Impact of delayed diagnosis and treatment in clinically isolated syndrome and multiple sclerosis

Medication adherence to disease-modifying therapies among a cohort of Jordanian patients with relapsing-remitting multiple sclerosis: a multicentre cross-sectional study

OBJECTIVES

To evaluate medication adherence to oral and parenteral disease-modifying therapies (DMTs) and to explore factors associated with medication non-adherence in patients with multiple sclerosis (MS).

METHODS

A cross-sectional multicentre study was conducted among patients with MS. Patients who attended outpatient clinics of neurology departments from three major referral centres were invited to participate in the study. Medication adherence was measured using the Multiple Sclerosis Treatment Adherence Questionnaire.

KEY FINDINGS

A total of 319 patients with MS on DMT were included in the final analyses, their average age was 35 years and more than two-thirds (72.1%) of them were women. The adherent group comprised 46.7% of patients. The results of association analyses showed that factors that were associated with adherence level were female gender (P = 0.034), non-smoking/x-smoking (P = 0.007), school education (P = 0.019), unemployment (P = 0.006), history of previous DMT (P = 0.020), longer previous treatment duration (P = 0.008), and type of current DMT (P = 0.020). Among the non-adherent patients, there were significant differences between oral and parenteral DMT users in the importance of barriers to adherence (P < 0.001). Additionally, the degree of treatment satisfaction was higher in oral users than in parenteral users (P < 0.001).

CONCLUSIONS

The adherence level was quite low. Gender, smoking status, education, employment status, history of previous DMT, previous treatment duration and type of current DMT were associated with medication non-adherence in our patients with MS. These factors should be considered when evaluating medication adherence, and the modifiable factors may represent potential targets for interventions to improve pharmaceutical care planning in patients with MS.

MRI of the Entire Spinal Cord-Worth the While or Waste of Time? A Retrospective Study of 74 Patients with Multiple Sclerosis

Spinal cord lesions are included in the diagnosis of multiple sclerosis (MS), yet spinal cord MRI is not mandatory for diagnosis according to the latest revisions of the McDonald Criteria. We investigated the distribution of spinal cord lesions in MS patients and examined how it influences the fulfillment of the 2017 McDonald Criteria. Seventy-four patients with relapsing-remitting MS were examined with brain and entire spinal cord MRI. Sixty-five patients received contrast. The number and anatomical location of MS lesions were assessed along with the Expanded Disability Status Scale (EDSS). A Chi-square test, Fischer’s exact test, and one-sided McNemar’s test were used to test distributions. MS lesions were distributed throughout the spinal cord. Diagnosis of dissemination in space (DIS) was increased from 58/74 (78.4%) to 67/74 (90.5%) when adding cervical spinal cord MRI to brain MRI alone (p = 0.004). Diagnosis of dissemination in time (DIT) was not significantly increased when adding entire spinal cord MRI to brain MRI alone (p = 0.04). There was no association between the number of spinal cord lesions and the EDSS score (p = 0.71). MS lesions are present throughout the spinal cord, and spinal cord MRI may play an important role in the diagnosis and follow-up of MS patients.

Early-Onset Alcohol Dependence and Multiple Sclerosis: Diagnostic Challenges

Multiple sclerosis (MS) is an inflammatory demyelinating disorder characterized by the progressive disruption of the myelin sheath around the nerve fibres. The early initiation of disease-modifying treatments is crucial for preventing disease progression and neurological damage. Unfortunately, a diagnostic delay of several years is not uncommon, particularly in the presence of physical and mental comorbidities. Among psychiatric comorbidities, the role of alcohol misuse is still under debate. In this paper, we discuss a case of early-onset alcohol dependence and its possible role in delaying the initiation of a specific therapy for MS. The differential diagnosis between idiopathic and secondary neurodegenerative disorders is often challenging. When dealing with patients reporting an early-onset substance abuse (likely to present organic damage), clinicians may be prone to formulate a diagnosis of secondary neuropathy, particularly when facing non-specific symptoms. This case report highlights the need for in-depth medical investigations (including imaging) in the presence of neurological signs suggesting a damage of the central nervous system, prompting a differential diagnosis between idiopathic and secondary neurodegenerative conditions. Indeed, a timely diagnosis is crucial for the initiation of specific therapies positively affecting the outcome.

Assessment of delayed diagnosis and treatment in multiple sclerosis patients during 1990-2016

Multiple sclerosis (MS) is the most common inflammatory demyelinating disease in the central nervous system. It is one of the major causes of disability in young adults. Early diagnosis and treatment of this disease could decrease later disability and additional costs. In this cross-sectional analytical study, a total of 351 patients were selected from among the multiple sclerosis patients that went to MS clinic or neurologic clinic in 1990-2016. Data were collected and analysed by SPSS v16. This study was conducted on 82.6% females and 17.4% males. Family history of MS was positive in 12.8% of cases. Mean time of onset of symptoms till first medical visit was 3.25 months. Mean time from first medical visit to diagnosis was 14.98 months. Mean time from onset of symptoms till diagnosis was 18.01 months and the mean time from onset of symptoms till initiation of treatment was 18.73 months. Also, 29.3% of cases had delay in first medical visit and 42.2% of cases had delay in diagnosis of MS more than 6 weeks from first medical visit. Overall, delay in first medical visit and diagnosis of MS has decreased over the years. However, there is still delay in diagnosis of MS. Factors associated with delay are low education, male gender, living in rural areas, primary progressive MS, age at MS diagnosis and first clinical symptoms.

