Arts, Books, Medical, Science

Book Review: Cured

SCIENCE: SPONTANEOUS REMISSION

Rediger

Intro: Can hope and happiness cure the incurable? 

Jeffrey Rediger, a psychiatrist at Harvard Medical School, could hardly have imagined that his compelling book about illness and wellness, would have been published in the middle of a virulent and catastrophic pandemic.

Dr Rediger offers many clinically documented examples of patients stricken with terrible, often terminal, diseases and sometimes given just weeks to live, who then confounded medical science and got better. He tells us how they did it, or at least how they appeared to do it.

In one way, the coronavirus makes these stories less than timely. Nobody is suggesting that changes in diet, exercise, eliminating stress, or finding love (all of which are used to explain various cases of “spontaneous remission”), can overwhelm the dreaded and deadly Covid-19.

Yet in many other ways, Cured couldn’t be timelier. In this crisis, we are all thinking about our health like never before and the notion that we might, in some circumstances, be able to chase away life-threatening diseases ourselves, feels more resonant than ever.

Rediger introduces us to Claire Haser, who was 63 when, in 2008, she was diagnosed with the most aggressive form of pancreatic cancer. Told to expect no more than 12 months, she declined dangerous surgery in favour of letting “nature take its course”. But she resolved to focus not on dying, but on living “with as much zest and happiness as I could for however long I had left”. The year passed. Then another.

In 2013, she was hospitalised for a scan of her abdomen, unrelated to her illness. Doctors were astonished to find the tumour had vanished.

Nobody knows for sure what made the tumour disappear. Diet was perhaps part of it; Claire had started eating much more healthily, but she’d altered her mindset, too, confronting certain fears and obstacles that had always held her back in life. All these factors, Rediger argues, allowed her immune system to do its job again.

Rediger has spent 17 years examining cases of spontaneous remission all over the world, looking for common ground. Many of these people he met, whose remarkable stories are explained by science as “flukes” and by religion as “miracles”, had radically changed their lifestyles. This connection between mind and body has never been encouraged by Western cultures, but it is at the heart of Eastern medicine.

Physical, mental, emotional and spiritual health are all irrevocably entwined and, just as they can combine to make us ill, so they can sometimes combine to make us better.

If you’re unconvinced by how powerful the mind can be in generating physical wellbeing, consider the placebo effect. Rediger recalls the case of a Mr Wright in 1957, who, dying from cancer of the lymph nodes, begged his doctors to try experimental drug Krebiozen.

As soon as they did, his astonished doctor reported that his tumours “melted like snowballs on a hot stove”. Two months later, reports circulated that this supposed miracle drug was a fake.

Mr Wright immediately relapsed, but as he lay close to death, his doctor told him the reports were wrong and he had a double-strength version of the serum. He injected it. The tumours vanished again. But the doctor had injected only water.

Rediger wants Western clinicians to embrace the “medicine of hope”.

He isn’t trying to dissuade us from seeking medical intervention. He accepts that, more often than not, there is no simple, non-medical equation; that “eat right” plus “fall in love” does not usually add up to a cure for aggressive diseases.

But how reassuring it is, especially in these horribly uncertain times, to know that sometimes it does.

– Cured by Jeffrey Rediger is published by Penguin, 400pp

Standard

Hues Like Hers

Arts, Poetry, Scotland

Hues Like Hers

Image
Education, Information, Science, Society, Technology

Information Society: Probability and Statistics

INFORMATION AGE

WE live in an information age in which modern technology makes it easy to gather large amounts of information on almost every aspect of our lives. However, on its own this information is of only limited value – it needs to be organised and analysed to be of practical use.

 

INFORMATION about population numbers have been collected since ancient times (see Appendage), but the science of analysing and making sense of data – statistics – is relatively recent. Although now not usually considered to be a branch of mathematics, statistics relies on mathematical analysis to interpret information and is closely linked to the area of mathematics known as probability theory.

Chance and probability

The beginnings of probability theory came from the fascination that two 17th-century French mathematicians had with games of chance. Blaise Pascal and Pierre de Fermat discussed, in a series of letters, a method of calculating the chances of success in gambling games, and they were the first to give the subject of probability a scientific treatment.

What they discussed was a mathematical way of determining the probability of a particular outcome occurring in a random event, such as tossing a coin or throwing a dice. When a coin is tossed there are two possibilities: heads or tails. Each is equally likely: there is one chance in two that the coin will come up heads (or tails), or in other words the probability is 1/2. The six faces of a dice give one chance in six of throwing any particular number, a probability of 1/6. In games using more than one dice, or a deck of cards, or a roulette wheel, the calculation becomes more complex but is essentially built from basic principles and is the same. From this discussion of gambling games, a theory of probability evolved.

