Breast CancerNCT07826338
Artificial Intelligence-supported Mobile Application for Patients With Breast Cancer
A study testing AI-Supported Mobile Application in people with Breast Cancer and Chemotherapy Side Effects, run by Ege University at 1 site in Turkey (Türkiye).
Trial summary
This randomized controlled clinical trial aims to evaluate the effects of an artificial intelligence-supported mobile application on symptom management, self-efficacy, and quality of life in breast cancer patients receiving chemotherapy. Read more about this study
- Who is it for?
- Ages 18 years and older, women only
- Conditions the study is for
- Breast Cancer, Chemotherapy Side Effects
- What is being tested?
- AI-Supported Mobile Application
- Type of treatment
- Lifestyle or therapy programme
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 70 participants
- Where
- 1 siteTurkey (Türkiye)
- Study dates
- 22 Jun 2026to 31 Oct 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
- Female patients aged 18 years and older.
- Diagnosed with breast cancer.
- Patients with Stage 0, I, II, or III breast cancer.
- Receiving chemotherapy for the first time.
- Eastern Cooperative Oncology Group (ECOG) Performance Status score of 0 or 1.
- In a stable physical and psychological condition that does not interfere with participation in the study.
Show all 9Show fewer
- Able to read and write in Turkish.
- Own a smartphone and have sufficient technological skills to use the mobile application.
- Willing to participate in the study and able to provide written informed consent.
Who cannot join
- Patients diagnosed with a primary cancer other than breast cancer.
- Patients with severe comorbid diseases.
- Patients receiving concurrent radiotherapy.
- Patients diagnosed with inflammatory breast cancer.
- Patients using luteinizing hormone-releasing hormone (LHRH) analogs.
- Patients with severe cognitive impairment or psychiatric disorders.
- Patients who do not have access to a mobile device or internet connection.
- Patients who do not have the skills necessary to use the mobile application.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
Turkey (Türkiye)1 site, 1 recruiting
- Recruiting
Ege University Hospital, Berna Türek Chemotherapy Center
Izmir, İzmir, 35100+
Yasemin Yıldırım, Prof. Dr., +00905057516663, yasemin.kyildirim@ege.edu.tr
Gökhan Sezgin, PhD Candidate
About this study
Official title: Effects of an Artificial Intelligence-supported Mobile Application on Symptom Management, Self-efficacy, and Quality of Life in Patients With Breast Cancer
This randomized controlled clinical trial aims to evaluate the effects of an artificial intelligence-supported mobile application on symptom management, self-efficacy, and quality of life in breast cancer patients receiving chemotherapy. The study will be conducted between June 2026 and December 2026 at the Ege University Hospital Berna Türek Chemotherapy Center and the İzmir City Hospital Chemotherapy Center. Seventy breast cancer patients who will receive chemotherapy for the first time will be randomly assigned to either an intervention group using the mobile application or a control group receiving standard care. The study seeks to answer the following key questions: Does the artificial intelligence-supported mobile application improve symptom management? Does use of the application increase patients' self-efficacy? Does the application improve quality of life compared with standard care? Participants in the intervention group will use the mobile application during chemotherapy, report daily symptoms, and receive personalized symptom-management recommendations generated by an artificial intelligence system trained by the research team. Participants in both groups will complete symptom, self-efficacy, and quality-of-life assessments at baseline, after the first chemotherapy cycle (cycle length varies by chemotherapy protocol; all cycles are defined according to each patient's prescribed treatment regimen), and after the fourth cycle. The control group will receive standard care and complete the same assessments through face-to-face visits. This study is designed to assess the effectiveness of artificial intelligence-supported mobile health interventions in breast cancer care and their potential to improve symptom management, self-efficacy, and quality of life.
