Association of oral disease-modifying agents and their adherence trajectories with annual relapses in multiple sclerosis.

BACKGROUND: Real-world effectiveness can vary across oral disease-modifying agents (DMAs) and their adherence trajectories in patients with multiple sclerosis (MS). However, previous studies have not considered longitudinal adherence patterns while evaluating oral DMAs. OBJECTIVES: This study aimed to evaluate the association of oral DMAs and their adherence trajectories with annualized relapse rate (ARR) in patients with MS. METHODS: This retrospective observational cohort study based on the 2015-2019 MarketScan Commercial Claims and Encounters Database involved continuous enrolled adults (18-64 years) with ≥1 MS diagnosis (ICD-9/10-CM:340/G35) and ≥ 1 oral DMA prescription. Patients were grouped into incident fingolimod (FIN), teriflunomide (TER), and dimethyl fumarate (DMF) users based on the index DMA with a one-year washout period. Annual DMA adherence trajectories based on the monthly Proportion of Days Covered (PDC) one year after treatment initiation were identified using Group-Based Trajectory Modeling (GBTM). The validated claims-based ARR was evaluated during the one-year follow-up period using generalized boosted model-based inverse probability treatment weights with negative binomial regression model. RESULTS: The study cohort consisted of 994 MS patients who initiated with FIN (23.0%), TER (22.3%), and DMF (54.7%) during the study period. GBTM grouped eligible patients into three adherence trajectories: complete adherers (59.2%), slow decliners (23.8%), and rapid decliners (17.0%). The proportion of complete adherers varied across the oral DMAs (FIN: 67.1%, TER: 55.4%, and DMF: 57.4%). The negative binomial regression modeling revealed that, while there was no difference in ARR across the three DMAs, rapid decliners (adjusted incidence rate ratio[aIRR]: 1.6, 95% CI: 1.1-2.4) had a higher rate of relapses compared to completely adherent patients. The type of oral DMAs did not moderate the relationship between ARR and the adherence trajectory groups. CONCLUSIONS: Adherence trajectories classified as rapid decliners were associated with a higher ARR than complete adherers after adjusting for their type of oral DMAs. Longitudinal medication adherence patterns are critical in reducing relapse rates in MS.

The PICOTS-ComTeC Framework for Defining Digital Health Interventions: An ISPOR Special Interest Group Report.

OBJECTIVES: Digital health definitions are abundant, but often lack clarity and precision. We aimed to develop a minimum information framework to define patient-facing digital health interventions (DHIs) for outcomes research. METHODS: Definitions of digital-health-related terms (DHTs) were systematically reviewed, followed by a content analysis using frameworks, including PICOTS (population, intervention, comparator, outcome, timing, and setting), Shannon-Weaver Model of Communication, Agency for Healthcare Research and Quality Measures, and the World Health Organization's Classification of Digital Health Interventions. Subsequently, we conducted an online Delphi study to establish a minimum information framework, which was pilot tested by 5 experts using hypothetical examples. RESULTS: After screening 2610 records and 545 full-text articles, we identified 101 unique definitions of 67 secondary DHTs in 76 articles, resulting in 95 different patterns of concepts among the definitions. World Health Organization system (84.5%), message (75.7%), intervention (58.3%), and technology (52.4%) were the most frequently covered concepts. For the Delphi survey, we invited 47 members of the ISPOR Digital Health Special Interest Group, 18 of whom became the Delphi panel. The first, second, and third survey rounds were completed by 18, 11, and 10 respondents, respectively. After consolidating results, the PICOTS-ComTeC acronym emerged, involving 9 domains (population, intervention, comparator, outcome, timing, setting, communication, technology, and context) and 32 optional subcategories. CONCLUSIONS: Patient-facing DHIs can be specified using PICOTS-ComTeC that facilitates identification of appropriate interventions and comparators for a given decision. PICOTS-ComTeC is a flexible and versatile tool, intended to assist authors in designing and reporting primary studies and evidence syntheses, yielding actionable results for clinicians and other decision makers.

