Live data from Hacker News

$5 device tests for breast cancer in under 5 seconds: study

studyfinds.org

111–120 of 137 posts

Re: $5 device tests for breast cancer in under 5 seconds: study

#111
post #57

Earlier quoted context omitted.

You can absolutely draw conclusions about the statistical power of the test. That’s what statistics is for. If this sample data is randomly sampled it looks like it will be a fairly high precision test for invasive cancers, with room for false negatives. You would have had to have gotten very unlucky to see such a difference in distributions even on a small sample like this. But sure, let’s get more samples.

Thank you for this! I get frustrated with the "N of only 21? Might as well flip a coin!" responses. Like you say, the whole purpose of statistical testing is to give an accurate, numeric value that says how likely the results are due to chance. One thing I'd note, though, is that the paper's title is "High sensitivity saliva-based biosensor in detection of breast cancer biomarkers: HER2 and CA15-3". My understanding…

My assumption is that 98% of people have no idea what the right sample size is for this particular experiment, including myself of course.

To all who criticize and ridicule someone who would like to have more samples, why do you think 21 is such a perfect number in this case? Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?

Re: $5 device tests for breast cancer in under 5 seconds: study

#112

Earlier quoted context omitted.

Thank you for this! I get frustrated with the "N of only 21? Might as well flip a coin!" responses. Like you say, the whole purpose of statistical testing is to give an accurate, numeric value that says how likely the results are due to chance. One thing I'd note, though, is that the paper's title is "High sensitivity saliva-based biosensor in detection of breast cancer biomarkers: HER2 and CA15-3". My understanding…

This is why science has gotten harder these days. When there were only half a billion people, sampling 500 got you 1 in a million coverage. Now there are 8 billion people, so it's worth 16 times less. As more people are made, science will suffer because the percentage is so much less. In fact, this is why I always trust science in small towns more. In Colma, for instance, you sample 500 and you have covered 33% of th…

TBH, I can't tell if this is sarcastic or not, because there is so much in this comment that belies a fundamental misunderstanding of statistical testing and statistical power, which is the point I was trying to make.

> Now there are 8 billion people, so it's worth 16 times less.

That is not how statistics works, at all.

> In fact, this is why I always trust science in small towns more. In Colma, for instance, you sample 500 and you have covered 33% of the people.

These are the sentences that made me think this had to be satire (presumably you want "science" to apply to places outside of Colma...), but in all honesty these days it's really hard to tell.

Re: $5 device tests for breast cancer in under 5 seconds: study

#113
Largely BS.

1) These are not clinical biomarkers used for detection of cancer now, and in fact, they are known NOT to be clinical biomarkers useful for detecting cancer. 2) This is a publication focusing on the device/method, not the clinical application. It is published in a journal of vacuum science, not a cancer biology or medical journal. 3) There are several inaccurate things in the paper, one being that they state that current technology requires 1-2 weeks to measure either biomarker. Wrong, clinical tests exist today that can perform those immunoassays in minutes on large automated analyzers. 4) This isn't fraud, it's just a really typically overhyped report of a novel device/meausrement strategy (and it's not that novel) that targets a biomarker that has a role in cancer, and then some mass media picks it up and says that they have "the test for cancer". This happens all the time. 5) This should maybe be considered a proof of concept about the electronics of their detection strategy, since the immunoassay component is known (immunoassays to both biomarkers are not only published, but commercialized) and the clinical use of the biomarkers is not at all diagnostic for cancer or useful for screening.

Re: $5 device tests for breast cancer in under 5 seconds: study

#114
post #110

Earlier quoted context omitted.

Not quite. Theranos was stating that they were capable of doing what was impossible prior. The real issue with Theranos was physics. A single drop of blood is simply not a large enough sample for them to do all the testing they claimed. As in, impossible with today's tech and in the near future. These folks are just stating that, "so far, this looks promising". At least, thats my read. YMMV.

It is important to point out that what they claimed to do is not technically impossible actually. They just didn't do it, and lied about it. That was the real problem. It's very unfortunate, because it is technically possible, just very difficult to achieve, even in academia (so it won't be done first in industry). This was the absolute worst part of Theranos, is that they deter others from trying to make headway in…

I don't believe they could run a battery of 81+ tests on a drop of blood. There simply isn't enough there. Why do you think they take tubes of blood for testing, currently?

The issue is concentrations and the presence of them in sufficient amounts to be detected reliably and consistently.

edit: typo.. words are hard.

Re: $5 device tests for breast cancer in under 5 seconds: study

#115

Earlier quoted context omitted.

Thank you for this! I get frustrated with the "N of only 21? Might as well flip a coin!" responses. Like you say, the whole purpose of statistical testing is to give an accurate, numeric value that says how likely the results are due to chance. One thing I'd note, though, is that the paper's title is "High sensitivity saliva-based biosensor in detection of breast cancer biomarkers: HER2 and CA15-3". My understanding…

My assumption is that 98% of people have no idea what the right sample size is for this particular experiment, including myself of course. To all who criticize and ridicule someone who would like to have more samples, why do you think 21 is such a perfect number in this case? Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?

> To all who criticize and ridicule someone who would like to have more samples, why do you think 21 is such a perfect number in this case? Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?

This is the point that you are fundamentally misunderstanding. Nobody is making the argument that "21 is such a perfect number in this case". The rest of your sentences ("Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?") seem to point to a belief that people are pulling numbers based on a finger in the wind.

The whole point of (a lot of) statistical testing is that it allows you to come up with a specific number that determines how likely a particular result is due to chance. That is what the p is just basically pulled out of thin air, and p-hacking is another topic...) That is, I and the comment I replied to aren't making the argument that 21 "is such a perfect number". We're making the argument that even with a small sample size it's possible to determine the relative error bars, with precision, using statistical methods, not just pulling a number based on feels. Yes, larger sample sizes reduce the size of those error bars. But often not in ways that are "intuitive". You have to do the math.

