Thursday, November 14, 2019

Productivity measures for the increase in life expectancy

In my previous post in this blog I spoke about the article entitled Are ideas getting harder to find? which can be downloaded from the Stanford University website. In this paper, the authors also analyze the increase in life expectancy in the USA and the effort necessary to achieve it, and reach the following results:

  • The annual increase in life expectancy at birth in the USA was almost double between 1900 and 1950, compared to the years between 1950 and today (see the attached figure, taken from the article). In both periods, however, the increase was approximately linear. For the authors, this shows that life expectancy is one of the few macroeconomic variables that has not been subject to an exponential increase in the last century, which contradicts the forecasts by Ray Kurzweil and others, who resort to such exponential increase to predict that we will achieve immortality in the near future. I have attacked this idea in other posts in this blog.
  • To measure the research effort on the field of increased life expectancy, the authors of the article compute the number of publications in three specific specialties: cancer research; breast cancer research, as an instance of the previous case; and heart disease. This covers the most frequent causes of death by disease in recent times. In particular, a distinction is made between the total number of publications and those that refer to clinical studies.
  • To measure the research productivity in these fields, they calculate the number of years of increase in life expectancy per thousand inhabitants that can be attributed to the advances made in the three specialties mentioned, and detect that a maximum in cancer research was reached shortly before 1990. In the case of breast cancer, the maximum was reached by 1985. In both cases, productivity declined rapidly after those maximums. In the case of heart disease, the evolution was more variable, with considerable ups and downs.
  • The two attached figures, also taken from the article, show the relationship between both variables: research effort and productivity. In each figure, the vertical axis represents the quotient between the number of years of life expectancy increase per hundred thousand inhabitants, divided by the number of publications (or the number of clinical studies) carried out in that field. It can be noticed that the maximum research efficiency was achieved, in the case of cancer, towards 1985, and in heart disease towards 1970. In later years, the research efficiency has been decreasing, until reaching minimum levels in the case of clinical trials.
These are the conclusions of the authors of the article:
Between 1985 and 2006, declining research productivity means that the number of years of life saved per 100,000 people in the population by each publication of a clinical trial related to cancer declined from more than 8 years to just over one year... Next, however, notice that the changes were not monotonic if we go back to 1975. Between 1975 and the mid-1980s, research productivity for [the] cancer research categories increased quite substantially. The production function for new ideas is obviously complicated and heterogeneous. These cases suggest that it may get easier to find new ideas at first before getting harder, at least in some areas.
It is clear that the assumption that we are about to achieve immortality thanks to explosive advances in medicine is quite far from reality.

The same post in Spanish
Thematic Thread on Linguistics and Medicine: Previous Next
Thematic Thread on Science in General: Previous Next
Manuel Alfonseca

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