Dataset Information

Leveraging real-world data to investigate multiple sclerosis disease behavior, prognosis, and treatment.

ABSTRACT: Randomized controlled clinical trials and real-world observational studies provide complementary information but with different validity. Some clinical questions (disease behavior, prognosis, validation of outcome measures, comparative effectiveness, and long-term safety of therapies) are often better addressed using real-world data reflecting larger, more representative populations. Integration of disease history, clinician-reported outcomes, performance tests, and patient-reported outcome measures during patient encounters; imaging and biospecimen analyses; and data from wearable devices increase dataset utility. However, observational studies utilizing these data are susceptible to many potential sources of bias, creating barriers to acceptance by regulatory agencies and the medical community. Therefore, data standardization and validation within datasets, harmonization across datasets, and application of appropriate analysis methods are important considerations. We review approaches to improve the scope, quality, and analyses of real-world data to advance understanding of multiple sclerosis and its treatment, as an example of opportunities to better support patient care and research.

SUBMITTER: Cohen JA

PROVIDER: S-EPMC6950891 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Leveraging real-world data to investigate multiple sclerosis disease behavior, prognosis, and treatment.

Cohen Jeffrey A JA Trojano Maria M Mowry Ellen M EM Uitdehaag Bernard Mj BM Reingold Stephen C SC Marrie Ruth Ann RA

Multiple sclerosis (Houndmills, Basingstoke, England) 20191128 1

Randomized controlled clinical trials and real-world observational studies provide complementary information but with different validity. Some clinical questions (disease behavior, prognosis, validation of outcome measures, comparative effectiveness, and long-term safety of therapies) are often better addressed using real-world data reflecting larger, more representative populations. Integration of disease history, clinician-reported outcomes, performance tests, and patient-reported outcome meas ...[more]

PMID: 31778094

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Project description:BACKGROUND:Internet search data on health-related terms can reflect people's concerns about their health status in near real time, and hence serve as a supplementary metric of disease characteristics. However, studies using internet search data to monitor and predict chronic diseases at a geographically finer state-level scale are sparse. OBJECTIVE:The aim of this study was to explore the associations of internet search volumes for lung cancer with published cancer incidence and mortality data in the United States. METHODS:We used Google relative search volumes, which represent the search frequency of specific search terms in Google. We performed cross-sectional analyses of the original and disease metrics at both national and state levels. A smoothed time series of relative search volumes was created to eliminate the effects of irregular changes on the search frequencies and obtain the long-term trends of search volumes for lung cancer at both the national and state levels. We also performed analyses of decomposed Google relative search volume data and disease metrics at the national and state levels. RESULTS:The monthly trends of lung cancer-related internet hits were consistent with the trends of reported lung cancer rates at the national level. Ohio had the highest frequency for lung cancer-related search terms. At the state level, the relative search volume was significantly correlated with lung cancer incidence rates in 42 states, with correlation coefficients ranging from 0.58 in Virginia to 0.94 in Oregon. Relative search volume was also significantly correlated with mortality in 47 states, with correlation coefficients ranging from 0.58 in Oklahoma to 0.94 in North Carolina. Both the incidence and mortality rates of lung cancer were correlated with decomposed relative search volumes in all states excluding Vermont. CONCLUSIONS:Internet search behaviors could reflect public awareness of lung cancer. Research on internet search behaviors could be a novel and timely approach to monitor and estimate the prevalence, incidence, and mortality rates of a broader range of cancers and even more health issues.

Project description:Background: Multiple Sclerosis Partners Advancing Technology and Health Solutions (MS PATHS) is the first example of a learning health system in multiple sclerosis (MS). This paper describes the initial implementation of MS PATHS and initial patient characteristics. Methods: MS PATHS is an ongoing initiative conducted in 10 healthcare institutions in three countries, each contributing standardized information acquired during routine care. Institutional participation required the following: active MS patient census of ≥500, at least one Siemens 3T magnetic resonance imaging scanner, and willingness to standardize patient assessments, share standardized data for research, and offer universal enrolment to capture a representative sample. The eligible participants have diagnosis of MS, including clinically isolated syndrome, and consent for sharing pseudonymized data for research. MS PATHS incorporates a self-administered patient assessment tool, the Multiple Sclerosis Performance Test, to collect a structured history, patient-reported outcomes, and quantitative testing of cognition, vision, dexterity, and walking speed. Brain magnetic resonance imaging is acquired using standardized acquisition sequences on Siemens 3T scanners. Quantitative measures of brain volume and lesion load are obtained. Using a separate consent, the patients contribute DNA, RNA, and serum for future research. The clinicians retain complete autonomy in using MS PATHS data in patient care. A shared governance model ensures transparent data and sample access for research. Results: As of August 5, 2019, MS PATHS enrolment included participants (n = 16,568) with broad ranges of disease subtypes, duration, and severity. Overall, 14,643 (88.4%) participants contributed data at one or more time points. The average patient contributed 15.6 person-months of follow-up (95% CI: 15.5-15.8); overall, 166,158 person-months of follow-up have been accumulated. Those with relapsing-remitting MS demonstrated more demographic heterogeneity than the participants in six randomized phase 3 MS treatment trials. Across sites, a significant variation was observed in the follow-up frequency and the patterns of disease-modifying therapy use. Conclusions: Through digital health technology, it is feasible to collect standardized, quantitative, and interpretable data from each patient in busy MS practices, facilitating the merger of research and patient care. This approach holds promise for data-driven clinical decisions and accelerated systematic learning.

