Evidence map›Paper›PMID 35932062›Full record

ArticleTrials2022

Tuberculosis (TB) Aftermath: study protocol for a hybrid type I effectiveness-implementation non-inferiority randomized trial in India comparing two active case finding (ACF) strategies among individuals treated for TB and their household contacts.

Samyra R Cox, Abhay Kadam, Sachin Atre, Akshay N Gupte, Hojoon Sohn, Nikhil Gupte, Trupti Sawant, Vishal Mhadeshwar, Ryan Thompson, Emily Kendall and 9 more

Erratum issued Registry-linked trialAbstract readClinical Trial Protocol
In one paragraph

Article in Trials, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. It is linked to trial NCT04333485 (Tuberculosis), which is not on this map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT04333485 nacompletednot on this map

Tuberculosis (TB) Aftermath: a Hybrid Type I Effectiveness-implementation Non-inferiority Randomized Trial in India Comparing Two Active Case Finding (ACF) Strategies Among Individuals Treated for TB and Their Household Contacts

TypeinterventionalSponsorJohns Hopkins UniversityRan2021 to 2025Enrolled3,094ConditionsTuberculosis (TB)ArmsHome-based Active Case Finding (HACF), Telephonic Active Case Finding (TACF)
3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

  1. Post-tuberculosis lung disease in treated extra-pulmonary tuberculosis.American journal of respiratory and critical care medicine · 2026
    Article
  2. A Point-of-Care Prediction Tool for Recurrent Tuberculosis.Clinical infectious diseases : an official publication of the Infectious Diseases Society of America · 2026
    Article
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

19 authors.

Samyra R CoxJohns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA. scox26@jh.edu.ORCID http://orcid.org/0000-0001-9953-1693
Abhay KadamJohns Hopkins India, G-4 & G-5, PHOENIX Building, OPP. to Residency Club, Pune, Maharashtra, 411001, India.
Sachin AtreDr. D.Y. Patil Medical College, Hospital and Research Centre, Dr. D.Y. Patil Vidyapeeth, Sant Tukaram Nagar, Pimpri Colony, Pimpri-Chinchwad, Maharashtra, 411018, India.
Akshay N GupteJohns Hopkins School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA.
Hojoon SohnJohns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA.
Nikhil GupteJohns Hopkins School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA.
Trupti SawantDr. D.Y. Patil Medical College, Hospital and Research Centre, Dr. D.Y. Patil Vidyapeeth, Sant Tukaram Nagar, Pimpri Colony, Pimpri-Chinchwad, Maharashtra, 411018, India.
Vishal MhadeshwarJohns Hopkins India, G-4 & G-5, PHOENIX Building, OPP. to Residency Club, Pune, Maharashtra, 411001, India.
Ryan ThompsonJohns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA.
Emily KendallJohns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA.
Christopher HoffmannJohns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA.
Nishi SuryavanshiJohns Hopkins School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA.
Deanna KerriganJohns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA.
Srikanth TripathyDr. D.Y. Patil Medical College, Hospital and Research Centre, Dr. D.Y. Patil Vidyapeeth, Sant Tukaram Nagar, Pimpri Colony, Pimpri-Chinchwad, Maharashtra, 411018, India.
Arjunlal KakraniDr. D.Y. Patil Medical College, Hospital and Research Centre, Dr. D.Y. Patil Vidyapeeth, Sant Tukaram Nagar, Pimpri Colony, Pimpri-Chinchwad, Maharashtra, 411018, India.
Madhusudan S BarthwalDr. D.Y. Patil Medical College, Hospital and Research Centre, Dr. D.Y. Patil Vidyapeeth, Sant Tukaram Nagar, Pimpri Colony, Pimpri-Chinchwad, Maharashtra, 411018, India.
Vidya Mave *Johns Hopkins School of Medicine, 600 N Wolfe St, Baltimore, MD, 21287, USA.
Jonathan E Golub *Johns Hopkins Bloomberg School of Public Health, 615 N Wolfe St, Baltimore, MD, 21205, USA.
TB Aftermath study team

Funding

TB AftermathR01AI143748 · NIAID · JOHNS HOPKINS UNIVERSITY · PI GOLUB, JONATHAN E., MAVE, VIDYA · 2020 to 2025
$3.1M
NIAID NIH HHS R01 AI143748NIH HHS R01AI143748
6 · The paper itself

Abstract

backgroundApproximately 7% of all reported tuberculosis (TB) cases each year are recurrent, occurring among people who have had TB in the recent or distant past. TB recurrence is particularly common in India, which has the largest TB burden worldwide. Although patients recently treated for TB are at high risk of developing TB again, evidence around effective active case finding (ACF) strategies in this population is scarce. We will conduct a hybrid type I effectiveness-implementation non-inferiority randomized trial to compare the effectiveness, cost-effectiveness, and feasibility of two ACF strategies among individuals who have completed TB treatment and their household contacts (HHCs).

methodsWe will enroll 1076 adults (≥ 18 years) who have completed TB treatment at a public TB unit (TU) in Pune, India, along with their HHCs (averaging two per patient, n = 2152). Participants will undergo symptom-based ACF by existing healthcare workers (HCWs) at 6-month intervals and will be randomized to either home-based ACF (HACF) or telephonic ACF (TACF). Symptomatic participants will undergo microbiologic testing through the program. Asymptomatic HHCs will be referred for TB preventive treatment (TPT) per national guidelines. The primary outcome is rate per 100 person-years of people diagnosed with new or recurrent TB by study arm, within 12 months following treatment completion. The secondary outcome is proportion of HHCs < 6 years, by study arm, initiated on TPT after ruling out TB disease. Study staff will collect socio-demographic and clinical data to identify risk factors for TB recurrence and will measure post-TB lung impairment. In both arms, an 18-month "mop-up" visit will be conducted to ascertain outcomes. We will use the RE-AIM framework to characterize implementation processes and explore acceptability through in-depth interviews with index patients, HHCs and HCWs (n = 100). Cost-effectiveness will be assessed by calculating the incremental cost per TB case detected within 12 months and projected for disability-adjusted life years averted based on modeled estimates of morbidity, mortality, and time with infectious TB. DISCUSSION: This novel trial will guide India's scale-up of post-treatment ACF and provide an evidence base for designing strategies to detect recurrent and new TB in other high burden settings.

trial registrationNCT04333485 , registered April 3, 2020. CTRI/2020/05/025059 [Clinical Trials Registry of India], registered May 6 2020.

Indexed as

Mass ScreeningTuberculosisAdultCost-Benefit AnalysisEquivalence Trials as TopicHealth PersonnelHumansIndiaRandomized Controlled Trials as TopicActive case findingHybrid effectiveness-implementation trialIndiaRecurrenceTuberculosis

Identifiers

PMID35932062
PMCPMC9354295

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.