Read the detailed description
Breast cancer is the most commonly diagnosed cancer worldwide and remains the leading cause of cancer-related mortality among women. Despite advances in diagnosis and treatment, patients undergoing chemotherapy frequently experience a wide range of physical and psychological symptoms, including fatigue, nausea, vomiting, pain, sleep disturbances, anxiety, depression, and impaired body image. These symptoms may negatively affect treatment adherence, self-management abilities, and health-related quality of life. Inadequately managed symptoms can also lead to treatment delays, dose reductions, emergency department visits, and hospitalizations. Effective symptom management is therefore a critical component of breast cancer care. Self-efficacy, defined as an individual's belief in their ability to successfully perform behaviors required to achieve desired outcomes, plays an important role in symptom management and adaptation to cancer treatment. Higher levels of self-efficacy have been associated with better symptom control, improved psychological well-being, enhanced patient-provider communication, and greater treatment adherence. In addition, maintaining and improving quality of life has become a major goal of contemporary cancer care. Mobile health technologies have emerged as promising tools for supporting symptom monitoring and self-management among cancer patients. Previous studies have demonstrated that electronic patient-reported outcome systems can facilitate timely symptom reporting, reduce symptom burden, improve quality of life, and potentially enhance survival outcomes. However, many existing mobile applications for breast cancer patients focus on limited aspects of care and do not comprehensively address the broad range of symptoms experienced during chemotherapy. Artificial intelligence has the potential to enhance mobile health interventions by providing personalized, real-time recommendations based on patient-reported data. Artificial intelligence-supported systems can analyze symptom reports, identify symptom severity, and deliver tailored guidance to support symptom self-management. Such personalized interventions may increase patient engagement, improve symptom control, strengthen self-efficacy, and ultimately enhance quality of life. The purpose of this randomized controlled trial is to evaluate the effects of an artificial intelligence-supported mobile application on symptom management, self-efficacy, and quality of life among breast cancer patients receiving chemotherapy for the first time. The study will be conducted between June 2026 and December 2026 at the Berna Türek Chemotherapy Center of Ege University Hospital and the Chemotherapy Center of İzmir City Hospital. A total of 70 breast cancer patients who meet the eligibility criteria will be enrolled and randomly assigned to either an intervention group (n=35) or a control group (n=35). Participants in the intervention group will download and use an artificial intelligence-supported mobile application on their Android smartphones on the first day of chemotherapy. Following chemotherapy initiation, participants will report their symptoms daily through the application. Based on symptom severity and patient-reported information, the artificial intelligence component of the application will provide individualized symptom-management recommendations developed according to evidence-based practices and supervised by the research team. Participants will also have access to educational content regarding breast cancer and its treatment through the application. Participants in the control group will receive standard care routinely provided by the treatment centers. Outcome assessments will be conducted at baseline (first chemotherapy day), at the end of the first chemotherapy cycle (cycle length varies by chemotherapy protocol; all cycles are defined according to each patient's prescribed treatment regimen), and at the end of the fourth chemotherapy cycle. Data will be collected using the patient identification form, the memorial symptom assessment scale (MSAS), the chemotherapy symptom management self-efficacy scale for breast cancer patients, the european organisation for research and treatment of cancer quality of life questionnaire core 30 (EORTC QLQ-C30 version 3.0), and the breast cancer-specific module (EORTC QLQ-BR23). All data will be collected by the same researcher. The primary hypothesis is that patients using the artificial intelligence-supported mobile application will demonstrate better symptom management, higher self-efficacy levels, and improved quality of life compared with patients receiving standard care alone. Findings from this study may contribute to the growing evidence regarding the integration of artificial intelligence and mobile health technologies into supportive cancer care and provide guidance for future digital health interventions targeting symptom management in breast cancer patients.
