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| Name | Class |
|---|---|
| Illumina, Inc. | INDUSTRY |
| Optum, Inc. | INDUSTRY |
| Quest Diagnostics-Nichols Insitute | INDUSTRY |
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This study will investigate the role of polygenic risk scores (PRS) in preventive health.
This study will investigate the role of polygenic risk scores (PRS) in preventive health. Specifically, the purpose of this study is to determine whether knowledge of the degree of coronary artery disease (CAD) genetic risk or glaucoma genetic risk, as measured and conveyed by a PRS, influences patient and physician decision-making as well as clinical outcomes during short-term (6-month / 2-year) and long-term (3-year / 5-year) follow-up. A CAD and glaucoma PRS will be calculated for all study participants, with participants randomized to receiving either their CAD or glaucoma PRS. This study design allows for causal attribution of preventive actions and clinical outcomes to the receipt and degree of genetic risk. The design is informed by a pilot (MyGeneRank) and phase 1 (PEPRS first phase) study, with the key extensions being the addition of randomization and increasing the study population size to power causal association with long-term, hard clinical outcomes.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Subjects identified by Optum Health | Experimental | 10,000 individuals identified by Optum Health as likely meeting inclusion criteria by claims analysis. |
|
| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| Genetic risk assessment | Behavioral | A coronary artery disease (CAD) and glaucoma polygenic risk scores (PRS) will be calculated for all study participants, with participants randomized to receiving either their CAD or glaucoma PRS. |
| Measure | Description | Time Frame |
|---|---|---|
| Composite MACE in intermediate to high clinical risk population | Incident MACE. Binary outcome measured at 5-years post-enrollment by EHR analysis. An interim analysis will be performed at 3-years. MACE is defined as arterial revascularization or hospitalization for unstable angina, myocardial infarction, stroke, or death from cardiovascular causes. The rate of incident MACE will be compared across CAD vs glaucoma arms overall in individuals achieving a baseline PCE≥7.5%. | 5 years post enrollment |
| Measure | Description | Time Frame |
|---|---|---|
| Composite MACE in high PRS | Incident MACE. Binary outcome measured at 3- and 5-years post-enrollment by EHR analysis. The rate of incident MACE will be compared across high CAD PRS individuals receiving vs blinded to their genetic risk in individuals achieving a baseline PCE≥5%. | 5 years post enrollment |
| MACE Components |
| Measure | Description | Time Frame |
|---|---|---|
| Lifestyle changes | Adoption of Healthy Lifestyle. Binary outcomes derived from baseline and 6-months post-enrollment by survey-based self-report. Adoption of a healthy lifestyle is defined among individuals who self-report non-smoking, active lifestyle, or healthy diet at 6-months after initially reporting the absence of any of these healthy behaviors at baseline. These factors will be analyzed as separate binary outcomes and as a composite healthy lifestyle factor defined by an increase in the number of healthy lifestyle factors self-reported at 6-months vs baseline |
Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Ali Torkamani, PhD | Contact | 858-784-2082 | atorkama@scripps.edu |
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| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 30894319 | Background | Arnett DK, Blumenthal RS, Albert MA, Buroker AB, Goldberger ZD, Hahn EJ, Himmelfarb CD, Khera A, Lloyd-Jones D, McEvoy JW, Michos ED, Miedema MD, Munoz D, Smith SC Jr, Virani SS, Williams KA Sr, Yeboah J, Ziaeian B. 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines. J Am Coll Cardiol. 2019 Sep 10;74(10):1376-1414. doi: 10.1016/j.jacc.2019.03.009. Epub 2019 Mar 17. | |
| 20167359 |
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Research records with patient identification will be kept for 6 years after study completion. The collected data and related de-identified health information may be kept indefinitely. Record retention will comply with the specific requirements of the Scripps IRB (i.e., Scripps Research must keep HIPAA form for at least 6 years after study completion).
