| Literature DB >> 28116160 |
Gabriella Passerini1, Gloria Dalla Costa2, Francesca Sangalli2, Lucia Moiola2, Bruno Colombo2, Massimo Locatelli1, Giancarlo Comi2, Roberto Furlan3, Vittorio Martinelli2.
Abstract
Background. The presence of CSF oligoclonal bands (OBs) is an independent prognostic factor for multiple sclerosis (MS), but the difficulties in the standardization of the test and the interlaboratory variation in reporting have contributed to its limited use in the diagnosis of the disease. Standard nephelometric assays to measure free light chains (FLC) levels have been recently developed and the test may improve the detection of intrathecal B cells activity. Methods. The presence of OBs, kappa and lambda FLC levels, and standard indices of intrathecal inflammation were assessed in 100 consecutive patients, including patients with MS, clinically isolated syndromes (CIS), other inflammatory diseases of the CNS, and other noninflammatory diseases. Results. Both KFLC and LFLC correlated strongly with the presence of OCBs and with all common tests for intrathecal inflammation (p < 0.001 for all comparisons). KFLC and LFLC were significantly different in patients with MS and CIS compared to the other groups (p < 0.001 and p < 0.001, resp.) and had a better diagnostic accuracy than all the other tests (area under the curve 82.3 % for KFLC index and 79.3 % for LFLC index). Conclusion. Nephelometric assays for KFLC in CSF reliably detect intrathecal immunoglobulin synthesis and discriminate MS patients.Entities:
Year: 2016 PMID: 28116160 PMCID: PMC5225376 DOI: 10.1155/2016/2303857
Source DB: PubMed Journal: Mult Scler Int ISSN: 2090-2654
Characteristics of the patient groups.
| All patientsa ( | Subgroupb | |
|---|---|---|
| Group 1: MS | 34 (34) | |
| Group 2: CIS | 22 (22) | |
| Group 3: Other inflammatory diseases | 23 (23) | |
| Dysimmune leukoencephalopathy | 10 (43.5) | |
| Meningitis, encephalitis | 2 (8.6) | |
| Cranial neuritis | 3 (13.0) | |
| Polyneuropathy | 5 (21.7) | |
| Vasculitis | 1 (4.3) | |
| Behcet's disease | 1 (4.3) | |
| Neuromyelitis optica | 1 (4.3) | |
| Group 4: Noninflammatory diseases | 21 (21) | |
| Neurodegenerative diseases | 6 (28.6) | |
| Cerebrovascular diseases | 4 (19.0) | |
| Neoplastic diseases | 3 (14.3) | |
| Metabolic encephalopathy | 6 (28.6) | |
| Migraine | 1 (4.8) | |
| Psychiatric disorders | 1 (4.8) |
aExpressed as number (%) of all patients.
bExpressed as number (%) of the rows' total.
Demographics and standard CSF characteristics of the patient groups.
| Characteristic | MS ( | CIS ( | Other inflammatory diseases ( | Noninflammatory diseases ( |
|
|---|---|---|---|---|---|
| Age, median (IQ range) | 37.4 (27.8–46.3) | 28.5 (24.4–43.0) | 53.0 (46.8–64.7) | 46.9 (41.8–62.9) | <0.001 |
| Gender | |||||
| Females, number (%) | 21 (61.8) | 17 (77.3) | 12 (52.2) | 15 (71.4) | ns |
| Males, number (%) | 13 (38.2) | 5 (22.7) | 11 (47.8) | 6 (28.6) | |
| CSF-restricted oligoclonal bands | |||||
| Negative, number (%) | 7 (20.6) | 9 (41.0) | 19 (82.6) | 19 (90.5) | <0.001 |
| Positive, number (%) | 27 (79.4) | 13 (59.0) | 4 (17.4) | 2 (9.5) | |
| Link index, median (IQ range) | 0.6 (0.6–0.8) | 0.6 (0.4–0.7) | 0.5 (0.4–0.5) | 0.5 (0.5–0.6) | <0.001 |
| Tourtellotte index, median (IQ range) | 1.7 (−2.2–5.2) | −1.7 (−4.5–1.1) | −3.0 (−3.8–0.7) | −1.9 (−2.8–0.9) | <0.001 |
| Reiber IgG, median (IQ range) | −0.1 (−0.5–0.7) | −0.4 (−1.1–0.0) | −1.0 (−1.9–0.5) | −1.0 (−1.7–0.7) | <0.001 |
| Qalb, median (IQ range) | 5.1 (4.1–6.2) | 4.2 (3.4–5.2) | 7.0 (5.0–9.9) | 7.1 (5.2–9.8) | <0.001 |
Diagnostic accuracy of free light chain (a) and CSF standard indices (b) in multiple sclerosis (MS) and clinically isolated syndrome suggestive of MS diagnosis.
