One Million Cancer Treatment Months

Cancer Clinical Trial

— OMCAT  

Official title:

Development of an Artificial Intelligence-based Incident Prediction Algorithm to Improve Cancer Patient Care and Patient Safety

Clinical Trial Details — Status: Recruiting

Administrative data

• NCT number: NCT04531995
• Other study ID #: CAN-20-01
• Status: Recruiting
• Start date: August 3, 2022
• Est. completion date: December 2025

Study information

• Verified date: September 2022
• Source: Cankado GmbH
• Contact: Christian Tonk, MSc.
• Phone: +4922142915300
• Email: c.tonk[@]cankado.com
• Is FDA regulated: No
• Study type: Observational [Patient Registry]

Clinical Trial Summary

The OMCAT Register aims to provide learning databases in cancer comprising both PRO data using PRO-React and "ground truth" (outcome data verified by the physician during patient examinations). Intelligent learning and knowledge engineering procedures will utilize this PRO data to provide high-quality event prediction algorithms. The ground-truth data enables so-called "supervised learning" techniques of artificial intelligence, because predicted events can be verified with a high level of certainty from ground-truth data.

Description:

The next generation of PRO-React by CANKADO is designed to predict impending incident threats at an earlier stage than previously feasible and -- by more timely intervention -- help physicians to eliminate or mitigate the severity of an unfavourable event, reduce the required intensity of countermeasures, or otherwise reduce patient risks.

A highly reliable identification of situations classified as "low-risk" by CANKADO could also enable a more focused utilization of resources as well as enhanced patient comfort and decreased stress, e.g., due to less frequent monitoring visits or reduced need for invasive diagnostics.

The OMCAT Register aims to provide learning databases in cancer comprising both PRO data using PRO-React and "ground truth" (outcome data verified by the physician during patient examinations). Intelligent learning and knowledge engineering procedures will utilize this PRO data to provide high-quality event prediction algorithms. The ground-truth data enables so-called "supervised learning" techniques of artificial intelligence, because predicted events can be verified with a high level of certainty from ground-truth data.

The PRO data of a patient provide what is known in engineering, physics, and statistics as "time series" of observations. The unique feature of PRO time series for applications in cancer is the very high "sampling frequency" (e.g., daily or better) compared to examinations, which generally occur at fixed, and much less frequent intervals. Prediction algorithms based on PRO data would thus be ideally suited to reduce the delay in detecting events, for example, by triggering physician appointments or indicating the need for more intensive medical diagnostics.

Recruitment information / eligibility

• Status: Recruiting
• Enrollment: 166000
• Est. completion date: December 2025
• Est. primary completion date: December 2025
• Accepts healthy volunteers: No
• Gender: All
• Age group: 18 Years and older

Eligibility

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

Related Conditions & MeSH terms

• Cancer

Intervention

Device:
• CANKADO PRO-React Onco
CANKADO PRO-React Onco is approved as class I medical device within the European Union (registration number DE /CA59 /371/2020-R/Hd) and is compliant with the FDA classification for Mobile Medical Devices (2015) Appendix B. The purpose of CANKADO PRO-React Onco is to be an automated digital support for patients to help them decide how urgent it is to contact the attending physician based on the symptoms they independently record in the system. It supports patients with cancer under systemic, anti-tumor or anti-hormonal therapy in adjuvant, neoadjuvant, post-neoadjuvant or palliative situations. It is unsuitable for patients undergoing radiotherapy, cell and gene therapy, surgical procedures or alternative healing methods.

Locations

Country	Name	City	State
Germany	Onkologische Praxis Moers	Moers
Germany	Ev. Krankenhaus Bethesda Praxis für gynäkologische Onkologie	Mönchengladbach
Germany	Schwerpunktpraxis für Hämatologie und Onkologie	Soest
Germany	Hämatologisch-Onkologische Schwerpunktpraxis - Novum medicum	Würzburg

Sponsors (1)

Lead Sponsor	Collaborator
Cankado GmbH

Country where clinical trial is conducted

Germany, 

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Health Status	Using the EuroQol-visual analogue scale, abbreviated as EQ-VAS Scale, containing values between 100 (best imaginable health) and 0 (worst imaginable health), (answered by patients)	6 months
Primary	Complaints/Symptoms	Assessed using a question set aligned with the PRO-CTCAE and CTCAE (answered by patients)	6 months
Primary	Presence or Absence of SAEs	yes/no (answered by physician)	6 months
Primary	Presence or Absence of dosis reductions	yes/no (answered by physician)	6 months
Primary	Presence or Absence of treatment interruptions	yes/no (answered by physician)	6 months
Primary	Presence or Absence of disease progression	yes/no (answered by physician)	6 months
Primary	Presence or Absence of disease regression	yes/no (answered by physician)	6 months
Primary	Presence or Absence of death	yes/no (answered by physician)	6 months
Secondary	Cancer type	according to ICD classification	6 months
Secondary	Patient Typology	According to Bloem et al (PMID: 32771005)	6 months
Secondary	Timepoints of patient documentation	The timepoints at which a patient uses the CANKADO System to document patient-reported outcomes are retrieved from the system including date and time	6 months
Secondary	Frequency of patient documentation	The frequency at which a patient uses the CANKADO System to document patient-reported outcomes are calculated using the timepoints of patient documentation	6 months