Re: Epidemiology Epedemic - Ideas for Individual Overdose?

["Howard Long" <hflong@pacbell.net>]

Jerry, I agree with everything below except your spelling of  "epedemic".



Seriously, epidemiology is a good source of ideas, and great teacher of

skepticism.

But, even the best of studies, like Fields (Iowa lung cancer related to more

radon), or the Women's Health Initiative (WHI) by top universities

(comparing estrogen/progestin with placebo) does great harm, when

misapplied.



Am Cancer Soc concluded "radon causes lung cancer" from that high radon, low

lung cancer 1% outlier - although B Cohen found counties with most radon had

lowest corrected  lung cancer mortality rates.



 JAMA, NEJM, and all the "standard care" lemmings followWHI in fearmongering

older women out of bone-saving e/p replacement, by citing 25% more heart

attacks than placebo - although by separating the 50% of never-smokers

(still concealed) there might be a 250% LESS CV death rate for them, as in

Layde's classic study (graphed in all oral contraceptive disclosure).

Misapplied, again.



Also, individual differences in response are vast.  So application of

epidemiologic data is an art for physicians to test gradually on

individuals. It is not a science for socialist medicine bureaucrats to

dictate. That is why HMOs, Clinton care and Single Payer won't work here -

and England's private care expands.  HSAs, self managed care with tax

savings and  cheap, $4,000 deductible insurance (the plan proposed by Bush),

has worked best.



Does anybody on Radsafe have data, even anecdotes, of how to predict

individual  responses to low level ionizing radiation? We do for sunshine:

"Wear a sombrero - you have fair skin and freckles." The best I can guess is

1, feeling of warmth or 2, redness. This may be important for HPs and MDs to

advise individuals  exposed to terrorist activity, CT, treatment of

gangrene, etc.



ALARA is archaic, lazy and damaging.



Howard Long



Original Message ----- 

From: "jjcohen" <jjcohen@PRODIGY.NET>

To: <radsafe@list.vanderbilt.edu>

Sent: Saturday, July 03, 2004 11:10 AM

Subject: Fw: Epidemiology Epedemic>

> ----- Original Message -----

> From: jjcohen

> To: Jerry Cohen

> Sent: Friday, July 02, 2004 4:38 PM

> Subject: Fw: Epidemiology Epedemic

> > ----- Original Message -----

> From: jjcohen

> To: radsafe@list.vanderbilt.edu

> Sent: Friday, July 02, 2004 4:08 PM

> Subject: Fw: Epidemiology Epedemic

> > In previous discussions on radsafe, concerns were expressed regarding

how

> epidemiology had been applied in determining effects of exposure to radon,

> radioactivity , and 'hazardous" materials in general.

> It appeared, at least to me, that certain epidemiological determinations

> were being made that defied common sense. Recently, on another website, I

> came across the following review  and thought the group might be interest.

> Anyone have any thoughts on the subject??   Jerry Cohen

>

> An Epidemic of Epidemiology

> by Rob Lyons

>

> Fifty years ago, we discovered that smoking is bad for us. In 1954, Austin

> Bradford Hill and Richard Doll published a preliminary report on a study

> showing the very strong correlation between smoking and premature

mortality

> (1).

>  However, this classic study has in many ways sent medical science up a

blind

> alley. While the dangers of smoking have been demonstrated in numerous

> subsequent studies, the attempts to find the New Smoking - another example

> of an environmental or lifestyle factor that causes substantial health

> problems - have largely failed. But the many pieces of junk science that

> have been produced in the process have provided the ammunition for

> unwarranted health scares too numerous to mention.

>

>  This state of affairs is well described in John Brignell's new book The

> Epidemiologists. Hill and Doll were given the task of trying to find out

why

> cases of lung cancer had increased 15-fold in only 25 years. Their first

> attempt was to ask 649 lung cancer patients, and 649 matched controls,

about

> their habits. What they found was a correlation between smoking and lung

> cancer, albeit not a very strong one. However, it was strong enough to

> warrant a fuller study, starting with a large group of healthy

individuals,

> assessing their smoking habits and then monitoring them to see what

diseases

> they developed.