- Conditions
- Breast Cancer, Chemotherapy Side Effects
- Being tested
- AI-Supported Mobile Application
- Keywords
- breast cancer, artificial intelligence, mobile health, Symptom Management, Self-Efficacy, Quality of Life
- Medical subject headings
- Breast Neoplasms
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-Supported Mobile ApplicationBehavioural
Participants will use an AI-supported mobile application starting on the first day of chemotherapy. The application allows daily symptom reporting, provides AI-based personalized symptom management recommendations, and includes educational information about breast cancer and its treatment.
| Study group | Role | What they receive |
|---|---|---|
| AI-Supported Mobile Application + Standard Care | Experimental | Breast cancer patients receiving first-time chemotherapy will use an AI-supported mobile application in addition to standard care. Participants will report daily symptoms through the application and receive personalized AI-generated symptom management recommendations and educational content. Receives: Behavioral: AI-Supported Mobile Application |
| Standard Care | No intervention | Participants will receive routine standard care provided by the chemotherapy centers without access to the mobile application. |
What is being measured
The primary outcome is the main question the study is designed to answer.
Symptom burden
Symptom burden will be assessed using the Memorial Symptom Assessment Scale (MSAS). The scale comprises a total of 32 symptoms, which are evaluated in terms of frequency, severity, and distress. On the Memorial Symptom Assessment Scale, each symptom is examined for presence or absence. If a symptom is present, it is rated as follows: for frequency: 1 (rarely), 2 (occasionally), 3 (frequently), 4 (almost constantly); for severity: 1 (mild), 2 (moderate), 3 (severe), 4 (very severe); for distress: 0 (not at all), 1 (a little bit), 2 (somewhat), 3 (quite a bit), 4 (very much). Higher scores on the Memorial Symptom Assessment Scale indicate greater frequency, severity, and distress of the experienced symptoms.
Measured: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)
Chemotherapy symptom management self-efficacy
Self-efficacy will be measured using the Chemotherapy Symptom Management Self-Efficacy Scale for Breast Cancer Patients. The scale consists of 27 items and three subdimensions. Each item is rated on a 0-10 Likert scale (0 = not confident at all, 10 = very confident). The total score ranges from 0 to 270. Higher scores indicate better self-efficacy (greater confidence in managing chemotherapy-related symptoms).
Measured: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)
Quality of Life (EORTC QLQ-C30)
Quality of life will be evaluated using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30 Version 3.0). The scale contains 30 items assessing functional scales (physical, role, cognitive, emotional, social), symptom scales (fatigue, pain, nausea/vomiting, dyspnea, insomnia, appetite loss, constipation, diarrhea, financial difficulties), and global health status. All scores are transformed to a 0-100 range. Higher scores on global health status and functional scales indicate better quality of life, while higher scores on symptom scales indicate worse quality of life.
Measured: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)
Quality of Life (EORTC QLQ-BR23)
Quality of life will be evaluated using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Breast Cancer Module 23 (EORTC QLQ-BR23). The scale contains 23 items assessing breast cancer-specific functional domains (body image, sexual functioning, sexual enjoyment, future perspective) and symptom domains (systemic therapy side effects, breast symptoms, arm symptoms, hair loss). All scores are transformed to a 0-100 range. Higher scores on functional scales indicate better quality of life, while higher scores on symptom scales indicate worse quality of life.
Measured: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Sep 2026
- Study start22 Jun 2026
- Primary completion22 Oct 2026 (estimated)
- Study completion31 Oct 2026 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (7)Papers the sponsor has linked to this study.
- Other trials for Breast CancerStudies of the same condition, open and under way.
- More trials run by Ege UniversityThe sponsor's other registered studies.
- 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
- 70 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Ege University
- Sponsor type
- University, hospital or other
- Collaborators
- Health Institutes of Turkey
- Responsible party
- Principal investigator, Gökhan SEZGİN, Ege University
- Investigators
- Yasemin Yıldırım, Prof. Dr., Principal investigator, Ege University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07826338
- Sponsor's protocol ID
- 25-6T/63
- Other IDs
- 48671
- Status last verified
- Sep 2026
- First submitted
- 10 Jun 2026
- Last updated
- 17 Sep 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Individual participant data will not be shared because this study does not include a data-sharing plan approved by the ethics committee, and participants did not provide consent for public data sharing. To ensure confidentiality and protect participant privacy, de-identified individual-level data will remain with the research team only.
