Michael S Lauer

National Heart, Lung, and Blood Institute, 베서스다, Maryland, United States

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Publications (50)645.96 Total impact

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    ABSTRACT: Previous reports from National Institutes of Health and National Science Foundation have suggested that peer review scores of funded grants bear no association with grant citation impact and productivity. This lack of association, if true, may be particularly concerning during times of increasing competition for increasingly limited funds. We analyzed the citation impact and productivity for 1755 de novo investigator-initiated R01 grants funded for at least 2 years by National Institute of Mental Health between 2000 and 2009. Consistent with previous reports, we found no association between grant percentile ranking and subsequent productivity and citation impact, even after accounting for subject categories, years of publication, duration and amounts of funding, as well as a number of investigator-specific measures. Prior investigator funding and academic productivity were moderately strong predictors of grant citation impact.Molecular Psychiatry advance online publication, 2 June 2015; doi:10.1038/mp.2015.71.
    Molecular Psychiatry 06/2015; DOI:10.1038/mp.2015.71 · 15.15 Impact Factor
  • Michael S Lauer, David Gordon, Michelle Olive
    Circulation Research 04/2015; 116(8):1301-3. DOI:10.1161/CIRCRESAHA.114.305893 · 11.09 Impact Factor
  • Michael S Lauer
    Clinical Trials 12/2014; 11(6):622-3. DOI:10.1177/1740774514553482 · 1.94 Impact Factor
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    ABSTRACT: Rationale: We previously demonstrated absence of association between peer-review-derived percentile ranking and raw citation impact in a large cohort of National Heart, Lung, and Blood Institute cardiovascular R01 grants, but we did not consider pregrant investigator publication productivity. We also did not normalize citation counts for scientific field, type of article, and year of publication. Objective: To determine whether measures of investigator prior productivity predict a grant's subsequent scientific impact as measured by normalized citation metrics. Methods and Results: We identified 1492 investigator-initiated de novo National Heart, Lung, and Blood Institute R01 grant applications funded between 2001 and 2008 and linked the publications from these grants to their InCites (Thompson Reuters) citation record. InCites provides a normalized citation count for each publication stratifying by year of publication, type of publication, and field of science. The coprimary end points for this analysis were the normalized citation impact per million dollars allocated and the number of publications per grant that has normalized citation rate in the top decile per million dollars allocated (top 10% articles). Prior productivity measures included the number of National Heart, Lung, and Blood Institute-supported publications each principal investigator published in the 5 years before grant review and the corresponding prior normalized citation impact score. After accounting for potential confounders, there was no association between peer-review percentile ranking and bibliometric end points (all adjusted P>0.5). However, prior productivity was predictive (P<0.0001). Conclusions: Even after normalizing citation counts, we confirmed a lack of association between peer-review grant percentile ranking and grant citation impact. However, prior investigator publication productivity was predictive of grant-specific citation impact.
    Circulation Research 09/2014; 115(7):617-24. DOI:10.1161/CIRCRESAHA.115.304766 · 11.09 Impact Factor
  • Michael S. Lauer
    JACC Cardiovascular Imaging 09/2014; 7(9):879–881. DOI:10.1016/j.jcmg.2014.06.009 · 6.99 Impact Factor
  • Michael S. Lauer
    Journal of the American College of Cardiology 09/2014; 64(9):907–909. DOI:10.1016/j.jacc.2014.05.051 · 15.34 Impact Factor
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    Journal of the American Medical Informatics Association 05/2014; 21(4). DOI:10.1136/amiajnl-2014-002864 · 3.93 Impact Factor
  • Michael S Lauer, Denise Bonds
    American heart journal 04/2014; 167(4):419-20. DOI:10.1016/j.ahj.2013.12.003 · 4.56 Impact Factor
  • Michael S Lauer
    Circulation Research 03/2014; 114(7):1080-2. DOI:10.1161/CIRCRESAHA.114.303627 · 11.09 Impact Factor
  • David J Gordon, Michael S Lauer
    New England Journal of Medicine 02/2014; 370(8):782. DOI:10.1056/NEJMc1315653 · 54.42 Impact Factor
