How do I interpret an AST trend across three draws?

I have the full paper rather than the abstract, and the supplementary appendix.

I have the document in front of me and I can read the numbers. What I cannot do is interpret them.

I am reasonably comfortable with statistics and completely uncomfortable with chromatography, or vice versa.

Which parts of this are informative and which are decoration?

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.

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.

On the detail: 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.

External quality assurance schemes document between-laboratory differences on common analytes that routinely exceed the size of clinically interesting changes.

The caveat is that a panel is not a diagnosis and interpreting one is a clinician's job, particularly when several values move together.

Baseline first, then a repeat under identical conditions. Everything else is secondary.

The relevant statistical point is that a ninety-five per cent reference interval means one analyte in twenty will read out of range in a healthy person by construction.

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.

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.

Pre-analytical factors — posture, tourniquet time, fasting, sample handling — are the largest source of error in routine biochemistry, well ahead of the analysis itself.

Nothing here is medical advice. If something is out of range and you do not know why, that is a consultation rather than a research project.

One out-of-range value on a twenty-analyte panel is expected. Two on a repeat is a finding.

The short version: a small, well-chosen panel with a baseline beats a large one without.

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.

Ordering tests you will not act on generates anxiety and incidental findings, both of which have costs.

Same laboratory, same time, same fasting state, or the comparison is not a comparison.

Start with a baseline. A result taken before anything started converts most later ambiguity into a simple comparison, and it cannot be obtained retrospectively.

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.

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.

Research-use compounds are not approved for human use, and no panel makes that safer.

Decide the action for each result before you order the test.

edited 23 Aug 2024 by Dr_Colm_Fitzhenry — added the placebo-arm figures

Answering this needs to distinguish screening from monitoring. A screening panel looks for the unexpected; a monitoring panel tracks something you already have a reason to watch.

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.

The caveat is the population. Trial participants were screened, monitored and supported; the effect size in an unmonitored setting is not the trial effect size, and it is not obvious in which direction the difference runs.

Keep the full report, not the number. You will need the units and the interval later.