Publications
Fjell M, Langius-Eklof A, Nilsson M, Wengstrom Y, Sundberg K. Reduced symptom burden with the support of an interactive app during neoadjuvant chemotherapy for breast cancer - A randomized controlled trial. Breast. 2020 Jun;51:85-93. doi: 10.1016/j.breast.2020.03.004. Epub 2020 Mar 20.
PubMed 32247251Grasic Kuhar C, Gortnar Cepeda T, Kovac T, Kukar M, Ruzic Gorenjec N. Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study. JMIR Mhealth Uhealth. 2020 Aug 4;8(8):e17408. doi: 10.2196/17408.
PubMed 32427567Baik SH, Oswald LB, Buitrago D, Buscemi J, Iacobelli F, Perez-Tamayo A, Guitelman J, Diaz A, Penedo FJ, Yanez B. Cancer-Relevant Self-Efficacy Is Related to Better Health-Related Quality of Life and Lower Cancer-Specific Distress and Symptom Burden Among Latina Breast Cancer Survivors. Int J Behav Med. 2020 Aug;27(4):357-365. doi: 10.1007/s12529-020-09890-9.
PubMed 32394220Jiang L, Xu J, Wu Y, Liu Y, Wang X, Hu Y. Effects of the "AI-TA" Mobile App With Intelligent Design on Psychological and Related Symptoms of Young Survivors of Breast Cancer: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2024 Jun 4;12:e50783. doi: 10.2196/50783.
PubMed 38833298Seven M, Pasalak S, Bagcivan G, Ozkasap O, Selcukbirick F. A Mobile Application for Symptom Management in Patients With Breast Cancer. Oncol Nurs Forum. 2022 Aug 18;49(5):409-420. doi: 10.1188/22.ONF.409-420.
PubMed 36067241El-Amir A, El-Baiomy EM, Sabry NA, Kassem L, Chesney MA, Wallston KA. The relationship between coping self-efficacy and B cells in breast cancer patients. J Egypt Natl Canc Inst. 2023 Sep 4;35(1):28. doi: 10.1186/s43046-023-00187-y.
PubMed 37661196Balci H, Faydali S. The Effect of Education Performed Using Mobile Application on Supportive Care Needs and Quality of Life in Women with Breast Cancer: Randomized Controlled Trial. Semin Oncol Nurs. 2024 Aug;40(4):151684. doi: 10.1016/j.soncn.2024.151684. Epub 2024 Jul 4.
PubMed 38969573
Study at a glance
From the registry record, last updated by the sponsor on 17 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Effects of an Artificial Intelligence-supported Mobile Application on Symptom Management, Self-efficacy, and Quality of Life in Patients With Breast Cancer
- ClinicalTrials.gov ID
- NCT07826338
- Acronym / sponsor ID
- 25-6T/63
- Conditions
- Breast Cancer, Chemotherapy Side Effects
- Keywords
- breast cancer, artificial intelligence, mobile health, Symptom Management, Self-Efficacy, Quality of Life
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 70 participants (estimated)
- Lead sponsor
- Ege UniversityUniversity, hospital or other
- Collaborators
- Health Institutes of Turkey
- Study start
- 22 Jun 2026 (actual)
- Primary completion
- 22 Oct 2026 (estimated)
- Study completion
- 31 Oct 2026 (estimated)
- First posted
- 17 Sep 2026 (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.