None of what I wrote above is meant to imply that statistical tests can't be misused, or that they often require assumptions about the underlying population distribution that may not be correct.

Re: $5 device tests for breast cancer in under 5 seconds: study

#116

Earlier quoted context omitted.

Thank you for this! I get frustrated with the "N of only 21? Might as well flip a coin!" responses. Like you say, the whole purpose of statistical testing is to give an accurate, numeric value that says how likely the results are due to chance. One thing I'd note, though, is that the paper's title is "High sensitivity saliva-based biosensor in detection of breast cancer biomarkers: HER2 and CA15-3". My understanding…

My assumption is that 98% of people have no idea what the right sample size is for this particular experiment, including myself of course. To all who criticize and ridicule someone who would like to have more samples, why do you think 21 is such a perfect number in this case? Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?

It is a function of the effect size, not the experiment. When the effect size is large, you need fewer samples to detect it reliably. In this case it looks pretty large. Would you want more people before rolling it out? Of course. But it’s very unlikely to be vaporware provided the samples are random.

Re: $5 device tests for breast cancer in under 5 seconds: study

#117
post #57

Earlier quoted context omitted.

You can absolutely draw conclusions about the statistical power of the test. That’s what statistics is for. If this sample data is randomly sampled it looks like it will be a fairly high precision test for invasive cancers, with room for false negatives. You would have had to have gotten very unlucky to see such a difference in distributions even on a small sample like this. But sure, let’s get more samples.

It's been a while since I took statistics, but isn't the whole point of testing that it needs to have a high Bayes factor, and to be confident that said Bayes factor is high? In this case, and my lack of understanding in both bio and stats is showing here, we're trying to develop a test for breast cancer. An ideal test will have high sensitivity and specificity, and a tight confidence interval for both of those numbe…

Suppose you had cancer and could roll a die, and if the die came up six, it would tell you with high certainty you had cancer, and if it came up as anything else, it would tell you nothing.

If the test is very cheap, it’s probably a great test presuming you get to see the dice roll itself.

The cost and invasiveness of the test is important.

Re: $5 device tests for breast cancer in under 5 seconds: study

#118

Earlier quoted context omitted.

Really? Will the $5 Arduino people woo the doctor near you with golf trips? Will they strong arm HMOs to cover the cost? Will they carpetbomb the airwaves telling consumers to “ask their doctor?” Will they defeat the army of marketers and salespeople with entrenched competing tech? This device may be total crap, I don’t know, but “trust the system” isn’t a great way to navigate the American medical system. Other coun…

Doctors do gravitate towards effective tests and medicines, and insurance plans are interest in cheaper alternatives. There is a lot that could be improved about the US medical system, but Nobody has to bribe doctors and insurance to sell tongue depressors.

I would bet someone out there has attempted to come up with a high-margin tongue depressor with fancy built-in features. But the plain wooden stick is already entrenched and obviously effective (for depressing tongues).

This is the opposite. If the state of the art was a fancy tongue manipulation machine that cost $30k, used licensed consumables billed at $100/patient, and did a bunch of non-essential things that doctors found convenient once in a while, would someone selling a box of sticks get anywhere?

Re: $5 device tests for breast cancer in under 5 seconds: study

#119
post #90
post #57

Earlier quoted context omitted.

You can absolutely draw conclusions about the statistical power of the test. That’s what statistics is for. If this sample data is randomly sampled it looks like it will be a fairly high precision test for invasive cancers, with room for false negatives. You would have had to have gotten very unlucky to see such a difference in distributions even on a small sample like this. But sure, let’s get more samples.

With so few controls, it’s still not a well designed comparison. Most scientists deal with low sample sizes, especially in first trials. However, what is often overlooked is the need for sufficient numbers of negative controls. If they only had 4 control patients, that’s completely inadequate to draw any real conclusions. With access to a biobank at U of Florida, they should have been able to test more samples — espe…

A small control sample is not “few controls”. Misleading term. “Negative controls” is not a thing either. Just the control group is fine.

The error bars are not really needed. Your eyeballs are doing just fine. Yes, they overlap. Yes, it would likely have a high false negative rate.

A false negative rate is not a problem for a cheap test. This test is not meant to replace higher quality and more invasive tests. A high precision, low recall test still has significant value. You merely have to accept that a negative result tells you very little.

If we imagined for instance, that the false positive rate is very low despite the overwhelmingly larger population of people without cancer, then this would be of enormous value.

Re: $5 device tests for breast cancer in under 5 seconds: study

#120

Earlier quoted context omitted.

My assumption is that 98% of people have no idea what the right sample size is for this particular experiment, including myself of course. To all who criticize and ridicule someone who would like to have more samples, why do you think 21 is such a perfect number in this case? Wouldn't 15 be enough, if statistics and all applies? 10? 1? Would 30 be too much?

It is a function of the effect size, not the experiment. When the effect size is large, you need fewer samples to detect it reliably. In this case it looks pretty large. Would you want more people before rolling it out? Of course. But it’s very unlikely to be vaporware provided the samples are random.

Thank you! Came here to say, but found, that you've already written it.

Effect size is going to be important when talking about clinical significance, not just statistic significance, too.

I also want to point out that we have no stats on sensitivity, specificity, or diagnostic odds ratio, which are all clinically relevant to physicians deciding when to test and how to interpret test results.

The good news is that it's a non-invasive, low cost test which plays a factor in clinical decision-making.

Post reply on HN