Several studies have looked at the use of statins to reduce the risk of cardiovascular disease for those with no pre-existing cardiac disease. The results of the meta-analysis were NNT for preventing heart attacks was = 60 NNH Number needed to harm (develop diabetes) = 67 We can conclude that__________ No benefit harm determination can be made The harms outweigh the benefits the benefits outweigh the harms
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- NNT (Number Needed to Treat) is the average number of patients who need to be treated to prevent one additional bad outcome (e.g., heart attack). A lower NNT indicates a more effective treatment. - NNH (Number Needed to Harm) is the average number of Show more…
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Subjects with pre‑existing cardiovascular symptoms who were receiving subitramine, an appetite suppressant, were found to be at increased risk of cardiovascular events while taking the drug. The study included 10054 overweight or obese subjects with preexisting cardiovascular disease and/ or type 2 diabetes. The subjects were randomly assigned to subitramine ( 5064 subjects) or a placebo ( 4990 subjects) in a double‑blind fashion. The primary outcome measured was the occurrence of any of the following events: nonfatal myocardial infarction or stroke, resuscitation after cardiac arrest, or cardiovascular death. The primary outcome was observed in 575 subjects in the subitramine group and 503 subjects in the placebo group. Do the data give good reason to think that there is a difference between the proportions of treatment and placebo subjects who experienced the primary outcome? (a) State hypotheses, find the test statistic and use either software or Table A for the 𝑃 ‑value. Give both the test statistic and the 𝑃-value to three decimal places. Test statistic 𝑧= 2.0567 𝑃 ‑value = .0397 What is the conclusion found from the 𝑃 ‑value? Select the correct explanation. We have strong evidence that the proportion of subjects on sibutramine who are suffering a primary outcome differs from those who are on the placebo. We are unable to come to a conclusion with the provided information. We have no evidence that the proportion of subjects on sibutramine who are suffering a primary outcome differs from those who are on the placebo. We have very little evidence that the proportion of subjects on sibutramine who are suffering a primary outcome differs from those who are on the placebo. (b) Why was it important to have a placebo in this study? Select the correct explanation. None of the reasons are correct. Because the 𝑃 ‑value is small, there is a no difference in the proportion of primary outcomes between sibutramine and placebo. Because the patients might have an extreme reaction to sibutramine usage. A placebo should be used to blind patients to which group they are in and to account for any possible placebo effect.
Lien L.
The Nurses' Health Study (NHS) is another very large observational study which has brought many insights into women's health. It began in 1976 by Dr. Frank Speizer, with questionnaires that were mailed to 121,964 female registered nurses in the United States asking about their medical history, cholesterol and blood pressure, current medications, and so on (one of the benefits of studying nurses is their ability to give reliably accurate answers to these questions). The study's initial focus was on investigating the long-term health effects of oral contraceptives, whose use had become much more widespread in the U.S. during the 1960s, but the focus soon expanded to investigating a wide variety of questions on women's health. The NHS continues to this day, tracking its third generation of nurses in the US. One of the most consequential early findings from the NHS was about hormone replacement therapy (HRT): supplementary estrogen and progesterone for post-menopausal women to relieve side effects of declining hormone levels due to menopause. The NHS found that HRT in postmenopausal women was negatively associated with heart attack risk. In a landmark 1985 paper in the New England Journal of Medicine (NEJM), Speizer and his coauthors wrote that "As compared with the risk in women who had never used postmenopausal hormones, the age-adjusted relative risk of coronary disease in those who had ever used them was 0.5 (95 per cent confidence limits, 0.3 and 0.8; P = 0.007)... These data support the hypothesis that the postmenopausal use of estrogen reduces the risk of severe coronary heart disease." (Stampfer et al., 1985) In other words, the authors are saying that women on HRT are half as likely to suffer a heart attack over a certain time period. We'll define the term "relative risk" later in this section, and we'll also investigate the interpretation of these claims and their statistical basis. Because women could (and did) drop into and out of the comparison groups in the middle of the study, it is difficult to make a table like we usually would, with one row per participant. In medical studies, individuals are typically weighted by the amount of time that they enrolled in the study. A more convenient sampling unit is a person-month at risk, which is one month spent by a particular woman in one of the comparison groups, during which she might or might not suffer a heart attack. Here, "at risk" just means the woman is being tracked by the survey in either of the two comparison groups, so that if she had a heart attack it would be counted in our data set. Example: The table below tracks the histories of two hypothetical post-menopausal women in a six-month longitudinal study, who both enter the study in January 1978: Name Month HRT Heart Attack Alice Jan 1978 0 0 Alice Feb 1978 0 0 Alice Mar 1978 0 1 Beatrice Jan 1978 0 0 Beatrice Feb 1978 0 0 Beatrice Mar 1978 0 0 Beatrice Apr 1978 1 0 Beatrice May 1978 1 0 Beatrice Jun 1978 1 0 The probability that a heart attack will happen to a given at-risk person in a given duration of time is called the hazard rate. The NHS calculated its effects in terms of the relative risk, which is simply the hazard rate for person-months in the HRT (Group A) group divided by the hazard rate in the no-HRT (Group B) group. Relative Risk = Hazard Rate (Treatment Group) / Hazard Rate (Control Group) Question 3. Complete the following statements, by setting the variable names to the value that correctly fills in the blank. If the hazard rate of the treatment group is greater than the hazard rate of the control group, the relative risk will be _greater than_ one. This means that individuals in the treatment group are at _higher_ risk of having a heart attack compared to those in the control group. If the hazard rate of the treatment group is less than the hazard rate of the control group, the relative risk will be _less than_ one. This means that individuals in the treatment group are at _lower_ risk of having a heart attack compared to those in the control group. If the hazard rate of the treatment group is equal to the hazard rate of the control group, the relative risk will be _equal to_ one. This means that individuals in the treatment group are at _equal_ risk of having a heart attack compared to those in the control group.
Shyam P.
Exercises 6.174 through 6.177 refer to a study on hormone replacement therapy. Until 2002, hormone replacement therapy (HRT), taking hormones to replace those the body no longer makes after menopause, was commonly prescribed to postmenopausal women. However, in 2002 the results of a large clinical trial $^{44}$ were published, causing most doctors to stop prescribing it and most women to stop using it, impacting the health of millions of women around the world. In the experiment, 8506 women were randomized to take HRT and 8102 were randomized to take a placebo. Table 6.13 shows the observed counts for several conditions over the five years of the study. (Note: The planned duration was 8.5 years. If Exercises 6.174 through 6.177 are done correctly, you will notice that several of the p-values are just below 0.05 . The study was terminated as soon as HRT was shown to significantly increase risk [using a significance level of $\alpha=0.05]$, because at that point it was unethical to continue forcing women to take HRT). Does HRT influence the chance of a woman getting cardiovascular disease?
Inference for Means and Proportions
Hypothesis Test for a Difference in Proportions
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