This randomized controlled clinical trial aims to evaluate the effects of an artificial intelligence-supported mobile application on symptom management, self-efficacy, and quality of life in breast cancer patients receiving chemotherapy. The study will be conducted between June 2026 and December 2026 at the Ege University Hospital Berna Türek Chemotherapy Center and the İzmir City Hospital Chemotherapy Center. Seventy breast cancer patients who will receive chemotherapy for the first time will be randomly assigned to either an intervention group using the mobile application or a control group receiving standard care. The study seeks to answer the following key questions: Does the artificial intelligence-supported mobile application improve symptom management? Does use of the application increase patients' self-efficacy? Does the application improve quality of life compared with standard care? Participants in the intervention group will use the mobile application during chemotherapy, report daily symptoms, and receive personalized symptom-management recommendations generated by an artificial intelligence system trained by the research team. Participants in both groups will complete symptom, self-efficacy, and quality-of-life assessments at baseline, after the first chemotherapy cycle (cycle length varies by chemotherapy protocol; all cycles are defined according to each patient's prescribed treatment regimen), and after the fourth cycle. The control group will receive standard care and complete the same assessments through face-to-face visits. This study is designed to assess the effectiveness of artificial intelligence-supported mobile health interventions in breast cancer care and their potential to improve symptom management, self-efficacy, and quality of life.
Detailed description
Breast cancer is the most commonly diagnosed cancer worldwide and remains the leading cause of cancer-related mortality among women. Despite advances in diagnosis and treatment, patients undergoing chemotherapy frequently experience a wide range of physical and psychological symptoms, including fatigue, nausea, vomiting, pain, sleep disturbances, anxiety, depression, and impaired body image. These symptoms may negatively affect treatment adherence, self-management abilities, and health-related quality of life. Inadequately managed symptoms can also lead to treatment delays, dose reductions, emergency department visits, and hospitalizations. Effective symptom management is therefore a critical component of breast cancer care. Self-efficacy, defined as an individual's belief in their ability to successfully perform behaviors required to achieve desired outcomes, plays an important role in symptom management and adaptation to cancer treatment. Higher levels of self-efficacy have been associated with better symptom control, improved psychological well-being, enhanced patient-provider communication, and greater treatment adherence. In addition, maintaining and improving quality of life has become a major goal of contemporary cancer care. Mobile health technologies have emerged as promising tools for supporting symptom monitoring and self-management among cancer patients. Previous studies have demonstrated that electronic patient-reported outcome systems can facilitate timely symptom reporting, reduce symptom burden, improve quality of life, and potentially enhance survival outcomes. However, many existing mobile applications for breast cancer patients focus on limited aspects of care and do not comprehensively address the broad range of symptoms experienced during chemotherapy. Artificial intelligence has the potential to enhance mobile health interventions by providing personalized, real-time recommendations based on patient-reported data. Artificial intelligence-supported systems can analyze symptom reports, identify symptom severity, and deliver tailored guidance to support symptom self-management. Such personalized interventions may increase patient engagement, improve symptom control, strengthen self-efficacy, and ultimately enhance quality of life. The purpose of this randomized controlled trial is to evaluate the effects of an artificial intelligence-supported mobile application on symptom management, self-efficacy, and quality of life among breast cancer patients receiving chemotherapy for the first time. The study will be conducted between June 2026 and December 2026 at the Berna Türek Chemotherapy Center of Ege University Hospital and the Chemotherapy Center of İzmir City Hospital. A total of 70 breast cancer patients who meet the eligibility criteria will be enrolled and randomly assigned to either an intervention group (n=35) or a control group (n=35). Participants in the intervention group will download and use an artificial intelligence-supported mobile application on their Android smartphones on the first day of chemotherapy. Following chemotherapy initiation, participants will report their symptoms daily through the application. Based on symptom severity and patient-reported information, the artificial intelligence component of the application will provide individualized symptom-management recommendations developed according to evidence-based practices and supervised by the research team. Participants will also have access to educational content regarding breast cancer and its treatment through the application. Participants in the control group will receive standard care routinely provided by the treatment centers. Outcome assessments will be conducted at baseline (first chemotherapy day), at the end of the first chemotherapy cycle (cycle length varies by chemotherapy protocol; all cycles are defined according to each patient's prescribed treatment regimen), and at the end of the fourth chemotherapy cycle. Data will be collected using the patient identification form, the memorial symptom assessment scale (MSAS), the chemotherapy symptom management self-efficacy scale for breast cancer patients, the european organisation for research and treatment of cancer quality of life questionnaire core 30 (EORTC QLQ-C30 version 3.0), and the breast cancer-specific module (EORTC QLQ-BR23). All data will be collected by the same researcher. The primary hypothesis is that patients using the artificial intelligence-supported mobile application will demonstrate better symptom management, higher self-efficacy levels, and improved quality of life compared with patients receiving standard care alone. Findings from this study may contribute to the growing evidence regarding the integration of artificial intelligence and mobile health technologies into supportive cancer care and provide guidance for future digital health interventions targeting symptom management in breast cancer patients.
