Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania: The prospective Kilombero and Ulanga antiretroviral cohort.

BACKGROUND: In sub-Saharan Africa, diagnosis and management of extrapulmonary tuberculosis (EPTB) in people living with HIV (PLHIV) remains a major challenge. This study aimed to characterize the epidemiology and risk factors for poor outcome of extrapulmonary tuberculosis in people living with HIV (PLHIV) in a rural setting in Tanzania.
METHODS: We included PLHIV >18 years of age enrolled into the Kilombero and Ulanga antiretroviral cohort (KIULARCO) from 2013 to 2017. We assessed the diagnosis of tuberculosis by integrating prospectively collected clinical and microbiological data. We calculated prevalence- and incidence rates and used Cox regression analysis to evaluate the association of risk factors in extrapulmonary tuberculosis (EPTB) with a combined endpoint of lost to follow-up (LTFU) and death.
RESULTS: We included 3,129 subjects (64.5% female) with a median age of 38 years (interquartile range [IQR] 31-46) and a median CD4+ cell count of 229/μl (IQR 94-421) at baseline. During the median follow-up of 1.25 years (IQR 0.46-2.85), 574 (18.4%) subjects were diagnosed with tuberculosis, whereof 175 (30.5%) had an extrapulmonary manifestation. Microbiological evidence by Acid-Fast-Bacillus stain (AFB-stain) or Xpert® MTB/RIF was present in 178/483 (36.9%) patients with pulmonary and in 28/175 (16.0%) of patients with extrapulmonary manifestations, respectively. Incidence density rates for pulmonary Tuberculosis (PTB and EPTB were 17.9/1000person-years (py) (95% CI 14.2-22.6) and 5.8/1000 py (95% CI 4.0-8.5), respectively. The combined endpoint of death and LTFU was observed in 1058 (33.8%) patients, most frequently in the subgroup of EPTB (47.2%). Patients with EPTB had a higher rate of the composite outcome of death/LTFU after TB diagnosis than with PTB [HR 1.63, (1.14-2.31); p = 0.006]. The adjusted hazard ratios [HR (95% CI)] for death/LTFU in EPTB patients were significantly increased for patients aged >45 years [HR 1.95, (1.15-3.3); p = 0.013], whereas ART use was protective [HR 0.15, (0.08-0.27); p <0.001].
CONCLUSIONS: Extrapulmonary tuberculosis was a frequent manifestation in this cohort of PLHIV. The diagnosis of EPTB in the absence of histopathology and mycobacterial culture remains challenging even with availability of Xpert® MTB/RIF. Patients with EPTB had increased rates of mortality and LTFU despite early recognition of the disease after enrollment.

Introduction

Tuberculosis (TB) remains a leading cause of death, especially in patients co-infected with HIV. Of the 10 million patients diagnosed with TB globally in 2017, 9% were co-infected with HIV. Of these, 72% live in Africa and contribute 84% of the 300’000 deaths [1]. Tanzania is one of the thirty high-endemic countries with an estimated TB incidence rate of 269/100’000 in the general population, an HIV-TB coinfection rate of 31% and a mortality rate in HIV-co-infected patients of 39/100’000 [1].

While TB is primarily a pulmonary disease, extrapulmonary manifestations account for 14% of incident TB cases worldwide [1]. In countries with a high HIV/TB co-infection rate such as Tanzania, 20% of incident TB manifest as extrapulmonary TB (EPTB) [1]. TB can affect any organ—however, lymph nodes and pleura are the most frequent localizations [2, 3]. In African settings TB lymphadenitis has accounted for 61%–78% and TB pleurisy for 10.6% of EPTB cases [4-6].

Diagnosis of EPTB remains challenging in resource-limited settings, as clinical manifestations are diverse, microbiological testing depends on invasive procedures and the gold standard of mycobacterial culture or supporting histopathology is mostly unavailable. The low bacillary load in tissues leads to poor sensitivity of microscopy for acid-fast bacilli (AFB) [7]. In a recent metanalysis on a wide range of different samples including cerebrospinal fluid, lymph nodes and a variety of tissues of patients with suspected EPTB, Xpert® MTB/RIF showed a high specificity of ≥ 98% in cerebrospinal fluid, pleural fluid, urine, and peritoneal fluid compared to culture, whereas the sensitivity ranged from 31% in pleural tissue to> 80% in urine and bone or joint fluid and tissue and 97% in bone or joint fluid compared to culture [8].

This low sensitivity of microbiological tests and the lack of diagnostic tools for important differential diagnoses of EPTB, e.g. malignancy or heart failure in case of pleural effusions [9], result in diagnostic uncertainty. As a consequence, many patients with compatible symptoms receive anti-tuberculous treatment without confirmatory testing [10], resulting in overtreatment of tuberculosis, and underdiagnosis of alternative conditions [11, 12].

Data on outcome and predictors of survival are scarce and most knowledge comes from retrospective studies. Poor outcomes have been reported in patients with central nervous manifestations [13], lymphopenia [14], older age and late presentation [15].

Our study aimed to characterize the epidemiology of EPTB in people living with HIV (PLHIV) in a rural setting in Tanzania, and to evaluate risk factors of poor outcomes such as LTFU or death and predictors for this outcome.

Methods

Study site and patient population

For this prospective study, we included all patients aged ≥18 years enrolled into the Kilombero and Ulanga Antiretroviral Cohort (KIULARCO) between January 1st, 2013 until December 31st, 2017 who completed a baseline evaluation and at least one clinical follow-up. Exclusion criteria were lack of informed consent, no follow-up visits or age <18years.

The KIULARCO is an ongoing cohort of HIV-infected patients in care at the Chronic Diseases Clinic Ifakara (CDCI) located at the St. Francis Referral Hospital in the southwest of Tanzania. Since its starts 2005, KIULARCO has enrolled more than 10,000 consenting patients with approximately 4,000 patients currently under active follow-up. The CDCI provides services for HIV according to guidelines issued by the national AIDS control program (NACP). While initially treatment guidelines recommended start of cART for patients with an HIV infection WHO stage III/IV or CD4 cell count below 350cells/ul [16], the CD4 threshold was adapted to 500cells/ul in 2013 [17] and removed to allow treatment for all in 2015 [18].

Within routine care, stable patients are assessed by a clinician 4 times per year. During clinical visits, information on demographics, clinical parameters, co-morbidities, prescription of cART and co-medications, adherence and laboratory monitoring are entered into a customized electronic clinical record system designed for subsequent scientific analysis (OpenMRS, http://openmrs.org) [19, 20]. In 2012, the clinic integrated TB services and implemented systematic screening for TB with the World Health Organization (WHO) symptom screening tool and Xpert® MTB/RIF for patients with suspected TB (Cepheid, USA) [21-24]. In patients suspected of PTB, sputum smear and, in patients with EPTB, urine or a sample from a sterile site is examined by bacilloscopy and Xpert® MTB/RIF analysis. In addition, from July 2016 to June 2017, a prospective observational study on the value of sonography to rule out tuberculosis was performed at St. Francis Referral Hospital according to the Focused Assessment with Sonography for HIV and Tuberculosis protocol (FASH) [25]. The study included HIV-positive and -negative patients with symptoms of TB and comprised performance of sonography to detect pleural or cardiac effusion, tuberculoma of liver and spleen, ascites, abdominal lymphadenopathy and ileum wall thickening. Xpert®MTB/RIF testing from sputum, urine samples and sterile fluids (thoracentesis, pericardiocentesis, ascites tap) improving standards for diagnosis of TB.

Definitions

To define PTB and EPTB, the International Classification of disease (ICD-10) [26] code and results from microbiological tests were used (S1 Table). Due to the unavailability of a local pathology service, no histopathological features were included in the disease definitions.