The impact of the face-to-face consultation on decisional conflict in complex decision-making in multiple sclerosis: A pilot study

Background

The role of face-to-face consultations in medicine is increasingly being challenged. Disease activity, national guidelines, life goals e.g. pregnancy, multiple therapies and side effects need to be considered on starting disease modifying treatments (DMTs) in people with multiple sclerosis (pwMS).

Objectives

We studied the impact of a face-to-face consultation on decision making, using decisional conflict (DC) as the primary outcome.

Methods

Prospective cohort study of 73 pwMS attending clinics who were making decisions about DMTs followed for one year. Prerequisites and consultation features were measured with the SURE scale for DC used as the primary outcome at baseline and at one year.

Results

The patient activation measure (PAM) was the only driver prior to the consultation associated with DC (p = 0.02) showing those less engaged were more likely to have DC. Overall, 51/73 (70%) of people made their treatment decision or reinforced a former decision during the consultation. We found making a treatment decision between the original consultation and the follow-up was associated with resolving DC (p = 0.008).

Conclusions

Patient engagement impacts DC but the HCP delivering the optimal Shared Decision Making (SDM) approach is additionally significant in reducing DC. In complex decisions there is a clear role for face-to-face consultations in current practice.

Management of central nervous system demyelinating diseases during the coronavirus disease 2019 pandemic: a practical approach

BACKGROUND

The novel coronavirus disease 2019 (COVID-19) pandemic poses a potential threat to patients with autoimmune disorders, including multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). Such patients are usually treated with immunomodulatory or immunosuppressive agents, which may tamper with the organism's normal response to infections. Currently, no consensus has been reached on how to manage MS and NMOSD patients during the pandemic.

OBJECTIVE

To discuss strategies to manage those patients.

METHODS

We focus on how to 1) reduce COVID-19 infection risk, such as social distancing, telemedicine, and wider interval between laboratory testing/imaging; 2) manage relapses, such as avoiding treatment of mild relapse and using oral steroids; 3) manage disease-modifying therapies, such as preference for drugs associated with lower infection risk (interferons, glatiramer, teriflunomide, and natalizumab) and extended-interval dosing of natalizumab, when safe; 4) individualize the chosen MS induction-therapy (anti-CD20 monoclonal antibodies, alemtuzumab, and cladribine); 5) manage NMOSD preventive therapies, including initial therapy selection and current treatment maintenance; 6) manage MS/NMOSD patients infected with COVID-19.

CONCLUSIONS

In the future, real-world case series of MS/NMOSD patients infected with COVID-19 will help us define the best management strategies. For the time being, we rely on expert experience and guidance.

Initiating disease-modifying treatments in multiple sclerosis: Measuring the decision process using decisional conflict and decisional regret scales

Introduction

Initiating disease-modifying treatments (DMTs) in multiple sclerosis (MS) is a major decision for people with (pw)MS but little is known about how the decision is perceived by the individual.

Objectives

The aim of the study was to determine if decisional conflict (DC) and decisional regret reflect different stages of the decision-making process when initiating DMTs.

Methods

This was a cross-sectional study of three cohorts of pwMS (n = 254), a 'MS conference attendees', 'on treatment' and an 'offered treatment' cohort. Questionnaires assessing DC, decisional regret and control preference were performed.

Results

Forty-four per cent (113/254) of pwMS were dissatisfied with their treatment status and 53% (135/254) had DC. DC (p = 0.013) and decisional regret (p = 0.027) increase in treatment-naïve pwMS and also in those 'offered treatment' dissatisfied with their treatment status (p < 0.0001), whilst those 'on treatment' have low Decisional Regret Scale (DRS) score (p = 0.0005). DC and DRS were only correlated with treatment status in those on treatment and not in treatment-naïve patients. F (58/135) pwMS satisfied with treatment had DC. DC (n = 236, adjusted R ² 0.137, p = 0.000) and DRS (n = 235, adjusted R ² 0.232, p = 0.000) were increased by dissatisfaction with treatment, lower potency treatment, being from the 'MS conference attendees' cohort and reliance on the doctor's decision, with DC additionally associated with being employed.

Conclusions

DC and decisional regret vary in populations at different stages of initiating DMTs and are impacted by non-treatment issues.

Follow-Up of Emergency Department MRI Scans Suggesting New Diagnosis of CNS Demyelination

OBJECTIVE

The literature has shown that new cases of multiple sclerosis (MS) can be missed in the emergency department (ED), causing unnecessary delays for patients. In 2012, an MRI scanner was introduced into the ED of our institution. This study examines the potential value of the radiologists' MRI reports for patients with previously undiagnosed MS who presented to the ED.

