Observation is a skill. Discovering what is present and also what is absent requires focus, objectivity, and awareness. Van Gogh, The Starry Night. 1889 can be viewed at Museum of Modern Art in New York City.
I like to use art as an interdisciplinary tool when working with clinical data and numeracy. I notice colleagues don't want to raise their hands to admit they don't understand hazard ratios or calculating number needed to treat (NNT)--but will scrunch up their faces and ask questions about what they observe in art.
We can often look at works of art and create a story. If I was to describe the picture above to you and help you "see" it too, what should I say? Should the information be factual and objective or subjective? Would that influence how you visualized the facts?
Cardiovascular Mortality in Patients With Type 2 Diabetes and Recent Acute Coronary Syndromes From the EXAMINE Trial
RESULTS Rates of CV death were 4.1% for alogliptin and 4.9% for placebo (hazard ratio [HR] 0.85; 95% CI 0.66, 1.10). A total of 736 patients (13.7%) experienced a first nonfatal CV event (5.9% MI, 1.1% stroke, 3.0% HHF, and 3.8% UA). Compared with patients not experiencing a nonfatal event, the adjusted HR (95% CI) for death was 3.12 after MI (2.13, 4.58; P < 0.0001) 4.96 after HHF (3.29, 7.47; P < 0.0001), 3.08 after stroke (1.29, 7.37; P = 0.011), and 1.66 after UA (0.81, 3.37; P = 0.164). Mortality rates after a nonfatal event were comparable for alogliptin and placebo.
CONCLUSIONS In patients with type 2 diabetes and a recent ACS, the risk of CV death was higher after a postrandomization, nonfatal CV event, particularly heart failure, compared with those who did not experience a CV event. The risk of CV death was similar between alogliptin and placebo.
What is the story?
From the press office in New Orleans 76th American Diabetes Association Sessions
New Orleans (June 11, 2016) – Health-related quality of life (HRQOL) is an important area of investigation that has gained increasing recognition and is a critical element of diabetes research, treatment and care, according to experts at the Symposium, “Beyond A1C—Why Quality of Life Matters,” presented on June 11, 2016, during the American Diabetes Association’s 76th Scientific Sessions®, June 10-14, 2016, at the Ernest N. Morial Convention Center in New Orleans.
I unofficially transitioned from a medical writer for hire, to a journalist curious about the intersection of health policy, health economics, clinical medicine and research. Unable to pick a favorite genre I slowly learned the impossibility of pulling on too many individual strings. The story was and is complex.
The most valuable lessons I learned were in the audience of policy meetings at the Brookings Insititution, National Press Club, and the White House. Discussions (often heated) about health economics and outcomes research led by the formal medical director of CMS at an advisory council meeting were eye opening. Once you learn--you can't go back. I can't pretend that diabetes is just diabetes and a pill or injection is the answer.
I recently approached the mic at a session sponsored by the Johns Hopkins Institute for Basic Biomedical Sciences. Weighty Matters: Recent Advances in Metabolism, Obesity and Diabetes Research was targeted to journalists. Except there was limited or no data. No skill session on how to evaluate clinical data. I asked about a bariatric procedure and the risk of malabsorption of nutrients if indeed the digestive tract was abbreviated. You could hear crickets.
My goal is to unpack the science. If we understand the evidence--both what we know and don't know--better decisions will be made. Better articles, education, and recommendations for patients at the point of care.
Recommending gastric bypass as a national solution for our diabetes epidemic is bad medicine and bad economics.-- Mark Hyman, MD
I was scheduled to attend the 76th Scientific Sessions of the American Diabetes Association. Professionally I was filled with anticipation. It is no trivial matter to be granted media access as a digital media professional, a.k.a. blogger. I had to submit analytics from my web traffic, share data regarding site visitors and pages viewed etc. and be open to having the content reviewed and considered.
I was in...
I did not attend. I will be staying up-to-date and writing about the sessions but not with my peers in a fully-staffed press room. Sometimes the personal over-rides the professional and you have to face the reality of the situation. A few client projects escalated requiring close oversight. I have been at conferences trying to juggle phone conversations, go-to-meetings, and deadlines and it isn't pretty.
I made a tough call. Tough because I thrive for the live connection. Access is my secret sauce and I use it liberally.
Lucky for me, I have been thinking about writing more specifically about diabetes. What a perfect time to slow down and create a narrative. But first, we need context. A level set of sorts to set the stage for how we think about clinical evidence. We also need to consider how we utilize surrogate measures to determine clinical efficacy and safety in clinical trials and what that means for the real world population (outside of a controlled clinical trial).
The figure below, highlights a comparison between agencies and their acceptance of surrogates --red for non-accepted surrogates, green for accepted surrogates.
Comparison of international agencies: concerns with surrogate outcomes. Y axis: Drug submission. X axis: Agency. *No: no (e2) = implicit no “evidence 2”; no (ref) = implicit no “reference”; no (e) = explicit no “evidence 1”; no (e1 + e2) = explicit no “evidence 1” and implicit no “evidence 2”; Yes: yes (e1) = implicit yes “evidence 1”; yes (e2) = implicit yes “evidence 2”; yes (used) = implicit yes “used before”; yes (ref) = implicit yes “reference”; yes (e) = explicit yes; Not identified: N/S = no statement; N/A = not applicable; Red shades = negative statements of surrogate acceptability; Green shade = positive statement of surrogate acceptability; HbA1c = hemoglobin A1c; 6MWD = 6 minute walk distance; composite = histology, virology, serology; SVR = sustained virological response; CDR = Common Drug Review; HC = Health Canada; FDA = Food and Drug Administration; EMA = European Medicines Agency; NICE = National Institute for Health and Clinical Excellence; PBS = Pharmaceutical Benefit Scheme; SMC = Scottish Medicines Consortium.v
Surrogate outcomes are defined as a laboratory measurement or a physical sign used as a substitute for a clinically meaningful endpoint that measures directly how a patient feels, functions or survives, and that is expected to predict the effect of the therapy.
I am not suggesting that I have any answers. But I do have a lot of questions. I field dozens of calls within medical education about writing need assessments for diabetes funding of interventions. Everybody wants to do what they have always done. "Hey, write about this class of drugs because the funder is <<insert pharma>>". No thank you. There is too much to lose.
Looking at a therapeutic area pipe-line and deciding what the gaps should be is like locking the barn door after the cows have wandered off. You need to look at the data--be open to the bounty of freely available datasets. Be open to making a difference. Let's figure it out together... moo.
2016 Banting Medal for Scientific Achievement
I continue to be puzzled by the quote by ADA--"The numbers associated with diabetes make a strong case for devoting more resources to finding a cure."
The statistics (at least to me) point to need for population health interventions and prevention strategies. Health costs are unsustainable and the diversion of funds looking for cures downstream of deleterious social correlates leaves me gobsmacked.
Thoughtful discussions about content development and outcomes analytics that apply the principles and frameworks of health policy and economics to persistent and perplexing health and health care problems...