data&donuts
  • Data & Donuts (thinky thoughts)
  • COLLABORATor
  • Data talks, people mumble
  • Cancer: The Brand
  • Time to make the donuts...
  • donuts (quick nibbles)
  • Tools for writers and soon-to-be writers
  • datamonger.health
  • The "How" of Data Fluency

The data-chiatrist is in...

6/12/2016

 
I am not a statistician. I am a consumer of statistics courses from undergraduate, graduate, and post-graduate studies. I possess a theoretical grasp of numeracy that still allows a never-ending pipeline of questions and scientific inquiry.

I am unable to think of one post-graduate course that hasn't become out-dated. A dusty PhD in an obscure biological subspecialty may gain entry but my expertise in population genetics would be a relic--if I wan't continually learning...

I have mentioned the fire-hose of data and information--let's try to find a story in the numbers.
Picture
Picture
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?
​stay tuned...

Beyond A1C—Why Quality of Life Matters

6/11/2016

 
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. 
 
Treating People, Not Numbers: Assessing Health-Related Quality of Life (HRQOL)
Diabetes treatment and care often focuses on measurable goals, such as maintaining target blood glucose levels. “It’s important, however, for healthcare providers and investigators to also take into account patients’ quality of life (QOL), which is more difficult to measure, yet can greatly impact outcomes,” said Lawrence Fisher, PhD, Professor Emeritus, Department of Family and Community Medicine at the University of California, San Francisco, in his presentation, “Quality of Life, Issues of Conceptualization and Measurement.”
 
“Using blood glucose numbers or improved glycemic control as outcome measures is too limited,” continued Fisher. “Patient quality of life can be a better predictor of mortality and morbidity than some biologic measures.”
 
It is critical that a comprehensive HRQOL assessment is incorporated into the structure of trials—to measure at baseline and at intervals that correspond and complement the study’s treatment protocol. “Patients provide a perspective that investigators can often miss. Early and continuous patient feedback is crucial for us to develop and employ the most effective strategies that can improve QOL and biologic outcome measures.”
 
All outcomes will not be achieved at the same pace, noted Fisher. For example, changes in glycemic control, behavior and quality of life are unlikely to occur simultaneously. “The introduction of a continuous glucose monitor might lead in the short term to improvements in glycemic control. However, the initial data overload can be very distressing for patients, so changes in quality of life might not become apparent until far later in comparison to changes in blood glucose levels.”
 
”We must consider patient experience feedback and quality of life data to be as important as biologic outcomes,” Fisher concluded.
 
Questionnaires Measure Quality of Life for People with Type 1 Diabetes and Their Caregivers
“Questionnaires for people with type 1 diabetes and their caregivers should soon provide a better means of measuring quality of life across the course of their lives, from early childhood through late adulthood,” said Marisa E. Hilliard, PhD, Assistant Professor of Pediatrics, Baylor College of Medicine, Texas Children’s Hospital, in her presentation, “Developing a Measure of Diabetes Health-related Quality of Life Across the Lifespan—Preliminary Qualitative Findings.”
 
Hilliard and her team are currently conducting a mixed-methods study—interviewing people with type 1 diabetes and their caregivers (parents and partners) in order to better understand the quality of life issues they experience at different points in life. 
The interviews have informed the research team’s development of new patient-reported outcome measures of diabetes-related quality of life, which will be validated across the United States this year. The new measures will be able to inform and improve patient-centered research and care. 
 
“People with diabetes are more than their glycemic control data,” she said. “The day-to-day experiences of living with and managing type 1 diabetes need to be better understood and addressed in clinical research and practice. Developed from the personal stories of people with diabetes and their family members, we hope the new patient-reported outcome measures we are developing will advance our ability to prioritize quality of life in clinical research and care. It is equally as important as glycemic control to the overall health and well-being of people with diabetes and their families.”
 
“Several themes have emerged from an analysis of the interviews conducted to-date,” said Hilliard, such as “worries about life with diabetes, challenges of managing diabetes care expenses, and the importance of supportive communication among family members and health care providers. We have learned quite a bit from how people told their stories and what they emphasized. For example, we were pleased to hear so many of our participants talking about the ’silver linings‘ of life with diabetes, their strategies to manage the burdens of diabetes, and their gratitude for the pace of technology advances and for the strong support of the diabetes community.”
 
 “By creating a suite of QOL measures that extend across the lifespan and can be used with both people with diabetes and their caregivers, we anticipate the measures will allow for consistent, longitudinal and outcomes research that can more accurately evaluate the impact of treatments and therapies on everyday life,” she said. “This will help bring to market new intervention approaches that meet more of the needs of people with and impacted by diabetes.”
 
