‘If not TB, what could it be?’ Chest X-ray findings from the 2016 Kenya Tuberculosis Prevalence Survey

Mungai, Brenda; Joekes, Elizabeth; Masini, Enos; Obasi, Angela; Manduku, Veronica; Mugi, Beatrice; Ong’ang’o, Jane Rahedi; Kirathe, Dickson; Kiplimo, Richard; Sitienei, Joseph; Oronje, Rose; Morton, Ben; Squire, S Bertel; MacPherson, Peter

doi:10.1136/thoraxjnl-2020-216123

Cited by 27 publications

(40 citation statements)

References 18 publications

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“…In this pragmatic trial, alternative diagnoses to TB were not investigated, with participants referred to routine clinic or hospital care as required. If DCXR-CAD is widely implemented, clear clinical pathways for people who have an abnormal CAD4TB score, but who are sputum Xpert negative, will be required [ 41 ]. Although more participants initiated TB treatment in the HIV-TB screening arm compared to the other arms, the proportion with undiagnosed TB was similar across arms.…”

Section: Discussionmentioning

confidence: 99%

Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis

et al. 2021

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Background Suboptimal tuberculosis (TB) diagnostics and HIV contribute to the high global burden of TB. We investigated costs and yield from systematic HIV-TB screening, including computer-aided digital chest X-ray (DCXR-CAD). Methods and findings In this open, three-arm randomised trial, adults (≥18 years) with cough attending acute primary services in Malawi were randomised (1:1:1) to standard of care (SOC); oral HIV testing (HIV screening) and linkage to care; or HIV testing and linkage to care plus DCXR-CAD with sputum Xpert for high CAD4TBv5 scores (HIV-TB screening). Participants and study staff were not blinded to intervention allocation, but investigator blinding was maintained until final analysis. The primary outcome was time to TB treatment. Secondary outcomes included proportion with same-day TB treatment; prevalence of undiagnosed/untreated bacteriologically confirmed TB on day 56; and undiagnosed/untreated HIV. Analysis was done on an intention-to-treat basis. Cost-effectiveness analysis used a health-provider perspective. Between 15 November 2018 and 27 November 2019, 8,236 were screened for eligibility, with 473, 492, and 497 randomly allocated to SOC, HIV, and HIV-TB screening arms; 53 (11%), 52 (9%), and 47 (9%) were lost to follow-up, respectively. At 56 days, TB treatment had been started in 5 (1.1%) SOC, 8 (1.6%) HIV screening, and 15 (3.0%) HIV-TB screening participants. Median (IQR) time to TB treatment was 11 (6.5 to 38), 6 (1 to 22), and 1 (0 to 3) days (hazard ratio for HIV-TB versus SOC: 2.86, 1.04 to 7.87), with same-day treatment of 0/5 (0%) SOC, 1/8 (12.5%) HIV, and 6/15 (40.0%) HIV-TB screening arm TB patients (p = 0.03). At day 56, 2 SOC (0.5%), 4 HIV (1.0%), and 2 HIV-TB (0.5%) participants had undiagnosed microbiologically confirmed TB. HIV screening reduced the proportion with undiagnosed or untreated HIV from 10 (2.7%) in the SOC arm to 2 (0.5%) in the HIV screening arm (risk ratio [RR]: 0.18, 0.04 to 0.83), and 1 (0.2%) in the HIV-TB screening arm (RR: 0.09, 0.01 to 0.71). Incremental costs were US$3.58 and US$19.92 per participant screened for HIV and HIV-TB; the probability of cost-effectiveness at a US$1,200/quality-adjusted life year (QALY) threshold was 83.9% and 0%. Main limitations were the lower than anticipated prevalence of TB and short participant follow-up period; cost and quality of life benefits of this screening approach may accrue over a longer time horizon. Conclusions DCXR-CAD with universal HIV screening significantly increased the timeliness and completeness of HIV and TB diagnosis. If implemented at scale, this has potential to rapidly and efficiently improve TB and HIV diagnosis and treatment. Trial registration clinicaltrials.gov NCT03519425.

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Section: Discussionmentioning

confidence: 99%

Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis

et al. 2021

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“…(16,29,30) Conditions other than TB may be as, or more prevalent than TB in high TB prevalence settings, and require comprehensive approaches to ensure participants in TB screening programmes are linked to appropriate care. (31) TB screening programs should plan for this and take into consideration resource implications to ensure additional health benefits through the identification of populations at risk of diseases other than TB. In addition to diagnostic accuracy; clinical utility, acceptability and feasibility of using CAD should be assessed.…”

Section: Figure 3: Model-based Sensitivity and Specificity Of Cad4tbv6 For Bacteriologically-confirmed Pulmonary Tb At Minimum And Optimumentioning

confidence: 99%

Accuracy of computer-aided chest X-ray screening in the Kenya National Tuberculosis Prevalence Survey

