Breast CancerAI-ChemoAppNCT07273812
Evaluating an AI-Based Mobile Application for Chemotherapy Support in Breast Cancer Patients
A study testing AI-Based Mobile Application for Personalized Chemotherapy Support in people with Breast Cancer and Breast Neoplasm, run by Dena h. Al-Tameemi at 1 site in Iraq.
Trial summary
The goal of this clinical trial is to learn if an Arabic-language mobile application that uses artificial intelligence (AI) can help women with breast cancer during chemotherapy. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Breast Cancer, Breast Neoplasm, Chemotherapy-Related Toxicities
- What is being tested?
- AI-Based Mobile Application for Personalized Chemotherapy Support
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 130 participants
- Where
- 1 siteIraq
- Study dates
- 1 Jun 2026to 6 Nov 2026
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- Women only
- No healthy volunteers
- Adult, Older adult
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Samer Imad Mohammed, PhD contact
Iraq1 site, 1 recruiting
- Recruiting
Oncology Teaching Hospital-Medical City- Baghdad
Baghdad
Rasha Saer Abbood, F.I.B.M.S med.oncology, 009647813281259, Drrasha85@yahoo.com
About this study
Official title: Evaluating an AI-Based Mobile Application for Chemotherapy Support in Breast Cancer Patients: A Randomized Controlled Trial
The goal of this clinical trial is to learn if an Arabic-language mobile application that uses artificial intelligence (AI) can help women with breast cancer during chemotherapy. The app is designed to give personalized support by reminding participants about their medications, teaching them how to manage treatment side effects, and alerting their healthcare team about serious symptoms.
The main questions this study aims to answer are:
Read more
- Does the AI-based mobile app provide accurate and safe recommendations for the patients?
- Does using the AI-based mobile app help lower treatment-related symptoms and side effects compared to usual care?
- Does the app help participants take their medications more regularly?
- Does it increase participants' understanding and satisfaction with the information they receive about their treatment?
Researchers will compare two groups:
Group 1: Participants who use the AI-based mobile app plus usual oncology care. Group 2: Participants who receive usual care only.
Participants will:
- Use the mobile app daily for 12 weeks while receiving chemotherapy.
- Complete short questionnaires about symptoms, medication use, and quality of life at the start and end of the study.
- Report any problems or feedback about using the app. The AI app is for support and education only. It does not make treatment decisions. All information from the app will be reviewed by oncologists and pharmacists to ensure participant safety.
Read the detailed description
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.
- Conditions
- Breast Cancer, Breast Neoplasm, Chemotherapy-Related Toxicities, Medication Adherence, Quality of Life in Cancer Patients, Accuracy of AI App
- Being tested
- AI-Based Mobile Application for Personalized Chemotherapy Support, Usual Care
- Keywords
- Artificial Intelligence, Mobile Application, digital health, supportive care, chemotherapy, patient education, Symptom Monitoring, Human-in-the-Loop AI, Breast Cancer Chemotherapy, Oncology, Arabic Language App, Pharmacy Iraq, Randomized Controlled Trial
- Medical subject headings
- Breast Neoplasms, Medication Adherence, Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Based Mobile Application for Personalized Chemotherapy SupportBehavioural
Also called AI Breast Cancer Support App, AI-ChemoApp
The intervention is an Arabic-language mobile application powered by artificial intelligence (AI) designed to provide personalized chemotherapy support for women with breast cancer.
The app assists participants by monitoring symptoms, sending medication adherence reminders, and offering educational content on managing side effects and improving treatment understanding.
It uses a conversational interface based on natural language processing (NLP) to communicate with users.
Participants are asked to use the app daily for 12 weeks while receiving chemotherapy.
A human-in-the-loop system ensures oncologists and pharmacists review AI-generated advice for accuracy and safety.
