Acute Myeloid Leukemia
Conditions
Brief summary
This clinical trial studies how well a mobile intervention consisting of a text messaging program and an electronic smart pill bottle with medication reminders works to improve adherence to oral anti-cancer medications among patients with acute myeloid leukemia (AML). Medication adherence is how well patients take medications as prescribed by their doctors, and good medical adherence is when patients take medications correctly. Poor medication adherence has been shown to be a barrier to effective treatment. Collecting feedback on patient experiences using the mobile intervention may help doctors design new methods and material for providing educational information to AML patients who are taking oral anti-cancer medications.
Detailed description
PRIMARY OBJECTIVE: I. To examine the feasibility, acceptability and preliminary efficacy of txt4AML in a pilot single arm study. SECONDARY OBJECTIVE: I. To explore the association between overall treatment responses and real-time oral anti-cancer medication (OAM) adherence. EXPLORATORY OBJECTIVE: I. To summarize and assess other patient-reported outcomes, collected either as patient chart review or through self-reported survey, as well as the patient post-intervention interviews. OUTLINE: Patients receive interactive text messages to help with adherence to medications and a smart pill bottle with medication reminders on study.
Interventions
Receive interactive text messaging.
Receive medication reminders via smart pill bottle
OTHERSurvey Administration
Ancillary studies
OTHERQuality-of-Life Assessment
Ancillary studies
Sponsors
Thomas Jefferson University
Study design
Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
HEALTH_SERVICES_RESEARCH
Masking
NONE
Eligibility
Sex/Gender
ALL
Age
18 Years to No maximum
Healthy volunteers
No
Inclusion criteria
* Patients diagnosed with acute myeloid leukemia (AML) * Patients will be or is taking venetoclax (or any other oral anticancer medication) as part of their first line therapy * Has a phone with text capabilities * Among patients aged 18 and older we will enroll participants regardless of race or ethnicity
Exclusion criteria
* Individuals who are terminally ill (defined as having less than 2 months to live) * Individuals for whom there is documentation of inability to provide consent in the medical record * Do not speak/read English * This study will exclude pediatric patients (defined as individuals under age 18 years)
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Real-time oral anticancer medication (OAM) medication adherence | At baseline | Will be measured daily by AdhereTech wireless smart pill bottles, which are Health Insurance Portability and Accountability Act (HIPAA)-compliant Food and Drug Administration (FDA) Class I medical devices that monitor electronic tracking of bottle and percent of pills detected inside the bottle. Will be summarized using proportions and 95% Clopper-Pearson exact confidence intervals. |
| MD Anderson Symptom Inventory for acute myeloid leukemia/myelodysplastic syndrome (MDASI)-(AML)/MDS survey response | At baseline | Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Complete remission (CR) | At baseline, 1, and 2 months | Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence |
| Incomplete blood count recovery (Cri) | At baseline, 1, and 2 months | Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence. |
| Partial remissions (PR) | At baseline, 1, and 2 months | Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence. |
| Morphologic leukemia-free state (MLFS) | At baseline, 1, and 2 months | Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence. |
Countries
United States
Outcome results
None listed