Clinical trial NCT05122624: A Clinical Risk Score for Early Management of TB in Uganda
Official title: PredicTB: Validating a Clinical Risk Score for Early Management of Tuberculosis in Ugandan Primary Health Clinics
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Tuberculosis, Pulmonary
Lead sponsor: Johns Hopkins Bloomberg School of Public Health
Sponsor class: OTHER
Collaborators: name: National Institute of Allergy and Infectious Diseases (NIAID)
First posted: 2021-11-17
Enrollment: 3332
Sex: ALL
Minimum age (years): 15
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Allocation: NON_RANDOMIZED
Intervention model: PARALLEL
Intervention model description: The study includes an intervention arm (four clinics) and a control arm (four clinics).
Primary purpose: DIAGNOSTIC

Brief summary: Although curative treatment exists, tuberculosis (TB) remains the leading cause of infectious mortality worldwide - often because people seek care for TB symptoms in highly resource-constrained clinics that cannot provide same-day diagnostic testing. The research team has developed an easy-to-use clinical risk score that, if implemented in these settings, might help clinicians identify patients at high risk for TB and thereby start treatment for those patients on the same day. This study will investigate the effectiveness and implementation of this score in four peri-urban clinics in Uganda, providing critical pragmatic data to inform (or halt) the design of a definitive large-scale cluster randomized trial.

Detailed description: An estimated 1.5 million people die of tuberculosis (TB) every year. Many of these are people who seek care in under-resourced clinics (for example, in rural areas or informal settlements) where same-day TB diagnosis is not available. These patients are often unable to return promptly to receive their results and start treatment, resulting in ongoing disease transmission and often death. If TB treatment could be started on the same day as these patients initially seek care, substantial mortality and transmission could be averted. The research team has developed and validated a clinical risk score ("PredicTB") for adult pulmonary TB that could aid in clinical decision-making. This risk score ranges from 1-10, can be calculated by hand in under a minute using readily available clinical data (e.g., age, sex, self-reported HIV status), and has sufficiently high accuracy to inform decisions about same-day empiric treatment initiation while confirmatory test results are pending. Same-day treatment initiation improves patient outcomes for other infectious diseases (for example, sexually transmitted diseases including HIV), and this novel clinical risk score holds similar promise for TB, the leading cause of infectious mortality worldwide. However, before conducting a large-scale cluster randomized trial to evaluate whether this score could improve patient-important outcomes, it is critical to first generate evidence that this score could be effective and be implemented in the most-resource-limited settings for which it is intended.

The research team proposes a type 2 hybrid effectiveness-implementation evaluation of the PredicTB clinical risk score in four peri-urban clinics in Uganda, with an additional four clinics serving as a comparison group. The Specific Aims are to evaluate the effectiveness of PredicTB on clinical outcomes including rapid treatment initiation, TB mortality, and loss to care (Aim 1); to evaluate the implementation of PredicTB in terms of reach, adoption, implementation, and maintenance (Aim 2); and the project the long-term impact and cost-effectiveness of PredicTB implementation (Aim 3). The primary outcome is the increase in the proportion of patients with microbiologically confirmed TB who start treatment within seven days of initial presentation. To accomplish these aims, the research team will adopt a highly pragmatic study design in which the research team train clinicians in the use of the PredicTB score and perform quarterly site visits but otherwise minimize contact between study staff and treating clinicians. This will enable the research team to evaluate whether implementation of PredicTB is likely to impact clinical decision-making and patient outcomes under actual field settings. If successful, this evaluation will provide critical data to justify (or halt) the conduct of a large-scale pragmatic clinical trial - not only will it generate preliminary evidence of effectiveness, but it will also inform appropriate implementation. Patients in highly resource-constrained settings are at the greatest risk of suffering the ill effects of TB disease, including long-term morbidity and death. This study represents an important first step toward improving clinical management for these marginalized patients and thus toward reaching global targets for ending the TB epidemic.

Eligibility criteria: Inclusion Criteria:

* All adult patients submitting sputum for a new diagnosis of pulmonary TB in the four study clinics and four comparison clinics between month -6 and month 18 will have their records abstracted by study staff.
* Starting in the 13th month after PredicTB implementation (i.e., after the 12-month post-implementation period has ended), study staff will position themselves in the four study clinics for purposes of recruiting and enrolling adult patients submitting sputum for a new diagnosis of pulmonary TB. No exclusions will be made except for age (as above), and we will seek to enroll all consecutive patients until our target sample size (25 participants per clinic, total n = 100) has been reached.

Exclusion Criteria:

* Age \< 15 years old

Primary outcomes:
measure: Difference in 7-day Treatment Initiation From Pre-implementation to Post-implementation
timeFrame: Up to 12 months post intervention
measure: Implementation: Percentage of Encountered Patients at Intervention Arm Who Initiated the Same-day Treatment Based on PredicTB Score as Indicated
timeFrame: Up to 12 months
Secondary outcomes:
measure: Incremental Cost-effectiveness of PredicTB
timeFrame: Months 0 - 12
measure: Difference in TB Mortality From Pre-implementation to Post-implementation
timeFrame: 12 Months
measure: Difference in Loss to Care From Pre-implementation To Post-implementation
timeFrame: 12 Months
measure: Difference in Percentage of Participants With Microbiologically Confirmed TB
timeFrame: Up to 12 months post-implementation
measure: Reach: Percentage of Patients Who Were Administered (or Evaluated) by PredicTB Score
timeFrame: Up to 12 months
measure: Adoption: Percentage of Providers Adopting PredicTB
timeFrame: Month 18
measure: Maintenance: Change in Effectiveness Over Time in the Post-implementation Phase at Intervention Arm
timeFrame: Up to 12 months
measure: Modeled Changes in 5-year Mortality With PredicTB
timeFrame: Month 12
Other outcomes:
Locations:
city: Kampala
country: Uganda
facility: Makerere University
Study officials:
affiliation: Johns Hopkins Bloomberg School of Public Health
name: David W Dowdy, MD/PHD
role: PRINCIPAL_INVESTIGATOR
References: