Simultaneous alleviation of verification and reference standard biases in a community-based tuberculosis screening study using Bayesian latent class analysis.

BACKGROUND: Estimation of prevalence and diagnostic test accuracy in tuberculosis (TB) prevalence surveys suffer from reference standard and verification biases. The former is attributed to the imperfect reference test used to bacteriologically confirm TB disease. The latter occurs when only the participants screening positive for any TB-compatible symptom or chest X-ray abnormality are selected for bacteriological testing (verification). Bayesian latent class analysis (LCA) alleviates the reference standard bias but suffers verification bias in TB prevalence surveys. This work aims to identify best-practice approaches to simultaneously alleviate the reference standard and verification biases in the estimates of pulmonary TB prevalence and diagnostic test performance in TB prevalence surveys. METHODS: We performed a secondary analysis of 9869 participants aged ≥15 years from a community-based multimorbidity screening study in a rural district of KwaZulu-Natal, South Africa (Vukuzazi study). Participants were eligible for bacteriological testing using Xpert Ultra and culture if they reported any cardinal TB symptom or had an abnormal chest X-ray finding. We conducted Bayesian LCA in five ways to handle the unverified individuals: (i) complete-case analysis, (ii) analysis assuming the unverified individuals would be negative if bacteriologically tested, (iii) analysis of multiply-imputed datasets with imputation of the missing bacteriological test results for the unverified individuals using multivariate imputation via chained equations (MICE), and simultaneous imputation of the missing bacteriological test results in the analysis model assuming the missing bacteriological test results were (iv) missing at random (MAR), and (v) missing not at random (MNAR). We compared the results of (i)-(iii) to the analysis based on a composite reference standard (CRS) of Xpert Ultra and culture. Through simulation with an overall true prevalence of 2.0%, we evaluated the ability of the models to alleviate both biases simultaneously. RESULTS: Based on simulation, Bayesian LCA with simultaneous imputation of the missing bacteriological test results under the assumption that the missing data are MAR and MNAR alleviate the reference standard and verification biases. CRS-based analysis and Bayesian LCA assuming the unverified are negative for TB alleviate the biases only when the true overall prevalence is <3.0%. Complete-case analysis produced biased estimates. In the Vukuzazi study, Bayesian LCA with simultaneous imputation of the missing bacteriological test results under the MAR and MNAR assumptions produced overall PTB prevalence of 0.9% (95% Credible Interval (CrI): 0.6-1.9) and 0.7% (95% CrI: 0.5-1.1) respectively alongside realistic estimates of overall diagnostic test sensitivity and specificity with substantially overlapping 95% CrI. The CRS-based analysis and Bayesian LCA assuming the unverified were negative for TB produced 0.7% (95% CrI: 0.5-0.9) and 0.7% (95% CrI: 0.5-1.2) overall PTB prevalence respectively with realistic estimates of overall diagnostic test sensitivity and specificity. Unlike CRS-based analysis, Bayesian LCA of multiply-imputed data using MICE mitigates both biases. CONCLUSION: The findings demonstrate the efficacy of these advanced techniques in alleviating the reference standard and verification biases, enhancing the robustness of community-based screening programs. Imputing missing values as negative for bacteriological tests is plausible under realistic assumptions.

Computer-aided detection thresholds for digital chest radiography interpretation in tuberculosis diagnostic algorithms.

Objectives: Use of computer-aided detection (CAD) software is recommended to improve tuberculosis screening and triage, but threshold determination is challenging if reference testing has not been performed in all individuals. We aimed to determine such thresholds through secondary analysis of the 2019 Lesotho national tuberculosis prevalence survey. Methods: Symptom screening and chest radiographs were performed in participants aged ≥15 years; those symptomatic or with abnormal chest radiographs provided samples for Xpert MTB/RIF and culture testing. Chest radiographs were processed using CAD4TB version 7. We used six methodological approaches to deal with participants who did not have bacteriological test results to estimate pulmonary tuberculosis prevalence and assess diagnostic accuracy. Results: Among 17 070 participants, 5214 (31%) had their tuberculosis status determined; 142 had tuberculosis. Prevalence estimates varied between methodological approaches (0.83-2.72%). Using multiple imputation to estimate tuberculosis status for those eligible but not tested, and assuming those not eligible for testing were negative, a CAD4TBv7 threshold of 13 had a sensitivity of 89.7% (95% CI 84.6-94.8) and a specificity of 74.2% (73.6-74.9), close to World Health Organization (WHO) target product profile criteria. Assuming all those not tested were negative produced similar results. Conclusions: This is the first study to evaluate CAD4TB in a community screening context employing a range of approaches to account for unknown tuberculosis status. The assumption that those not tested are negative - regardless of testing eligibility status - was robust. As threshold determination must be context specific, our analytically straightforward approach should be adopted to leverage prevalence surveys for CAD threshold determination in other settings with a comparable proportion of eligible but not tested participants.

Piloting a new method to estimate action thresholds in medicine through intuitive weighing.

OBJECTIVES: In clinical decision-making, physicians take actions such as prescribing treatment only when the probability of disease is sufficiently high. The lowest probability at which the action will be considered, is the action threshold. Such thresholds play an important role whenever decisions have to be taken under uncertainty. However, while several methods to estimate action thresholds exist, few methods give satisfactory results or have been adopted in clinical practice. We piloted the adapted nominal group technique (aNGT), a new prescriptive method based on a formal consensus technique adapted for use in clinical decision-making. DESIGN, SETTING AND PARTICIPANTS: We applied this method in groups of postgraduate students using three scenarios: treat for rifampicin-resistant tuberculosis (RR-TB), switch to second-line HIV treatment and isolate for SARS-CoV-2 infection. INTERVENTIONS: The participants first summarise all harms of wrongly taking action when none is required and wrongly not taking action when it would have been useful. Then they rate the statements on these harms, discuss their importance in the decision-making process, and finally weigh the statements against each other. MAIN OUTCOME MEASURES: The resulting consensus threshold is estimated as the relative weights of the harms of the false positives divided by the total harm, and averaged out over participants. In some applications, the thresholds are compared with an existing method based on clinical vignettes. RESULTS: The resulting action thresholds were just over 50% for RR-TB treatment, between 20% and 50% for switching HIV treatment and 43% for COVID-19 isolation. These results were considered acceptable to all participants. Between sessions variation was low for RR-TB and moderate for HIV. Threshold estimates were moderately lower with the method based on clinical vignettes. CONCLUSIONS: The aNGT gives sensible results in our pilot and has the potential to estimate action thresholds, in an efficient manner, while involving all relevant stakeholders. Further research is needed to study the value of the method in clinical decision-making and its ability to generate acceptable thresholds that stakeholders can agree on.

Evaluation of tuberculosis diagnostic test accuracy using Bayesian latent class analysis in the presence of conditional dependence between the diagnostic tests used in a community-based tuberculosis screening study.

Diagnostic accuracy studies in pulmonary tuberculosis (PTB) are complicated by the lack of a perfect reference standard. This limitation can be handled using latent class analysis (LCA), assuming independence between diagnostic test results conditional on the true unobserved PTB status. Test results could remain dependent, however, e.g. with diagnostic tests based on a similar biological basis. If ignored, this gives misleading inferences. Our secondary analysis of data collected during the first year (May 2018 -May 2019) of a community-based multi-morbidity screening program conducted in the rural uMkhanyakude district of KwaZulu Natal, South Africa, used Bayesian LCA. Residents of the catchment area, aged ≥15 years and eligible for microbiological testing, were analyzed. Probit regression methods for dependent binary data sequentially regressed each binary test outcome on other observed test results, measured covariates and the true unobserved PTB status. Unknown model parameters were assigned Gaussian priors to evaluate overall PTB prevalence and diagnostic accuracy of 6 tests used to screen for PTB: any TB symptom, radiologist conclusion, Computer Aided Detection for TB version 5 (CAD4TBv5≥53), CAD4TBv6≥53, Xpert Ultra (excluding trace) and culture. Before the application of our proposed model, we evaluated its performance using a previously published childhood pulmonary TB (CPTB) dataset. Standard LCA assuming conditional independence yielded an unrealistic prevalence estimate of 18.6% which was not resolved by accounting for conditional dependence among the true PTB cases only. Allowing, also, for conditional dependence among the true non-PTB cases produced a 1.1% plausible prevalence. After incorporating age, sex, and HIV status in the analysis, we obtained 0.9% (95% CrI: 0.6, 1.3) overall prevalence. Males had higher PTB prevalence compared to females (1.2% vs. 0.8%). Similarly, HIV+ had a higher PTB prevalence compared to HIV- (1.3% vs. 0.8%). The overall sensitivity for Xpert Ultra (excluding trace) and culture were 62.2% (95% CrI: 48.7, 74.4) and 75.9% (95% CrI: 61.9, 89.2), respectively. Any chest X-ray abnormality, CAD4TBv5≥53 and CAD4TBv6≥53 had similar overall sensitivity. Up to 73.3% (95% CrI: 61.4, 83.4) of all true PTB cases did not report TB symptoms. Our flexible modelling approach yields plausible, easy-to-interpret estimates of sensitivity, specificity and PTB prevalence under more realistic assumptions. Failure to fully account for diagnostic test dependence can yield misleading inferences.