Usual CareOther
Also called ordinary care, standard care
Standard oncology care provided by the hospital team, including chemotherapy administration, routine follow-up, and patient education according to local protocols.
| Study group | Role | What they receive |
|---|---|---|
| AI-Based Mobile Application Plus Usual Care | Experimental | Participants in this group will receive the AI-based mobile application in addition to usual oncology care.
The Arabic-language mobile app uses artificial intelligence (AI) to provide personalized chemotherapy support, including symptom monitoring, medication adherence reminders, and educational guidance.
Participants will use the app daily for 12 weeks during their chemotherapy cycles.
All AI-generated advice is reviewed by oncologists and pharmacists to ensure clinical safety.
They will also receive standard oncology care provided by the hospital team, including chemotherapy administration, routine follow-up, and patient education according to local protocols. Receives: Behavioral: AI-Based Mobile Application for Personalized Chemotherapy Support; Other: Usual Care |
| Usual Care Only | Active comparator | Participants in this group will receive standard oncology care provided by the hospital team, including chemotherapy administration, routine follow-up, and patient education according to local protocols.
They will not have access to the AI-based mobile application. Receives: Other: Usual Care |
What is being measured
The primary outcome is the main question the study is designed to answer.
Change in Symptom Burden and Chemotherapy-Related Toxicities (Arabic PRO-CTCAE)
Symptom burden and treatment-related toxicities will be assessed using the validated Arabic version of the Patient-Reported Outcomes-Common Terminology Criteria for Adverse Events (PRO-CTCAE). Participants will report frequency, severity, and interference of common chemotherapy-related symptoms such as fatigue, nausea, vomiting, pain, and neuropathy. Mean score changes between baseline and 12 weeks will be compared between the AI app group and the usual care group to evaluate whether the intervention lowers symptom burden and improves self-management.Data will be collected at Baseline and weekly thereafter.
Measured: Up to 12 weeks
Medication Adherence Score (Arabic MMAS-8
Medication adherence will be measured using the 8-item Morisky Medication Adherence Scale (MMAS-8) in its validated Arabic version. Participants' self-reported responses generate a score from 0-8, with higher scores indicating better adherence. The mean change in adherence scores from baseline to 12 weeks will be compared between groups to determine the app's effectiveness in promoting medication adherence during chemotherapy.
Measured: Baseline and at weeks 6,12.
Change in Patient Knowledge and Information Satisfaction (EORTC QLQ-INFO25)
The Arabic version of EORTC QLQ-INFO25 questionnaire will assess participants' perception of the adequacy, clarity, and usefulness of information provided about their disease, treatment, and care. The total score ranges from 0 to 100, with higher scores reflecting greater satisfaction with information. The AI-based mobile app is expected to increase knowledge and satisfaction through personalized, accessible education.
Measured: Baseline and at weeks 6,12.
Change in General Quality of Life (EORTC QLQ-C30)
Quality of life (QoL) will be measured using the validated Arabic version of the EORTC QLQ-C30. The EORTC QLQ-C30 is a 30-item questionnaire used to assess the quality of life of cancer patients. It incorporates five functional scales (physical, role, cognitive, emotional, and social), three symptom scales (fatigue, pain, and nausea/vomiting), and a global health status/QoL scale. Raw scores are transformed to a linear scale ranging from 0 to 100.
Functional Scales \& Global Health Status: Higher scores represent a higher/better level of functioning and quality of life.
Symptom Scales: Higher scores represent a higher/worse level of symptomatology.
Measured: Baseline and at weeks 6,12.
Change in Breast Cancer-Specific Quality of Life (EORTC QLQ-BR23)
The Arabic version of EORTC QLQ-BR23 will be used to assess the change in Breast Cancer-Specific Quality of Life.The EORTC QLQ-BR23 is a supplementary module specifically for breast cancer patients. It consists of 23 items covering functional scales (body image, sexual functioning, future perspective) and symptom scales (side effects of systemic therapy, breast symptoms, arm symptoms, hair loss). Raw scores are transformed to a linear scale ranging from 0 to 100.
