Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis.

BACKGROUND: Tuberculosis (TB) is the leading cause of death among HIV-positive patients. We assessed the cost-effectiveness of including lateral-flow urine lipoarabinomannan (LF-LAM) in TB diagnostic algorithms for severely ill or immunosuppressed HIV-positive patients with symptoms of TB in Kenya.
METHODS: From a decision-analysis tree, ten diagnostic algorithms were elaborated and compared. All algorithms included clinical exam. The costs of each algorithm were calculated using a 'micro-costing' method. The efficacy was estimated through a prospective study that included severely ill or immunosuppressed (CD4<200cells/μL) HIV-positive adults with symptoms of TB. The cost-effectiveness analysis was performed using the disability-adjusted life year (DALY) averted as effectiveness outcome. A 4% discount rate was applied.
RESULTS: The algorithm that added LF-LAM alone to the clinical exam lead to the least average cost per TB case detected (€47) and was the most cost-effective with a cost/DALY averted of €4.6. The algorithms including LF-LAM, microscopy and X-ray, and LF-LAM and Xpert in sputum, detected a high number of TB cases with a cost/DALY averted of €6.1 for each of them. In the comparisons of the algorithms two by two, using LF-LAM instead of microscopy (clinic&LAM vs clinic&microscopy) and using LF-LAM along with GeneXpert in sputum instead of GeneXpert in urine along with GeneXpert in sputum, (clinic&LAM&Xpert_sputum vs clinic&Xpert_sputum&Xpert_urine) led to the highest increase in the cost-effectiveness ratios (ICERs): €-7.2 and €-12.6 respectively. In these two comparisons, using LF-LAM increased the number of TB patients detected while reducing costs. Adding LF-LAM to smear microscopy alone or to smear microscopy and Xray led to the highest increase in the additional number of TB cases detected (31 and 25 respectively) with an incremental efficiency estimated at 134 and 344 DALYs respectively. The ICERs were €22.0 and €8.6 respectively.
CONCLUSION: Including LF-LAM in TB diagnostic algorithms is cost-effective for severely ill or immunosuppressed HIV-positive patients.

Introduction

Tuberculosis (TB) in one of the leading causes of death worldwide [1]. Of the 10 million estimated incident TB cases in 2017, 9% were among HIV-positive patients [1]. Currently, TB diagnosis relies mainly on microscopic examination of sputum; culture methods on liquid media and molecular methods. Microscopic examination of sputum is a fast, easy and affordable method [2]. However, smear microscopy has low sensitivity (~50%) that is even lower in HIV-positive patients [3-5]. Culture methods on liquid media have a high sensitivity but require a high laboratory infrastructure level, highly qualified staff and scrupulous respect for safety standards. Molecular methods, such as GeneXpert are easy to use, requires little handling and can detect tuberculosis in few hours. It also makes it possible to identify those who have resistance to rifampicin, a very good marker of Multi-drug-Resistant (MDR) TB [6]. WHO recommends this test as an initial test for anyone with signs and symptoms of tuberculosis [7] However, new TB technologies also represent additional cost for national TB programs [8]. In addition, microscopy, culture and GeneXpert, require the production of a sputum sample of sufficient quality and volume to obtain a valid result [9], which presents a challenge in advanced HIV as these patients often have difficulties producing sputum and are more likely to have disseminated forms of TB. In parallel, a new point-of-care urine test, Alere Determine lateral-flow TB lipoarabinomannan Ag (LF-LAM) has emerged as an additional tool with ability to detect TB in advanced HIV-positive patients and presenting advantages over sputum-based testing [9, 10]. LF-LAM is an immunochromatographic test for the qualitative detection of lipoarabinomannan antigen of Mycobacteria. The test is easy to perform and requires limited infection control measures [11]. LF-LAM is performed manually by applying 60μL of urine on the strip and incubating at room temperature for 25 minutes. The intensity of any visible band on the test strip is graded by comparing it with the intensities of the bands on a manufacturer-supplied reference card. LF-LAM utility is greater in HIV-positive patients with advanced immunodeficiency. In a meta-analysis of five studies, the pooled sensitivity and specificity in patients with CD4 below 200 cells/μL was 50% and 90% respectively [12]. WHO currently recommends the test in patients with symptoms of TB and very immunocompromised (CD4<100 cells/μL) or seriously ill [10]. This point-of-care technology can be an efficient tool to aid the diagnosis of TB in resource limited contexts.

Kenya is one of the 30 high TB burden countries with an incidence of 588/100,000 in 2016 [13]. The Nyanza region, where Homa Bay is located, is the area with the highest case load reported in the country [14]. In Homa Bay, the overall HIV prevalence among people aged 15–49 years was estimated at 20.7% in 2017 [14, 15], more than four times the national average in the country and 74% among TB patients [13-15]. TB and HIV care was provided in Homa Bay District Hospital by the Ministry of Health and Médecins Sans Frontières free of charge. HIV testing was proposed to all patients with symptoms of TB. A previous prospective observational study conducted in the same site showed that LF-LAM increased the diagnostic yield in ambulatory and hospitalized, immunocompromised (CD4<200cell/μL) or seriously ill, HIV-positive patients with symptoms of TB [15]. Using data from this cohort study, we aimed to evaluate the cost-effectiveness of introducing urine LF-LAM assay in 10 different TB diagnostic algorithms for this population of HIV-positive patients. We expect that this study would help lower-middle-income countries where all TB technologies are not available to determine how to improve TB diagnosis by looking at the most cost-effective combinations of technologies. The novelty of the study is the comparison of ten diagnostic algorithms combining different diagnostic tools.

Materials and methods

Study population

This study uses data from a single- centred, prospective study conducted between October 2013 and August 2015 at the Homa Bay County Hospital (Kenya) [15]. The population of the prospective study consisted on adults (≥15 years) with symptoms of TB hospitalized in the in-patient department or attending the out-patients TB clinic, who were either severely ill, or with a CD4 count below 200cells/μl or a body mass index (BMI) below 17Kg/m2, and who had not taken fluoroquinolones or anti-tuberculosis drugs in the month prior to the consultation. On the first day of consultation, the clinical officer performed a clinical exam, a chest X-ray and a LF-LAM test. In addition, two sputum samples (spot and early morning) were collected for smear microscopy, GeneXpert assay and Mycobacterium tuberculosis complex (MTBC) culture. For patients not able to produce sputum, GeneXpert and MTBC culture were performed in centrifuged urine from the same sample initially collected for LF-LAM. Smear microscopy and GeneXpert results were given the same day or the day after sample collection. The decision of whether or not to start TB treatment was made by the clinician officer based on the clinical exam, the chest X-ray and the laboratory results. For patients not started on TB treatment a second clinical exam were performed at day 5. The cost-effectiveness analyses included only patients with valid GeneXpert or culture results in sputum or urine. Confirmed TB was defined as positive GeneXpert or MTB culture.

