Prostate Carcinoma
Conditions
Brief summary
This trial studies the effect of an eHealth coaching program (PACK Health) on patient reported outcomes of men with prostate cancer. An electronic health support program may affect prostate cancer patients' reported side effects and outcomes of care.
Detailed description
PRIMARY OBJECTIVES: I. To model the trajectory of patient reported outcomes (PROs), as measured by the National Institutes of Health (NIH) Patient Reported Outcomes Measurement Information System (PROMIS) Global Health Scale (version \[v\]1.2), among men newly diagnosed with prostate cancer who are engaged in either active surveillance or active treatment, while enrolled in an e-health coaching program. Ia. To compare the trajectories of (PROs) between men who are engaged in either active surveillance or active treatment, while enrolled in an e-health coaching program. SECONDARY OBJECTIVES: I. To evaluate the effect of digital health coaching program on: Ia. Physical and mental health of men newly diagnosed with prostate cancer as measured by the subscales of the PROMIS Global Health Scale (v 1.2). Ib. The global health outcomes of men with prostate cancer who are in active treatment by active treatment type (i.e. surgery, radiation, chemotherapy, hormonal therapy, or a combination of these methodologies). Ic. The symptom experience of men newly diagnosed with prostate cancer as measured by the MD Anderson Symptom Inventory (MDASI). Id. The frequency of emergency room visits and hospital admissions for patients receiving treatment in the ambulatory setting. II. To evaluate the relationship between financial toxicity, as measured by the Consumer Score for Financial Toxicity (COST), and quality of life, as measured by the Expanded Prostate Cancer Index Composite for Clinical Practice (EPIC-CP). OUTLINE: Patients are contacted once weekly by a health coach by text message, phone call, email, or a mobile application, for 3 months. The total time interacting with the health coach is about 3.5-4.5 hours across the study. Patients also complete surveys over 30 minutes each time at baseline and every 30 days for 3 months.
Interventions
BEHAVIORALBehavioral Intervention
Participate in PACK Health
OTHERSurvey Administration
Complete survey
Sponsors
National Cancer Institute (NCI)
M.D. Anderson Cancer Center
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SUPPORTIVE_CARE
Masking
NONE
Eligibility
Sex/Gender
MALE
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Able to read, speak and consent in English * Newly diagnosed (within 6 months of diagnosis) with prostate cancer * Internet access via smart phone, tablet, a computer, or another device with the capacity to receive calls, texts, or e-mails, as well as the electronic study assessments
Exclusion criteria
* Individuals who are terminally ill, defined as individuals identified by their physician as likely having 6 months or less to live, or those individuals transitioned to hospice care * Individuals who have a prior diagnosis of prostate cancer * Individuals for whom there is documentation of inability to provide consent in the medical record
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Model trajectories of men who participate in eHealth program | Up to 3 months | Summary statistics and box plots will also be used to describe Patient Reported Outcomes Measurement Information System (PROMIS) (1.2) and other inventory scores and subscale scores by cohort and assessment time. A linear mixed effects model will be used to assess PROMIS (version 1.2) (and scores over time). The models will include assessment time, treatment and a treatment by time interaction as fixed effects and intercept as a random effect. |
| The number of emergency room visits | Baseline through day 90 | A generalized linear mixed model (GLMM) using a log link function will be used to model the number of emergency room visits. Generalized linear mixed Tobit models will be used if the data are found to be zero-inflated. |
| Number of hospital admissions | Baseline through day 90 | A GLMM using a log link function will be used to model the number of emergency room visits. Generalized linear mixed Tobit models will be used if the data are found to be zero-inflated. |
Countries
United States
Outcome results
None listed