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Trial registered on ANZCTR

Registration number
Ethics application status
Date submitted
Date registered
Date last updated
Date data sharing statement initially provided
Type of registration
Prospectively registered

Titles & IDs
Public title
Can treatment outcomes in drug-resistant tuberculosis (TB) patients be improved with mHealth: The V-SMART trial
Scientific title
Harnessing new mHealth technologies to Strengthen the Management of
Multidrug-Resistant Tuberculosis in Vietnam: The V-SMART trial
Secondary ID [1] 301154 0
Universal Trial Number (UTN)
Trial acronym
Linked study record

Health condition
Health condition(s) or problem(s) studied:
Tuberculosis 317277 0
Condition category
Condition code
Infection 315400 315400 0 0
Other infectious diseases
Respiratory 315510 315510 0 0
Other respiratory disorders / diseases
Public Health 315511 315511 0 0
Health service research

Study type
Description of intervention(s) / exposure
Patients randomized into the intervention arm, in addition to standard care practices, will have a mobile application downloaded onto their smartphones to support their treatment journey. Patients who do not have a smartphone will be loaned one as part of the study. The application was specifically designed for the study and will allow patients direct communication with their designated healthcare worker and provide a platform to report their medication adherence and identification of potential treatment adverse events on a daily basis. The application will also allow healthcare workers to support patients through direct messaging and communicating selected treatment monitoring indicators as they become available, directly on the application. The application is intended to provide a 'bridge' for communication between patients and healthcare workers outside their routine visits; this will allow for more prompt identification of treatment adherence problems or investigation of potential adverse events, ultimately improving successful treatment outcomes. Patients will be encouraged to use the App daily for the duration of their treatment (8-11 months for short regimen or 18-20 months on long regimen)

Antibiotic treatment is in accordance with the guidelines of the Vietnam National Tuberculosis Program.

We have also created an analytics platform on a 'web-based' version fo the App to monitor patient and healthcare usage of the App. In addition, their are daily push-notification reminders to patients and healthcare workers to use and respond to actions on the App.
Intervention code [1] 317461 0
Treatment: Other
Comparator / control treatment
Patients randomized into the control arm will be managed according to standard care practices within the Programmatic Management for Drug-resistant TB (PMDT) programme in Vietnam. Standard care practices involves patients being evaluated at routine clinic visits (usually monthly) for understanding their treatment adherence and diagnosing adverse events. Antibiotic treatment is in accordance with the guidelines of the Vietnam National Tuberculosis Program.
Control group

Primary outcome [1] 323651 0
Treatment success - proportion of randomized patients with treatment success (defined as treatment completion and/or bacteriological cure) after 24 months.

Treatment success is a standard WHO programmatic indicator of treatment outcome, obtained from routine PMDT registries, comprising the sum of treatment completion and
bacteriological cure.
Timepoint [1] 323651 0
24 month post-enrolment
Secondary outcome [1] 382487 0
Time-to-sputum culture conversion -number of days from diagnosis to the first of three consecutive negative sputum culture results, without subsequent reversion
Timepoint [1] 382487 0
2 months post-treatment
Secondary outcome [2] 382488 0
Reported Grade 3 and 4 adverse events during treatment - proportion of patients with any Grade 3 or 4 adverse events occurring from the date of randomisation up to 30 days after the final dose of treatment.
Timepoint [2] 382488 0
30 days post-treatment completion
Secondary outcome [3] 382489 0
Health-related quality of life at the completion of treatment - SF-36 questionnaire
Timepoint [3] 382489 0
6 and 24 months post-randomization.
Secondary outcome [4] 382490 0
All-cause mortality - proportion of patients dying between randomization and the end of 24 months’ follow-up.
Timepoint [4] 382490 0
24 months post-randomization
Secondary outcome [5] 382491 0
Cost effectiveness - cost per quality adjusted life year (QALY) gained based upon detailed patient health costs data collected at study site.
Timepoint [5] 382491 0
Patients on the short-course regimen will have this evaluated at the 11month timepoint, while patients on the long-course treatment will have this evaluated at the 21 month timepoint.
Secondary outcome [6] 382492 0
Acceptability is defined as the relative satisfaction of patients and providers using the mHealth application. This will be assessed using a combination of structured qualitative interviews during and after study follow-up. The structured interviews be one-on-one in-depth interviews and last approximately 30-45 mins. Consent for audio-recording will be requested prior to the interview.
Timepoint [6] 382492 0
During study implementation and at the end of follow-up (24 months)
Secondary outcome [7] 382493 0
Fidelity - degree to which the mHealth application was delivered in the intervention arm as intended

Examples of process indicators:
% downtime of the application
% of participants with a functional smartphone
No. of hours of initial training on the use/deployment of mHealth application attended by PMDT staff

Each of these components will be assessed via App analytics, however attendance of trainings will be done using records from the site initiation visit training.
Timepoint [7] 382493 0
Process indicators collected from health facilities throughout the study
Secondary outcome [8] 382494 0
Feasibility - relative ease of implementation and operation of the mHealth application within existing health systems, technology infrastructure and supply chain. All the example indicators below will be assessed using App analytics.

