AI as an Aid for Weekly Symptom Intake in Radiotherapy

NCT06525181 | Recruiting

• 1 other identifier: BR-001
• Study Type: interventional
• Target: 200
• Locations: 1 country
• Sites: 1

Brief Summary

The study investigates the use of artificial intelligence (AI) and large language models (LLMs) to enhance the efficiency and accuracy of weekly treatment consultations (OTVs) in radiotherapy. It hypothesizes that an AI-enabled symptom summary tool will match traditional medical review methods in accuracy while saving time. The study includes patients undergoing pelvic radiotherapy and excludes those with pelvic reirradiation or who have undergone surgery. Patients will receive both standard and AI-assisted weekly consultations, with AI summaries generated using the OpenAI GPT-4 API. Blinded oncologists will compare the accuracy and quality of the AI-generated and doctor-generated summaries, while patients and doctors will rate these summaries. The primary objective is to evaluate the accuracy and time efficiency of AI-assisted symptom summaries compared to traditional methods.

Conditions

Radiotherapy Side Effect; Pelvic Cancer; Patient

Keywords

Artificial Intelligence; Patient-Reported Outcome

Outcome Measures

Primary Outcomes (1)

• The Physician Documentation Quality Instrument-9 (PDQI-9)

  The Physician Documentation Quality Instrument-9 (PDQI-9) will be used to evaluate the quality of the documentation. The PDQI-9 is a validated questionnaire that assesses nine key elements of documentation quality: completeness, correctness, consistency, comprehensibility, relevance, organization, conciseness, formatting, and overall impression.

  2 months

Secondary Outcomes (4)

• Time tracking

  2 months

• Accuracy

  2 months

• Physician satisfaction

  2 months

• Patient satisfaction

  2 months

Study Arms (2)

Standard weekly symptom assessment by physicians

ACTIVE COMPARATOR

Other: Standard weekly symptom intake

AI-assisted symptom intake

EXPERIMENTAL

Other: Generative Artificial Intelligence

Interventions

Generative Artificial Intelligence OTHER

Gen AI assisted symptom intake summarization

AI-assisted symptom intake

Standard weekly symptom intake OTHER

Standard weekly symptom intake performed by a physician

Standard weekly symptom assessment by physicians

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• All patients undergoing radiotherapy in the pelvic region.

You may not qualify if:

• Cases of pelvic reirradiation or operated cases.

Sponsors & Collaborators

• jaide: lead
• National Cancer Institute, Brazil: collaborator

Study Sites (1)

Instituto Nacional de Câncer José Alencar Gomes da Silva - INCA

Rio de Janeiro, Brazil

RECRUITING

MeSH Terms

Conditions

Radiation Injuries; Pelvic Neoplasms

Condition Hierarchy (Ancestors)

Wounds and Injuries; Neoplasms by Site; Neoplasms

Central Study Contacts

Rachele Grazziotin, MD

CONTACT

(21)3207-4550; cep@inca.gov.br

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NON RANDOMIZED
• Masking: NONE
• Purpose: OTHER
• Intervention Model: PARALLEL
• Sponsor Type: INDUSTRY
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: July 18, 2024
• First Posted: July 29, 2024
• Study Start: July 22, 2024
• Primary Completion: November 1, 2024
• Study Completion: December 15, 2024
• Last Updated: October 10, 2024

Record last verified: 2024-10

Data Sharing

• IPD Sharing: Will not share

Locations

BR (1)