Laboratories and networks
Change analysers knowing which patients move.
We turn the method comparison you already run into the answer clinicians ask for: whose results cross a decision limit, and what to re-test while you switch.
- CD4 results changed category after a platform switch
- 535
- expected from repeat testing alone
- 238
- of the excess over a default-imprecision expectation, caught by line correction and a re-test band on unseen data
- 66%
- of results re-tested to get there
- 15%
SampleSample report built from public data.
What you get
Beyond the bias
Your validation software sizes the difference between the analysers. The report adds what that difference means for your patients.
Bias where clinicians act
An average bias hides what happens at the concentrations that drive decisions.
Bias at each of your own decision limits, with its interval.
Patients across each limit
Clinicians want to know which of their patients changed category.
Results crossing each limit, in each direction, set against what repeat testing alone would move.
A re-test band for the switch
Both analysers run side by side for weeks, and borderline results need a rule.
A narrow band around each limit where a new result is repeated, sized to the budget you choose.
Comparable across sites
ISO 15189 asks whether results from different instruments are comparable.
On request, the same analysis across your network: whether sites report interchangeably, and which site moves which patients. Scoped per network; not part of the standard program yet.
See it on real data
One platform switch, sized and managed
A sample report built from a published CD4 platform change, as if a laboratory had run its own pairs.
All four clinical thresholds (100, 200, 350, 500 cells/µL)
Crossed between the two systems: 535
Expected from repeat testing alone: about 238
Fig. 1. Sample built from public data: 1,885 paired CD4 counts from an open-access deposit, one platform replaced by another. Reported without adjustment, 535 results change category against about 238 expected from repeat testing alone. Flagging the results that land in a narrow band around each threshold for re-test, and converting the rest with the comparison line, catches 66% of that excess on data the band was not fitted to, while re-testing 15% of results; the comparison line alone catches 46%.
Source Coetzee LM, Glencross DK (2017). PLoS One. doi:10.1371/journal.pone.0187456 (opens in a new tab); PMC5669480 (opens in a new tab). Licence: CC BY 4.0 (opens in a new tab). Re-analysed by NakedSignal.
Show the numbers
| Measure | Value |
|---|---|
| Paired CD4 counts | 1,885 |
| Clinical thresholds (cells/µL) | 100, 200, 350, 500 |
| Results that changed CD4 category, unadjusted | 535 |
| Expected to change from repeat testing alone | 238.49 |
| Excess caught by comparison line and re-test band, unseen data (%) | 66 |
| Results re-tested, unseen data, median (%) | 15 |
| Repeat-test imprecision | Default value |
How it works
From paired results to a clinician note
Bring your pairs
The same samples measured on the old and new analyser, with your decision limits. One file per site for a network.
Size the change locally
The program runs on your own computer: bias, crossings and a re-test band at each of your limits, against what repeat testing alone would move.
Brief your clinicians
You get the report and a one-page note for requesting clinicians, written from the same numbers.
Runs inside your laboratory
The program runs offline on your own computer. The files that leave are designed to carry only aggregates, and you sign off what is released. Repeated releases from nearly identical data can reveal more, so the next versions add a local release guard. Security and data handling
Guides
Go deeper
- GuideBias at clinical decision limitsWhy average bias hides what matters in a method comparison, and how to count patients who cross a decision limit, with a worked example on public data.
- GuideCrossings by chanceThe chance that a repeat result lands on the other side of a decision limit, from imprecision and distance to the limit, summed to an expected count, and set against bias.
- GuideComparability across analysers and sitesWhat ISO 15189:2022 and CLSI EP31 ask when one test runs on more than one instrument, and how to report comparability at decision limits, with public data from three meters in two settings.
Changing an analyser soon?
Tell us what you are switching. We will show you what the report would cover and what it needs from you.