Guides
Guides
Reference notes on method comparison and result comparability, written to be reused. Each cites its sources.
Bias at clinical decision limits: what a method comparison misses
Why an average bias hides what matters when an analyser changes, how to estimate bias at each decision limit, and how to count the patients who cross it against what repeat testing alone would move. With a worked example on public data.How many results cross a decision limit by chance? Repeat testing as the baseline
The chance that a repeat result lands on the other side of a limit, from imprecision and distance to the limit; summing it to an expected count; why bias dominates at larger shifts; and how measured and assumed imprecision change the answer. With worked examples on public data.Reagent and calibrator lot changes: verifying with patient samples at decision limits
Why quality control may not show a lot shift, what CLSI EP26 asks and where it leaves gaps, how to read a small patient-sample comparison against repeat testing, and how to see drift across several lots.Are your analysers interchangeable? Comparability of results across instruments and sites
What ISO 15189:2022 and CLSI EP31 ask when one test runs on more than one analyser or site, and how to report comparability at the decision limits. With public data from one analyser against three meters in two settings.Point-of-care HbA1c against the laboratory at 5.7, 6.5 and 7 percent
What NGSP and IFCC standardisation does and does not guarantee at the diagnostic and target lines, how to read bias at each line, and how many results change category against repeat testing alone, on five public comparisons.Jaffe or enzymatic creatinine: what a method change does at the decision lines
Why the two chemistries differ, what IDMS traceability fixes and what it does not, and a public case where a method change moved fewer results than repeat testing alone would, set against point-of-care comparisons that moved more.Central lab, local lab, new device: measurement change in trials and in medical AI
How a change of laboratory, device or site moves people across a protocol threshold or a model input, how to size it against measurement noise, and how to fix the check before unblinding. What we offer is labelled as an offer.