>

>  This study began in 1951. Their method was to write to every doctor in

the

> country - around 35,000 doctors replied, of whom only 17 per cent were

> lifelong non-smokers (how times change). The doctors were asked just a few

> questions about their smoking habits. Three years later, Hill and Doll

> published their first analysis of the results, and were already able to

> indicate how strong the link was between smoking and lung cancer.

>

>  What they found was that persistent smokers were 24 times more likely to

> develop lung cancer than non-smokers. Moreover, the risk of death from

heart

> disease in any particular year was roughly doubled. This study has been

> followed up every few years, and these results have been confirmed time

and

> again.

>

>  Hill made it clear, however, that such a study had to comply with some

> pretty strict criteria in order to be considered valid. These criteria are

> worth restating, because they stand in sharp contrast to the bulk of

> epidemiological research:

>

> 1. Strength

> Is the association strong enough that we can rule out other factors?

> 2. Consistency

> Have the results been replicated by different researchers, and under

> different conditions?

> 3. Specificity

> Is the exposure associated with a very specific disease as opposed to a

wide

> range of diseases?

> 4. Temporality

> Did the exposure proceed the disease?

> 5. Biological gradient

> Are increasing exposures associated with increasing risk of disease?

> 6. Plausibility

> Is there a credible scientific mechanism that can explain the association?

> 7. Coherence

> Is the association consistent with the natural history of the disease?

> 8. Experimental evidence

> Does a physical intervention show results consistent with the association?

> 9. Analogy

> Is there a similar result to which we can draw a relationship?

> Above all, as Brignell emphasizes, correlation does not prove causation.

He

> draws an analogy with growing tomatoes and fertilizer. It can easily be

> shown that increasing use of fertilizer will increase tomato yields. But

> fertilizer does not cause tomatoes, it merely promotes the process of

> growth. The same goes for smoking and lung cancer. Smoking may massively

> promote the growth of lung cancer, but it does not cause the tumours. Hill

> and Doll had nothing to say about why cancer occurs in the first place.

>

> Nonetheless, it is an entirely reasonable conclusion to draw that smokers

> will, on average, die younger than non-smokers, and we do not need to know

> the precise mechanism to conclude that giving up smoking is prudent from a

> health viewpoint.

>

> What is not reasonable is the response to this one, classic study. First,

it

> has provided the justification for state intervention in lifestyle in a

> previously unprecedented way. Secondly, it has encouraged the

proliferation

> of other studies, which make grand statements about disease based on

> correlations far weaker than those found by Hill and Doll.

>

> Brignell's book is a handy demolition of the science and statistics behind

> this epidemic of epidemiology. He shows how statistical tests were

> originally developed, based on certain assumptions. However, these

> assumptions have long since been forgotten, so that meeting certain

abstract

> criteria has been elevated above whether the results are actually of any

> real-world importance.

>

> The most important of these is the test for statistical significance. The

> idea behind this is that patterns can be found in any set of random

results.

> For example, in the spiked office, there are a number of people who were

> born in May or June, but none were born in July. It would be possible to

> draw the conclusion that there is something special about being born in

May

> or June that predisposes people to become journalists. This would be a

> bizarre conclusion to draw from just a handful of people. In fact, the

> spread of birthdays is completely coincidental.

>

> In research it is therefore useful to have a preliminary statistical test

of

> results, to see how likely it is that they could be due to blind chance.

The

> usual benchmark is that if the chances of a set of results being

> coincidental are less than five per cent, it is reasonable to go on to

> assess whether the results are actually meaningful.

>

> First, just because a study passes this test does not mean its results

> aren't a complete coincidence. In fact, by definition, five per cent of

> studies could pass this test even though the results are meaningless.

>

> Secondly, just because the results are statistically significant doesn't

> mean they are practically significant. Brignell gives the example of a

book

> called The Causes of Cancer, written by Richard Doll and Richard Peto.

