The relationship between CSF/serum immunoglobulin and albumin ratio across laboratories: a retrospective, multi-center study

The relationship between cerebrospinal fluid (CSF)/serum immunoglobulin (Ig) ratios (QIg) and CSF/serum albumin ratio (Qalb) is a commonly used biomarker in routine CSF diagnostics. It is used to quantitatively determine the presence of an intrathecal Ig synthesis, which is important for the diagnosis of various inflammatory neurological diseases. Which approach to describe the relationship between Qalb and QIg should be applied has been a matter of debate for decades. To compare different linear and non-linear models to determine which model fits the relationship between QIgG, QIgA, QIgM and Qalb best. We included CSF and serum sample pairs collected for routine diagnostic purpose across seven sites of patients without evidence of intrathecal Ig synthesis (defined by negative oligoclonal IgG bands and the condition QIgG > QIgA > QIgM, respectively). Linear, quadratic, cubic, root and power models were fitted for the mean relationship between QIgG, QIgA, QIgM and Qalb, as well as to determine the 97.5th percentile as upper limit of normal (ULN). Model fit was evaluated by various goodness-of-fit measures including mean absolute error (MAE) and the mean percentage error (MPE). A total of 22,207 patients at a median age of 49 (2.5th, 97.5th percentile: 10, 82) years comprising 52% females were included. The median Qalb was 5.8 × 10−3 (2.4 × 10−3, 23 × 10−3), QIgG 3.0 × 10−3 (1.2 × 10−3, 13.4 × 10−3), QIgA 1.7 × 10−3 (0.6 × 10−3, 9.5 × 10−3) and QIgM 0.6 × 10−3 (0.2 × 10−3, 6.0 × 10−3). The goodness-of-fit measures for the mean relationship between QIgG and Qalb were similar across models [maximum difference in MAE (ΔMAE) between models was 0.01 × 10−3, in MPE (ΔMPE) 0.3 percentage points (pp)], but showed higher differences for QIgA [ΔMAE: 0.03 × 10−3, ΔMPE: 3 pp] and even higher for QIgM [ΔMAE: 0.08 × 10−3, ΔMPE: 18 pp] in favor of non-linear models. Similar findings were obtained for ULN (ΔMPE: QIgG 3 pp; QIgA 7 pp; QIgM 13 pp) again in favor of non-linear models. Linear and non-linear models can be used to approximate the relationship between QIgG and Qalb. Non-linear models explain the relationship between QIgA, QIgM and Qalb. Appropriate Qalb-dependent ULN for QIgG, QIgA, QIgM based on power model and quantile regression are provided.