Ignite Creation Date:
2024-05-06 @ 2:26 PM
Last Modification Date:
2024-10-26 @ 1:31 PM
Study NCT ID:
NCT04318886
Status:
RECRUITING
Last Update Posted:
2023-11-18
First Post:
2020-03-20
Brief Title:
Lay Coach-Led Early Palliative Care for Underserved Advanced Cancer Caregivers The Project ENABLE Cornerstone RCT
Sponsor:
University of Alabama at Birmingham
Organization:
University of Alabama at Birmingham
Study Overview
Official Title:
Lay Coach-Led Early Palliative Care for Underserved Advanced Cancer Caregivers The Project ENABLE Cornerstone RCT
Status:
RECRUITING
Status Verified Date:
2023-11
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
None
Brief Summary:
Many of the 28 million family caregivers FCGs of persons with advanced cancer are underserved particularly African-Americans and rural-dwellers in the Southern US Most have poor access and awareness of community-based palliative care services and have received no formal support or training despite providing assistance to their relatives an average of 8 hrsday Providing intense care and witnessing a close friend or family member struggle with advanced cancer can result in FCGs experiencing marked distress particularly as their care recipients near end of life EOL Reports from NCI and NINR caregiving summits systematic reviews and the National Academy of Medicine have highlighted major limitations of cancer caregiver interventions including a lack of attention to underserved populations and cost poor scalability over reliance on highly-trained professionals eg nurses psychologists behavioral therapists lengthy sessions over a short duration and a lack of demonstrated impact on patient outcomes and healthcare utilization To address this gap the investigators have developed and tested feasibility and acceptability of a lay navigator-led early palliative care intervention called ENABLE Cornerstone for rural and minority family caregivers of persons with advanced cancer in the Southern US Evolving out of the teams prior trials and community stakeholder formative evaluation work this multicomponent intervention is based on Pearlins Stress-Health Process Model where lay navigators overseen by an interdisciplinary outpatient palliative care team employ health coaching techniques and caregiver distress screening to behaviorally activate and reinforce psychoeducation on managing stress and coping getting and asking for help improving caregiving skills and decision-makingadvance care planning over 6 brief in-persontelephonic sessions plus monthly follow-up from diagnosis through early bereavement This proposed hybrid type I randomized effectiveness-implementation trial will determine whether ENABLE Cornerstone compared to usual care can improve family caregiver Aim 1 and patient outcomes Aim 2 and will evaluate implementation costs cost effectiveness and healthcare utilization Aim 3 over 24 weeks with 294 family caregivers and their patients with newly-diagnosed advanced cancer To maximize recruitment the investigators will recruit from two community cancer centers in Birmingham AL and Mobile AL Our theory-driven standardized approach is innovative because it uses lay navigators in collaboration with a palliative care interdisciplinary team to promote caregiver activation skills and knowledge enhancement as opposed to other difficult-to-implement intervention models that rely mostly on delivery of services by advanced practice professionals providing lengthy sessions over a short duration If effectiveness is established the ENABLE Cornerstone intervention offers a highly scalable and reproducible model of formal caregiver support that would be primed for dissemination and implementation
Detailed Description:
This hybrid type I randomized effectiveness-implementation trial is designed to answer the question Is ENABLE Cornerstone efficacious in enhancing caregiver and patient outcomes The primary aims are to assess the effectiveness of ENABLE Cornerstone over 24 weeks Primary and Secondary Aim The investigators will also explore implementation cost and cost effectiveness including healthcare utilization Aim 3 and other potential mediatormoderator effects of the intervention on coping social support and preparedness Exploratory Aim The study will recruit 294 family caregivers over the age of 21 reporting that they are the primary unpaid provider of support to a close family member or friend who has been newly-diagnosed with an advanced stage cancer within the past 60 days Half of the participants will be randomized to ENABLE Cornerstone n147 which consists of 6 brief weekly in-persontelephone sessions followed by monthly follow-up every 4 weeks as needed by participants The other half will be assigned to a usual care condition n147 The randomization scheme stratified by site UAB and MCI in block lengths of 8 will be executed in REDCap a clinical trials management software program using a computer-generated algorithm Assessments will be administered via telephone by a research coordinator blind to group assignment Participants will complete outcome assessments upon enrollment T1 and at 12 T2 24 T3 and every 12 weeks thereafter The T2 assessment captures the short-term outcomes of the most intensive part of the intervention The T3 assessment will capture the long-term outcomes of the intervention Subsequent assessments explore the sustained effect of ENABLE Cornerstone at the patients end-of-life and post death The primary outcome is whether the intervention affects the slope of FCG distress at 24 weeks
An intention to treat ITT approach will be used for all analyses That is all caregivers and patients will be included in their respective assigned conditions regardless of their degree of participation in the study Primary data analysis will begin with descriptive statistics for baseline caregiver and patient characteristics and outcomes The investigators will examine balance between study groups with respect to baseline characteristics using effect sizes such as the standardized mean difference for numerical variables and Cramers V for categorical variables Conceptually relevant baseline factors showing non-trivial imbalances between groups will be then used as adjusting covariates in the longitudinal group comparisons Distributional assumptions will be examined and when appropriate we will employ inferential and modeling procedures robust to distributional assumptions such as normality Patterns of missing data will be examined and whether baseline characteristics are associated with dropout Conceptually relevant baseline factors predictive of dropout will then be used as adjusting covariates in the longitudinal group comparisons Mixed-effect modeling techniques and covariate adjustment will reduce the impact of missing data as the missingness is not assumed completely at random MCAR but conditionally on the covariates at random ie MAR a milder assumption We will use the latest versions of SAS and R for all analyses and reports
