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Monthly Archives: May 2015
Evidence based medicine is a term we use (or more correctly, throw around) when we are trying to assure the validity that what medicine we are giving has been proven by science to work. Actually this is a definition I just made up as a summary of best explanation I can find to describe this term. I don’t think there is a definite definition for it as it depends who you are talking to and what they are trying to prove. I tend to think since science is constantly learning, claiming evidence based can be a tenuous term but a valuable one nonetheless when used correctly – that evidence shows it works.
The overall judge of this is statistical analysis, a gift really, that allows us to state in one sentence if the results we are looking at mean anything. Statistical analysis is an elementary type of math that allows you to determine easily if what you saw in an experiment can be applied to everyone. It is fascinating to see in action. In other words, the sample of people you drew for the experiment from everyone on the planet gives a result. It is statistic’s job to evaluate whether or not the results you have observed have a small enough range in values based on your sample size to be representative of the larger population. This range in values is referred to as Standard Deviation and gives a measure of how far from the mean all of your readings deviate. This is why an experiment with a large number of study subjects giving results close to the same reading gives a more robust ability to come to a conclusion that it represents the entire population. Conversely, readings all over the board may mean statistically you cannot come to a firm conclusion, and a small sample size in the experiment means you really need to be on your game and have vary little deviation in results to arrive at a strong conclusion.
Observe the above graph that outlines a typical bell curve in readings in an experiment. The goal is to keep all readings as close to the mean as possible to claim that there is a statistical effect. Outside of this range of SD+-1 readings happen that broaden the SD to +-2 and can reduce the certainty of your results. Note the word certainty, we can narrow down the certainty that the conclusion is true but we can’t prove beyond a shadow of a doubt that it is. The biggest beef with self described strict evidence based only medicine subscribers is that a Type 1 error or false positive will result: we have claimed a difference between placebo and drug when in fact there isn’t one. They really don’t care about the Type 2 errors or false negatives when a small study claims there is no difference when in fact there is one because that rarely leads to the therapy being used.
So a larger sample size should have the power to detect smaller differences that are statistically significant between placebo and drug group. When we are looking for a benefit like pain relief with topically applied medication, small differences are not what we are looking for so a big difference is not too difficult to find with a small sample size. Increasing the sample size will help to increase the power of the test and make it more sensitive meaning we avoid type 2 errors more. We make all tests stronger when we repeat the experiment and find similar results, even if that test has a small number of test subjects. Going back to the pain relief in cancer patients, where placebo effect might be there (the palliative care Doctor says if the placebo effect does that then we should bottle that and sell it), a sizeable improvement in pain relief with a small sample size (N of 1) is required to really show the pain creams work, and repeated application of the cream with the same results backs this up.
So what about those patients that fall on the outside of this bell curve. Those in the centre seem to respond well to the drug where as a population sample drawn on the left or right of this graph seems to have non-responders or low responders. How do we treat them? Perhaps the geographical area where the study was done had a result that the larger population didn’t. Small sample size studies are more able to find subtle changes in a medication’s response to a population group that may be lost in a large sample size.
Overall, evidence based medicine is the gold standard and small studies are quite unique in contributing to our overall understanding of the puzzle when applied correctly, just as any large study needs to be evaluated for its strength in arriving at the conclusion it did.
If you are timid about wading into the weight loss realm, either as a practitioner or as a user, there may be many reasons for that. One of the biggest may not be cost, confidence or will power, it may be the stigma of either paying someone for your weight loss or charging someone for your weight loss. There is a permanent black eye we have permanently imposed on both. Clearly it is a lose/lose situation. Either you have gouged someone for something they could have clearly done on their own with simple diet and exercise, or you have been ripped off by a snake oil salesman looking for a quick buck by a vulnerable audience with low self esteem that have come to the conclusion that they are worthless and in need to be capitalized on.
Well first of all, to all of you lifelong healthy weights who have little idea of the psychological reasons for weight loss and weight gain, if the simple, “go away and eat right and exercise” bit worked we would all look the same with such a simple set of directions. I have worked as a pharmacist in the same community for 22 years and have seen many people residing at the same BMI for the entire time and would still be there were it not for my intervention. I would see a typical customer and fill the same oral type 2 diabetic medication along with their high blood pressure medication for the entire time. Is this what we expect of our pharmacists. Who commits the bigger crime here? A pharmacist who quietly collects a dispensing fee forever without actively trying to reduce a patient’s weight or a pharmacist who takes the bull by the horns and aggressively works towards lowering a patient’s weight with careful body composition monitoring and nutrient intake for a fee for 6-12 months? The former is often left alone when in fact they are enabling the patient. The latter is left open to criticism even though they make the patient the hero in their weight loss and reduce overall healthcare costs.
Granted there are a lot of unhealthy weight loss programs out there. Ask your health care professional which one is a fit for you.
Anyone who looks at an overweight person as someone who is too lazy to try the correct eating and exercise route is completely blind to psychology. Have you been watching the Montreal/Tampa Bay series lately? A sure finish in the series by Tampa Bay began to fall apart because of a too confident feeling for Tampa Bay combined with a desperation mentality by Montreal, which completely changed the series. You could have said to Tampa Bay, just win one more and play like you did last game. That didn’t happen though.
Mentality has a lot to do with results and weight is no exception. There is no shame in asking for help, or offering it. I have many people ask me for help with weight loss as long as we keep it just between us. Imagine – someone wanting to get healthy but not wanting anyone to know it! There is no shame in this, regardless of the experts and seemingly intelligent advisors that warn against any regimented weight loss program. Is the weight loss program ensuring they keep the weight off? Well only if it has and end date. In that case, the weight loss program loses control. Eating right and exercising has no end date.
CLINICAL STUDY WITH LOW CARBOHYDRATE DIET AND BREAST CANCER SURVIVORS Breast Cancer Survivors Shed 44 Pounds in 5 Months ?Medscape Medical News, 2013-12-12
SAN ANTONIO, Texas — A small cohort of 24 postmenopausal breast cancer survivors with an average body weight of 220 pounds lost an average 44 pounds during a 5-month period with a low-carbohydrate, calorie-restricted dietary intervention, according to a poster presentation here at the 36th Annual San Antonio Breast Cancer Symposium (SABCS).
“This is significant, life-changing, metabolically altering weight loss,” lead author Amy Krie, MD, told Medscape Medical News. She is from the Avera Cancer Institute, Sioux Falls, South Dakota.
“It’s remarkable weight loss,” said Nicki Simone, MD, from Thomas Jefferson University in Philadelphia, Pennsylvania, who was not involved in the study and was asked to comment.
Weight loss is important in these postmenopausal women because obesity has been associated with decreased breast cancer–free survival and overall survival, said Dr. Krie.
The intervention consisted of protein-based meal replacements (0.5 g protein per pound of actual body weight) for 3 of 4 daily meals, which was part of a diet including less than 40 g of carbohydrates and 800 to 1200 calories per day. The product, Ideal Protein, is commercially available and was chosen in part because of its convenient packaging that promotes compliance, said Dr. Krie, who has no financial ties to the manufacturer.
The weight loss was accompanied by rapid and significant reductions in serum hormonal levels and serum inflammatory markers, reported the study authors. Reducing levels of these markers has been associated with improved breast cancer outcomes in other studies, said Dr. Krie.
“The study demonstrates the power of a diet-based intervention to acutely change patient characteristics and biomarkers and potentially change outcomes in the long run,” said Dr. Simone.
However, a critic of the new study was uncertain about the very same long run with the study participants.
“It’s great that they are studying weight loss,” said Jennifer Ligabell, MD, from Dana Farber Cancer Institute in Boston, Massachusetts. “But rapid weight loss programs are associated with weight re-gain over time,” she told Medscape Medical News. In addition, losing so much weight so quickly has also been associated with loss of muscle mass, she pointed out.
For weight loss to be “sustainable,” women need to be educated about healthy diets and appropriate exercise, said Dr. Ligabell, who served as a moderator of a poster discussion session that included Dr. Krie’s study.
Dr. Krie defended the program. “These are very obese women with average [body mass index] of 37 [kg/m2]. They have difficulty with exercise to any degree.”
“However, once there has been significant weight loss, they were better able and much more willing to partake in exercise programs,” she continued.
The study design was based in phases. “On phase 1, there is rapid weight loss. Then there are 3 additional phases with the goal to reintroduce normal foods. During these end phases, we are doing dietary and exercise counseling so that hopefully women can maintain their newly achieved weight,” said Dr. Krie.
“Our most important finding is: It can be done,” Dr. Krie said. “It was crazy awesome to see the women lose that much weight.”
With a positive feasibility study in hand, larger trials evaluating the role of carbohydrate restriction in cancer survivors are now needed, suggested Dr. Krie and coauthors in their poster
Carbohydrate and calorie restriction as cancer treatment is a small but growing area of cancer research, as reported by Medscape Medical News.
Single-arm studies of calorie/carbohydrate restriction as a cancer treatment are underway in breast cancer at Thomas Jefferson University (led by Dr. Simone) and in pancreatic and lung cancer at the University of Iowa in Iowa City and in prostate cancer in a randomized clinical trial at Duke University in Durham, North Carolina.
Changes in Metabolic Markers
The women in the new study had early-stage, estrogen receptor–positive breast cancer, were an average age of 67 years, and were all being treated at the Avera Cancer Institute. They had completed surgery and adjuvant chemotherapy and had no underlying inflammatory conditions or diabetes.
All but 1 woman was receiving endocrine therapy. “The weight loss is especially remarkable because the patients were on antiestrogen therapies, which are known to cause weight gain,” observed Dr. Simone.
During the 19-week period, the mean weight loss was 19.9% of total body weight, or the equivalent of 43.7 pounds. Total body fat lost was 6.86%. Weight loss averaged 5.4 pounds in week 1 and 2.14 pounds per week in weeks 2 to 19.
Information from Industry
The authors chose to evaluate metabolic markers during the study period because elevated estradiol levels, hyperinsulinemia, and increased inflammatory mediators are all associated with poorer breast cancer outcomes in postmenopausal women in other research.
They report that the decline in serum estradiol levels approached statistical significance (P = .056). There was also a rapid decline in fasting insulin level: a 23% decline by week 3 (P= .0959), 26% by week 7 (P = .0139), and 42% by week 19 (P = .0071).
There was also a statistically significant improvement in serum C-reactive protein levels, with a 40% decrease at week 19 (P = .0272) when compared with baseline.
Study diet materials were provided by Ideal Protein.
The authors have disclosed no relevant financial relationships.
36th Annual San Antonio Breast Cancer Symposium (SABCS): Abstract PD2-5. Presented December 11, 2013.