Statistical stuff happensVioxx, placebo power and other wonders

A few headlinesLow 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 (1813 -1858)

• Sir Ronald Aylmer Fisher (1890 -1962)

• Sir Austin Bradford Hill (1897-1991)

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 Darwin’s 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. Fisher’s 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 Correlation is not not

causation!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 that’s 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 Parkinson’s 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 Correlation is not not

causation!causation!

Does

size

Matter?

21st 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 1FDA Advisory Committee

A Kaplan-Meier analysis (Figure 31) of the cumulative incidence of confirmedthrombotic 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 ofcontinuous 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 overlappinglines. The changing pattern of treatment effect over time was confirmed by the failed testfor 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 placebocurve after 18 months compared with the preceding 18 months (Figure 31). Baseline

characteristics of those patients with events beginning after 18 months were comparablebetween 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 experimentsThe 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 experimentsThe 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 corollaryIn 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.

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