Ethical approval

The study protocol was approved by the Kenya Medical Research Institute Ethical Review Committee and the Ethical Review Committee at the Comité de Protection des Personnes (CPP), Saint-Germain-en-Laye, France15. Before enrolment in the prospective efficacy study, written informed consent was obtained from all adult participants (≥18 years) and from guardians in the case of minors.

Study model

Using the prospective study efficacy data results of Huerga et al [15], a decision-analysis tree was constructed to determine the cost effectiveness of each TB diagnostic algorithm. In total, 10 algorithms for TB diagnosis were compared (Fig 1). All algorithms contained a clinical exam as the first step. The first group of algorithms included smear microscopy while the second group included GeneXpert with and without addition of the urine LF-LAM. Combining clinical exam with either smear-microscopy alone or LF-LAM test alone resulted in algorithms 1 (A1-smear) and 2 (A2- LAM). A1 with additional chest X-ray resulted in algorithm 3 (A3-smear&Xray) and with additional LF-LAM resulted in algorithm 4 (A4-smear&LAM). A1 with both additional chest X-ray and LF-LAM resulted in algorithm 5 (A5-LAM&smear+Xray). Within the second group of algorithms, clinical exam was combined with GeneXpert in sputum, whether alone as algorithm 6 (A6-Xpert) or with additional GeneXpert in urine as in algorithm 7 (A7-Xpert&Xpert_urine). Etiher LF-LAM or chest X-ray or both were added to GeneXpert in algorithm 8 (A8-LAM&Xpert), in algorithm 9 (A9-Xpert&X-ray) and algorithm 10 (A10-LAM&Xpert&Xray).

Fig 1

Diagnostic algorithms using microscopy or GeneXpert alone or in combination with chest X-ray versus LF-LAM alone or in addition to other TB diagnostic tools.

All algorithms included a clinic examination. Therefore, to simplify the wording we removed the term “clinic” from the label of the algorithms. The following algorithms were compared between them:

A2-LAM versus A1-smear

A4-smear&LAM versus A1-smear

A4-smear&LAM versus A3-smear&Xray

A5-LAM&smear&Xray versus A3-smear&Xray

A4-smear&LAM versus A6-Xpert

A7-Xpert&Xpert_urine versus A6-Xpert

A8-LAM&Xpert versus A6-Xpert

A8-LAM&Xpert versus A7-Xpert&Xpert_urine

A8-LAM&Xpert versus A9-Xpert&X-ray

A10-LAM&Xpert+Xray versus A9-Xpert&X-ray

Since LF-LAM, smear microscopy and GeneXpert results were available within 24 hours following the initial consultation, chest X-ray was performed only in cases with a negative result to those.

Cost estimation

The costing analysis followed the recommendations of International Society for Pharmacoeconomics and Outcomes Research (ISPSOR) [16] and the French Health Authority [17-18]. A health service perspective under real conditions was adopted. The cost evaluation was based on the analysis of the production costs [17]. “Micro-costing” method was adopted for costs of implementing each algorithm [19]. The evaluation of the costs was done by identifying, measuring and valuating the resources used in the production process [17-20]. The same costing approach that Yakhelef et al. [19] was adopted. So, for each test or test prescribed, variable and fixed costs were considered. These costs included both direct (resources used only by the TB diagnostic service) and joint (shared between different services) costs, including variable and fixed costs (depreciation of equipment and buildings). Variable costs estimates were based on expenditures established a posteriori from quantities actually used (consumables, fuel, medicine, actual working time) and from prices in the Kenyan market in 2013 and 2014, using a conversion rate of 113.55 KES for 2013; 118.96 KES for 2014 and 110.12 KES for 2015 (Kenyan shilling) for €1 (www.fxtop.com). Joint costs were calculated based upon allocation keys [17-19]. Costs for clinician, nurse, radiologist and laboratory technician were calculated by multiplying the time spent in the activity by the cost of a unit (minute) of work time or from the average number of patients per day (for supervisory staff). For follow-up of TB treatment, patients had weekly nursing consultations (about 5 min) during the first 2 months, followed by monthly consultations in the last 4 months. Two types of costs were identified. Firstly, the direct variable costs directly attributable to the implementation of each algorithm (consumables, small medical and non-medical equipment). Insofar as certain of these costs were difficult to attribute, an allocation key (proportion of activity for TB diagnosis among total hospital activity) was applied: on the one hand between microscopy (10%), culture laboratory (50%) and for GeneXpert (40%); one the other hand, between LF-LAM (50%) and CD4 (50%). Secondly, the fixed costs related to the depreciation of medical and nonmedical equipment. For microscopy exam, medical and non-medical equipment were mainly a microscope, a Bio Safety Cabinet, air conditioners and refrigerators. On the other hand, Bio Safety Cabinet Class II was used to prepare the sample for both the GeneXpert test and the MTB culture. Thus, we applied an allocation key according to their respective activity: 40% for GeneXpert test and 60% for the MTB culture. The rest of medical equipment were directly attributable to the GeneXpert (GeneXpert instrument, Battery and Catridges) and culture (Autoclave, Incubator CO2, bath water, etc). For LF-LAM tests, medical material was two Ependorff pipettes. Based on the nomenclature used by the city of Lyon [21], the lifetime for depreciation estimates is 10 years for laboratory equipment, 15 years for air conditioning, 7 years for refrigerators and 25 years for buildings [19]. The total cost was estimated by adding the cost of all categories listed above according to their use in each algorithm. The culture laboratory shared waste water treatment and waste management with the rest of the hospital. For running costs, we used an allocation key related to the surface area. We therefore allocated 4.06% of these total expenditures to the culture laboratory. Afterwards, we allocated 40% of these cost to the GeneXpert (60% for the culture). The costs of the TB treatment (€44.12) for a 6-month rifampicin-based regimen) and Chest X-ray (€1.64/X-ray) were based on a lump sum estimated by MSF. As the cost-effectiveness analysis exceeds one-year time horizon, a 4% discounting rate in order to taking into account the preference for the present was applied, as recommended by the French Health Authority [17].

Outcomes and measurement of effectiveness

The cost-effectiveness analysis was performed using the disability-adjusted life year (DALY) averted as effectiveness outcome. DALYs are the sum of the Years Lost due to Disability (YLD) and the Years of Life Lost (YLL) due to premature mortality [22]. The YLD in a population are calculated by the number of years persons live with a disability multiplied by a disability weight reflecting the severity of the disability. This weight varies between 0 (no burden) and 1 (mortality). The YLD averted was obtained from the number of TB patients detected by culture or GeneXpert. As recommended by the French Health Authority, the same discount rate of 4% was applied [17]. Parameter estimates for DALY measurement are shown in Table 1.

Table 1

Parameters for DALYs estimation.

