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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.
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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Clinical Decision Aid Group | In this group, physicians will use standard care plus the clinical decision aid. |
| |
| Control Group | In this group, physicians will use standard care only. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Clinical Decision Aid | Other | The clinical decision aid tool will be used at the subject's first visit (Week 0), Week 12 and Week 24. |
|
| Measure | Description | Time Frame |
|---|---|---|
| Medication use | The number of subjects in which medication use pursued is consistent with current medical society recommendations appropriate for the subject. | Week 0 |
| Medication use | The number of subjects in which medication use pursued is consistent with current medical society recommendations appropriate for the subject. | Week 12 |
| Medication use | The number of subjects in which medication use pursued is consistent with current medical society recommendations appropriate for the subject. | Week 24 |
| Imaging surveillance | The number of subjects in which imaging surveillance pursued is consistent with current medical society recommendations appropriate for the subject. | Week 0 |
| Imaging surveillance | The number of subjects in which imaging surveillance pursued is consistent with current medical society recommendations appropriate for the subject. | Week 12 |
| Imaging surveillance | The number of subjects in which imaging surveillance pursued is consistent with current medical society recommendations appropriate for the subject. | Week 24 |
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Inclusion Criteria:
Exclusion Criteria:
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Cancer survivors at intermediate, high, or very high risk for developing cardiovascular disease will pursue a cardio-oncology visit.
| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Yee Chung Cheng, MD | Contact | 414-805-4600 | ycheng@mcw.edu |
| Name | Affiliation | Role |
|---|---|---|
| Yee Chung Cheng, MD | Medical College of Wisconsin | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Froedtert & the Medical College of Wisconsin | Milwaukee | Wisconsin | 53226 | United States |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 36691060 | Background | 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. | |
| 41378455 |
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| Standard Care | Other | Cardiology clinic visits will take place at the subjects first visit (Week 0), Week 12 and Week 24. |
|
| Derived |
| Brown 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. |
| 37891699 | Derived | Brown 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. |
| ID | Term |
|---|---|
| D006333 | Heart Failure |
| D003324 | Coronary Artery Disease |
| D058729 | Peripheral Arterial Disease |
| D007511 | Ischemia |
| D006973 | Hypertension |
| D003920 | Diabetes Mellitus |
| D009202 | Cardiomyopathies |
| D066126 | Cardiotoxicity |
| D009369 | Neoplasms |
| ID | Term |
|---|---|
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
| D003327 | Coronary Disease |
| D017202 | Myocardial Ischemia |
| D001161 | Arteriosclerosis |
| D001157 | Arterial Occlusive Diseases |
| D014652 | Vascular Diseases |
| D050197 | Atherosclerosis |
| D016491 | Peripheral Vascular Diseases |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D044882 | Glucose Metabolism Disorders |
| D008659 | Metabolic Diseases |
| D009750 | Nutritional and Metabolic Diseases |
| D004700 | Endocrine System Diseases |
| D064420 | Drug-Related Side Effects and Adverse Reactions |
| D064419 | Chemically-Induced Disorders |
| D011832 | Radiation Injuries |
| D014947 | Wounds and Injuries |
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| ID | Term |
|---|---|
| D059039 | Standard of Care |
| ID | Term |
|---|---|
| D019984 | Quality Indicators, Health Care |
| D011787 | Quality of Health Care |
| D006298 | Health Services Administration |
| D017530 | Health Care Quality, Access, and Evaluation |
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