8,769 research outputs found

    Prognosis of the individual course of disease - steps in developing a decision support tool for Multiple Sclerosis

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    <p>Abstract</p> <p>Background</p> <p>Multiple sclerosis is a chronic disease of uncertain aetiology. Variations in its disease course make it difficult to impossible to accurately determine the prognosis of individual patients. The Sylvia Lawry Centre for Multiple Sclerosis Research (SLCMSR) developed an "online analytical processing (OLAP)" tool that takes advantage of extant clinical trials data and allows one to model the near term future course of this chronic disease for an individual patient.</p> <p>Results</p> <p>For a given patient the most similar patients of the SLCMSR database are intelligently selected by a model-based matching algorithm integrated into an OLAP-tool to enable real time, web-based statistical analyses. The underlying database (last update April 2005) contains 1,059 patients derived from 30 placebo arms of controlled clinical trials. Demographic information on the entire database and the portion selected for comparison are displayed. The result of the statistical comparison is provided as a display of the course of Expanded Disability Status Scale (EDSS) for individuals in the database with regions of probable progression over time, along with their mean relapse rate. Kaplan-Meier curves for time to sustained progression in the EDSS and time to requirement of constant assistance to walk (EDSS 6) are also displayed. The software-application OLAP anticipates the input MS patient's course on the basis of baseline values and the known course of disease for similar patients who have been followed in clinical trials.</p> <p>Conclusion</p> <p>This simulation could be useful for physicians, researchers and other professionals who counsel patients on therapeutic options. The application can be modified for studying the natural history of other chronic diseases, if and when similar datasets on which the OLAP operates exist.</p

    How do people with multiple sclerosis experience prognostic uncertainty and prognosis communication? A qualitative study

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    Background: Disease progression in multiple sclerosis (MS) is highly variable and predicting prognosis is notoriously challenging. Patients’ prognosis beliefs, responses to prognostic uncertainty and experiences of prognosis-related communication with healthcare professionals (HCPs) have received little study. These issues have implications for patients’ psychological adjustment and are important in the context of the recent development of personalised prognosis forecasting tools. This study explored patient perspectives on the experience of prognostic uncertainty, the formation of expectations about personal prognosis and the nature of received and desired prognosis communication. Methods: 15 MS patients participated in in-depth semi-structured interviews which were analysed using inductive thematic analysis. Results: Six themes captured key aspects of the data: Experiencing unsatisfactory communication with HCPs, Appreciating and accepting prognostic uncertainty, Trying to stay present-focused, Forming and editing personal prognosis beliefs, Ambivalence towards forecasting the future, and Prognosis information delivery. MS patients report having minimal communication with HCPs about prognosis. Over time MS patients appear to develop expectations about their disease trajectories, but do so with minimal HCP input. Provision of prognosis information by HCPs seems to run counter to patients’ attempts to remain present-focused. Patients are often ambivalent about prognosis forecasting and consider it emotionally dangerous and of circumscribed usefulness.Conclusions: HCPs must carefully consider whether, when and how to share prognosis information with patients; specific training may be beneficial. Future research should confirm findings about limited HCP-patient communication, distinguish predictors of patients’ attitudes towards prognostication and identify circumstances under which prognostic forecasting benefits patients. <br/

    A novel prognostic score to assess the risk of progression in relapsing-remitting multiple sclerosis patients

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    BACKGROUND: At patient-level, the prognostic value of several features that are known to be associated with an increased risk of converting from relapsing remitting (RR) to secondary phase (SP) multiple sclerosis (MS), remain limited.METHODS: Among 262 RRMS patients followed up for ten years, we assessed the probability of developing the SP course based on clinical and conventional and non-conventional magnetic resonance imaging (MRI) parameters at diagnosis and after two years. We used a machine learning method, the Random Survival Forests, to identify, according to their minimal depth (MD), the most predictive factors associated with the risk of SP conversion, which were then combined to compute the Secondary Progressive Risk Score (SP-RiSc).RESULTS: During the observation period, 69 (26%) patients converted to SPMS. The number of cortical lesions (MD=2.47) and age (MD=3.30) at diagnosis, the global cortical thinning (MD = 1.65), the cerebellar cortical volume loss (MD = 2.15) and the cortical lesion load increase (MD=3.15) over the first two years, exerted the greatest predictive effect. Three patients' risk-groups were identified; in the high-risk group, 85% (46 out of 55) of patients entered the SP phase in 7 median years. The SP-RiSc optimal cut-off estimated was 17.7 showing specificity and sensitivity of 87% and 92% respectively, and overall accuracy of 88%.CONCLUSIONS: The SP-RiSc yielded a high performance in identifying MS patients with high probability to develop SPMS, which can help improve management strategies. These findings are the premise of further larger prospective studies to assess its use in clinical settings