Parameters	Value	Source
Age at onset of disability	Individual patient data	[15]
Duration of disability L without treatment (years)	1	[23]
Duration of disability L with treatment (years)	11	[23]
Age of death	Individual patient data	[15]
Disability weight TB with HIV infection	0.408	[23]
Life expectancy at age of death		[24]
Discount rate	0.04	[17]

Cost-effectiveness analysis

The diagnostic efficiency of each algorithm was estimated by calculating the incremental cost-effectiveness ratio (ICER) obtained as follows [25]:

The incremental cost was equal to the difference in terms of cost of implementing an algorithm versus another one. Similarly, the incremental effects were equal to the difference in DALYs averted when implementing an algorithm versus another one [25, 26]. We compared ICERs to a country’s willingness-to-pay threshold at €2,673, three times Kenya Gross Annual Income (GNI)[27]. Willingness to pay is the maximum amount a society would be willing to pay to acquire the TB screening technologies considered. The threshold was defined in reference to the country’s GNI/capita following standard benchmarks proposed in international work on cost-effectiveness. When ICERs fall below the defined threshold then interventions were considered cost-effective [28-31]. This range of threshold values is generally assumed to encompass the decision makers’ willingness-to-pay for an additional unit of effectiveness in health, however much debate still surrounds the determination of an acceptable threshold [32]. To simultaneously account for uncertainty across all parameter inputs, we conducted probabilistic sensitivity analysis using Monte Carlo simulation [33-35]. In each of the 10,000 simulations computed, model inputs were drawn from the data distribution of each parameter (beta probability of effectiveness and Poisson for cost data)[34]. We present the uncertainty around our incremental cost-effectiveness ratios with cost-effectiveness planes [36] and acceptability curves [37] and apply a one-way sensitivity analysis around 0% and 2.5% discount rates [17,18]. Cost-effectiveness calculations and sensitivity analyses were conducted with TreeAge Pro (TreeAge Software, Inc., 2016).

Results

Of the 275 patients included in the cost-effectiveness study, 138 (50.2%) were women, 49 (17.8%) were seriously ill, 149 (54.2%) were on antiretroviral treatment, 127 (46.2%) had a body mass index below 17Kg/m2. Median age was 35 years [IQR: 29–43] and median CD4 count was 113 [IQR: 49–204]. The distribution of the patients according to the level of CD4 count was: 69 (25.6%) <50 cells/μL, 42 (15.6%) 50–99 cells/μL, 83 (30.7%) 100–199 cells/μL, 76 (28.2%) ≥200 cells/μL. In total, 183 (66.6%) patients were hospitalized and 92 (33.5%) were ambulatory. Of the patients with a test result, LF-LAM was positive in 121/275 (44.0%) patients, sputum microscopy in 74/250 (29.6%), Xpert in sputum in 102/251 (40.6%), Xpert in urine in 13/24 (54.2%) and MTB culture in 107/ (44.4%). A total of 156/275 (56.7%) patients had confirmed TB.

Analysis of costs

The costing details are presented in Table 2. All costs are annualised costs. The main costs were anti-tuberculosis drugs treatment €41.42, followed by the GeneXpert test €8.40, the smear microscopy exam (€3.44); the LF-LAM test (€2.69), the clinical exam (€1.62) and the chest Xray (€1.12). Therefore, the cost of the drug was the main driver of the total cost of TB treatment (91%), the cost of the cartridges was the main component of the cost of GeneXpert test (67%), the cost of human resources was the cost the most important for the clinical and microscopic test (respectively 100% and 70%) and finally, the cost in material and supply represented the most important cost for the LF-LAM test (98%) (Table 2).

Table 2

Costing details, in Euros (4% discount).

Parameters items	Unit cost (€)	%
	Clinical exam cost
Human resources	1.62	100
	Sputum exam
Human costs	2.43	70.64
Laboratory maintenance and running	0.30	8.72
Material and furniture	0.33	9.59
Laboratory equipment	0.21	6.10
Non laboratory equipment	0.17	4.94
Total	3.44	100
	LF-LAM
Human costs	0.03	1.24
Material and furniture	2.63	97.65
Laboratory equipment	0.03	1.11
Total	2.69	100
	Chest X-ray
Human costs	0.14	12.5
Lump sum Xray	0.98	87.5
Total	1.12	100
	GeneXpert
Human cost	0.78	9.32
Training	0.05	0.60
Material and furniture	0.94	11.19
Cartridges	5.64	67.12
Running cost	0.62	7.38
Laboratory equipment	0.21	2.50
Non laboratory equipment	0.03	0.36
Infrastructure	0.13	1.55
Total	8.40	8.40
	Tuberculosis treatment
Human resources costs	3.33	8.04
Drugs	37.65	90.88
Laboratory maintenance and running	0.15	0.36
Material and furniture	0.21	0.51
Laboratory equipment	0.06	0.14
Non laboratory equipment	0.03	0.07
Total	41.43	100

Effectiveness analysis

Of the 275 patients, 97 patients were started on TB treatment through the algorithm A1-smear; 120 through the algorithm A2-LAM; 114 through the A3-smear&Xray; 128 through the A4-smear&LAM; 139 through the A5-LAM&smear&Xray; 116 through the A6-Xpert; 127 through the A7-Xpert&Xpert_urine; 137 through the A8-LAM&Xpert versus; 130 through the A9-Xpert&X-ray; 147 through the A10-LAM&Xpert&Xray (Table 3).

Table 3

Total cost and total DALYs averted (in euros, 4% discount, N = 275).

Algorithm(All algorithms include clinical exam as the first step in the diagnostic procedure)	Cost/TB case detected	Total TB detected confirmed by culture or GeneXpert	Costs (C)	DALYS (E)	Cost/Dalys
			(sd)	(sd)
			95%†	95%†
A1- Smear	58.75	97	5698.79	1117.52	5.10
			(1168.22)	(60.52)
			[3578.91; 8075.35]	[990.54; 1219.66]
A2- LAM	46.76	120	5612.27	1220.34	4.60
			(1170.96)	(154.41)
			[349.53; 8063.86]	[895.82; 1487.38]
A3- Smear&Xray	61.27	114	6985.27	1241.79	5.63
			(1276.50)	(42.20)
			[4633.90; 9622.90]	[1139.18; 1308.20]
A4-Smear&LAM	61.85	128	7917.63	1252.03	6.32
			(1467.62)	(180.68)
			[5235.30; 10962.78]	[868.91; 1561.51]
A5- LAM&smear&Xray	69.91	139	9718.50	1586.13	6.13
			(1542.25)	(93.59)
			[6862.41; 12896.07]	[1355.74; 1711.43]
A6- Xpert_sputum	48.39	116	5613.61	1193.12	4.70
			(1158.80)	(131.33)
			[3482.65; 8035.22]	[914.21 ; 1415.83]
A7- Xpert_sputum&Xpert_urine	63.57	127	8073.62	1217.66	6.63
			(1793.56)	(136.58)
			[4838.89 ; 11817.48]	[929.50 ; 1451.09]
A8-LAM&Xpert_sputum	57.28	137	7848.52	1284.57	6.11
			(1482.61)	(209.30)
			[5170.56; 10933.14]	[843.59; 1639.10]
A9- Xpert_sputum&X-ray	54.31		7061.09	1431.73	4.93
		130	(1274.41)	(73.14)
			[4687.28; 9691.11]	[1247.47 ; 1529.79]
A10- LAM&Xpert_sputum&Xray	66.38	147	9758.26	1651.43	5.91
			(1541.70)	(107.11)
			[6885.31; 12931.95]	[1388.34; 1796.55]

