Patient-reported outcomes in multiple sclerosis: a prospective registry cohort study

Registries have the potential to tackle some of the current limitations in determining the long-term impact of multiple sclerosis. Online assessments using patient-reported outcomes can streamline follow-up enabling large-scale, long-term, cost-effective, home-based, and patient-focused data collection. However, registry data are sparsely sampled and the sensitivity of patient-reported outcomes relative to clinician-reported scales is unknown, making it hard to fully leverage their unique scope and scale to derive insights. This retrospective and prospective cohort study over 11 years involved 15 976 patients with multiple sclerosis from the United Kingdom Multiples Sclerosis Register. Primary outcomes were changes in two patient-reported outcomes: Multiple Sclerosis Impact Scale motor component, and Multiple Sclerosis Walking Scale. First, we investigated their validity in measuring the impact of physical disability in multiple sclerosis, by looking at their sensitivity to disease subtype and duration. We grouped the available records (91 351 for Multiple Sclerosis Impact Scale motor and 68 092 for Multiple Sclerosis Walking Scale) by these two factors, and statistically compared the resulting groups using a novel approach based on Monte Carlo permutation analysis that was designed to cope with the intrinsic sparsity of registry data. Next, we used the patient-reported outcomes to draw novel insights into the developmental time course of subtypes; in particular, the period preceding the transition from relapsing to progressive forms. We report a robust main effect of disease subtype on the patient-reported outcomes and interactions of disease subtype with duration (all P < 0.0001). Specifically, patient-reported outcomes worsen with disease duration for all subtypes (all P < 0.0001) apart from benign multiple sclerosis (Multiple Sclerosis Impact Scale motor: P = 0.796; Multiple Sclerosis Walking Scale: P = 0.983). Furthermore, the patient-reported outcomes of each subtype are statistically different from those of the other subtypes at all time bins (Multiple Sclerosis Impact Scale motor: all P < 0.05; Multiple Sclerosis Walking Scale: all P < 0.01) except when comparing relapsing-remitting multiple sclerosis with benign multiple sclerosis and primary progressive multiple sclerosis with secondary progressive multiple sclerosis. Notably, there were statistically significant differences between relapsing-remitting and progressive subtypes at disease onset. Critically, the patient-reported outcomes are sensitive to future transitions to progressive subtypes, with individuals who transition presenting with higher patient-reported outcomes in their relapsing-remitting phase compared to individuals who don’t transition since onset (all P < 0.0001). Patient-reported outcomes capture different patterns of physical worsening over disease length and across subtypes; therefore, they are a valid tool to measure the physical impact of multiple sclerosis over the long-term and cost-effectively. Furthermore, more advanced physical disability manifests years before clinical detection of progressive subtypes, adding evidence to the presence of a multiple sclerosis prodrome

The impact of smoking cessation on multiple sclerosis disease progression

The negative impact of smoking in MS is well established, however, there is much less evidence as to whether smoking cessation is beneficial to progression in MS. Adults with MS registered on the United Kingdom MS Register (2011-2020) formed this retrospective and prospective cohort study. Primary outcomes were changes in 3 patient reported outcomes (PROs): normalised MS Physical Impact Scale (MSIS-29-Phys), normalised MS Walking Scale (MSWS-12) and the Hospital Anxiety and Depression Scale (HADS-Anxiety and HADS-Depression). Time to event outcomes were clinically significant increases in the PROs. 7983 participants were included, 4130 (51.7%) of these had ever smoked; of whom 1315 (16.5%) were current smokers and 2815/4130 (68.2%) were former smokers. For all PROs, current smokers at the time of completing their first questionnaire had higher PRO scores indicating higher disability compared to those who had never smoked (∼10 points difference in MSIS-29-Phys and MSWS-12; 1.5-1.8 point for HADS-anxiety and HADS-depression). There was no improvement in PRO scores with increasing time since quitting in former smokers. 923 participants formed the prospective parallel group, which demonstrated that MSIS-29-phy 5.03, [3.71, 6.34], MSWS-12 5.28, [3.62, 6.94] and HADS-depression 0.71, [0.47, 0.96] worsened over a period of 4 years, whereas HADS-anxiety remained stable. Smoking status was significant at year 4; current smokers had higher MSIS-29-Phys and HADS-Anxiety scores (3.05 [0.22, 5.88], 1.14 [0.52,1.76]) while former smokers had a lower MSIS-29 score of -2.91[-5.03, -0.79]. 4642 participants comprised the time to event analysis. Still smoking was associated with a shorter time to worsening event in all PROs (MSIS-29-Phys: n = 4436, p = 0.0013; MSWS-12: n = 3902, p = 0.0061; HADS-anxiety: n = 4511, p = 0.0017; HADS-depression: n = 4511, p &amp;lt; 0.0001). Worsening in motor disability (MSIS-29-Phys and MSWS-12) was independent of baseline HADS-anxiety and HADS-depression scores. There was no statistically significant difference in the rate of worsening between never and former smokers. When smokers quit, there is a slowing in the rate of motor disability deterioration so that it matches the rate of motor decline in those who have never smoked. This suggests that smoking cessation is beneficial for people with MS

