Milton Packer M.D.

Packer, M. (2018). “Derangements in adrenergic-adipokine signalling establish a neurohormonal basis for obesity-related heart failure with a preserved ejection fraction.” Eur J Heart Fail. Mar 1. [Epub ahead of print].

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Among patients with heart failure and a preserved ejection (HFpEF), obesity is associated with a distinct phenotype that is characterized by adiposity-driven plasma volume expansion and cardiac overfilling, which is coupled with an impairment of ventricular distensibility. These pathophysiological abnormalities may be related to the increased actions of specific adipocyte-derived signalling molecules (aldosterone, neprilysin and leptin) that work in concert with increased renal sympathetic nerve traffic and activated beta2 -adrenergic receptors to promote sodium retention, microvascular rarefaction, cardiac fibrosis and systemic inflammation. This interplay leads to striking activation of the mineralocorticoid receptor, possibly explaining why obese patients with heart failure are most likely to benefit from spironolactone and eplerenone in large-scale clinical trials. Additionally, adipocytes express and release neprilysin, which (by degrading endogenous natriuretic peptides) can further promote plasma volume expansion and cardiac fibrosis. Heightened neprilysin activity may explain the low circulating levels of natriuretic peptides in obesity, the accelerated breakdown of natriuretic peptides in HFpEF, and the cardiac decompression following neprilysin inhibition in HFpEF patients who are obese. Furthermore, as adipose tissue accumulates and becomes dysfunctional, its secretion of leptin promotes renal sodium retention, microvascular changes and fibrotic processes in the heart, and systemic inflammation; these effects may be mediated or potentiated by the activation of beta2 -adrenergic receptors. These adrenergic-adipokine interactions provide a mechanistic framework for novel therapeutic strategies to alleviate the pathophysiological abnormalities of obesity-related HFpEF. Ongoing trials are well-positioned to test this hypothesis.

Packer, M. (2018). “Data sharing in medical research.” Bmj 360: k510.

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The imperative for data sharing is now widely understood by the research community. After years of debate, there is a growing consensus that data sharing is an inseparable part of the research process. My publicly stated position is that an investigator who performs studies in people has implicitly agreed to a social contract, which includes the responsibility to make the raw data available for examination.3 It has always been delusional for researchers to imagine that the public would believe their findings and accept their conclusions without access to supporting data. If clinicians are expected to change their practice based on their reading of medical journals, they need to know that the evidence in published papers can be verified . . . Trust is the crux of the matter. Some researchers who did not provide datasets may have been sceptical of Naudet and colleagues’ motives; meanwhile, Naudet and colleagues may have harboured subconscious doubts about the researchers’ claim that their raw data would support their findings. Interestingly, in the majority of their audits (82%, 95% confidence interval 59% to 94%), the authors verified the primary conclusions of the researchers’ work. Is that reassuring? They only looked at the primary endpoint data; they did not validate secondary analyses, and they could not verify the findings from datasets that were withheld. Undoubtedly, this paper will be perceived by some as encouraging and by others as distressing. When mutual distrust is so pervasive, progress on data sharing will be slow and painful. How do we build trust? Everyone who submits research for the public good should naturally expect that they will be asked to make their data available for examination and reanalysis. This is not a new idea. Citizens who pay taxes assume that some federal agency is poised to check their calculations. In the United States, every pharmaceutical company that submits an application to the Food and Drug Administration for a new chemical entity does so with the full understanding and expectation that their raw data will be audited and that their analyses will be verified. Why should individual researchers be an exception? Perhaps, industry can put pressure on their sponsored investigators to let go. (Excerpt from text, p. 1; no abstract available.)

Mogensen, U. M., J. Gong, P. S. Jhund, L. Shen, L. Kober, A. S. Desai, M. P. Lefkowitz, M. Packer, J. L. Rouleau, S. D. Solomon, B. L. Claggett, K. Swedberg, M. R. Zile, G. Mueller-Velten and J. J. V. McMurray (2018). “Effect of sacubitril/valsartan on recurrent events in the Prospective comparison of ARNI with ACEI to Determine Impact on Global Mortality and morbidity in Heart Failure trial (PARADIGM-HF).” Eur J Heart Fail. Feb 12. [Epub ahead of print].