Functional Scales: Higher scores represent better functioning. Symptom Scales: Higher scores represent worse symptoms.
Measured: Baseline and at weeks 6,12.
Secondary outcomes (4)
Accuracy of AI-Generated Advice Compared with Oncologist Assessment
The accuracy and clinical appropriateness of the AI-generated recommendations will be evaluated by comparing the app's advice logs to oncologist judgments on the same patient-reported scenarios. Agreement will be assessed using Cohen's kappa coefficient to determine the reliability of the AI-based symptom triage.
Measured: Through study completion, an average of 12 weeks.
User Satisfaction and App Usability Score
Participants will evaluate the application using a structured questionnaire assessing multiple domains including ease of use, perceived usefulness, information clarity, and trust in AI recommendations.
Responses are measured on a 5-point Likert scale: 1 = Strongly Disagree 2 = Disagree 3 = Neutral 4 = Agree 5 = Strongly Agree
The final outcome is reported as an aggregate average score across all items. Scale Range: 1 to 5.
Interpretation: Higher scores indicate higher user satisfaction
Measured: At 12 weeks (end of intervention)
App Usage Frequency
Engagement is assessed by monitoring the backend usage logs to determine the average number of distinct application sessions (log-ins) per participant. Unit of Measure: Sessions per week
Measured: Continuously during the 12-week intervention.
Identification of Technical, Ethical, and Implementation Barriers
Qualitative data will be collected through semi-structured interviews to identify challenges related to app usability, privacy concerns, data reliability, and clinical integration. Thematic analysis will be conducted to inform strategies for safe and effective implementation of AI-based supportive care tools in Iraqi oncology settings.
Measured: After 12 weeks of intervention use and upon study completion.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted10 Dec 2025
- Study start1 Jun 2026
- Primary completion6 Aug 2026 (estimated)
- Study completion6 Nov 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Breast CancerStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Enrolment
- 130 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Dena h. Al-Tameemi
- Sponsor type
- University, hospital or other
- Collaborators
- Baghdad Medical City
- Responsible party
- Sponsor-investigator, Dena h. Al-Tameemi, University of Baghdad
- Investigators
- Samer Imad Mohammed, Assistant Prof, Principal investigator, University of Baghdad-College of Pharmacy
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07273812
- Sponsor's protocol ID
- RECAUBCP2192506C
- Acronym
- AI-ChemoApp
- Status last verified
- Nov 2025
- First submitted
- 17 Nov 2025
- Last updated
- 12 Jun 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Yes: Deidentified individual participant data (IPD) that underlie the results reported in published articles will be made available to qualified academic researchers upon reasonable request. Data sharing will occur after publication of the main results and subject to approval by the Research Ethics Committee, College of Pharmacy, University of Baghdad. Data will include coded variables without any identifiers to ensure participant confidentiality.
Publications
Batran RA, Tahoun S, Helmy L, Bahr A, Khalil A, Kamel M, Elsokary M. Breast Cancer in the Middle East and North Africa: Economic Burden, Market Trends, and Care Challenges. JCO Oncol Pract. 2026 May;22(5):769-779. doi: 10.1200/OP-25-00354. Epub 2025 Jul 16.
PubMed 40669034Anber ZNH, Saleh BOM, Al-Rawi SA. The cardiotoxicity effect of different chemotherapeutic regimens in Iraqi patients with breast cancer: A follow up study. Heliyon. 2019 Aug 1;5(8):e02194. doi: 10.1016/j.heliyon.2019.e02194. eCollection 2019 Aug.
PubMed 31406940Suhail M, Saulat F, Khurram H, Fatima F, Zenab A, Wasim M, Sadia NU, Afzaal F, Latif H, Nasrullah M. Knowledge, Attitude and Practice Related to Chemotherapy Among Cancer Patients. Inquiry. 2024 Jan-Dec;61:469580241246460. doi: 10.1177/00469580241246460.
