Potential Market for Novel Tuberculosis Diagnostics: Worth the Investment?

Background. The potential available market (PAM) for new diagnostics for tuberculosis that meet the specifications of the high-priority target product profiles (TPPs) is currently unknown. Methods. We estimated the PAM in 2020 in 4 high-burden countries (South Africa, Brazil, China, and India) for tests that meet the specifications outlined in the TPPs. The yearly PAM was estimated for the most likely application of each TPP. Results. In 2020 the PAM for all 4 countries together was estimated to be (1) 12M tests/year with a value of 48M-71M USD for a sputum smear-replacement test; (2) 16M tests/year with a value of 65M-97M USD for a biomarker test; (3) 18M tests/year with a value of 18M-35M USD for a triage test; (4) 12M tests/year with a value of 59M-2238M USD for a tuberculosis detection plus drug susceptibility test (DST) all-in-one or 1.5M tests/year for a DST that follows a positive tuberculosis detection test with a corresponding value of 75M-121M for both tuberculosis detection and DST. Conclusions. Although there is a considerable potential market for novel tuberculosis diagnostics that fit the specification of the TPPs in the 4 high-burden countries, the actual market for an individual product remains uncertai

Direct and indirect costs of tuberculosis among immigrant patients in the Netherlands

<p>Abstract</p> <p>Background</p> <p>In low tuberculosis (TB) incidence countries TB affects mostly immigrants in the productive age group. Little empirical information is available about direct and indirect TB-related costs that patients face in these high-income countries. We assessed the direct and indirect costs of immigrants with TB in the Netherlands.</p> <p>Methods</p> <p>A cross-sectional survey at 14 municipal health services and 2 specialized TB hospitals was conducted. Interviews were administered to first or second generation immigrants, 18 years or older, with pulmonary or extrapulmonary TB, who were on treatment for 1–6 months. Out of pocket expenditures and time loss, related to TB, was assessed for different phases of the current TB illness.</p> <p>Results</p> <p>In total 60 patients were interviewed. Average direct costs spent by households with a TB patient amounted €353. Most costs were spent when being hospitalized. Time loss (mean 81 days) was mainly due to hospitalization (19 days) and additional work days lost (60 days), and corresponded with a cost estimation of €2603.</p> <p>Conclusion</p> <p>Even in a country with a good health insurance system that covers medication and consultation costs, patients do have substantial extra expenditures. Furthermore, our patients lost on average 2.7 months of productive days. TB patients are economically vulnerable.</p

Treatment for radiographically active, sputum culture-negative pulmonary tuberculosis: a systematic review and meta-analysis

Background: People with radiographic evidence for pulmonary tuberculosis (TB), but negative sputum cultures, have increased risk of developing culture-positive TB. Recent expansion of X-ray screening is leading to increased identification of this group. We set out to synthesise the evidence for treatment to prevent progression to culture-positive disease. Methods: We conducted a systematic review and meta-analysis. We searched for prospective trials evaluating the efficacy of TB regimens against placebo, observation, or alternative regimens, for the treatment of adults and children with radiographic evidence of TB but culture-negative respiratory samples. Databases were searched up to 18 Oct 2022. Study quality was assessed using ROB 2·0 and ROBINS-I. The primary outcome was progression to culture-positive TB. Meta-analysis with a random effects model was conducted to estimate pooled efficacy. This study was registered with PROSPERO (CRD42021248486). Findings: We included 13 trials (32,568 individuals) conducted between 1955 and 2018. Radiographic and bacteriological criteria for inclusion varied. 19·1% to 57·9% of participants with active x-ray changes and no treatment progressed to culture-positive disease. Progression was reduced with any treatment (6 studies, risk ratio [RR] 0·27, 95%CI 0·13–0·56), although multi-drug TB treatment (RR 0·11, 95%CI 0·05–0·23) was significantly more effective than isoniazid treatment (RR 0·63, 95%CI 0·35–1·13) (p = 0·0002). Interpretation: Multi-drug regimens were associated with significantly reduced risk of progression to TB disease for individuals with radiographically apparent, but culture-negative TB. However, most studies were old, conducted prior to the HIV epidemic and with outdated regimens. New clinical trials are required to identify the optimal treatment approach

Economic analysis of different throughput scenarios and implementation strategies of computer-aided detection software as a screening and triage test for pulmonary TB.

