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Improving Cardiovascular Health Through American Heart Association Funded Research

Disclosure: None
Pub Date: Thursday, July 6, 2017
Author: Steven D. Barger, PhD
Affiliation: Department of Psychological Sciences, Northern Arizona University, Flagstaff, Ariz.


Liaw L, Freedman JE, Becker LB, Mehta NN, Liscum L; on behalf of the Peer Review Subcommittee of the American Heart Association National Research Committee; Council on Cardiovascular and Stroke Nursing; Council on Cardiovascular Radiology and Intervention; Council on Cardiovascular Surgery and Anesthesia; Council on Clinical Cardiology; Council on Genomic and Precision Medicine; Council on Hypertension; Council on Quality of Care and Outcomes Research; and Stroke Council. Peer review practices for evaluating biomedical research grants: a scientific statement from the American Heart Association [published online ahead of print July 6, 2017]. Circ Res. doi: 10.1161/RES.0000000000000158.

Article Text

“Funding research is a cornerstone of the American Heart Association’s lifesaving mission. It is a pillar upon which the AHA was founded nearly a century ago. It is ingrained in our organization’s DNA, and will always be part of our ongoing legacy.”

AHA Research Programs

“We are working toward improving the cardiovascular health of all Americans by 20 percent, and reducing deaths from cardiovascular diseases and stroke by 20 percent, all by the year 2020.”

American Heart Association

Research funding at the American Heart Association (AHA) supports basic and applied research to improve cardiovascular health and reduce cardiovascular disease burden. In 2015, the AHA provided over $163 million dollars in funding to support their mission to build healthier lives free of cardiovascular diseases and stroke. AHA funds both primary research and research fellowships that support emerging scholars’ careers in cardiovascular research (AHA, 2017). This integrated approach contributes to the vigor of the CVD research enterprise and the successes of these efforts are well documented (AHA).

Despite many successes, the AHA acknowledges that many highly meritorious grants are not funded. Given limited resources how can peer review, the process by which funding decisions are made, be improved? The AHA and the Peer Review Subcommittee are to be commended for their critical evaluation of this question.1 However, the best approach to achieve AHA goals are through better alignment of research priorities with the mission. First, studies that include pragmatic clinical outcomes reflecting morbidity and mortality are most likely to achieve targeted reductions in disease burden and should be emphasized accordingly. 2 The AHA already supports this approach via the Strategically Focused Research Networks3 which explicitly require a combination of basic, clinical and population methods for funded projects. Nevertheless, this is the exception at AHA – in 2016 basic science peer review committees outnumbered clinical and outcomes research committees 3:1.1 Thus biomedical funding at AHA (and the NIH4) disproportionately support descriptive rather than etiological approaches to disease. These patterns can become entrenched and inhibit progress toward AHA’s public health goals.2 Scaffolding research that emphasizes pragmatic clinical outcomes should advance progress towards AHA 2020 targets.

Retroactive evaluation of CVD morbidity and mortality changes could be used to evaluate resource allocation in the AHA research portfolio. These would identify more efficient approaches5 as well as those initiatives that should be reconsidered.2 For example, one could imagine a population attributable risk fraction of healthier lives created or deaths averted as a result of advances made in funded research. Contextualizing this fraction in light of base rates of risk, exposure and extent of dissemination would be particularly valuable for comparing different disease targets or health improvements.6 These metrics would provide a more robust indication of the human benefit of AHA funded research.

Another means to achieve disease reduction targets is to fund a portfolio of studies that re-examine widely adopted clinical practices. These studies are needed because some practices, such as percutaneous coronary intervention for persons with stable coronary artery disease, provide no benefit compared to less expensive and less invasive medical management.7 Resources spent on ineffective treatments cannot reduce disease burden and divert resources from effective practices. This approach would fulfill one of the 12 “essential elements” of AHA research, identification of key questions that could provide extraordinary impact in science and toward Mission [emphasis added].8 Impact is particularly likely given that many clinical practices are discovered to be ineffective.9 It should be noted, however, that the impact towards mission element conflicts with another essential element, innovation. Innovative or novel research questions by definition cannot correct ineffective standards of care. Consequently, AHA funding criteria disadvantage the type of research that has strong potential to improve population health. Similarly, optimal implementation of existing therapies and disease reduction approaches are not novel but may save more lives than medical innovations.10

A crucial step in identifying and supporting good science is to mandate peer review practices that reflect current best practices in research. In their critique of peer review Liaw et al.1 recommend research reproducibility as a way to improve funding decisions. Open data, open protocols and shared analytic syntax facilitate reproducibility. Hence, peer review decisions should incorporate concrete requirements for data sharing.11 The International Committee of Medical Journal Editors have proposed sharing clinical trial data as a requirement for publication12 and, since 2015, an Open Data policy has been in force at AHA.13 However, the extent of archiving of AHA funded research is unknown as is the extent to which these archives have been utilized to reproduce research outcomes. Perhaps additional funds could be earmarked for confirmation of research outcomes using these archives. The sensitivity of research outcomes to different statistical and methodological choices can be determined through a variety of approaches14,15 Reanalysis of sponsored AHA data is also desirable as it advances another essential element of AHA research, accountability (AHA 2017).

