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Reporting drugs and treatments

Reporting drugs and treatments. Thomas Abraham. What we will learn today. The difference between absolute and relative risk reduction A basic way to interpret P values and CI (confidence intervals) Number needed to treat (NNT) All of these are to help you evaluate and report on studies.

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Reporting drugs and treatments

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  1. Reporting drugs and treatments Thomas Abraham

  2. What we will learn today • The difference between absolute and relative risk reduction • A basic way to interpret P values and CI (confidence intervals) • Number needed to treat (NNT) • All of these are to help you evaluate and report on studies

  3. Nov 1995, results of the trial of a drug announced 6,595 men in the west of Scotland with elevated cholesterol level participated in trial that lasted 5 years One group (treatment group ) was given a cholesterol lowering drug, pravastatin Another group (control group) was given a placebo

  4. The results were impressive For those who took the drug: 31 % reduction of risk from heart attacks 28 % reduction of risk of death from coronary heart disease 31 % reduction of risk from heart attack, or death from heart disease

  5. Combined risk from heart attacks and death from heart disease 7.9% 5.5%

  6. Risk from heart attack and death from heart disease Control group A 7.9% Treatment group B 5.5% How do you measure the difference between these two groups?

  7. Absolute and relative risk reduction • Absolute risk reduction looks at the difference between the treatments: A-B =2.4% • Relative risk reduction looks at how much better one treatment is than the other (A-B/ A) x 100=30.37% A Control B Treatment 7.9% 5.5%

  8. Absolute and relative risk • Absolute risk is your risk of getting a particular disease, or condition • Relative risk measures how much your risk is reduced with the new treatment, or procedure, compared with the old. • Relative risk figures tend to look dramatic

  9. Absolute risk reduction= • Relative risk reduction=

  10. Non fatal Myocardial Infarction A Control 6.5% B Treatment 4.6% Relative risk= ? Absolute Risk= ?

  11. What were the different outcomes the study measured? • Which outcome was the treatment the most effective in?

  12. P values and Confidence Intervals ( CI) • P value or probability value= The probability that a result could have occurred by chance P < .05 means a less than 5 percent probability that this result could have occurred by chance P< .01 means a less than 1 percent probability that this could have occurred by chance P <.001 means ? (move decimal point two places to the right)

  13. According to scientific convention, P<.05 is significant, and P<.01 is highly significant.

  14. Rank the following P values in terms of significance • P<.1 • P<.001 • P<.01 • P<.4 • P<.04 • P<.5 • P<.0001 • P<.05

  15. Confidence intervals (CI) • The confidence level tells you the range within which a true value will lie. It is generally measured at the 95% level. • For example, 31 ( 17-43) 95% CI would indicate that 95% probability that the real value is between 17 and 43.

  16. Number needed to Treat (NNT) • The number of persons who needed to be treated with a drug, to prevent one person from getting the disease. • Calculated as the inverse of the absolute risk reduction percentage

  17. Absolute Risk Reduction = A-B= .5% . 5% means out of 100 people, .5 death was prevented To prevent one death: 200 people need to be treated ( 100/ARR%) Time-5 years. Therefore 200 people over 5 years to prevent 1 case

  18. Non fatal Myocardial Infarction A Control 6.5% B Treatment 4.6% Absolute Risk Reduction = A-B= 2.9% Number needed to treat 100 people, 2.9 heart attacks prevented To prevent one heart attack= 100/ARR%= 100/2.9 Over 5 years

  19. Check list When you hear about a new drug or treatment, check both absolute and relative risk reduction figures. http://www.bbc.co.uk/news/health-16961112 Ask ( or calculate) number needed to treat Ask about possible harms Ask about costs

  20. http://www.youtube.com/watch?v=lNFuEcy5ekg&feature=related

  21. From last week • When evaluating research findings • Published or not published? • Quality of study: numbers of people or cases studied, methodology of study • Newsworthiness

  22. Your course work • Three news stories from journal articles • Due Feb 28, March 28 and March 17(you can turn them in earlier if you wish) • Length: 400-500 words • Go to Eureka alert, as well as Jama and BMJ • Links to press releases on our course website • Find an article that you think might be newsworthy and interesting.

  23. Do some background research on the topic. • Go to Pubmed for earlier studies • Contact authors of paper, as well as people in Hong Kong who might have comments. • Give yourself one week for each

  24. Contacting paper authors • Why? • Not to “get a quote” • To help bring out the significance, or importance of study • To help you understand things you do not understand • Read the paper and do research before getting in touch, so you do not ask basic questions

  25. What I will look for • Is the story newsworthy? • Have you explained the research well? • Have you looked at the costs and benefits • (Look at the health news review website for an idea of what I will be looking for)

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