BackgroundArtificial Intelligence (AI) systems have demonstrated potential in detecting tuberculosis (TB) associated abnormalities from chest X-ray (CXR) images. Thus, they might provide a solution to radiologist shortages in high TB burden countries. However, the cost of implementing computer-aided detection (CAD) software has thus far been understudied. In this study, we performed a costing analysis of CAD software when used as a screening or triage test for pulmonary TB, estimated the incremental cost compared to a radiologist reading of different throughput scenarios, and predicted the cost for the national scale-up plan in Pakistan.MethodsFor the study, we focused on CAD software reviewed by the World Health Organization (CAD4TB, Lunit INSIGHT CXR, qXR) or listed in the Global Drug Facility diagnostics catalogue (CAD4TB, InferRead). Costing information was obtained from the CAD software developers. CAD4TB and InferRead use a perpetual license pricing model, while Lunit and qXR are priced per license for restricted number of scans. A major implementer in Pakistan provided costing information for human resource and software training. The per-screen cost was estimated for each CAD software and for radiologist for 1) active case finding, and 2) facility based CXR testing scenarios with throughputs ranging from 50,000-100,000 scans. Moreover, we estimated the scale-up cost for CAD or radiologist CXR reading in Pakistan based on the National Strategic Plan, considering that to reach 80% diagnostic coverage, 50% of TB patients would need to be found through facility-based triage and 30% through active case finding (ACF).ResultsThe per-screen cost for CAD4TB (0.25 USD- 2.33 USD) and InferRead (0.19 USD- 2.78 USD) was lower than that of a radiologist (0.70 USD- 0.93 USD) for high throughput scenarios studied. In comparison, the per-screen cost for Lunit (0.94 USD- 1.69 USD) and qXR (0.95 USD-1.9 USD) were only comparable with that of the radiologists in the highest throughput scenario in ACF. To achieve 80 percent diagnostic coverage at scale in Pakistan, the projected additional cost of deploying CAD software to complement the current infrastructure over a four-year period were estimated at 2.65-19.23 million USD, whereas Human readers, would cost an additional 23.97 million USD.ConclusionsOur findings suggest that using CAD software could enable large-scale screening programs in high TB-burden countries and be less costly than radiologist. To achieve minimum cost, the target number of screens in a specific screening strategy should be carefully considered when selecting CAD software, along with the offered pricing structure and other aspects such as performance and operational features. Integrating CAD software in implementation strategies for case finding could be an economical way to attain the intended programmatic goals

Variation in T-SPOT.TB Spot Interpretation between Independent Observers from Different Laboratories▿

T-SPOT.TB is a specific assay for the diagnosis of tuberculosis. The assay needs to be performed with freshly isolated cells, and interpretation requires training. T-SPOT.TB has been used in various clinical-epidemiological settings, but so far no studies have evaluated the effect of interobserver variation in test reading. Our aim was to evaluate variation between different observers in reading T-SPOT.TB results. The study was nested within an ongoing cohort study, in which part of the T-SPOT.TB had been performed with frozen material. Culture plates were read visually by four different observers from two laboratories and by two automated readers. Of 313 T-SPOT.TB assays, 235 were performed with fresh cells and 78 were performed with frozen cells. No significant difference was found between results obtained with fresh cells and those obtained with frozen cells. The percentage of positive results varied between readers by maximally 15%; five/six raters were within a 6% difference in positive results. Analysis of the observed interrater differences showed that some individuals systematically counted more spots than others did. Because test interpretation includes subtraction of background values, this systematic variance had little influence on interindividual differences. The test result as positive or negative varied between independent raters, mainly due to samples with values around the cutoff. This warrants further study regarding determinants affecting the reading of T-SPOT.TB