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| ID | Term |
|---|---|
| D003324 | Coronary Artery Disease |
| D005901 | Glaucoma |
| ID | Term |
|---|---|
| D003327 | Coronary Disease |
| D017202 | Myocardial Ischemia |
| D006331 | Heart Diseases |
| D002318 | Cardiovascular Diseases |
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Incident MACE components (arterial revascularization or hospitalization for unstable angina, myocardial infarction, stroke, or death from cardiovascular causes). Binary outcomes measured at 3- and 5-years post-enrollment by EHR analysis. The rate of each incident MACE component will be compared across CAD vs glaucoma arms overall in individuals achieving a baseline PCE≥7.5%. |
| 5 years post enrollment |
| Treated Glaucoma | Incident glaucoma diagnosis with initiation of treatment. Binary outcome measured at 3- and 5-years post-enrollment by EHR analysis. Incident treated glaucoma is defined as any individual with a claim for ophthalmic surgery (laser trabeculoplasty, laser peripheral iridotomy, cycloablation) or a prescription ophthalmic solution with one or a combination of the following active ingredients: prostaglandin analogs (tafluprost, bimatoprost, latanoprostene, travaprost, latanoprost), beta blockers (timolol, levobunolol, metipranolol, betaxolol, carteolol), alpha agonists (brimonidine, apraclonidine), cholinergic agonists (pilocarpine, carbachol), carbonic anhydrase inhibitors (methazolamide, dorzolamide, brinzolamide), and/or rho kinase inhibitor (netarsudil). The rate and age of incident glaucoma diagnosis with treatment will be compared across CAD and glaucoma arms overall, as well as across high glaucoma PRS individuals receiving vs blinded to their genetic risk. | 5 years post enrollment |
| LDL-C lowering | Adequate LDL-C lowering. Binary outcome measured at 2-, 3-, and 5-years post enrollment by EHR entry. Adequate LDL-C lowering is defined as 30% or more reduction from baseline study measured LDL-C. The rate of adequate LDL-C lowering will be compared across CAD vs glaucoma arms overall, across high CAD PRS individuals receiving vs blinded to their genetic risk, and in association with high vs low CAD PRS in individuals receiving vs blinded to their genetic risk. Within these groups, the rate of adequate LDL-C lowering will be determined in the total population, as well as subgroups stratified by baseline PCE status. PCE strata are: <5%, 5%≤PCE<7.5%, and ≥7.5%. | 5 years post enrollment |
| Statin or other lipid lowering therapy initiation or intensification | New or intensified prescriptions for statins or other LDL lowering therapy. Binary outcome measured at 6-months post-enrollment by survey-based self-report and EHR analysis. A prescription is considered new if no equivalent EHR entry exists 1-year prior to enrollment. A statin prescription is considered intensified if it changes intensity tiers (high-, moderate-, and low-intensity) as described in the 2013 ACC/AHA Guidelines on the Treatment of Blood Cholesterol12. The rate of lipid lowering therapy initiation and intensification will be compared across high CAD PRS individuals receiving vs blinded to their genetic risk, and in association with high vs low CAD PRS in individuals receiving vs blinded to their genetic risk. Within these groups, the rate of statin or other lipid lowering therapy initiation or intensification will be determined in the total population, as well as subgroups stratified by baseline PCE status. PCE strata are: <5%, 5%≤PCE<7.5%, and ≥7.5%. | 1 year post enrollment |