PubMed 38616652Yelne S, Chaudhary M, Dod K, Sayyad A, Sharma R. Harnessing the Power of AI: A Comprehensive Review of Its Impact and Challenges in Nursing Science and Healthcare. Cureus. 2023 Nov 22;15(11):e49252. doi: 10.7759/cureus.49252. eCollection 2023 Nov.
PubMed 38143615Shaban M, Osman YM, Mohamed NA, Shaban MM. Empowering breast cancer clients through AI chatbots: transforming knowledge and attitudes for enhanced nursing care. BMC Nurs. 2025 Jul 29;24(1):994. doi: 10.1186/s12912-025-03585-w.
PubMed 40731340
Study at a glance
From the registry record, last updated by the sponsor on 12 Jun 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Evaluating an AI-Based Mobile Application for Chemotherapy Support in Breast Cancer Patients: A Randomized Controlled Trial
- ClinicalTrials.gov ID
- NCT07273812
- Acronym / sponsor ID
- AI-ChemoApp / RECAUBCP2192506C
- Conditions
- Breast Cancer, Breast Neoplasm, Chemotherapy-Related Toxicities, Medication Adherence, Quality of Life in Cancer Patients, Accuracy of AI App
- Keywords
- Artificial Intelligence, Mobile Application, digital health, supportive care, chemotherapy, patient education, Symptom Monitoring, Human-in-the-Loop AI
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 130 participants (estimated)
- Lead sponsor
- Dena h. Al-TameemiUniversity, hospital or other
- Collaborators
- Baghdad Medical City
- Study start
- 1 Jun 2026 (actual)
- Primary completion
- 6 Aug 2026 (estimated)
- Study completion
- 6 Nov 2026 (estimated)
- First posted
- 10 Dec 2025 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The goal of this clinical trial is to learn if an Arabic-language mobile application that uses artificial intelligence (AI) can help women with breast cancer during chemotherapy. The app is designed to give personalized support by reminding participants about their medications, teaching them how to manage treatment side effects, and alerting their healthcare team about serious symptoms.
The main questions this study aims to answer are:
- Does the AI-based mobile app provide accurate and safe recommendations for the patients?
- Does using the AI-based mobile app help lower treatment-related symptoms and side effects compared to usual care?
- Does the app help participants take their medications more regularly?
- Does it increase participants' understanding and satisfaction with the information they receive about their treatment?
Researchers will compare two groups:
Group 1: Participants who use the AI-based mobile app plus usual oncology care. Group 2: Participants who receive usual care only.
Participants will:
- Use the mobile app daily for 12 weeks while receiving chemotherapy.
- Complete short questionnaires about symptoms, medication use, and quality of life at the start and end of the study.
- Report any problems or feedback about using the app. The AI app is for support and education only. It does not make treatment decisions. All information from the app will be reviewed by oncologists and pharmacists to ensure participant safety.
Detailed description
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.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-Based Mobile Application Plus Usual Care | Experimental | Behavioral: AI-Based Mobile Application for Personalized Chemotherapy Support, Other: Usual CareParticipants in this group will receive the AI-based mobile application in addition to usual oncology care. The Arabic-language mobile app uses artificial intelligence (AI) to provide personalized chemotherapy support, including symptom monitoring, medication adherence reminders, and educational guidance. Participants will use the app daily for 12 weeks during their chemotherapy cycles. All AI-generated advice is reviewed by oncologists and pharmacists to ensure clinical safety. They will also receive standard oncology care provided by the hospital team, including chemotherapy administration, routine follow-up, and patient education according to local protocols. |
| Usual Care Only | Active comparator | Other: Usual CareParticipants in this group will receive standard oncology care provided by the hospital team, including chemotherapy administration, routine follow-up, and patient education according to local protocols. They will not have access to the AI-based mobile application. |
Who may qualify
- Ages
- 18 years and older
- Sex
- Female only
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
Key inclusion criteria (7 listed)
- 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).
