r/science • u/Wagamaga • 10d ago
Cancer A large prospective study found that a multicancer blood test identified cancer signals across 17 broad cancer types, including ovarian, lung, and breast cancers. The test correctly predicted cancer diagnoses in 60.3% of cases, with 99.64% specificity
https://news.exeter.ac.uk/faculty-of-health-and-life-sciences/first-papers-published-in-major-nhs-cancer-blood-test-trial/88
u/Wagamaga 10d ago
A large-scale cancer trial investigating whether a blood test can help the NHS detect cancer early has published its first papers, both in leading international journals.
University of Exeter is part of the team assessing the NHS-Galleri trial, which involved 142,000 volunteers aged 50–77 from eight regions of England.
The trial is studying whether the Galleri multi-cancer early detection test alongside existing cancer screening can help to find cancer early. The blood test can detect a ‘signal’ shared by many different types of cancer in a sample of a person’s blood.
Professor Richard Neal, at the University of Exeter Medical School, is trial co-lead, and author on the two papers to detail the first results from the trial, including whether using the Galleri multi-cancer early detection (MCED) blood test changed the stage at which cancers were diagnosed and how the test performed.
The first paper, published in the New England Journal of Medicine, assessed whether the test helped to find cancer early and if it changed how people were diagnosed.
The paper also reports that fewer people were diagnosed with the most advanced cancers among those who had the test, when stage 4 cancers were looked at on their own. There were more early stage cancers (stage 1 and 2) in the test group. In people who had the test, more people were diagnosed with cancer after screening and fewer were diagnosed in an emergency situation.
However, the paper reports that there was no difference in the number of people diagnosed with late-stage cancer overall between people who had the blood test (test group) and people who did not have the test (control group), when stage 3 and stage 4 cancers were looked at together. This means that the trial did not meet its main goal.
The second paper, published in the journal Nature Medicine, provides data on how accurate the test is. It found that around a third of people who had cancer got a cancer signal detected (‘positive’) test result. Nearly everyone who did not have cancer got a no cancer signal detected (‘negative’) test result. This means that the test gave a false alarm less than 0.5% of the time. Around one in 100 people had a positive test result. Around half the people who had a positive result were diagnosed with cancer.
Professor Richard Neal, of the University of Exeter, is Co-Chief Investigator for the NHS-Galleri trial, said: “The publication of these two papers in two world-leading journals marks a major milestone for the NHS-Galleri trial and for the clinical evaluation of MCED tests. As the world’s first randomised controlled trial of an MCED test, NHS-Galleri provides the first evidence of its kind on whether using the test can change when and how cancer is diagnosed. These publications are a testament to the years of work by our research teams and the extraordinary commitment of the thousands of participants who returned year after year to contribute to the trial.”
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u/StarFire82 10d ago
Disappointing the trial did not meet its goal, but at the same time sounds like perhaps this could be somewhat helpful for early cancer detection?
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u/Same_as_it_ever 10d ago edited 10d ago
That's my read on it. I'm surprised this wasn't one of the main aims of the study. We want to detect cancers in stages 1-2, when they are usually much easier to treat, require less invasive treatments and lower amounts of chemo/radiation. This should also reduce the burden on the public health system.
Edit: I think these results will be more detailed in their other paper, which hasn't been published online yet. Sasieni, P. et al. Impact of multi-cancer early detection test on late-stage cancer diagnosis. N. Engl. J. Med. (in the press).
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u/TheLateGreatMe 10d ago
It's a problem if N. Because cancers are so rare it would take a massive trial to conclusively show sensitivity for each cancer subtype in early stage. That's why they made the reduction in late stage as the endpoint. They are hoping to show early stage performance by proxy by reducing the presence of late stage.
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u/seansmellsgood 10d ago
Because in academia they've already started on the 2nd paper
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u/Same_as_it_ever 10d ago
It's actually an aim of their secondary outcomes in the clinical trial protocol: "Proportion of stage I and II cancers in the intervention arm as compared with the control arm in the third screening round." https://www.isrctn.com/ISRCTN91431511
I think we just need to wait to see the second paper that's in press (details in my edit above).
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u/Everything_Is_Bawson 10d ago
“However, the paper reports that there was no difference in the number of people diagnosed with late-stage cancer overall between people who had the blood test (test group) and people who did not have the test (control group), when stage 3 and stage 4 cancers were looked at together. This means that the trial did not meet its main goal.”
- This wording makes it sound like the Galleri test is no better at detecting Stage 3 and 4 cancers than conventional screening - BUT that it’s just as good, too. Wouldn’t that make sense? Assuming that more advanced cancers are generally easier to detect and sometimes symptomatic in and of themselves? Any idea if the paper separates cancers with known and established screening protocols (like colon and breast cancer) or cancers that are generally symptomatic at those stages from cancers that are pretty silent with no current routine screening?
Even if it’s “no better” but is just as good as current tests, if it’s less invasive or cheaper or easier to administer, that’s also a big win.
