Clinical trial · Observational
PAtient Similarity for Decision-Making in Prevention of Cardiovascular Toxicity (PACT): A Feasibility Study
NCT05377320CI-TRIAL-00096547not yet recruitingClinicalTrials.gov clinicaltrialsProvenance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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.
Conditions
Conditions (8)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Cardiomyopathies | — | UNRESOLVED | — |
| Cardiotoxicity | — | UNRESOLVED | — |
| Coronary Artery Disease | — | UNRESOLVED | — |
| Diabetes Mellitus | — | UNRESOLVED | — |
| Heart Failure | — | UNRESOLVED | — |
| Hypertension | — | UNRESOLVED | — |
| Ischemia | — | UNRESOLVED | — |
| Peripheral Artery Disease | — | UNRESOLVED | — |
Interventions
Interventions (2)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Clinical Decision Aid | Other | — | UNRESOLVED |
| Standard Care | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- label
- Clinical Decision Aid Group
- description
- In this group, physicians will use standard care plus the clinical decision aid.
- interventionNames
- Other: Clinical Decision Aid
- label
- Control Group
- description
- In this group, physicians will use standard care only.
- interventionNames
- Other: Standard Care
Primary outcomes (6)
- measure
- Medication use
- timeFrame
- Week 0
- description
- The number of subjects in which medication use pursued is consistent with current medical society recommendations appropriate for the subject.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
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.
References
Publications (3)
- BACKGROUNDBrown 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. PMID 36691060
- DERIVEDBrown SA, Fang MZ, Sparapani R, Zhou Y, Osinski K, Taylor B, Yu D, Blessing J, Shah R, Collier P, BagheriMohamadiPour M, Zhang J, Kothari A, Echefu G, Rickards J, Otto C, Sanchez Z, Olson J, Arruda-Olson A, Cheng YC, Cheng F; Cardio-Oncology Artificial Intelligence Informatics and Precision Equity, and Patient Similarity Algorithms in the Prevention of Cardiovascular Toxicity Research Team Investigators. PrevCardioOncAI: Machine Learning Algorithms for Predicting Cardiovascular Disease in Cancer Survivors. J Am Heart Assoc. 2025 Dec 16;14(24):e030363. doi: 10.1161/JAHA.123.030363. Epub 2025 Dec 11. PMID 41378455
- DERIVEDBrown SA, Hamid A, Pederson E, Bs AH, Maddula R, Goodman R, Lamberg M, Caraballo P, Noseworthy P, Lukan O, Echefu G, Berman G, Choudhuri I; Cardio-Oncology Artificial Intelligence Informatics & Precision Equity (CAIPE) and Patient Similarity Algorithms in the Prevention of Cardiovascular Toxicity (PACT) Research Team Investigators. Simplified rules-based tool to facilitate the application of up-to-date management recommendations in cardio-oncology. Cardiooncology. 2023 Oct 27;9(1):37. doi: 10.1186/s40959-023-00179-w. PMID 37891699