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    ABSTRACT: Funding decisions for cardiovascular R01 grant applications at NHLBI largely hinge on percentile rankings. It is not known whether this approach enables the highest impact science. To conduct an observational analysis of percentile rankings and bibliometric outcomes for a contemporary set of funded NHLBI cardiovascular R01 grants. We identified 1492 investigator-initiated de novo R01 grant applications that were funded between 2001 and 2008, and followed their progress for linked publications and citations to those publications. Our co-primary endpoints were citations received per million dollars of funding, citations obtained within 2-years of publication, and 2-year citations for each grant's maximally cited paper. In 7654 grant-years of funding that generated $3004 million of total NIH awards, the portfolio yielded 16,793 publications that appeared between 2001 and 2012 (median per grant 8, 25th and 75th percentiles 4 and 14, range 0 - 123), which received 2,224,255 citations (median per grant 1048, 25th and 75th percentiles 492 and 1,932, range 0 - 16,295). We found no association between percentile ranking and citation metrics; the absence of association persisted even after accounting for calendar time, grant duration, number of grants acknowledged per paper, number of authors per paper, early investigator status, human versus non-human focus, and institutional funding. An exploratory machine-learning analysis suggested that grants with the very best percentile rankings did yield more maximally cited papers. In a large cohort of NHLBI-funded cardiovascular R01 grants, we were unable to find a monotonic association between better percentile ranking and higher scientific impact as assessed by citation metrics.
    Circulation Research 01/2014; DOI:10.1161/CIRCRESAHA.114.302656 · 11.09 Impact Factor
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    ABSTRACT: Background Rapid publication of clinical trials is essential in order for the findings to yield maximal benefits for public health and scientific progress. Factors affecting the speed of publication of the main results of government-funded trials have not been well characterized. Methods We analyzed 244 extramural randomized clinical trials of cardiovascular interventions that were supported by the National Heart, Lung, and Blood Institute (NHLBI). We selected trials for which data collection had been completed between January 1, 2000, and December 31, 2011. Our primary outcome measure was the time between completion of the trial and publication of the main results in a peer-reviewed journal. Results As of March 31, 2012, the main results of 156 trials (64%) had been published (Kaplan-Meier median time to publication, 25 months, with 57% published within 30 months). Trials that focused on clinical events were published more rapidly than those that focused on surrogate measures (median, 9 months vs. 31 months; P<0.001). The only independent predictors of more rapid publication were a focus on clinical events rather than surrogate end points (adjusted publication rate ratio, 2.11; 95% confidence interval, 1.26 to 3.53; P = 0.004) and higher costs of conducting the trial, up to a threshold of approximately $5 million (P<0.001). The 37 trials that focused on clinical events and cost at least $5 million accounted for 67% of the funds spent on clinical trials but received 82% of the citations. After adjustment of the analysis for a focus on clinical events and for cost, trial results that were classified as positive were published more quickly than those classified as negative. Conclusions Results of less than two thirds of NHLBI-funded randomized clinical trials of cardiovascular interventions were published within 30 months after completion of the trial. Trials that focused on clinical events were published more quickly than those that focused on surrogate end points.
    New England Journal of Medicine 11/2013; 369(20):1926-34. DOI:10.1056/NEJMsa1300237 · 54.42 Impact Factor
  • Michael S Lauer, Ralph B D'Agostino
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    ABSTRACT: The randomized trial is one of the most powerful tools clinical researchers possess, a tool that enables them to evaluate the effectiveness of new (or established) therapies while accounting for the effects of unmeasured confounders and selection bias by indication. Randomized trials, especially huge megatrials, have transformed medical practice. Thanks to randomized trials, we no longer, for example, treat acute myocardial infarction with lidocaine and nitrates. Instead we use rapid revascularization, anticoagulants, and antiplatelet agents, and during long-term follow-up we routinely prescribe statins, beta-blockers, and angiotensin-converting-enzyme inhibitors. But the reputation of randomized trials has suffered of late,(1) owing to reasonable . . .
    New England Journal of Medicine 08/2013; 369(17). DOI:10.1056/NEJMp1310102 · 54.42 Impact Factor
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    ABSTRACT: Outcomes have improved significantly in pediatric cardiovascular disease in recent decades. The challenge now is to sustain these advances through innovative clinical trials, fundamental molecular investigations, genetics and genomics, and outreach to families, emphasizing the importance of participating in research. We describe several such efforts and provide a vision of the future for pediatric cardiovascular research. (J Am Coll Cardiol 2013;61:2565-7) (C) 2013 by the American College of Cardiology Foundation
