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by grawprog 2219 days ago
Makes you wonder how many people have actually died so far this way. Being told to stay home and not spread covid, meanwhile something else is actually terribly wrong.
6 comments

There was an Oncologist who was talking about how the number of women coming in for regular exams was non-existent for two months. A few months is enough time for breast cancer to go from stage 1 to stage 2, and for 5 year survival rates to drop by a third[0].

There are going to be a ton of secondary effects due to prematurely closing or clearing out hospitals and clinics, and many people have already died from completely preventable illnesses, with some clinics telling people to not come in when they should have.

[0]: https://unherd.com/thepost/professor-karol-sikora-fear-is-mo...

I think this is a very misleading way of looking at it.

For example the US Preventative Task Force evaluates evidence and recommends screening guidelines as well as giving the strength of the evidence.

For breast cancer, the only recommended screening is that women age 50 to 74 have mammograms every 2 years. And that is B grade evidence.

https://www.uspreventiveservicestaskforce.org/uspstf/recomme...

With screenings, you have to be really careful about selection bias. Basically, screening will catch a larger proportion of slow growing cancer. Also with respect to staging, the slower growing a cancer, the earlier the stage you will catch it at.

My guess would be that if you have a cancer that is rapidly going from stage 1 to stage 2, you would already have a worse outcome and the 2 months screening hiatus is not going to be that big a difference maker.

EDIT:

In case people ask about clinical breast exams and self breast exams, here are the American Cancer Society guidelines:

"Research has not shown a clear benefit of regular physical breast exams done by either a health professional (clinical breast exams) or by women themselves (breast self-exams)."

https://www.cancer.org/cancer/breast-cancer/screening-tests-...

So the only guidelines with evidence backing them up call for 2 year screenings. Within that framework, a 2 month delays are not going to be very clinically significant.

A few months is enough time for breast cancer to go from stage 1 to stage 2 ...

Do women normally have breast exams every few months?

I don't understand where you'd get that implication.

Some presumably fairly predictable fraction would have an exam scheduled during the beginning of the epidemic, and a certain fraction of them would have undiagnosed cancer. It seems reasonable to assume significant negative consequences for those people.

Presumably some women would have had an exam in February but developed enough cancer to be visible in March, so delaying a couple of months had a huge positive impact on their outcome. How can we measure the net result of all these variables?
The way you measure it is how the GP defined it: percent women who develop early stage breast cancer per month * number of months closed per year.
That only makes sense if a woman gets screened monthly, which they don't.
No. It varies by age or location but it'd be once a year at max - unless perhaps you had already had it or for some other reason were extraordinarily high risk.
Exams performed by someone else? About once a year.

A self-exam once a month is one of those "good hygiene" things, though, and might be a decent idea to promote right now while people are getting cagey.

According to this New York Times article from the beginning of May, excess deaths in the United States outpaced official Coronavirus reporting by 33%. This obviously varies significantly by country. Certainly many more people are dying at home than previous years.

https://www.nytimes.com/interactive/2020/05/05/us/coronaviru...

The key phrase if you want to learn more is "excess deaths"

My understanding is that excess deaths statistic would also COVID deaths. You'd need to subtract COVID deaths from excess deaths. (and be certain that all COVID deaths are reported as such...)
Right - so ~25% of excess deaths in April in the United States were not directly caused by COVID-19, but were almost certainly indirectly caused by the virus, either via the 'medical care chilling effect' mentioned above, or through misattribution, or through other mechanisms like the increase in suicide.

This excess death mechanism has the potential to be very severe in very poor countries, where famine is likely to follow this plague. It's really quite sad.

Not really COVID deaths, you have to seperate them from the lockdown deaths.
The problem is that SARS-CoV-2 is so capable of infecting and disrupting a broad variety of cells that many multi-organ symptoms might manifest, so it wouldn't be a surprise if that's what's presumed to be the cause of an ailment at first considering its reproduction number.
It's terrifying. A friend of a friend of my wife just lost her baby. It was something that would have been easily seen in a routine screening, but because of COVID the OB/GYN wasn't having patients come to the office. It's heart breaking.
Are you saying she wouldn't have lost the baby if she had a routine screen or it would have given her the ability to deal with the issue a litle bit easier by planning a dnc?

I've been part of many miscarriages and doctors can tell you something is wrong but rarely can they fix anything before 12 weeks.

I honestly don't know, I'm several hops away from the source, but when my wife told me it sounded like they could have saved the baby had they known.
150,000 people typically get diagnosed with cancer each month in the US. With hospitals shut that isn't happening.

https://www.cancer.gov/about-cancer/understanding/statistics

The indirect fallout from this will be huge.

From delayed diagnostics, to "elective" surgeries that can't take place, to suicides. It's going to be on the order of the direct deaths at least.

The only real measurable indirect improvement is a lot less people dead in traffic accidents.

> It's going to be on the order of the direct deaths at least.

Possibly. And many will interpret this as the cure being "worse of (or as bad as) the disease".

But what we should really be comparing this to is the number of deaths we'd have if we didn't do anything to reduce the spread.

Anybody has good simulation data that takes into account what we learned so far?

On top of that, it wouldn't be like the hospitals would be business as usual if the lockdown didn't occur. Models mostly showed they would have had their hands full with covid cases (and therefore still not handling normal cases and elective stuff). Additionally many people going to hospitals for whatever reason would likely end up exposed to COVID.
The ex-Covid death rate in New York is significantly above its baseline. Part of this may be undiagnosed covid deaths, but with less people out doing dangerous things, a lot of it is probably people avoiding hospitals.
ex-Covid rate is more likely due to undiagnosed covid. Especially when you look at the excess death rate compared to previous annual rates. (at least last time I looked at the graphs).

But regardless none of it is any good for anyone.

The excess death rate (ex covid) is relative to previous annual rates. I don't think you can disambiguate between "deaths due to undiagnosed covid" and "deaths due to untreated illness due to avoiding hospitals"
You're right. But if the excess mirrors the diagnosed rate (rise and fall) one might reasonably infer that it is driven by covid. Compared to deaths resulting from/driven by people staying away from hospitals which would depend on when lockdowns were announced, when behaviors changed, etc.

Although both mechanisms would bear some relation, it looked to me more like it was driven by spread of the infection rather than changes to behavior.

The point that you can't really separate them completely is well-taken though.

EDIT: I'm clearly all over the place with terminology. Something along the lines of looking at the (all_cause_mortality - covid_deaths - historic_avg) residual and seeing how closely it mirrors say alpha*covid_deaths where alpha is some constant. If it mirrored it well (or for example preceded it and the lock downs in the manner that would be expected of infection) one might infer that those deaths were probably covid. If on the other hand they were strictly related to the time the news broke and lock downs and changes to hospital admittance rates, then it might be better explained as resulting from lockdown issues.

> But if the excess mirrors the diagnosed rate (rise and fall) one might reasonably infer that it is driven by covid. Compared to deaths resulting from/driven by people staying away from hospitals which would depend on when lockdowns were announced, when behaviors changed, etc.

Yea absolutely. I haven't seen yet seen any analysis that does this, but I'm sure one will come along soon