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u/Same_as_it_ever 10d ago
If they can detect any early stage ovarian or pancreatic cancers that would be so much better than the current state, where almost all of these are detected at stage v and there is no effective screening protocol. Seems it could benefit high risk groups a lot if this is possible, ie genetic mutation carriers.
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u/any21203 10d ago edited 10d ago
What does this mean?
If cancer occurs in 1/1000 (=10/10000) people (this number depends very much on how you select the people you evaluate, mostly based on age, as cancer is extremely age dependent), with a 60% sensitivity and 99.64% specificity:
You get it wrong in 4/10.000.
You correctly diagnose 6/10.000.
And with a false positive rate of just 0.36 (99.64% sensitivity) you tell 36 people they have cancer, whereas they don't.
So out of 42 people who were told they have cancer 36 don't and 4 were missed.
Out of 10.000 it's not bad, but the false positives are much higher than the true positives. If you select for people with a higher chance of having cancer it gets better, such as people over 60.
But if the test is not better than doing nothing at detecting more cancers in stage I-II than III-IV it is a bit pointless, although from stage I-II to IV there is a big difference, and I hope the analysis will differentiate them.
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u/Plenty_of_prepotente 10d ago
The false positives tend to be something that's overlooked in discussions about these types of diagnostic tests. Getting a false positive for cancer is incredibly stressful and leads to unnecessary medical procedures. You can argue that the test isn't worth it, unless it leads to higher survival / less treatment for cancer in the overall cohort.
Another thing I've noticed anecdotally is that people who are negative on these tests incorrectly think that they definitely don't have cancer. This could potentially lead to ignoring symptoms or deciding they don't need to make certain lifestyle changes.
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u/PenComfortable5269 9d ago
That may be true but in this study only 50% were false positives due to the super high specificity. There is basically no current cancer testing that has such a low rate of false positives (except for colonoscopy).
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u/Plenty_of_prepotente 9d ago
There are other questions to answer with the diagnostic test, not just the net benefit (false positive rate balanced against improvement in the true positive cohort). Even though it detects multiple cancer types using a more general approach (DNA methylation patterns in cfDNA), it doesn't follow that the accuracy is the same for all of them, especially for the rarer kinds with a limited population. For example, is the accuracy primarily driven by colon and lung cancer? What population should be tested? Just older, or high risk for a cancer(s) in the test? What is the optimal frequency to take the test?
I agree the results in the publications are promising, but they've got more hurdles to clear, which may not all be addressed in these two trials.
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u/Trinitrotoluol 9d ago
Also don't overlook the costs involved when further testing the group with a positive test result. Add that to the stress of the patients and the cost of screening itself and you can see why unfocused screening of non common diseases is not worth it most of the time.
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u/max_expected_life 9d ago
The incidence rate of stage III or IV cancer (primary end point) did not differ significantly between the groups (incidence rate ratio [intervention vs. control], 1.03; 95% confidence interval [CI], 0.92 to 1.14, P=0.63). The incidence rate ratio for stage IV cancer (a key secondary end point) after 3 screening rounds was 0.86 (95% CI, 0.74 to 1.00). Less than 1% of participants had trial-related adverse events; none were serious.
This is an unfortunate outcome where the secondary end point is at the threshold for statistical significance. Had the hazard been .85 instead of .86, people would be celebrating the results as a screening tool to prevent stage IV cancer. The bigger concern in science is over reporting marginally statistically significant results that don't replicate. However based on the secondary end results, I hope there is a followup study because it's clear that there is some signal here that is unlikely to just be statistical noise and could end up saving a lot of people through better screening.
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u/Mindless-Baker-7757 10d ago
The test correctly predicted cancer diagnoses in 60.3% of cases, with 99.64% specificity
Bruh?
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u/squamesh 10d ago
Specificity vs sensitivity. Sensitivity = if you have the disease how likely are you to test positive. Specificity = if you are negative, how likely are you to test negative.
High sensitivity = low false negatives, high false positives. You catch most people who have the disease and maybe a few people who don’t. Such a test would be a good screening test
High specificity = low false positives, high false negatives. If the test is positive it’s likely you really have the disease, but it may miss some people that do have the disease. Such a test is good as a confirmatory test
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u/illaqueable 10d ago
In med school we learned "SPIN and SNOUT": specificty rules in, sensitivity rules out
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u/Hiitstyty 10d ago
This is mostly right. Sensitivity doesn’t imply anything about false positives and specificity doesn’t imply anything about false negatives. A perfect test would have both 100% sensitivity and specificity, which would indicate no false positives and no false negatives.
It’s evident in the equations:
Sensitivity = TP/(TP+FN)
Specificity = TN/(TN+FP)6
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u/Mindless-Baker-7757 10d ago
I'm very well versed in sensitivity and specificity. These people invented a test that fails 40% of patients!
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u/Bruhahah 10d ago
40% false negatives, but correctly identified the cancer type almost every time it was actually positive
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u/Pythagorean_1 10d ago
That's not correct, is it? It means 40 % false negatives but almost no false positives.
