A program to enhance cancer treatment through patient-reported outcomes and AI
Development of an Artificial Intelligence-based Incident Prediction Algorithm to Improve Cancer Patient Care and Patient Safety
Cankado GmbH · NCT04531995
This study is testing a new program that uses patient feedback and AI to see if it can help catch health issues in cancer patients earlier and make their treatment easier and more comfortable.
Quick facts
| Study type | Observational |
|---|---|
| Enrollment | 166000 (estimated) |
| Ages | 18 Years and up |
| Sex | All |
| Sponsor | Cankado GmbH (industry) |
| Locations | 4 sites (Moers and 3 other locations) |
| Trial ID | NCT04531995 on ClinicalTrials.gov |
What this trial studies
The OMCAT Register aims to create a comprehensive database for cancer treatment by integrating patient-reported outcomes (PRO) and verified clinical data. Utilizing advanced artificial intelligence techniques, the program seeks to develop predictive algorithms that can identify potential health threats in cancer patients earlier than traditional methods. This proactive approach allows for timely interventions, potentially reducing the severity of adverse events and improving patient comfort by minimizing the need for invasive diagnostics and frequent monitoring. The study focuses on leveraging high-frequency PRO data to enhance the accuracy of predictions and resource allocation in cancer care.
Who should consider this trial
Good fit: Ideal candidates for this study are adults aged 18 and older who have been diagnosed with cancer and are prescribed the CANKADO PRO-React Onco.
Not a fit: Patients who are unable to provide informed consent or are currently enrolled in another treatment trial may not benefit from this study.
Why it matters
Potential benefit: If successful, this program could lead to earlier interventions in cancer treatment, improving patient outcomes and reducing treatment-related stress.
How similar studies have performed: While the use of AI in predicting health outcomes is an emerging field, this specific approach combining PRO data with supervised learning techniques is relatively novel.
Eligibility criteria
Show full inclusion / exclusion criteria
Inclusion Criteria: * Signed informed consent * Age ≥ 18 years * Diagnosed with cancer * Prescribed CANKADO PRO-React Onco Exclusion Criteria: * Lack of consent to study participation or lack of patient's ability to consent * Enrolled in this trial within a further treatment
Where this trial is running
Moers and 3 other locations
- Onkologische Praxis Moers — Moers, Germany (RECRUITING)
- Ev. Krankenhaus Bethesda Praxis für gynäkologische Onkologie — Mönchengladbach, Germany (NOT_YET_RECRUITING)
- Schwerpunktpraxis für Hämatologie und Onkologie — Soest, Germany (RECRUITING)
- Hämatologisch-Onkologische Schwerpunktpraxis - Novum medicum — Würzburg, Germany (RECRUITING)
Study contacts
- Study coordinator: Christian Tonk, MSc.
- Email: c.tonk@cankado.com
- Phone: +4922142915300
How to participate
- Review the eligibility criteria above with your treating physician.
- Visit the official trial page on ClinicalTrials.gov for the most current contact information and recruitment status.
- Contact the listed study coordinator or principal investigator to request pre-screening. Pre-screening is free and never obligates you to enroll.
Conditions: Cancer, Artificial Intelligence