World-first experimental cancer treatment paves way for clinical trial

Even then though, in e.g. Victorian times, the median (50th percentile) gets skewed by horrendously high infant mortality.

Looking at the 75th or 80th percentile, or the life expectancy for an 18 year old, is a better measure. High scores for the 75th can mask deaths due to inequality to some extent, but because wealth distributions are _so_ skewed at the top, the 75th percentile typically looks more like an average/poor person than a rich person.

Because that's the modern definition of life expectancy: the average (mean). Probably because the primary driver behind the production of actuarial tables has always been for insurance, annuities, and similar purposes. For calculating costs and valuations the mean is often a better measure because the distribution of deaths isn't normal. Though in modern actuarial tables you'll often find both.

I would assume popular literature quotes expectancy figures from birth because that's the easiest thing to do when you're just trying to give a single simple figure. But actuarial tables have always been just that--tables. Given a person at age X, what's their life expectancy. The first row will be from birth, but people with money on the line have always understood that number is mostly irrelevant. Here's an actuarial table from the 3rd century which was built for calculating annuities: https://en.wikipedia.org/wiki/Ulpian%27s_life_table Interestingly that table seems to use median life expectancy.

Actuarial science was a significant driver in the development of modern statistics and mathematics, especially as the market for financial products exploded over the past several centuries. The tables and models for life expectancy from 150 years ago were startlingly accurate, even in their forecasts of changing life expectancies. When Social Security was passed in the 1930s the models for how life expectancies would change, both from infancy and across all the age brackets, were spot on with actual changes up to the 1990s.

In general a lot of the research around aging is more motivated by a desired outcome than a the evidence in question. Telomeres, for instance, are clearly correlational rather than causal with contrary evidence in numerous species such as mice most obviously. In general there seems to be practically a rule that any observation of biological immortality is later met with a refutation. For instance lobsters are observed to eventually stop even trying to moult as they age, which inevitably leads to their death. Senescence manifesting differently in different species obviously does not imply immortality.

People, even very smart people, have a habit of lying to themselves when they want something to be true. Obviously religion is a good example of this in the past. And in the present I think we're largely just replacing religion with pseudo-scientific hypotheses to the same end. For instance I personally am a strong believer in the simulation hypothesis, at least I think I am. I don't know whether I "really" believe it's as sound as it seems, or if it's a coping mechanism to balance a secular worldview and the desire to not die. I mean it's not really even a theory since if it turns out to be true, and one day I simply 'wake up' - is that new reality "real" or just another simulation? But I'm at least aware of the fact I may well be lying to myself with a highly debatable theory.