The idea was further developed by the next generation of mathematicians. French mathematician Abraham de Moivre discovered a pattern to the probability of outcomes, now known as normal distribution and represented graphically as the bell curve.

Bell Curve

[Bell Curve: Normal distribution] – When certain values (such as height) are plotted against the number of occurrences of that value (how many people are of a specific height), the result is often a bell-shaped curve – the normal distribution. The most common value, at the peak, is the mean (average).

British mathematician and clergyman Thomas Bayes took de Moivre’s ideas further with his theorem of conditional probabilities, which makes it possible to calculate the probability of a particular event occurring when that event is conditional on other factors and the probabilities of those factors are known. Bayes’ work was further developed by Pierre-Simon Laplace, a French mathematician and astronomer whose application of Bayes’ theorem to real cases led to a new field of study: statistics.

Detecting patterns

The pioneering work in statistics was done by de Moivre, who used data about death rates and rates of interest to devise a theory of annuities, which enabled insurance companies to compile tables of risk for life assurance based on scientific principles. This application of mathematics to data in records was at first known as “political arithmetic”, and, as patterns emerged in collections of data, research began into their underlying statistical laws. To begin with, statistics was concerned with social issues, and advances in sociology and criminology were made by the Belgian mathematician Adolphe Quetelet, who introduced the concept of the “average man”. He also believed mathematics lay at the heart of every science, and statistical analysis could be applied to data of all kinds. Perhaps the area where this had greatest effect was medicine, where an important new study, epidemiology (occurrence of disease in populations), developed from medical statistics.

As more practical use was made of probability theory and statistics, the mathematics behind them was developed by various mathematicians, including the Frenchman Adrien-Marie Legendre, the German Carl Friedrich Gauss, and the Russian Andrey Nikolaevich Kolmogorov, whose systematic approach to the subject forms the basis for much of modern probability theory.

Modern statistics

Statistics plays a key role in much of modern life. Governments collect and analyse a wide range of personal data to detect patterns that can help shape policies. Businesses use market research to gather information about potential customers and apply statistical methods to analyse the data. In science, statistics and probability are central to subjects such as quantum theory and are also essential to many other subjects, from psychology and economics to information science.

Data Samples

In practice, the data used for statistical analysis must be sound for it to produce useful results. The data must be collected using a valid method that measures what is intended, and the data must be accurate. It is also essential that the set of data is large enough and constitutes a representative sample. For example, in general public opinion polls the right questions must be asked in an unambiguous, neutral way; sufficient numbers of people must be polled; and, as a whole, the respondents must be representative of the population (for instance, in age and gender).

Applications

Coxcomb2

Florence Nightingale’s “coxcomb” graph – This graph devised by Florence Nightingale shows the relative causes of death among soldiers in one 12-month period during the Crimean War (1854-56).

. Coxcomb graphs – Working as a nurse for British troops during the Crimean War, Florence Nightingale kept records of troop deaths and later used the information to create what are now called “coxcomb” graphs. These highlighted the number of deaths that were not directly caused by combat but by factors such as wound infection and disease.

. Computerised Modelling – The development of probability and statistics gave scientists new ways to analyse and conceptualise the physical world.

Many natural systems are influenced by numerous factors and exhibit chaotic behaviour. For example, influences on the weather include air, land, and sea temperatures, winds, sea currents, humidity, and the amount of sunlight. Minute changes in any one of these factors can have a profound effect on the weather. Because of this, weather forecasting relies on numerical models in which statistical methods are used to arrive at predictions that have various degrees of probability of being correct.

. Quantum Theory – The currently accepted theory of the nature and behaviour of matter at the subatomic level, quantum theory uses probability as one of its fundamental tenets. For example, according to quantum theory it is impossible to know precisely the location and momentum of subatomic particles such as electrons “orbiting” the nucleus of an atom; it is only possible to specify regions – known as clouds – where particles may be located with the highest probability.

Appendage

Early Censuses

The earliest known census dates from ancient Babylonian times, about 3800 BCE, and recorded the human population and agricultural data.

Many of the other ancient civilisations also regularly recorded population numbers, often for the purposes of taxation. In the Middle Ages, probably the best-known census is the Domesday Book, which was instigated by William I of England in 1086 to tax the recently conquered population. These early censuses were simply records of numbers because mathematical techniques for analysing data had not yet been developed.

Standard