    Retrospective cohort study to devise a treatment decision score predicting adverse 24-month radiological activity in early multiple sclerosis

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    Background: Multiple sclerosis (MS) is a chronic neuroinflammatory disease affecting about 2.8 million people worldwide. Disease course after the most common diagnoses of relapsing-remitting multiple sclerosis (RRMS) and clinically isolated syndrome (CIS) is highly variable and cannot be reliably predicted. This impairs early personalized treatment decisions. Objectives: The main objective of this study was to algorithmically support clinical decision-making regarding the options of early platform medication or no immediate treatment of patients with early RRMS and CIS. Design: Retrospective monocentric cohort study within the Data Integration for Future Medicine (DIFUTURE) Consortium. Methods: Multiple data sources of routine clinical, imaging and laboratory data derived from a large and deeply characterized cohort of patients with MS were integrated to conduct a retrospective study to create and internally validate a treatment decision score [Multiple Sclerosis Treatment Decision Score (MS-TDS)] through model-based random forests (RFs). The MS-TDS predicts the probability of no new or enlarging lesions in cerebral magnetic resonance images (cMRIs) between 6 and 24 months after the first cMRI. Results: Data from 65 predictors collected for 475 patients between 2008 and 2017 were included. No medication and platform medication were administered to 277 (58.3%) and 198 (41.7%) patients. The MS-TDS predicted individual outcomes with a cross-validated area under the receiver operating characteristics curve (AUROC) of 0.624. The respective RF prediction model provides patient-specific MS-TDS and probabilities of treatment success. The latter may increase by 5–20% for half of the patients if the treatment considered superior by the MS-TDS is used. Conclusion: Routine clinical data from multiple sources can be successfully integrated to build prediction models to support treatment decision-making. In this study, the resulting MS-TDS estimates individualized treatment success probabilities that can identify patients who benefit from early platform medication. External validation of the MS-TDS is required, and a prospective study is currently being conducted. In addition, the clinical relevance of the MS-TDS needs to be established

    THE MOTHERHOOD CHOICE: DEVELOPMENT AND EVALUATION OF A DECISION AID FOR WOMEN WITH MULTIPLE SCLEROSIS

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    Multiple sclerosis (MS) is the most common neurological disease affecting young adults. MS affects approximately 1 in 1000 people and, like other autoimmune diseases, women are more likely to be affected than men. The illness typically onsets between the ages of 20 and 40, and hence usually affects women of child-bearing age. The course of the MS is often unclear for years after diagnosis and since most women are diagnosed in their child-bearing years, they often have to make reproductive choices before their prognosis is clear and while the future remains uncertain. For women with MS, starting a family is an individual choice that needs to balance the importance of motherhood for the woman and her partner against the risks that she will be unable to care for the infant or child as a result of increasing disability. In other areas of medicine where finely balanced decisions are required, there has been a recent proliferation of decision aids that aim to inform people of the benefits and risks of opposing courses of action. In addition, decision aids help patients to weigh their values against the risks and benefits to make an informed decision. Despite the existence of over 200 decision aids to help patients consider decisions related to their medical conditions, not one exists that deals with the decision of whether or not to have a family for women with a chronic disability, such as MS. This thesis developed and evaluated a decision aid for women with MS to help them decide whether to start, forego or enlarge their families. The study utilised the criteria set out for the development of decision aids, according to the Cochrane Systematic Review of Patient Decision Aids (O'Connor et al., 2003). The first aim was to determine the proportion of women who are undecided about the motherhood choice and for whom a decision aid may be relevant. Results found that the motherhood choice was relevant to 46% of the women who responded to an initial mail-out. The second study aimed to establish women’s current concerns and thoughts regarding pregnancy and motherhood, and their response to the pilot decision aid. Twenty women participated in qualitative interviews and results supported previous findings that the mother’s health concerns, coping with parenting and societal attitudes are significant concerns when considering this decision. This study further identified concerns from different groups that had a direct impact on the decision to have children, including the experience of parenting, the child’s well-being and the timing and pressure of the decision. The main study was a randomised controlled trial of the decision aid aiming to determine whether the decision aid facilitated decision-making in women with MS. The study confirmed that the decision aid presented a balanced view to women, increased knowledge, reduced decisional conflict, increased decisional self-efficacy and certainty of the decision, and was free from adverse effects on psychopathology. The final component of the study was a 12 month follow-up which aimed to explore the long-term effectiveness of the decision aid and what aspects were valued by the women who received it. It was found that over time, women in the intervention group did maintain their certainty, but women in the control group also became more certain of their choice. At follow-up, the difference in certainty was no longer significant between the two groups. However, women did report that the intervention was useful in (a) providing access to information previously unavailable or difficult to obtain, (b) facilitating communication between women, their partners and health care professionals, (c) aiding them in considering and utilising their networks of support, and (d) preparing them for potential difficulties. In summary, this thesis developed and evaluated a decision aid for women with MS who are considering motherhood. The results showed that many women were undecided and, in the absence of good information on the topic, many women had concerns about pregnancy and parenthood. The decision aid was shown to be effective across a range of measures and free from adverse psychological effects. Hence, this is evidence-based resource can now be recommended for those women with MS who are currently contemplating motherhood

