Measurement batch differences and between‐batch conversion of Alzheimer's disease cerebrospinal fluid biomarker values

Abstract

Introduction Batch differences in cerebrospinal fluid (CSF) biomarker measurement can introduce bias into analyses for Alzheimer's disease studies. We evaluated and adjusted for batch differences using statistical methods. Methods A total of 792 CSF samples from 528 participants were assayed in three batches for 12 biomarkers and 3 biomarker ratios. Batch differences were assessed using Bland‐Altman plot, paired t test, Pitman‐Morgan test, and linear regression. Generalized linear models were applied to convert CSF values between batches. Results We found statistically significant batch differences for all biomarkers and ratios, except that neurofilament light was comparable between batches 1 and 2. The conversion models generally had high R 2 except for converting P‐tau between batches 1 and 3. Discussion Between‐batch conversion allows harmonized CSF values to be used in the same analysis. Such method may be applied to adjust for other sources of variability in measuring CSF or other types of biomarkers.

Preanalytical stability of plasma/serum brain‐derived tau

“…Longitudinal biofluid biomarker analyses can be complicated by the need to remeasure baseline samples with the same reagent batch as the follow-up ones to avoid batch effects. 19 Here, we evaluated a workaround of measuring a small, representative selection of baseline samples along with the follow-up ones (∼10% of the total samples) to improve efficiency and save time and resources. Plasma BD-tau concentrations in the first and repeated runs were nearly identical, with minor analytical errors that were within the range of expectations.…”

A new protocol for a single-stage combined cardiopulmonary and echocardiography exercise test: a pilot study

“…To assess agreement between the test method pairs, three methods were used: (i) Bland–Altman plots with percentage outside of limits of agreement (LoA) as a measure of outlier frequency, 95% LoA, as a measure of variability and mean difference as a measure of systematically fixed bias 27 ; (ii) Lin’s concordance coefficient, as a measure of both precision and accuracy to determine how far the observed data deviate from the line of perfect concordance (higher coefficient represents better linear correlation) 27 ; and (iii) Pitman–Morgan correlation between difference and mean with Bradley–Blackwood omnibus test of equality of means and variances, to assess whether there is proportional bias, affecting values with higher means more, with the Bradley–Blackwood P < 0.05 and positive Pitman–Morgan coefficient denoting lower concordance at higher values. 28 , 29 …”

AD‐associated CSF biomolecular changes are attenuated in KL‐VS heterozygotes

“…Statistical conversion models were developed based on this subset and applied to adjust for the batch differences and harmonize the values across batches. 31 …”

“…The samples were immunoassayed for Aβ42, t‐tau, and p‐tau181 with INNOTEST ELISAs (Fujirebio, Ghent, Belgium) in two batches as described previously, 18,30 with a subset of samples re‐assayed. Statistical conversion models were developed based on this subset and applied to adjust for the batch differences and harmonize the values across batches 31 …”