Project description:Alemtuzumab is a humanized monoclonal antibody approved for the treatment of relapsing-remitting multiple sclerosis (RRMS), given as two annual courses on five consecutive days at baseline and on three consecutive days 12 months later. Here we provide an update on the long-term efficacy and safety of alemtuzumab in RRMS, including real-world experience, and advances in our understanding of its mechanism of action. Recent data from the phase II/III extension study have demonstrated that alemtuzumab reduces relapse rates, disability worsening, and the rate of brain volume loss over the long term, with many patients achieving no evidence of disease activity. In high proportions of patients, preexisting disability remained stable or improved. Alemtuzumab is associated with a consistent safety profile over the long term, with no new safety signals emerging and the overall annual incidence of reported adverse events decreasing after the first year on treatment. Acyclovir prophylaxis reduces herpetic infections, and monitoring has been shown to mitigate the risk of autoimmune adverse events, allowing early detection and overall effective management. Data from clinical practice and ongoing observational studies are providing additional information on the real-world use of alemtuzumab. Recent evidence on the mechanism of action of alemtuzumab indicates that in addition to its previously known effects of inducing depletion and repopulation of T and B lymphocytes, it also results in a relative increase of cells with memory and regulatory phenotypes and a decrease in cells with a proinflammatory signature, and may further promote an immunoregulatory environment through an impact on other innate immune cells (e.g. dendritic cells) that play a role in MS. These effects may allow preservation of innate immunity and immunosurveillance. Together, these lines of evidence help explain the durable clinical efficacy of alemtuzumab, in the absence of continuous treatment, in patients with RRMS.

Project description:Background: Natalizumab (NTZ) and fingolimod (FTY) are second-line disease modifying treatments (DMTs) approved for Relapsing - Remitting Multiple Sclerosis (RRMS). Few studies are available on a direct comparison between NTZ and FTY, based on post-marketing experience, with conflicting results and reporting relatively short follow-up period. Aim: We hereby report real-world experience of a MS Center with respect to NTZ vs. FTY comparison in terms of efficacy and safety, referencing long-term follow-up. Methods: We used retrospective data for all patients that received 2nd-line treatment NTZ (since May 2007) or FTY (since September 2011). Primary endpoints were, among others, annual EDSS score (mean change from baseline), time to disability worsening or improvement, Annualized Relapse Rate (ARR) after 12 and 24 months and upon total treatment duration, time to first relapse and time to radiological progression. Results: A total of 138 unmatched patients, 84 treated with NTZ and 54 treated with FTY were included. Following Propensity Score (PS) matching, 31 patients in each group were retained. Mean follow-up period for NTZ- and FTY-treated patients was 4.43 ± 0.29 and 3.59 ± 0.32 years (p = 0.057), respectively. In the matched analysis, time to disability improvement and time to disability worsening was comparable between groups. A higher proportion of patients remained free of relapse under NTZ, compared to FTY (Log Rank test p = 0.021, HR: 0.25, 95% CI: 0.08-0.8), as well as free of MRI activity (Log Rank test p = 0.006, HR: 0.26, 95% CI: 0.08-0.6). Treatment discontinuation due to MRI activity was significantly higher for FTY-treated patients compared to NTZ (Log Rank test p = 0.019, HR: 0.12, 95% CI: 0.05-0.76). Conclusion: Our results indicate toward NTZ superiority with respect to relapse and MRI activity outcomes. The fact that NTZ-treated patients may achieve long-standing clinical and radiological remission points toward the need for long follow-up data.

Dataset Information

Leveraging real-world data to investigate multiple sclerosis disease behavior, prognosis, and treatment.

Publications

Leveraging real-world data to investigate multiple sclerosis disease behavior, prognosis, and treatment.

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