†CIs estimated using 10,000 non-parametric bootstrapping replicates

Cost-Effectiveness analysis

Table 3 presents the cost and DALYs/algorithm. The mean annualised cost of care for the 275 patients ranged from €5,612 (bootstrap 95% CI €3,495; 8,083) for the A2-LAM algorithm to €9,758 for the A10-LAM&Xpert&Xray (bootstrap 95% CI €6,940; 12,901). The mean DALYs ranged from 1,118 (bootstrap 95% CI €991; 1,220) from the A1-smear algorithm to 1,651 for the A10-LAM&Xpert&Xray (bootstrap 95% CI €1,388; 1,797). The two algorithms leading to the highest average cost/TB case detected were the algorithms that included more than 2 diagnostic tools in addition to the clinical exam: A10-LAM&Xpert_sputum&Xray (€66) and A5-LAM&smear&Xray algorithm (€70). These were also the algorithms that diagnosed the highest number of TB cases. The two algorithms leading to the least average cost/TB case detected were: A2-LAM (€47) and A6-Xpert_sputum (€48). These two algorithms detected a relatively high number of TB cases and they were the most cost-effective with a cost/DALY of €4.6 and €4.7 respectively.

Incremental costs and DALYs and the incremental cost effectiveness ratio are shown in Table 4. The algorithms with the highest increase in the cost-effectiveness ratio were replacing smear with LF-LAM and replacing GeneXpert in urine with LF-LAM. Replacing smear with LF-LAM test (A2-LAM versus A1-smear) allowed to detect 23 additional patients and reduced the cost by €87 for an incremental efficiency of 103 DALYs. Replacing GeneXpert in urine with LF-LAM test (A8-LAM&Xpert versus A7-Xpert&Xpert_urine) detected 10 additional patients and reduced the cost by €225 for an incremental efficiency of 70 DALYs.

Table 4

Incremental cost, incremental DALYs averted and ICER.

Algorithm(All algorithms include clinical exam as the first step in the diagnostic procedure)	Proportion of detected patients	ΔC (sd)(€, 95% CI†)	ΔE (Dalys)(sd)(95% CI†)	ICER (sd)(95% CI†)
A2- LAM vs. A1- Smear	+23	-86.52(1188.88)[-2412.32; 2274.95]	102.82(165.34)(-238.61; 395.47)	- 7.19(630.68)[-61.57 ; 62.93]
A4-Smear&LAM vs A1- Smear	+31	2218.84(1012.27)[-292.36; 4277.66]	134.51(189.68)(-263.24; 470.41)	21.96(1109.97)[-82.04; 103.27]
A4-Smear&LAM vs A3- Smear&Xray	+14	932.36(1044.36)[-1079.67; 3040.75]	10.24(185.66)(-376.58; 330.06)	7.78(652.37)[-79.70; 87.95]
A5- LAM&smear&Xray vs. A3- Smear&Xray	+25	2733.23(932.01)[1031.98; 4655.32]	344.34(103.09)(98.91; 511.07)	8.63(83.34)[-2.88; 21.41]
A4-Smear&LAM vs A6- Xpert_sputum	+12	2304.02(1495.18)[-627.40; 5320.22]	58.91(224.51)(-393.45; 479.22)	5.60(656.04)[-138.95; 144.29]
A7- Xpert_sputum&Xpert_urine vs. A6- Xpert_sputum	+11	2460.01(1029.11)[-449.47; 695.97]	24.53(188.64)(-342.98; 393.73)	2.64(749.79)[-226.23; 208.12]
A8-LAM&Xpert_sputum vs A6- Xpert_sputum	+21	2234.92(1085.30)[196.13; 4453.12]	91.44(246.42)(-411.40; 551.03)	24.02(982.73)[-114.03; 123.40]
A8-LAM&Xpert_sputum vs A7- Xpert_sputum&Xpert_urine	+10	-225.09(1377.01)[-3067.17; 2404.47]	66.90(248.52)[-435.93; 534.72)	- 12.56(905.64)[-58.28; 56.91]
A7- Xpert_sputum&Xpert_urine vs A9- Xpert_sputum&X-ray	+7	787.43(1078.75)[-1293.07; 2942.31]	-147.16(220.59)(-609.71; 250.60)	68.76(6743.72)[-85.76; 85.89]
A10- LAM&Xpert_sputum&Xray vs A9- Xpert_sputum&X-ray	+17	2697.17(933.73)[-972.34; 4609.89]	219.70(128.91)(-66.34; 456.55)	35.52(1452.88)[-37.85; 68.64]

†CIs estimated using 10,000 non-parametric bootstrapping replicates; ICER: Incremental Cost-Effectiveness Ratio

On the other hand, adding LF-LAM to smear microscopy alone (A4-smear&LAM versus A1-smear) or to smear microscopy and Xray (A5-LAM&smear&Xray versus A3-smear&Xray) detected respectively 31 and 25 additional patients for an incremental cost of €2,219 and €2,733. Their incremental efficiency was estimated respectively at 134 and 344 DALYs.

Fig 2 show the uncertainty assessment from the bootstrap procedure plotted on a cost-effectiveness plane for each algorithm comparison. This figure plot the differences in costs and differences in DALYs averted observed in the 10,000 bootstrap replicates. ICER's cost-effectiveness plane provides a visual representation of the comparison of the two algorithms. The cost-effectiveness plane is thus divided into four quadrants, a north-west-south-east axis where the new strategy is either dominated (it is more expensive and less efficient) or dominant (it is less expensive and more efficient), and a north-east-south-west axis where the decision-maker has to arbitrate between a health gain and a higher cost, or possibly accept a worse result for a lower expense according to the country willingness to pay [38]. ICERs give us the cost/gain of an additional efficiency unit. Introducing LF-LAM test gave us an approximately equivalent ICER when performed in addition to sputum microscopy (A4-smear &LAM versus A3-smear&Xray), performed in replacement of sputum microscopy (A2-LAM versus A1-smear) or done in parallel with sputum microscopy exam and Chest X-ray (A5-LAM&smear&Xray versus A3-smear&Xray), with respectively, €8/DALYs averted; €7/DALYs averted and €9/DALYs averted. The ICER reached €36/DALYs averted when LF-LAM test was performed instead of the GeneXpert test (A10-LAM&Xpert versus A9-Xpert&X-ray) and fell at €3/DALYs averted when an additional GeneXpert urine test was performed in addition to an GeneXpert sputum test (A7-Xpert&Xpert_urine versus A6-Xpert7 versus A6).

Fig 2

Cost-effectiveness planes.

This graph represent the differences in costs and DALYs between algorithms. DALYs are plot on the x axis and costs on the y axis. Results in costs and differences in DALYs averted observed in the 10, 000 bootstrap replicates.