> Illustrating Doll's fall from previous high standards, the book describes

> some deaths of people in their 80s and 90s as 'premature'.

>

>   The public health agenda is justified by research that is often

completely

> worthless

> These days, however, it seems that any result that passes this 'p-test' is

> increasingly regarded as significant. Five per cent sounds like a low risk

> of results being meaningless, until you realise that researchers often

> plough through many, potential risk factors (what Brignell calls a 'data

> dredge'), look for an apparently significant result, then try to speculate

> some kind of mechanism to explain it, no matter how bizarre. So a test

> designed as an initial filter to weed out spurious results is used to give

> credence to them.

>

> Thus he provides a huge list of different factors that have, at one time

or

> other, been accused of causing cancer: abortion, acetaldehyde, acrylamide,

> acrylontiril, agent orange, alar, alcohol, air pollution, aldrin,

alfatoxin,

> arsenic, asbestos, asphalt fumes, atrazine, AZT.and that's just the letter

> 'A'.

> There are also a number of techniques in epidemiology for imposing

> assumptions on to data. The best of these is trend fitting. No set of data

> will exactly fit a pattern but often a clear trend can be found

nonetheless.

> However, many studies appear to resort to drawing a line through an

> apparently unconnected series of measurements to demonstrate an underlying

> effect.

>

> Epidemiology can be an effective tool when applied to the spread of

> infectious disease. Unfortunately, there really isn't anything like enough

> infectious disease in the developed world to justify the existence of so

> many departments and researchers. In fact, the overwhelming cause of death

> in the developed world is old age - a factor that is, incredibly,

frequently

> ignored by researchers. A person in their eighties is a thousand times

more

> likely to develop cancer than someone in their thirties. This factor is so

> powerful that for most of the causes of disease studied, a very minor

> underestimation of the effect of age can wipe out any putative effect from

> the factor in hand.

>

> Age is obvious - but many other confounding factors are not. Therefore, we

> return to Hill's first criterion: to be sure there is actually something

> going on, the effect must be strong. Otherwise, any apparent effect may

> prove to be entirely illusory.

>

> A topical example of this is passive smoking, and in particular what

> Brignell calls 'the greatest scientific fraud ever'. In 1992, the US

> Environmental Protection Agency published a meta-study, bringing together

> many other studies on passive smoking. Unfortunately, the results were

> negative. It appeared that passive smoking was not a health risk at all.

> Mere facts could not be allowed to get in the way of a health scare, so

some

> imagination was applied to the problem. One negative study was removed -

but

> the meta-study still produced no statistically significant result.

>

> So the goalposts were not so much moved as widened. The organisation found

> that there was a greater than five per cent chance that the results were

> coincidental, but less than 10 per cent - so they accepted them anyway. In

> other words, the EPA accepted a bigger risk that the effect they found was

> purely due to chance, quite at odds with standard practice.

>

> The increased risk of lung cancer they found - 19 per cent - was frankly

too

> small to have been conceivably detected given the methods they used. There

> are lots of ways in which inaccuracy could have crept into this final

> result. For example, is it really possible to merge the results of many

> different studies, all with different methodologies and subjects,

> accurately? How could someone's actual exposure to environmental smoke be

> measured over the course of years? Were all the people who said that they

> were non-smokers absolutely honest? As indicated above, were other

possible

> contributory factors such as age, gender and income controlled for

> accurately?

>

> We can be pretty confident about Hill and Doll's conclusions about lung

> cancer because the effect they found is massive - an increased risk of

2400

> percent. To suggest that such a small effect as 19 per cent could be

> accurately measured in this way is like trying to time a race with a

> sundial.

>

> That has not prevented smoking being banned in public places on the

grounds

> that thousands of people might die from inhaling second-hand smoke. The

> public health agenda is therefore driven and justified by research that is

> more often than not completely worthless.

>

> It is undoubtedly the case that Hill and Doll's study has caused people to

> give up smoking and extended many lives as a result. But it has also

> inspired a heap of unnecessary panics based on dodgy research, and public

> health campaigners only too willing to tell us how to live our lives.



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