Microbiologically confirmed PTB was diagnosed, if a sputum sample was positive or an ICD-10 code for PTB (A15.x and A16.x except A15.6 and A16.5) was documented, and TB treatment was initiated 1 week before until 3 months after the working diagnosis of suspected TB. Microbiologically confirmed EPTB was diagnosed, if acid-fast bacilli on microscopy or Xpert® MTB/RIF were positive from an extrapulmonary site. Additionally, if an ICD-code for TB pleurisy (A15.6) was documented and anti-TB treatment was started 1 week before until 3 months after the working diagnosis, the infection was considered as confirmed. Microbiologically confirmed combined PTB and EPTB was defined as either a) presence of acid-fast bacilli/positive Xpert MTB/RIF from sputum and A15.6, A17, A18 or A19 or b) presence of acid-fast bacilli/positive Xpert MTB/RIF from a sterile site and cough or infiltrate on a chest x-ray without an alternative explanation.

Clinical PTB was defined as ICD-10 code A16 (excluding A16.5) without microbiological confirmation and start of TB treatment 1 week before until 3 months after working diagnosis of suspected TB. Clinical EPTB was defined as ICD-10 code A16.5, A17, A18, A19 without microbiological confirmation and without cough or infiltrate on chest x-ray, and start of TB treatment 1 week before until 3 months after working diagnosis of suspected TB.

Combined clinical PTB and EPTB was defined as A16.5, A17, A18, A19 and presence of cough or infiltrate on chest x-ray without microbiological confirmation, and initiation of an anti-tuberculous treatment starting 1 week before until 3 months after an established working diagnosis.

No presence of tuberculosis was defined as absence of positive microbiological results, ICD-10 code for tuberculosis and no initiation of anti-tuberculosis therapy.

Cases of TB diagnosed during the first 90 days of observation after enrollment were judged as prevalent at enrolment to allow for delays in diagnoses in order to prevent over classification of incident cases. Group descriptions using the term “extrapulmonary manifestation” include patients in the EPTB as well as the EPTB/PTB group.

Anemia was defined as ICD-10 codes D50-D64.9 or by a hemoglobin level below 12g/l or 11g/l for men and women, respectively. Arterial hypertension was defined as ICD-10 codes I10—I15 or measured blood pressure of >140/90mmHg upon two consecutive measurements or active antihypertensive treatment. Undernutrition was defined as ICD-10 codes E44-E46 or a body mass index (BMI) <18.5kg/m2, obesity as E66.0-E66.9 or a BMI >30.0kg/m2. Acute kidney failure was diagnosed by ICD-10 codes N17.0–17.9, chronic kidney failure by N18.0–18.9 or an uninterrupted estimated glomerular filtration rate (according to the CKD-EPI formula) <60ml/min/1.73m2 for > 3 months.

Patients were considered being lost to follow-up (LTFU) if they did not present to the clinic within 60 days after their last scheduled appointment. We decided to use a composite clinical outcome of death and LTFU due to a significant rate of LTFU in our cohort and an assumed high mortality in those patients. [27].

Data management and analysis

All included patients were assigned to the 4 following groups: PTB, EPTB, combined PTB and EPTB and no TB. Continuous variables were summarized using median and interquartile range and categorical variables with counts and frequencies. Comparisons of continuous and categorical variables were done using the Mann–Whitney U test and the chi-square test, respectively. Prevalence and incidence density rates (i.e. count of incident cases per 1000py of subjects at risk) were calculated including confirmed and clinically diagnosed cases of tuberculosis. Kaplan–Meier estimates were used to plot cumulative survival probabilities. An univariable Cox proportional hazard model was used to model time to the composite outcome of lost to follow-up (LTFU) and death after TB diagnosis in the three subgroups with TB. Univariable and multivariable Cox proportional hazards models were fitted for patients with EPTB (period starting from the date of first diagnosis of EPTB) to explore associations of a priori defined variables (sex, age, CD4+ cell count at baseline, WHO stage at baseline, cART and CNS manifestations of TB) with the composite outcome of LTFU and death. The age variable was dichotomized at the upper quartile of the distribution of the cohort. The proportional hazard assumption was checked using Schoenfeld residuals. Missing data were excluded (complete case analysis). All statistical analyses were performed using Stata 12.1 (StataCorp, USA).

Ethical considerations

All participants involved in this study gave written informed consent for the collection, storage and use of clinical data for research purposes within KIULARCO. The study protocol of KIULARCO has been approved by the Ifakara Health Institute Institutional Review Board, the National Institute of Medical Research in Tanzania, the Tanzanian Commission of Science and Technology as well as the Ethics committee of Northwest and Central Switzerland.

Results

Study population

In total, 3,620 patients were enrolled into KIULARCO between January 1st 2013 and December 31st 2017. Of these, we excluded 363 patients <18 years of age and 128 patients without any follow-up visits, resulting in 3,129 patients included in the final analysis (Fig 1). No characterization of the 128 patients excluded was done due to high rates of missing values. The median follow-up time was 1.25 years (IQR 0.46–2.85, range 3 days to 5 years) resulting in a total of 5370 person-years of follow-up.

Fig 1

Flowchart of patients included in the study.

Patients screened and included in the study. After inclusion, patients were allocated to 4 groups: patients with no tuberculosis (no TB), patients with pulmonary Tuberculosis (PTB), patients with extrapulmonary tuberculosis (EPTB) and patients with pulmonary and extrapulmonary tuberculosis. LTFU, lost to follow-up.

Baseline characteristics of patients at the time of enrolment into KIULARCO according to TB group are shown in Table 1. The median age ranged from 36.5 years (IQR 31.3, 42.6) in the EPTB group to 39.9 years (IQR 34.0, 46.8) in the PTB group. The majority of patients (64.7%) were females, only the subgroup of patients with combined PTB and EPTB comprised more males (54.8%). The HIV infection at enrolment was more advanced in patients with a consecutive diagnosis of TB at any location: WHO stage 3/4 was attributed to 34.7% in the no TB group versus 79.7%, 75.9% and 85.7% of the PTB, EPTB and PTB/EPTB group, respectively. The highest median CD4+ cell count was observed in the no TB group with 262 cells/μl, whereas in all other groups the median count was <200 cells/μl (113, 159 and 128 cells/μl in the PTB, EPTB and PTB/EPTB group, respectively). Patients with EPTB were more frequently married and less frequently smokers.

Table 1

Baseline characteristics.