Study design
- Primary purpose
- Supportive care
- Allocation
- Randomised
- Intervention model
- Parallel groups
- Masking
- None (open label)
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| AI-Supported Mobile Application + Standard Care | Experimental | Behavioral: AI-Supported Mobile ApplicationBreast cancer patients receiving first-time chemotherapy will use an AI-supported mobile application in addition to standard care. Participants will report daily symptoms through the application and receive personalized AI-generated symptom management recommendations and educational content. |
| Standard Care | No intervention | –Participants will receive routine standard care provided by the chemotherapy centers without access to the 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 (9 listed)
- Female patients aged 18 years and older.
- Diagnosed with breast cancer.
- Patients with Stage 0, I, II, or III breast cancer.
- Receiving chemotherapy for the first time.
- Eastern Cooperative Oncology Group (ECOG) Performance Status score of 0 or 1.
Key exclusion criteria (8 listed)
- Patients diagnosed with a primary cancer other than breast cancer.
- Patients with severe comorbid diseases.
- Patients receiving concurrent radiotherapy.
- Patients diagnosed with inflammatory breast cancer.
- Patients using luteinizing hormone-releasing hormone (LHRH) analogs.
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-Supported Mobile ApplicationParticipants will use an AI-supported mobile application starting on the first day of chemotherapy. The application allows daily symptom reporting, provides AI-based personalized symptom management recommendations, and includes educational information about breast cancer and its treatment. | Behavioural | AI-Supported Mobile Application + Standard Care |
Primary outcome
Symptom burden
Time frame: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)
Symptom burden will be assessed using the Memorial Symptom Assessment Scale (MSAS). The scale comprises a total of 32 symptoms, which are evaluated in terms of frequency, severity, and distress. On the Memorial Symptom Assessment Scale, each symptom is examined for presence or absence. If a symptom is present, it is rated as follows: for frequency: 1 (rarely), 2 (occasionally), 3 (frequently), 4 (almost constantly); for severity: 1 (mild), 2 (moderate), 3 (severe), 4 (very severe); for distress: 0 (not at all), 1 (a little bit), 2 (somewhat), 3 (quite a bit), 4 (very much). Higher scores on the Memorial Symptom Assessment Scale indicate greater frequency, severity, and distress of the experienced symptoms.
Chemotherapy symptom management self-efficacy
Time frame: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)
Self-efficacy will be measured using the Chemotherapy Symptom Management Self-Efficacy Scale for Breast Cancer Patients. The scale consists of 27 items and three subdimensions. Each item is rated on a 0-10 Likert scale (0 = not confident at all, 10 = very confident). The total score ranges from 0 to 270. Higher scores indicate better self-efficacy (greater confidence in managing chemotherapy-related symptoms).
Quality of Life (EORTC QLQ-C30)
Time frame: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)
Quality of life will be evaluated using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30 Version 3.0). The scale contains 30 items assessing functional scales (physical, role, cognitive, emotional, social), symptom scales (fatigue, pain, nausea/vomiting, dyspnea, insomnia, appetite loss, constipation, diarrhea, financial difficulties), and global health status. All scores are transformed to a 0-100 range. Higher scores on global health status and functional scales indicate better quality of life, while higher scores on symptom scales indicate worse quality of life.
Quality of Life (EORTC QLQ-BR23)
Time frame: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)
Quality of life will be evaluated using the European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Breast Cancer Module 23 (EORTC QLQ-BR23). The scale contains 23 items assessing breast cancer-specific functional domains (body image, sexual functioning, sexual enjoyment, future perspective) and symptom domains (systemic therapy side effects, breast symptoms, arm symptoms, hair loss). All scores are transformed to a 0-100 range. Higher scores on functional scales indicate better quality of life, while higher scores on symptom scales indicate worse quality of life.
