Tuberculosis Clinical Trial
Official title:
Cost-effectiveness of a Population-based Active TB Control Program for Tuberculosis, Lima, Peru
The purpose of this study is to determine the effectiveness and cost-effectiveness of a new population-based active case-finding program among adult household contacts of new infectious TB cases to detect active TB cases in the largest district, Lima, Peru.
The Ministry of Health TB program of the District SJL (DISA NTP) is undertaking new public
health intervention that involves the active evaluation of household contacts. We are
collaborating to roll this intervention out as a stepped wedge pragmatic randomized
controlled trial in order to evaluate the effectiveness and cost-effectiveness of this
intervention.
Intervention Model
The intervention is rolled out across all clusters (or health centres) in the form of a
stepped wedge design, that is a unidirectional crossover, such that all clusters start in
the control arm and are then randomized to the time point of cross over to the intervention
arm. This continues in steps until all clusters (or health centres) have crossed over to the
intervention arm. The randomization of health centres is to the timepoint at which they will
cross over to the intervention arm. This randomization was stratified by clinicTB rates
<100/100,000, TB rates 100 to 200/100,000, and clinics with TB rates >200/100,000, to ensure
balance of clinic sizes randomized to the intervention arm at each time point.
Power analysis
Given that the number of clusters, or health centres (n=35) is fixed, a power analysis was
undertaken to estimate the smallest detectable difference between the overall yields of the
active intervention (ACF) and the passive case finding (PCF) in the current study. The power
analysis for stepped wedge clustered designs must be modified to account for the stepped
implementation and the variation in cluster sizes we are likely to observe. In a parallel
study designed to achieve a specified level of power, the same population in a stepped wedge
design will have less the specified level of power, and the standard normal deviates should
be increased by an inflation factor. Using a similar approach and accounting for stepped
wedge design and the varying cluster sizes within the sample, in comparison to the expected
baseline 1% case detection among household contacts we anticipate in passive case finding,
we should have a power of greater than 90% detect differences between 3% and 4% ( with
overall yields of ACF with 4 or 5%) between the intervention and control arms. Based on
previous studies, we anticipate this should be adequate to determine an effect that would be
of clinical and programmatic importance.
The study will be undertaken in district clinics over the course of 18 months (3 baseline
and 15 months of the ACF program phase-in). In 2010, DISA NTP reported 1,871 TB cases within
35 clinics over 12 months (unpublished Ministry of Health data). We anticipate median of 5
household contacts per TB case (range 3-7) . In previous studies within the district,
response rates to index case enrollment to studies in the district have been over 80%. In a
study recruiting 60 Multidrug resistant (MDR) TB index cases and 80 randomly selected
drug-sensitive TB controls in SJL, 92% of case and 98% of controls selected agreed to
participate in the study. Therefore, given our current proposed roll out over 15 months, if
we conservatively estimate 70% participation and 3 household contacts per home we would
anticipate approximately 1900 index TB cases and approximately 5700 household contacts.
Data extraction and management
DISA NTP routinely collect data on household contacts evaluated in public health forms
within TB case histories. Similarly, during home visits, additional ACF forms on household
contacts will be collected. The new ACF TB forms are public health forms that DISA NTP has
developed, however with input from the study investigators, both to ensure data completeness
and quality and to incorporate any data on time and cost of the program. The study
investigators will provide a role in pilot testing and validation of the data collection
tools and program procedures. DISA NTP staff will conduct all home visits, all evaluations
TB cases and contacts and related data collection. Currently all NTP data at the clinic
level are paper-based and maintained in individual TB case charts.
Study specific teams (university-based) will audit and extract the routine public health and
the active intervention TB forms. This strategy will ensure a real-life pragmatic
perspective of the program using DISA NTP staff to implement the program in the context of
their regular TB program, however provide additional monitoring and digitizing of data for
evaluation. Dedicated study field workers will extract PCF and ACF data prospectively from
the original TB case histories, household contact evaluation and ACF intervention (where
applicable) forms within index TB patient charts at DISA NTP clinics. Information from the
case histories for each TB patient's household contacts will be collected in the first
month, at 3 months and 6 month time periods. The extraction method will include where
possible and allowed photocopy of the relevant public health forms. These forms are then
summarized in study data extraction forms and entered into a single secure database. Data
are verified by a supervisor comparing extraction forms to the chart forms, and the database
electronic records to the extraction forms.
Analysis
The primary outcome of interest is the overall yield of secondary TB cases from either the
new active program compared with the passive routine program and associated costs of each.
Univariate analyses will be performed to describe population characteristics. Analysis will
be undertaken according the principles of intention-to-treat (ITT), using data collected
from individual TB case records at randomized clinics, such that contacts detected as
secondary cases will be assigned to the intervention or comparator in their clinic at that
time period. A marginal logistic regression model will be estimated using Generalized
Estimated Equations (GEE ). The GEE will be modeled using a logit link function, and a
robust variance estimation which is robust to misspecification of the correlation structure.
Analysis will be at the unit of the individual accounting for the clustering by clinic.
Covariates included in the model will include individual level age, gender, previous TB
treatment, index TB case smear positivity gradient and clinic level covariates. The
treatment effect will be an odds ratio of the time to case detection in the intervention
group (ACF) in comparison to the comparator (PCF).
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Allocation: Randomized, Intervention Model: Crossover Assignment, Masking: Open Label, Primary Purpose: Screening
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