[Retric]

That's demonstrably false. Early screening is useful, but that's also a medical procedure.

Really what we care about is cancer deaths at a specific age AKA what % of 15 year old people die of cancer and that really has dropped. Even beyond that the absolute rate of cancer deaths in the US peaked in 1990 216 per 100k vs 2015 at 158 per 100k. Which is a massive drop even over 1950's pre screening and younger population numbers of 193 per 100k.

PS: Stomach cancer is flat out much less common because we understand a major cause now. Cervical cancer rates will similarly drop from the HPV vaccine.

[tinokid]

> Even beyond that the absolute rate of cancer deaths in the US peaked in 1990 216 per 100k vs 2015 at 158 per 100k. Which is a massive drop even over 1950's pre screening and younger population numbers of 193 per 100k.

Hmmm... Apply a 25 year lag. https://www.cdc.gov/mmwr/preview/mmwrhtml/figures/m4843a2f1....

>PS: Stomach cancer is flat out much less common because we understand a major cause now. Cervical cancer rates will similarly drop from the HPV vaccine.

Yes...lots of progress in infectious disease treatment, very little with cancer treatment.

[Retric]

Lung cancer has not changed overall numbers all that much from 1990. https://seer.cancer.gov/statfacts/html/lungb.html So, no it's not responsible for the massive drop in cancer deaths by age group.

I included HPV and Stomach cancer in a PS specifically because they are minor changes to overall numbers. Sunscreen also impacts the rates people get cancer, but it's a very minor effect.

[tinokid]

"Not all that much" is not how I would describe a chart like this: http://www.clevelandclinicmeded.com/medicalpubs/diseasemanag...

And lung cancer is not the only cancer caused by smoking.

In any case, cancer death rates and changes in risk factors do not speak directly to the claim about treatment effectiveness. If you are diagnosed with cancer, you are basically every bit as f'ed today as you were 50 years ago, except in the special case that your cancer happens to be one of those that never would have been noticed back then.

[Retric]

Notice that Male at the bottom of the cart women are only down 17%. That makes the impact on overall numbers significantly lower. It's also a chart of deaths, what you want to support the idea that treatment is useless is a chart of new cases.

Also, see that huge drop in Prostate and Colorectum cancer. Yea, that has nothing to do with smoking it's almost completely related to better treatment making a huge difference.

And again, we are not looking at equivalent populations. The older the US population the worse cancer numbers look in absolute terms.

So, even the chart you are using to support your argument actually supports mine.

PS: To account for a 25% drop in cancer deaths lung cancers could have hit zero in that cart and it would still not be enough.

[vonmoltke]

You are referring to cancer prevention, while the GP is referring to cancer treatment.

[grzm]

I'm not sure I follow. Screening detects cancer that is already there, hopefully in early stages when it might be treated more easily. In both cases, cancer is already present.

[tinokid]

Treating infectious disease than can cause cancer (H. pylori, HPV) has nothing to do with cancer treatment.

Treating, for example, thyroid or prostate cancers that would not have killed the person improves cancer survival statistics but nothing else.

[Retric]

I included that as a PS specifically because they don't change overall numbers much. Yes, it's true some cancers are becoming less common, but ~50% of the population get's cancer it's very common even if the numbers are shifting around slightly.

[grzm]

Thanks for clarifying what you intended when you meant screening, which is differentiated from screening for cancer itself, which is how I read your upthread comment "[s]ome nipped a potentially fatal cancer in the bud".

[astura]

Its complicated...

https://sciencebasedmedicine.org/the-early-detection-of-canc...

>Unless one can follow a cohort over time, there is no way of accurately estimating the probability that a subclinically detected abnormality will naturally progress to an adverse outcome. The probability of such an outcome is mathematically constrained, however, by the prevalence of the detected abnormality. The upper limit of this probability can be derived from reasoning that dates to the 17th century, when vital statistics were first collected. If the number of persons dying from a specific disease is fixed, then the probability that a person with the disease will eventually die from it is inversely related to the prevalence of the disease. Therefore, given fixed mortality rates, an increase in the detection of a potentially fatal disease decreases the likelihood that the disease detected in any one person will be fatal..... Lead-time and length biases pertain not only to changes that lower the threshold for detecting disease, but also to new treatments that are applied at the same time. Whether or not new therapy is more effective than old therapy, patients given diagnoses with the use of lower detection thresholds will appear to have better outcomes than their historical controls because of these biases. Consequently, new therapies often appear promising and could even replace older therapies that are more effective or have fewer side effects. Because the decision to treat or to investigate the need for treatment further is increasingly influenced by the results of diagnostic imaging, lead-time and length biases increasingly pervade medical practice.

>There is another complication that these more powerful imaging modalities can lead to that wasn’t discussed in the paper, stage migration. This is a phenomenon that occurs when more sophisticated imaging studies or more aggressive surgery leads to the detection of tumor spread that wouldn’t have been noted in an identical patient using previously used tests. This phenomenon is colloquially known in the cancer biz as the Will Rogers effect. The name is based on Will Rogers’ famous joke: “When the Okies left Oklahoma and moved to California, they raised the average intelligence level in both states.” This little joke describes very well what can happen in cancer. What in essence happens is that technology results in a migration of patients from one stage to another that does the same thing for cancer prognosis that Will Rogers’ famous quip did for intelligence. Consider this example. Patients who would formerly have been classified as, for example, stage II cancer (any cancer), thanks to better imaging or more aggressive surgery, have additional disease or metastases detected that wouldn’t have been detected in the past. They are now, under the new conditions and using the new test, classified as stage III, even though in the past they would have been classified as stage II. This leads to the paradoxical statistical effect of making the survival of both groups (stage II and III) appear better, without any actual change in the overall survival of the group as a whole. This paradox comes about because the patients who “migrate” to stage III tend to have a lower volume of disease or less aggressive disease compared to the average stage III patient and thus a better prognosis. Adding them to the stage III patients from before thus improves the apparent survival of stage III patients as a group. The converse is that patients with more disease that was previously undetected, tended to be the stage II patients who would have recurred and done more poorly compared to the average patient with stage II disease; i.e., the worst prognosis stage II patients. But now, they have “migrated” to stage III, leaving behind stage II patients who truly do not have as advanced disease and thus in general have a better prognosis. Thus, the prognosis of the stage II group also ends up appearing to be better with no real change in the overall survival from this cancer.

[Retric]

That's a problem if you want to compare the effectiveness of specific treatments. AKA, is doing A, or B, better than C. Or even more basically are screenings useful?

If you want to look overall you can look at the number of people dying at each age of each type of cancer independent of both diagnosis and treatment. AKA how many 43 year old women died of breast cancer. That also has some problems for people that died of cancer before it was detected as cancer, or people who died of suicide or related complications but not necessarily cancer on it's own. Even more critical is reduction in the rate people get cancer in the first place.

Still we are not talking about a small gap, when you start seeing a 30+% drop for a wide range of cancers it's easy to see that yes treatments are extremely useful. Even if you only get an extra say 2 years that's still 2 years to die of a car crash and not cancer.