopy and Xpert MTB/RIF^® assay for diagnosis of pulmonary tuberculosis among patients attending Ambo hospital, west-central Ethiopia,” BMC Infect. Dis., vol. 17, no. 1, pp. 1–9, 2017. doi: 10.1186/s12879-017-2701-5 [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref050] 50.Steingart K. R. et al., “Fluorescence versus conventional sputum smear microscopy for tuberculosis: a systematic review,” Lancet Infect. Dis., vol. 6, no. 9, pp. 570–581, 2006. doi: 10.1016/S1473-3099(06)70578-3 [DOI] [PubMed] [Google Scholar]

[pone.0254082.ref051] 51.NTLP, “Tubeculosis Prevalence in Tanzania,” National Tuberculosis and Leprosy Program Tanzania, 2012. [Online]. https://ntlp.go.tz/tuberculosis/tb-prevalence/. [Accessed: 20-May-2021].

[pone.0254082.ref052] 52.Siddaiah A. et al., “Tuberculosis notification in a private tertiary care teaching hospital in South India: A mixed-methods study,” BMJ Open, vol. 9, no. 2, pp. 1–13, 2019. [DOI] [PMC free article] [PubMed] [Google Scholar]

[pone.0254082.ref053] 53.Stallworthy G., Dias H. M., and Pai M., “Quality of tuberculosis care in the private health sector,” J. Clin. Tuberc. Other Mycobact. Dis., vol. 20, p. 100171, 2020. doi: 10.1016/j.jctube.2020.100171 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Impact of Isoniazid Preventive Therapy on Tuberculosis incidence among people living with HIV: A secondary data analysis using Inverse Probability Weighting of individuals attending HIV care and treatment clinics in Tanzania

Werner M Maokola

Bernard J Ngowi

Michael J Mahande

Jim Todd

Masanja Robert

Sia E Msuya

Roles

Abstract

Background

Objectives

Methods

Results

Conclusion

Background

Methods

Study design and study population

Study setting

Data collection

Data analysis

Ethical consideration

Results

(1) Baseline characteristics of study participants

Fig 1. Flow diagram for Isoniazid Preventive Therapy and TB diagnosis among PLHIV.

Table 1. Baseline characteristics of study participants, N = 161,417.

(2) Balance of covariates after IPTW

Table 2. Balance between unweighted and weighted samples after Inverse Probability of Treatment Weighting.

(3) TB cases, follow up time and TB incidence rate

Table 3. The incidence of TB cases, total person-year and TB rates among 24,800 PLHIV who received IPT and a weighted sample of those who did not receive IPT.

Fig 2. Kaplan Meier graph showing cumulative Tuberculosis incidence depending on the status of Isoniazid Preventive Therapy.

(4) Risk factors for TB disease

Table 4. Risk factors for TB disease using weighted sample.

Discussion

Conclusion

Supporting information

Acknowledgments

Abbreviations

Data Availability

Funding Statement

References

Author response to previous submission

Decision Letter 0

Katalin Andrea Wilkinson

Roles

Author response to Decision Letter 0

Decision Letter 1

Katalin Andrea Wilkinson

Roles

Author response to Decision Letter 1

Decision Letter 2

Katalin Andrea Wilkinson

Roles

Acceptance letter

Katalin Andrea Wilkinson

Roles

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases