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AI could revolutionize TB care by predicting who needs shorter treatment

NCT ID NCT07611695

Knowledge-focused Sponsor: Huashan Hospital Source: ClinicalTrials.gov ↗

What the study statuses mean

This study's is highlighted.

Recruitment status, easiest to join first

Recruiting now
This trial is taking on new participants right now.
Not yet recruiting This study
Registered, but not yet taking participants.
By invitation only
Not open to general applications. Only people the study team invites can take part.
Paused
Paused for now. It may or may not start again.
Ongoing
Running, but no longer taking on new participants.
Completed
The trial has finished. Results may not be published yet.
Stopped early
Stopped early, before it reached the end. That can be for many reasons, including safety.
Cancelled
Cancelled before anyone took part.

Expanded access (not trials)

Expanded access
Not a trial. This treatment can be requested outside a study, case by case, for people who qualify.
Expanded access (paused)
Not a trial. The treatment can normally be requested outside a study, but is unavailable right now.
Expanded access (ended)
Not a trial. The treatment could once be requested outside a study, but no longer can.
Approved
The treatment has been approved, so it is available normally rather than through this programme.

When the status isn't known

Details not published
The full record has not been published yet, so there is little to show here.
Status unknown
This status has not been confirmed recently, so it may be out of date.

First seen Jun 25, 2026 · Last updated Jun 27, 2026 · Updated 1 time

Summary

This study will use artificial intelligence to analyze data from over 31,000 tuberculosis patients. The goal is to create a system that helps doctors decide which patients can be cured with a short treatment course and which need longer therapy. The AI will be tested to see if it can improve cure rates and personalize care for each patient.

What this could mean

Our plain-language read of the trial. This is informational only, not medical advice or a prediction.

What this could lead to
If successful, this AI system could help doctors quickly identify which TB patients need shorter or longer treatment, leading to more personalized and effective care.
What could go wrong
This is an observational study, not a treatment trial, so it won't directly test a new drug or cure. The AI model may not work as well in real-world settings or for all patient groups.

This is an AI summary of the original study and may miss details. Read our disclaimer.

Study facts

What this study's own registry entry says, in plain language.

Participants

About 31,600 people

The number the study aims to enrol. It can still change while the study runs.

Expected to start

Jun 2026

An estimate. Start dates often move.

Expected to finish

Jun 2028

An estimate. End dates often move.

Lead sponsor

Other sponsor

The registry's catch-all category, for sponsors it does not file as a company, a government agency, or a research network.

Who can take part

This study's own entry requirements. Only the study team can say for certain whether you qualify.

Who is studied

Pulmonary tuberculosis (TB) patients diagnosed and treated (or will treat) in several TB clinical centers from China

Ages

Children (under 18), adults (18 to 64) and older adults (65 and over)

Sex

Anyone

Healthy volunteers

Not accepted

This study is not open to healthy volunteers. The entry requirements below say who it is open to.

Show the full entry requirements

Copied word for word from the study's registry entry, so the wording is the study team's rather than ours.

Inclusion Criteria for Model Development Cohort: * Patient with clinically diagnosed or bacteriologically confirmed pulmonary tuberculosis (TB) who received TB treatment; * Initiation of TB treatment on or after January 1, 2021; * Complete key diagnosis and treatment data available in the electronic medical record system. Inclusion Criteria for External Validation Cohort: * Patient with clinically diagnosed or bacteriologically confirmed pulmonary tuberculosis (TB) who is planning to start TB treatment; * Voluntary participation with signed informed consent form (for adults ≥18 years); parental / guardian consent and co-signed informed consent form are required for minors aged ≤ 18 years. Exclusion Criteria: * Co-morbidity confounding: the presence of other active, life-threatening disease (e.g. late-stage malignancy, non-HIV severe immunodeficiency) for which the expected survival or priority of treatment may substantially interfere with the attribution of TB treatment outcomes; * Extremely poor treatment adherence: documented evidence indicating that the patient either never initiated treatment or was permanently lost to follow-up within the early treatment period (\<2 weeks), precluding the collection of any valid outcome data.

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Conditions

The condition(s) this trial relates to.

active tuberculosis pulmonary tuberculosis tuberculosis

As listed by the trial registrant

The condition terms exactly as the trial's registrant entered them.

Pulmonary tuberculosis Tuberculosis (TB) Tuberculosis active

How to take part

Only the study team decides who joins. These are the ways to reach them.

  1. The places running it

    2 sites. The list below names each one and where it is.

  2. The official record

    ClinicalTrials.gov lists the study team's own contact details, including names and phone numbers. We don't republish those.

    Open the record ↗

  3. A doctor treating you

    A doctor who knows your case can contact a study site on your behalf, and can tell you whether this study is worth pursuing at all.

Contacts and locations

Locations

  • Huashan Hospital Affiliated to Fudan University

    Shanghai, 210000, China

  • Hunan Chest Hospital

    Changsha, Hunan, China

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