For specific aims 1 and 2 a longitudinal model fitted with linear mixed methods will be used for each outcome The focus of inference will be the between-group difference in outcome change from baseline over 12 and 24 weeks modeled by a time by group interaction A random effect for subject will be fitted to account for covariance among repeated measures on the same individuals The fixed-effect part of the model has the form Yb_0b_1Cornerstoneb_2Week12b_3Week24b_4CornerstoneWeek12b_5CornerstoneWeek24 where Y is the expected value ie the mean of the outcome according to the predictor combinations Cornerstone is a binary indicator of group assignment 1ENABLE Cornerstone 0usual care and Week24 and Week12 are binary indicators of the follow-up time points For the usual care group the mean outcome at baseline is estimated by the b_0 coefficient the mean outcome at Week 12 is estimated by b_0b_2 and the mean outcome at Week 24 is estimated by b_0b_3 For the ENABLE Cornerstone group the mean outcome at baseline is estimated by b_0b_1 the mean outcome at Week 12 is estimated by b_0b_1b_2b_4 and the mean outcome at Week 24 is estimated by b_0b_1b_3b_5 The overall treatment effect will be computed as the average between-group difference in change from baseline averaged over Week 12 and Week 24 estimated with a linear contrast 12b_4b_5 From the perspective of significance testing the test for the interaction effect a 2-degree of freedom test is the test of difference in change from baseline between the study groups since the groups are randomized and the mean outcome at baseline should be similar If necessary the team will conduct covariate adjustment for baseline factors unbalanced between the groups or predictive of dropout
For specific aim 3 this within-trial analysis will be conducted separately from the perspectives of healthcare payers and FCGs and patients following current recommendations Because the ENABLE Cornerstone intervention potentially affects FCG and patient distress and QOL and by consequence potentially affects healthcare utilization and costs upfront implementation costs will be weighed against potential savings in healthcare costs and effectiveness measured by improvements in quality of life adjusted years QALY over the follow-up period
An intention to treat ITT approach will be used for all analyses That is all caregivers and patients will be included in their respective assigned conditions regardless of their degree of participation in the study Primary data analysis will begin with descriptive statistics for baseline caregiver and patient characteristics and outcomes The investigators will examine balance between study groups with respect to baseline characteristics using effect sizes such as the standardized mean difference for numerical variables and Cramers V for categorical variables Conceptually relevant baseline factors showing non-trivial imbalances between groups will be then used as adjusting covariates in the longitudinal group comparisons Distributional assumptions will be examined and when appropriate we will employ inferential and modeling procedures robust to distributional assumptions such as normality Patterns of missing data will be examined and whether baseline characteristics are associated with dropout Conceptually relevant baseline factors predictive of dropout will then be used as adjusting covariates in the longitudinal group comparisons Mixed-effect modeling techniques and covariate adjustment will reduce the impact of missing data as the missingness is not assumed completely at random MCAR but conditionally on the covariates at random ie MAR a milder assumption We will use the latest versions of SAS and R for all analyses and reports
For specific aims 1 and 2 a longitudinal model fitted with linear mixed methods will be used for each outcome The focus of inference will be the between-group difference in outcome change from baseline over 12 and 24 weeks modeled by a time by group interaction A random effect for subject will be fitted to account for covariance among repeated measures on the same individuals The fixed-effect part of the model has the form Yb_0b_1Cornerstoneb_2Week12b_3Week24b_4CornerstoneWeek12b_5CornerstoneWeek24 where Y is the expected value ie the mean of the outcome according to the predictor combinations Cornerstone is a binary indicator of group assignment 1ENABLE Cornerstone 0usual care and Week24 and Week12 are binary indicators of the follow-up time points For the usual care group the mean outcome at baseline is estimated by the b_0 coefficient the mean outcome at Week 12 is estimated by b_0b_2 and the mean outcome at Week 24 is estimated by b_0b_3 For the ENABLE Cornerstone group the mean outcome at baseline is estimated by b_0b_1 the mean outcome at Week 12 is estimated by b_0b_1b_2b_4 and the mean outcome at Week 24 is estimated by b_0b_1b_3b_5 The overall treatment effect will be computed as the average between-group difference in change from baseline averaged over Week 12 and Week 24 estimated with a linear contrast 12b_4b_5 From the perspective of significance testing the test for the interaction effect a 2-degree of freedom test is the test of difference in change from baseline between the study groups since the groups are randomized and the mean outcome at baseline should be similar If necessary the team will conduct covariate adjustment for baseline factors unbalanced between the groups or predictive of dropout
For specific aim 3 this within-trial analysis will be conducted separately from the perspectives of healthcare payers and FCGs and patients following current recommendations Because the ENABLE Cornerstone intervention potentially affects FCG and patient distress and QOL and by consequence potentially affects healthcare utilization and costs upfront implementation costs will be weighed against potential savings in healthcare costs and effectiveness measured by improvements in quality of life adjusted years QALY over the follow-up period
Study Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None