I am reading the trial table rather than the press release, which is why the numbers differ.
This is presented as though it settles something, and I am not convinced it does.
I have two documents that appear to disagree, which is what prompted this.
What does this actually establish, and what does it not?
Answer first: decide what you would do differently for each possible result before you order the panel. Anything that fails that test is a number you will worry about and not act on.
A twenty-analyte panel run on a healthy person will produce, on average, one out-of-range result purely from how reference intervals are constructed. That is arithmetic rather than pathology.
| Quantity | Value | Derivation |
|---|---|---|
| Control-arm event rate | 8.0 % | From the trial table, not the abstract |
| Hazard ratio | 0.80 | Reported |
| Treated event rate | 6.4 % | 8.0 × 0.80 |
| Absolute risk reduction | 1.6 pp | 8.0 − 6.4 |
| Number needed to treat | 63 | 1 ÷ 0.016 |
| Relative risk reduction | 20 % | 1 − 0.80 |
The last two rows describe the same finding. Only one of them is used in headlines.
Repeat before you react. A single abnormal value has a substantial probability of being within the combined biological and analytical variation of a normal one.
External quality assurance schemes document between-laboratory differences on common analytes that routinely exceed the size of clinically interesting changes.
Keep the full report, not the number. You will need the units and the interval later.
edited 22 Jul 2024 by ben_akintola — added the citation requested in comments
Analytical standards and reagents with traceable certificates. Every quantitative result you read inherits the accuracy of the standard behind it.
Shop standardsThe short version: a small, well-chosen panel with a baseline beats a large one without.
A sensible core for this population is a full blood count, renal function with electrolytes, liver enzymes with bilirubin, a fasting lipid panel with apolipoprotein B, HbA1c and thyroid-stimulating hormone.
Specifically, haemolysis in the sample raises potassium and several enzymes spuriously. If a result is bizarre, ask whether the sample was flagged before building a theory on it.
Biological variation data are published per analyte and are the basis for the reference change value — the difference between two results that is larger than noise.
The caveat is that a panel is not a diagnosis and interpreting one is a clinician's job, particularly when several values move together.
Decide the action for each result before you order the test.
edited 21 Jul 2024 by Dr_Elias_Weiss — clarified the distinction between purity and content
Mechanically, this is answerable, and the answer is mostly about which tests rather than how many.
Delta checks — comparing against your own previous value — are far more sensitive than comparing against a population interval, which is the argument for keeping a series rather than a snapshot.
Keep the reports rather than the numbers. Units, reference intervals and methods all vary, and a bare number two years later is not comparable to anything.
Research-use compounds are not approved for human use, and no panel makes that safer.
Same laboratory, same time, same fasting state, or the comparison is not a comparison.
Standardise the conditions — same time of day, same fasting state, same laboratory — or you are measuring the conditions rather than yourself.
Timing matters per analyte: cortisol and testosterone are diurnal, triglycerides are postprandial, and creatinine responds to hydration and to recent training. Fixing the conditions removes most of the noise.
Reference intervals are conventionally the central ninety-five per cent of a reference population, which is the direct cause of the one-in-twenty out-of-range rate on a healthy panel.
One out-of-range value on a twenty-analyte panel is expected. Two on a repeat is a finding.
Start with a baseline. A result taken before anything started converts most later ambiguity into a simple comparison, and it cannot be obtained retrospectively.
Same laboratory, same method, same time of day, same fasting state. Between-laboratory differences on several common analytes are larger than the changes people are trying to detect.
Ordering tests you will not act on generates anxiety and incidental findings, both of which have costs.
Baseline first, then a repeat under identical conditions. Everything else is secondary.
Ask PeptideStack is a static archive. Posting is closed, but the norms are worth stating: answer the question that was asked, show your working, cite the trial or the certificate, and say plainly where the evidence runs out.