Advanced Patient Monitoring and A.I. Supported Outcomes Assessment in Lung Cancer Using Internet of Things Technologies (A.I. - APALITT)

Institute of Hospitalization and Scientific Care (IRCCS)

Status: Enrolling

Conditions: Non-small-cell Lung Cancer

Treatments: Device: Fitbit charge

Study type: Interventional

Funder types: Other

Identifiers

NCT05815472

3817

Details and patient eligibility

About

The use of advanced technological tools able to exploit patient-centered "Real World Data", represents an innovative and fascinating challenge for the most modern personalized medicine paradigms.

Monitoring oncological patients during multimodal cancer therapies may represent a significant step towards a comprehensive and reliable quality of life assessment, prevention of toxicity before its clinical onset and treatment outcomes prediction.

The big data approach, being able to collect, manage and interpret large volumes of health data, eventually supported by artificial intelligence (A.I.) is therefore fundamental in this setting and may be translated in the next future in tangible advantages for the patients.

Primary aim of the project is to assess patients experience of using portable monitoring systems during multimodal oncological therapies and follow up period, through the use of a dedicated app and wearable technology (i.e. monitoring bracelet), as Electronic Health Record data harvesting devices.

More specifically, the patients report experience measure of man/women affected by locally advanced non-small-cell lung cancer undergoing chemo(radio)therapy followed either by surgery or immunotehrapy (e.g. describing toxicity, instrumental activities of daily living and stress/coping levels) will be analyzed.

The machine learning assisted analysis of these data will allow to identify patients profile that may be used as risk categories to optimize assistance and follow up practices.

This is an observational study with device, co-financed, monocentric study with a foreseen study duration of 36 months.

Enrollment: 50 estimated patients

Sex: All

Ages: Under 75 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

• Aged < 75
• Clinically able to use portable technologies
• Able to understand and sign informed consent

Exclusion criteria

• Major psychiatric disorder
• ECOG>2 performance status
• Not able to use portable technologies

Trial design

Primary purpose: Diagnostic

Allocation: N/A

Interventional model: Single Group Assignment

Masking: None (Open label)

---

50 participants in 1 patient group

Patients affected by locally advanced non-small-cell lung cancer

Experimental group

Description:

Patients affected by locally advanced non-small-cell lung cancer (staged III according to 8th TNM classification), undergoing induction therapy (IT) followed by either radical surgery or immunotherapy boost and treated in Fondazione Policlinico Universitario "A. Gemelli" IRCCS of Rome, Italy, will be enrolled in this study.

Treatment:

Device: Fitbit charge