Skip to content

A Clinical Risk Score for Early Management of TB in Uganda

PredicTB: Validating a Clinical Risk Score for Early Management of Tuberculosis in Ugandan Primary Health Clinics

Status
Completed
Phases
NA
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT05122624
Acronym
PredicTB
Enrollment
3332
Registered
2021-11-17
Start date
2021-11-10
Completion date
2024-02-29
Last updated
2024-07-23

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Tuberculosis, Pulmonary

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.

Interventions

OTHERPredicTB score

This is an easy-to-use clinical risk score designed to improve early management of tuberculosis in highly resource-constrained settings where same-day microbiological testing is unavailable. It consists of readily accessible demographic and clinical data and is scored from 1-10. We will train clinic staff in eight clinics (four study clinics and four comparison clinics) on the Ugandan standard of care for the diagnosis and treatment of TB. In addition, in the four study clinics, we will provide training on the PredicTB score.

Sponsors

National Institute of Allergy and Infectious Diseases (NIAID)
CollaboratorNIH
Johns Hopkins Bloomberg School of Public Health
Lead SponsorOTHER

Study design

Allocation
NON_RANDOMIZED
Intervention model
PARALLEL
Primary purpose
DIAGNOSTIC
Masking
NONE

Intervention model description

The study includes an intervention arm (four clinics) and a control arm (four clinics).

Eligibility

Sex/Gender
ALL
Age
15 Years to No maximum
Healthy volunteers
No

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

Design outcomes

Primary

MeasureTime frameDescription
Difference in 7-day Treatment Initiation From Pre-implementation to Post-implementationUp to 12 months post interventionThe 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
Implementation: Percentage of Encountered Patients at Intervention Arm Who Initiated the Same-day Treatment Based on PredicTB Score as IndicatedUp to 12 monthsPercentage 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

Secondary

MeasureTime frameDescription
Difference in Loss to Care From Pre-implementation To Post-implementation12 MonthsThe 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 TBUp to 12 months post-implementationDifference 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
Reach: Percentage of Patients Who Were Administered (or Evaluated) by PredicTB ScoreUp to 12 monthsPercentage 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
Incremental Cost-effectiveness of PredicTBMonths 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)
Maintenance: Change in Effectiveness Over Time in the Post-implementation Phase at Intervention ArmUp to 12 monthsPercentage 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
Modeled Changes in 5-year Mortality With PredicTBMonth 12Modeled 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
Adoption: Percentage of Providers Adopting PredicTBMonth 18Percentage 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
Difference in TB Mortality From Pre-implementation to Post-implementation12 MonthsThe 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

Countries

Uganda

Participant flow

Pre-assignment details

The study was initially conducted in eight primary health clinics (four clinics in the intervention arm and the other four clinics in the control arm). During the study, a total of three clinics (two in the intervention arm and one in the control arm) were replaced with other facilities of similar size and location for the remainder of the study period, resulting in 11 participating clinics.

Participants by arm

ArmCount
Score Intervention Arm
The PredicTB score will be implemented in this arm. PredicTB score: This is an easy-to-use clinical risk score designed to improve early management of tuberculosis in highly resource-constrained settings where same-day microbiological testing is unavailable. It consists of readily accessible demographic and clinical data and is scored from 1-10. We will train clinic staff in eight clinics (four study clinics and four comparison clinics) on the Ugandan standard of care for the diagnosis and treatment of TB. In addition, in the four study clinics, we will provide training on the PredicTB score.
1,826
Score Intervention Arm
The PredicTB score will be implemented in this arm. PredicTB score: This is an easy-to-use clinical risk score designed to improve early management of tuberculosis in highly resource-constrained settings where same-day microbiological testing is unavailable. It consists of readily accessible demographic and clinical data and is scored from 1-10. We will train clinic staff in eight clinics (four study clinics and four comparison clinics) on the Ugandan standard of care for the diagnosis and treatment of TB. In addition, in the four study clinics, we will provide training on the PredicTB score.
6
Control Arm
The standard of care will be conducted in this arm.
1,506
Control Arm
The standard of care will be conducted in this arm.
5
Total3,343

Baseline characteristics

CharacteristicScore Intervention ArmControl ArmTotal
Age, Continuous36 years35 years36 years
HIV status
Negative
760 Participants741 Participants1501 Participants
HIV status
Positive
857 Participants684 Participants1541 Participants
HIV status
Unknown/Missing
209 Participants81 Participants290 Participants
Microbiologically confirmed TB173 Participants138 Participants311 Participants
Race and Ethnicity Not Collected0 Participants
Region of Enrollment
Uganda
1826 Participants1506 Participants3332 Participants
Sex: Female, Male
Female
1077 Participants834 Participants1911 Participants
Sex: Female, Male
Male
749 Participants671 Participants1420 Participants
Sputum specimen submitted1348 Participants1007 Participants2355 Participants