Although the cost-effectiveness is done from the DALY, we chose to complement this with calculation of cost/TB case detected in order to provide information about the resource requirements for implementing the chosen algorithm. The cost/TB case detected ranged from €47 (A2-LAM algorithm) to €70 (A5- LAM&smear+Xray).

The Monte Carlo percent at willingness to pay (€2,673) is shown in Fig 3 where all algorithms were compared together. It represents the probability that one strategy will be efficient compared to all others. This global comparison could orient policy makers on the most efficient algorithm if the set of TB diagnostic tools is available in their country. For a willingness to pay of €2, 673, the acceptability percentage showed that there is 70% of chance that algorithm A10-LAM&Xpert+/-Xray was the most efficient. This percentage dropped to 29% for A5-LAM&smear+/-Xray algorithm. This rate reached 0% for A1-clinic&smear; A3-clinic&smear+/-Xray; A4-smear&LAM; A6-Xpert; A7-Xpert&Xpert_urine and A8-LAM&Xpert algorithms.

Fig 3

Probability of cost-effectiveness of each algorithm according to the society’s Willingness To Pay (€2,673).

The results of the sensitivity analyses do not change our results.

Discussion

The objective of this study was to rationally and comprehensively evaluate the cost of introduction of LF-LAM in TB diagnostic algorithms for severely ill or immunosuppressed HIV-positive patients. The comparison of the algorithms two by two leads to four main conclusions. Firstly, replacing smear microscopy with LF-LAM test is highly cost-effective. There are 23 additional patients detected for lower cost (€-87) and 103 effective incremental DALYs averted. This result is interesting and encouraging in the prospect of improving access to care in rural and remote areas that do not have access to even basic diagnostic devices, and no trained human resources. Scarcity of water and unreliable electricity supply are additional challenges in setting up smear microscopy. In order to circumvent these problems, LF-LAM could be an alternative to sputum microscopy for HIV-positive patients as it requires minimal skills and no laboratory equipment. More, LF-LAM is affordable, easy to transport, to use and produces results quickly. Secondly, in the same way, is the possibility to optimize the smear exam by adding the LF-LAM test, where 31 additional patients were detected for an ICER of €22/DALYs averted. In addition, it is preferable to favor the association of smear microscopy with LF-LAM rather than Chest-Xray as more patients were detected even though the ICER was less (€8/DALYs averted). Chest Xray requires expertise for interpreting with high inter-observer variability [39]. However, when this examination exists in addition to the smear, the addition of LF-LAM remains highly cost-effective with 25 additional patients detected and an ICER at €9/DALYs averted. Thirdly, it is more cost-effective to perform smear and LF-LAM tests than GeneXpert test alone and when GeneXpert is available, it is more cost-effective to perform GeneXpert in sputum and LF-LAM test rather than GeneXpert in sputum and GeneXpert in urine. The incremental cost is higher (€2,460 versus €2,234), but the incremental effectiveness is more important (91 DALYs averted versus 25 DALYs averted). The economic evaluation demonstrates that the incorporation of LF-LAM diagnostic tests in the set of TB diagnostic tool is highly cost-effective and complementary to clinical and radiological exams and GeneXpert. LF-LAM can be a real alternative for HIV-positive patients in areas with limited laboratory capacity. The cost-effectiveness analysis showed that the complementarity of all test was highly cost effective given the threshold of €2,673, the three times Kenya/capita annual gross income [27].

We also conducted an additional analysis where the ten algorithms are compared all together (Appendix Figure) in order to know which diagnostic algorithm should be preferred if the states had the set of available tests. We found that the A10-LAM & Xpert+/-Xray algorithm was the most cost-effective algorithm. Indeed, the 10,000 replicates bootstrap results shown that the A10-LAM&Xpert+/-Xray algorithm would be the preferred strategy given a willingness to pay of €2, 673. This algorithm had a 70% probability to be the most efficient. Despite the higher cost of this algorithm, this analysis shows that implementing an algorithm which includes all TB diagnostics tools available is highly cost-effective. This second analysis is interesting for countries with sufficient resources to have all available tests, but also having a sufficient enabling environment to allow the proper use of these tests (human resources, transportation etc.). Our main analysis will apply to countries with limited resources to provide all the tests such as where only sputum microscopy is implemented.

In a context of limited resources and fixed budget, a threshold serves as a reference for decision-makers. This normative threshold of three/capita gross national income implemented by Garber and Phelps [38] is used insofar as it is consistent with accepted practice for economic evaluation. The use of threshold values in decision-making has raised the question of possible uncontrolled growth in health expenditure. However, there are considered relevant as they represent the society’s willingness to pay [40].

This is in line with other cost-effectiveness studies of TB diagnostics incorporating the use of LF-LAM test in addition to GeneXpert assay conducted in Uganda [41] and in Uganda and South Africa [42]. In the Uganda study, the combination of GeneXpert with LF-LAM was considered highly cost-effective (ICER $57/DALY-averted) as compared to an algorithm of GeneXpert testing alone. In a study conducted in Uganda and South Africa, Sun et al. [42] found a cost-effectiveness of $353/DALY averted in South Africa and $86/DALY averted in Uganda. Sensitivity analysis confirmed the aforementioned results. In Malawi and South Africa, Reddy et al. [43] found a cost-effectiveness of $450/YLS in Malawi and $840/YLS in South Africa. We calculated of cost/TB case detected to provide an option for countries to identify resource requirements for implementing the chosen algorithm. It gives a basis for budgetary impact evaluation.

This study has some limitations. The first one is related to the study design. The diagnostic algorithms were evaluated from the same patient population in a prospective cohort and were not randomly allocated to different patient groups. Therefore, algorithms were not fully independent from each other, which may have affected their effectiveness outcomes. A second limitation is using culture or GeneXpert confirmed TB as reference for the assessment of the algorithms’ performance. This allowed to use a strong reference but excluded from the study population patients without culture or GeneXpert results. Some of them were diagnosed only through LF-LAM. The cost-effectiveness of using LF-LAM could have been higher if patients with symptoms and no culture or GeneXpert results had been included.

Conclusion

Using urine LF-LAM in addition or as replacement of other diagnostic TB tools is highly cost-effective for severely ill or immunosuppressed HIV-positive patients. A budget impact analysis is needed to guide policy makers.

Study database.

