Mobile Intervention to Improve Adherence of Oral Anti-cancer Medications Among Acute Myeloid Leukemia Patients, the txt4AML Study

Mobile Intervention to Improve Adherence of Oral Anti-cancer Medications Among Acute Myeloid Leukemia Patients, the txt4AML Study

txt4AML: An Innovative Mobile Intervention to Improve Oral Anti-Cancer Medications Among Acute Myeloid Leukemia Patients

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.

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.

Patients receive interactive text messages to help with adherence to medications and a smart pill bottle with medication reminders on study.

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.

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.

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

Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence.

MD Anderson Symptom Inventory for acute myeloid leukemia/myelodysplastic syndrome (MDASI)-(AML)/MDS survey response

Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence.

MD Anderson Symptom Inventory for acute myeloid leukemia/myelodysplastic syndrome (MDASI)-(AML)/MDS survey response

Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence.

Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence

Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence.

Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence.

Will be analyzed using univariable logistic regression models with the primary predictor of averaged daily real-time OAM medication adherence.

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)