Comparative adherence trajectories of oral disease-modifying agents in multiple sclerosis.

STUDY OBJECTIVE: This study compared the adherence trajectories of fingolimod (FIN), teriflunomide (TER), and dimethyl fumarate (DMF) users with multiple sclerosis (MS) as there is limited evidence regarding the comparative adherence patterns of different oral disease-modifying agents (DMAs). DESIGN: A retrospective cohort study DATA SOURCE: 2015-2019 IBM MarketScan Commercial Claims Database. PATIENTS: Adults (≥18 years) with MS (International Classification of Diseases [ICD]-9/10-Clinical Modification [CM]:340/G35) diagnosis and ≥1 DMA prescription. INTERVENTION: Incident FIN-, TER-, or DMF use based on the index DMA with 1 year of washout period. MEASUREMENTS: The DMA adherence trajectories based on the proportion of days covered (PDC) were examined using the Group-Based Trajectory Modeling (GBTM) one year after the treatment initiation. Generalized boosting models (GBM)-based inverse probability treatment weights (IPTW) were incorporated in multinomial logistic regression to assess the comparative adherence trajectories across oral DMAs with FIN group as a reference category. MEASUREMENTS AND MAIN RESULTS: The study cohort consisted of 1913 patients with MS who were initiated with FIN (24.2%, n = 462), TER (24.0%, n = 458), and DMF (51.9%, n = 993) during 2016-2018. The adherence rate (PDC ≥ 0.8) among FIN, TER, and DMF users was found to be 70.8% (n = 327), 59.6% (n = 273), and 61.0% (n = 606), respectively. The GBTM grouped patients into three adherence trajectories: Complete Adherers-59.1%, Slow Decliners-22.6%, and Rapid Discontinuers-18.3%. The multinomial logistic regression model involving GBM-based IPTW revealed that DMF (adjusted odds ratio [aOR]: 2.32, 95% confidence interval [CI]:1.57-3.42) and TER (aOR: 2.50, 95% CI: 1.62-3.88) users had higher odds to be rapid discontinuers relative to FIN users. In addition, TER users were more likely (aOR: 1.50, 95% CI: 1.06-2.13) to be slow decliners compared with FIN users. CONCLUSION: Teriflunomide and DMF were associated with poorer adherence trajectories than FIN. More research is needed to evaluate the clinical implications of these adherence trajectories of oral DMAs to optimize the management of MS.

How Useful Are Digital Health Terms for Outcomes Research? An ISPOR Special Interest Group Report.

OBJECTIVES: This study aimed to review definitions of digital health and understand their relevance for health outcomes research. Four umbrella terms (digital health, electronic health, mobile health, and telehealth/telemedicine) were summarized in this article. METHODS: PubMed/MEDLINE, Embase, Cochrane Library, and EconLit were searched from January 2015 to May 2020 for systematic reviews containing key Medical Subject Headings terms for digital health (n = 38) and synonyms of "definition." Independent pairs of reviewers performed each stage of the review, with reconciliation by a third reviewer if required. A single reviewer consolidated each definition for consistency. We performed text analysis via word clouds and computed document frequency-and inverse corpus frequency scores. RESULTS: The search retrieved 2610 records with 545 articles (20.9%) taken forward for full-text review. Of these, 39.3% (214 of 545) were eligible for data extraction, of which 134 full-text articles were retained for this analysis containing 142 unique definitions of umbrella terms (digital health [n = 4], electronic health [n = 36], mobile health [n = 50], and telehealth/telemedicine [n = 52]). Seminal definitions exist but have increasingly been adapted over time and new definitions were created. Nevertheless, the most characteristic words extracted from the definitions via the text analyses still showed considerable overlap between the 4 umbrella terms. CONCLUSIONS: To focus evidence summaries for outcomes research purposes, umbrella terms should be accompanied by Medical Subject Headings terms reflecting population, intervention, comparator, outcome, timing, and setting. Ultimately a functional classification system is needed to create standardized terminology for digital health interventions denoting the domains of patient-level effects and outcomes.

Cost comparison of adverse event management among breast and ovarian cancer patients treated with poly (ADP-ribose) polymerase inhibitors: analysis based on phase 3 clinical trials.

Background: The economic impact of adverse events (AEs) for poly (ADP-ribose) polymerase inhibitors (PARPis) in ovarian or breast cancer has not been widely evaluated. Objective: Compare PARPi-related AE management costs from a US payer perspective. Methods: The frequency of treatment-related grade 3-4 AEs was obtained from published clinical trials of PARPis for the treatment of advanced ovarian cancer (AOC), platinum-sensitive recurrent ovarian cancer (PSROC), and metastatic breast cancer (MBC). AE management costs per patient (2020 USD) per treatment course were calculated by multiplying the AE unit costs by the frequency of AEs for each arm of each trial. Sensitivity analyses were conducted according to the lower and upper limits of the 95% confidence interval for AE rates and unit costs, respectively. Scenarios were also performed to explore the uncertainty of outcomes. Results: Total AE management costs in AOC were: $3,904, olaparib; $5,595, olaparib plus bevacizumab; and $12,215, niraparib. In PSROC, total costs were: $3,894, olaparib; $6,001, rucaparib; and $11,492, niraparib, and in MBC: $3,574, olaparib; and $9,489, talazoparib. Hematological toxicities were the key drivers of AE management costs for PARPis. Conclusions: The main AEs among PARPis were hematological. Olaparib was associated with lower AE costs compared to other PARPis.

Association of the Healthcare Effectiveness Data and Information Set (HEDIS) Follow-Up Care Measures and Medication Adherence Among Medicaid Insured Children with ADHD.

OBJECTIVES: To assess the association of HEDIS C&M phase follow-up measure with ADHD medication adherence. METHODS: A retrospective study was conducted using Medicaid data (2014-2016) of children initiated with ADHD medication. Patients were categorized as meeting the C&M follow-up measure or not according to the HEDIS specifications. Medication adherence was measured using both Proportion of Days Covered (PDC) & Group-Based Trajectory Modeling (GBTM). The association of medication adherence with HEDIS measure was assessed using Chi-square test. RESULTS: Nearly all (97%) children with PDC≥0.7 and 72% of patients following the late decliner adherence trajectory met the HEDIS C&M follow-up criteria. In contrast, none of the children with PDC<0.7 and only two following rapid and slow decliner trajectories met the criteria. CONCLUSION: ADHD medication adherence, regardless of how it was measured, clearly differentiated children with and without C&M phase follow-up, which essentially questions the implication of HEDIS C&M phase follow-up care measure.

Factors associated with oral fingolimod use over injectable disease- modifying agent use in multiple sclerosis.

