Statistical stuff happens Vioxx, placebo power and other wonders

A few headlines Low fat diet breast cancer hope ( BBC May 2005 ) Breast cancer link to high fat foods ( The Scotsman, July 2003 ) Low- Fat Diet May Control Prostate Cancer ( Health News, August 2005 ) Low-fat diet, not wine, fights heart disease in France (CNN May, 1999 ) High-Fat Meal May Raise Risk Of Blood Clotting -- Increasing Heart Attack And Stroke Risk ( American Heart Association, November 1997 )

National study finds no effect from reducing total dietary fat The study, a project of the National Institutes of Health, had taken eight years, cost $415 million, and involved nearly 49,000 older women, 40 percent of whom were assigned to a diet that kept their intake of calories from fat significantly below that of the other 60 percent. Researchers had expected to confirm what earlier studies and conventional medical wisdom had long suggested -- that consuming less fat is good for your health. Researchers found no difference between the two groups in terms of risk of breast cancer, colon cancer, heart disease or stroke. Public release date: 7- Feb-2006

Three Great Men Dr John Snow ( ) Sir Ronald Aylmer Fisher ( ) Sir Austin Bradford Hill ( )

Dr John Snow The father of modern epidemiology

Sir Ronald Aylmer Fisher perhaps the most original mathematical scientist of the [twentieth] century Bradley Efron Annals of Statistics (1976) Fisher was a genius who almost single-handedly created the foundations for modern statistical science …. Anders Hald A History of Mathematical Statistics (1998) Sir Ronald Fisher … could be regarded as Darwins greatest twentieth-century successor. Richard Dawkins River out of Eden (1995) I occasionally meet geneticists who ask me whether it is true that the great geneticist R. A. Fisher was also an important statistician. Leonard J. Savage Annals of Statistics (1976)

Randomisation! Let it not be thought that Fisher in any way regarded Randomisation as an optional extra to significance testing. One of the earliest sub- headings in his seminal book is Randomisation; the Physical Basis of the validity of the Test. Fishers many words on the subject can be boiled down to a simple statement – no randomisation means no significance!

The one-in-twenty lottery!

Publication Bias!

Sir Austin Bradford Hill Association of cigarettes with lung cancer Over-emphasis of significance testing The Hill Criteria –Not about causation!

Relative Risk If X% of people exposed to a putative cause suffer a certain effect and Y% not exposed to the cause (or alternatively the general population) suffer the same effect, the RR is X/Y

Relative Risk In epidemiologic research, [increases in risk of less than 100 percent] are considered small and are usually difficult to interpret. Such increases may be due to chance, statistical bias, or the effects of confounding factors that are sometimes not evident.[Source: National Cancer Institute, Press Release, October 26, 1994.] 100% increase is a relative risk of 2.0

The little red book

Some major causes of error Statistical variation Confusing correlation with causation Confounding factors Trend fitting Extrapolation Ignoring inconvenient data

Some major causes of error Statistical variation Confusing correlation with causation Confounding factors Trend fitting Extrapolation Ignoring inconvenient data

Diet Coke is mainly drunk by fat people. Therefore Diet Coke causes obesity.

Correlation is not causation!

Some major causes of error Statistical variation Confusing correlation with causation Confounding factors Trend fitting Extrapolation Ignoring inconvenient data

Example of confounding The Henry Ford Hospital in Detroit published a report linking the use of antibiotics in children with the subsequent development of asthma. They ignored the fact that the antibiotics must have been prescribed for serious conditions, including lung infections.

Some major causes of error Statistical variation Confusing correlation with causation Confounding factors Trend fitting Extrapolation Ignoring inconvenient data

Some major causes of error Statistical variation Confusing correlation with causation Confounding factors Trend fitting Extrapolation Ignoring inconvenient data

What happens next?

1975

Now thats extrapolation!

Some major causes of error Statistical variation Confusing correlation with causation Confounding factors Trend fitting Extrapolation Ignoring inconvenient data

Keys

Keys redrawn

The data dredge The data dredge is a method of producing impressive results by examining in one cohort a number of combinations of diseases and causes, but treating them as though they were all independent trials. e.g. for ten combinations P<0.05 is claimed, whereas in reality it is P<0.401.

The Harvard Nurses Health Study Vitamin and carotenoid intake and risk of squamous cell carcinoma of the skin. Vitamin D, milk consumption, and hip fractures: a prospective study among postmenopausal women. Prospective study of sleep duration and coronary heart disease in women. Prospective study of self-reported sleep duration and incident diabetes in women. Meat, fish and egg intake and risk of breast cancer. Major dietary patterns and the risk of colorectal cancer in women. Adolescent diet and risk of breast cancer. Plasma folate, vitamin B6, vitamin B12, homocysteine, and risk of breast cancer. High-dose antioxidant supplements and cognitive function in community-dwelling elderly women. Caffeine, postmenopausal estrogen, and risk of Parkinsons disease. Television watching and other sedentary behaviors in relation to risk of obesity and type 2 diabetes mellitus in women ……………….. Just a dozen of the 500 plus papers

Correlation is not causation!

Does size Matter?

21 st April 2006 Jury: Merck liable in elderly man's death RIO GRANDE CITY, Texas -- A state jury found Merck & Co. liable Friday for the death of a 71-year-old man who had a fatal heart attack within a month of taking its since-withdrawn painkiller Vioxx and ordered the company to pay $32 million. Merck said it would appeal. Vioxx was found to greatly increase the risk of heart attacks in people who took the painkiller for 18 months or longer.

Rofecoxib 1 FDA Advisory Committee A Kaplan-Meier analysis (Figure 31) of the cumulative incidence of confirmed thrombotic cardiovascular serious adverse events over time shows that the separation of the trend lines for rofecoxib and placebo did not begin until after 18 months of continuous daily treatment. Prior to 18 months there was no apparent difference in the cumulative incidence of these events in the two groups as evidenced by the overlapping lines. The changing pattern of treatment effect over time was confirmed by the failed test for proportionality of hazards (p=0.006). The difference between rofecoxib and placebo beginning after 18 months appears to primarily reflect a relative flattening of the placebo curve after 18 months compared with the preceding 18 months (Figure 31). Baseline characteristics of those patients with events beginning after 18 months were comparable between the treatment groups (data not shown).

The difference between rofecoxib and placebo beginning after 18 months appears to primarily reflect a relative flattening of the placebo curve after 18 months compared with the preceding 18 months (Figure 31).

What they are actually saying Regardless of the age of the patient, taking a placebo for more than eighteen months effectively prevents heart disease!

Electric breakdown (1964)

The law of experiments The first trial always produces a result that is bizarre and points to a great scientific breakthrough. First corollary The effect never reappears in any subsequent trials.

The law of experiments The first trial always produces a result that is bizarre and points to a great scientific breakthrough. First corollary The effect never reappears in any subsequent trials. Second corollary In fields such as epidemiology and drug testing there is only one trial.

And finally This lecture has dealt with the lunatic fringe of certain branches of science in general and epidemiology in particular. It is important to remember, however, that the tradition of Dr John Snow lives on in the huge organisation of disease detectives, who monitor potential epidemics and organise the international response to them.