Evaluating an AI-Based Mobile Application for Chemotherapy Support in Breast Cancer Patients

Despite advances in oncology care, breast cancer patients in Iraq face significant challenges regarding medication adherence and symptom management during the inter-cycle chemotherapy periods. This randomized controlled trial aims to bridge this gap by evaluating the efficacy, safety, and feasibility of a specialized, Arabic-language Artificial Intelligence (AI) mobile application.

Current standard care in the local setting often relies on episodic clinic visits, leaving patients without real-time support for side effects experienced at home. This study hypothesizes that a continuous, AI-driven digital intervention can reduce symptom burden and improve adherence to chemotherapy and supportive care medications (e.g., antiemetics) compared to standard care alone. The application utilizes Natural Language Processing (NLP) to provide conversational support tailored specifically to the cultural and linguistic context of Iraqi patients.

The intervention integrates a "Human-in-the-loop" safety model to ensure clinical accuracy. The AI algorithms are trained on clinical practice guidelines adapted for the local formulary.

Symptom Triage Logic: The app utilizes an algorithm based on the CTCAE grading system. Low-grade symptoms trigger self-care advice (e.g., hydration, dietary changes), while high-grade symptoms trigger immediate alerts to the patient to seek care and a notification to the study investigators.

Adherence Algorithms: Unlike static alarms, the notification system adapts to the specific chemotherapy cycle (e.g., AC or Taxane-based regimens) to remind patients of specific supportive medications required on specific days.

Control Group Specification (Standard of Care) Participants randomized to the control arm will receive the institutional standard of care. This includes routine oncologist consultations, standard written or verbal discharge instructions regarding chemotherapy side effects, and pharmacy dispensing counseling. They will not have access to the interactive AI features but will undergo the same schedule of outcome assessments to ensure rigorous comparison.

This study represents the first empirical effort to integrate AI-driven digital health tools into the public oncology sector in Iraq. It aims to validate whether automated, algorithmic triage is a feasible addition to the healthcare infrastructure in low-resource settings.

Inclusion criteria

• Confirmed diagnosis of breast cancer stages I, II, or III.
• Patients must be currently scheduled to initiate their first-ever cycle of chemotherapy.
• Age 18 years or older.
• Ability to understand and provide informed consent.
• Possession of a smartphone (Android or iOS) and functional digital literacy, defined as the ability to independently navigate mobile applications, read on-screen text in Arabic, and input daily health data. (for the intervention group).
• Willingness to comply with study procedures and follow-up schedules.
• Ability to communicate in Arabic, as the mobile application and chatbot will be developed in Arabic.

Exclusion criteria

• Patients with Stage IV (Metastatic) breast cancer.
• Patients receiving concurrent hormonal therapy during the chemotherapy phase, to isolate chemotherapy-induced adverse events.

Patients with cognitive impairment or severe psychiatric disorders that would preclude effective interaction with the mobile application or questionnaire completion.

• Patients receiving palliative care where symptom management is the sole focus and active chemotherapy is not being administered with curative or life prolonging intent.
• Patients participating in other interventional clinical trials that might confound the outcomes of this study.
• Patients with severe comorbidities that could significantly impact their ability to participate or bias outcome measures.