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posted by martyb on Thursday January 09 2020, @04:19PM   Printer-friendly
from the yay! dept.

Cancer Mortality Continues Steady Decline, Driven by Progress against Lung Cancer:

The cancer death rate declined by 29% from 1991 to 2017, including a 2.2% drop from 2016 to 2017, the largest single-year drop in cancer mortality ever reported. The news comes from Cancer Statistics, 2020, the latest edition of the American Cancer Society's annual report on cancer rates and trends.

The steady 26-year decline in overall cancer mortality is driven by long-term drops in death rates for the four major cancers -- lung, colorectal, breast, and prostate, although recent trends are mixed. The pace of mortality reductions for lung cancer -- the leading cause of cancer death -- accelerated in recent years (from 2% per year to 4% overall) spurring the record one-year drop in overall cancer mortality. In contrast, progress slowed for colorectal, breast, and prostate cancers.

Let's hope progress accelerates with CRISPR and other new tools.

Journal Reference:
Rebecca L. Siegel, Kimberly D. Miller, Ahmedin Jemal. Cancer statistics, 2020. CA: A Cancer Journal for Clinicians, 2020; DOI: 10.3322/caac.21590


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  • (Score: 0) by Anonymous Coward on Thursday January 09 2020, @10:29PM (8 children)

    by Anonymous Coward on Thursday January 09 2020, @10:29PM (#941646)

    No, cancer rates in a given tissue peak when the tissue stem cells have undergone about log(1/n, base = 1 - p) divisions since fertilization. Where n is average number of accumulated "errors" required and p is the geometric mean of the probably of an error per division in that cell lineage. For most cancers it seems to work out to about 75 years old (at least in the SEER population), but of course p can be influenced by environmental factors, n can be influenced by genetic factors, etc.

    People dying from other stuff before that peak will cut down on population cancer rates.

  • (Score: 2) by ikanreed on Thursday January 09 2020, @11:02PM (7 children)

    by ikanreed (3164) Subscriber Badge on Thursday January 09 2020, @11:02PM (#941663) Journal

    Being that I work directly in field of cancer genomics, I feel safe to say no, what the fuck are you talking about.

    • (Score: 0) by Anonymous Coward on Thursday January 09 2020, @11:23PM

      by Anonymous Coward on Thursday January 09 2020, @11:23PM (#941669)

      They don't teach you armitage doll in cancer genomics?

    • (Score: 0) by Anonymous Coward on Thursday January 09 2020, @11:26PM

      by Anonymous Coward on Thursday January 09 2020, @11:26PM (#941671)

      Have you ever even looked at age specific mortality for various cancers? Or just age-adjusted, pop-adjusted crap like in this paper?

    • (Score: 0) by Anonymous Coward on Friday January 10 2020, @02:31AM (4 children)

      by Anonymous Coward on Friday January 10 2020, @02:31AM (#941744)

      Do this simulation:

      1) Get four quarters, call them A, B, C, D
      2) Flip coin A until you have observed heads and record how many flips it took
      3) Repeat step 2 for coins B:D
      4) Record the *max* number of flips for that round
      5) Repeat steps 2-4 until you have enough to see the distribution of max flips per round
      6) Record the mode (most common # of flips required for all four coins to have turned up heads)

      Each flip is a cell division, each coin is an "error" that is accumulating (usually assumed to be a mutation to an oncogene or tumor suppressor gene or whatever). Eg, in this case we need to get 4 genes mutated, each with 50% chance of mutating each division.

      It will have a peak at log(1/4, base = 0.5), that's why age specific cancer incidence peaks at a certain age. You'll find so much inane BS written about this "peak cancer age" but it is straight armitage doll. The above is a simplification of the full model (constant error rate, independent/irreversable errors, looks at divisions instead chronological age, etc), but should demonstrate the concept.

      • (Score: 2) by ikanreed on Friday January 10 2020, @01:35PM (3 children)

        by ikanreed (3164) Subscriber Badge on Friday January 10 2020, @01:35PM (#941855) Journal

        The problem isn't that I don't understand your gross simplification.

        • (Score: 0) by Anonymous Coward on Friday January 10 2020, @03:48PM (2 children)

          by Anonymous Coward on Friday January 10 2020, @03:48PM (#941912)

          Well, it is just the armitage-doll model which many people have managed to understand. So it is probably that you are trained in genomics which in my experience is a very unscientific field. It is a bunch of memorizing arbitrary "facts" instead of thinking scientifically.

          • (Score: 2) by ikanreed on Friday January 10 2020, @04:16PM (1 child)

            by ikanreed (3164) Subscriber Badge on Friday January 10 2020, @04:16PM (#941928) Journal

            God help you if you dare actually know the central dogma of biology.

            • (Score: 0) by Anonymous Coward on Friday January 10 2020, @05:41PM

              by Anonymous Coward on Friday January 10 2020, @05:41PM (#941969)

              Look, if you cannot understand the armitage-doll model (that cancer is due to accumulation of some kind of error) there is something wrong with how you have been trained.