    THE MOTHERHOOD CHOICE: DEVELOPMENT AND EVALUATION OF A DECISION AID FOR WOMEN WITH MULTIPLE SCLEROSIS

    Get PDF
    Multiple sclerosis (MS) is the most common neurological disease affecting young adults. MS affects approximately 1 in 1000 people and, like other autoimmune diseases, women are more likely to be affected than men. The illness typically onsets between the ages of 20 and 40, and hence usually affects women of child-bearing age. The course of the MS is often unclear for years after diagnosis and since most women are diagnosed in their child-bearing years, they often have to make reproductive choices before their prognosis is clear and while the future remains uncertain. For women with MS, starting a family is an individual choice that needs to balance the importance of motherhood for the woman and her partner against the risks that she will be unable to care for the infant or child as a result of increasing disability. In other areas of medicine where finely balanced decisions are required, there has been a recent proliferation of decision aids that aim to inform people of the benefits and risks of opposing courses of action. In addition, decision aids help patients to weigh their values against the risks and benefits to make an informed decision. Despite the existence of over 200 decision aids to help patients consider decisions related to their medical conditions, not one exists that deals with the decision of whether or not to have a family for women with a chronic disability, such as MS. This thesis developed and evaluated a decision aid for women with MS to help them decide whether to start, forego or enlarge their families. The study utilised the criteria set out for the development of decision aids, according to the Cochrane Systematic Review of Patient Decision Aids (O'Connor et al., 2003). The first aim was to determine the proportion of women who are undecided about the motherhood choice and for whom a decision aid may be relevant. Results found that the motherhood choice was relevant to 46% of the women who responded to an initial mail-out. The second study aimed to establish women’s current concerns and thoughts regarding pregnancy and motherhood, and their response to the pilot decision aid. Twenty women participated in qualitative interviews and results supported previous findings that the mother’s health concerns, coping with parenting and societal attitudes are significant concerns when considering this decision. This study further identified concerns from different groups that had a direct impact on the decision to have children, including the experience of parenting, the child’s well-being and the timing and pressure of the decision. The main study was a randomised controlled trial of the decision aid aiming to determine whether the decision aid facilitated decision-making in women with MS. The study confirmed that the decision aid presented a balanced view to women, increased knowledge, reduced decisional conflict, increased decisional self-efficacy and certainty of the decision, and was free from adverse effects on psychopathology. The final component of the study was a 12 month follow-up which aimed to explore the long-term effectiveness of the decision aid and what aspects were valued by the women who received it. It was found that over time, women in the intervention group did maintain their certainty, but women in the control group also became more certain of their choice. At follow-up, the difference in certainty was no longer significant between the two groups. However, women did report that the intervention was useful in (a) providing access to information previously unavailable or difficult to obtain, (b) facilitating communication between women, their partners and health care professionals, (c) aiding them in considering and utilising their networks of support, and (d) preparing them for potential difficulties. In summary, this thesis developed and evaluated a decision aid for women with MS who are considering motherhood. The results showed that many women were undecided and, in the absence of good information on the topic, many women had concerns about pregnancy and parenthood. The decision aid was shown to be effective across a range of measures and free from adverse psychological effects. Hence, this is evidence-based resource can now be recommended for those women with MS who are currently contemplating motherhood

    Computational classifiers for predicting the short-term course of Multiple sclerosis