For all variables, 1 = « Yes » , 0 = « No »; Sex: 1 = male, 2 = Female; Ageonsetdisease = « age of onset of disease »; Yearbirth = « year of birth »; StandardresidualLE = « Standard residual life expectancy »; age of death HIV/TB = « expected age of death due to the HIV/TB co-infection »; BMI = « Body Mass Index »; lamfinal = « LAM test result »; goldstandall = « TB confirmed »; lamsmear = « algorithm Lam&Smear »; mortality2m = « Death at 2 month »; Cliniclam = « algorithm clinic&lam »; Clinicsmear = « algorithm clinic&smear »; Clinicsmearxray = « algorithm clinic&smear&xray »; Cliniclamsmear = « algorithm clinic&lam&smear »; Clinicxray = « algorithm clinic&xray »; Clinicxraylam = « algorithm clnic&xray&lam »; Clinicsmearxraylam = « algorithm clinic&smear&ray&lam »; clinicxpert1 = « algorithm clinic&xpert sputum »; clinicxpertlam1 = « algorithm clinic&xpert sputum&lam »; clinicxpertxray1 = « algorithm clnic&xray&xpert sputum »; clinicxpertxraylam1 = « algorithm clinic&xray&xpert sputum&lam »; YLD = « Years Lost due to Disability »; YLL = « Years of Life Lost due to premature mortality »; YLD treated clinicLAM = « Nmber of years lost due to screening for algorithm clinic&lam »; YLD treated Clinicsmear = « Number of years lost due to screening for algorithm clinic&smear »; YLD treated Clinicsmearxray = « Number of years lost due to screening for algorithm clinic&smear&xray »; YLD treated Cliniclamsmear = « Number of years lost due to screening for algorithm clinic&lam&smear »; YLD treated Clinicxray = « Number of years lost due to screening for algorithm clinic&xray »; YLD treated Clinicxraylam = « Number of years lost due to screening for algorithm clnic&xray&lam »; YLD treated Clinicsmearxraylam = « Number of years lost due to screening for algorithm clinic&smear&ray&lam »; YLD treated clinicxpert1 = « Number of years lost due to screening for algorithm clinic&xpert sputum »; YLD treated clinicxpertlam1 = « Number of years lost due to screening for algorithm clinic&xpert sputum&lam »; YLD treated clinicxpertxray1 = « Number of years lost due to screening for algorithm clnic&xray&xpert sputum »; YLD treated clinicxpertxraylam1 = « Number of years lost due to screening for algorithm clinic&xray&xpert sputum&lam »; DALYs = « Disability-Adjusted Life Year »; DALYavertedclinicLAM = « DALYs averted with algorithm clinic&lam »; DALYavertedClinicsmear = « DALYs averted with algorithm clinic&smear »; DALYavertedClinicsmearxray = « DALYs averted with algorithm clinic&smear&xray »; DALYavertedCliniclamsmear = « DALYs averted with algorithm clinic&lam&smear »; DALYavertedClinicxray = « DALYs averted with algorithm clinic&xray »; DALYavertedClinicxraylam = « DALYs averted with algorithm clnic&xray&lam »; DALYavertedClinicsmearxraylam = « DALYs averted with algorithm clinic&smear&ray&lam »; DALYavertedclinicxpert1 = « DALYs averted with algorithm clinic&xpert sputum »; DALYavertedclinicxpertlam1 = « DALYs averted with algorithm clinic&xpert sputum&lam »; DALYavertedclinicxpertxray1 = « DALYs averted with algorithm clnic&xray&xpert sputum »; DALYavertedclinicxpertxraylam1 = « DALYs averted with algorithm clinic&xray&xpert sputum&lam ».

(XLSX)

Click here for additional data file.

1 Oct 2019

PONE-D-19-20635

Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis

PLOS ONE

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https://doi.org/10.1371/journal.pone.0170976

https://doi.org/10.1371/journal.pmed.1002792

https://dx.doi.org/10.1371%2Fjournal.pone.0117009

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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: The manuscript entitled “Cost-effectiveness of diagnostic including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis” investigates the cost-effectiveness of including lateral-flow urine lipoarabinomannan (LF-LAM) in TB diagnostic algorithm for severely ill or immunosuppressed HIV-positive patients with symptoms of TB. Ten diagnostic algorithms have been elaborated and compared, and make a conclusion that including LF-LAM in TB diagnostic algorithms is cost-effective for severely ill or immunosuppressed HIV-positive patients.

Series of data have been done by authors to confirm the conclusion. However, there are some drawbacks making the paper to be reconsidered, as detailed below, before it can become suitable for publication in “PLOS ONE”.

Specific comments to the paper:

1. HIV patients often have difficulties to produce sputum, thus only the GeneXpert, LF-LAM seem to be fast and effective ways to detect TB. What the purpose of the research? What the novelty of the research?

2. All the figures in the manuscript were not clear, need to revise.

Reviewer #2: Manuscript PONE-D-19-20635: Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis

Key Results:

In the manuscript, Yakhelef et al. attempt to determine the cost effectiveness of the implementation of urine LF-LAM test for the detection of Tuberculosis (TB) positive patients whom are severely immunocompromised or are HIV positive using previous data from a study conducted at the Homa Bay County Hospital in Kenya. The authors used ten different algorithms, each containing a different combination of TB treatments starting from a smear alone up to combinations containing a mixture of LF-LAM, Gene Xpert from sputum, Gene Xpert from urine and X-ray detection. Their findings were reported in cost/patient/year in Euros as well as disability adjusted life year (DALY). From their analysis, the authors found that the greatest cost for treatment was anti-tuberculosis drugs (€41.42) and the cheapest costs was the chest X-ray (€1.12). When looking at the total cost/algorithm, the most expensive was A10 consisting of LF-LAM, Xpert from sputum and chest X-ray (€9758), while the least expensive was A2 consisting of LF-LAM alone (€5612). The mean DALY scores were found to be 1118 at its lowest for A1 and 1651 at its highest for A10. Using a cost effectiveness ratio, ICER, the authors determined that the two algorithms with the highest ratios were A2, detecting an additional 23 patients and decreasing costs by €87 as compared to A1, and A8, detecting an additional 10 patients and decreasing costs by €225 as compared to A7. Both of these findings indicate that adding LF-LAM to TB testing may decrease costs while increasing detection. Overall, the authors came to several conclusions: First, that adding LF-LAM testing to current methods is cost effective. Additionally, using LF-LAM in place of chest X-rays has the ability to detect more TB positive patients. Next, replacing Xpert in urine with LF-LAM is more cost effective and lastly, when comparing all of the algorithms to each other, A10 emerges as the most cost effective and most efficient overall if the country had the funds to implement it.

Validity:

After reading this manuscript, I believe that the concepts and findings of this study are valid and novel and may help provide further insight into the reduction of cost of TB diagnosis in resource deprived areas of the world.

Originality:

The results of this manuscript are original and significant. Further studies are needed to incorporate these findings into policy and influence policy makers, however, the authors address this issue in the paper.

Data and Methodology:

The data and methodology of this manuscript are valid and presented in a clear and concise manner. All data is presented clearly and are easy to interpret.

Appropriate use of Statistics:

The statistics in this manuscript are presented properly with a description of methods used, the proper numbers and significance values.

Conclusions:

Based on the experimental design and results presented, the conclusions present as valid and reliable.

Suggested Improvements:

Minor revisions:

- Introduction: This paper focuses on the LF-LAM assay, however, the assay is not described anywhere in the manuscript. Please consider adding a brief overview of the assay to familiarize the reader with what it does.

- Line 110: The title of your figure should give the reader a brief description of what they are looking at. Please consider revising this title as well as those in other figures and tables in the manuscript as many are very sparse in description.

- Cost estimation: Line 129: The acronym IPSOR is used without definition. Please define.

- Cost estimation: Line 163: The acronym CXR is used without definition. Please define.

- Cost estimation: Line 155: “pipette” should be plural in this case, should be “pipettes”

- Cost estimation: Line 164: Here and in several places in the manuscript you indicate that a 4% discount was applied, however, I could not find the reasoning for this discount. Please consider adding an explanation to the manuscript.

- Line 173: “Tables 1” does not need to be plural in this instance, should be “Table 1”

- Study population: Line 199: Are these all of the statistics that are available for the patients? Consider adding additional statistics if possible.

- Study population: Line 200: “patients had a confirmed TB” should not have an “a”. Should read “patients had confirmed TB”

- Line 218: “Tables 3” does not need to be plural. Should read “Table 3”

- Line 249: “Figures 2” does not need to be plural. Should read “Figure 2”

- Line 256: The acronym WTP is used without definition. Please define.

- Lines 274-279: This paragraph is very confusing the way that it is written, please consider revising.

- Line 326: The acronym GNI is used without definition. Please define.

References:

References are cited properly and addressed properly where needed.

Clarity and Context:

The abstract, introduction and conclusion contain the proper information that will engage the reader and provide insight to the paper as a whole.

Scope of Expertise:

None of the material presented were out of the scope of my expertise. All were logical and easily understood.

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23 Nov 2019

Response to Reviewers

PONE-D-19-20635

Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis

Journal Requirements:

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

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:

http://www.journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and http://www.journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf

Réponse : we modified according to the requirements of PLOS ONE :

- The affiliation of the authors and we wrote a legend about the work of each author

- We modified the presentation of figures and tables titles and legends

2. We noticed you have some minor occurrence(s) of overlapping text with the following previous publication(s), which needs to be addressed: :

https://doi.org/10.5588/ijtld.13.0630

https://doi.org/10.1371/journal.pone.0170976

https://doi.org/10.1371/journal.pmed.1002792

https://dx.doi.org/10.1371%2Fjournal.pone.0117009

https://halshs.archives-ouvertes.fr/halshs-01241824/file/2015.34.pdf

In your revision ensure you cite all your sources (including your own works), and quote or rephrase any duplicated text outside the Methods section. Further consideration is dependent on these concerns being addressed.

Response: Thank you, we modify as follows:

- https://doi.org/10.5588/ijtld.13.0630 � This reference has been added [19] (lines 148, 157, 174 of the manuscript) and we modify the passages where there were certain occurrences (lines 148 to 154 and 179 to 182 of the manuscript)

- https://doi.org/10.1371/journal.pone.0170976 �This reference [15] has been added lines 78 and 110 of the manuscript

- ttps://halshs.archives-ouvertes.fr/halshs-01241824/file/2015.34.pdf � we modify the sections where there were certain occurrences (lines 355 to 357 of the manuscript)

- https://dx.doi.org/10.1371%2Fjournal.pone.0117009 �This reference [30] has been added lines 206

3. We note that you have numbered 5 affiliations in your title page, but only assigned 1,2,3, & 4 to authors. Please assign all the affiliations listed to an author, or remove no.5 if it is not needed

Response: Thank you, the mistake has been corrected.

4. We note that you have stated that you will provide repository information for your data at acceptance. Should your manuscript be accepted for publication, we will hold it until you provide the relevant accession numbers or DOIs necessary to access your data. If you wish to make changes to your Data Availability statement, please describe these changes in your cover letter and we will update your Data Availability statement to reflect the information you provide.

Response: thanks for the comment, it is well noted

We have added a paragraph “supporting information” line 505-507

5. Review Comments to the Author

Reviewer #1:

1. HIV patients often have difficulties to produce sputum, thus only the GeneXpert, LF-LAM seem to be fast and effective ways to detect TB. What the purpose of the research? What the novelty of the research?

Response:

Thank you for this question. To enlighten the reader we have added a paragraph on the purpose as well as the novelty of this research at the end of the introduction (lines 85 to 88 of the manuscript)

2. All the figures in the manuscript were not clear, need to revise.

Response: Thank you for this remark. We have improved the quality of the figures. In case our article is accepted, we will also discuss with PLOS One production team how to improve further the quality of the figures.

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

Reviewer #2: Manuscript PONE-D-19-20635: Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis

- Introduction: This paper focuses on the LF-LAM assay, however, the assay is not described anywhere in the manuscript. Please consider adding a brief overview of the assay to familiarize the reader with what it does.

Response: Thank you for this proposition, we have added a brief overview of the assay (lines 62 to 71 of the manuscript)

- Line 110: The title of your figure should give the reader a brief description of what they are looking at. Please consider revising this title as well as those in other figures and tables in the manuscript as many are very sparse in description.

Response: Thank you for this remark, we agree. We have changed Figure titles as follows:

- Fig 1. Diagnostic algorithms using microscopy or GeneXpert alone or in combination with chest X-ray versus LF-LAM alone or in addition to other TB diagnostic tools (lines 125-126 of the manuscript)

- Fig 2. Cost-effectiveness planes (This graph represent the differences in costs and DALYs between algorithms. DALYs are plot on the x axis and costs on the y axis. Results in costs and differences in DALYs averted observed in the 10, 000 bootstrap replicates) lines 296 to 298 of the manuscript)

- Fig 3. Probability of cost-effectiveness of each algorithm according to the society’s Willingness To Pay (WTP) (€2,673) (lines 308-309 of the manuscript)

- Cost estimation: Line 129: The acronym IPSOR is used without definition. Please define.

Response : Thank you for this remark, the acronym has been defined (lines 145-146 of the manuscript)

- Cost estimation: Line 163: The acronym CXR is used without definition. Please define.

Response : Thank you for this remark, we have changed CXR by Chest X-ray. (line 180 of the manuscript)

- Cost estimation: Line 155: “pipette” should be plural in this case, should be “pipettes”

Response :Thank you for this remark, we have added an « s » to the word pipettes (line 172 of the manuscript)

- Cost estimation: Line 164: Here and in several places in the manuscript you indicate that a 4% discount was applied, however, I could not find the reasoning for this discount. Please consider adding an explanation to the manuscript.

Response :. Thank you for this comment. We have added an explanation and justified the rate discount chosen which is a recommendation of the French Health Authority (lines 181-182 and 189 of the manuscript)

- Line 173: “Tables 1” does not need to be plural in this instance, should be “Table 1”

Response: Thank you , we have deleted the « s » (line 192 of the manuscript)

- Study population: Line 199: Are these all of the statistics that are available for the patients? Consider adding additional statistics if possible.

Response: Thank you. We have included some additional description of the population as suggested (lines 218 to 225 of the manuscript)

- Study population: Line 200: “patients had a confirmed TB” should not have an “a”. Should read “patients had confirmed TB”

Response : Thank you , we have deleted the « a » (line 226 of the manuscript)

- Line 218: “Tables 3” does not need to be plural. Should read “Table 3”

Response : Thank you , we have deleted the « s » (line 244 of the manuscript)

- Line 249: “Figures 2” does not need to be plural. Should read “Figure 2”

Response : Thank you, we have removed the « s » (line 275 of the manuscript)

- Line 256: The acronym WTP is used without definition. Please define.

Response : Thank you, we have removed the acronym all over the manuscript and used the full word and, we propose to add a definition at this level (lines 202-203 of the manuscript).

- Lines 274-279: This paragraph is very confusing the way that it is written, please consider revising.

Response: Thank you for this comment. We have modified the paragraph as suggested (line 299 to 306 of the manuscript)

- Line 326: The acronym GNI is used without definition. Please define.

Response: Thank you for this comment. Thank you, we have removed the acronym all over the manuscript and used the full word.

Submitted filename: Response to Reviewers.docx

Click here for additional data file.

3 Dec 2019

PONE-D-19-20635R1

Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis

PLOS ONE

Dear Dr. Nadia,

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.

We would appreciate receiving your revised manuscript. When you are 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.

If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter.

To enhance the reproducibility of your results, we recommend that if applicable you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see: http://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols

Please include the following items when submitting your revised manuscript:

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Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

We look forward to receiving your revised manuscript.

Kind regards,

Frederick Quinn

Academic Editor

PLOS ONE

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Reviewers' comments:

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Comments to the Author

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Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

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

Reviewer #1: The revised manuscrip covered all my comments, while there are still exist several minimal mistakes in the revised mauscript.

minimal comments:

1. In line 152, there are two dots, remove one.

2. In the revise manuscript, several references "underline", remove the underline. such as, in line 181, 185, 189, et al.

3. In line 156, reference [17], [19], should be changed into [17, 19].

4. In line 158, in the sentence “number of patients/day", should be changed into "number of patients per day".

5. In line 160, "First" should be changed into "Firstly".

6. In Table 1, in the setences "Age at oneset of disablity a" and "Age of death a", what the word a stand for?

7. In the line 201, the reference [23-24], shoukd be changed into [23, 24].

8. In the line 213, the reference [17-18], shoukd be changed into [17, 18].

9. In the line 222, 100~199 cells/u, should be changed into 100~199 cells/uL.

10. The references in this manuscript should be adjust to fit the PloS One. I saw many differences in the references, such as reference 10, 201-9, should be changed into 201-209. Please doubcheck the references.

Reviewer #2: None. The authors have addressed all of the suggestions that were put forth by me in the initial review. Thank you.

**********

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

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

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

Reviewer #1: No

Reviewer #2: No

[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 to be viewed.]

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 us at figures@plos.org. Please note that Supporting Information files do not need this step.

4 Dec 2019

Response to Reviewers

PONE-D-19-20635R1

Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis

PLOS ONE

6. Review Comments to the Author

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

Reviewer #1: The revised manuscrip covered all my comments, while there are still exist several minimal mistakes in the revised mauscript.

minimal comments:

1. In line 152, there are two dots, remove one.

Response: Thank you , we have deleted the dots (line 152 of the manuscript)

2. In the revise manuscript, several references "underline", remove the underline. such as, in line 181, 185, 189, et al.

Response : Thank you for this remark, we have modified all “underline” references

3. In line 156, reference [17], [19], should be changed into [17, 19].

Response : Thank you for this remark, we have changed reference [17] [19] by [17,19] (line 156 of the manuscript)

4. In line 158, in the sentence “number of patients/day", should be changed into "number of patients per day".

Response : Thank you for this remark, we have changed “number of patients/day” by “number of patients per day” (line 158 of the manuscript)

5. In line 160, "First" should be changed into "Firstly".

Response : Thank you for this remark, we have changed “First” by “Firstly” (line 160 of the manuscript)

6. In Table 1, in the setences "Age at oneset of disablity a" and "Age of death a", what the word a stand for?

Response: Thank you for this careful reading, this is a mistake, we have deleted the “a” (table 1 of the manuscript)

7. In the line 201, the reference [23-24], shoukd be changed into [23, 24].

Response : Thank you for this remark, we have changed reference [23-24] by [23, 24] (line 199 of the manuscript)

8. In the line 213, the reference [17-18], shoukd be changed into [17, 18].

Response : Thank you for this remark, we have changed reference [17-18] by [17, 18] (line 211 of the manuscript)

9. In the line 222, 100~199 cells/u, should be changed into 100~199 cells/uL.

Response : Thank you for this remark, we have changed 100~199 cells/u by 100~199 cells/uL (line 220 of the manuscript)

10. The references in this manuscript should be adjust to fit the PloS One. I saw many differences in the references, such as reference 10, 201-9, should be changed into 201-209. Please doubcheck the references.

Response : Thank you for this remark, we have adjusted the following refeneces : 6, 10, 23, 28, 35, 39, 40, 42

Reviewer #2: None. The authors have addressed all of the suggestions that were put forth by me in the initial review. Thank you.

________________________________________

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.

Response : Thank you, this is well noted

Submitted filename: Response to Reviewers_.docx

Click here for additional data file.

13 Dec 2019

Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis

PONE-D-19-20635R2

Dear Dr. Nadia,

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

Within one week, you will receive an e-mail containing information on the amendments required prior to publication. When all required modifications have been addressed, you will receive a formal acceptance letter and your manuscript will proceed to our production department and be scheduled for publication.

Shortly after the formal acceptance letter is sent, an invoice for payment will follow. To ensure an efficient production and billing process, please log into Editorial Manager at https://www.editorialmanager.com/pone/, click the "Update My Information" link at the top of the page, and update your user information. 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 enable them to help maximize its impact. If they will be preparing press materials for this manuscript, you must inform our press team as soon as possible and 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.

With kind regards,

Frederick Quinn

Academic Editor

PLOS ONE

Additional Editor Comments (optional):

Reviewers' comments:

Reviewer's Responses to Questions

Comments to the Author

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

Reviewer #1: All comments have been addressed

Reviewer #2: All comments have been addressed

**********

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

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

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

Reviewer #1: Yes

Reviewer #2: Yes

**********

6. Review Comments to the Author

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

Reviewer #1: The revised manuscript covered all my comments.I have no comments to the authors. Thus, I recommend to accept this manuscript.

Reviewer #2: The authors had addressed my issues and concerns in a previous revision. I have no additional comments.

**********

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

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

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

Reviewer #1: No

Reviewer #2: No

7 Jan 2020

PONE-D-19-20635R2

Cost-effectiveness of diagnostic algorithms including lateral-flow urine lipoarabinomannan for HIV-positive patients with symptoms of tuberculosis

Dear Dr. Yakhelef:

I am 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 notify them about your upcoming paper at this point, to enable them to help maximize its impact. If they will be preparing press materials for this manuscript, 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.

For any other questions or concerns, please email plosone@plos.org.

Thank you for submitting your work to PLOS ONE.

With kind regards,

PLOS ONE Editorial Office Staff

on behalf of

Dr. Frederick Quinn

Academic Editor

PLOS ONE