Use of Statistics in Medical Research: Assessment Answers

Introduction

Drug development is one of the most important aspects of healthcare provision and is one of the most heavily funded fields. Drugs have reduced mortality rate in diseases such as cancer and HIV/AIDS. While most lifestyle diseases are not curable, the medical field has taken advantage of modern technology to develop drugs that improve the quality of life and increase patient survival rates. This is done by having well-structured medical research including tests and data analysis on various drug treatments and on individuals from varying demographic structure. In recent days, one of the most successful drug development was that of COVID-19 vaccine which has vastly reduced the rates of infection.[1] This report will look into the use of statistical analysis in drug development and how data and statistics can be used to increase accuracy in the testing processes. The objectives of the report include:

1. To determine the data collection and sampling methodologies that are used in drug development processes in line with subsequent data analysis
2. To determine the statistical analysis methods and rules that can be used in the drug research process
3. To determine the importance of visualizations in medical research reporting
4. To determine the importance of unbiased data in medical research

Body

Interviewer

What area of Biomedical Sciences interests you and why?

Me: I have been interested in the medical research and especially drug development ever since the development of the COVID-19 vaccine in 2020 which has been impactful in reducing the spread of the disease.

Interviewer

What aspect of drug development would you be most fascinated by?

Me: I am fascinated by the use of data and statistics and its importance in developing accurate outcomes. I believe statistics is important in sampling, data collection, data analysis and medical research reporting at the end of the project. Therefore, statistics is clearly impactful in the entire project cycle.

Interviewer

 Give me an example of a drug development project and what statistical methodologies you would use in the stages you have just stated.

Me: For example, this would be highly applicable in a cancer drug development project. Cancer is one of the leading causes of deaths across the globe affecting both the young and the old. [2] While there have been methods of treatment such as chemotherapy and surgery, further research is underway to develop drugs that are less invasive than the current methods. The drug testing process is the most important process and should ensure that study subjects are selected across varying demographic populations.

Interviewer

How would you ensure the various demographics are represented in the research?

Me: There are varying sampling techniques but the most suitable one in this case would be stratified sampling technique. A number of respondents would be selected based demographic groups/strata such as gender, age, race, economic status, at-risk etc. Then further samples can be derived from the groups who would then be used in the drug test.

Interviewer

How then would you conduct the research on the sampled study subjects?

Me: After having a well-balanced demographic study subjects, I would then do the research by administering the drug as well as the placebo to them. A placebo is important in any medical research since it helps to fully evaluate the efficacy of the drug. Placebo effects influences the physiological mechanisms of the study subject.[3] The study subjects will then be monitored over a given period of time to evaluate whether there is cancer progression and physical and psychological effect of the drug on the patients. This will be done while controlling for the confounding effect of other factors. The cancer progression can be recorded using cancer index which can be analyzed further at the end of the data collection process.

Interviewer

What statistical analysis methods do you this would be best in such a study?

Me: I believe both descriptive and inferential statistics would be important to the study

Interviewer

What descriptive statistics would you use?

Me: In biomedical research, descriptive statistics is important in describing the basic features of the data in the study.[4] It gives statistics such as mean, median, mode, variances and standard errors. These are easy to generate using statistical software such as R, SPSS, Stata etc.

Interviewer

What inferential statistics would you use and how do you this it will best capture the outcome of the study?

Me: Inferential statistics are often used to approve or disapprove a test hypothesis. I would first come up with a hypothesis. For example, I would test the hypothesis on which factors best contribute to non-progressive cancer patients. The factors assessed would be the subject’s BMI, Blood Pressure and Age. I would use the following formulae to do the Linear Regression:

This will give a least squares regression outcome that determines what effect a change in BMI, BP and Age have on non-progressive cancer.

This can further be determined by doing correlation analysis on the data. Correlation analysis is similar to linear regression except in correlation, relationship is evaluated across each pair of variable under investigation.

Interviewer

Tell me more about how you would analyze the drug efficacy in relation to the placebo.

Me: I would use the t-test in this case which is an inferential statistical analysis method used to evaluate differences in means. [5]I would divide the data by ‘drug treatment’ and ‘placebo’ treatment and analyze the ‘Reduced Cancer Index’ which records the non-progressive cancer patients. I would then do the t-test analysis assuming unequal variances which gives the mean, variance, mean difference, p-value and critical value. I would the use the p-value 95% significance level to test whether there is significant mean difference between the two datasets or not.

Interviewer

Statistics seems to be a big part of the research project but don’t you think all these formulas and numbers can be confusing to the reader of the medical report?

Me: Data analysis is important in establishing accuracy in drug development but I agree, this can be a little too much for a common reader. This is why we use data visualization plots such as scatter plots pie-charts, histograms, line graphs etc. There are thousands of visualizations which are useful in data representation and are easy to understand. They also capture the readers’ attention without requiring them to necessarily understand the numbers and the formulas.

Conclusion

The use of statistics in drug development research can be useful in determining the efficacy of the drug and which demographic groups best benefit from the drug. The data captured can also be used to evaluate whether pre-existing health conditions such as high blood pressure are affected by the developed drug. Proper sampling techniques and data analysis are important in ensuring the success of the drug when it is released to the market. These finding would be represented in tables, charts (example shown in Figure 1 below), and diagrams for easy interpretation by the ordinary reader. Deeper analysis including formulas and statistical and medical conclusion will also be used for further research and interpretation by the medical community.

Figure 1: Example of a Scatter plot visualization

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