	EPTB	PTB	PTB and EPTB	no TB	p-value
N (total = 3129)	91	399	84	2555
Microbiologically confirmed TB	8 (8.8%)	144 (36.1%)	34 (40.4%)£, 20 (23.8%)$	-
Positive Xpert® MTB/RIF	7 (7.7%)	84 (21.0%)	16 (19%)£ / 12 (14.3%)$	-
Year of registration					<0.001
2013	15 (16.5%)	57 (14.3%)	8 (9.5%)	332 (13.0%)
2014	16 (17.6%)	112 (28.1%)	17 (20.2%)	476 (18.6%)
2015	26 (28.6%)	133 (33.3%)	32 (38.1%)	630 (24.7%)
2016	17 (18.7%)	64 (16.0%)	9 (10.7%)	548 (21.4%)
2017	17 (18.7%)	33 (8.3%)	18 (21.4%)	569 (22.3%)
Age, years, median (IQR)	36.5 (31.3, 42.6)	39.9 (34.0, 46.8)	39.9 (33.6, 45.5)	38.0 (31.2, 46.2)	0.007
Sex, female	55 (60.4%)	214 (53.6%)	38 (45.2%)	1716 (67.2%)	<0.001
Marital status					0.001
Married/living in relationship	54 (59.3%)	205 (51.4%)	54 (64.3%)	1581 (61.9%)
Living alone	37 (40.7%)	194 (48.6%)	30 (35.7%)	974 (38.1%)
Smoking, current	8 (8.8%)	37 (9.3%)	7 (8.3%)	102 (4.0%)	<0.001
Missing information	2 (2.2%)	14 (3.5%)	2 (2.4%)	233 (9.1%)
Alcohol consumption, current	14 (15.4%)	67 (16.8%)	9 (10.7%)	297 (11.6%)	0.12
Missing information	2 (2.2%)	14 (3.5%)	2 (2.4%)	233 (9.1%)
HIV WHO stage					<0.001
1	14 (15.4%)	45 (11.3%)	9 (10.7%)	1086 (42.5%)
2	7 (7.7%)	29 (7.3%)	2 (2.4%)	385 (15.1%)
3	27 (29.7%)	238 (59.6%)	37 (44.0%)	588 (23.0%)
4	42 (46.2%)	80 (20.1%)	35 (41.7%)	299 (11.7%)
Missing information	1 (1.1%)	7 (1.8%)	1 (1.2%)	197 (7.7%)
CD4+ cell count (/μl)					<0.001
<100	30 (33.0%)	160 (40.1%)	29 (34.5%)	459 (18.0%)
100–199	21 (23.1%)	67 (16.8%)	20 (23.8%)	387 (15.1%)
200–499	25 (27.5%)	83 (20.8%)	21 (25.0%)	837 (32.8%)
> = 500	7 (7.7%)	33 (8.3%)	2 (2.4%)	439 (17.2%)
Missing information	8 (8.8%)	56 (14.0%)	12 (14.3%)	433 (16.9%)
CD4+ count (/μl), median (IQR)	159 (60, 303)	113 (49, 280)	128 (54, 220)	262 (117, 450)	<0.001
Comorbidities
Anemia	72 (80.0%)	292 (73.2%)	72 (85.7%)	1189 (46.6%)	<0.001
Thrombocytopenia	15 (16.7%)	58 (14.5%)	13 (15.5%)	300 (11.8%)	0.18
Undernutrition	21 (23.3%)	151 (37.8%)	24 (28.6%)	359 (14.1%)	<0.001
Obesity	1 (1.1%)	11 (2.8%)	2 (2.4%)	136 (5.3%)	0.030
Arterial Hypertension	10 (11.1%)	40 (10.0%)	10 (11.9%)	377 (14.8%)	0.059
Cryptococcosis	3 (3.3%)	8 (2.0%)	1 (1.2%)	56 (2.2%)	0.80
Viral hepatitis	4 (4.4%)	26 (6.5%)	6 (7.1%)	140 (5.5%)	0.73
Acute kidney failure	5 (5.6%)	9 (2.3%)	6 (7.1%)	33 (1.3%)	<0.001
Chronic kidney failure	0 (0.0%)	2 (0.5%)	2 (2.4%)	21 (0.8%)	0.28
Malaria	8 (8.9%)	55 (13.8%)	10 (11.9%)	206 (8.1%)	0.002
Lower respiratory tract infection	4 (4.4%)	60 (15.0%)	7 (8.3%)	195 (7.6%)	<0.001

EPTB, extrapulmonary tuberculosis; IQR, interquartile range; PTB, pulmonary tuberculosis; TB, tuberculosis; WHO, world health organisation

£ positive sputum sample;

$ positive extrapulmonary sample

Regarding comorbidities within the first three months after enrolment, anemia was highly prevalent in all groups, but more so in patients with TB with the highest prevalence in the PTB/EPTB group with up to 85.7%. Undernutrition was also more prevalent in TB groups (no TB 14.1%, PTB 37.8%, EPTB 23.3%, PTB/EPTB 28.6%).

Prevalence and incidence of EPTB, PTB and combined PTB/EPTB

Overall, 574 (18.4%) patients were diagnosed with confirmed or clinical TB at any localization (Fig 1). An extrapulmonary manifestation was observed in 175 (5.6%) patients, whereof 84 (48%) had concurrent pulmonary TB (PTB and EPTB group) and 91 (52%) no signs of pulmonary TB (EPTB group). Exclusive pulmonary manifestations were documented in 399 (12.8%) patients (PTB group).

The diagnosis of EPTB was made a median of 3.5 (IQR 1–21.5, range 0–1181) days and PTB at 2 (IQR 1–17, range 0–1296) days after enrolment. Most cases of TB were diagnosed during the first 90 days of observation and thus classified as prevalent at enrolment: this was the case in 334 (83.7%) in PTB, 78 (85.7%) in EPTB and 71 (84.5%) in PTB/EPTB. Tuberculosis diagnoses occurring 3 months or later after enrolment (incident cases) were diagnosed at an incidence density rate of 17.9/1000py (95% CI 14.2–22.6) for PTB and 5.8/1000py (95% CI 4.0–8.5) for EPTB corresponding to 5 cases of PTB, and 13 cases of EPTB and EPTB/PTB each.

Analyzing the time point of diagnosis of TB in relation to start of cART, in the majority of patients (406/508; 71.8%) TB was diagnosed before start of cART (Fig 2). No further information from the clinical notes concerning possible TB-associated immune reconstitution inflammatory syndrome (TB-IRIS) was available. In the subset of patients with initiation of cART ahead of a diagnosis of an incident case of TB, the median time from initiation of cART to the diagnosis of PTB and EPTB was 285 days (IQR 128–659) and 305 days (IQR 114–752, p = 0.78), respectively, possibly representing unmasking IRIS cases.

Fig 2

Interval between start of antiretroviral treatment and diagnosis of tuberculosis.

(A) extrapulmonary tuberculosis (EPTB), (B) pulmonary tuberculosis (PTB). Time point “0” denotes the initiation of cART, negative values indicate that the diagnosis of TB was preceding the initiation of cART.

Clinical presentation and microbiological testing

Affected organs in the 175 patients (multiple per patient possible) diagnosed with EPTB or PTB/EPTB were pleural space in 42 (24.0%), lymph node in 41 (23.4%), pericardium in 32 (18.3%), central nervous system in 21 (12%), urogenital tract in 18 (10.3%), peritoneum in 17 (9.7%), miliary in 13 (7.4%), bone in 2 (1.1%) and other in 21 (12.0%) of patients.

In total, 178/483 (36.9%) of patients with a pulmonary manifestation (i.e. the PTB and the combined PTB/EPTB group) and 28/175 (16.0%) of patients with an extrapulmonary manifestation were confirmed microbiologically (Table 1).

In total, we tested 1,241 samples (of 807 patients) with Xpert® MTB/RIF, whereof 500 (40.2%) were of extrapulmonary origin. Overall, 157/1241 (12.7%) samples analyzed were positive. Sputum samples were positive in 132/741 (17.8%) samples, extrapulmonary samples in 25/500 (5.0%) samples (Table 2). Over the study period, the number of performed Xpert® MTB/RIF tests per year increased for all materials with maximum usage in 2017 (S1 Dataset).

Table 2

Count and proportion of positive GeneXpert MTB/RIF by patient group (multiple tests per patients possible).

	EPTB	PTB	PTB and EPTB	No TB	Total
Sputum	0/28	106/275 (38.5%)	26/42 (61.9%)	0/396	132/741 (17.8%)
CSF	2/10 (20%)	0/12	0/9	0/72	2/103 (1.9%)
Pleural fluid	0/6	0/9	5/18 (27.7%)	0/0	5/33 (15.2%)
Ascitic fluid	1/4 (25%)	0/0	0/3	0/11	1/18 (5.6%)
Urine	4/24 (16%)	0/85	13/46 (28.3%)	0/188	17/343 (5%)
Lymph node	0/0	0/0	0/1	0/2	0/3

multiple tests per patient possible

CSF, cerebrospinal fluid; EPTB, extrapulmonary tuberculosis; PTB, pulmonary tuberculosis; TB, tuberculosis

Treatment and outcome

Combined antiretroviral therapy (cART) according to national guidelines was initiated in 2,786 (89.0%) of included patients after a median of 6 days (IQR 1–19 days, 90th percentile 102 days) from enrolment in the cohort. Out of the 574 patients with any diagnosis of TB, 508 (88.5%) started cART after a median of 23 (IQR 10–56) days. In the subset of patients with EPTB (including PTB/EPTB), 148 (82%) started cART after a median of 20 (IQR 7–40) days after enrolment. The most frequent combinations of antiretrovirals initiated were tenofovir disoproxil/lamivudine/efavirenz in 1,911 (68.5%) and tenofovir disoproxil/emtricitabine/efavirenz in 423 (15.2%) of patients started on cART.

