Indirect methods for reference intervals

Thomas Streichert

Rainer Haeckel

Working Group Guide Limits

Crucial Information for Decisions

Sodium mmol/l 135-145

Lab-ReportName: Müller, Lieschen Gender: female DOB: 6.11.1958

140

Measurand Result UnitReference

Interval

IVD-Tests and Decisions

2016 , Rohr, UP,, PLOS ONE

Richtwerte bei quantitativen Untersuchungen im medizinischen Laboratorium. J Lab Med 2009;33:228

Reference Limits

DecisionLimits

Action

Limits

TherapeuticIntervals

(TDM)

Proposal for the classification of Guide Limits

Criterion – Reference Interval (RI)

95% IntervalRI

Reference Intervals

Where do you get yourreference intervals from?

From the kit insert! I use the intervals given

by the manufacturer!

Hmm - sometimes I usereference intervals from

textbooks.

Wait! For TSH, I found a very good paper and

now I use the intervalsfrom Wiseguy et. al.!

Did you evaluate them? Did you check the

transferability?

Aaahem – no...

Legal requirements?

98/79/EG IVD DirectiveEuropean Law

National LawAct on Medical Devices

(MPG)

RiliBÄKFederal Chamber of Physicians

Medical Products Operator Ordinance(MPBetreibV)

A norm is not a law!

DIN EN ISO 15189 + 22870

According to the European Directive IVD medical devices, manufacturers are obliged to supply their clients with appropriate RLs for the use of their assay platforms and reagents.

Following the International Organization for Standardization (ISO) 15189 standard for clinical laboratory accreditation each laboratory should periodically re-evaluate its own RLs.

Estimation of Reference Intervals

Direct Methods

Indirect Methods

Reference Population

Reference Individuals

Reference Sample Group

Result Unit

129 mmol/l

135 mmol/l

140 mmol/l

141 mmol/l

136 mmol/l

145 mmol/l

142 mmol/l

Reference Values

Reference Distribution

Reference Limits andReference Intervals

Sodium135-145 mmol/l

10 mmol/l

IFCC – Direct Concept for Reference Intervals

„Problems“ with Direct Methods

Direct Methods Indirect Methods

Subpopulation usually “healthy” closer to patients´situation

Ethical problems must be considered not relevant(Data privacy)

Stratifications (Age, gender) difficult easy

Expenses high, dependent on number of samples

negligible

Complexity of statistics low high

Confidence limits usually broader usually smaller

Transferability problems relevant not relevant

Adopted from Haeckel et al, 2017, Manuscript

Concept – Indirect Methods

Selection of the results from a mixed population (containing diseased and non-

diseased subjects!)

Identification of a probably „healthy“ subpopulation.

Reference Values (Results)

Reference Distribution

Reference Intervals and Reference Limits

How does it work?

DataLIS

n>250000

Results

R for statistical computing and graphicsPackages: geoR, mgcv, msm

www.r-project.org, The R logo is © 2016 The R Foundation2017, Haeckel, Review (Draft)

RLEExcel-Tool

(VBA)

1. Hoffmann: PP-plot and QQ-plot

3. Bhattacharya: resolution in normal distributed subgroups

4. Naus et al.: resolution after gamma-transformation 5. Baadenhuijsen et al. : resolution after Box Cox transformation 6. Pryce Karisto et al.: resolution in 2 different normal distributions with one common mode 7. Martin et al.: Gram-Charlier series

8. Arzideh et al.: resolution after preselection according to direct characteristics (e.g. excluding intensive care patients)

9. Wosniok and Haeckel: SD estimation of the difference between mode derived of the linear and logarithmic scale

Number of samples needed?

2017, CCLM Rainer Haeckel*, Werner Wosniok, Farhad Arzideh, Jakob Zierk, Eberhard Gurr and Thomas Streichert,

Drift-Analysis

Density Plot and Calculation of RLs

WBC

Sex Age (Min) Age (Max) L RL U RL

Leukocytes absolut(in use)

Thomas, 7. Edition

Sysmex

RLE35 (UKK)n= 4345 (m)n= 4487 (w)

Trillium (UKK)

RLE (MHH)

Trilium (MHH)

M and W

M and W

MW

MW

MW

MW

MW

15

18

1818

1818

1818

1818

1818

99

99

9999

9999

199199

199199

199199

4,4

3,5

3,914,49

3,573,63

3,83,7

3,783,7

3,73,7

11,3

9,8

10,9012,68

11,7613,05

13,113,1

12,3712,76

13,413,1

https://www.pedref.org/index.html

AP – Data PoolingDifferences between centers?

2017, Jakob Zierk*, Farhad Arzideh, Rainer Haeckel, Holger Cario, Michael C. Frühwald, Hans-Jürgen Groß, Thomas Gscheidmeier, Reinhard Hoffmann, Alexander Krebs,Ralf Lichtinghagen, Michael Neumann, Hans-Georg Ruf, Udo Steigerwald, Thomas Streichert, Wolfgang Rascher, Markus Metzler and Manfred Rauh ,CCLM

AP – Pediatric RIsNumber of Samples

Zierk et al. 2017

AP – Pediatric RIs

Comparison of 2.5th and 97.5th percentiles for alkaline phosphatase activity (solid lines) to reference intervals from the CALIPER

study (dotted lines)

Age- and sex-dependent percentile charts for alkaline phosphatase activity, showing the 50th percentile (solid lines,

blue), 25th and 75th percentiles (dashed lines, green), 10th and 90th percentiles (dashdotted lines, orange), and

2.5th and 97.5th percentiles (dotted lines, red); Zierk et al. 2017

Direct Methods vs. Indirect Methods

Direct Methods Indirect Methods

Subpopulation usually “healthy” closer to patients´situation

Ethical problems must be considered not relevant(Data privacy)

Stratifications (Age, gender) difficult easy

Expenses high, dependent on number of samples

negligible

Complexity of statistics low high

Confidence limits usually broader usually smaller

Transferability problems relevant not relevant

Adopted from Haeckel et al, 2017, Manuscript

Conclusions

• There are a number of indirect methods for the estimation of reference intervals.

• DGKL developed an algorithm for public use: RLE

• Advantages Direct vs. Indirect Methods

• IFCC C-RIDL states that indirect approaches for RL estimation could offer additional information to direct methods (especially at the edges of age)

Working Group GLs C-RIDL

• Thomas Streichert (Speaker)

• Rainer Haeckel (Secretary)

• Eberhard Gurr

• Farhard Arzideh

• Rainer Klauke

• Jakob Zierk

• Bernd Wolters

• Werner Wosniok

• Y. Özarda (Chair)

• D. Kang

• J. Macri

• K. Sikaris

• T. Streichert

• B. Yadav

• G. Jones

Thank you!

Data drift – Example FolatFolat deficiency<4,6 µg/L

2017 2016 2015 2014

UKK 32 % 9 % 9 % 8 %

MVZO 26 % 13 % 7 % 2,5 %