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Because TB control is still hampered by the limitations of diagnostic tools, diagnostic uncertainty is common. The decision to offer treatment is based on clinical decision-making. The therapeutic threshold, test threshold and test-treatment threshold can guide in making these decisions. This review summarizes the literature on methods to estimate the therapeutic threshold that have been applied for TB. Only five studies estimated the threshold for the diagnosis of TB. The therapeutic threshold can be estimated by prescriptive methods, based on calculations, and by descriptive methods, deriving the threshold from observing clinical practice. Test and test-treatment thresholds can be calculated using the therapeutic threshold and the characteristics of an available diagnostic test. Estimates of the therapeutic threshold for pulmonary TB from intuitive descriptive approaches (20%–50%) are higher than theoretical prescriptive calculations (2%–3%). In conclusion, estimates of the therapeutic threshold for pulmonary TB depend on the method used. Other methods exist within the field of decision-making that have yet to be implemented or adapted as tools to estimate the TB therapeutic threshold. Because clinical decision-making is a core element of TB management, it is necessary to find a new, clinician-friendly way to unbiasedly estimate context-specific, agreed upon therapeutic thresholds. [ABSTRACT FROM AUTHOR]

Simple Summary: We hypothesised that change in a magnetic resonance imaging (MRI) biomarker, the apparent diffusion coefficient (ADC) after 14 days of treatment could be a proxy for tumour regression grade (TRG) on pathology. Measurement of the imaging biomarker was standardised across centres. We restricted measurements to liver metastases from colorectal cancer and ensured a standardised chemotherapy approach. We identified and eliminated significant measurement error due to MRI scanner performance. We excluded studies that failed to conform to the imaging protocol or where images contained movement artefact. We ensured stability of the scanners by periodic quality control testing and used a standard, widely used data analysis technique to derive the ADC. Despite these measures, our results showed no significant correlation between ADC and TRG or between ADC and percentage of viable tumour, percentage necrosis, percentage fibrosis or a tumour proliferation index. This may reflect the complex cellular architecture of tumours after treatment. Background: Tumour apparent diffusion coefficient (ADC) from diffusion-weighted magnetic resonance imaging (MRI) is a putative pharmacodynamic/response biomarker but the relationship between drug-induced effects on the ADC and on the underlying pathology has not been adequately defined. Hypothesis: Changes in ADC during early chemotherapy reflect underlying histological markers of tumour response as measured by tumour regression grade (TRG). Methods: Twenty-six patients were enrolled in the study. Baseline, 14 days, and pre-surgery MRI were performed per study protocol. Surgical resection was performed in 23 of the enrolled patients; imaging-pathological correlation was obtained from 39 lesions from 21 patients. Results: There was no evidence of correlation between TRG and ADC changes at day 14 (study primary endpoint), and no significant correlation with other ADC metrics. In scans acquired one week prior to surgery, there was no significant correlation between ADC metrics and percentage of viable tumour, percentage necrosis, percentage fibrosis, or Ki67 index. Conclusions: Our hypothesis was not supported by the data. The lack of meaningful correlation between change in ADC and TRG is a robust finding which is not explained by variability or small sample size. Change in ADC is not a proxy for TRG in metastatic colorectal cancer. [ABSTRACT FROM AUTHOR]

This document is a correction notice for a study titled "Viraemic-time predicts mortality among people living with HIV on second-line antiretroviral treatment in Myanmar: A retrospective cohort study." The correction addresses errors in the Funding and Competing Interests statements. The correct statements indicate that the study was financially supported by MSF, and MSF also provided support for salaries and publication costs. The authors declare no competing interests, and there are no patents or marketed products associated with the research. The study was conducted by multiple authors affiliated with various institutions. [Extracted from the article]

Background: Digital polymerase chain reaction (dPCR) is an increasingly popular technology for detecting and quantifying target nucleic acids. Its advertised strength is high precision absolute quantification without needing reference curves. The standard data analytic approach follows a seemingly straightforward theoretical framework but ignores sources of variation in the data generating process. These stem from both technical and biological factors, where we distinguish features that are 1) hard-wired in the equipment, 2) user-dependent and 3) provided by manufacturers but may be adapted by the user. The impact of the corresponding variance components on the accuracy and precision of target concentration estimators presented in the literature is studied through simulation. Results: We reveal how system-specific technical factors influence accuracy as well as precision of concentration estimates. We find that a well-chosen sample dilution level and modifiable settings such as the fluorescence cut-off for target copy detection have a substantial impact on reliability and can be adapted to the sample analysed in ways that matter. User-dependent technical variation, including pipette inaccuracy and specific sources of sample heterogeneity, leads to a steep increase in uncertainty of estimated concentrations. Users can discover this through replicate experiments and derived variance estimation. Finally, the detection performance can be improved by optimizing the fluorescence intensity cut point as suboptimal thresholds reduce the accuracy of concentration estimates considerably. Conclusions: Like any other technology, dPCR is subject to variation induced by natural perturbations, systematic settings as well as user-dependent protocols. Corresponding uncertainty may be controlled with an adapted experimental design. Our findings point to modifiable key sources of uncertainty that form an important starting point for the development of guidelines on dPCR design and data analysis with correct precision bounds. Besides clever choices of sample dilution levels, experiment-specific tuning of machine settings can greatly improve results. Well-chosen data-driven fluorescence intensity thresholds in particular result in major improvements in target presence detection. We call on manufacturers to provide sufficiently detailed output data that allows users to maximize the potential of the method in their setting and obtain high precision and accuracy for their experiments. [ABSTRACT FROM AUTHOR]

The 2018-2020 Ebola virus disease (EVD) outbreak in the Democratic Republic of the Congo (DRC) was the largest since the disease's discovery in 1976. Rapid identification and isolation of EVD patients are crucial during triage. This study aimed to develop a clinical prediction score for EVD using clinical and epidemiological predictors. We conducted a retrospective cross-sectional study using surveillance data from EVD outbreak, collected during routine clinical care at the Ebola Transit Center (ETC) in Beni, DRC, from 2018 to 2020. The Spiegelhalter and Knill-Jones method was used for score development, including potential predictors with an adjusted likelihood ratio above 2 or below 0.50. Validation was performed using a dataset previously published in PLOSOne by Tshomba et al. Among 3725 patients screened, 3698 fulfilled the inclusion criteria, with 571 (15.4%) testing positive for EVD via RT-PCR Test. Seven predictive factors were identified: asthenia, sore throat, conjunctivitis, bleeding gums, hematemesis, contact with a sick person, and contact with a traditional healer. The prediction score achieved an Area under the receiver operating characteristic (AUROC) of 0.764, with 81.4% sensitivity and 53.6% specificity at a -1 cutoff. External validation demonstrated an AUROC of 0.766, with 80.8% sensitivity and 41.4% specificity at the -1 cutoff. Our study developed a screening tool to assess the risk of suspected patients developing EVD and being admitted to ETUs for RT-PCR testing and treatment. External validation results affirmed the model's reliability and generalizability in similar settings, suggesting its potential integration into clinical practice. Given the severity and urgency of EVD as well as the risk nosocomial EVD transmission, it is essential to continuously update these models with real-time data on symptoms, disease progression, patient outcomes and validated RDT during EVD outbreaks. This approach will enhance model accuracy, enabling more precise risk assessments and more effective outbreak management., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Yango et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Background: Ebola virus disease (EVD) outbreaks have emerged in Central and West Africa. EVD diagnosis relies principally on RT-PCR testing with GeneXpert®, which has logistical and cost restrictions at the peripheral level of the health system. Rapid diagnostic tests (RDTs) would offer a valuable alternative at the point-of-care to reduce the turn-around time, if they show good performance characteristics. We evaluated the performance of four EVD RDTs against the reference standard GeneXpert® on stored EVD positive and negative blood samples collected between 2018 and 2021 from outbreaks in eastern Democratic Republic of the Congo (DRC)., Methods: We conducted a prospective and observational study in the laboratory on QuickNavi-Ebola™, OraQuick® Ebola Rapid Antigen, Coris® EBOLA Ag K-SeT, and Standard® Q Ebola Zaïre Ag RDTs using left-over archived frozen EDTA whole blood samples. We randomly selected 450 positive and 450 negative samples from the EVD biorepositories in DRC, across a range of GeneXpert® cycle threshold values (Ct-values). RDT results were read by three persons and we considered an RDT result as "positive", when it was flagged as positive by at least two out of the three readers. We estimated the sensitivity and specificity through two independent generalized (logistic) linear mixed models (GLMM)., Findings: 476 (53%) of 900 samples had a positive GeneXpert Ebola result when retested. The QuickNavi-Ebola™ showed a sensitivity of 56.8% (95% CI 53.6-60.0) and a specificity of 97.5% (95% CI 96.2-98.4), the OraQuick® Ebola Rapid Antigen test displayed 61.6% (95% CI 57.0-65.9) sensitivity and 98.1% (95% CI 96.2-99.1) specificity, the Coris® EBOLA Ag K-SeT showed 25.0% (95% CI 22.3-27.9) sensitivity and 95.9% (95% CI 94.2-97.1) specificity, and the Standard® Q Ebola Zaïre Ag displayed 21.6% (95% CI 18.1-25.7) sensitivity and 99.1% (95% CI 97.4-99.7) specificity., Interpretation: None of the RDTs evaluated approached the "desired or acceptable levels" for sensitivity set out in the WHO target product profile, while all of the tests met the "desired level" for specificity. Nevertheless, the QuickNavi-Ebola™ and OraQuick® Ebola Rapid Antigen Test demonstrated the most favorable profiles, and may be used as frontline tests for triage of suspected-cases while waiting for RT-qPCR confirmatory testing., Funding: Institute of Tropical Medicine Antwerp/EDCTP PEAU-EBOV-RDC project., Competing Interests: Declaration of interests US CDC provided the Xpert® Ebola cartridges. FIND purchased OraQuick Ebola Rapid Antigen tests and donated to INRB through US CDC partnership. Institute of Tropical Medicine-Antwerp purchased Coris® Ag K-SeT and Standard® Q line Zaïre Ebola Rapid diagnostic tests with the financial support of the EDCTP PEAU- EBOV-RDC project under grant agreement RIA2018EF-2087, and through the FA5 DRC Program funded by the Directorate General for Development Cooperation and Humanitarian Aid (DGD) of the Belgian government. Hokkaido University provided QuickNavi Ebola rapid tests to INRB via Japanese International Cooperation Agency (JICA). Rodolphe Mérieux INRB-Goma Laboratory supported the study with laboratory supplies. DMB is a PhD fellow supported by the Belgian Directorate-general Development Cooperation and Humanitarian Aid. JB-P, ADW, FE-A, BKJ, FM-M, JDK, HK-M, EI-N, PM-K, PM-K, SM-M, MK, AT, PF, NMM, EMM, MAK-M, ET-T, PNF, SR, AL, AN-N, MEM, JMM, JJM-T, KKA, JvG, SA-M declare no competing interests., (Copyright © 2023. Published by Elsevier B.V.)

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., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 The Authors.)