Artificial Intelligence to Search for Abnormalities in Ambulatory Cancer Patients

NCT ID: NCT05412420

Last Updated: 2023-11-30

Basic Information

• Recruitment Status: COMPLETED
• Clinical Phase: NA
• Total Enrollment: 500 participants
• Study Classification: INTERVENTIONAL
• Study Start Date: 2022-08-03
• Study Completion Date: 2023-10-13

Brief Summary

During treatment, cancer patients may experience side effects related to their disease but also to the different treatments they receive.

Currently, adverse effects and toxicities are well codified in the oncology community, notably via the NCI CTCAE criteria.

Unlike objective data such as a blood sample or a CTscan, a major bias in patient assessment is the subjective assessment of the physician or its team at a given time, which may not reflect the overall situation (for better or worse). Several studies had already highlighted the discrepancies between medical and patient data collection.

Self-assessment of symptoms is one way to overcome this bias. Moreover, there are now a large number of solutions that allow to perform these self-assessments at home.

Thanks to these tools, there are now two situations, the scheduled evaluation (before a chemotherapy treatment, or after a surgical procedure for instance) and the unscheduled situations, where it is the patient himself who can trigger an evaluation form.

These new evaluation methods also allow to take a quality of life approach. Patient-reported outcomes (PROs) is now a valid evidence-based assay to detect patient's symptoms and therefore provide helpful clinical information to healthcare providers.

The goal of this study is to go one step further than the previous PROs studies and evaluate the ability to train a machine learning algorithm to detect at-risk situations and lay the foundation for a viable solution for future prospective and randomized trials.

Conditions

Solid Tumor

Keywords

Electronic survey; Artificial intelligence; Quality of life; Patient-Reported Outcomes (PROs); Symptom management; eHealth; Machine learning

Study Design

• Allocation Method: NA
• Intervention Model: SINGLE_GROUP
• Primary Study Purpose: PREVENTION
• Blinding Strategy: NONE

Study Groups

Patient Self-Reporting of Symptoms

Group Type: EXPERIMENTAL

Patient Self-Reporting of Symptoms

Intervention Type: OTHER

At baseline, clinical research staff will:

• verify the possibility of an internet connection at the patient's home
• help the patient to fill in the 1st questionnaire (baseline questionnaire - frailty)

Every two weeks for 3 months:

• patients complete questionnaires via app (toxicity; quality of life, medication adherence)
• responses are verified by clinical research staff
• In case of severe symptoms, the clinician contacts the patient and arranges for management.

At the end of the study :

• patients answer a satisfaction questionnaire

Interventions

Patient Self-Reporting of Symptoms

At baseline, clinical research staff will:

• verify the possibility of an internet connection at the patient's home
• help the patient to fill in the 1st questionnaire (baseline questionnaire - frailty)

Every two weeks for 3 months:

• patients complete questionnaires via app (toxicity; quality of life, medication adherence)
• responses are verified by clinical research staff
• In case of severe symptoms, the clinician contacts the patient and arranges for management.

At the end of the study :

• patients answer a satisfaction questionnaire

Intervention Type: OTHER

Eligibility Criteria

Inclusion Criteria

• Follow-up for a solid tumor
• Chemotherapy treatment (oral and/or injectable) scheduled or in progress
• Life expectancy > 3 months
• Performance Status (PS) < 3
• Have an internet connection or assistance to answer questions throughout the study (nurse, family members, etc.)
• Patient having understood, signed and dated the consent form
• Patient affiliated to the social security system

Exclusion Criteria

• Lack of means to answer the online questionnaires
• Patient in another therapeutic trial with an experimental molecule
• Patients and their families who cannot read or speak French
• Persons deprived of liberty or under guardianship (including curatorship)

• Minimum Eligible Age: 18 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: No

Sponsors

Institut de Cancérologie de Lorraine

OTHER

Sponsor Role: lead

Responsible Party

Responsibility Role: SPONSOR

Principal Investigators

LAMBERT AURELIEN, MD

Role: PRINCIPAL_INVESTIGATOR

Institut de Cancérologie de Lorraine

Locations

Institut de Cancerologie de Lorraine

Vandœuvre-lès-Nancy, , France

Countries

France

Other Identifiers

2022-A01034-39

Identifier Type: -

Identifier Source: org_study_id