Clinical trial NCT05377320: PAtient Similarity for Decision-Making in Prevention of Cardiovascular Toxicity (PACT): A Feasibility Study
Official title: PAtient Similarity for Decision-Making in Prevention of Cardiovascular Toxicity (PACT): A Feasibility Study
Study type: OBSERVATIONAL
Overall status: NOT_YET_RECRUITING
Conditions: Heart Failure
Coronary Artery Disease
Peripheral Artery Disease
Ischemia
Hypertension
Diabetes Mellitus
Cardiomyopathies
Cardiotoxicity
Keywords: clinical decision aid
cancer
cardiac dysfunction
cardio-oncology
artificial intelligence
machine learning
adverse events
Lead sponsor: Medical College of Wisconsin
Sponsor class: OTHER
First posted: 2022-05-17
Enrollment: 60
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Observational model: COHORT
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Cancer survivors at intermediate, high, or very high risk for developing cardiovascular disease will pursue a cardio-oncology visit.

Brief summary: This is a single-center, double-arm, open-label, randomized feasibility study that will determine whether a novel clinical decision aid accessed via the electronic health record will be acceptable to both cancer survivors and their cardiologists, will favorably impact appropriate medication use and cardiac imaging surveillance, and will improve clinician and patient decision-making, perception, and behavior towards cardioprotective medication usage and cardiovascular disease imaging utilization.

Detailed description: For this feasibility study, the researchers will create the clinical decision aid and test the central hypothesis that this novel clinical decision aid accessed via the electronic health record will be acceptable to both cancer survivors and their cardiologists and will favorably impact appropriate medication use and cardiac imaging surveillance. The hypothesis is supported by preliminary data suggesting that an initial and rudimentary version of the clinical aid increases appropriate medication use and imaging follow-up in cardio-oncology patients. Success will be determined by ≥85% of clinic visits using the clinical decision aid resulting in pursuit of medication use and cardiac imaging surveillance patterns commensurate with recommendations specific to cancer survivors, with overall rates the same or higher than the group without the clinical decision aid, as well as overall favorable patient and physician focus group comments and survey responses.

Eligibility criteria: Inclusion Criteria:

1. Patients ≥18 years with a history of cancer.
2. Have not previously visited a cardiologist to assess cardiovascular risk after cancer diagnosis.
3. Clinically at intermediate, high, or very high risk for cardiovascular diseases determined based on imprecise clinical risk models, such as those used for cardiac dysfunction.
4. Ability to understand a written informed consent form, and willing to sign it prior to study registration.

Exclusion Criteria:

1. Patient \<18 years.
2. Without a personal history of cancer.
3. Existing cardiomyopathy diagnosed after cancer diagnosis.
4. Documented cognitive impairment.
5. Patient or patient representative who is unable and unwilling to sign the informed consent form.

Primary outcomes:
measure: Medication use
timeFrame: Week 0
measure: Medication use
timeFrame: Week 12
measure: Medication use
timeFrame: Week 24
measure: Imaging surveillance
timeFrame: Week 0
measure: Imaging surveillance
timeFrame: Week 12
measure: Imaging surveillance
timeFrame: Week 24
Secondary outcomes:
Other outcomes:
Locations:
city: Milwaukee
country: United States
facility: Froedtert & the Medical College of Wisconsin
state: Wisconsin
Study officials:
affiliation: Medical College of Wisconsin
name: Yee Chung Cheng, MD
role: PRINCIPAL_INVESTIGATOR
References:
citation: Brown SA, Chung BY, Doshi K, Hamid A, Pederson E, Maddula R, Hanna A, Choudhuri I, Sparapani R, Bagheri Mohamadi Pour M, Zhang J, Kothari AN, Collier P, Caraballo P, Noseworthy P, Arruda-Olson A; Cardio-Oncology Artificial Intelligence Informatics and Precision Equity (CAIPE) Research Team Investigators. Patient similarity and other artificial intelligence machine learning algorithms in clinical decision aid for shared decision-making in the Prevention of Cardiovascular Toxicity (PACT): a feasibility trial design. Cardiooncology. 2023 Jan 23;9(1):7. doi: 10.1186/s40959-022-00151-0.