Clinical trial · Interventional
Training Data Collection & AI Development
LIFECHAMPS: A Collective Intelligence Platform to Support Cancer Champions Small-Scale Pilot
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
The aim of this study is to facilitate collection of real-world data to test and train the analytics engine for each prototype algorithm. Preliminary datasets will be generated to enable a dry run of the prototype algorithms to check their predictive functionality as part of simulated 'experimental' scenarios at each LifeChamps partner site. This preparatory work will be critical to the development of the LifeChamps platform, prior to progressing to a larger scale feasibility trial.
Conditions
Conditions (2)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Breast Cancer | Malignant Breast Neoplasm | CURATED_EXACT | 0.92 |
| Prostate Cancer | Malignant Prostate Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| LifeChamps Platform | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (1)
- type
- EXPERIMENTAL
- label
- LifeChamps Platform
- description
- Participants will be asked to use the LifeChamps platform and will be provided with the study equipment.
- interventionNames
- Other: LifeChamps Platform
Primary outcomes (1)
- measure
- Analytical models
- timeFrame
- 6 months
- description
- The collected data will be used to train and test the analytical models. For example, the initial data from sensors will be refined, further, with statistical, spectral and supervised learning analyses to identify and extract possible patterns (e.g., activities of daily living) inside their signals. Sensor, EHR and PROM data will be all analysed together through exploratory algorithms (e.g., pairwise Markov random fields, Bayesian networks) to identify possible interactions and dependencies among their trajectories, mapping the frailty and QOL domains of elderly prostate and breast cancer patients across all the data collection process.
Secondary outcomes (9)
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 65 Years
Show eligibility criteria text
Inclusion Criteria: * Breast or prostate cancer. * Diagnosed with early stage (I-III) cancer (breast, prostate) and living beyond initial cancer treatment (curative/incurable). * Diagnosed with advanced or metastatic disease with life expectancy \>12 months. * At least 1 month after a) local treatment with curative intent (surgery, radiotherapy) or b) initiation of systemic treatment (hormone treatment, CDK4/6 or new generation antiandrogens). * Absence of diagnosed secondary malignancy. * Deemed by a member of the multidisciplinary team as physically and psychologically fit to participate in the study. * Able to read, write and understand the respective local language (greek). * Achieve a score of above 2 on the Mini-Cog during the screening process. * Able to bring and use own Android version 10 (or above) device during the study. * Domestic 24/7 internet access via wi-fi and/or 4G mobile data (will be provided if unavailable). Exclusion Criteria: * Currently receiving chemotherapy. * Terminal cancer stage on palliative care. * Survival prognosis of \<18 months from the time of recruitment. * Unwilling to provide written informed consent. * Presence of internal medical device (e.g. pacemaker etc.)
References
Publications (0)
Data not yet available