Key exclusion criteria (6 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-Based Mobile Application for Personalized Chemotherapy SupportAlso: AI Breast Cancer Support App, AI-ChemoAppThe intervention is an Arabic-language mobile application powered by artificial intelligence (AI) designed to provide personalized chemotherapy support for women with breast cancer. The app assists participants by monitoring symptoms, sending medication adherence reminders, and offering educational content on managing side effects and improving treatment understanding. It uses a conversational interface based on natural language processing (NLP) to communicate with users. Participants are asked to use the app daily for 12 weeks while receiving chemotherapy. A human-in-the-loop system ensures oncologists and pharmacists review AI-generated advice for accuracy and safety. | Behavioural | AI-Based Mobile Application Plus Usual Care |
| Usual CareAlso: ordinary care, standard careStandard oncology care provided by the hospital team, including chemotherapy administration, routine follow-up, and patient education according to local protocols. | Other | AI-Based Mobile Application Plus Usual Care, Usual Care Only |
Primary outcome
Change in Symptom Burden and Chemotherapy-Related Toxicities (Arabic PRO-CTCAE)
Time frame: Up to 12 weeks
Symptom burden and treatment-related toxicities will be assessed using the validated Arabic version of the Patient-Reported Outcomes-Common Terminology Criteria for Adverse Events (PRO-CTCAE). Participants will report frequency, severity, and interference of common chemotherapy-related symptoms such as fatigue, nausea, vomiting, pain, and neuropathy. Mean score changes between baseline and 12 weeks will be compared between the AI app group and the usual care group to evaluate whether the intervention lowers symptom burden and improves self-management.Data will be collected at Baseline and weekly thereafter.
Medication Adherence Score (Arabic MMAS-8
Time frame: Baseline and at weeks 6,12.
Medication adherence will be measured using the 8-item Morisky Medication Adherence Scale (MMAS-8) in its validated Arabic version. Participants' self-reported responses generate a score from 0-8, with higher scores indicating better adherence. The mean change in adherence scores from baseline to 12 weeks will be compared between groups to determine the app's effectiveness in promoting medication adherence during chemotherapy.
Change in Patient Knowledge and Information Satisfaction (EORTC QLQ-INFO25)
Time frame: Baseline and at weeks 6,12.
The Arabic version of EORTC QLQ-INFO25 questionnaire will assess participants' perception of the adequacy, clarity, and usefulness of information provided about their disease, treatment, and care. The total score ranges from 0 to 100, with higher scores reflecting greater satisfaction with information. The AI-based mobile app is expected to increase knowledge and satisfaction through personalized, accessible education.
Change in General Quality of Life (EORTC QLQ-C30)
Time frame: Baseline and at weeks 6,12.
Quality of life (QoL) will be measured using the validated Arabic version of the EORTC QLQ-C30. The EORTC QLQ-C30 is a 30-item questionnaire used to assess the quality of life of cancer patients. It incorporates five functional scales (physical, role, cognitive, emotional, and social), three symptom scales (fatigue, pain, and nausea/vomiting), and a global health status/QoL scale. Raw scores are transformed to a linear scale ranging from 0 to 100. Functional Scales \& Global Health Status: Higher scores represent a higher/better level of functioning and quality of life. Symptom Scales: Higher scores represent a higher/worse level of symptomatology.
Change in Breast Cancer-Specific Quality of Life (EORTC QLQ-BR23)
Time frame: Baseline and at weeks 6,12.
The Arabic version of EORTC QLQ-BR23 will be used to assess the change in Breast Cancer-Specific Quality of Life.The EORTC QLQ-BR23 is a supplementary module specifically for breast cancer patients. It consists of 23 items covering functional scales (body image, sexual functioning, future perspective) and symptom scales (side effects of systemic therapy, breast symptoms, arm symptoms, hair loss). Raw scores are transformed to a linear scale ranging from 0 to 100. Functional Scales: Higher scores represent better functioning. Symptom Scales: Higher scores represent worse symptoms.
