What the quacks fear more than the Devil fears Holy Water

I wrote the text long ago, back in 2001. This is the original: http://www.ariplex.com/ama/amasumpf.htm
My thanks to Steelclaws, who now made an English translation. Here it is:

What the quacks fear more than the Devil fears Holy Water

A sensational title? That is true, but it is appropriate.

Let's start the topic with a simple example, that of two paths through a swamp:

You probably now have two thoughts:

1st, naturally to take the path B

2nd, to ask what does the example have to do with the title.

The answer will possibly amaze you: The above example has a devastating effect if you use it in a forum or a discussion.

You can test this: Use the example in a discussion about the impact and effect of evidence of remedies completely unexpectedly and without explanation.

Why, and that's the sticking point, is there then an awkward silence? Why this fear?

Let's analyse the whole issue.

The example has the two possibilities. Option A is a very dangerous path, B is a dangerous path, but much safer than A.

The choice between A and B will not go away. One of the two paths MUST be taken. But which one?

It does not take much thought to see that the path B provides a better probability of survival. So why should anyone take the greater risk of the path A?

Taking the path B, 800 arrived out of 1000. The survival probability is thus 80% (eighty percent).

10 out of 1000 arrived after taking the path A. The survival probability is therefore 1% (one percent).

When someone goes through the swamp, he can survive both the paths B and A. But he won't know before taking one of the paths if he will survive.

Taking the path B is not a guarantee of survival. Why is it still better to follow it? Answer: Because it can be assumed that the probability of survival will not be very different compared to the previous attempts at taking the path B. The important concept is "reproducibility" (repeatability). If we send 1000 people over route B and 800 of them survive, then we can be reasonably sure that of the next 1000 also 800 will survive. But we can not predict which individuals will survive.

In daily life, the concept of reproducibility is not often considered - and in deciding "path A or path B?" one does not think much on the concept. It is simply assumed that - "if so many come through" - we'll handle it as good as they did. But this is nothing but the practical implementation of the concept of reproducibility!

The reproducibility is one of the crucial points in medicine. Should you take drug A or drug B? Answer: You choose the drug whose results are reproducibly shown to be the best. Why should you settle for something worse?

The reproducibility in medications or treatments requires constant monitoring. It is possible that suddenly the drug won't work any longer or previously unknown side effects occur. Some side effects appear only after a long delay.

The reproducibility is not for granted and it is not something unchangeable! They have to control it by constantly monitoring ALL cases.

This means statistics, statistics, statistics. Statistics help to save lives.

Based on the swamp example, the statistics say that 80% survive the path B and only 1% path A. Because of reproducibility, it will be better to take B in the future.

Concerning drugs, the statistics say that drug B is better than drug A. And so the trap snaps shut: would you take a drug where they conceal the probability of effectiveness?

What do you think of a manufacturer who bluntly declares that he was not accountable on the probability of effectiveness: You should take his treatments - and that's it! ...

"Not possible" you say. Unfortunately, however, as the many examples in recent years have shown again and again, it is very possible.

Instead of publishing the statistics on effectiveness, these manufacturers claim with barely surpassable impudence, for example, that their medicines and healing methods can not be tested - because you "must individualise the remedies for every person".

Certainly, but the crocodiles in the swamp go individually to every traveller, and it is the bottom line whether a green or a black or a brown crocodile bites last. Dead is dead. And "dead is dead" also applies to people who need medicine! What counts is the number of survivors. If a treatment has not 1 or 2, but hundreds of individual drugs, why not? Then count the survivors of this form of treatment. Really simple.

Although simple, yet the statistics is withheld. One could speculate whether the statistics were perhaps too complicated, but that is not the case. Counting the survivors is really easy. Nevertheless, it is not done ...

One might argue that it is not always a matter of life and death. That is correct. But if a person is sick, then there is the possibility 1) he will become healthy and possibility 2) he will not become healthy. And between sick and healthy it should be possible to distinguish So, it is not that difficult. But YET!, the manufacturers refuse.

What reason could there be to refuse to provide the evidence for the efficacy of a cure or a treatment, moreover, when such supposedly fantastic effectiveness is being advertised with?

If the drug is really that good, then it is logical that the proof can be provided without any doubt. Or maybe not ...?

If the drug is, however, bogus, so - what then ...? But that's never the case, isn't it, because otherwise the manufacturer would not advertise it with the claims of effectiveness. Or does it ...?

Did you know, that in Germany there are sold every year for a two-digit sum of billions of Euros medicines and remedies for which there is NO evidence of effectiveness?

To summarize:

With a simple example it can be shown that reproducibility is the foundation of a reasonable (rational) medicine.

Only through continuous monitoring of effects and side effects - and their analysis - can the quality of a medicine be determined.

Even if there are variants of a medicine, a collated statistics can show its success or failure.

And yet - there are manufacturers who refuse to test for efficacy.

Which path would you take, A or B?

Aribert Deckers

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