Examples of process indicators:
% of participants who access the application once per week
% of PMDT staff accessing mHealth dashboard
% of participants who use application to report AE’s
Timepoint [8] 382494 0
Process indicators collected from health facilities throughout the study

Key inclusion criteria
- Aged greater than or equal to 15 years
- Have a diagnosis of bacteriologically confirmed pulmonary and/or extrapulmonary rifampicin resistant (RR) or multidrug-resistant (MDR)-TB
- Have commenced MDR-TB treatment within the previous 30 days
- Demonstrate the ability to operate simple functions on a smartphone (including entering a passcode, opening an application and making a phone call)
Minimum age
15 Years
Maximum age
No limit
Both males and females
Can healthy volunteers participate?
Key exclusion criteria
- Inability to provide written informed consent (e.g. due to a significant communication impairment)
- Do not intend to receive treatment within participating provinces over the subsequent 12 month period
- Another person residing within the same household, at least one day per week, has already been enrolled and randomized within this study.

Study design
Purpose of the study
Allocation to intervention
Randomised controlled trial
Procedure for enrolling a subject and allocating the treatment (allocation concealment procedures)
Allocation will be concealment to enrolment staff as randomisation will be done at a central office by computer, and communicated to the study doctor via a short messaging service (SMS) message or phone call.
Methods used to generate the sequence in which subjects will be randomised (sequence generation)
Block randomization
Masking / blinding
Open (masking not used)
Who is / are masked / blinded?

Intervention assignment
Other design features
Not Applicable
Type of endpoint(s)
Statistical methods / analysis
Sample size - The current proportion of patients with MDR-TB achieving treatment success is 75% (2017 program data). We expect an improvement in treatment success (bacteriological response or completion) by 8% (i.e. from 75% to 83%), a minimal clinically important difference. Using the standard Schlesselman formula for the difference in two proportions, with a power of 0.8, and alpha of 0.05, we require 406 subjects per group. Expecting a 10% loss to follow-up, compatible with our findings in the ACT study, we will recruit a total of 902 patients across the 7 Provinces.

Primary objective
The effectiveness of the mHealth intervention will be assessed by comparing the treatment
success rates between patients in the intervention and standard care arms, 24 months
after treatment initiation. We will use a marginal Poisson regression model estimated via a
generalized estimating equation (GEE) to test the effect of the intervention on treatment success.

Secondary outcomes
Time-to-sputum culture conversion:
We will compare time from treatment initiation to sputum culture conversion by month six between the two arms by conduct a survival analysis using a Cox proportional hazard model adjusting for potential confounders.

Proportion of patients with Grade 3 and 4 adverse events during treatment:
We expect the proportion of grade 3 or 4 adverse events will be greater in the standard care arm, due to delayed identification consistent with barriers in the routine programme. The effect of the intervention on incidence of severe adverse events will be estimated using a marginal logistic regression model estimated via GEE. We will also investigate predictors associated with this outcome using the same approach.

Health-related quality of life:
Patient quality of life will be evaluated using a standardized matrix referred to as the SF-36 scale, a measure of health status that enables evaluation of the effect of an intervention upon quality of life.

All-cause Mortality:
All-cause mortality will be evaluated by research staff 24 months after randomisation. The mortality status of study participants will be evaluated in two ways: 1) through existing patient information collected and maintained by PMDT staff channels; and 2) through study staff who will maintain regular contact with participants and/or their designated family members during, and at the end of the follow-up period post-treatment (including patients who are lost to follow-up).

Cost effectiveness:
Programme and treatment costs will be estimated using a mixture of top-down and bottom-up methods. Incremental cost-effectiveness ratios (ICERs) will be calculated for the primary
outcome of the trial and per QALY gained using utility weights derived from responses to the SF-36. Costs and effects will be presented in both discounted and undiscounted form. Different discounting rates and thresholds will be used to assess the robustness of results.
The Budget Impact Assessment (BIA) will estimate the affordability of the intervention based on short-term costs and savings from the payer’s perspective. Data sources for the cost
effectiveness analysis and BIA will include payment records, staff and patients interviews and
project databases. Results will be shared with country experts to ensure face validity.

Acceptability, Feasibility and Fidelity:
Process indicators of the intervention will be measured using routinely collected data from health facilities and analyzed using descriptive statistics . Up to thirty in-depth interviews will be performed to evaluate staff and patient knowledge, attitudes and practices regarding the
technology, its acceptability, ease of use, and enablers and barriers to use. We will use the theoretical framework of acceptability (TFA) to explore appropriateness, feelings and perceptions of patients and providers involved with implementation of the mHealth application.

Recruitment status
Not yet recruiting
Date of first participant enrolment
Date of last participant enrolment
Date of last data collection
Sample size
Accrual to date
Recruitment outside Australia
Country [1] 22518 0
Viet Nam
State/province [1] 22518 0
Ha Noi
Country [2] 22519 0
Viet Nam
State/province [2] 22519 0
Ho Chi Minh
Country [3] 22520 0
Viet Nam
State/province [3] 22520 0
An Giang
Country [4] 22521 0
Viet Nam
State/province [4] 22521 0
Can Tho
Country [5] 22522 0
Viet Nam
State/province [5] 22522 0
Da Nang
Country [6] 22523 0
Viet Nam
State/province [6] 22523 0
Thanh Hoa
Country [7] 22524 0
Viet Nam
State/province [7] 22524 0
Tien Giang

Funding & Sponsors
Funding source category [1] 305597 0
Government body
Name [1] 305597 0
National Health and Medical Research Council (NHMRC)
Address [1] 305597 0
16 Marcus Clarke St,
ACT 2601
Country [1] 305597 0
Funding source category [2] 305608 0
Government body
Name [2] 305608 0
National Foundation for Science and Technology Development (NAFOSTED)
Address [2] 305608 0
4th floor,
39 Tran Hung Dao Street,
Hoan Kiem District,
Ha Noi City
Country [2] 305608 0
Viet Nam
Primary sponsor type
University of Sydney
The University of Sydney
NSW 2006
Secondary sponsor category [1] 306011 0
Other Collaborative groups
Name [1] 306011 0
Woolcock Institute of Medical Research
Address [1] 306011 0
431 Glebe Point Road,
NSW 2037
Country [1] 306011 0

Ethics approval
Ethics application status
Ethics committee name [1] 305896 0
University of Sydney Human Research Ethics Committee
Ethics committee address [1] 305896 0
The University of Sydney
NSW 2006
Ethics committee country [1] 305896 0
Date submitted for ethics approval [1] 305896 0
Approval date [1] 305896 0
Ethics approval number [1] 305896 0

Brief summary
We hypothesize that an mHealth application supporting MDR-TB patients by providing effective health information and enhanced health system support when they experience adverse events (the intervention), will improve their clinical outcomes compared to patients who do not utilize such an application (standard care).

The primary objective of this study is to evaluate the effectiveness of a ‘mHealth’ digital adverse event support intervention, compared to “standard care” (without the mHealth intervention), upon treatment success (comprising treatment completion and/or bacteriological cure), among patients with MDR-TB treated in the PMDT program.

The use of an mHealth application could potentially serve as a scalable platform to support MDR-TB patients during treatment, ideally reducing the occurrence of Grade 3 and 4 AEs through better identification and management of Grade 1 and 2 AE’s. The study will provide valuable evidence for MDRTB programmes globally on strategies for improving patient management and clinical outcomes.
Trial website
Trial related presentations / publications
Public notes

Principal investigator
Name 101974 0
A/Prof Greg J. Fox
Address 101974 0
The University of Sydney
Rm 5216, Level 2 Medical Foundation Building K25,
92-94 Parramatta Road,
NSW 2006
Country 101974 0
Phone 101974 0
+61 2 9036 3121
Fax 101974 0
Email 101974 0
Contact person for public queries
Name 101975 0
A/Prof Greg J. Fox
Address 101975 0
The University of Sydney
Rm 5216, Level 2 Medical Foundation Building K25,
92-94 Parramatta Road,
NSW 2006
Country 101975 0
Phone 101975 0
+61 2 9036 3121
Fax 101975 0
Email 101975 0
Contact person for scientific queries
Name 101976 0
A/Prof Greg J. Fox
Address 101976 0
The University of Sydney
Rm 5216, Level 2 Medical Foundation Building K25,
92-94 Parramatta Road,
NSW 2006
Country 101976 0
Phone 101976 0
+61 2 9036 3121
Fax 101976 0
Email 101976 0

Data sharing statement
Will individual participant data (IPD) for this trial be available (including data dictionaries)?
No/undecided IPD sharing reason/comment
What supporting documents are/will be available?
Study protocol
Informed consent form
How or where can supporting documents be obtained?
Type [1] 7830 0
Study protocol
Citation [1] 7830 0
This will be submitted for publication.
Link [1] 7830 0
Email [1] 7830 0
Other [1] 7830 0
Attachment [1] 7830 0
Type [2] 7831 0
Informed consent form
Citation [2] 7831 0
This will be included as a supplement to the protocol.
Link [2] 7831 0
Email [2] 7831 0
Other [2] 7831 0
Attachment [2] 7831 0
Summary results
No Results