Adverse events

Event typeEG000
affected / at risk
EG001
affected / at risk
deaths
Total, all-cause mortality
12 / 31617 / 211
other
Total, other adverse events
0 / 3160 / 211
serious
Total, serious adverse events
0 / 3160 / 211

Outcome results

Primary

Difference in 7-day Treatment Initiation From Pre-implementation to Post-implementation

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

Time frame: Up to 12 months post intervention

Population: This outcome includes individuals who were diagnosed with tuberculosis.

ArmMeasureValue (NUMBER)
Score Intervention ArmDifference in 7-day Treatment Initiation From Pre-implementation to Post-implementation1 percentage of participants
Control ArmDifference in 7-day Treatment Initiation From Pre-implementation to Post-implementation-13 percentage of participants
Primary

Implementation: Percentage of Encountered Patients at Intervention Arm Who Initiated the Same-day Treatment Based on PredicTB Score as Indicated

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

Time frame: Up to 12 months

Population: This outcome includes individuals who presented TB symptoms. This outcome is relevant to intervention arm only.

ArmMeasureValue (NUMBER)
Score Intervention ArmImplementation: Percentage of Encountered Patients at Intervention Arm Who Initiated the Same-day Treatment Based on PredicTB Score as Indicated46 percentage of participants
Secondary

Adoption: Percentage of Providers Adopting PredicTB

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

Time frame: Month 18

Population: This outcome analysis is relevant to intervention arm only. Per protocol, healthcare providers were not considered enrolled.

ArmMeasureValue (NUMBER)
Score Intervention ArmAdoption: Percentage of Providers Adopting PredicTB100 percentage of providers
Secondary

Difference in Loss to Care From Pre-implementation To Post-implementation

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

Time frame: 12 Months

Population: This outcome includes individuals who were diagnosed with tuberculosis.

ArmMeasureValue (NUMBER)
Score Intervention ArmDifference in Loss to Care From Pre-implementation To Post-implementation1 percentage of participants
Control ArmDifference in Loss to Care From Pre-implementation To Post-implementation1 percentage of participants
Secondary

Difference in Percentage of Participants With Microbiologically Confirmed TB

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

Time frame: Up to 12 months post-implementation

Population: This outcome includes individuals who were diagnosed with tuberculosis.

ArmMeasureValue (NUMBER)
Score Intervention ArmDifference in Percentage of Participants With Microbiologically Confirmed TB14 percentage of participants
Control ArmDifference in Percentage of Participants With Microbiologically Confirmed TB0 percentage of participants
Secondary

Difference in TB Mortality From Pre-implementation to Post-implementation

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

Time frame: 12 Months

Population: This outcome includes individuals who were diagnosed with tuberculosis.

ArmMeasureValue (NUMBER)
Score Intervention ArmDifference in TB Mortality From Pre-implementation to Post-implementation-1 percentage of participants
Control ArmDifference in TB Mortality From Pre-implementation to Post-implementation-1 percentage of participants
Secondary

Incremental Cost-effectiveness of PredicTB

(cost of implementing PredicTB - cost of standard of care)/(projected disability-adjusted life years (DALYs) in standard of care - projected DALYs with PredicTB)

Time frame: Months 0 - 12

Population: Data was not collected.

Secondary

Maintenance: Change in Effectiveness Over Time in the Post-implementation Phase at Intervention Arm

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

Time frame: Up to 12 months

Population: This outcome is relevant to intervention arm only

ArmMeasureValue (NUMBER)
Score Intervention ArmMaintenance: Change in Effectiveness Over Time in the Post-implementation Phase at Intervention Arm-16 percentage of participants
Secondary

Modeled Changes in 5-year Mortality With PredicTB

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

Time frame: Month 12

Population: Data was not collected.

Secondary

Reach: Percentage of Patients Who Were Administered (or Evaluated) by PredicTB Score

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

Time frame: Up to 12 months

Population: This outcome includes individuals who presented TB symptoms. This outcome is relevant to intervention arm only.

ArmMeasureValue (NUMBER)
Score Intervention ArmReach: Percentage of Patients Who Were Administered (or Evaluated) by PredicTB Score66 percentage of participants

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026