| Statin or other lipid lowering therapy persistence | Statin or other lipid lowering therapy prescription renewal. Binary outcome measured at 2-years post-enrollment by EHR analysis. Statin persistence is defined as prescription renewal within 60 days of the end of the duration of an index statin prescription made after study enrollment13. The rate of lipid lowering therapy persistence will be compared across high CAD PRS individuals receiving vs blinded to their genetic risk, and in association with high vs low CAD PRS in individuals receiving vs blinded to their genetic risk. Within these groups, the rate of statin or other lipid lowering therapy persistence will be determined in the total population, as well as subgroups stratified by baseline PCE status. PCE strata are: <5%, 5%≤PCE<7.5%, and ≥7.5%. | 2 years post enrollment |
| Statin or other lipid lowering therapy adherence | Statin or other lipid lowering therapy prescription possession. Binary outcome measured at 2-years post-enrollment by EHR entry. Statin adherence is defined as prescription coverage of no less than 80% of the days between the index statin prescription and the end of the 2-year follow-up period13. The rate of lipid lowering therapy adherence will be compared across high CAD PRS individuals receiving vs blinded to their genetic risk, and in association with high vs low CAD PRS in individuals receiving vs blinded to their genetic risk. Within these groups, the rate of statin or other lipid lowering therapy adherence will be determined in the total population, as well as subgroups stratified by baseline PCE status. PCE strata are: <5%, 5%≤PCE<7.5%, and ≥7.5%. | 2 years post enrollment |
| Glaucoma screening | Adoption of glaucoma screening. Binary outcome measured at 6-months and 2-years post-enrollment by self-report electronic survey. An analysis using claims and EHR data will be conducted if the degree of missingness data (due to, e.g. uncaptured optometrist visits) is no greater than 20%. The rate of glaucoma screening will be compared across high glaucoma PRS individuals receiving vs blinded to their genetic risk, and in association with high vs normal glaucoma PRS in individuals receiving vs blinded to their genetic risk. | 2 years post enrollment |
| Physician Utility | Physician confidence, perceived utility, and actions attributable to genomic testing. Measured at 6-months and 1-year by survey-based self-report. Physician utility is characterized using a survey. Analyses are descriptive. | 1 year |
| 6 months post enrollment |
| Background |
| Sattar N, Preiss D, Murray HM, Welsh P, Buckley BM, de Craen AJ, Seshasai SR, McMurray JJ, Freeman DJ, Jukema JW, Macfarlane PW, Packard CJ, Stott DJ, Westendorp RG, Shepherd J, Davis BR, Pressel SL, Marchioli R, Marfisi RM, Maggioni AP, Tavazzi L, Tognoni G, Kjekshus J, Pedersen TR, Cook TJ, Gotto AM, Clearfield MB, Downs JR, Nakamura H, Ohashi Y, Mizuno K, Ray KK, Ford I. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet. 2010 Feb 27;375(9716):735-42. doi: 10.1016/S0140-6736(09)61965-6. Epub 2010 Feb 16. |
| 24655568 | Background | Macedo AF, Taylor FC, Casas JP, Adler A, Prieto-Merino D, Ebrahim S. Unintended effects of statins from observational studies in the general population: systematic review and meta-analysis. BMC Med. 2014 Mar 22;12:51. doi: 10.1186/1741-7015-12-51. |
| 25748612 | Background | Mega JL, Stitziel NO, Smith JG, Chasman DI, Caulfield M, Devlin JJ, Nordio F, Hyde C, Cannon CP, Sacks F, Poulter N, Sever P, Ridker PM, Braunwald E, Melander O, Kathiresan S, Sabatine MS. Genetic risk, coronary heart disease events, and the clinical benefit of statin therapy: an analysis of primary and secondary prevention trials. Lancet. 2015 Jun 6;385(9984):2264-2271. doi: 10.1016/S0140-6736(14)61730-X. Epub 2015 Mar 4. |
