The results of solid cancer mortality analyses in the 0–2 Gy dose range and over the entire follow-up (i.e., 1950–2009) were similar, revealing significant upward curvature in dose response for each sex.[Brenner et al, 2022, page 13]
It was the U.S. military itself that organized the study of the radiation effects of atomic bombs—a situation akin to granting a criminal credibility in counting their victims.
When breast cancer incidence after bombing was reported in 1979 (Tokunaga et al, JNCI) in women over 40 at the time of the bombing, there was only 107 breast cancers in a population of 18,464 women over a period of 24 years, which is the main period of occurrence of breast cancer. Today, the lifetime risk of breast cancer is 1 in 8 in the USA.
It is simply impossible to believe results in the fields where the US army is involved.
Let me understand better. "significant upward curvature among males (P=0.001) but not among females (P=0.624)" is comparing the quadratic fit to the 'no-effect' dose-response? Or to the LNT dose-response?
And how can there be such vast differences between male and female?
And the parameters in Figure 2 are those of your SNT fit, not shown?
As outlined in the piece, the RERF definition of significant curvature is that the quadratic coefficient intheir linear quadratic fit is at least 1/4 the linear coefficient.
Obviously, this is a highly non-standard definition of curvature. Then they assume the linear fit is the null hypothesis and do a statistical test to see if the data rejects that incorrectly chosen null. In 3 of the 4 cases, it did.
The REF data is a mess. It has all sorts of problems. In the female incidence case, the low points around 3 Gy worked strongly against a quadratic fit. They point to a sigmoid fit which would push more curvature into the low end.
No, the numbers were left over from some testing. I was too lazy to take them out.
It was the U.S. military itself that organized the study of the radiation effects of atomic bombs—a situation akin to granting a criminal credibility in counting their victims.
https://www.pnas.org/doi/full/10.1073/pnas.95.10.5426
When breast cancer incidence after bombing was reported in 1979 (Tokunaga et al, JNCI) in women over 40 at the time of the bombing, there was only 107 breast cancers in a population of 18,464 women over a period of 24 years, which is the main period of occurrence of breast cancer. Today, the lifetime risk of breast cancer is 1 in 8 in the USA.
It is simply impossible to believe results in the fields where the US army is involved.
Let me understand better. "significant upward curvature among males (P=0.001) but not among females (P=0.624)" is comparing the quadratic fit to the 'no-effect' dose-response? Or to the LNT dose-response?
And how can there be such vast differences between male and female?
And the parameters in Figure 2 are those of your SNT fit, not shown?
As outlined in the piece, the RERF definition of significant curvature is that the quadratic coefficient intheir linear quadratic fit is at least 1/4 the linear coefficient.
Obviously, this is a highly non-standard definition of curvature. Then they assume the linear fit is the null hypothesis and do a statistical test to see if the data rejects that incorrectly chosen null. In 3 of the 4 cases, it did.
The REF data is a mess. It has all sorts of problems. In the female incidence case, the low points around 3 Gy worked strongly against a quadratic fit. They point to a sigmoid fit which would push more curvature into the low end.
No, the numbers were left over from some testing. I was too lazy to take them out.