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Development and Usability Evaluation of a Knowledge Graph-Based Symptom Management System for Patients With Breast Cancer Undergoing Chemotherapy

Development and Usability Evaluation of a Knowledge Graph-Based Symptom Management Recommendation System for Patients With Breast Cancer Undergoing Chemotherapy

Status
Not yet recruiting
Phases
Unknown
Study type
Interventional
Source
ClinicalTrials.gov
Registry ID
NCT07495358
Acronym
KG-SMR-BC
Enrollment
30
Registered
2026-03-27
Start date
2026-04-15
Completion date
2026-12-15
Last updated
2026-04-01

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Breast Neoplasms, Syndrome

Keywords

breast cancer, symptom management, chemotherapy, recommender system

Brief summary

Patients with breast cancer patients undergoing chemotherapy commonly experience multiple co-occurring symptoms that are dynamic, interrelated, and difficult to manage using conventional approaches. Existing symptom management strategies often fail to address the complexity and evolving nature of symptom experiences during treatment. This study aims to develop a knowledge graph-based symptom management recommendation system for patients with breast cancer undergoing chemotherapy and to evaluate its usability and preliminary effectiveness among both patients and nurses. The system integrates evidence-based guidelines, clinical expertise, and patient-reported data to provide personalized recommendations for symptom management. In this study, patients will use the system to report symptoms and receive tailored management recommendations, while nurses will use it to support clinical decision-making and symptom management. Usability, acceptability, and user experience will be assessed for both patients and nurses, and changes in symptom burden and management outcomes will be evaluated. The findings are expected to inform the feasibility and optimization of multi-user digital health interventions for comprehensive symptom management in oncology care.

Interventions

BEHAVIORALKnowledge Graph-Based Symptom Management System

The intervention is a knowledge graph-based symptom management system designed for patients with breast cancer undergoing chemotherapy. The system integrates evidence-based guidelines, clinical expertise, and patient-reported data to generate personalized symptom management recommendations. Patients use the system to report symptoms and receive tailored management strategies. Nurses use the system to support clinical decision-making and provide symptom management guidance. The intervention aims to improve symptom management and support patient-centered care.

Sponsors

Capital Medical University
Lead SponsorOTHER

Study design

Allocation
NA
Intervention model
SINGLE_GROUP
Primary purpose
SUPPORTIVE_CARE
Masking
NONE

Intervention model description

This is a single-arm interventional study in which participants with early-stage breast cancer undergoing chemotherapy will use a knowledge graph-based symptom management system. Participants will report symptoms and receive personalized management recommendations through the system. Nurses will use the system to support symptom management and clinical decision-making. Usability, acceptability, and preliminary effectiveness will be evaluated.

Eligibility

Sex/Gender
ALL
Age
18 Years to 80 Years
Healthy volunteers
No

Inclusion criteria

* Aged 18 to 80 years * Pathologically confirmed breast cancer * Stage I-III breast cancer * Planning to initiate or currently receiving neoadjuvant or adjuvant chemotherapy * Expected to continue chemotherapy during the study period and complete at least two treatment time points/cycles * Able and willing to provide informed consent * Able to complete basic smartphone operations and system tasks independently or with guidance from the research staff

Exclusion criteria

* Recurrent or metastatic breast cancer (stage IV) * Significant cognitive impairment or communication barriers that preclude informed consent or completion of study procedures * Severe psychiatric disorders or unstable psychiatric symptoms that may interfere with study participation * Considered unsuitable for participation by the clinical or research team because of unstable medical condition or need for acute management

Design outcomes

Primary

MeasureTime frameDescription
mHealth App Usability QuestionnaireAt the end of the study period (approximately 6-8 weeks after system use)System usability assessed using the System Usability Scale (SUS), a validated 10-item questionnaire evaluating overall usability of the system.
Post-Study System Usability QuestionnaireAt the end of the study period (approximately 6-8 weeks after system use)Usability of the knowledge graph-based symptom management system assessed using a standardized mHealth usability questionnaire, including ease of use, usefulness, and user satisfaction.

Secondary

MeasureTime frameDescription
MD Anderson Symptom InventoryAt baseline and at the end of the study period (approximately 6-8 weeks after system use)Symptom severity and interference assessed using the MD Anderson Symptom Inventory (MDASI), a validated instrument measuring multiple symptoms in patients with cancer.
Average session duration per useUp to 12 weeksThe average duration of each system use session per participant, recorded automatically via system logs.
Number of system uses per weekUp to 12 weeksThe number of times each participant accesses the system per week, recorded automatically via system logs
Number of completed symptom reportsUp to 12 weeksThe total number of symptom reports submitted by each participant through the system, recorded automatically via system logs.
Semi-structured interviews (patient experience and satisfaction)At the end of the study period (approximately 6-8 weeks after system use)Patient experience and satisfaction explored through semi-structured interviews, focusing on usability, perceived usefulness, and barriers to system use.
Task-based usability assessmentBaselineTask-based usability assessment evaluating users' ability to complete predefined tasks, including task completion rate, time on task, and error rate.

Contacts

CONTACTRuolin Li, MS
rlli99@163.com+8615909837326
CONTACTJun-E Liu, Prof.
liujune66@ccmu.edu.cn

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Apr 2, 2026