The Feasibility and Acceptability of an mHealth Conversational Agent Designed to Support HIV Self-testing in South Africa: Cross-sectional Study.

BACKGROUND: HIV testing rates in sub-Saharan Africa remain below the targeted threshold, and primary care facilities struggle to provide adequate services. Innovative approaches that leverage digital technologies could improve HIV testing and access to treatment. OBJECTIVE: This study aimed to examine the feasibility and acceptability of Nolwazi_bot. It is an isiZulu-speaking conversational agent designed to support HIV self-testing (HIVST) in KwaZulu-Natal, South Africa. METHODS: Nolwazi_bot was designed with 4 different personalities that users could choose when selecting a counselor for their HIVST session. We recruited a convenience sample of 120 consenting adults and invited them to undertake an HIV self-test facilitated by the Nolwazi_bot. After testing, participants completed an interviewer-led posttest structured survey to assess their experience with the chatbot-supported HIVST. RESULTS: Participants (N=120) ranged in age from 18 to 47 years, with half of them being men (61/120, 50.8%). Of the 120 participants, 111 (92.5%) had tested with a human counselor more than once. Of the 120 participants, 45 (37.5%) chose to be counseled by the female Nolwazi_bot personality aged between 18 and 25 years. Approximately one-fifth (21/120, 17.5%) of the participants who underwent an HIV self-test guided by the chatbot tested positive. Most participants (95/120, 79.2%) indicated that their HIV testing experience with a chatbot was much better than that with a human counselor. Many participants (93/120, 77.5%) reported that they felt as if they were talking to a real person, stating that the response tone and word choice of Nolwazi_bot reminded them of how they speak in daily conversations. CONCLUSIONS: The study provides insights into the potential of digital technology interventions to support HIVST in low-income and middle-income countries. Although we wait to see the full benefits of mobile health, technological interventions including conversational agents or chatbots provide us with an excellent opportunity to improve HIVST by addressing the barriers associated with clinic-based HIV testing.

Implications of covariate induced test dependence on the diagnostic accuracy of latent class analysis in pulmonary tuberculosis.

Background: In application studies of latent class analysis (LCA) evaluating imperfect diagnostic tests, residual dependence among the diagnostic tests still remain even after conditioning on the true disease status due to measured variables known to affect prevalence and/or alter diagnostic test accuracy. Presence of severe comorbidities such as HIV in pulmonary tuberculosis (PTB) diagnosis alter the prevalence of PTB and affect the diagnostic performance of the available imperfect tests in use. This violates two key assumptions of LCA: (1) that the diagnostic tests are independent conditional on the true disease status (2) that the sensitivity and specificity remain constant across subpopulations. This leads to incorrect inferences. Methods: Through simulation we examined implications of likely model violations on estimation of prevalence, sensitivity and specificity among passive case-finding presumptive PTB patients with or without HIV. Jointly conditioning on PTB and HIV, we generated independent results for five diagnostic tests and analyzed using Bayesian LCA with Probit regression, separately for sets of five and three diagnostic tests using four working models allowing: (1) constant PTB prevalence and diagnostic accuracy (2) varying PTB prevalence but constant diagnostic accuracy (3) constant PTB prevalence but varying diagnostic accuracy (4) varying PTB prevalence and diagnostic accuracy across HIV subpopulations. Vague Gaussian priors with mean 1 and unknown variance were assigned to the model parameters with unknown variance assigned Inverse Gamma prior. Results: Models accounting for heterogeneity in diagnostic accuracy produced consistent estimates while the model ignoring it produces biased estimates. The model ignoring heterogeneity in PTB prevalence only is less problematic. With five diagnostic tests, the model assuming homogenous population is robust to violation of the assumptions. Conclusion: Well-chosen covariate-specific adaptations of the model can avoid bias implied by recognized heterogeneity in PTB patient populations generating otherwise dependent test results in LCA.

Feasibility of implementing the advanced HIV disease care package as part of community-based HIV/TB activities: a mixed-methods study protocol.

INTRODUCTION: Although the advanced HIV disease (AHD) care package reduces morbidity and mortality in people with AHD (defined in people living with HIV as WHO stage 3 or 4, CD4 count <200 cells/µL or age <5 years), it is barely implemented in many countries. A novel point-of-care CD4 test rapidly identifies AHD. We evaluate the feasibility of implementing the AHD care package as part of community-based HIV/tuberculosis services. METHODS AND ANALYSIS: This two-phased study is guided by the Medical Research Council framework for evaluation of complex interventions. Stage 1 is a stakeholder consultation to define tools and indicators to assess feasibility of the AHD care package. Stage 2 is the implementation of the AHD care package during a facility-based tuberculosis diagnostic accuracy study in high-burden HIV/tuberculosis settings. Consenting adults with tuberculosis symptoms in two sites in Lesotho and South Africa are eligible for inclusion. HIV-positive participants are included in the feasibility study and are offered a CD4 test, a tuberculosis-lipoarabinomannan assay and those with CD4 count of ≤200 cells/µL a cryptococcal antigen lateral flow assay. Participants are referred for clinical management following national guidelines. The evaluation includes group discussions, participant observation (qualitative strand) and a semistructured questionnaire to assess acceptability among implementers. The quantitative strand also evaluates process compliance (process rating and process cascade) and early outcomes (vital and treatment status after twelve weeks). Thematic content analysis, descriptive statistics and data triangulation will be performed. ETHICS AND DISSEMINATION: The National Health Research and Ethics Committee, Lesotho, the Human Sciences Research Council Research Ethics Committee and Provincial Department of Health, South Africa and the Ethikkommission Nordwest- und Zentralschweiz, Switzerland, approved the protocol. Dissemination will happen locally and internationally at scientific conferences and in peer-reviewed journals. TRIAL REGISTRATION NUMBER: NCT04666311.

Randomized Phase IIA Trial of Gemcitabine Compared With Bleomycin Plus Vincristine for Treatment of Kaposi's Sarcoma in Patients on Combination Antiretroviral Therapy in Western Kenya.

PURPOSE: Kaposi's sarcoma (KS) is a spindle cell tumor resulting from growth dysregulation in the setting of infection with human herpes virus-8 (also called KS herpes virus). Advanced KS is characterized by poor responses to antiretroviral therapy and some of the chemotherapy readily accessible to patients in low-resource areas. Gemcitabine induced partial and complete regression of AIDS-associated KS (AIDS-KS) in 11 of 24 patients in a pilot study. The current study compares the antimetabolite gemcitabine with the standard care bleomycin and vincristine (BV) in the treatment of chemotherapy-naïve patients with AIDS-KS in a resource-limited setting. PATIENTS AND METHODS: Patients with persistent or progressive KS despite treatment with combined antiretroviral therapy were randomly assigned to receive gemcitabine 1,000 mg/m2 or bleomycin 15 IU/ m2 and vincristine 1.4 mg/m2 given twice weekly. The main end point was objective response by bidirectional measurement, adverse events, and quality of life after three cycles of chemotherapy. RESULTS: Of 70 participants enrolled, 36 received gemcitabine and 34 received BV. Complete response was achieved in 12 patients (33.3%) in the gemcitabine arm and six (17.6%) in the BV arm ( P = .175). The partial response rate was 52.8% (n = 19) in the gemcitabine arm and 58.8% (n = 20) in the BV arm. Both study arms reported similar neurologic and hematologic adverse events; there was statistically significant baseline to post-treatment improvement in health-related quality-of-life scores. CONCLUSION: The results of this randomized, phase IIA trial demonstrate gemcitabine activity in chemotherapy-naïve patients with AIDS-KS, on the basis of response rates, adverse events, and health-related quality-of-life scores.