Cost of three models of care for drug-resistant tuberculosis patients in Nigeria

Background: Nigeria accounts for a significant proportion of the global drug-resistant tuberculosis (DR-TB) burden, a large proportion of which goes untreated. Different models for managing DR-TB treatment with varying levels of hospitalization are in use across Nigeria, however costing evidence is required to guide the scale up of DR-TB care. We aimed to estimate and compare the costs of different DR-TB treatment and care models in Nigeria. Methods: We estimated the costs associated with three models of DR-TB treatment and care: Model (A) patients are hospitalized throughout the 8-month intensive phase, Model (B) patients are partially hospitalized during the intensive phase and Model (C) is entirely ambulatory. Costs of treatment, in-patient and outpatient care and diagnostic and monitoring tests were collected using a standardized data collection sheet from six sites through an ingredient's approach and cost models were based on the Nigerian National Tuberculosis, Leprosy and Buruli Ulcer Guideline - Sixth Edition (2014) and Guideline for programmatic and clinical management of drug-resistant tuberculosis in Nigeria (2015). Results: Assuming adherence to the Nigerian DR-TB guidelines, the per patient cost of Model A was 18,528 USD, Model B 15,159 USD and Model C 9425 USD. Major drivers of cost included hospitalization (Models A and B) and costs of out-patient consultations and supervision (Model C). Conclusion: Utilizing a decentralized ambulatory model, is a more economically viable approach for the expansion of DR-TB care in Nigeria, given that patient beds for DR-TB treatment and care are limited and costs of hospitalized treatment are considerably more expensive than ambulatory models. Scale-up of less expensive ambulatory care models should be carefully considered in particular, when treatment efficacy is demonstrated to be similar across the different models to allow for patients not requiring hospitalization to be cared for in the least expensive way

Serial testing for latent tuberculosis using QuantiFERON-TB Gold In-Tube: A Markov model.

Healthcare workers (HCWs) in low-incidence settings are often serially tested for latent TB infection (LTBI) with the QuantiFERON-TB Gold In-Tube (QFT) assay, which exhibits frequent conversions and reversions. The clinical impact of such variability on serial testing remains unknown. We used a microsimulation Markov model that accounts for major sources of variability to project diagnostic outcomes in a simulated North American HCW cohort. Serial testing using a single QFT with the recommended conversion cutoff (IFN-g &gt; 0.35 IU/mL) resulted in 24.6% (95% uncertainty range, UR: 23.8-25.5) of the entire population testing false-positive over ten years. Raising the cutoff to &gt;1.0 IU/mL or confirming initial positive results with a (presumed independent) second test reduced this false-positive percentage to 2.3% (95%UR: 2.0-2.6%) or 4.1% (95%UR: 3.7-4.5%), but also reduced the proportion of true incident infections detected within the first year of infection from 76.5% (95%UR: 66.3-84.6%) to 54.8% (95%UR: 44.6-64.5%) or 61.5% (95%UR: 51.6-70.9%), respectively. Serial QFT testing of HCWs in North America may result in tremendous over-diagnosis and over-treatment of LTBI, with nearly thirty false-positives for every true infection diagnosed. Using higher cutoffs for conversion or confirmatory tests (for initial positives) can mitigate these effects, but will also diagnose fewer true infections

Gamma Interferon Release Assays for Detection of Mycobacterium tuberculosis Infection

Identification and treatment of latent tuberculosis infection (LTBI) can substantially reduce the risk of developing active disease. However, there is no diagnostic gold standard for LTBI. Two tests are available for identification of LTBI: the tuberculin skin test (TST) and the gamma interferon (IFN-γ) release assay (IGRA). Evidence suggests that both TST and IGRA are acceptable but imperfect tests. They represent indirect markers of Mycobacterium tuberculosis exposure and indicate a cellular immune response to M. tuberculosis. Neither test can accurately differentiate between LTBI and active TB, distinguish reactivation from reinfection, or resolve the various stages within the spectrum of M. tuberculosis infection. Both TST and IGRA have reduced sensitivity in immunocompromised patients and have low predictive value for progression to active TB. To maximize the positive predictive value of existing tests, LTBI screening should be reserved for those who are at sufficiently high risk of progressing to disease. Such high-risk individuals may be identifiable by using multivariable risk prediction models that incorporate test results with risk factors and using serial testing to resolve underlying phenotypes. In the longer term, basic research is necessary to identify highly predictive biomarkers