Mungai

Ong’ang’o

et al. 2021

Preprint

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BackgroundCommunity-based screening for tuberculosis (TB) could improve detection but is resource intensive. We set out to evaluate the accuracy of computer-aided TB screening using digital chest X-ray (CXR) to determine if this approach met target product profiles (TPP) for community-based screening.MethodsCXR images from participants in the 2016 Kenya National TB Prevalence Survey were evaluated using CAD4TBv6 (Delft Imaging), giving a probabilistic score for pulmonary TB ranging from 0 (low probability) to 99 (high probability). We constructed a Bayesian latent class model to estimate the accuracy of CAD4TBv6 screening compared to bacteriologically-confirmed TB across CAD4TBv6 threshold cut-offs, incorporating data on Clinical Officer CXR interpretation, participant demographics (age, sex, TB symptoms, previous TB history), and sputum results. We compared model-estimated sensitivity and specificity of CAD4TBv6 to optimum and minimum TPPs.ResultsOf 63,050 prevalence survey participants, 61,848 (98%) had analysable CXR images, and 8,966 (14.5%) underwent sputum bacteriological testing; 298 had bacteriologically-confirmed pulmonary TB. Median CAD4TBv6 scores for participants with bacteriologically-confirmed TB were significantly higher (72, IQR: 58-82.75) compared to participants with bacteriologically-negative sputum results (49, IQR: 44-57, p<0.0001). CAD4TBv6 met the optimum TPP; with the threshold set to achieve a mean sensitivity of 95% (optimum TPP), specificity was 83.3%, (95% credible interval [CrI]: 83.0%—83.7%, CAD4TBv6 threshold: 55). There was considerable variation in accuracy by participant characteristics, with older individuals and those with previous TB having lowest specificity.ConclusionsCAD4TBv6 met the optimal TPP for TB community screening. To optimise screening accuracy and efficiency of confirmatory sputum testing, we recommend that an adaptive approach to threshold setting is adopted based on participant characteristics.Take home messageCAD4TBv6 met the optimal WHO target product profile for a community TB screening tool. Specificity was lower in adults with previous TB and those aged 41 years or older; an adaptive approach to setting CAD thresholds will likely be required to optimize use.

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“…Computer‐assisted digital chest X‐ray (CADXR) displays high sensitivity for the identification of features of TB but is not well calibrated for identifying non‐TB X‐ray abnormalities [5]. Additionally, non‐TB X‐ray abnormalities have not been well characterised in the sub‐Saharan African setting [4].…”

Section: Introductionmentioning

confidence: 99%

Pattern of abnormalities amongst chest X‐rays of adults undergoing computer‐assisted digital chest X‐ray screening for tuberculosis in Peri‐Urban Blantyre, Malawi: A cross‐sectional study

Twabi

Semphere

Mukoka

et al. 2021

Tropical Med Int Health

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Background The prevalence of diseases other than tuberculosis (TB) detected during chest X‐ray screening is poorly described in sub‐Saharan Africa. Computer‐assisted digital chest X‐ray technology is available for TB screening and has the potential to be a screening tool for non‐communicable diseases as well. Low‐ and middle‐income countries are in a transition period where the burden of non‐communicable diseases is increasing, but health systems are mainly focused on addressing infectious diseases. Methods Participants were adults undergoing computer‐assisted chest X‐ray screening for tuberculosis in a community‐wide tuberculosis prevalence survey in Blantyre, Malawi. Adults with abnormal radiographs by field radiographer interpretation were evaluated by a physician in a community‐based clinic. X‐ray classifications were compared to classifications of a random sample of normal chest X‐rays by radiographer interpretation. Radiographic features were classified using WHO Integrated Management for Adult Illnesses (IMAI) guidelines. All radiographs taken at the screening tent were analysed by the Qure.ai qXR v2.0 software. Results 5% (648/13,490) of adults who underwent chest radiography were identified to have an abnormal chest X‐ray by the radiographer. 387 (59.7%) of the participants attended the X‐ray clinic, and another 387 randomly sampled normal X‐rays were available for comparison. Participants who were referred to the community clinic had a significantly higher HIV prevalence than those who had been identified to have a normal CXR by the field radiographer (90 [23.3%] vs. 43 [11.1%] p‐value < 0.001). The commonest radiographic finding was cardiomegaly (20.7%, 95% CI 18.0–23.7). One in five (81/387) chest X‐rays were misclassified by the radiographer. The overall mean Qure.ai qXR v2.0 score for all reviewed X‐rays was 0.23 (SD 0.20). There was a high concordance of cardiomegaly classification between the physician and the computer‐assisted software (109/118, 92.4%). Conclusion There is a high burden of cardiomegaly on a chest X‐ray at a community level, much of which is in patients with diabetes, heart disease and high blood pressure. Cardiomegaly on chest X‐ray may be a potential tool for screening for cardiovascular NCDs at the primary care level as well as in the community.

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‘If not TB, what could it be?’ Chest X-ray findings from the 2016 Kenya Tuberculosis Prevalence Survey

Cited by 27 publications

References 18 publications

Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis

Computer-aided X-ray screening for tuberculosis and HIV testing among adults with cough in Malawi (the PROSPECT study): A randomised trial and cost-effectiveness analysis

Accuracy of computer-aided chest X-ray screening in the Kenya National Tuberculosis Prevalence Survey

Pattern of abnormalities amongst chest X‐rays of adults undergoing computer‐assisted digital chest X‐ray screening for tuberculosis in Peri‐Urban Blantyre, Malawi: A cross‐sectional study

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