4 ms·

Reference link has more details: “ Results Higher levels of all immune markers were correlated with a reduced risk of symptomatic infection. Vaccine efficacy of

Reference link has more details: “ Results Higher levels of all immune markers were correlated with a reduced risk of symptomatic infection. Vaccine efficacy of 80% against primary symptomatic COVID-19 was achieved with an antibody level of 40923 (95% CI: 16748, 125017) and 63383 (95% CI: 16903, not computed (NC)) for anti-spike and anti-RBD, and 185 (95% CI: NC, NC) and 247 (95% CI: 101, NC) for pseudo- and live-neutralisation assays respectively. Antibody responses did not correlate with overall protection against asymptomatic infection.” https://www.medrxiv.org/content/10.1101/2021.06.21.21258528v1 https://www.medrxiv.org/content/10.1101/2021.06.21.21258528v... Does anyone know which units these use and how to convert to AU/mL?

yorwba 5y ago
That's the study mentioned as "earlier data" in the Nature article. The newer study that the article is mostly talking about is the first reference, https://doi.org/10.1056/NEJMoa2109072 https://doi.org/10.1056/NEJMoa2109072 .
KarlKemp 5y ago
I believe these are AU. Only it's AU not as in astronomical units, but arbitrary units. And they are likely arbitrary in a different way than whatever values you have in mind. These are used in cases where you can measure something, such as the how dark some liquid gets after some reaction, but cannot, or don't bother, to turn that into some "real" number such as the number/concentration of particles in the liquid causing the effect. So these units are comparable across several experiments or measurements using the same protocol. Sometimes they are tied to the equipment used and can be compared to other data from the same equipment. But other than that, only the relative values or, as in this case, the finding of proportionality is meaningful.
- sologoub 5y ago
  Thanks for explaining! So in other words these cannot be compared with unrelated studies or test results.
  - KarlKemp 5y ago
    Find experiments using the same instruments, and you can compare raw numbers, sometimes. But, to get a general idea: just look at the values they got across their population, remove any extreme outliers, and put it next to some chart using units you want to convert to. Make sure they are on the same scale (i. e. linear or log). The mean and other quantiles should correspond. Or, depending on what you're looking for, just eyeballing fig. 1 (https://www.medrxiv.org/content/medrxiv/early/2021/06/24/2021.06.21.21258528/F1.large.jpg https://www.medrxiv.org/content/medrxiv/early/2021/06/24/202...) itself might be enough. It shows (little surprise) that the bulk of measurements cluster in "safe" territory. That asignificant number of people show stronger reactions than that bulk, by sometimes orders of magnitude, but don't derive (much/yet) additional protection from it. And that a number of individuals show a weak response and are at risk, without that group being distinct from the rest in any specific way. Rather, it's a continuum

yorwba 5y ago

That's the study mentioned as "earlier data" in the Nature article. The newer study that the article is mostly talking about is the first reference, https://doi.org/10.1056/NEJMoa2109072 https://doi.org/10.1056/NEJMoa2109072 .

KarlKemp 5y ago

I believe these are AU. Only it's AU not as in astronomical units, but arbitrary units. And they are likely arbitrary in a different way than whatever values you have in mind. These are used in cases where you can measure something, such as the how dark some liquid gets after some reaction, but cannot, or don't bother, to turn that into some "real" number such as the number/concentration of particles in the liquid causing the effect. So these units are comparable across several experiments or measurements using the same protocol. Sometimes they are tied to the equipment used and can be compared to other data from the same equipment. But other than that, only the relative values or, as in this case, the finding of proportionality is meaningful.

sologoub 5y ago
Thanks for explaining! So in other words these cannot be compared with unrelated studies or test results.
- KarlKemp 5y ago
  Find experiments using the same instruments, and you can compare raw numbers, sometimes. But, to get a general idea: just look at the values they got across their population, remove any extreme outliers, and put it next to some chart using units you want to convert to. Make sure they are on the same scale (i. e. linear or log). The mean and other quantiles should correspond. Or, depending on what you're looking for, just eyeballing fig. 1 (https://www.medrxiv.org/content/medrxiv/early/2021/06/24/2021.06.21.21258528/F1.large.jpg https://www.medrxiv.org/content/medrxiv/early/2021/06/24/202...) itself might be enough. It shows (little surprise) that the bulk of measurements cluster in "safe" territory. That asignificant number of people show stronger reactions than that bulk, by sometimes orders of magnitude, but don't derive (much/yet) additional protection from it. And that a number of individuals show a weak response and are at risk, without that group being distinct from the rest in any specific way. Rather, it's a continuum