Designing a Study/Clinical Trial/Dissertation, Etc.
To give an over view of clinical trial
- PDF / 2,932,741 Bytes
- 43 Pages / 439.37 x 666.14 pts Page_size
- 32 Downloads / 279 Views
Designing a Study/Clinical Trial/ Dissertation, Etc. I don’t teach my children. I create condition for them to learn. Albert Einstein
Learning Objectives
To give an over view of clinical trial Phases of trials for drugs Steps of clinical trial Principles of designing a trial Presentation of data Principles of clinical audit Principles of mass screening
General Considerations Clinical trial is defined as a study on human beings designed to test a device or drug or a procedure. Clinical trials are required to answer a clinical problem whether a treatment or surgery is superior to another or a particular drug is effective in a particular condition. Sometimes the drug or the procedure already exists but we want to know new things about it. Also, trials are required to convince the government regulatory authorities for projects or launching a new drug. Let us consider a few examples of why we need trials and audit in our day-to-day practice. In the 1990s there were strong recommendations for hormone replacement therapy (HRT) to mitigate the postmenopausal symptoms and to prevent osteoporosis. Today, there is clear evidence that HRT should not be used as a routine, because of VTE complications. So the current practice is not to use HRT. We got this information because of good clinical trials.
© Springer Science+Business Media Singapore 2017 H.K. Ramakrishna, Medical Statistics, DOI 10.1007/978-981-10-1923-4_7
85
86
7
Designing a Study/Clinical Trial/Dissertation, Etc.
As undergraduates we read Halsted operation as the standard operation for carcinoma breast. Today no surgeon performs this operation. Why? There were good trials by which we came to know that these practices were wrong, and we have better options. We need trials to get these data. This knowledge of design of trials and biostatistics helps us to analyze and interpret the presented data correctly. While reading journals or explanation by medical representatives, we come across terms like relative risk reduction, absolute rate reduction, and number needed to treat. To understand these concepts, consider this example. This example is also useful to highlight why should we know how to interpret the data and statistical terms. Sometimes the pharmaceutical companies use the term relative risk reduction. If we do not know the proper interpretation, we will be misled to overrate the efficacy of the drug and prescribe their drugs. Suppose there is a condition which has mortality of 3 in 10,000 and a particular drug is shown to reduce this mortality to 2 per 10,000. Then relative risk reduction is 33 %. Pharmaceutical company may hide the other details and show only this line in bold highlighted letters “The drug reduces relative risk by 33 %.” This 33 % looks very impressive, and if we do not know how to interpret the result, we may recommend this drug to our patients. If we analyze the actual data and not the conclusion, we will see that absolute risk reduction is only 0.01 %, because it has reduced the mortality rate by 1 in 10,000. That is to say, we hav
Data Loading...