Association of Epstein-Barr virus antibody titers with a human IL-10 promoter polymorphism in Japanese women

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A Polymorphism in the HLA-DPB1 Gene Is Associated with Susceptibility to Multiple Sclerosis

We conducted an association study across the human leukocyte antigen (HLA) complex to identify loci associated with multiple sclerosis (MS). Comparing 1927 SNPs in 1618 MS cases and 3413 controls of European ancestry, we identified seven SNPs that were independently associated with MS conditional on the others (each ). All associations were significant in an independent replication cohort of 2212 cases and 2251 controls () and were highly significant in the combined dataset (). The associated SNPs included proxies for HLA-DRB1*15:01 and HLA-DRB1*03:01, and SNPs in moderate linkage disequilibrium (LD) with HLA-A*02:01, HLA-DRB1*04:01 and HLA-DRB1*13:03. We also found a strong association with rs9277535 in the class II gene HLA-DPB1 (discovery set , replication set , combined ). HLA-DPB1 is located centromeric of the more commonly typed class II genes HLA-DRB1, -DQA1 and -DQB1. It is separated from these genes by a recombination hotspot, and the association is not affected by conditioning on genotypes at DRB1, DQA1 and DQB1. Hence rs9277535 represents an independent MS-susceptibility locus of genome-wide significance. It is correlated with the HLA-DPB1*03:01 allele, which has been implicated previously in MS in smaller studies. Further genotyping in large datasets is required to confirm and resolve this association

Cancer Biomarker Discovery: The Entropic Hallmark

Background: It is a commonly accepted belief that cancer cells modify their transcriptional state during the progression of the disease. We propose that the progression of cancer cells towards malignant phenotypes can be efficiently tracked using high-throughput technologies that follow the gradual changes observed in the gene expression profiles by employing Shannon's mathematical theory of communication. Methods based on Information Theory can then quantify the divergence of cancer cells' transcriptional profiles from those of normally appearing cells of the originating tissues. The relevance of the proposed methods can be evaluated using microarray datasets available in the public domain but the method is in principle applicable to other high-throughput methods. Methodology/Principal Findings: Using melanoma and prostate cancer datasets we illustrate how it is possible to employ Shannon Entropy and the Jensen-Shannon divergence to trace the transcriptional changes progression of the disease. We establish how the variations of these two measures correlate with established biomarkers of cancer progression. The Information Theory measures allow us to identify novel biomarkers for both progressive and relatively more sudden transcriptional changes leading to malignant phenotypes. At the same time, the methodology was able to validate a large number of genes and processes that seem to be implicated in the progression of melanoma and prostate cancer. Conclusions/Significance: We thus present a quantitative guiding rule, a new unifying hallmark of cancer: the cancer cell's transcriptome changes lead to measurable observed transitions of Normalized Shannon Entropy values (as measured by high-throughput technologies). At the same time, tumor cells increment their divergence from the normal tissue profile increasing their disorder via creation of states that we might not directly measure. This unifying hallmark allows, via the the Jensen-Shannon divergence, to identify the arrow of time of the processes from the gene expression profiles, and helps to map the phenotypical and molecular hallmarks of specific cancer subtypes. The deep mathematical basis of the approach allows us to suggest that this principle is, hopefully, of general applicability for other diseases

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified