Prognostic value of cerebrospinal fluid analysis at the time of a first demyelinating event

Prognostic models for predicting clinical disease progression, worsening and activity in people with multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system that affects millions of people worldwide. The disease course varies greatly across individuals and many disease-modifying treatments with different safety and efficacy profiles have been developed recently. Prognostic models evaluated and shown to be valid in different settings have the potential to support people with MS and their physicians during the decision-making process for treatment or disease/life management, allow stratified and more precise interpretation of interventional trials, and provide insights into disease mechanisms. Many researchers have turned to prognostic models to help predict clinical outcomes in people with MS; however, to our knowledge, no widely accepted prognostic model for MS is being used in clinical practice yet.

OBJECTIVES

To identify and summarise multivariable prognostic models, and their validation studies for quantifying the risk of clinical disease progression, worsening, and activity in adults with MS.

SEARCH METHODS

We searched MEDLINE, Embase, and the Cochrane Database of Systematic Reviews from January 1996 until July 2021. We also screened the reference lists of included studies and relevant reviews, and references citing the included studies.

SELECTION CRITERIA

We included all statistically developed multivariable prognostic models aiming to predict clinical disease progression, worsening, and activity, as measured by disability, relapse, conversion to definite MS, conversion to progressive MS, or a composite of these in adult individuals with MS. We also included any studies evaluating the performance of (i.e. validating) these models. There were no restrictions based on language, data source, timing of prognostication, or timing of outcome.

DATA COLLECTION AND ANALYSIS

Pairs of review authors independently screened titles/abstracts and full texts, extracted data using a piloted form based on the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS), assessed risk of bias using the Prediction Model Risk Of Bias Assessment Tool (PROBAST), and assessed reporting deficiencies based on the checklist items in Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD). The characteristics of the included models and their validations are described narratively. We planned to meta-analyse the discrimination and calibration of models with at least three external validations outside the model development study but no model met this criterion. We summarised between-study heterogeneity narratively but again could not perform the planned meta-regression.

MAIN RESULTS

We included 57 studies, from which we identified 75 model developments, 15 external validations corresponding to only 12 (16%) of the models, and six author-reported validations. Only two models were externally validated multiple times. None of the identified external validations were performed by researchers independent of those that developed the model. The outcome was related to disease progression in 39 (41%), relapses in 8 (8%), conversion to definite MS in 17 (18%), and conversion to progressive MS in 27 (28%) of the 96 models or validations. The disease and treatment-related characteristics of included participants, and definitions of considered predictors and outcome, were highly heterogeneous amongst the studies. Based on the publication year, we observed an increase in the percent of participants on treatment, diversification of the diagnostic criteria used, an increase in consideration of biomarkers or treatment as predictors, and increased use of machine learning methods over time. Usability and reproducibility All identified models contained at least one predictor requiring the skills of a medical specialist for measurement or assessment. Most of the models (44; 59%) contained predictors that require specialist equipment likely to be absent from primary care or standard hospital settings. Over half (52%) of the developed models were not accompanied by model coefficients, tools, or instructions, which hinders their application, independent validation or reproduction. The data used in model developments were made publicly available or reported to be available on request only in a few studies (two and six, respectively). Risk of bias We rated all but one of the model developments or validations as having high overall risk of bias. The main reason for this was the statistical methods used for the development or evaluation of prognostic models; we rated all but two of the included model developments or validations as having high risk of bias in the analysis domain. None of the model developments that were externally validated or these models' external validations had low risk of bias. There were concerns related to applicability of the models to our research question in over one-third (38%) of the models or their validations. Reporting deficiencies Reporting was poor overall and there was no observable increase in the quality of reporting over time. The items that were unclearly reported or not reported at all for most of the included models or validations were related to sample size justification, blinding of outcome assessors, details of the full model or how to obtain predictions from it, amount of missing data, and treatments received by the participants. Reporting of preferred model performance measures of discrimination and calibration was suboptimal.

AUTHORS' CONCLUSIONS

The current evidence is not sufficient for recommending the use of any of the published prognostic prediction models for people with MS in clinical routine today due to lack of independent external validations. The MS prognostic research community should adhere to the current reporting and methodological guidelines and conduct many more state-of-the-art external validation studies for the existing or newly developed models.

