In fact, I'm quite angry that there aren't enough patient-oriented sites that overcome the pessimism and despair that the medical literature probably engenders in people who do not understand statistics. The excessive use of median survival times when talking about cancer probably contributes to depression and hopelessness in patients and families, at a time when they should be fighting with all their might.
To put it simply, the median (where 50% of the population falls) is not always the same as the mean (average). So if 50% of people with a certain diagnosis die within 3 months, then 50% do not, and some people may survive for many years later. We call this a skewed distribution, and in my extensive reading about GBMs, being over 60, having an inoperable tumour or one that can only be partly removed, being physically unwell, and male makes someone more likely to be in the first 50%. Many people die because their tumours are caught too late, or are inoperable, some older patients are not even offered surgery - this data shouldn't be used to create outcome data for all people with GBMs, as it will give an overly negative impression for younger patients and those who have surgery. Ideally, the outcome data should be stratified by age, gender, health status, location of the tumour, extent of surgical resection (full, partial, incomplete), type of treatment given, and should note the duration of the follow-up studies. It's a highly complicated issue, and all patients and families with any kind of difficult diagnosis, like mine, should be able to access educative and hope-inspiring resources, rather the misery-provoking wasteland that's out there.
Luckily, there is an essay by Stephen J Gould that is fantastic, and saves me writing my own. If you don't want to read the whole thing, I'll quote a couple of excellent passages from his essay here, in the hope that it will give you hope for me.
cancerguide.org/median_not_msg.html
Gould was diagnosed with intestinal mesothelioma and survived 20 years, despite the median survival time in the literature being only 3 months.
"Attitude clearly matters in fighting cancer. We don't know why (from my old-style materialistic perspective, I suspect that mental states feed back upon the immune system). But match people with the same cancer for age, class, health, socioeconomic status, and, in general, those with positive attitudes, with a strong will and purpose for living, with commitment to struggle, with an active response to aiding their own treatment and not just a passive acceptance of anything doctors say, tend to live longer. A few months later I asked Sir Peter Medawar, my personal scientific guru and a Nobelist in immunology, what the best prescription for success against cancer might be. "A sanguine personality," he replied. Fortunately (since one can't reconstruct oneself at short notice and for a definite purpose), I am, if anything, even-tempered and confident in just this manner.
…
"The problem may be briefly stated: What does "median mortality of eight months" signify in our vernacular? I suspect that most people, without training in statistics, would read such a statement as "I will probably be dead in eight months" - the very conclusion that must be avoided, since it isn't so, and since attitude matters so much.
…
"When I learned about the eight-month median, my first intellectual reaction was: fine, half the people will live longer; now what are my chances of being in that half. I read for a furious and nervous hour and concluded, with relief: damned good. I possessed every one of the characteristics conferring a probability of longer life: I was young; my disease had been recognized in a relatively early stage; I would receive the nation's best medical treatment; I had the world to live for; I knew how to read the data properly and not despair.
"Another technical point then added even more solace. I immediately recognized that the distribution of variation about the eight-month median would almost surely be what statisticians call "right skewed." (In a symmetrical distribution, the profile of variation to the left of the central tendency is a mirror image of variation to the right. In skewed distributions, variation to one side of the central tendency is more stretched out - left skewed if extended to the left, right skewed if stretched out to the right.) The distribution of variation had to be right skewed, I reasoned. After all, the left of the distribution contains an irrevocable lower boundary of zero (since mesothelioma can only be identified at death or before). Thus, there isn't much room for the distribution's lower (or left) half - it must be scrunched up between zero and eight months. But the upper (or right) half can extend out for years and years, even if nobody ultimately survives. The distribution must be right skewed, and I needed to know how long the extended tail ran - for I had already concluded that my favorable profile made me a good candidate for that part of the curve.
"The distribution was indeed, strongly right skewed, with a long tail (however small) that extended for several years above the eight month median. I saw no reason why I shouldn't be in that small tail, and I breathed a very long sigh of relief. My technical knowledge had helped. I had read the graph correctly. I had asked the right question and found the answers. I had obtained, in all probability, the most precious of all possible gifts in the circumstances - substantial time. I didn't have to stop and immediately follow Isaiah's injunction to Hezekiah - set thine house in order for thou shalt die, and not live. I would have time to think, to plan, and to fight.
O"ne final point about statistical distributions. They apply only to a prescribed set of circumstances - in this case to survival with mesothelioma under conventional modes of treatment. If circumstances change, the distribution may alter. I was placed on an experimental protocol of treatment and, if fortune holds, will be in the first cohort of a new distribution with high median and a right tail extending to death by natural causes at advanced old age."
