Predicting Doom
- lung cancer
- survivor
- scanziety
- survivor statistics
- lung cancer statistics
- lung cancer survival statistics
- gould survival essay
- stephen jay gould survivor statistics
- understanding lung cancer survivor statistics
- what survivor statistics dont consider
- the median isnt the message
- gould cancer essay
- predicting lung cancer death
- coping lung cancer statistics
- lung cancer death forecast
- lung cancer death statistic
- death lung cancer
- death with lung cancer
- predicting death lung cancer
- tom galli lungevity
Entry posted by Tom Galli
2,984 views
I am not a statistics wizard; an engineer, I value the predictive power of statistics. Indeed, if one can precisely control variables, a statistics-based prediction of the future is remarkably accurate. The joy of predicting end strength for a new carbon-nanotube concrete mix design melts the heart of this engineer. But, concrete is a thing with but 4 variables to control. Human beings have perhaps millions of variables, thus predictions about people are vastly more complicated and inaccurate.
Statistically-based predictive power has a foreboding downside. The methodology is used by the medical profession to forecast life after diagnosis with late-stage lung cancer. Unfortunately, I have first-hand experience once predicted with but 6 months of remaining life nearly 13 years ago! My doom was forecasted with high statistical confidence and for a while, I believed it.
In the dwell time between treatments, I searched for methods used to generate my projection of demise. Each patient’s type, stage, age, ethnicity, race, and date of diagnosis are reported to the National Cancer Institute on diagnosis. Deaths are also reported but not the cause of death. Nothing is captured on complicating health problems like cardio-pulmonary disease, diabetes, or other life-threatening maladies. The predictive data set appeared slim and uncontrolled.
My doom and resulting gloom waned while mindlessly searching web pages for statistical good news. Ammunition in the form of a powerful essay by the noted Harvard biologist Stephen Jay Gould – “The Median Isn’t The Message” – contained: “…leads us to view statistical measures of central tendency [median or mean] wrongly, indeed opposite to the appropriate interpretation in our actual world of variation, shadings, and continua.”
This meant the statistician seeks to combine data and express it as a median or mean to predict or explain. I’d forgotten that I was one inaccurate variable in a “world of variation.” One data point used to calculate a central tendency of survival for about 1.4 million Americans diagnosed in 2004. I might be the one holding the right-shifted curve from intersection with the axis of doom.
Gould survived 20-years beyond his late-stage, nearly always fatal, abdominal mesothelioma cancer diagnosis. Ironically, he passed after contracting another form of unrelated cancer. A distinguished scientist, Gould eloquently described the limits of science and statistics by suggesting that “a sanguine personality” might be the best prescription for success against cancer. There is always hope, with high confidence. Listen to his essay here.
Stay the course.
____________
Get your copy of Scanziety here https://www.amazon.com/Scanziety-Retrospection-Lung-Cancer-Survivor-ebook/dp/B01JMTX0LU
1 Comment
Recommended Comments