Wearable Technology and Machine Learning for Early Detection and Risk Assessment of Unacceptable Toxicities in a Paediatric Oncology Cohort

NCT ID: NCT07030998

Last Updated: 2025-11-17

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Total Enrollment

150 participants

Study Classification

OBSERVATIONAL

Study Start Date

2025-10-15

Study Completion Date

2027-12-31

Brief Summary

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Data collection study to establish a predictive model of infection observed during childhood cancer therapy using data captured by wearable technology.

Detailed Description

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Rationale: Development in treatment for childhood cancers has improved remarkably with the 5-year survival rate now exceeding 80% in developed countries. However, these treatments are not without their adverse effects. The international Childhood Cancer Survivor study revealed that 62.3% of survivors had at least one chronic health condition and 27.5% had a severe or life-threatening condition as a direct result of their cancer treatment (DOI: 10.1056/NEJMsa060185). One of the adverse events experienced by 90% of children treated for cancer is infection. Septic shock, the most severe of infection outcomes, is characterized by life-threatening organ dysfunction, is the most and carriers a mortality rate of 41 to 46% (DOI: 10.1016/j.jped.2023.01.001). Beyond mortality, delayed first antibiotic administration (\> 1 hour from fever onset \>38 degrees) is associated with intensive care admissions, prolonged hospital stays, and adverse outcomes. Fluctuations in physiology can precede fever onset by 72 hours in patients with infection. This may provide a window for early detection of infection via wearable technology. The WEARABLES study will combine wearable technology with machine learning to develop an infection prediction model to allow earlier detection and reduce the suffering of children with cancer.

Trial Design: This is a non-interventional silent pilot trial to establish a predictive model for infection observed during childhood cancer therapy using data passively captured via wearables.

The study will be conducted in patients (5-18 years) with a new cancer diagnosis, currently receiving treatment at The Royal Children's Hospital, and have access to an iPhone (either themselves as an adolescent and young adult or via their parents/guardian). Once consented the wearable device will be paired to the patients or parent/guardians phone, and the WEARABLES app will be downloaded onto the phone. Once the device has been set up correctly, the wearable device will collect a range of vital signs for the duration of the study (4 weeks), and a weekly survey will be sent to check for symptoms and/or hospital admissions for infection. At the end of the 4 weeks, participants will receive a final survey to evaluate the feasibility of using a wearable device for toxicity detection. No further involvement will be asked of participants for this pilot trial. All data collected will be utilized to develop a machine learning model for sepsis/infection before being prospectively validated in a second trial.

Conditions

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Cancer Infection Digital Health Wearable Devices

Study Design

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Observational Model Type

CASE_ONLY

Study Time Perspective

PROSPECTIVE

Interventions

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Wearable Device

Wearable device to collect the following health metrics directly from participants for the duration of the study (4 weeks). Health metrics are collected every 15 minutes, except for the ECG which will be collected once per week.

Data points:

* ECG data (Once per week)
* Exercise time
* Body Temperature
* Heart Rate
* Irregular Heart Rhythm
* Blood Oxygen Saturation
* Respiratory Rate

Intervention Type DEVICE

Eligibility Criteria

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Inclusion Criteria

* Paediatric, adolescent or young adult diagnosis of cancer AND receiving therapy placing them at risk of infection
* Receiving cancer treatment at The Royal Children's Hospital
* Patients aged 5-18 years at time of the eligibility screening
* If aged \< 16 years, parent or guardian able to provide consent
* iPhone 8 or later (iOS must be up to date/updated at time of enrolment)
* At least 10MB of iPhone storage for WEARABLES app and data collection.
* Willing and able to wear a wearable device for a period of 4 weeks (during waking hours).
* Consent to data being shared to the WEARABLES app (owned by the research team).

Exclusion Criteria

* \<5 years of age.
* \<16 years of age without guardian or parent consent.
* Aged 16-18 and unable to provide consent.
* Participant did not consent to wearing Apple Watch for a period of 4 weeks.
Minimum Eligible Age

5 Years

Maximum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Murdoch Childrens Research Institute

OTHER

Sponsor Role lead

Responsible Party

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Responsibility Role SPONSOR

Locations

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The Royal Children's Hospital

Parkville, Victoria, Australia

Site Status RECRUITING

Countries

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Australia

Central Contacts

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Lane Collier

Role: CONTACT

03 9936 6324

A/Prof Rachel Conyers

Role: CONTACT

03 9345 5522

Facility Contacts

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Lane Collier

Role: primary

03 9936 6324

A/Prof Rachel Conyers

Role: backup

03 9345 5522

Other Identifiers

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111206

Identifier Type: -

Identifier Source: org_study_id

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