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 17 Sep 2026.
- Background: PubMed 32247251Fjell M, Langius-Eklof A, Nilsson M, Wengstrom Y, Sundberg K. Reduced symptom burden with the support of an interactive app during neoadjuvant chemotherapy for breast cancer - A randomized controlled trial. Breast. 2020 Jun;51:85-93. doi: 10.1016/j.breast.2020.03.004. Epub 2020 Mar 20.
- Background: PubMed 32427567Grasic Kuhar C, Gortnar Cepeda T, Kovac T, Kukar M, Ruzic Gorenjec N. Mobile App for Symptom Management and Associated Quality of Life During Systemic Treatment in Early Stage Breast Cancer: Nonrandomized Controlled Prospective Cohort Study. JMIR Mhealth Uhealth. 2020 Aug 4;8(8):e17408. doi: 10.2196/17408.
- Background: PubMed 32394220Baik SH, Oswald LB, Buitrago D, Buscemi J, Iacobelli F, Perez-Tamayo A, Guitelman J, Diaz A, Penedo FJ, Yanez B. Cancer-Relevant Self-Efficacy Is Related to Better Health-Related Quality of Life and Lower Cancer-Specific Distress and Symptom Burden Among Latina Breast Cancer Survivors. Int J Behav Med. 2020 Aug;27(4):357-365. doi: 10.1007/s12529-020-09890-9.
- Background: PubMed 38833298Jiang L, Xu J, Wu Y, Liu Y, Wang X, Hu Y. Effects of the "AI-TA" Mobile App With Intelligent Design on Psychological and Related Symptoms of Young Survivors of Breast Cancer: Randomized Controlled Trial. JMIR Mhealth Uhealth. 2024 Jun 4;12:e50783. doi: 10.2196/50783.
- Background: PubMed 36067241Seven M, Pasalak S, Bagcivan G, Ozkasap O, Selcukbirick F. A Mobile Application for Symptom Management in Patients With Breast Cancer. Oncol Nurs Forum. 2022 Aug 18;49(5):409-420. doi: 10.1188/22.ONF.409-420.
- Background: PubMed 37661196El-Amir A, El-Baiomy EM, Sabry NA, Kassem L, Chesney MA, Wallston KA. The relationship between coping self-efficacy and B cells in breast cancer patients. J Egypt Natl Canc Inst. 2023 Sep 4;35(1):28. doi: 10.1186/s43046-023-00187-y.
- Background: PubMed 38969573Balci H, Faydali S. The Effect of Education Performed Using Mobile Application on Supportive Care Needs and Quality of Life in Women with Breast Cancer: Randomized Controlled Trial. Semin Oncol Nurs. 2024 Aug;40(4):151684. doi: 10.1016/j.soncn.2024.151684. Epub 2024 Jul 4.
- Individual participant dataSharing planned: No. Individual participant data will not be shared because this study does not include a data-sharing plan approved by the ethics committee, and participants did not provide consent for public data sharing. To ensure confidentiality and protect participant privacy, de-identified individual-level data will remain with the research team only.
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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.
Yasemin Yıldırım, Prof. Dr. principal investigator
Ege University
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-Supported Mobile Application in people with Breast Cancer and Chemotherapy Side Effects, run by Ege University at 1 site in Turkey (Türkiye).
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 9 inclusion and 8 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 17 Sep 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 Turkey (Türkiye). 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 Gökhan Sezgin, PhD Candidate (+00905363005966, gokhan.sezgin95@gmail.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Symptom burden (time frame: Baseline, after the end of Cycle 1 (each cycle is 21 days), and after the end of Cycle 4 (approximately up to 12 weeks)). The study lists 4 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 NCT07826338, which also lists 7 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 17 Sep 2026.