UMIN-CTR Clinical Trial
| Unique ID issued by UMIN | UMIN000059009 |
|---|---|
| Receipt number | R000067489 |
| Scientific Title | Development and Evaluation of an AI-Based Online Cancer Consultation System |
| Date of disclosure of the study information | 2025/09/05 |
| Last modified on | 2025/09/05 16:32:06 |
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Basic information
Public title
Development and Evaluation of an AI-Based Online Cancer Consultation System
Acronym
AI-Based Online Cancer Consultation
Scientific Title
Development and Evaluation of an AI-Based Online Cancer Consultation System
Scientific Title:Acronym
AI-Based Online Cancer Consultation
Region
| Japan |
Condition
Condition
Cancer
Classification by specialty
| Medicine in general |
Classification by malignancy
Malignancy
Genomic information
NO
Objectives
Narrative objectives1
This study aims to evaluate the usefulness of a hybrid online cancer consultation system by comparing responses generated through three approaches using a dedicated web-based application: (i) generative AI, (ii) healthcare professionals, and (iii) a hybrid model combining AI and healthcare professionals. Both patients and healthcare professionals will assess these responses
Basic objectives2
Others
Basic objectives -Others
.The hybrid approach seeks to leverage the cross-disciplinary knowledge and rapid response capability of AI, while ensuring medical, social, and ethical validity, as well as empathy and psychological support for patients, through the involvement of healthcare professionals. By integrating these complementary strengths, we aim to develop an efficient and high-quality online hybrid cancer consultation system that addresses the unmet needs of face-to-face cancer consultation support in real-world clinical practice.
Trial characteristics_1
Trial characteristics_2
Developmental phase
Assessment
Primary outcomes
Overall evaluation score by the consultee
Key secondary outcomes
Overall evaluation score by healthcare professionals
Consultee-reported evaluation scores: clarity of advice, appropriateness of advice, timeliness in resolving the consultation, attitude of the advisor, willingness to recommend the advisor to family/friends, willingness to consult the advisor again, and ranking of the three types of advisors
Healthcare professional-reported evaluation scores: clarity of advice, appropriateness of advice, timeliness in resolving the consultation, attitude of the advisor, and frequency of inadequate/invalid responses
Time from consultation submission to completion of advice
Proportion of consultations completed
Base
Study type
Observational
Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment
Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10
Eligibility
Age-lower limit
| 18 | years-old | <= |
Age-upper limit
| Not applicable |
Gender
Male and Female
Key inclusion criteria
Patients diagnosed with cancer and receiving care at our institution, as well as their family members. Eligible participants include those regardless of treatment type or treatment status, including patients under follow-up without active treatment.
Patients with cancer or their family members
Individuals capable of using a personal computer or smartphone to participate in online consultations
Individuals who have provided written informed consent to participate in this study
Age >=18 years
Key exclusion criteria
Individuals without cancer and their family members
Individuals unable to use a personal computer or smartphone for online consultation
Target sample size
100
Research contact person
Name of lead principal investigator
| 1st name | Hiroya |
| Middle name | |
| Last name | Takeuchi |
Organization
Hamamatsu University School of Medicine
Division name
Cance center
Zip code
431-3192
Address
Handayama 1-20-1, Hamamatsu, Shizuoka
TEL
0534352111
karayama@hama-med.ac.jp
Public contact
Name of contact person
| 1st name | Masato |
| Middle name | |
| Last name | Karayama |
Organization
Hamamatsu University School of Medicine
Division name
Cancer Center
Zip code
431-3192
Address
Handayama 1-20-1, Hamamatsu, Shizuoka
TEL
0534352111
Homepage URL
karayama@hama-med.ac.jp
Sponsor or person
Institute
Hamamatsu University School of Medicine
Institute
Department
Personal name
Funding Source
Organization
Japan Society for the Promotion of Science
Organization
Division
Category of Funding Organization
Other
Nationality of Funding Organization
Other related organizations
Co-sponsor
Name of secondary funder(s)
IRB Contact (For public release)
Organization
Hamamatsu University School of Medicine
Address
Handayama 1-20-1, Hamamatsu, Shizuoka
Tel
0534352680
rinri@hama-med.ac.jp
Secondary IDs
Secondary IDs
NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW
Institutions
Institutions
Other administrative information
Date of disclosure of the study information
| 2025 | Year | 09 | Month | 05 | Day |
Related information
URL releasing protocol
Publication of results
Unpublished
Result
URL related to results and publications
Number of participants that the trial has enrolled
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description
Progress
Recruitment status
Enrolling by invitation
Date of protocol fixation
| 2025 | Year | 03 | Month | 10 | Day |
Date of IRB
| 2025 | Year | 07 | Month | 28 | Day |
Anticipated trial start date
| 2025 | Year | 07 | Month | 28 | Day |
Last follow-up date
| 2030 | Year | 03 | Month | 31 | Day |
Date of closure to data entry
Date trial data considered complete
Date analysis concluded
Other
Other related information
Written informed consent will be obtained from participants.
Consultee participants (study subjects) will submit their questions in text format through a dedicated web application developed for this study.
For each question, an advisor with expertise in the relevant field will provide a response (advisor response). Subsequently, a response will be generated using ChatGPT (AI response), and the advisor will then revise the AI-generated response to produce a hybrid response. The type of advisor will remain blinded to the consultee.
The consultee will evaluate all three types of responses.
In addition, multiple healthcare professionals, independent of the advisors, will evaluate the responses provided by the advisors.
Management information
Registered date
| 2025 | Year | 09 | Month | 05 | Day |
Last modified on
| 2025 | Year | 09 | Month | 05 | Day |
Link to view the page
Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000067489