Look AHEAD: Modest Weight Loss Yields Long-Term Quality of Life Benefits
Modest weight loss can significantly improve quality of life for middle-aged and older adults with type 2 diabetes, yielding benefits such as greater ease in performing daily tasks, reduced pain, greater mobility and a better state of mind, according to a review of findings from the Look AHEAD study. The analysis, “Quality of Life Findings from the Look AHEAD Study,” will be presented by Gareth R. Dutton, PhD, Associate Professor of Medicine, University of Alabama Division of Preventive Medicine.
 
The National Institute of Health-funded Look AHEAD (Action for Health in Diabetes) trial () was designed to test whether intensive lifestyle intervention (ILI)—healthy eating and increased physical activity—for weight loss could reduce the occurrence of cardiovascular disease, stroke and cardiovascular-related deaths in obese and overweight patients with type 2 diabetes. While the intervention yielded no reduction in the rate of cardiovascular events, it did achieve other benefits including improved quality of life. The trial included 5,145 adults from 16 clinical centers across the country, ages 45 to 75, with type 2 diabetes and a body mass index (BMI) greater than 25. Patient accrual was terminated after 11 years, when conclusions indicated the study’s primary outcome of reducing cardiovascular events would not be achieved. At that time, median follow-up for patients was 9.6 years. 
 
Study participants were randomly assigned to ILI (n=2,570) or standard of care diabetes support and education (the control group, n=2,575). The ILI group achieved significantly greater weight loss than the control group, with a mean weight loss of 6 percent at the end of the study, compared to 3.5 percent in the control group. Patients in the ILI group experienced significant QOL improvements, such as improved physical function and mobility (defined as the ability to get around and perform daily functions without pain or other limitations).
 
In addition, the ILI group experienced a 48 percent lower risk of loss of mobility, with 12.3 percent (308 of 2,514 patients) of those in the ILI group experiencing severe mobility-related disability after one year, compared to 18.9 percent (474 of 2,502 patients) in the control group. After four years, 20.6 percent (n=517) of the ILI group experienced severe mobility-related disability, compared to 26.2 percent (n=656) of those in the control group. Participants in the ILI group were also 15 percent less likely to experience elevated symptoms of depression eight years following the initiation of treatment.
 
Both groups experienced decreased physical function over time. The ILI group, however, demonstrated an initial significant improvement in functioning during the first year of treatment and continued to report better physical function during the following 8 years of the trial. This suggests that modest weight loss may help to mitigate deteriorations in physical function and QOL that typically occur with aging.  
 
“It is notable that some of the quality of life benefits—physical functioning and depressive symptoms—were still present nearly a decade after individuals began treatment for weight loss,” said Dutton. “These long-term benefits were also preserved even when there was some degree of weight regain.”  
 
“The results highlight the need to consider a variety of benefits for patients with type 2 diabetes who are able to lose a modest amount of weight,” said Dutton. “Many of the outcomes we measured, including physical functioning, mobility and depressive symptoms, are very important to patients who are understandably interested in maximizing their quality of life and maintaining their independence for as long as possible.”
 
Dutton’s review includes data previously published in Diabetes Care, the New England Journal of Medicine, and the Archives of Internal Medicine.-- mkirkwood@diabetes.org


  • Impact of Intensive Lifestyle Intervention on Depression and Health-Related Quality of Life in Type 2 Diabetes: The Look AHEAD Trial
  • Lifestyle Change and Mobility in Obese Adults with Type 2 Diabetes
  • Impact of a weight management program on health-related quality of life in overweight adults with type 2 diabetes

​

T2 diabetes: the underlying cause...

6/11/2016

 
Picture
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
Picture
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.

Surrogates are often biomarkers such as hemoglobin A1C [HbA1c], blood pressure, lipid levels, etc. Surrogate outcomes are used in clinical trials for reasons of efficiency and practicality; they can be measured with fewer patients, less invasiveness and a shorter observation period.

Where surrogate outcomes have validated links with final endpoints, their use can greatly facilitate clinical research. However, in the absence of validated links, there can be uncertainty about patient benefit; and even where the epidemiologic basis is sound, long-term safety and other unanticipated issues may predominate.

For example, while blood pressure is conclusively linked to cardiovascular morbidity and mortality, antihypertensive drugs do not necessarily reduce morbidity or mortality as expected.-- Surrogate outcomes: experiences at the Common Drug Review
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...

​Stay-tuned @graphemeconsult

    Picture

    Why diabetes?

    Context is everything. Chronic diseases share common pathways -- metabolic derangements are seen in Alzheimer's Disease and a variety of other disease pathways.

    ​Time to create a narrative...

    Archives

    February 2017
    January 2017
    October 2016
    June 2016

    Categories

    All

    RSS Feed

Proudly powered by Weebly
  • Data & Donuts (thinky thoughts)
  • COLLABORATor
  • Data talks, people mumble
  • Cancer: The Brand
  • Time to make the donuts...
  • donuts (quick nibbles)
  • Tools for writers and soon-to-be writers
  • datamonger.health
  • The "How" of Data Fluency