Background: Fingolimod is the first approved oral disease-modifying agent (DMA) in 2010 to treat Multiple Sclerosis (MS). There is limited real-world evidence regarding the determinants associated with fingolimod use in the early years. Objective: The objective of this study was to examine the factors associated with fingolimod prescribing in the initial years after the market approval. Methods: A retrospective, longitudinal study was conducted involving adults (≥18 years) with MS from the 2010-2012 IBM MarketScan. Individuals with MS were selected based on ICD-9-CM: 340 and a newly initiated DMA prescription. Based on the index/first DMA prescription, patients were classified as fingolimod or injectable users. All covariates were measured during the six months baseline period prior to the index date. Multivariable logistic regression was performed to determine the predisposing, enabling, and need factors, conceptualized as per the Andersen Behavioral Model (ABM), associated with prescribing of fingolimod versus injectable DMA for MS. Results: The study cohort consisted of 3118 MS patients receiving DMA treatment. Of which, 14.4% of patients with MS initiated treatment with fingolimod within two years after the market entry, while the remaining 85.6% initiated with injectable DMAs. Multivariable regression revealed that the likelihood of prescribing oral DMA increased by 2-3 fold during 2011 and 2012 compared to 2010. Patients with ophthalmic (adjusted odds ratio [aOR]-2.60), heart (aOR-2.21) and urinary diseases (aOR-1.37) were more likely to receive fingolimod. Patients with other neurological disorders (aOR-0.50) were less likely to receive fingolimod than those without neurological disorders. Use of symptomatic medication (for impaired walking (aOR-2.60), bladder dysfunction (aOR-1.54), antispasmodics (aOR-1.48), and neurologist consultation (aOR-1.81) were associated with higher odds of receiving fingolimod. However, patients with non-MS associated emergency visits (aOR-0.64) had lower odds of receiving fingolimod than those without emergency visits. Conclusions: During the initial years after market approval, patients with highly active MS were more likely to receive oral fingolimod than injectable DMAs. More research is needed to understand the determinants of newer oral DMAs.

Marginal Health Care Expenditure Burden Among U.S. Civilian Noninstitutionalized Individuals with Multiple Sclerosis: 2010-2015.

BACKGROUND: Multiple sclerosis (MS) is a chronic neuroinflammatory disorder with significant health care burden. However, little is known about health care expenditures since the introduction of oral agents for MS after 2010. OBJECTIVE: To analyze health care expenditures in individuals with MS using Medical Expenditure Panel Survey (MEPS) data from 2010-2015. METHODS: This retrospective cross-sectional study included adults (≥ 18 years) with MS (Clinical Classification Code 080) and those without MS based on the 2010-2015 full year consolidated MEPS Household Component and Medical Provider Component data files. Descriptive weighted analyses were performed to compare health care expenditures between individuals with MS and without MS. The 2-part model involving probit and generalized linear models was used to estimate the marginal increase in total health care expenditures for MS patients. RESULTS: There were 0.61 million patients (95% CI = 0.50-0.72) diagnosed with MS annually, accounting for a prevalence of 0.25%. The 2-part model revealed that the marginal total health care expenditures in patients diagnosed with MS were $20,103.49 (95% CI = $14,516.24-$25,690.73) more compared with those without MS. Further, the mean adjusted prescription medication expenditures for the MS group were $13,092.16 (95% CI = $9,452.20-$16,732.12) higher than the non-MS group and accounted for 65.12% of total health care expenditures in MS. CONCLUSIONS: MS is an expensive neuroinflammatory disease with a majority of the burden attributable to prescription medications. High prescription expenditure burden can be a barrier to optimal patient care in MS. DISCLOSURES: No funding was received for this study. Hutton reports grants from Adamas, Biogen, EMD Serono, Genzyme, Hoffman-LaRoche, MedImmune, Mallinckrodt, and Novartis and fees from Biogen, Celgene, Genzyme, Genentech, and Novartis, outside the submitted work. Aparasu reports grants from Novartis, Incyte, and Astellas, outside the submitted work. Earla and Thornton have nothing to disclose. Part of the study findings was presented at the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) 2019 National Conference; May 18-22, 2019; New Orleans, LA.

Paraquat - A deadly poison: Report of a case and review.

Paraquat is a bipyridilium herbicide used widely in our country and is a highly toxic compound. A 16-year-old female patient was admitted to the emergency department of our tertiary care hospital in South India with the history of alleged consumption of paraquat poison. Since there is dearth of high quality evidence- based treatment for this poisoning, different treatment modalities have been tried to manage patient's condition. In this case, none of the strategies could work well. Most of the patients reported with paraquat intoxication are from agricultural background; usually such patients cannot afford the treatment expenses. This paper presents a fatal case of acute poisoning with paraquat who succumbed to acute respiratory distress syndrome (ARDS).