The contrast is the type of trend. In samples from people who got cancer age had a greater correlation with short telomeres. However, in samples from patients in the three or four years immediately before cancer diagnosis, there was a significantly longer telomere length.
People who will get cancer’s telomeres shorten more rapidly with age, but are longer right before they get cancer. It’s a dynamic process and it’s apparently got some weird complications to it. Mostly interesting to me because it suggests body-wide mechanisms of telomere regulation that have something to do with cancer genesis.
Oh, whether short vs long is associated with cancer. I guess that should have been clear from De Vliegende Hollander’s query.
On a different note, that second graph looks like nonsense to me. The cancer group holds steady, while the control group bobs up and down. The effect is in the control group, not in the cancer group. This graph tells nothing about cancer. 95% it’s pure nonsense, but maybe it tells something about the control group—it’s predicting their censoring by death. Which is why it’s crazy to use time to censoring as the metric for the control group.
What’s the contrast? Isn’t the situation exactly the same, statistically distinguishable, but practically meaningless?
The contrast is the type of trend. In samples from people who got cancer age had a greater correlation with short telomeres. However, in samples from patients in the three or four years immediately before cancer diagnosis, there was a significantly longer telomere length.
People who will get cancer’s telomeres shorten more rapidly with age, but are longer right before they get cancer. It’s a dynamic process and it’s apparently got some weird complications to it. Mostly interesting to me because it suggests body-wide mechanisms of telomere regulation that have something to do with cancer genesis.
Oh, whether short vs long is associated with cancer. I guess that should have been clear from De Vliegende Hollander’s query.
On a different note, that second graph looks like nonsense to me. The cancer group holds steady, while the control group bobs up and down. The effect is in the control group, not in the cancer group. This graph tells nothing about cancer. 95% it’s pure nonsense, but maybe it tells something about the control group—it’s predicting their censoring by death. Which is why it’s crazy to use time to censoring as the metric for the control group.