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AIMS: Recurrent hospitalizations are a major part of the disease burden in heart failure (HF), but conventional analyses consider only the first event. We compared the effect of sacubitril/valsartan vs. enalapril on recurrent events, incorporating all HF hospitalizations and cardiovascular (CV) deaths in PARADIGM-HF, using a variety of statistical approaches advocated for this type of analysis. METHODS AND RESULTS: In PARADIGM-HF, a total of 8399 patients were randomized and followed for a median of 27 months. We applied various recurrent event analyses, including a negative binomial model, the Wei, Lin and Weissfeld (WLW), and Lin, Wei, Ying and Yang (LWYY) methods, and a joint frailty model, all adjusted for treatment and region. Among a total of 3181 primary endpoint events (including 1251 CV deaths) during the trial, only 2031 (63.8%) were first events (836 CV deaths). Among a total of 1195 patients with at least one HF hospitalization, 410 (34%) had at least one further HF hospitalization. Sacubitril/valsartan compared with enalapril reduced the risk of recurrent HF hospitalization using the negative binomial model [rate ratio (RR) 0.77, 95% confidence interval (CI) 0.67-0.89], the WLW method [hazard ratio (HR) 0.79, 95% CI 0.71-0.89], the LWYY method (RR 0.78, 95% CI 0.68-0.90), and the joint frailty model (HR 0.75, 95% CI 0.66-0.86) (all P < 0.001). The effect of sacubitril/valsartan vs. enalapril on recurrent HF hospitalizations/CV death was similar. CONCLUSIONS: In PARADIGM-HF, approximately one third of patients with a primary endpoint (time-to-first) experienced a further event. Compared with enalapril, sacubitril/valsartan reduced both first and recurrent events. The treatment effect size was similar, regardless of the statistical approach applied.E

Vaduganathan, M., B. Claggett, M. Packer, J. J. V. McMurray, J. L. Rouleau, M. R. Zile, K. Swedberg and S. D. Solomon (2018). “Natriuretic Peptides as Biomarkers of Treatment Response in Clinical Trials of Heart Failure.” JACC Heart Fail. Mar 4. [Epub ahead of print].

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BACKGROUND: The lack of reliable predictors of the efficacy of drugs and devices in heart failure (HF) has presented a major hurdle to the development and evaluation of novel therapies. OBJECTIVES: To determine whether treatment-related changes in natriuretic peptides (NP) predict longer-term therapeutic effects in clinical trials of HF. METHODS: We conducted a trial-level analysis of 16 phase-3 chronic HF trials completed between 1987 and 2013 studying 18 therapeutic comparisons in 48,844 patients. We calculated weighted Pearson correlation coefficients between average control- or placebo-corrected changes in NPs and the longer-term treatment effects on clinical endpoints (expressed as log-transformed hazard ratios). RESULTS: Median follow-up for clinical endpoints was 28 (interquartile range: 18 to 36) months. NPs were available in a median of 748 (interquartile range: 270 to 1868) patients and measured at a median of 4 (interquartile range 3 to 6) months after randomization. Treatment-related changes in NPs were not correlated with longer-term treatment effects on all-cause mortality (r=0.12, P=0.63), but were correlated with HF hospitalization (r=0.63, P=0.008). Correlation with HF hospitalization improved when analyses were restricted to trials completed in the last decade (>2010; r=0.92, P=0.0095), employing NT-proBNP assays (r=0.65, P=0.06), and evaluating inhibitors of the renin-angiotensin-aldosterone-system (r=0.97, P=0.0002). CONCLUSIONS: When examining a broad range of interventions, therapy-related changes in NPs appeared modestly correlated with longer-term therapeutic effects on hospitalization for HF, but not with effects on all-cause mortality. These observations raise important caveats regarding the use of NPs in phase II trials for decision-making regarding phase III trials.

Packer, M. (2018). “Is metformin beneficial for heart failure in patients with type 2 diabetes?” Diabetes Res Clin Pract 136: 168-170.

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Heart failure is a common and serious cardiovascular complication of type 2 diabetes. Many antihyperglycemic drugs can increase the risk of heart failure. However, it is commonly believed that metformin – the first-line treatment for type 2 diabetes – reduces the risk of and improves the clinical course of heart failure. It is estimated that 20-25% of patients taking metformin have heart failure. Metformin has been shown to have favorable effects on the course of heart failure in experimental models. Furthermore, when compared with other antihyperglycemic medications in nonrandomized epidemiological studies, metformin users had a lower risk of new-onset heart failure and a lower risk of death if they already had heart failure. However, these reports are difficult to interpret, given the potential for prescribing bias and the likelihood that comparator agents caused cardiovascular harm. Meta-analyses of randomized controlled clinical trials have not demonstrated benefits of metformin on the risk of or the clinical course of heart failure. Given metformin’s importance in the management of type 2 diabetes and its widespread use in heart failure, the current confidence in its benefits in high-risk patients needs to be re-evaluated.