Biological variation estimates of thyroid related measurands – meta-analysis of BIVAC compliant studies

[helvella]

Anyone able to help? diogenes

I found this, and it looked like it might be interesting and relevant. Then I tried reading it and found it got more and more difficult to follow!

What was clear, though, was that the existing situation is not satisfactory.

[I][B]Biological variation estimates of thyroid related measurands – meta-analysis of BIVAC compliant studies[/B]

Pilar Fernández-Calle, Jorge Díaz-Garzón, William Bartlett, Sverre Sandberg, Federica Braga, Boned Beatriz, Anna Carobene, Abdurrahman Coskun, Elisabet Gonzalez-Lao, Fernando Marques, Carmen Perich, Margarida Simon, Aasne K. Aarsandand on behalf of the EFLM Working Group on Biological Variation and Task Group for the Biological Variation Database

From the journal Clinical Chemistry and Laboratory Medicine (CCLM)

doi.org/10.1515/cclm-2021-0904

Abstract

Objectives

Testing for thyroid disease constitutes a high proportion of the workloads of clinical laboratories worldwide. The setting of analytical performance specifications (APS) for testing methods and aiding clinical interpretation of test results requires biological variation (BV) data. A critical review of published BV studies of thyroid disease related measurands has therefore been undertaken and meta-analysis applied to deliver robust BV estimates.

Methods

A systematic literature search was conducted for BV studies of thyroid related analytes. BV data from studies compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) were subjected to meta-analysis. Global estimates of within subject variation (CVI) enabled determination of APS (imprecision and bias), indices of individuality, and indicative estimates of reference change values.

Results

The systematic review identified 17 relevant BV studies. Only one study (EuBIVAS) achieved a BIVAC grade of A. Methodological and statistical issues were the reason for B and C scores. The meta-analysis derived CVI generally delivered lower APS for imprecision than the mean CVA of the studies included in this systematic review.

Conclusions

Systematic review and meta-analysis of studies of BV of thyroid disease biomarkers have enabled delivery of well characterized estimates of BV for some, but not all measurands. The newly derived APS for imprecision for both free thyroxine and triiodothyronine may be considered challenging. The high degree of individuality identified for thyroid related measurands reinforces the importance of RCVs. Generation of BV data applicable to multiple scenarios may require definition using “big data” instead of the demanding experimental approach.

Keywords: biological variation; biological variation data critical appraisal checklist (BIVAC); meta-analysis; thyroid biomarkers [/I]

Full paper freely accessible here including PDF option:

degruyter.com/document/doi/...

Fernández-Calle, Pilar, Díaz-Garzón, Jorge, Bartlett, William, Sandberg, Sverre, Braga, Federica, Beatriz, Boned, Carobene, Anna, Coskun, Abdurrahman, Gonzalez-Lao, Elisabet, Marques, Fernando, Perich, Carmen, Simon, Margarida, Aarsand, Aasne K. and on behalf of the EFLM Working Group on Biological Variation and Task Group for the Biological Variation Database,. "Biological variation estimates of thyroid related measurands – meta-analysis of BIVAC compliant studies" Clinical Chemistry and Laboratory Medicine (CCLM), vol. , no. , 2021. doi.org/10.1515/cclm-2021-0904

[diogenes Remembering]

The paper measures by meta-analysis the precision, consistency and accuracy in several assays for TSH, T4, T3 FT4 and FT3. It finds FT4 and FT3 assays lower in precision and consistency than the total assays. It also studies these parameters in different conditions eg pregnancy. By consistency I mean serial measurements on the same person. The problem with this paper is that it only encounters a small proprtion of the available assays, whose identity is often unclear. So the study can only apply to these tests and can say nothing about others not used in the analysis. No doubt within the methods measured one could pick out the better ones, but it is limited by omission of the many others perhaps not so popularly used.

[Charlie-Farley]

Bit heavy going - will need to read this a few more times and not on an iPhone 😂

I noted in the discussion they recognised diurnal effects on TSH levels and they did seem to understand that the study was limited - talking a lot about the potential for ‘big data’ to deliver more realistic ranges for BV (biological variation) in different groups. I’m wondering though if they understand this big data may not make diagnosis any more precise with tighter ranges and that the big data may actually lead them to realise the inherent variability? No mention of setting results into context by looking at symptoms (how the patient feels is still not priority).