Accuracy and consequences of usingtrial-of-antibioticsfor TB diagnosis (ACT-TB study): protocol for a randomised controlled clinical trial

Abstract

IntroductionOver 40% of global tuberculosis case notifications are diagnosed clinically without mycobacteriological confirmation. Standard diagnostic algorithms include ‘trial-of-antibiotics’—empirical antibiotic treatment given to mycobacteriology-negative individuals to treat infectious causes of symptoms other than tuberculosis, as a ‘rule-out’ diagnostic test for tuberculosis. Potentially 26.5 million such antibiotic courses/year are prescribed globally for the 5.3 million/year mycobacteriology-negative patients, making trial-of-antibiotics the most common tuberculosis diagnostic, and a global-scale risk for antimicrobial resistance (AMR). Our systematic review found no randomised controlled trial (RCT) to support use of trial-of-antibiotic. The RCT aims to determine the diagnostic and clinical value and AMR consequences of trial-of-antibiotics.Methods and analysisA three-arm, open-label, RCT randomising (1:1:1) Malawian adults (≥18 years) seeking primary care for cough into: (a) azithromycin 500 mg one time per day for 3 days or (b) amoxicillin 1 g three times per day for 5 days or (c) standard-of-care (no immediate antibiotic). We will perform mycobacteriology tests (microscopy, Xpert MTB/RIF (Mycobacterium tuberculosis/rifampicin) andMycobacterium tuberculosisculture) at baseline. We will use audiocomputer-assisted self-interview to assess clinical improvement at day 8. First primary outcome will be proportion of patients reporting day 8 improvement out of those with negative mycobacteriology (specificity). Second primary outcome will be day 29 incidence of a composite endpoint of either death or hospitalisation or missed tuberculosis diagnosis. To determine AMR impact we compare proportion of resistant nasopharyngealStreptococcus pneumoniaeisolates on day 29. 400 mycobacteriology-negative participants/arm will be required to detect a ≥10% absolute difference in diagnostic specificity with 80% power. We will estimate measures of effect by comparing outcomes in antibiotic arms (combined and individually) to standard-of-care.Ethics and disseminationThe study has been reviewed and approved by Malawi College of Medicine Research and Ethics Committee, London School of Hygiene & Tropical Medicine (LSHTM) Research Ethics Committee and Regional Committee for Health and Research Ethics – Norway, and Malawi Pharmacy, Medicines and Poisons Board. We will present abstracts at relevant conferences, and prepare a manuscript for publication in a peer-reviewed journal.Trial registration numberThe clinical trial is registered with ClinicalTrials.gov,NCT03545373

Trial-of-antibiotics to assist tuberculosis diagnosis in symptomatic adults in Malawi (ACT-TB study): a randomised controlled trial

“…We conducted this three-arm, individually randomised, open-label, controlled trial among adults who presented with cough for at least 14 days at two primary care centres in Blantyre, Malawi. The study design has been described in detail elsewhere 17 and the protocol and statistical analysis plan are available in the appendix (pp 5, 84) . The study was reviewed and approved by the Kamuzu University of Health Sciences Research and Ethics Committee, London School of Hygiene & Tropical Medicine Research Ethics Committee, Regional Committee for Health and Research Ethics–Norway, and Malawi Pharmacy, Medicines, and Poisons Board ( appendix p 106 ).…”

“…Clinical and laboratory procedures at days 8 and 29 are described in the published protocol paper. 17 …”

“… 14 , 15 , 16 We aimed to conduct a randomised controlled trial (the accuracy and consequences of using trial-of-antibiotics for tuberculosis diagnosis [ACT-TB]) to investigate the effect of a trial-of-antibiotic intervention on diagnostic, clinical, and antimicrobial resistance outcomes in Malawi. 17 …”

TSSG-CNN: A Tuberculosis Semantic Segmentation-Guided Model for Detecting and Diagnosis Using the Adaptive Convolutional Neural Network

“…This work is motivated by the need to improve TB diagnosis and screening, particularly in impoverished areas where access to trained medical personnel is limited. Traditional methods of TB detection that solely depend on the laborious, subjective manual analysis of chest X-rays may lead to delayed therapy initiation and inaccurate diagnosis [ 11 ]. Moreover, the majority of automatic TB detection systems now focus solely on classification algorithms, neglecting the importance of accurately locating relevant regions within chest X-rays.…”