Cerebrospinal Fluid IgM and Oligoclonal IgG Bands in Multiple Sclerosis: A Meta-Analysis of Prevalence and Prognosis

The presence of intrathecal IgM synthesis (ITMS) has been associated with an aggressive multiple sclerosis (MS) clinical course. In the present systematic review, we aimed at assessing the prevalence of ITMS among different MS phenotypes. Moreover, we aimed at quantifying the risk of a second relapse in ITMS positive and oligoclonal IgG bands (OCGBs)-positive patients. We selected clinical studies reporting the ITMS prevalence assessed as oligoclonal IgM Bands (OCMBs), lipid-specific OCMBs (LS-OCMBs), and/or as an intrathecal IgM production > 0% (IgMLoc, Reiber formula). The overall prevalence of ITMS was higher in relapsing-remitting (RR) than clinically isolated syndrome (CIS) patients (40.1% versus 23.8%, p < 0.00001), while was in line with that detected in primary progressive MS (PPMS, 26.7%). Almost all patients (98%) with ITMS had also OCGBs. The risk of having a second relapse was higher in OCGBs positive patients (HR = 2.18, p = 0.007) but much higher in ITMS positive patients (HR = 3.62, p = 0.0005). This study revealed that the prevalence of ITMS is higher in RRMS patients. It suggests that the risk of having a second relapse, previously ascribed to OCGBs, may, to a certain extent, be related to the presence of intrathecal IgM.

A multi-biomarker follow-up study of patients with multiple sclerosis

OBJECTIVES

This study aimed to examine the levels of the macrophage marker sCD163 and other biomarkers at the time of diagnosis of patients with either clinically isolated syndrome (CIS) or relapsing-remitting multiple sclerosis (RRMS), and assess relation to clinical indicators of prognosis, disease activity (DA), and changes in the levels of these biomarkers at follow-up.

MATERIALS AND METHODS

The clinical status and MRI were reevaluated in 56 patients more than 1 year after diagnosis with a median follow-up time of 2 years. Levels of biomarkers in serum and cerebrospinal fluid (CSF) samples were evaluated by enzyme-linked immunosorbent assays.

RESULTS

There was no significant difference in time to DA between patients with CIS and RRMS. A high sCD163 ratio (>0.07) was significantly (P = 0.04) associated with time to DA in the untreated patient group. In 21 patients reevaluated with serum and CSF samples, the sCD163 ratio levels decreased from 0.068 to 0.054 (P = 0.026) in the CIS/RRMS-treated group. The CSF CXCL13, CXCL13 ratio, CSF neurofilament light polypeptide and osteopontin levels also decreased significantly in the CIS/RRMS-treated group.

CONCLUSIONS

The levels of all biomarkers changed concurrently with MS treatment. The sCD163 ratio was identified as a potential novel marker for time to DA.

Increased prevalence of lymphoid tissue inducer cells in the cerebrospinal fluid of patients with early multiple sclerosis

BACKGROUND

Inflammatory cytokines produced by cells of the immune system are believed to play a central role in the pathogenesis of multiple sclerosis (MS). Innate lymphoid cells (ILCs) have been shown to produce and secrete a wide range of the cytokines involved in MS pathogenesis; however, a possible implication of ILCs in MS development and disease progression has not been investigated.

OBJECTIVE

With this study, we aimed to clarify a potential role of ILCs in the early stages of MS.

METHODS AND RESULTS

Using flow cytometry, we analysed the prevalence and phenotype of ILCs in the cerebrospinal fluid (CSF) of patients experiencing their first or second demyelinating event. We found a substantial increase in both frequency and number of ILCs, in particular the LTi subset, as compared to healthy controls. We also found an association between CSF pleocytosis and an increased frequency of LTi cells in the CSF, suggesting a favoured recruitment of blood derived LTi cells.

CONCLUSION

Our data suggests a role for ILCs, and in particular the LTi subset, in the early stages of MS. This finding represents an important contribution to the understanding of early inflammation in MS, and adds new knowledge beneficial for future MS therapies.

Permeability of the blood-brain barrier predicts conversion from optic neuritis to multiple sclerosis