The absence of gold standards for funding decisions is another barrier to improving peer review. Liaw et al. note the fuzzy criteria used to denote quality peer review as well as the limitations of more concrete indicators such as citation counts and number of publications. These bibliometric indices are at best surrogate markers of research quality and at worst are circular artifacts of the system.2 Bibliometric indices can be useful, however, when they are used to identify biased citation networks in grant proposals. Greenberg showed that citation bias (i.e., systematic exclusion of evidence inconsistent with a hypothesis) is present both in published manuscripts and in funded NIH grant proposals.16 This analysis also revealed distortion of prior research as well as outright invention; for example, claiming as fact something that was stated only as a hypothesis in the cited source. Thus, peer review could be improved by attending to the breadth and accuracy of evidence used to support the background and rationale for research proposals. Given failures of extant review panels to detect such bias,16 ad hoc or specialized reviewers outside the disciplinary boundaries of peer review committees may be needed.

Another essential element guiding research at AHA is optimization. Optimization seeks to expand collaboration to leverage research dollars and outcomes. 8 In addition to confirmation of study results, soliciting de novo analysis of AHA-funded research is a way to leverage research dollars. This leveraging was exemplified by a recent challenge using data from a National Heart, Lung and Blood Institute (NHLBI) funded trial of intensive blood pressure reduction.17 Using modest financial incentives, researchers not involved in the initial trial identified specific patient profiles who were much more or less likely to benefit from intensive blood pressure reduction, eg, lower clinical CVD risk without serious side effects (eg, kidney damage) versus no CVD risk benefit and likely serious side effects.18 These clinically important insights for hypertension management were complemented by the development of novel methodological approaches for reanalysis of existing data – approaches that are broadly applicable to other clinical trial data sets (NEJM). Thus, both confirmation of results and de novo analysis of primary data can promote a more robust and efficient use of resources, fulfilling the letter and spirit of AHA’s funding philosophy. Of course, optimizing research in this way should be accompanied by mechanisms to assign scientific credit to those who initially gathered the data.19

In conclusion, research sponsors are responsible for funding research that results in worthwhile achievements 20 and it is laudable that the AHA Research Committee is scrutinizing peer review practices.1 Peer review seeks to advance the AHA mission by funding research most likely to impact human health. This effort can best be evaluated by asking whether funded studies “… have improved quality of life and life expectancy, by how much, for how many, and for whom.”2


  1. Liaw L, Freedman JE, Becker LB, Mehta NN, Liscum L. Peer review practices for evaluating biomedical research grants. Circulation. in press.
  2. Joyner MJ, Paneth N, Ioannidis JPA. What happens when underperforming big ideas in research become entrenched? JAMA. 2016;316(13):1355–1356.
  3. American Heart Association. Strategically focused research programs. 2017. Accessed April 13, 2017
  4. Kuller L. Is phenomenology the best approach to health research? Am J Epidemiol. 2007;166(10):1109–1115.
  5. Macleod MR, Michie S, Roberts I, Dirnagl U, Chalmers I, Ioannidis JPA, Al-Shahi Salman R, Chan A-W, Glasziou P. Biomedical research: increasing value, reducing waste. Lancet. 2014;383(9912):101–104.
  6. Woolf SH. The need for perspective in evidence-based medicine. JAMA. 1999;282(24):2358–2365.
  7. Prasad V, Cifu A, Ioannidis JPA. Reversals of established medical practices: evidence to abandon ship. JAMA. 2012;307(1):37–38.
  8. American Heart Association. AHA Mission, Vision, and the 12 Essential Elements that Guide the AHA Research Program. 2017.  Accessed April 13, 2017
  9. Prasad V, Vandross A, Toomey C, Cheung M, Rho J, Quinn S, Chacko SJ, Borkar D, Gall V, Selvaraj S, Ho N, Cifu A. A decade of reversal: an analysis of 146 contradicted medical practices. Mayo Clin Proc. 2013;88(8):790–798.
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  11. Morey RD, Chambers CD, Etchells PJ, Harris CR, Hoekstra R, Lakens D, Lewandowsky S, Morey CC, Newman DP, Schönbrodt FD, Vanpaemel W, Wagenmakers E-J, Zwaan RA. The Peer Reviewers’ Openness Initiative: incentivizing open research practices through peer review. R Soc Open Sci. 2016;3(1):150547.
  12. Taichman DB, Backus J, Baethge C, Bauchner H, de Leeuw PW, Drazen JM, Fletcher J, Frizelle FA, Groves T, Haileamlak A, James A, Laine C, Peiperl L, Pinborg A, Sahni P, et al. Sharing clinical trial data — a proposal from the International Committee of Medical Journal Editors. N Engl J Med. 2016;374(4):384–386.
  13. American Heart Association. Open science policy statements for AHA funded research. Accessed April 13, 2017.
  14. Patel CJ, Burford B, Ioannidis JPA. Assessment of vibration of effects due to model specification can demonstrate the instability of observational associations. J Clin Epidemiol. 2015;68(9):1046–1058.
  15. Steegen S, Tuerlinckx F, Gelman A, Vanpaemel W. Increasing transparency through a multiverse analysis. Perspect Psychol Sci. 2016;11(5):702–712.
  16. Greenberg SA. How citation distortions create unfounded authority: analysis of a citation network. BMJ. 2009;339:b2680–b2680.
  17. The SPRINT Research Group. A randomized trial of intensive versus standard blood-pressure control. N Engl J Med. 2015;373(22):2103–2116.
  18. Balicer R, Dagan N. To treat intensively or not – individualized decision making support tool. Accessed April 13, 2017
  19. Bierer BE, Crosas M, Pierce HH. Data authorship as an incentive to data sharing. N Engl J Med. 2017.
  20. Chalmers I, Bracken MB, Djulbegovic B, Garattini S, Grant J, Gülmezoglu AM, Howells DW, Ioannidis JPA, Oliver S. How to increase value and reduce waste when research priorities are set. Lancet. 2014;383(9912):156–165.

-- The opinions expressed in this commentary are not necessarily those of the editors or of the American Heart Association --