Table 3 and Fig 3 show the numbers of patients who died or were lost to follow-up. Overall, 154 (4.9%) patients died (14.3% of patients with EPTB, 8.5% of patients with PTB and 3.7% of patients without TB). The combined endpoint of death/LTFU was most frequent in patients with EPTB (47.2% for EPTB alone, 46.4% for PTB/EPTB). The crude hazard ratios [HR (95% CI)] for death/LTFU after a diagnosis of TB were increased in the EPTB [HR 1.63, (1.14–2.31); p = 0.006] and the combined EPTB and PTB subgroup [HR 1.65, (1.15–2.46); p = 0.006] in comparison with the PTB subgroup (Fig 3).

Table 3

Composite outcome of death/LTFU.

	EPTB (n = 91)	PTB (n = 399)	EPTB and PTB (n = 84)	No TB (n = 2555)	p-value
Dead/LTFU	43 (47.2%)	137 (34.3%)	39 (46.4%)	839 (32.8%)	0.003
Dead	13 (14.3%)	34 (8.5%)	12 (14.3%)	95 (3.7%)	<0.001

EPTB, extrapulmonary tuberculosis; LTFU, lost to follow-up; PTB, pulmonary tuberculosis; TB, tuberculosis

p-values indicated are derived by multiple group comparison using chi-square tests.

Fig 3

Kaplan-Meier curves for composite outcome of lost to follow-up/dead in patients with tuberculosis.

Cox proportional hazard models were fitted using the data of all 175 with an EPTB (EPTB and PTB/EPTB group) to analyze factors associated with the composite outcome of death and LTFU (Table 4). In both the univariable and multivariable model, patients with EPTB, who have ever received cART had a significantly decreased risk of death/LTFU compared to patients who were not yet on cART (HR 0.15, 95% CI 0.08–0.27). The multivariable hazard ratios for death/LTFU were significantly increased for patients aged >45 years (HR 1.95, 95% CI 1.15–3.3).

Table 4

Cox proportional hazard model for composite outcome of LTFU/death in EPTB patients (with or without pulmonary manifestation).

	Univariable		Multivariable
	HR (95% CI)	p	HR (95% CI)	p
Female sex a	0.86 (0.52, 1.41)	0.541	0.86 (0.52, 1.41)	0.541
CD4+ cell count at baseline [cells/ul)
<200	Reference		Reference
≥200	0.87 (0.53, 1.42)	0.59	0.94 (0.56, 1.58)	0.829
WHO stage at baseline
I & II	Reference		Reference
III & IV	1.10 (0.62, 1.97)	0.743	0.88 (0.46, 1.67)	0.693
Tuberculous meningitis b	0.91 (0.44, 1.89)	0.805	0.71 (0.33, 1.50)	0.363
ART intake c	0.19 (0.11, 0.32)	<0.001	0.15 (0.08, 0.27)	<0.001
Age > 45 years d	1.35 (0.84, 2.16)	0.214	1.95 (1.15, 3.30)	0.013

ART, antiretroviral therapy; CI, confidence intervall; HR, hazard ratio; LTFU, lost to follow-up; WHO world health organization

Reference groups:

a male sex,

b no tuberculous meningitis,

c no ART intake,

d age ≤ 45 years

Discussion

In this rural sub-Saharan African cohort of PLHIV we found an EPTB prevalence of 5.6% with a high mortality of 14.3% (25/175) and a combined death/LTFU rate of 46.8%. Diagnosis remains a major challenge as only 36.9% of all pulmonary TB manifestations and 16% of extrapulmonary manifestations were confirmed by microbiology. Patients with EPTB not receiving cART and with an age >45 years had a higher risk for a poor outcome.

The overall TB prevalence of 18.4% in our study is comparable to the UNAIDS Report 2018 showing a TB prevalence of 16% in PLHIV [28]. However, the 30% of EPTB within TB cases is considerably higher than rates documented worldwide and in Tanzania (14%, 22%, respectively) [1]. Studies from other rural sub-Saharan African settings, e.g. Ethiopia, also found a high EPTB prevalence in PLHIV (36.8%) [29]. Reasons might be the high number of patients presenting with advanced HIV (65%) and co-factors such as undernutrition [19, 30], which has been demonstrated to be 30% in the same cohort [31] and is more prevalent in rural than in urban settings [32]. Over the study duration, the proportion of patients with a diagnosis of EPTB in all patients with TB increased from 28.8% in 2013 to 51% in 2017 patients. This might be likely due to reporting bias, as we concurrently did a prospective study on the impact of sonography for EPTB diagnosis, leading to a more sensitive evaluation of patients with TB [25]. In other settings, implementation of cART has led to a decrease in EPTB rates in PLHIV [33].

The mortality of 14.3% of EPTB patients is lower than a recent study in urban setting in Ghana with a mortality of 28.7% [34]. However, the rate of 14.3% we found is comparable to a multicohort study comparing clinical outcomes of EPTB in 22 ART programs with a mortality of 11.4% in PLHIV with EPTB [35]. Comparison between different studies remains a challenge, as diagnosis of EPTB is not very standardized and mostly done on clinical parameters only [25].

In our study, the rate of positive Xpert® MTB/RIF was low with 12.7% (157/1,241 samples analyzed). While the majority of positive samples (86.3%) originated from sputum, the rate of positive samples from extrapulmonary sites was very low with 5% (25/500). Poor sensitivity of Xpert® MTB/RIF has been demonstrated in PLHIV with HIV previously [5] and is partly due to challenges in proper sampling [36] and the paucibacillary nature of disease in PLHIV and in extrapulmonary sites [37, 38]. In one study overall sensitivity and specificity of Xpert® MTB/RIF compared to culture was 81.3% and 99.8%, respectively in patients with EPTB. However, when compared to a combination of culture and clinical diagnosis, the sensitivity of Xpert® MTB/RIF in cavitary fluids was under 50% [39]. The inclusion of the clinical diagnosis into a combined gold standard was based on post-mortem studies in PLHIV in resource-limited settings, which have shown a prevalence of TB in sub-Saharan Africa up to 43.2% [40]. A recent meta-analysis found a sensitivity of Xpert® MTB/RIF in pleural fluid of 50.9% and documents the important role of Xpert® MTB/RIF as confirmatory test in extrapulmonary samples, while exclusion remains a challenge [8].

While the majority of TB cases (71.8%) were diagnosed before the start of cART, a minority (9.1%) were diagnosed in first 30 days after, possibly presenting an unmasking IRIS. This hyper-responsiveness due to an increase in T-cells [41] has been reported to occur in 36–54% of TB/HIV co-infected patients [42, 43] and usually occurs within the first month after start of the antiretroviral therapy [44]. Patients presenting late after cART start with incident TB were few–unfortunately we could not analyze details on cART adherence or virological suppression as routine viral load was not implemented during the study period.

In a meta-analysis of PLHIV in sub-Saharan Africa around 40% of patients were LTFU five years after initiation of cART with death rates approaching 15% [45]. In our cohort this number was even higher in those with EPTB diagnosis. A recent meta-analysis including data of 7,377 patients who started cART and were subsequently LTFU showed a rate of 21.8% of subjects to be deceased while 14.8% of patients LTFU have been transferred to another clinic [46]. Factors associated with poor outcome in patients with EPTB in our study were age of >45 years and not being on cART. Both confirm previous studies, where age has been shown as a risk factor for disseminated TB and death [47, 48], while patients with EPTB co-infected with HIV without cART showed poorer outcomes than with cART [4].

The adjusted model did not show an association between indicators of HIV associated immunosuppression (WHO stage and CD4+ cell count) at baseline and the combined endpoint. This observation might be due to the inclusion of only patients developing EPTB into the model. By analyzing a selected group with a high probability of the endpoint as well as a presumed high level of functional immunodeficiency, WHO stage and CD4+ cell count might not further discriminate risk.