Optic neuritis is an acute inflammatory condition that is highly associated with multiple sclerosis. Currently, the best predictor of future development of multiple sclerosis is the number of T2 lesions visualized by magnetic resonance imaging. Previous research has found abnormalities in the permeability of the blood-brain barrier in normal-appearing white matter of patients with multiple sclerosis and here, for the first time, we present a study on the capability of blood-brain barrier permeability in predicting conversion from optic neuritis to multiple sclerosis and a direct comparison with cerebrospinal fluid markers of inflammation, cellular trafficking and blood-brain barrier breakdown. To this end, we applied dynamic contrast-enhanced magnetic resonance imaging at 3 T to measure blood-brain barrier permeability in 39 patients with monosymptomatic optic neuritis, all referred for imaging as part of the diagnostic work-up at time of diagnosis. Eighteen healthy controls were included for comparison. Patients had magnetic resonance imaging and lumbar puncture performed within 4 weeks of onset of optic neuritis. Information on multiple sclerosis conversion was acquired from hospital records 2 years after optic neuritis onset. Logistic regression analysis showed that baseline permeability in normal-appearing white matter significantly improved prediction of multiple sclerosis conversion (according to the 2010 revised McDonald diagnostic criteria) within 2 years compared to T2 lesion count alone. There was no correlation between permeability and T2 lesion count. An increase in permeability in normal-appearing white matter of 0.1 ml/100 g/min increased the risk of multiple sclerosis 8.5 times whereas having more than nine T2 lesions increased the risk 52.6 times. Receiver operating characteristic curve analysis of permeability in normal-appearing white matter gave a cut-off of 0.13 ml/100 g/min, which predicted conversion to multiple sclerosis with a sensitivity of 88% and specificity of 72%. We found a significant correlation between permeability and the leucocyte count in cerebrospinal fluid as well as levels of CXCL10 and MMP9 in the cerebrospinal fluid. These findings suggest that blood-brain barrier permeability, as measured by magnetic resonance imaging, may provide novel pathological information as a marker of neuroinflammation related to multiple sclerosis, to some extent reflecting cellular permeability of the blood-brain barrier, whereas T2 lesion count may more reflect the length of the subclinical pre-relapse phase.See Naismith and Cross (doi:10.1093/brain/awv196) for a scientific commentary on this article.

Cerebrospinal fluid CXCL13 in clinically isolated syndrome patients: Association with oligoclonal IgM bands and prediction of Multiple Sclerosis diagnosis

Cerebrospinal fluid (CSF) CXCL13 was shown to correlate with markers of intrathecal inflammation and CSF oligoclonal IgM bands (IgMOB) have been associated with a more severe Multiple Sclerosis (MS) course. We correlated CSF CXCL13 levels with clinical, MRI and CSF parameters, including CSF IgMOB, in 110 Clinically Isolated Syndrome (CIS) patients. CSF CXCL13 levels correlated with CSF cell count, total protein, IgG Index and with the presence of CSF IgGOB and IgMOB. CSF CXCL13 levels ≥15.4 pg/ml showed a good positive predictive value and specificity for a MS diagnosis and for a clinical relapse within one year from onset.

Cerebrospinal fluid levels of chitinase 3-like 1 and neurofilament light chain predict multiple sclerosis development and disability after optic neuritis

BACKGROUND

Cerebrospinal fluid (CSF) biomarkers have been suggested to predict multiple sclerosis (MS) after clinically isolated syndromes, but studies investigating long-term prognosis are needed.

OBJECTIVE

To assess the predictive ability of CSF biomarkers with regard to MS development and long-term disability after optic neuritis (ON).

METHODS

Eighty-six patients with ON as a first demyelinating event were included retrospectively. Magnetic resonance imaging (MRI), CSF leukocytes, immunoglobulin G index and oligoclonal bands were registered. CSF levels of chitinase-3-like-1, osteopontin, neurofilament light-chain, myelin basic protein, CCL2, CXCL10, CXCL13 and matrix metalloproteinase-9 were measured by enzyme-linked immunosorbent assay. Patients were followed up after 13.6 (range 9.6-19.4) years and 81.4% were examined, including Expanded Disability Status Scale and MS functional composite evaluation. 18.6% were interviewed by phone. Cox regression, multiple regression and Spearman correlation analyses were used.

RESULTS

Forty-six (53.5%) developed clinically definite MS (CDMS) during follow-up. In a multivariate model MRI (p=0.0001), chitinase 3-like 1 (p=0.0033) and age (p=0.0194) combined predicted CDMS best. Neurofilament light-chain predicted long-term disability by the multiple sclerosis severity scale (p=0.0111) and nine-hole-peg-test (p=0.0202). Chitinase-3-like-1 predicted long-term cognitive impairment by the paced auditory serial addition test (p=0.0150).

CONCLUSION

Neurofilament light-chain and chitinase-3-like-1 were significant predictors of long-term physical and cognitive disability. Furthermore, chitinase-3-like-1 predicted CDMS development. Thus, these molecules hold promise as clinically valuable biomarkers after ON as a first demyelinating event.

Cerebrospinal fluid immunoglobulin kappa light chain in clinically isolated syndrome and multiple sclerosis

Background

Oligoclonal bands (OCB) are the most widely used CSF test to support the diagnosis of MS and to predict conversion of clinically isolated syndrome (CIS) to multiple sclerosis (MS). Since OCB tests are based on non-quantitative and difficult to standardise techniques, measurement of immunoglobulin kappa free light chains (KFLC) may represent an easier to use quantitative test.

Methods

KFLC were measured in CSF and serum of 211 patients using ELISA. These include patients without any inflammatory central nervous system reaction (NIND, n = 77), MS (n = 20), viral CNS infections (V-CNS-I, n = 10), neuroborreliosis (NB, n = 17) and other bacterial CNS infections (B-CNS-I, n = 10). Furthermore a cohort of 77 patients with CIS, including 39 patients that remained CIS over follow-up of two years (CIS-CIS) and 38 patients that developed MS over the same follow-up time (CIS-MS).

Results

CSF-serum ratio of KFLC (Q KFLC) was elevated in all patients with MS, 86.8% of patients with CIS-MS and 61.5% of patients with CIS-CIS. It was significantly elevated in CIS with presence of OCB (p<0.001). Q KFLC significantly correlated with other CSF variables such as CSF leukocyte count (p<0.001, R = 0.46), CSF CXCL13 levels (p<0.001, R = 0.64) and also intrathecal IgG synthesis (p<0.001, R = 0.74) as determined by nephelometry and quotient diagram. OCB were detected in 66.7% of CIS-CIS and in 92.1% of CIS-MS.

Conclusions

Although the measurement of CSF KFLC is a rapid and quantitative easy to standardize tool, it is almost equal but not superior to OCB with regard to diagnostic sensitivity and specificity in patients with early MS.

Kappa free light chains: diagnostic and prognostic relevance in MS and CIS

Background

Quantification of kappa free light chains (KFLC) in cerebrospinal fluid shows high diagnostic sensitivity in multiple sclerosis and clinically isolated syndrome patients. However, a clearly defined threshold value is still missing and a possible prognostic value of the KFLC levels in these patients remains undefined.

Methods

Results of KFLC quantification in 420 controls were used to set an upper limit of normal KFLC concentration in CSF under different blood-CSF-barrier conditions. Additionally, KFLC values of MS and CIS patients were assessed and results were evaluated with reference to the patients corresponding disease courses.

Results

The calculated upper limit of normal KFLC-concentration covers 98% of these control patients. Using this cut-off, plasma cell activity in CSF can be detected in 97% of MS patients and in 97% of CIS patients. However, there is no evidence that the extent of KFLC elevation provides prognostic value in MS and CIS patients in this study.

Conclusion

KFLC determination should become a first line screen in the diagnostic algorithms of MS and CIS. The extent of elevation of intrathecal KFLC has no prognostic value on the disease course in MS and CIS patients.

Intrathecal oligoclonal IgG synthesis in multiple sclerosis

The diagnosis of multiple sclerosis is based on dissemination in time and space. Before 2010 lack of evidence for dissemination in space could be substituted by a paraclinical test, cerebrospinal fluid (CSF) oligoclonal bands (OCBs). The present meta-analysis (13,467 patients) shows that the diagnostic specificity of OCB drops from 94% to 61% if inflammatory etiologies are considered. Importantly, this was not caused by poor laboratory practice. This review on CSF OCB further illustrates the conceptional problem of substituting dissemination in space with a biomarker. The potential prognostic value of intrathecal OCB will need to be tested prospectively.

Neurofilaments as biomarkers in multiple sclerosis

Neurodegeneration is the correlate of disease progression in multiple sclerosis (MS) and thus biological biomarkers that sensitively reflect this process are much needed. Neurofilament protein subunits are potential cerebrospinal fluid (CSF) biomarkers for disease progression in MS. We argue that the neurofilament light subunit can reflect acute axonal damage mediated by inflammatory mechanisms and can imply prognostic value for conversion from clinically isolated syndrome (CIS) to definite MS. The neurofilament heavy subunit may rather reflect chronic irreversible damage and has prognostic value for disease progression or disability. The neurofilament intermediate subunit has not yet been studied. Recent studies showing higher neurofilament light or heavy subunit levels to be altered upon treatment regimes indicate their potential clinical value in monitoring treatment or side effects. Future studies should be aimed at the optimisation, standardisation and interlaboratory implementation of the assays and address the predictive value of these biomarkers.