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    The aim of this study was to assess the diagnostic accuracy (sensitivity and specificity) of clinical, imaging and motor evoked potentials (MEP) for predicting the short-term prognosis of multiple sclerosis (MS). METHODS: We obtained clinical data, MRI and MEP from a prospective cohort of 51 patients and 20 matched controls followed for two years. Clinical end-points recorded were: 1) expanded disability status scale (EDSS), 2) disability progression, and 3) new relapses. We constructed computational classifiers (Bayesian, random decision-trees, simple logistic-linear regression-and neural networks) and calculated their accuracy by means of a 10-fold cross-validation method. We also validated our findings with a second cohort of 96 MS patients from a second center. RESULTS: We found that disability at baseline, grey matter volume and MEP were the variables that better correlated with clinical end-points, although their diagnostic accuracy was low. However, classifiers combining the most informative variables, namely baseline disability (EDSS), MRI lesion load and central motor conduction time (CMCT), were much more accurate in predicting future disability. Using the most informative variables (especially EDSS and CMCT) we developed a neural network (NNet) that attained a good performance for predicting the EDSS change. The predictive ability of the neural network was validated in an independent cohort obtaining similar accuracy (80%) for predicting the change in the EDSS two years later. CONCLUSIONS: The usefulness of clinical variables for predicting the course of MS on an individual basis is limited, despite being associated with the disease course. By training a NNet with the most informative variables we achieved a good accuracy for predicting short-term disability

    Model for Prediction of Progression in Multiple Sclerosis

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    Multiple sclerosis is an idiopathic inflammatory disease of the central nervous system and the second most common cause of disability in young adults. Choosing an effective treatment is crucial to preventing disability. However, response to treatment varies greatly between patients. Because of this, accurate and timely detection of individual response to treatment is an essential requisite of efficient personalised multiple sclerosis therapy. Nowadays, there is a lack of comprehensive predictive models of response to individual treatment.This paper arises from the clinical need to improve this situation. To achieve it, all patient's information was used to evaluate the effectiveness of demographic, clinical and paraclinical variables of individual response to fourteen disease-modifying therapies in MSBase, an international cohort. A personalized prediction model to three stages of disease, as a support tool in clinical decision making for each MS patient, was developed applying machine learning and Big Data techniques. These techniques were also used to reduce the data set and define a minimum set of characteristics for each patient. Best predictors for the response to treatment were identified to refine the predictive model. Fourteen relevant variables were selected. A web application was implemented to be used to support the specialist neurologist in real time. This tool provides a prediction of progression in EDSS from the last relapse of an individual patient, and a report for the medical expert

    Development of a complex intervention to support the initiation of advance care planning by general practitioners in patients at risk of deteriorating or dying: a phase 0-1 study

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    Background: Most patients with life-limiting illnesses are treated and cared for over a long period of time in primary care and guidelines suggest that ACP discussions should be initiated in primary care. However, a practical model to implement ACP in general practice is lacking. Therefore, the objective of this study is to develop an intervention to support the initiation of ACP in general practice. Methods: We conducted a Phase 0-I study according to the Medical Research Council (MRC) Framework. Phase 0 consisted of a systematic literature review about the barriers and facilitators for GPs to engage in ACP, focus groups with GPs were held about their experiences, attitudes and concerns regarding initiating ACP in general practice and a review of ACP interventions to identify potential components for the development of our intervention. In Phase 1, we developed a complex intervention to support the initiation of ACP in general practice in patients at risk of deteriorating or dying, based on the results of Phase 0. The complex intervention and its components were reviewed and refined by two expert panels. Results: Phase 0 resulted in the identification of the factors inhibiting or enabling GPs' initiation of ACP and important components underpinning existing ACP interventions. Based on these findings, an intervention was developed in Phase 1 consisting of: (1) a training for GPs in initiating and conducting ACP discussions, (2) a register of patients eligible for ACP discussions, (3) an educational booklet on ACP for patients to prepare the ACP discussions that includes general information on ACP, a section on the role of GPs in the process of ACP and a prompt list, (4) a conversation guide to support GPs in the ACP discussions and (5) a structured documentation template to record the outcomes of discussions. Conclusion: Taking into account the barriers and facilitators for GPs to initiate ACP as well as the key factors underpinning successful ACP intervention in other health care settings, a complex intervention for general practice was developed, after gaining feedback from two expert panels. The feasibility and acceptability of the intervention will subsequently be tested in a Phase II study

    Peripheral blood biomarkers in multiple sclerosis.

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    Multiple sclerosis is the most common autoimmune disorder affecting the central nervous system. The heteroge-neity of pathophysiological processes in MS contributes to the highly variable course of the disease and unpre-dictable response to therapies. The major focus of the research on MS is the identification of biomarkers inbiologicalfluids, such as cerebrospinalfluid or blood, to guide patient management reliably. Because of the diffi-culties in obtaining spinalfluid samples and the necessity for lumbar puncture to make a diagnosis has reduced,the research of blood-based biomarkers may provide increasingly important tools for clinical practice. However,currently there are no clearly established MS blood-based biomarkers. The availability of reliable biomarkerscould radically alter the management of MS at critical phases of the disease spectrum, allowing for interventionstrategies that may prevent evolution to long-term neurological disability. This article provides an overview ofthis researchfield and focuses on recent advances in blood-based biomarker researc
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