4 secondary outcomes
Accuracy of AI-Generated Advice Compared with Oncologist Assessment
Time frame: Through study completion, an average of 12 weeks.
User Satisfaction and App Usability Score
Time frame: At 12 weeks (end of intervention)
App Usage Frequency
Time frame: Continuously during the 12-week intervention.
Identification of Technical, Ethical, and Implementation Barriers
Time frame: After 12 weeks of intervention use and upon study completion.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 12 Jun 2026.
- Background: PubMed 40669034Batran RA, Tahoun S, Helmy L, Bahr A, Khalil A, Kamel M, Elsokary M. Breast Cancer in the Middle East and North Africa: Economic Burden, Market Trends, and Care Challenges. JCO Oncol Pract. 2026 May;22(5):769-779. doi: 10.1200/OP-25-00354. Epub 2025 Jul 16.
- Background: PubMed 31406940Anber ZNH, Saleh BOM, Al-Rawi SA. The cardiotoxicity effect of different chemotherapeutic regimens in Iraqi patients with breast cancer: A follow up study. Heliyon. 2019 Aug 1;5(8):e02194. doi: 10.1016/j.heliyon.2019.e02194. eCollection 2019 Aug.
- Background: PubMed 38616652Suhail M, Saulat F, Khurram H, Fatima F, Zenab A, Wasim M, Sadia NU, Afzaal F, Latif H, Nasrullah M. Knowledge, Attitude and Practice Related to Chemotherapy Among Cancer Patients. Inquiry. 2024 Jan-Dec;61:469580241246460. doi: 10.1177/00469580241246460.
- Background: PubMed 38143615Yelne S, Chaudhary M, Dod K, Sayyad A, Sharma R. Harnessing the Power of AI: A Comprehensive Review of Its Impact and Challenges in Nursing Science and Healthcare. Cureus. 2023 Nov 22;15(11):e49252. doi: 10.7759/cureus.49252. eCollection 2023 Nov.
- Background: PubMed 40731340Shaban M, Osman YM, Mohamed NA, Shaban MM. Empowering breast cancer clients through AI chatbots: transforming knowledge and attitudes for enhanced nursing care. BMC Nurs. 2025 Jul 29;24(1):994. doi: 10.1186/s12912-025-03585-w.
- College of Pharmacy, University of Baghdad - Academic sponsorLink provided by the sponsor.
- Oncology Teaching Hospital, Baghdad - Study locationLink provided by the sponsor.
- National Cancer Institute - Breast Cancer OverviewLink provided by the sponsor.
- National Cancer Comprehensive Network- Treatment GuidelinesLink provided by the sponsor.
- Individual participant dataSharing planned: Yes. Deidentified individual participant data (IPD) that underlie the results reported in published articles will be made available to qualified academic researchers upon reasonable request. Data sharing will occur after publication of the main results and subject to approval by the Research Ethics Committee, College of Pharmacy, University of Baghdad. Data will include coded variables without any identifiers to ensure participant confidentiality.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Samer Imad Mohammed, PhD contact
Samer Imad Mohammed, Assistant Prof principal investigator
University of Baghdad-College of Pharmacy
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-Based Mobile Application for Personalized Chemotherapy Support in people with Breast Cancer and Breast Neoplasm, run by Dena h. Al-Tameemi at 1 site in Iraq.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 7 inclusion and 6 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 12 Jun 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Iraq. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Dena A. Al-Tameemi, MSc. (+9647901572647, dina.abbas2400p@copharm.uobaghdad.edu.iq), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Change in Symptom Burden and Chemotherapy-Related Toxicities (Arabic PRO-CTCAE) (time frame: Up to 12 weeks). The study lists 5 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07273812, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 12 Jun 2026.