| 27959714 | Background | Khera AV, Emdin CA, Drake I, Natarajan P, Bick AG, Cook NR, Chasman DI, Baber U, Mehran R, Rader DJ, Fuster V, Boerwinkle E, Melander O, Orho-Melander M, Ridker PM, Kathiresan S. Genetic Risk, Adherence to a Healthy Lifestyle, and Coronary Disease. N Engl J Med. 2016 Dec 15;375(24):2349-2358. doi: 10.1056/NEJMoa1605086. Epub 2016 Nov 13. |
| 27490785 | Background | Scott AW, Bressler NM, Ffolkes S, Wittenborn JS, Jorkasky J. Public Attitudes About Eye and Vision Health. JAMA Ophthalmol. 2016 Oct 1;134(10):1111-1118. doi: 10.1001/jamaophthalmol.2016.2627. |
| 24974815 | Background | Tham YC, Li X, Wong TY, Quigley HA, Aung T, Cheng CY. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. Ophthalmology. 2014 Nov;121(11):2081-90. doi: 10.1016/j.ophtha.2014.05.013. Epub 2014 Jun 26. |
| 24325017 | Background | Moyer VA; U.S. Preventive Services Task Force. Screening for glaucoma: U.S. Preventive Services Task Force Recommendation Statement. Ann Intern Med. 2013 Oct 1;159(7):484-9. doi: 10.7326/0003-4819-159-6-201309170-00686. |
| 28783162 | Background | Wang K, Gaitsch H, Poon H, Cox NJ, Rzhetsky A. Classification of common human diseases derived from shared genetic and environmental determinants. Nat Genet. 2017 Sep;49(9):1319-1325. doi: 10.1038/ng.3931. Epub 2017 Aug 7. |
| 29785010 | Background | Khawaja AP, Cooke Bailey JN, Wareham NJ, Scott RA, Simcoe M, Igo RP Jr, Song YE, Wojciechowski R, Cheng CY, Khaw PT, Pasquale LR, Haines JL, Foster PJ, Wiggs JL, Hammond CJ, Hysi PG; UK Biobank Eye and Vision Consortium; NEIGHBORHOOD Consortium. Genome-wide analyses identify 68 new loci associated with intraocular pressure and improve risk prediction for primary open-angle glaucoma. Nat Genet. 2018 Jun;50(6):778-782. doi: 10.1038/s41588-018-0126-8. Epub 2018 May 21. |
| 31959993 | Background | Craig JE, Han X, Qassim A, Hassall M, Cooke Bailey JN, Kinzy TG, Khawaja AP, An J, Marshall H, Gharahkhani P, Igo RP Jr, Graham SL, Healey PR, Ong JS, Zhou T, Siggs O, Law MH, Souzeau E, Ridge B, Hysi PG, Burdon KP, Mills RA, Landers J, Ruddle JB, Agar A, Galanopoulos A, White AJR, Willoughby CE, Andrew NH, Best S, Vincent AL, Goldberg I, Radford-Smith G, Martin NG, Montgomery GW, Vitart V, Hoehn R, Wojciechowski R, Jonas JB, Aung T, Pasquale LR, Cree AJ, Sivaprasad S, Vallabh NA; NEIGHBORHOOD consortium; UK Biobank Eye and Vision Consortium; Viswanathan AC, Pasutto F, Haines JL, Klaver CCW, van Duijn CM, Casson RJ, Foster PJ, Khaw PT, Hammond CJ, Mackey DA, Mitchell P, Lotery AJ, Wiggs JL, Hewitt AW, MacGregor S. Multitrait analysis of glaucoma identifies new risk loci and enables polygenic prediction of disease susceptibility and progression. Nat Genet. 2020 Feb;52(2):160-166. doi: 10.1038/s41588-019-0556-y. Epub 2020 Jan 20. |
| 24239923 | Background | Stone NJ, Robinson JG, Lichtenstein AH, Bairey Merz CN, Blum CB, Eckel RH, Goldberg AC, Gordon D, Levy D, Lloyd-Jones DM, McBride P, Schwartz JS, Shero ST, Smith SC Jr, Watson K, Wilson PW; American College of Cardiology/American Heart Association Task Force on Practice Guidelines. 2013 ACC/AHA guideline on the treatment of blood cholesterol to reduce atherosclerotic cardiovascular risk in adults: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. J Am Coll Cardiol. 2014 Jul 1;63(25 Pt B):2889-934. doi: 10.1016/j.jacc.2013.11.002. Epub 2013 Nov 12. No abstract available. |
| 23774515 | Background | Raebel MA, Schmittdiel J, Karter AJ, Konieczny JL, Steiner JF. Standardizing terminology and definitions of medication adherence and persistence in research employing electronic databases. Med Care. 2013 Aug;51(8 Suppl 3):S11-21. doi: 10.1097/MLR.0b013e31829b1d2a. |
| D001161 |
| Arteriosclerosis |
| D001157 | Arterial Occlusive Diseases |
| D014652 | Vascular Diseases |
| D009798 | Ocular Hypertension |
| D005128 | Eye Diseases |