Exploring humanistic burden of fatigue in adults with multiple sclerosis: an analysis of US National Health and Wellness Survey data.

BACKGROUND: This retrospective study examined the humanistic burden of fatigue in patients with relapsing-remitting multiple sclerosis (RRMS), compared with adults without MS, using data from the 2017 and 2019 US National Health and Wellness Survey. METHODS: The 5-item Modified Fatigue Impact Scale (MFIS-5) was used to assess level of fatigue (MFIS-5 score <15: low fatigue [LF]; MFIS-5 score ≥15: high fatigue [HF]) in patients with RRMS. Health-related quality of life (HRQoL) measures (Short Form 36-Item Health Survey version 2, Euroqol-5 Dimensions-5 Levels [EQ-5D-5L], Patient Health Questionnaire-9 [PHQ-9], Generalized Anxiety Disorder-7 [GAD-7], Perceived Deficits Questionnaire-5) and treatment-related characteristics were assessed. RESULTS: In total, 498 respondents were identified as RRMS (n=375 RRMS+LF, n=123 RRMS+HF) and compared with 1,494 matched non-MS controls. RRMS+LF and RRMS+HF had significantly lower Short Form 6 Dimensions health utility, Mental and Physical Component Summary, and EQ-5D-5L scores and higher PHQ-9 and GAD-7 scores, compared with matched non-MS controls (all p<0.001); scores were worse for RRMS+HF than RRMS+LF across all measures (all p<0.001). A higher proportion of RRMS+HF reported moderate-to-severe depression and moderate-to-severe anxiety, compared with RRMS+LF and matched non-MS controls (both p<0.001). Fatigue was a significant predictor of poor HRQoL across all measures (all p<0.001). CONCLUSIONS: Patients with RRMS experienced lower HRQoL with higher levels of fatigue, highlighting an unmet need. Results may help to inform physician-patient communication and shared decision-making to address fatigue and its associated impact on patients' HRQoL.

Budget Impact Analysis of Intensification with iGlarLixi Compared to Alternative Treatment Strategies Among Patients with Type 2 Diabetes Mellitus.

INTRODUCTION: The clinical benefits of treating patients with type 2 diabetes mellitus (T2DM) with fixed-ratio combination of insulin iGlar (iGlar) plus lixisenatide (iGlarLixi) were demonstrated in clinical trials and real-world evidence studies; however, its cost impact to healthcare payers is unknown. METHODS: A budget impact model was developed from a United States (US) payer's perspective for a hypothetical healthcare plan of 1 million people over a 1-year time horizon. In scenario analysis, patients with uncontrolled glycated hemoglobin (HbA1c) treated with 60 units or less of daily insulin (insulin cohort) or oral antidiabetic drugs (OADs) only (OAD cohort) were intensified to iGlarLixi/rapid-acting insulin (RAI)/glucagon-like peptide 1 receptor agonists (GLP-1RA) or iGlarLixi/iGlar/GLP-1RA, respectively. Model inputs from real-world data (RWD) included baseline market shares, proportion of patients intensifying to respective treatments, and dosing inputs; unit costs were obtained from published literature. One-way sensitivity analyses assessed the impact of individual parameters. RESULTS: Intensification with iGlarLixi resulted in the lowest incremental per member per month (PMPM) budget impact compared to other intensifying drugs (iGlar, RAI, and GLP-1RA). In the insulin cohort, the incremental PMPM cost for intensification with iGlarLixi ($0.03) was the lowest among intensifying drugs; GLP-1RA ($72.20) and RAI ($4.81). Similarly, the incremental PMPM cost for intensification with iGlarLixi was the lowest ($1.25) in the OAD cohort among intensifying drugs; GLP-1RA ($321.65) and iGlar ($114.82). In scenario analyses, when equal market intensification shares for iGlarLixi and GLP-1RA were explored, the incremental PMPM cost for iGlarLixi ($0.03) remained lower than GLP-1RA ($2.28) and RAI ($10.44) in the insulin cohort. CONCLUSIONS: Intensification with iGlarLixi was associated with lower costs compared to other treatment intensifications, as well as overall budget reductions compared to pre-intensification when considering cost savings attributable to reduction in HbA1c; therefore, its inclusion for the treatment of T2DM would represent a budget saving.

Clinical Benefits of Treating Patients with Type 2 Diabetes Mellitus with iGlarLixi: A Patient-Level Simulation Study.

INTRODUCTION: The fixed-ratio combination of insulin glargine (iGlar) plus lixisenatide (iGlarLixi) has proven efficacious in clinical trials; however, there is limited evidence of its benefits in a variety of real-world patients with type 2 diabetes mellitus (T2DM) who present in routine clinical practice. METHODS: A large integrated claims and EHR database was used to identify two real-world (RW) cohorts (ages ≥ 18) with T2DM who were eligible for treatment with iGlarLixi. At baseline, the first cohort (insulin cohort) received insulin with or without oral antidiabetic drugs (OADs), and the second cohort (OAD-only cohort) received OADs only. A Monte Carlo patient-level simulation was applied to each cohort based on treatment strategies and efficacies from the LixiLan-L and LixiLan-O trials to estimate reductions in glycated hemoglobin A1C (A1C) and the percentage achieving age-based A1C goals (≤ 7% for ages < 65 and ≤ 8% for ages ≥ 65) at 30 weeks. RESULTS: The RW insulin (N = 3797) and OAD-only (N = 17,633) cohorts differed considerably in demographics, age, clinical characteristics, baseline A1C levels, and background OAD therapies compared to the populations in the Lixilan-L and Lixilan-O trials. Regardless of the cohort description, A1C goals were achieved among 52.6% vs. 31.6% (p < 0.001) of patients in the iGlarLixi vs. the iGlar arms in the insulin cohort simulation, while A1C goals were achieved among 59.9% vs. 49.3% and 32.8% (p < 0.001) of patients in the OAD-only cohort simulation in the iGlarLixi vs. the iGlar and lixisenatide arms, respectively. CONCLUSIONS: Irrespective of the treatment regimen at baseline (insulin vs. OAD only), this patient-level simulation demonstrated that a greater proportion of patients achieved their A1C goals with iGlarlixi compared to iGlar or lixisenatide alone. These findings suggest that the benefits of iGlarLixi extend to clinically distinct RW populations.