    Journal of the American College of Cardiology 04/2013; 61(25). DOI:10.1016/j.jacc.2013.03.054 · 15.34 Impact Factor
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    ABSTRACT: In 2012, the National Cancer Institute (NCI) engaged the scientific community to provide a vision for cancer epidemiology in the 21st century. Eight overarching thematic recommendations, with proposed corresponding actions for consideration by funding agencies, professional societies, and the research community emerged from the collective intellectual discourse. The themes are (i) extending the reach of epidemiology beyond discovery and etiologic research to include multilevel analysis, intervention evaluation, implementation, and outcomes research; (ii) transforming the practice of epidemiology by moving towards more access and sharing of protocols, data, metadata, and specimens to foster collaboration, to ensure reproducibility and replication, and accelerate translation; (iii) expanding cohort studies to collect exposure, clinical and other information across the life course and examining multiple health-related endpoints; (iv) developing and validating reliable methods and technologies to quantify exposures and outcomes on a massive scale, and to assess concomitantly the role of multiple factors in complex diseases; (v) integrating "big data" science into the practice of epidemiology; (vi) expanding knowledge integration to drive research, policy and practice; (vii) transforming training of 21st century epidemiologists to address interdisciplinary and translational research; and (viii) optimizing the use of resources and infrastructure for epidemiologic studies. These recommendations can transform cancer epidemiology and the field of epidemiology in general, by enhancing transparency, interdisciplinary collaboration, and strategic applications of new technologies. They should lay a strong scientific foundation for accelerated translation of scientific discoveries into individual and population health benefits.
    Cancer Epidemiology Biomarkers & Prevention 03/2013; 22(4). DOI:10.1158/1055-9965.EPI-13-0146 · 4.32 Impact Factor
  • Michael S Lauer
    Statistics in Medicine 11/2012; 31(25):3066-7. DOI:10.1002/sim.5396 · 2.04 Impact Factor
  • Myron Waclawiw, Colin O. Wu, Song Yang, Michael S. Lauer
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    ABSTRACT: Comparative effectiveness research represents the kind of research that arguably more directly affects clinical practice and policy. It includes observational studies, clinical trials, and systematic syntheses of existing literature. In this commentary, I argue for the ongoing and critical role of randomization in comparative effectiveness, noting the key differences between practical and explanatory trials. Copyright © 2012 John Wiley & Sons, Ltd.
    Statistics in Medicine 11/2012; 31(25). DOI:10.1002/sim.5400 · 2.04 Impact Factor
  • Myron Waclawiw, Colin O. Wu, Song Yang, Michael S. Lauer
    Statistics in Medicine 11/2012; · 2.04 Impact Factor
  • Michael S Lauer
    JAMA The Journal of the American Medical Association 11/2012; 308(17):1804-5. DOI:10.1001/jama.2012.14838 · 30.39 Impact Factor
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    ABSTRACT: In his widely acclaimed book "The Difference," Scott Page, a Professor at the University of Michigan, described a computer modeling experiment designed to test the "Diversity Trumps Ability Theorem." The Theorem postulates that "collections of diverse individuals outperform collections of more individually capable individuals." The computer model showed that diversity enhanced the ability to solve problems or make accurate predictions2, but only when 4 conditions were met: 1) the problems were difficult, 2) all problem solvers were "smart" (but not the smartest), 3) diversity was sufficient to assure that different problem solvers could exploit the solutions of others, and 4) the populations of problem solvers and collections of problem solvers were large. As all 4 of these conditions are clearly met in heart, lung, and blood (HLB) research, we were stimulated to examine the diversity of topics and mechanisms in the NHLBI portfolio. [Extract].
    Circulation Research 08/2012; 111(7):833-6. DOI:10.1161/CIRCRESAHA.112.279596 · 11.09 Impact Factor

Publication Stats

635 Citations
645.96 Total Impact Points

Institutions

  • 2008–2015
    • National Heart, Lung, and Blood Institute
      • • Office of the Director
      • • Division of Cardiovascular Sciences (DCVS)
      베서스다, Maryland, United States
  • 2012
    • McMaster University
      Hamilton, Ontario, Canada
  • 2006
    • Cornell University
      Итак, New York, United States
    • Case Western Reserve University
      Cleveland, Ohio, United States
  • 2005
    • Case Western Reserve University School of Medicine
      Cleveland, Ohio, United States