A major strength of this study is the prospective assessment of TB by means of ICD-10 codes in a long-term cohort of PLHIV ensuring standardized reporting. Furthermore, this study depicts a sub-Saharan African rural setting representative of settings with limited diagnostic resources available to clinicians and a high proportion of diagnoses relying on clinical presentation only. Those conditions are neglected as many studies have been done in urban settings.

The clinical diagnosis of EPTB determined by the physician, however remains a major limitation, as it is a poorly defined entity which might have been assessed differently by physicians. Patients with important differential diagnoses such as cancer, heart failure, lung abscess or other diseases might have been missed. As in other studies from African settings [4, 5, 49, 50] the most frequent sites of EPTB were pleurisy and lymphadenopathy. As the lymphadenopathy was a clinical diagnosis without histological confirmation, the assumption of TB as underlying disease might have been overestimated.

Besides improving microbiological detection of TB, e.g. by Xpert MTB/RIF Ultra [51], lateral flow urine lipoarabinomannan assay (LF-LAM) [52] or adenosine deaminase [53, 54], the clinical evaluation might benefit from integration of an additional standardized testing, such as e.g. Focused Assessment with Sonography for HIV and Tuberculosis (FASH) [25, 55].

Another limitation is the rather low observation period of patients after start on cART (median 1.25 years), mainly due to the high number of patients LTFU, which precluded an exact estimation of the true mortality rate.

In conclusion, EPTB remains a relevant comorbidity with a high mortality and LTFU in a rural sub-Sahara African setting. Establishing a microbiological diagnosis of EPTB in the absence of culture and histopathology remains a major challenge in settings, where invasive diagnostic procedures are not routinely performed. Despite the increasing access to Xpert® MTB/RIF MTB/RIF in sub-Saharan Africa it remains unclear to what extent this translates in clinical benefit [56]. The lack of ART as a factor for poor prognosis points at the importance of early ART start. Further research needs to be conducted to better define clinical predictors and new microbiological tests to improve early detection and outcome of EPTB.

(XLSX)

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Definitions of tuberculosis.

(DOCX)

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11 Nov 2019

PONE-D-19-26934

Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania. The prospective Kilombero and Ulanga antiretroviral cohort.

PLOS ONE

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Reviewer #1: REVIEW OF MANUSCRIPT OCTOBER 2019

Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania. The

prospective Kilombero and Ulanga antiretroviral cohort.

GENERAL REMARKS

This prospective study examines extrapulmonary TB (EPTB) in HIV positive patients in Tanzania. The paper is well written and has a number of strengths. It will benefit from proof-reading to correct a few sentences where the words do not read well. Some suggestions are highlighted below and in the paper for the authors’ consideration to improve the paper.

TITLE

Instead of a full stop after Tanzania, a colon would be more appropriate as follows: Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania: The prospective Kilombero and Ulanga antiretroviral cohort

ABSTRACT

Reading through the paper, it appears that in addition to characterizing the epidemiology and clinical characteristics of these patients, the key outcomes of interest are death / loss to follow up rather than the broad term clinical outcomes which would also include outcomes such as cure. The authors should consider rewording the aim/objective to reflect the interest in the predictors of the outcome lost to follow up / death.

INTRODUCTION

The introduction is generally well written.

Page 4 Lines 80-81 My comment on the aim of the study highlighted under the ABSTRACT portion above also applies. The authors should consider rewording the aim/objective to reflect that they examined predictors of lost to follow up / death.

METHODS

Please indicate at the beginning of the Methods section that this is a prospective of study so that readers are aware of this methodology right from the start even before providing information on the study site and patient population.

It would be helpful to readers to have a good understanding of the study setting since the authors highlight that it is rural Tanzania. So even though the authors provide references for details on the cohort, providing a little bit of information on the setting and the context of these patients would be very useful for readers especially later on when the results show such high rates of lost to follow up.

Page 4 89-90 Please highlight what the guideline was for starting cART for HIV patients in the program.

Page 5 Lines 114-115 I found the following phrase “1 week before until 3 months after working diagnosis” challenging to understand. Is it to say that patients were designated as PTB even one week before they were assigned a diagnosis of TB? Please explain the phrase so that it is self-explanatory.

Page 6 Lines 151-152 Please explain how the incidence density was calculated

RESULTS

Page 7 Line 175 Please provide the range of the follow up period as well.

Page 7 Lines 179 – 188. The authors make statements such as “more advanced” and “no major differences”. It is not clear whether these inferences are being made from just eyeballing the figures in Table 1. Please indicate whether these differences were statistically significant or not statistically significant.

In Table 1, I noticed that registration was highest in 2015 and I am wondering whether there was some reason for this. The authors should please point out this finding and comment on it in the discussion.

Page 10 Line 209 For the incident TB cases, please indicate how many patients were diagnosed with TB 90 days after enrolment and the range of the period between the time of enrollment and the diagnosis of TB.

Please provide information on the prevalence of CNS manifestation in the EPTB patients.

Please indicate what the reference groups are for all the variables in Table 4

DISCUSSION

The authors indicate a high mortality of 14.3% among their EPTB patients. How does this finding compare with what other studies have found?

Given the various variables that the authors report on in their study, there is opportunity for rich discussion on the study findings. The authors should include more discussion on the poor outcome of their patients LTFU in view of the clinical characteristics reported on such as WHO stage, comorbidities and CD4 count.

In the conclusion, the authors highlight that lack of ART and age >45 years were risk factors for death or loss to follow-up. What recommendations do the authors offer for clinicians or program managers to address these findings?

Reviewer #2: Review report

Title : “Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania. The prospective Kilombero and Ulanga antiretroviral cohort.”

Title

1) I don’t understand why you have put “full stop” after Tanzania. Why not “:” ?

Abstract

1) Please you should explain all abbreviations at the first appearance in the text e.g: AFB, py, CI

2) You stated that: “The combined endpoint of death and LTFU was observed in 1058 (33.8%) patients, most frequently in the subgroup of EPTB (47.2%)”.

You should give hazard ratio

3) “(HR 1.95, 95%CI 1.15-3.3; p = 0.013)”: This is not well written.

You can for example state after hazard ratio [HR (95% CI)] and then after each risk factor you just need to put the values.

Introduction

1) Line 55-56: “…14% incident cases” where?

2) Line 71: Heart failure is not the classical differential diagnosis of pleural TB. Heart failure gives typically a transudate pleural effusion whereas pleural TB gives exudative pleural effusion. You should remove heart failure as a differential diagnosis.

Methods

1) Line 101: Which sites (localizations) did you use for sonography screening? You should specify.

2) The Methods section should begin by specify the group of patients included. You have put it at the end of the first paragraph.

3) I don’t understand the rationale of “antituberculous drugs started” one week before the working diagnosis. This claim is confusing me.

4) The section named definitions spanned data collection. You should rename or separate data collection and operational definitions sections.

5) All the definitions used are very hard to understand and are beat confusing. Can you specify the definitions used to create all the ICD10 codes?

6) The major issue in this chapter is the absence of histopathological features.

7) In HIV environment we usually used 90 days for LTFU definition and not 60 days. What are the rationales of 60 days choice?

8) Which statistical test did you use to compare Kaplan-Meier curves (Log-rank test?)

Results

1) What are the characteristics of 128 excluded patients in comparison of the characteristics of included ones?

2) Did you verify that the patients classified as LTFU were not died?

3) You have compared baseline characteristics in different groups without given p-value for comparison. The p-value is not specified in the Table 1.

4) The first column in your Table 1 should be EPTB and you should compare the other forms to this one.

5) Table 1 is not well formatted which horizontal lines inside the table.

6) Line 199: You should begin by EPTB

7) Is it any difference between the median time from initiation of cART to the diagnosis of PTB and EPTB

8) Line 222: I hope that the localization of EPTB was specified in all of your participants.

9) Lines 226 and 227: pulmonary and extrapulmonary manifestations refer to PTB and EPTB? Not clear.

10) Table 2: please correct “Lymph node”

11) Lines 240 and 241: please rephrase sentence. The second part is not understandable

12) Lines 250-251: EPTB and EPTB/PTB were compare to what (PTB or no TB)?

13) Figure 2 is difficult to understand. Negative month means what?

14) I did not see the verification of proportional hazard models assumptions.

Discussion

The discussion section is very well written.

**********

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Reviewer #1: Yes: Sally-Ann Ohene

Reviewer #2: Yes: Eric Walter PEFURA YONE

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Submitted filename: EPTB Tanzania PONE-D-19-26934_reviewer.pdf

Click here for additional data file.

17 Dec 2019

Please find the point to point reply in the Response to Reviewers letter as well.

TITLE

Reviewer #1

Instead of a full stop after Tanzania, a colon would be more appropriate as follows: Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania: The prospective Kilombero and Ulanga antiretroviral cohort.

Reviewer #2

1) I don’t understand why you have put “full stop” after Tanzania. Why not “:” ?

ANSWER: We agree with this consideration and have changed the title accordingly.

ABSTRACT

Reviewer #1

Reading through the paper, it appears that in addition to characterizing the epidemiology and clinical characteristics of these patients, the key outcomes of interest are death / loss to follow up rather than the broad term clinical outcomes which would also include outcomes such as cure. The authors should consider rewording the aim/objective to reflect the interest in the predictors of the outcome lost to follow up / death.

ANSWER: We reworded to ‘risk factors of poor outcome’.

Reviewer #2

1) Please you should explain all abbreviations at the first appearance in the text e.g: AFB, py, CI

ANSWER: We thank for this suggestion and have corrected the abbreviations.

2) You stated that: “The combined endpoint of death and LTFU was observed in 1058 (33.8%) patients, most frequently in the subgroup of EPTB (47.2%)”. You should give hazard ratio.

ANSWER: We constructed a cox model exclusively for patients with EPTB, so we could investigate risk factors for the combined endpoint in these patients. Therefore, no hazard ratios for comparisons of different study groups (e.g. EPTB vs. PTB) can be indicated, as the cox model did never include patients of e.g. the PTB group. However, with the data given in Table 3, the frequencies of the combined endpoint in the different study groups can be compared. We added details on the test used for the calculation of p-values in the table legend, in addition to the preexisting mention in the methods section.

3) “(HR 1.95, 95%CI 1.15-3.3; p = 0.013)”: This is not well written.

You can for example state after hazard ratio [HR (95% CI)] and then after each risk factor you just need to put the values.

ANSWER: We agree with this proposal and adjusted the writing.

INTRODUCTION

Reviewer #1

Page 4 Lines 80-81 My comment on the aim of the study highlighted under the ABSTRACT portion above also applies. The authors should consider rewording the aim/objective to reflect that they examined predictors of lost to follow up / death.

ANSWER: We corrected as suggested (page 4, line 80).

Reviewer #2

1) Line 55-56: “…14% incident cases” where?

ANSWER: According to the Tuberculosis Report 2018 it applies to the incidence globally. We specified accordingly.

2) Line 71: Heart failure is not the classical differential diagnosis of pleural TB. Heart failure gives typically a transudate pleural effusion whereas pleural TB gives exudative pleural effusion. You should remove heart failure as a differential diagnosis.

ANSWER: We thank for this feedback. In remote rural settings, the laboratory mostly cannot provide a detailed analysis of fluid allowing differentiation between a transudate and an exudative character. Therefore, heart failure remains a possible differential diagnosis of pleural effusion. We have added the word ‘clinical’ to stress the constraint of diagnostic options.

METHODS

Reviewer #1

Please indicate at the beginning of the Methods section that this is a prospective of study so that readers are aware of this methodology right from the start even before providing information on the study site and patient population. It would be helpful to readers to have a good understanding of the study setting since the authors highlight that it is rural Tanzania. So even though the authors provide references for details on the cohort, providing a little bit of information on the setting and the context of these patients would be very useful for readers especially later on when the results show such high rates of lost to follow up.

ANSWER: We thank the reviewer for this comment and added more details in the highlighted manuscript on page 4 lines 85ff.

Page 4 89-90 Please highlight what the guideline was for starting cART for HIV patients in the program.

ANSWER: We added references for the guidelines used, which are the current “national guidelines for the management of HIV and AIDS” (NACP), issued by the ministry of health of Tanzania.

During the study period the WHO guidelines recommendations and its derived NACP guidelines in start of antiretroviral drugs changed from HIV WHO stage III or IV or CD4 cell counts <350cells/mm3, to <500cells/mm3 to treatment of all HIV-positive individuals (page 4, line 93ff).

Page 5 Lines 114-115 I found the following phrase “1 week before until 3 months after working diagnosis” challenging to understand. Is it to say that patients were designated as PTB even one week before they were assigned a diagnosis of TB? Please explain the phrase so that it is self-explanatory.

ANSWER: We thank for this question. This sentence illustrates the difficulty that some patients started the treatment on a “probatory” base as the diagnosis of tuberculosis is often clinical only. Thus, the treatment might have started before the indication of an ICD-10 Code. We added working diagnosis of ‘suspected TB’ to make this clearer on page 5, line 120.

Page 6 Lines 151-152 Please explain how the incidence density was calculated.

ANSWER: The incidence density was calculated as (number of incident cases)/(person-time of subjects at risk in the unit of person-years). This contrasts with incidence rates (number of incident cases/numbers of subjects observed), which don’t incorporate a time dimension into the denominator. We added this in the definitions section on page 6, line 164.

Reviewer #2

1) Line 101: Which sites (localizations) did you use for sonography screening? You should specify.

ANSWER: We performed the sonography screening according to the Focused Assessment with Sonography for HIV and Tuberculosis protocol (FASH) and added the reference to the manuscript. The pathological findings screened for in the FASH-protocol were pleural or pericardial effusion, ascites, abdominal lymph nodes, hypoechogenic lesions in liver/spleen, Ileum wall thickening or ileum wall destruction (added on page 5, lines 109-111).

2) The Methods section should begin by specify the group of patients included. You have put it at the end of the first paragraph.

ANSWER: We thank for this correction, which was implemented in the manuscript.

3) I don’t understand the rationale of “antituberculous drugs started” one week before the working diagnosis. This claim is confusing me.

ANSWER: We thank the reviewer for this question. Please see our answer above to the same point raised by reviewer #1. Some patients started the treatment on clinical suspicion only, while microbiological prove follows later. We have added the explanation due to the possible premature start of TB-treatment before an indication of an ICD-10 diagnosis

4) The section named definitions spanned data collection. You should rename or separate data collection and operational definitions sections.

ANSWER: We reviewed the section entitled ‘definitions’ and believe the points mentioned should remain here as they are rather part of the analytical process than the prospective data collection.

5) All the definitions used are very hard to understand and are a bit confusing. Can you specify the definitions used to create all the ICD10 codes?

ANSWER: We agree it is a long paragraph, but we believe these definitions are key specifically for the field of the clinically suspected cases, which in daily life are done at the discretion of the treating physician. As we mentioned in the discussion this remains a limitation of the study. To simplify, we shortened the paragraph on definition of comorbidities on page 6, line 141 ff.

6) The major issue in this chapter is the absence of histopathological features.

ANSWER: We agree and have pointed this out in the methods page 5, line 116/117. Additionally, this is mentioned in the discussion as a limitation (page 14, line 336ff).

7) In HIV environment we usually used 90 days for LTFU definition and not 60 days. What are the rationales of 60 days choice?

ANSWER: When the definition for LTFU for use in this cohort was designed, we incorporated empirical evidence about the choice of the optimal cutoff to predict a true LTFU status. This study can be accessed at https://www.ncbi.nlm.nih.gov/pubmed/20219765 .

8) Which statistical test did you use to compare Kaplan-Meier curves (Log-rank test?)

ANSWER: We added a p-value derived by log-rank testing to Figure 3, comparing the 3 groups of patients with a diagnosis tuberculosis, including a mention of the test in the methods section (page 6, line 163).

The p-values already indicated in the text comparing risk factors for the composite outcome in patients with EPTB are derived from the survival analysis using the Cox proportional hazard model. We think this was appropriately indicated by mentioning p-values in exclusively in parenthesis after the respective hazard ratios.

RESULTS

COMMENT: Please note the change in the inclusion timeline on page 7, line 178; we replaced September 2013 with January 2013, which was a mistake in the first edition.

Reviewer #1

Page 7 Line 175 Please provide the range of the follow up period as well.

ANSWER: Please find the range in the highlighted manuscript (3 days-5 years) on page 7, line 182.

Page 7 Lines 179 – 188. The authors make statements such as “more advanced” and “no major differences”. It is not clear whether these inferences are being made from just eyeballing the figures Table 1. Please indicate whether these differences were statistically significant or not statistically significant.

ANSWER: We thank for this comment and added the p-values of comparison tests (according to the methods section) to table 1.

In Table 1, I noticed that registration was highest in 2015 and I am wondering whether there was some reason for this. The authors should please point out this finding and comment on it in the discussion.

ANSWER: We thank you for the observation and discussed the finding with all investigators. However, we could not find a convincing conclusion to explain this peak. Therefore, we believe, this might reflect natural fluctuation or factors not explainable with the data on hand. We have already commented this in the discussion on page 13, line 289ff.

Page 10 Line 209 For the incident TB cases, please indicate how many patients were diagnosed with TB 90 days after enrolment and the range of the period between the time of enrollment and the diagnosis of TB.

ANSWER: Out of a total of 574 patients with TB (399 PTB, 84 PTB/EPTB and 91 EPTB), 334 PTB, 71 PTB/ETPB and 78 EPTB cases were diagnosed within the 3 months (baseline prevalence). Thus, 5 cases of PTB, 13 EPTB and 13 cases of EPTB/PTB were diagnosed after these first 3 months. We added this information on page 10, line 215-216.)

The range of days has been added in the manuscript on page 10, line 210 and 211.

Please provide information on the prevalence of CNS manifestation in the EPTB patients.

ANSWER: The prevalence rates of varying organ manifestations of EPTB were described in the initial manuscript under subheading “Clinical presentation and microbiological testing” on page 10, line 227. This includes CNS manifestations as well, which were present in 12% of all cases of EPTB.

Please indicate what the reference groups are for all the variables in Table 4

ANSWER: Reference groups were added as footnotes to the table as requested.

Reviewer #2

1) What are the characteristics of 128 excluded patients in comparison of the characteristics of included ones?

ANSWER: Those patients had high rates of missing values for most variables used in table 1, thus no clear description of these patients was possible. We added a comment in the manuscript on page 7, line 180.

2) Did you verify that the patients classified as LTFU were not died?

ANSWER: As LTFU commonly indicates a category of subjects, whose outcome is unknown, we cannot know if patients died. Indeed, a high death rate is described in studies actively tracking patients lost to follow-up (e.g. Egger et al PLoS Med. 2011 Jan 18;8(1):e1000390): Correcting mortality for loss to follow-up: a nomogram applied to antiretroviral treatment programs in sub-Saharan Africa.) In our setting we do regular tracking, but still remain with a high percentage of patients LTFU.

3) You have compared baseline characteristics in different groups without given p-value for comparison. The p-value is not specified in the Table 1.

ANSWER: The p-values have been added to table 1.

4) The first column in your Table 1 should be EPTB and you should compare the other forms to this one.

ANSWER: We have changed the order as requested.

5) Table 1 is not well formatted which horizontal lines inside the table.

ANSWER: The table was indeed already designed to be legible without the necessity of horizontal lines. We removed the horizontal lines in the updated version.

6) Line 199: You should begin by EPTB

ANSWER: We thank for this correction and adjusted the title.

7) Is it any difference between the median time from initiation of cART to the diagnosis of PTB and EPTB

ANSWER: We added the p-value derived by a Mann–Whitney U test comparing the intervals to the results section, it was nonsignificant with a value of 0.78 (page 10, line 223).

8) Line 222: I hope that the localization of EPTB was specified in all of your participants.

ANSWER: In the 175 patients with an extrapulmonary manifestation the localization was always specified. The distribution of organ manifestations has already been described in the results section under “Clinical presentation and microbiological testing”.

9) Lines 226 and 227: pulmonary and extrapulmonary manifestations refer to PTB and EPTB? Not clear.

ANSWER: We used “manifestation” instead of “PTB and EPTB” to account for the fact that patients in both the EPTB and the combined PTB/EPTB study group show signs of extrapulmonary TB. The same is true for pulmonary manifestations which are present in the PTB and the combined PTB/EPTB group. The respective denominator in the numbers indicated in the same sentence is the appropriate sum of the two groups. We further clarified this in the methods (page 6, line 139).

10) Table 2: please correct “Lymph node”

ANSWER: We thank for the comment and corrected accordingly.

11) Lines 240 and 241: please rephrase sentence. The second part is not understandable

ANSWER: We agree with the comment and clarified the sentence (now page 11, line 248-249)

12) Lines 250-251: EPTB and EPTB/PTB were compare to what (PTB or no TB)?

ANSWER: Table 3 describes a crude comparison of outcomes in the four study groups. The indication of one p-value per row indicates that it describes a multiple group comparison across all 4 groups and not the result of an individual between-two-group comparison. We added a specification of this in the table legend (page 12, line 263).

13) Figure 2 is difficult to understand. Negative month means what?

ANSWER: The interval denotes the difference between date of diagnosis of TB and the initiation of cART in months. Positive numbers indicate, that the diagnosis of TB was after the initiation of cART, negative numbers indicate, that the diagnosis of TB was before the initiation of cART. We added a sentence in the figure legend (‘Out of the 574 patients with any diagnosis of TB, 508 (88.5%) started cART after a median of 23 (IQR 10-56) days.’)

14) I did not see the verification of proportional hazard models assumptions.

ANSWER: In the initial manuscript (“Data management and analysis”, page 6, line 165ff) we indicated, that Schoenfeld residuals were used to verify the proportional hazards assumption.

We are not sure, whether the reviewer was asking to actually see the results of the assumption testing done. In our opinion, it is good standard in medical literature to explicitly indicate that assumption testing was performed and to mention the respective method used. However, to our knowledge, the results of such testing are not commonly published with the article. If of interest for the reviewer, we show the results of the formal statistical testing here.

Variable rho chi2 df Prob>chi2

Sex 0.08087 0.51 1 0.4755

CD4+ cell count at baseline 0.13093 1.33 1 0.2485

Tuberculous meningitis -0.18395 2.67 1 0.1022

ART intake -0.17803 3.14 1 0.0762

Age > 45 years 0.09997 0.83 1 0.362

global test 7.79 5 0.1683

ACKNOWLEDGEMENTS

COMMENT: Page 16, line 356. We added the members of the KIULARCO study group in the acknowledgements. The corresponding author is Prof. Dr. Maja Weisser.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

16 Jan 2020

PONE-D-19-26934R1

Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania: The prospective Kilombero and Ulanga antiretroviral cohort.

PLOS ONE

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Reviewers' comments:

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Reviewer #2: (No Response)

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Reviewer #2: Partly

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Reviewer #2: Yes

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Reviewer #1: GENERAL REMARKS

The authors have done a good job addressing the points raised in the review. There are however a few outstanding minor points and some comments from the first review that the authors are kindly requested to address.

1. Please add ‘of suspected TB’ to the following phrase “1 week before until 3 months after working diagnosis” where it appears in the manuscript

2. The authors provide the following explanation to the reviewer comments “The incidence density was calculated as (number of incident cases)/(person-time of subjects at risk in the unit of person-years).” However this definition/explanation should not only be for the benefit of the reviewer but should be included in the manuscript.

3. Page 7 Line 188: Please include the range in the following format “3 days-5 years” in the manuscript instead of 0.01-5

4. Page 8 Line 198: The authors indicate “There were no major differences in marital status, education, smoking behavior and alcohol consumption”. However the p-values for smoking, marital status are significant and there is no data for education in the Table. The authors should please address these discrepancies/gap.

5. It looks like the following points from the initial review were not addressed by the authors so they should please address them:

DISCUSSION

The authors indicate a high mortality of 14.3% among their EPTB patients. How does this finding compare with what other studies have found?

Given the various variables that the authors report on in their study, there is opportunity for rich discussion on the study findings. The authors should include more discussion on the poor outcome of their patients LTFU in view of the clinical characteristics reported on such as WHO stage, comorbidities and CD4 count.

In the conclusion, the authors highlight that lack of ART and age >45 years were risk factors for death or loss to follow-up. What recommendations do the authors offer for clinicians or program managers to address these findings?

Reviewer #2: Review report

PONE-D-19-26934R1

Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania: The prospective Kilombero and Ulanga antiretroviral cohort.

Major comments

ABSTRACT

2) You stated that: “The combined endpoint of death and LTFU was observed in 1058 (33.8%) patients, most frequently in the subgroup of EPTB (47.2%)”. You should give hazard ratio.

ANSWER: We constructed a cox model exclusively for patients with EPTB, so we could investigate risk factors for the combined endpoint in these patients. Therefore, no hazard ratios for comparisons of different study groups (e.g. EPTB vs. PTB) can be indicated, as the cox model did never include patients of e.g. the PTB group. However, with the data given in Table 3, the frequencies of the combined endpoint in the different study groups can be compared. We added details on the test used for the calculation of p-values in the table legend, in addition to the preexisting mention in the methods section.

GENERAL COMMENTS

I don’t agree. When you used cox-model you should compare groups of patients in the cohort. The comparison of the group with outcome to the one without outcome would give the hazard of the outcome e.g: HR should be specified.

As I stated, the major problem of the paper is the absence of methods to roll out other differential diagnosis (no cytological or histological examinations).

**********

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Reviewer #1: Yes: Dr Sally-Ann Ohene

Reviewer #2: Yes: Eric Walter PEFURA YONE

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5 Feb 2020

GENERAL REMARKS

Please find a for table S1 in line 122, page 5.

Reviewer #1:

The authors have done a good job addressing the points raised in the review. There are however a few outstanding minor points and some comments from the first review that the authors are kindly requested to address.

1. Please add ‘of suspected TB’ to the following phrase “1 week before until 3 months after working diagnosis” where it appears in the manuscript.

We added accordingly (Line 135 and 138).

2. The authors provide the following explanation to the reviewer comments “The incidence density was calculated as (number of incident cases)/(person-time of subjects at risk in the unit of person-years).” However, this definition/explanation should not only be for the benefit of the reviewer but should be included in the manuscript.

We added this in the definitions section on page 6, line 164 ff.

3. Page 7 Line 188: Please include the range in the following format “3 days-5 years” in the manuscript instead of 0.01-5.

We adjusted the manuscript accordingly on page 7, line 190.

4. Page 8 Line 198: The authors indicate “There were no major differences in marital status, education, smoking behavior and alcohol consumption”. However, the p-values for smoking, marital status are significant and there is no data for education in the Table. The authors should please address these discrepancies/gap.

We corrected as suggested: ‘Patients with EPTB were more frequently married and less frequently smokers.’ (page 8, line 199 and table 1). We deleted the information on education.

5. It looks like the following points from the initial review were not addressed by the authors so they should please address them:

DISCUSSION

The authors indicate a high mortality of 14.3% among their EPTB patients. How does this finding compare with what other studies have found?

We added a section in the discussion, see page 14, line 302ff.

Given the various variables that the authors report on in their study, there is opportunity for rich discussion on the study findings. The authors should include more discussion on the poor outcome of their patients LTFU in view of the clinical characteristics reported on such as WHO stage, comorbidities and CD4 count.

The adjusted model did not show an association between indicators of HIV associated immunosuppression (WHO stage and CD4+ cell count) at baseline and the combined endpoint. This observation might be due to the inclusion of only patients developing EPTB into the model. By analyzing a selected group with a high probability of the endpoint as well as a presumed high level of functional immunodeficiency, WHO stage and CD4+ cell count might not further discriminate risk. Other parameters were not analyzed. We commented this on p 15, line 338 ff.

In the conclusion, the authors highlight that lack of ART and age >45 years were risk factors for death or loss to follow-up. What recommendations do the authors offer for clinicians or program managers to address these findings?

Lack of ART is an indicator of late presentation with insufficient time to start treatment in time, as ART initiation has to be postponed for 2-6 weeks in patients with EPTB not yet on ART. Therefore, the most important recommendation is early diagnosis of HIV and treatment start of ART. We adapted the conclusions on page 16, line 371 as follows: ‘The lack of ART as a factor for poor prognosis points at the importance of early HIV diagnosis and ART start’.

We abstained from giving recommendations for elder patients with an age >45 years. Firstly, we consider it difficult to give a recommendation based on an observational study, secondly there might be other confounders such as other age-related diseases increasing the mortality. Please see page 16, line 367

Reviewer #2:

ABSTRACT

You stated that: “The combined endpoint of death and LTFU was observed in 1058 (33.8%) patients, most frequently in the subgroup of EPTB (47.2%)”. You should give hazard ratio.

ANSWER: We constructed a cox model exclusively for patients with EPTB, so we could investigate risk factors for the combined endpoint in these patients. Therefore, no hazard ratios for comparisons of different study groups (e.g. EPTB vs. PTB) can be indicated, as the cox model did never include patients of e.g. the PTB group. However, with the data given in Table 3, the frequencies of the combined endpoint in the different study groups can be compared. We added details on the test used for the calculation of p-values in the table legend, in addition to the preexisting mention in the methods section.

GENERAL COMMENTS

I don’t agree. When you used cox-model you should compare groups of patients in the cohort. The comparison of the group with outcome to the one without outcome would give the hazard of the outcome e.g: HR should be specified.

As I stated, the major problem of the paper is the absence of methods to roll out other differential diagnosis (no cytological or histological examinations).

1) As your comment was pointing to results from table 3 where all study groups (i.e. including those with no TB) are summarized, we assumed you were also asking for HRs from a survival model of all patients in the study. As we explained in the previous comment and in the manuscript, we did not build a cox model including e.g. patients with no TB. This selection is based on the study question of finding risk factors in patients with EPTB. A model including also patients without any TB episodes would be much more complex (e.g. TB diagnosis would have to be modelled as a time-dependent covariate) and less interpretable without bringing any advantage for the answer of the study question.

However, we understand you comment as an indication for the need for a relative measure to compare the rate of the primary outcome in the patient groups with any TB as in Figure 3. To address this, we build a model including the PTB, EPTB and the EPTB/PTB groups and indicated HRs comparing those groups in the results section (p, line). This information replaces the results of the log-rank test in Figure 3 (added in the last round of review) in a more detailed way, so we removed it again.

In case this is not the information you were expecting, please specify in more detail the type of analysis to be conducted.

Abstract page 2, line 43. Results page 12, line 265.

HR 95% CI p

PTB Reference

EPTB 1.63 1.14-2.31 0.006

EPTB and PTB 1.65 1.15-2.36 0.006

2) We agree, that the absence of methods to roll out other differential diagnosis is a limitation of the study. We underline this in the discussion on page 16, line 349ff.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

18 Feb 2020

Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania: The prospective Kilombero and Ulanga antiretroviral cohort.

PONE-D-19-26934R2

Dear Dr. Weisser,

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With kind regards,

Marcel Yotebieng, M.D., MPH, Ph.D

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

19 Feb 2020

PONE-D-19-26934R2

Extrapulmonary tuberculosis in HIV-infected patients in rural Tanzania: The prospective Kilombero and Ulanga antiretroviral cohort.

Dear Dr. Weisser:

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PLOS ONE