A Step Ahead of MS : Predicting disease course after a clinically isolated syndrome

Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system (CNS), affecting genetically susceptible individuals, influenced by environmental factors. Because the course of MS is highly heterogeneous, prediction factors at time of the first attack (CIS) are needed. The need for reliable prog¬nostic factors is even more urgent since there is a growing number of disease modifying therapies (DMT) available for MS. Early initiation of these therapies is favourable for the prevention of future relapses and disability. The studies described in this thesis are executed within two prospective cohorts of adult and paediatric patients followed after a first attack of demyelination. We aimed to find prognostic factors (clinical and biomarkers) for the disease course after a first attack of demyelination both in children and adults

Validation of Six Nomograms for Predicting Non-sentinel Lymph Node Metastases in a Dutch Breast Cancer Population

Background: The usefulness of axillary lymph node dissection (ALND) in patients with positive sentinel nodes (SN) is still an ongoing debate. Several nomograms have been developed for predicting non-sentinel lymph node metastases (NSLNM). We validated six nomograms using data from 10 years of breast cancer surgery in our hospital. Methods: We retrospectively analyzed all patients with a proven breast malignancy and a SN procedure between 2001 and 2011 in our hospital. Results: Data from 1084 patients were reviewed; 260 (24 %) had a positive SN. No patients with isolated tumor cells, 6 patients (8 %) with micrometastases, and 65 patients (41 %) with macrometastases had additional axillary NSLNM. In 2 patients (3 %) with micrometastases, the ALND influenced postoperative treatment. In the group of patients with macrometastases tumor size >2 cm, extranodal growth and having no negative SNs were predictors of NSLNM. The revised MD Anderson Cancer Center and Helsinki nomograms performed the best, with an area under the curve value of 0.78. Conclusions: ALND could probably be safely omitted in most patients with micrometastases but is still indicated in patients with macrometastases, especially in patients with tumor size >2 cm, extranodal growth, and no negative SNs. The revised MD Anderson Cancer Center and Helsinki nomograms were the most predictive in our patient group

Smoking at time of CIS increases the risk of clinically definite multiple sclerosis

Background: Cigarette smoking is a modifiable risk factor that influences the disease course of patients with multiple sclerosis (MS). However, in patients with a clinically isolated syndrome (CIS), there are conflicting results about the association between smoking and the risk of a subsequent MS diagnosis. The aim of this study was to determine the risk of clinically definite MS (CDMS) in smoking and non-smoking patients at time of a first demyelinating event. Methods: Two hundred and fifty patients, aged 18–50 years, were included in our prospective CIS cohort. At time of the first neurological symptoms, patients completed a questionnaire about smoking habits. Cox regression analyses were performed to calculate univariate and multivariate hazard ratios for CDMS diagnosis in smoking and non-smoking CIS patients. Results: One hundred and fourteen (46%) CIS patients were diagnosed with CDMS during a mean follow-up of 58 months. In total, 79 (32%) patients smoked at time of CIS. Sixty-seven % of the smoking CIS patients were diagnosed with CDMS during follow-up compared to 36% of the non-smoking CIS patients (p < 0.001). Smoking at time of CIS was an independent predictor for CDMS diagnosis (HR 2.3; p = 0.002). Non-smoking CIS patients who had a history of smoking did not have a higher risk for CDMS than those who had never smoked. Conclusions: Smoking at time of CIS was an independent risk factor for a future CDMS diagnosis. This is an additional argument to quit smoking at time of the first attack of suspected MS

Fatigue after a first attack of suspected multiple sclerosis

Background: Fatigue is reported by more than 75% of multiple sclerosis (MS) patients. In an earlier study, we showed that fatigue is not only a common symptom in patien

Integrative network modeling reveals mechanisms underlying T cell exhaustion.

Failure to clear antigens causes CD8+ T cells to become increasingly hypo-functional, a state known as exhaustion. We combined manually extracted information from published literature with gene expression data from diverse model systems to infer a set of molecular regulatory interactions that underpin exhaustion. Topological analysis and simulation modeling of the network suggests CD8+ T cells undergo 2 major transitions in state following stimulation. The time cells spend in the earlier pro-memory/proliferative (PP) state is a fixed and inherent property of the network structure. Transition to the second state is necessary for exhaustion. Combining insights from network topology analysis and simulation modeling, we predict the extent to which each node in our network drives cells towards an exhausted state. We demonstrate the utility of our approach by experimentally testing the prediction that drug-induced interference with EZH2 function increases the proportion of pro-memory/proliferative cells in the early days post-activation

T-cell activation marker sCD27 is associated with clinically definite multiple sclerosis in childhood-acquired demyelinating syndromes

Background: Cerebrospinal fluid (CSF) levels of T-cell activation marker soluble CD27 (sCD27) are associated with subsequent disease activity after a first attack of suspected MS in adults. The predictive value for disease course in children with acquired demyelinating syndromes (ADS) is unknown. Objectives: To assess the predictive value of sCD27 levels for clinically definite multiple sclerosis (CDMS) diagnosis in childhood ADS. Methods: Children <18 years with a first demyelinating event were prospectively included and followed. Soluble CD27 was determined in CSF using an enzyme-linked immunosorbent assay (ELISA). Cox regression analyses were used to calculate hazard ratios (HRs) for CDMS. Results: A total of 94 ADS children were included (ADS with encephalopathy (ADS+) n = 33 and ADS without encephalopathy (ADS–) n = 61). Of the 61 ADS– children, 21 (48%) were diagnosed with CDMS during follow-up. At baseline, sCD27 levels were higher in patients with a future CDMS diagnosis (n = 29) than in monophasic ADS+ (n = 30), monophasic ADS– (n = 28) and relapsing non-MS patients (n = 7; p < 0.001). In ADS– patients, sCD27 was associated with CDMS (HR = 1.8 per 100 U/mL increase in sCD27 levels, p = 0.031), after adjustments for age, oligoclonal bands and the presence of dissemination in space on baseline magnetic resonance imaging (MRI). Conclusion: CSF sCD27 levels at first attack of demyelination were associated with CDMS diagnosis in children. This makes sCD27 a potential clinically relevant quantitative marker when performing routine CSF diagnostics