A Clinical Risk Score for Early Management of TB in Uganda

Not Applicable

Completed

Conditions: Tuberculosis, Pulmonary

Interventions: Other: PredicTB score

Registration Number: NCT05122624

Lead Sponsor: Johns Hopkins Bloomberg School of Public Health

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.

Recruitment & Eligibility

Status: COMPLETED

Sex: All

Target Recruitment: 3332

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

Study & Design

Study Type: INTERVENTIONAL

Study Design: PARALLEL

Arm && Interventions

Group	Intervention	Description
Score intervention arm	PredicTB score	The PredicTB score will be implemented in this arm.

Primary Outcome Measures

Name	Time	Method
Implementation: Percentage of Encountered Patients at Intervention Arm Who Initiated the Same-day Treatment Based on PredicTB Score as Indicated	Up to 12 months	Percentage of patients who initiated same-day treatment divided by the number of patients who had a higher PredicTB score than the clinic-specific score of treatment threshold in the post-implementation period in intervention arm
Difference in 7-day Treatment Initiation From Pre-implementation to Post-implementation	Up to 12 months post intervention	The percentage of participants with microbiologically confirmed TB who initiated treatment within 7 days during post-implementation 'minus' The percentage of participants with microbiologically confirmed TB who initiated treatment within 7 days during pre-implementation

Secondary Outcome Measures

Name	Time	Method
Difference in TB Mortality From Pre-implementation to Post-implementation	12 Months	The percentage of participants with microbiologically confirmed TB who died of any cause in the post-implementation "minus" The percentage of participants with microbiologically confirmed TB who died of any cause in the pre-implementation
Incremental Cost-effectiveness of PredicTB	Months 0 - 12	(cost of implementing PredicTB - cost of standard of care)/(projected disability-adjusted life years (DALYs) in standard of care - projected DALYs with PredicTB)
Difference in Loss to Care From Pre-implementation To Post-implementation	12 Months	The percentage of participants with microbiologically confirmed TB who were lost to follow-up in the post-implementation "minus" The percentage of participants with microbiologically confirmed TB who were lost to follow-up in the pre-implementation
Difference in Percentage of Participants With Microbiologically Confirmed TB	Up to 12 months post-implementation	Difference in the percentage of participants with microbiologically confirmed TB who initiated treatment within 7 days from post-implementation to pre-implementation at intervention arm "minus" Difference in the percentage of participants with microbiologically confirmed TB who initiated treatment within 7 days from post-implementation to pre-implementation at comparison arm
Maintenance: Change in Effectiveness Over Time in the Post-implementation Phase at Intervention Arm	Up to 12 months	Percentage of participants with microbiologically confirmed TB who initiated treatment within seven days in the post-implementation phase at intervention arm "minus" Percentage of participants with microbiologically confirmed TB who initiated treatment within seven days in the post-implementation phase at intervention arm
Adoption: Percentage of Providers Adopting PredicTB	Month 18	Percentage of providers using PredicTB in over 50% of encounters in which sputum is submitted for pulmonary TB diagnosis among those seeing \>5 patients who submit sputum for diagnosis of pulmonary TB
Modeled Changes in 5-year Mortality With PredicTB	Month 12	Modeled hypothetical, expected changes in mortality at year 5, comparing simulations in which PredicTB is implemented to those in which PredicTB is not implemented, using a Markov state-transition model
Reach: Percentage of Patients Who Were Administered (or Evaluated) by PredicTB Score	Up to 12 months	Percentage of patients who were administered (or evaluated) by PredicTB score among those who presented presumptive TB symptoms at clinics in the post-implementation period in intervention arm