FOCUSau: A Dyadic Digital Health Intervention to Improve the Wellbeing of People With Advanced Cancer and Their Carers — FOCUSau  

Advanced Cancer Clinical Trial

Official title: Improving the Wellbeing of People With Advanced Cancer and Their Family Carers: An Effectiveness Implementation Trial of an Australian Dyadic Digital Health Intervention (FOCUSau)

Status Not yet recruiting

Clinical Trial Summary

FOCUS is a dyadic, psychoeducational intervention developed in the USA, shown to improve the wellbeing and quality of life (QoL) of patients with advanced cancer and their primary family carers. The intervention consists of five core components underpinning the FOCUS acronym:

(F) supporting Family involvement, (O) supporting Outlook and meaning, (C) increasing Coping effectiveness, (U) reducing Uncertainty, and (S) Symptom management. Originally a nurse-delivered in-person intervention, FOCUS has been translated into a self-administered web-based intervention as part of an European study.

The overall aim of this project is to determine the effectiveness and sustainability of a digital health intervention (FOCUSau) aimed at improving the wellbeing and self-efficacy of patients with advanced cancer and their primary support person/carer.

A primary support person/carer is an unpaid individual identified by the person with advanced cancer (not necessarily a partner or family member) who is providing them with physical, social or emotional support. Hereafter referred to as a "carer". The term "dyad" refers to the patient and primary support person/carer.

The project objectives are:

1. adapt FOCUS to the Australian context and develop FOCUSau;

2. examine the effectiveness of FOCUSau in improving the wellbeing (primary outcomes: QoL and self-efficacy) of patients with advanced cancer and their primary family carer;

3. compare the type and costs of health service use by participants in the intervention and control group; and

4. assess the acceptability, feasibility and scalability of FOCUSau in order to inform sustainable implementation of the intervention within the Australian health care system.

A pragmatic phase III hybrid effectiveness-implementation trial with an integrated research design that includes digital health evaluation will be used in patients with advanced cancer and their primary support person/carer.

Data will be collected three times from patient-carer dyads:

1. at baseline (T0) after which the dyad will immediately be randomised to one of the study arms,

2. first follow-up at 12 weeks after baseline (T1) and,

3. second follow-up at 24 weeks after baseline (T2).

Clinical Trial Description

STUDY SETTING:

The patient-carer dyads will be recruited via two methods: (1) referral from hospitals or (2) self-referral. For method one, approximately six hospitals and/or cancer centres (metropolitan and regional) across Australia will be selected. For the self-referral recruitment method, patients who have been made aware of the project (but have not been officially screened by a clinician) may self-refer via a webform on the project website. These patients will be made aware via consumer/carer/cancer advocacy groups, or social media advertisement.

SAMPLE SIZE:

A pre-determined strict fixed sequence (FS) procedure defines prospectively hierarchical ordering of the primary endpoints; emotional wellbeing (1) and self-efficacy (2). Testing of null hypotheses proceeds according to their hierarchical order; that is, hypothesis 1 (H(1)0) is tested first at a significance level of 5%, and if H(1)0 is rejected then hypothesis 2 (H(2)0) is tested at the same significance level, otherwise H(2)0 is not tested at all. The strict FS approach has the highest power for testing the first hypothesis (outcome: emotional wellbeing) compared to the other methods, as it does not save any portion of alpha for testing later hypothesis. The reference mean value from The European Organization for Research and Treatment of Cancer (EORTC) for all cancer patients, stage III-IV is 71.5 (SD: 23.8). To maintain rigorous control over Type I errors due to multiple comparisons, the alpha level is set at 0.025 instead of the more common 0.05. This adjustment accounts for the multiple comparisons required in the study, including comparisons between a control group and two participant groups (patients and carers). Statistical power is set at 0.80. The expected difference between the control group and the intervention arm in the primary outcomes is 0.375 SD at T1 (12 weeks). With these parameters n=173 dyads are needed in each arm (i.e. 346 dyads in total). Anticipating a maximum 80% retention rate at T1 (USA FOCUS retention was 86%) approximately 433 dyads will need to be recruited. An enrolment rate of 55% of those eligible was achieved in prior digital health FOCUS study from 2014, however it is anticipated this will be higher for FOCUSau (estimating 70%) given the internet is much more widely available now and the digital recruitment approach; meaning that approximately 618 dyads who meet eligibility criteria will need to be identified. Evidence also suggests that recruitment rates can increase when a digital health intervention is offered.

DATA ANALYSIS:

The effectiveness of FOCUSau will be compared with the standard care (control group) for each participant population (patients/carers) using significance level of alpha=0.025. The hypotheses will be tested using a mixed model (per participant population) with the T1 measurement values for emotional wellbeing and self-efficacy as primary outcomes. These mixed models will be implemented using International Business Machines Corporation (IBM) Statistical Package for the Social Sciences (SPSS) for Windows Version 27.0 and R with recruitment centre treated as a random effect and randomisation group as predictor variables. As per the fixed sequence (FS) procedure, the null hypotheses of the second primary endpoint (self-efficacy) will only be tested if a significant result is found for the first primary endpoint (emotional wellbeing). Additionally, other factors identified in the literature will be incorporated as potentially predictive by including them as covariates in the mixed models. Analyses on both 'intention-to-treat' and per-protocol principles will be performed. To interpret the magnitude of the effects for the different outcomes, effect sizes will be estimated (Cohen's d).

The data analysis will encompass all primary and secondary outcomes. Primary endpoints, including emotional wellbeing and self-efficacy measured at T1, will be analysed first. Following that, secondary endpoints, comprising outcomes measured at T1 that are not primary endpoints, as well as all outcomes measured at T2 (occurring 24 weeks from T0), will be assessed. This approach allows for a comprehensive evaluation, including the examination of longer-term effects.

The robustness and validity of the results will be explored using sensitivity analyses by varying the parameter inputs (including sensitivity to the use of values for missing observations). The analysis will be conducted for the within trial period; the potential to extrapolate results over the longer-term will be assessed based on the proportion of patients alive at the end of follow-up.

The cost-effectiveness analysis will be reported as the mean costs of care per dyad in each arm of the study. Costs applied to health care service use will be as per Australian standard fees (e.g., via the Medicare Benefits Schedule). If a difference in outcomes is observed, as hypothesised, the incremental cost effectiveness of FOCUSau compared with control will be estimated in terms of the: (1) cost per additional patient with a meaningful improvement in emotional wellbeing (as assessed using the EORTC QLQ-C30 emotional wellbeing scale); and separately, (2) cost per additional carer with a meaningful change in self-efficacy (as assessed using the The Lewis´ Cancer self-efficacy scale). The base case analysis of cost-effectiveness will be conducted from a health care system perspective. Subsequent sensitivity analyses will modify the assessment of costs to adopt a societal perspective to capture the impact of informal care costs, as well as testing the robustness of the analysis results to variations in other parameter inputs.

Missing data for costs and outcomes will be described and summarised. Where missing data can be regarded as missing at random, likelihood (interpolation) methods will be used for analysis of those data as appropriate. ;

Related Conditions & MeSH terms

• Advanced Cancer
• Neoplasms

• NCT number: NCT06082128
• Study type: Interventional
• Source: University of Melbourne
• Contact: Shaira Baptista, PhD
• Phone: +61394160000
• Email: shaira.baptista@unimelb.edu.au
• Status: Not yet recruiting
• Phase: N/A
• Start date: December 2023
• Completion date: August 2025