One Million Cancer Treatment Months (OMCAT)

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

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.

Study Overview

• Status: Recruiting
• Conditions: Cancer
• Intervention / Treatment: 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 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.

• Study Type: Observational
• Enrollment (Anticipated): 166000

Contacts and Locations

• Study Contact: Name: Christian Tonk, MSc.; Phone Number: +4922142915300; Email: c.tonk@cankado.com

Study Locations

• Germany
  • Moers, Germany, 47441
    • Recruiting
    • Onkologische Praxis Moers
  • Mönchengladbach, Germany, 41061
    • Not yet recruiting
    • Ev. Krankenhaus Bethesda Praxis für gynäkologische Onkologie
  • Soest, Germany, 59494
    • Recruiting
    • Schwerpunktpraxis für Hämatologie und Onkologie
  • Würzburg, Germany, 97080
    • Recruiting
    • Hämatologisch-Onkologische Schwerpunktpraxis - Novum medicum

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: 18 years and older (Adult, Older Adult)
• Accepts Healthy Volunteers: No
• Genders Eligible for Study: All

• Sampling Method: Non-Probability Sample

Study Population

Cancer Patients under systemic, anti-tumor or anti-hormonal therapy in adjuvant, neoadjuvant, post-neoadjuvant or palliative situations with prescribed CANKADO PRO-React Onco will be enrolled.

Description

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

Study Plan

How is the study designed?

Design Details

• Observational Models: Cohort
• Time Perspectives: Prospective

What is the study measuring?

Primary Outcome Measures

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

Secondary Outcome Measures

Outcome Measure	Measure Description	Time Frame
Cancer type	according to ICD classification	6 months
Patient Typology	According to Bloem et al (PMID: 32771005)	6 months
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
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

Collaborators and Investigators

• Sponsor: Cankado GmbH
• Investigators: Study Director: Timo Schinköthe, PhD, Cankado GmbH

Study record dates

Study Major Dates

• Study Start (Actual): August 3, 2022
• Primary Completion (Anticipated): December 1, 2025
• Study Completion (Anticipated): December 1, 2025

Study Registration Dates

• First Submitted: August 21, 2020
• First Submitted That Met QC Criteria: August 25, 2020
• First Posted (Actual): August 31, 2020

Study Record Updates

• Last Update Posted (Actual): September 27, 2022
• Last Update Submitted That Met QC Criteria: September 26, 2022
• Last Verified: September 1, 2022

More Information

Terms related to this study

• Keywords: Artificial Intelligence
• Other Study ID Numbers: CAN-20-01

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No