| Markers | Cut-off point | Sensitivity | Specificity | Positive LR | Negative LR |
|---|---|---|---|---|---|
| KFLC (mg/l) in CSF | 4.1 | 66.1 | 77.3 | 2.9 | 0.4 |
| KFLC index | 2.4 | 89.3 | 77.3 | 3.9 | 0.1 |
| LFLC (mg/l) in CSF | 4.3 | 55.4 | 72.7 | 2.0 | 0.6 |
| LFLC index | 3.0 | 82.1 | 75.0 | 3.3 | 0.2 |
| Link index | 0.6 | 53.6 | 93.2 | 7.9 | 0.5 |
| Tourtellotte index | −0.9 | 60.7 | 75.0 | 2.4 | 0.5 |
| Reiber IgG | −0.6 | 71.4 | 79.5 | 3.5 | 0.4 |
| Qalb index | 5.8 | 76.8 | 65.9 | 2.3 | 0.4 |
KFLC, kappa free light chain; LFLC, lambda free light chain; LR, likelihood ratio.
Comparison of free light chains levels in CSF and free light chain indices in different patient groups.
| Characteristic | MS | CIS | Other inflammatory diseases | Noninflammatory diseases |
|
|---|---|---|---|---|---|
| KFLC (mg/l) in CSF, median (IQ range) | 9.1 (3.2–19.0) | 7.3 (1.4–15.2) | 2.3 (1.1–3.4) | 1.3 (1.1–4.0) | 0.002 |
| KFLC index, median (IQ range) | 22.4 (11.4–34.9) | 17.4 (3.7–34.8) | 1.9 (1.3–2.4) | 1.8 (1.5–2.2) | <0.001 |
| LFLC (mg/l) in CSF, median (IQ range) | 5.6 (2.2–9.3) | 4.5 (2.3–11.2) | 3.2 (1.1–5.7) | 4.7 (2.1–6.2) | 0.56 |
| LFLC index, median (IQ range) | 7.5 (3.5–12.9) | 5.9 (3.8–16.0) | 2.5 (1.6–2.9) | 2.8 (1.7–4.1) | <0.001 |
KFLC, kappa free light chain; LFLC, lambda free light chain; LR, likelihood ratio.
Figure 1Median values and ranges of KFLC index in different subgroups: multiple sclerosis (MS) subgroup; clinically isolated syndrome (CIS) subgroup; other inflammatory disorders subgroup; noninflammatory disorders subgroup.
Figure 2Receiver operator characteristic (ROC) curves of free light chain (a) and CSF standard indices (b) in multiple sclerosis (MS) and clinically isolated syndrome suggestive of MS diagnosis.
Figure 3KFLC threshold line (at KFLC index 2.43) in half-logarithmic diagram with results of MS, CIS, OIND, and NIND patients (a), OCB negative patients (b), and OCB positive patients (c). CIS: clinically isolated syndrome; MS: multiple sclerosis; OIND: other inflammatory neurological disease; NIND: noninflammatory neurological disease; KFLC: kappa free light chain; OCB: oligoclonal bands.
Figure 4Forest plot of sensitivities for studies using KFLC index to diagnose MS. Summary estimate for sensitivity is computed using the approach described by Reitsma et al.
Figure 5Forest plot of specificities for studies using KFLC index to diagnose MS. Summary estimate for specificity is computed using the approach described by Reitsma et al.
Figure 6SROC curve of the Reitsma model with the summary estimated (circle) and its confidence interval (elliptic).