AI App for Management of Atopic Dermatitis

NCT06362629 | Recruiting DMC

• 1 other identifier: WCH240407
• Study Type: interventional
• Target: 232
• Locations: 1 country
• Sites: 1

Brief Summary

Background: Atopic dermatitis (AD) is a chronic inflammatory skin disease characterized by recurrent rashes and itching, which seriously affects the quality of life of patients and brings heavy economic burden to society. The Treat to Target (T2T) strategy was proposed to guide optimal use of systemic therapies in patients with moderate to severe AD, and it is emphasized patients' adherence and combined evaluation from both health providers and patients. While effective treatments for AD are available, non-adherence of treatment is common in clinical practice due to the patients' unawareness of self-evaluation and lack of concern about the specific follow-up time points in clinics, which leads to the treatment failure and repeated relapse of AD. Hypothesis: An Artificial Intelligence assistant decision-making system (AIADMS) with implementation of the T2T framework could help control the disease progression and improve the clinical outcomes for AD. Overall objectives: the investigators aim to develop an AIADMS in the form of smartphone app to integrate T2T approach for both clinicians and patients, and design clinical trials to verify the effectiveness and safety of the app. Methods: This project consists of three parts, AI training model for diagnosis and severity grading of AD based on deep learning, development of Artificial Intelligence assistant decision-making system (AIADMS) in the form of app, and design of a randomized controlled trial to verify the effectiveness and safety of AIADMS App for improvement of the clinical outcomes in AD patients. Expected results: With application of AIADMS based app, the goal of T2T for patients with AD could be realized better, the prognosis could be improved, and more satisfaction could be achieved for both patients and clinicians. Impact: This is the first AIADMS based app for AD management running through thediagnosis, patients' self-participation, medical follow-up, and evaluation of achievement of goal of T2T.

Conditions

Atopic Dermatitis; Artificial Intelligence

Keywords

Atopic dermatitis; Treat to Target (T2T) strategy; Artificial Intelligence; app

Outcome Measures

Primary Outcomes (1)

• The overall efficiency rate of treating objectives including PP-NRS, EASI, SCORAD, POEM, and DLQI at 12 weeks after treatment

  The overall efficiency is calculated as "Total number of participants with effective treatment of 5 treating objectives / total number of participants \*100%". Criteria for effective treatment are as below: ① PP-NRS absolutely score ≤4, ② EASI -50, EASI -75, or EASI≤7, ③ SCORAD-50, SCORAD-75, or SCORAD ≤24, ④ POEM absolutely score ≤7, ⑤ DLQI absolutely score ≤5.

  12 months

Secondary Outcomes (3)

• The seperated efficiency rate of treating objectives including PP-NRS, EASI, SCORAD, POEM, and DLQI

  12 months

• The economic consumption

  12 months

• Satisfaction evaluation

  12 months

Study Arms (2)

App group

EXPERIMENTAL

Participants will be assisted to use the app during the process of management, and be followed-up at the scheduled time points including 2 weeks, 4 weeks, 8 weeks, 12 weeks, 6 months and 12 months after treatment, and the evaluation of five treating objectives including PP-NRS, EASI, SCORAD, POEM, and DLQI should be done on the day of follow-up.

Behavioral: Artificial Intelligence assistant decision-making system (AIADMS) App

Control group

NO INTERVENTION

The diagnosis, treatment, and follow-up of participants will be carried out according to the current routine on face-to-face basis. The time points of the participants follow-up will be determined by the responsible dermatologist, and the evaluation of five treating objectives including PP-NRS, EASI, SCORAD, POEM, and DLQI will be done and recorded on the day of follow-up.

Interventions

Artificial Intelligence assistant decision-making system (AIADMS) App BEHAVIORAL

Participants will be assisted to use the Artificial Intelligence assistant decision-making system (AIADMS) app during the process of management of AD, and be followed-up at the scheduled time points including 2 weeks, 4 weeks, 8 weeks, 12 weeks, 6 months and 12 months after treatment, and the evaluation of five treating objectives including PP-NRS, EASI, SCORAD, POEM, and DLQI should be done on the day of follow-up.

App group

Eligibility Criteria

• Age: 1 Year - 75 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)

You may qualify if:

• Diagnosed with AD, aged 1\~75 years; be able to communicate in Chinese; with basic reading and writing skills; participants or the guardian have smartphones or pads and are familiar with the use skills.

You may not qualify if:

• Mental illness; personality disorder; language barrier; hearing impairment; communication difficulties; with serious coexisting diseases, such as cardiopulmonary insufficiency, liver dysfunction, renal dysfunction, blood system diseases, tumors, or other diseases; other situations that not suitable for participating in clinical trial.

Sponsors & Collaborators

• West China Hospital: lead

Study Sites (1)

West China Hospital, Sichuan University

Chengdu, Sichuan, 610041, China

RECRUITING

MeSH Terms

Conditions

Dermatitis, Atopic; Alzheimer Disease

Interventions

Amyloid

Condition Hierarchy (Ancestors)

Skin Diseases, Genetic; Genetic Diseases, Inborn; Congenital, Hereditary, and Neonatal Diseases and Abnormalities; Dermatitis; Skin Diseases; Skin and Connective Tissue Diseases; Skin Diseases, Eczematous; Hypersensitivity, Immediate; Hypersensitivity; Immune System Diseases; Dementia; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Tauopathies; Neurodegenerative Diseases; Neurocognitive Disorders; Mental Disorders

Intervention Hierarchy (Ancestors)

Multiprotein Complexes; Macromolecular Substances; Proteins; Amino Acids, Peptides, and Proteins

Study Officials

• Jingyi Li, M.D.

  West China Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Jingyi Li, M.D.

CONTACT

+8618980605704; jingyili@wchscu.cn

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: NONE
• Purpose: TREATMENT
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Clinical professor

Study Record Dates

• First Submitted: April 8, 2024
• First Posted: April 12, 2024
• Study Start: September 1, 2024
• Primary Completion (Estimated): December 31, 2028
• Study Completion (Estimated): August 31, 2029
• Last Updated: October 15, 2024

Record last verified: 2024-04

Data Sharing

• IPD Sharing: Will share
• Shared Documents: STUDY PROTOCOL
• Time Frame: The IPD and supporting information will be available from January 01, 2026 to December 31, 2028.
• Access Criteria: Individual participant data sharing will be available after the principle investigator's agreement on reasonable request.

Locations

CN (1)