MATERIALS AND METHODS

In this retrospective study, electronic medical records were reviewed for patients without a prior diagnosis of a demyelinating disorder, who underwent imaging on the ED's MRI scanner between March 1, 2014, and March 1, 2016, and for whom the radiologist reported a possible demyelinating disorder.

RESULTS

Patient encounters of 61 women and 31 men (mean age, 41.2 years) met the inclusion criteria. In 48 of 92 (52.2%) cases where the radiology report suggested a demyelinating diagnosis, the patient was also given such a diagnosis as the final outcome. Where a demyelinating disorder was placed as the only, first, second, or third (or later) differential diagnosis, the final diagnosis was concordant with demyelination in 84.3% (43/51), 37.5% (3/8), 18.2% (2/11), and 0% (0/22) of cases, respectively (p < 0.01).

CONCLUSION

Radiologist-suggested demyelinating disease as the top differential diagnosis after MRI showed a high concordance rate with demyelinating disease being the final diagnosis. Scans in the ED for neurologic deficits can lead to early guidance for a diagnosis of demyelination to be made. Downstream effects may include reduced admission rates, avoidance of unnecessary use of other procedures, and early commencement of disease-modifying therapy.

Early recognition of multiple sclerosis using natural language processing of the electronic health record

BACKGROUND

Diagnostic accuracy might be improved by algorithms that searched patients' clinical notes in the electronic health record (EHR) for signs and symptoms of diseases such as multiple sclerosis (MS). The focus this study was to determine if patients with MS could be identified from their clinical notes prior to the initial recognition by their healthcare providers.

METHODS

An MS-enriched cohort of patients with well-established MS (n = 165) and controls (n = 545), was generated from the adult outpatient clinic. A random sample cohort was generated from randomly selected patients (n = 2289) from the same adult outpatient clinic, some of whom had MS (n = 16). Patients' notes were extracted from the data warehouse and signs and symptoms mapped to UMLS terms using MedLEE. Approximately 1000 MS-related terms occurred significantly more frequently in MS patients' notes than controls'. Synonymous terms were manually clustered into 50 buckets and used as classification features. Patients were classified as MS or not using Naïve Bayes classification.

RESULTS

Classification of patients known to have MS using notes of the MS-enriched cohort entered after the initial ICD9[MS] code yielded an ROC AUC, sensitivity, and specificity of 0.90 [0.87-0.93], 0.75[0.66-0.82], and 0.91 [0.87-0.93], respectively. Similar classification accuracy was achieved using the notes from the random sample cohort. Classification of patients not yet known to have MS using notes of the MS-enriched cohort entered before the initial ICD9[MS] documentation identified 40% [23-59%] as having MS. Manual review of the EHR of 45 patients of the random sample cohort classified as having MS but lacking an ICD9[MS] code identified four who might have unrecognized MS.

CONCLUSIONS

Diagnostic accuracy might be improved by mining patients' clinical notes for signs and symptoms of specific diseases using NLP. Using this approach, we identified patients with MS early in the course of their disease which could potentially shorten the time to diagnosis. This approach could also be applied to other diseases often missed by primary care providers such as cancer. Whether implementing computerized diagnostic support ultimately shortens the time from earliest symptoms to formal recognition of the disease remains to be seen.

Nanoscale Sensor Technologies for Disease Detection via Volatolomics

The detection of many diseases is missed because of delayed diagnoses or the low efficacy of some treatments. This emphasizes the urgent need for inexpensive and minimally invasive technologies that would allow efficient early detection, stratifying the population for personalized therapy, and improving the efficacy of rapid bed-side assessment of treatment. An emerging approach that has a high potential to fulfill these needs is based on so-called "volatolomics", namely, chemical processes involving profiles of highly volatile organic compounds (VOCs) emitted from body fluids, including breath, skin, urine and blood. This article presents a didactic review of some of the main advances related to the use of nanomaterial-based solid-state and flexible sensors, and related artificially intelligent sensing arrays for the detection and monitoring of disease with volatolomics. The article attempts to review the technological gaps and confounding factors related to VOC testing. Different ways to choose nanomaterial-based sensors are discussed, while considering the profiles of targeted volatile markers and possible limitations of applying the sensing approach. Perspectives for taking volatolomics to a new level in the field of diagnostics are highlighted.

Hybrid volatolomics and disease detection

This Review presents a concise, but not exhaustive, didactic overview of some of the main concepts and approaches related to "volatolomics"-an emerging frontier for fast, risk-free, and potentially inexpensive diagnostics. It attempts to review the source and characteristics of volatolomics through the so-called volatile organic compounds (VOCs) emanating from cells and their microenvironment. It also reviews the existence of VOCs in several bodily fluids, including the cellular environment, blood, breath, skin, feces, urine, and saliva. Finally, the usefulness of volatolomics for diagnosis from a single bodily fluid, as well as ways to improve these diagnostic aspects by "hybrid" approaches that combine VOC profiles collected from two or more bodily fluids, will be discussed. The perspectives of this approach in developing the field of diagnostics to a new level are highlighted.