“The Effect of Sitagliptin on Carotid Artery Atherosclerosis in Type 2 Diabetes”
Data from: The effect of sitagliptin on carotid artery atherosclerosis in Type 2 Diabetes: the PROLOGUE randomized controlled trial
Oyama J, Murohara T, Kitakaze M, Ishizu T, Sato Y, Kitagawa K, Kamiya H, Ajioka M, Ishihara M, Dai K, Nanasato M, Sata M, Maemura K, Tomiyama H, Higashi Y, Kaku K, Yamada H, Matsuhisa M, Yamashita K, Bando YK, Kashihara N, Ueda S, Inoue T, Tanaka A, Node K (2016) The Effect of Sitagliptin on Carotid Artery Atherosclerosis in Type 2 Diabetes: The PROLOGUE Randomized Controlled Trial. PLOS Medicine 13(6): e1002051.
Hans Rosling’s TED Talk, “The Best Stats You’ve Ever Seen,” does an incredible job of linking data to design to enable audiences to gain a better understanding of pressing global health issues. Rosling did a great job of making statistics much more interesting than just bar and line graphs in this talk. As a statistician and a medical doctor, Rosling brings stats to life in such a visual and dynamic way, as he examines common myths of third world countries such as child mortality and distribution of income.
After his introductory anecdotes, he began to strictly focus on the statistics, and attention switched to his exciting and visually pleasing presentation of his large quantity of global data. Rather than using the standard bar graph, Rosling used figures that moved to display trends and made his statistics very interactive as seen in the figure below. Overall, this presentation did exceed my expectations, since I did not expect a presentation of biostatistics to be so engaging. I was surprised to see how databases, statistics, and available technologies provide the population with so many answers to questions and clarifications of misconceptions made about the world in an interesting and visual manner. Rosling succeeded in debunking the myth that there is not a huge gap in income between the rich and the poor through the presentation of his data.
His strategies and data presentation were certainly innovative, and it was very interesting to compare and contrast his presentation style to that of many other TED speakers. This presentation was filled with quantifiable data, but still incorporated some humor, lightheartedness, and anecdotes occasionally to tie together his ideas. This made statistics understandable and applicable to a very wide audience. This data definitely has the potential to increase the audience’s understanding of common misconceptions regarding third world countries as well as the need for better education and communication. This TED talk did an incredible job of incorporating statistics to educate such a large audience about pressing global health issues such as child mortality and the distribution of income worldwide.
The study titled, Metabolic effects of Carvedilol vs. Metoprolol in Patients with Type 2 Diabetes Mellitus and Hypertension, is a randomized control trial. β-Blockers have been proven to decrease various cardiovascular risks such as hypertension and Type II diabetes in patients, so researchers wanted to investigate this further in this study. The investigators posed a research question to compare the effects of two different β-Blockers (Carvedilol and Metoprolol) in metabolic and glycemic control in diabetic patients with hypertension. They gave diabetic patients with hypertension a RAS blockade (renin-angiotensin system blockade) to determine how it would effect metabolic and glycemic control in a context of cardiovascular risk factors.
The researchers used a double-blind design for this experiment. This study targeted patients with hypertension and Type 2 DM with ages ranging from 36 to 85. There was a sample of 1235 participants in the study, and the patients were monitored over the course of 35 weeks. In the experiment, there were 2 groups formed. One group received a Carvedilol dosage of 6.25 to 25 mg twice daily, and the other group received a Metoprolol dosage of 50 to 200 mg twice daily. These ranges were dependent on the patients’ individual baselines. Blood pressure and hemoglobin were monitored throughout the experimentation.
The researchers concluded that both of the β-Blockers were tolerated by the patients. Carvedilol was more successful than the Metoprolol in regards to improving metabolic syndrome and not affecting glycemic control. Researchers used the mean change in HbA1c and blood pressure measurements over the course of the 35-week study. HbA1c was utilized as a marker, since it is linked linearly to the risk of cardiovascular complications in diabetic patients. To track the changes in the HbA 1c , Biostatisticians relied on confidence intervals and p-values from the mean HbA 1c , which they were then able to compare to a baseline measurement for each patient. Researchers concluded that the use of β-Blockers in the presence of RAS blockers reduces insulin resistance, which leads to greater glycemic control. Researchers were able to prove that levels of glycemic control do indeed predict cardiovascular events in patients with Type 2 DM and hypertension.
