OMCAT: One Million Cancer Treatment Months

Sponsor

Cankado Service GmbH (Industry)

Overall Status

Recruiting

CT.gov ID

NCT04531995

Collaborator

(none)

166,000

Enrollment

Locations

Anticipated Duration (Months)

41500

Patients Per Site

1038.8

Patients Per Site Per Month

Study Details

Study Description

Brief 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.

Condition or Disease	Intervention/Treatment	Phase
Cancer	Device: CANKADO PRO-React Onco

Detailed 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 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.

Study Design

Study Type:

Observational [Patient Registry]

Anticipated Enrollment :

166000 participants

Observational Model:

Cohort

Time Perspective:

Prospective

Official Title:

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

Actual Study Start Date :

Aug 3, 2022

Anticipated Primary Completion Date :

Dec 1, 2025

Anticipated Study Completion Date :

Dec 1, 2025

Outcome Measures

Primary Outcome Measures

Health Status [6 months]
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)
Complaints/Symptoms [6 months]
Assessed using a question set aligned with the PRO-CTCAE and CTCAE (answered by patients)
Presence or Absence of SAEs [6 months]
yes/no (answered by physician)
Presence or Absence of dosis reductions [6 months]
yes/no (answered by physician)
Presence or Absence of treatment interruptions [6 months]
yes/no (answered by physician)
Presence or Absence of disease progression [6 months]
yes/no (answered by physician)
Presence or Absence of disease regression [6 months]
yes/no (answered by physician)
Presence or Absence of death [6 months]
yes/no (answered by physician)

Secondary Outcome Measures

Cancer type [6 months]
according to ICD classification
Patient Typology [6 months]
According to Bloem et al (PMID: 32771005)
Timepoints of patient documentation [6 months]
The timepoints at which a patient uses the CANKADO System to document patient-reported outcomes are retrieved from the system including date and time
Frequency of patient documentation [6 months]
The frequency at which a patient uses the CANKADO System to document patient-reported outcomes are calculated using the timepoints of patient documentation

Eligibility Criteria

Criteria

Ages Eligible for Study:

18 Years and Older

Sexes Eligible for Study:

All

Accepts Healthy Volunteers:

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

Contacts and Locations

Locations

	Site	City	Country	Postal Code
1	Onkologische Praxis Moers	Moers	Germany	47441
2	Ev. Krankenhaus Bethesda Praxis für gynäkologische Onkologie	Mönchengladbach	Germany	41061
3	Schwerpunktpraxis für Hämatologie und Onkologie	Soest	Germany	59494
4	Hämatologisch-Onkologische Schwerpunktpraxis - Novum medicum	Würzburg	Germany	97080

Sponsors and Collaborators

Cankado Service GmbH

Investigators

Study Director: Timo Schinköthe, PhD, Cankado Service GmbH

Study Documents (Full-Text)

None provided.

More Information

Publications

None provided.

Responsible Party:

Cankado Service GmbH

ClinicalTrials.gov Identifier:

NCT04531995

Other Study ID Numbers:

CAN-20-01

First Posted:

Aug 31, 2020

Last Update Posted:

Aug 25, 2022

Last Verified:

Aug 1, 2022

Studies a U.S. FDA-regulated Drug Product:

Studies a U.S. FDA-regulated Device Product:

Keywords provided by Cankado Service GmbH

Artificial Intelligence

Study Results

No Results Posted as of Aug 25, 2022