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Developing Artificial Intelligence-based Algorism to Predict Side Effects and Symptoms From Chemotherapy | Clinical Trials | Clareo Health

RECRUITING

Developing Artificial Intelligence-based Algorism to Predict Side Effects and Symptoms From Chemotherapy

Developing Artificial Intelligence-based Algorism Based on Life-log Data Acquired From Wearable Device for the Prediction of Chemotherapy-induced Side Effects and Symptom

NCT05937477•Sehhoon Park

View on ClinicalTrials.gov

Summary

In this study, the investigators obtain wearable disease based biomarkers from patients diagnosed with cancer and undergoing chemotherapy, and simultaneously measure patient self-reported adverse events through an app to evaluate chemotherapy completion rates, emergency room visits, and frequency of CTCAE adverse events. The investigators will develop an artificial intelligence-based algorism that can predict patients' side effects based on biomarkers alone.

Detailed Description

In this study, patients diagnosed with lung, head and neck, and esophageal cancers and undergoing chemotherapy will be measured for self-reported side effects using a wearable device to collect biomarkers through an app, and the association between patient quality of life and side effects and biomarkers obtained from the wearable device will be analyzed. On the other hand, blood (EDTA 3cc) for pharmacogenomics testing will be tested once at any point during the study period as an indicator associated with side effects after chemotherapy.

Eligibility

Age

20 - No limit years

Sex

ALL

Healthy Volunteers

Inclusion Criteria

•20 years of age or older
•Must have diagnosed with lung, head and neck, or esophageal cancer,
•1. scheduled to receive their first treatment in preoperative or postoperative chemotherapy.
•2. scheduled for systemic chemotherapy due to recurrence or metastasis.
•Eastern Cooperative Oncology (ECOG) performance status of 0 to 2.
•Patients who have access to a smartphone and can use the mobile app on their own.
•Understand the purpose of the study and agree to participate in the study.

Exclusion Criteria

•Patients who, in the judgment of the researcher, have difficulty using the application.
•Patients who are judged by the medical staff to be unable to participate in the study.

Locations (1)

Samsung Medical Center

Seoul, Gangnamgu, South Korea

Key Dates

Start Date

June 8, 2023

Primary Completion Date

December 31, 2025

Completion Date

June 30, 2026

Last Updated

July 21, 2023

Enrollment

500

ESTIMATED participants

Conditions

Lung CancerHead and Neck CancerEsophageal Cancer

Interventions

Fitbit smartwatch

OTHER

Contacts

Sehhoon Park, MD

CONTACT

+82-10-9185-8619 sehhoon.park@samsung.com

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Data Source & Attribution

This clinical trial information is sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.

ClinicalTrials.gov last update: July 21, 2023Data synced to Clareo: March 29, 2026

Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.

Neither the United States Government nor Clareo Health make any warranties regarding the data. Check ClinicalTrials.gov frequently for updates.

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Developing Artificial Intelligence-based Algorism to Predict Side Effects and Symptoms From Chemotherapy

Inclusion Criteria

Exclusion Criteria

Magnetic Resonance Imaging of the Lung: Oncological Applications

Sacituzumab Tirumotecan (MK-2870) Versus Pemetrexed and Carboplatin Combination Therapy in Participants With Epidermal Growth Factor (EGFR)-Mutated, Advanced Nonsquamous Non-small Cell Lung Cancer (NSCLC) Who Have Progressed on Prior EGFR Tyrosine Kinase Inhibitors (MK-2870-009)

Testing the Addition of an Anti-Cancer Drug, TRC102, to the Usual Chemotherapy Treatment (Pemetrexed, Cisplatin or Carboplatin) During Radiation Therapy for Stage III Non-Squamous Non-Small Cell Lung Cancer

Association Between Galectin-3 Levels and Outcomes in Patients With Renal Cell Carcinoma, Transitional Cell Carcinoma , Non Small Cell Lung Cancer, and Hepatocellular Carcinoma, Treated With PD-1/PDL-1 Inhibitors

Reducing the Incidence of Symptomatic Brain Metastases With MRI Surveillance

Immunotherapy After Surgery for People Who Have No Remaining Cancer Cells After Standard Treatment for Early-Stage Non-Small Cell Lung Cancer, INSIGHT Trial