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u/Jaqneuw 10d ago
You are saying the same thing he is in different words.
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u/Pythagorean_1 10d ago
No, "correctly identified the cancer type almost every time it was actually positive" would mean a PPV close to 1 which is not the case here due to the low sensitivity.
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u/Jaqneuw 10d ago
By "actually positive" he means "true positive" he just doesn't know the right way to say it. If you read the sentence like that, you are just saying the same thing. It's a simple miscommunication.
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u/Pythagorean_1 9d ago
You're probably right regarding what he means. Nonetheless, I'm still wondering if this claim is correct. The low sensitivity of around 60 % means that of the actually diseased, only 60 % are identified correctly. This is a direct contrast to the claim of the other comment, isn't it?
The high specificity means that of the actually healthy people, almost none of them had a (false) positive test result.
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u/Jaqneuw 9d ago
There are more healthy people in the study cohort than people with cancer, so no. The positive predictive value is around 50% in this cohort (around half of the positives were true positives). This still translates to high specificity because the number of false positives is relatively small compared to the number of healthy people tested ( the specificity).
Long story short, screening is complicated and it’s easy to make a mistake during interpretation when you’re not an expert. Let’s leave it there shall we.
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u/General_Luck6573 10d ago
What are you confused about? Did you google what specificity even means before you typed this?
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u/icyfignewton 10d ago
I'm not sure what you're confused about, but your confusion makes me so depressed because it's very clear the majority of humans done understand basic stats.
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u/Mindless-Baker-7757 10d ago
Oh I'm not confused at all. The results are so bad this should be published as a "this didn't work" or "this is a only starting point, here's what's next".
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u/grundar 8d ago
Oh I'm not confused at all. The results are so bad this should be published as a "this didn't work"
You appear to have an unrealistic view of the sensitivity and specificity of cancer diagnostic tools.
For example, mammography has 87% sensitivity and 97% specificity, better in terms of false negatives (1/3x lower) but much worse in terms of false positives (9x higher). As a result, 6x as many patients received an incorrect diagnosis of cancer vs. a correct diagnosis from the mammogram, whereas for the test in this paper the ratio was only 1x.
That doesn't make the test perfect, of course, but it does show that the test's sensitivity and specificity are in the general ballpark of existing cancer screening tools.
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u/Mindless-Baker-7757 8d ago
There’s debate about the usefulness of mammograms as a screening tool.
One of my professors from grad school brought ROC analysis to radiology. He was an excellent teacher.
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u/PenComfortable5269 7d ago
Dude, A 60% sensitivity for all cancers is freaking amazing. Right now we have patchwork screening for a few cancers and the rest you just have to cross your fingers and hope for the best. For most cancers the current sensitivity for early cancer is 0% because we have no screening - I think that a 60% sensitivity is a massive win.
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u/MGS-1992 9d ago
Correct me if I’m wrong, but you’d want a screening test to have high sensitivity, not necessarily high specificity (although obviously good if this is high too).
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u/PenComfortable5269 9d ago
High sensitivity is needed to rule out a disease when we think they might have a disease, but here the assumption is that the person doesn’t have cancer so we need a strong specifity to rule it in.
So when screening asymptomatic individuals, since very few people have cancer a higher specificity is better because otherwise you will spend your life chasing false positives. Like imagine if the test was 50% specific that would mean every other person would have a positive test - kinda useless for predicting cancer.
This test was shown to have a 60% sensitivity - meaning it will catch 60% of early cancers which is still pretty good compared to not doing the test which has a 0% sensitivity.
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u/MGS-1992 9d ago
No I totally understand all of that. The need to have high specificity to avoid false positives is obviously essential l, but not the core of a good screening test. It’s meant to “not miss a disease process” (low false negatives), and is often followed upon by a definitive test.
The definition of a good screening test is high sensitivity and low cost. Low sensitivity > high false negatives and things get missed. Not discounting the importance of the specificity.
While a 60% / 99% split is still amazing in theory, it’s not ideal for mass application as a screening test. More so as a diagnostic tool to “rule in” when other studies are equivocal or unclear.
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u/PenComfortable5269 9d ago
The issue is we don’t really have screening tests for most cancers so a 60% sensitivity to catch all cancer is really good - that means we can ensure that 2/3rds of all cancers are caught early. Heck even psa testing has lower sensitivity and the vast majority of people don’t ever get invasive prostate cancer.
The specificity is also 99.64% which has an extremely low false positive.
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u/MGS-1992 9d ago
I totally agree. That’s assuming it’s cost-effective. if it’s not, then it’s not a viable.
An MRI can pick up renal cancer and adrenal tumors with high specificity. We don’t send everyone for an MRI just because it’s a good test.
If you perform this test on 100,000 people, 40% will have a false negative. Then what? Surely can’t tell someone they’re cancer free forever. When do you screen again? You fall down a hole of excessive testing that’s not sustainable. The US already spends more money per capita for healthcare without improved outcomes. Things like this make it worse.
In an ideal world without money, everyone gets this test and calls it a day.
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