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Active, Not Recruiting

NCT Number: NCT04879563

Artificial Intelligence Supporting CAncer Patients Across Europe - the ASCAPE Project

ASCAPE (Artificial intelligence Supporting CAncer Patients across Europe) is a collaborative research project involving 15 partners from 7 countries, including academic medical centers, SMEs (small and medium-sized enterprises), research centers and universities, aiming to leverage the recent advances in Big Data and AI (Artificial Intelligence) to support cancer patients' Quality of Life (QoL) and health status. Specifically, ASCAPE aims to provide personalized- and AI-based predictions for QoL issues in breast- and prostate cancer patients as well as suggest potential interventions to their physicians.

This project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 875351.

Active, Not Recruiting

This study is active but is not currently recruiting participants.

Key information

Conditions

Breast Cancer Breast Diseases Breast Neoplasms Genital Diseases Genital Diseases, Male Genital Neoplasms, Male Male Urogenital Diseases Neoplasms Neoplasms by Site Prostate Cancer Prostatic Diseases Prostatic Neoplasms Quality of Life Skin Diseases Skin and Connective Tissue Diseases Survivorship Toxicity Urogenital Diseases Urogenital Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Interventional

Phase

Phase 2

Primary location

Urology Department, Sismanogleio General Hospital, Athens, Greece

Loading trial locations.

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

The patient selection process varies among the different study sites. Three Hospitals (Sismanogleio General Hospital Athens (SGHA), Örebro University Hospital (ÖUH), Uppsala University Hospital (UUH)) will include patients with newly diagnosed breast- (ÖUH, UUH) or prostate cancer (SGHA, ÖUH) who are eligible for curative treatment with surgery (breast cancer in ÖUH and UUH; prostate cancer in NKUA) or radiotherapy (prostate cancer; ÖUH).

One Hospital (Barcelona) will include breast cancer survivors (at least 12 months after surgery or chemotherapy) with follow-up through the Hospital.

Finally, CareAcross will include patients with breast- or prostate cancer through its online platform for patients seeking for the CareAcross services.

Inclusion criteria

(breast cancer; ORB and Uppsala):

  • breast cancer diagnosis
  • no clinical evidence of metastatic disease
  • able for curative treatment with surgery with or without oncological treatment.

Inclusion criteria

(breast cancer; Barcelona)

  • prior early breast cancer who are at follow-up with at least 12 months after surgery or chemotherapy (whichever occurred last).

Inclusion criteria

(breast cancer; CareAcross)

  • breast cancer diagnosis (as per self-reported) irrespective of stage and treatment.

Inclusion criteria

(prostate cancer; SGHA and ORB)

  • proostate cancer diagnosis
  • no clinical evidence of metastatic disease
  • able for curative treatment with surgery with or without oncological treatment (SGHA) or radiotherapy (with or without prior surgery) irrespectively the type of radiotherapy (external radiotherapy, brachytherapy, or combination).

Inclusion criteria

(prostate cancer; CareAcross)

  • prostate cancer diagnosis (as per self-reported) irrespective of stage and treatment.

Exclusion criteria

(common in all study sites):

  • inability to give informed consent
  • inability / no access to smartphones, applications or internet services
  • patients with known medical history of allergy to the wearable material.

Treatment and study plan

ASCAPE-based follow-up strategy

Other

Follow-up through ASCAPE platform including AI-based predictions for health-related QoL issues and suggestions for personalized interventions depending on the type of QoL issue that needs to be tackled.

The ASCAPE-based follow-up strategy includes follow-up through validated QoL questionnaires, wearables for capturing active monitoring data, and mobile apps for answering the questionnaires and capturing potential health-related issues.

Primary outcomes

  1. Patients' experience using ASCAPE-based follow-up

    Time frame: At the end of intervention (month 12)

    Patients' experience to be followed with the help of an AI-based system per se, patients' satisfaction with this type of follow-up, potential barriers and facilitators of using wearables during follow-up, and motivation for following interventions based on AI-based follow-up

Secondary outcomes

  1. Patients' engagement to ASCAPE-based follow-up

    Time frame: Every three months until the end of intervention (12 months)

    Number of questionnaires submitted per patients; total time that the patients used the wearables

  2. Patients' adherence to AI-based proposed intervention

    Time frame: Every three months until the end of intervention (12 months)

  3. Assessment of health-related QoL over time

    Time frame: Every three months until the end of intervention (12 months)

  4. Physicians' views and experience regarding ASCAPE-based follow-up in terms of implementation into clinical practice

    Time frame: At the end of intervention (month 12)

    The following aspects will be considered: improvement in patient-doctor relationship; AI-based follow-up's efficiency to capture relevant QoL issues on time; changes in management or referrals made due to AI-based predictions; usefulness of the information provided by AI-based models; acceptability of integrating AI-based follow-up into clinical practice; assessment of the time needed to use AI-based follow-up in clinical practice

  5. Physicians' views and experience regarding ASCAPE-based follow-up in terms of interaction

    Time frame: At the end of intervention (month 12)

    This outcome includes issues related to the interaction between the AI-based follow-up platform and physicians as usability, accessibility, and qualitative assessment of the interface.

  6. Physicians' experience in using ASCAPE-based follow-up

    Time frame: At the end of intervention (month 12)

    This outcome includes issues related to trustworthiness, how confident physicians are regarding the reliability of AI-based follow-up, and psychological aspects in using an AI-based platform in clinical practice as perceived substitution crisis and behavioural intention.

Sponsors and collaborators

Lead sponsor

Region Örebro County

Other

Collaborators

  • ATOS
  • Arthur's Legal
  • CareAcross
  • DFKI - German Research Center for Artificial Intelligence
  • FORTH - Foundation for Research and Technology Hellas
  • Fundacio Clinic Barcelona
  • Fundacion iSYS
  • Intrasoft
  • National and Kapodistrian University of Athens
  • Siemens Corporation, Corporate Technology
  • Sphynx Technology Solutions AG
  • UBITECH
  • University of Novi Sad
  • University of Patras

Registry information

Acronym: ASCAPE

Important dates

Study start
2021
Primary completion
2024
Study completion
2025
First posted
May 10, 2021
Registry last updated
Nov 19, 2024

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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