Bakris GL, Fonseca V, Katholi RE, et al. Metabolic Effects of Carvedilol vs Metoprolol in Patients With Type 2 Diabetes Mellitus and Hypertension: A Randomized Controlled Trial. JAMA. 2004;292(18):2227-2236. doi:10.1001/jama.292.18.2227.
Biostatistics is a field that strives to apply the principals of science and statistics to find possible solutions to major public health issues. Biostatistics is such an important field for the proper and accurate analysis of a wide range of scientific data. Applications of biostatistics can be found in fields pertaining to biology, public health, as well as many other divisions of the health sciences. In both laboratory and clinical research, biostatistics is such an incredible resource to utilize when analyzing results from a diverse set of variables and evaluating evidence. Professionals in the field must determine where variation originates, whether it be chance, error, or a reaction from a treatment. Biostatistics it also useful when determining the difference between correlation and causation when striving to draw conclusions about the outcomes in a sample space.
Researchers rely on professionals in this field to analyze variables and to draw conclusions. This field provides so much opportunity to apply principals of statistics to real-word problems in a diverse set of disciplines. This field plays a huge role in the advancement of both laboratory research and clinical research. Biostatisticians are capable of applying the principals of mathematics to the sciences to “bridge the gap between theory and practice.”
This practice was especially evident in Hans Rosling’s TED talk “The Best Stats You’ve Ever Seen.” As a statistician and a medical doctor, Rosling brings statistics to life as he examines common myths of third world countries such as child mortality and distribution of income. He presents his data in such an engaging and visual manner, which enables the audience to realize how much valuable information can be deduced from statistics. Additionally, by presenting the data in such a visual and engaging manner, he proves that statistics can be so interesting and that there is so much to learn in this field.
Biostatisticians typically work for health organizations, companies, colleges and universities, and even government agencies. These professionals strive to improve the human health industry and to make the general population more knowledgeable about issues regarding public health. Biostatistics is such a huge industry that is expected to fill over 2000 new jobs by 2018 as the demand for these statisticians has been greatly increasing. The main fields that contribute the most to the biostatistics industry are academia, governmental, and pharmaceutical industries.
There are several degree options for someone interested in persuing a career in biostatistics. There are programs that enable students to receive a master’s degree in biostatistics as well as a doctoral degree. The master’s degree has some biomedical applications in clinic, industry, and public health. The doctoral degree would prepare a student to teach and do research in the field. The median salary for a biostatistician is approximately $90,000.
While it is human nature to try to deduce our own conclusions from our observations, quantitative data is a more accurate an effective means of deducting conclusions regarding variables. Once a research study is completed and all the data is collected, it is necessary to find a means of summarizing and interpreting the data. This information enables researchers to draw conclusions about treatments, which enables them to make discoveries and find new treatments for patients.
I had finally understood a Biostatistician’s role for the first time over the past summer when completing vision research. While I worked as a research assistant obtained from experimentation was sent out to a biostatistician who analyzed all the data and produced charts full of organized calculations and graphs (i.e confidence intervals and p values). Once all the data was analyzed, the primary researcher began to make connections and figure out the patterns in the data. From this, the primary researcher was able to accurately analyze what her results meant and began to consider why trends were or were not reflected in the data. From this she wrote up the study and included the analyzation of the data obtained from the biostatistician in results and discussion sections.
Although I do not feel like research and biostatistics are fields that I am interested in pursuing, I have a great appreciation for all of the work, time, and detail that goes into these fields. It was very interesting to have a little glimpse of the real world applications of biostatics just a few months before taking this course.
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“What Does a Career in Biostatistics Actually Look Like? | This Is Statistics.” This Is Statistics. N.p., 06 June 2016. <http://thisisstatistics.org/what-does-a-career-in-biostatistics-actually-look-like/>.