Clinical and economic outcomes associated with use of anti-arrhythmic drugs versus ablation in atrial fibrillation.

Aim: To evaluate the clinical and economic impact of antiarrhythmic drugs (AADs) compared with ablation both as individual treatments and as combination therapy without/with considering the order of treatment among patients with atrial fibrillation (AFib). Materials & methods: A budget impact model over a one-year time horizon was developed to assess the economic impact of AADs (amiodarone, dofetilide, dronedarone, flecainide, propafenone, sotalol, and as a group) versus ablation across three scenarios: direct comparisons of individual treatments, non-temporal combinations, and temporal combinations. The economic analysis was conducted in accordance with CHEERS guidance as per current model objectives. Results are reported as costs per patient per year (PPPY). The impact of individual parameters was evaluated using one-way sensitivity analysis (OWSA). Results: In direct comparisons, ablation had the highest annual medication/procedure cost ($29,432), followed by dofetilide ($7661), dronedarone ($6451), sotalol ($4552), propafenone ($3044), flecainide ($2563), and amiodarone ($2538). Flecainide had the highest costs for long-term clinical outcomes ($22,964), followed by dofetilide ($17,462), sotalol ($15,030), amiodarone ($12,450), dronedarone ($10,424), propafenone ($7678) and ablation ($9948). In the non-temporal scenario, total costs incurred for AADs (group) + ablation ($17,278) were lower compared with ablation alone ($39,380). In the temporal scenario, AADs (group) before ablation resulted in PPPY cost savings of ($22,858) compared with AADs (group) after ablation ($19,958). Key factors in OWSA were ablation costs, the proportion of patients having reablation, and withdrawal due to adverse events. Conclusion: Utilization of AADs as individual treatment or in combination with ablation demonstrated comparable clinical benefits along with costs savings in patients with AFib.

Body mass index and quality of life in people living with HIV.

With advances in the treatment of HIV, people living with HIV (PLWH) are now expected to have a near-normal life expectancy, but challenges remain in the form of substantially poorer health-related quality of life (HRQoL) than the general population. Being overweight or obese may pose an additional burden in PLWH, but few studies have evaluated the relationship between body mass index (BMI) and HRQoL in PLWH. This study aimed to evaluate and describe the association between HRQoL and BMI among PLWH in the US. Data were obtained from the 2018 and 2019 US National Health and Wellness Survey, an online, self-reported, general population survey. Analyses included 575 PLWH who self-reported a physician diagnosis and prescription use for the treatment of HIV, as well as 1725 propensity score matched non-HIV controls. After adjusting for age, sex, race, and comorbidities, higher BMI was associated with poorer physical (ß = -0.18, p = 0.005) and general (ß = -0.42, p = 0.014) HRQoL among PLWH. Additionally, PLWH reported poorer mental, physical, and general HRQoL than non-HIV controls; these relationships were not moderated by BMI. The potential negative impact of higher BMI on patients' humanistic outcomes should be considered in HIV management, including selection of treatment.

A value-based budget impact model for dronedarone compared with other rhythm control strategies.

Aim: The budgetary consequences of increasing dronedarone utilization for treatment of atrial fibrillation were evaluated from a US payer perspective. Materials & methods: A budget impact model over a 5-year time horizon was developed, including drug-related costs and risks for long-term clinical outcomes (LTCOs). Treatments included antiarrhythmic drugs (AADs; dronedarone, amiodarone, sotalol, propafenone, dofetilide, flecainide), rate control medications, and ablation. Direct comparisons and temporal and non-temporal combination scenarios investigating treatment order were analyzed as costs per patient per month (PPPM). Results: By projected year 5, costs PPPM for dronedarone versus other AADs decreased by $37.69 due to fewer LTCOs, treatment with dronedarone versus ablation or rate control medications + ablation resulted in cost savings ($359.94 and $370.54, respectively), and AADs placed before ablation decreased PPPM costs by $242 compared with ablation before AADs. Conclusion Increased dronedarone utilization demonstrated incremental cost reductions over time.

Assessment of economic burden of fatigue in adults with multiple sclerosis: An analysis of US National Health and Wellness Survey data.

BACKGROUND: Fatigue, a common disabling symptom in multiple sclerosis (MS), is reported by the majority of patients. However, evidence on the economic burden of fatigue in MS by fatigue status is limited. This study aimed to evaluate the economic burden of fatigue, including healthcare resource utilization (HCRU), labor force participation, and Work Productivity and Activity Impairment (WPAI), among adults with relapsing-remitting MS (RRMS) by low fatigue (LF) vs high fatigue (HF) and compared with adults without MS. METHODS: This cross-sectional, retrospective, observational study included pooled data from the 2017 and 2019 US National Health and Wellness Survey. The RRMS sample included respondents aged ≥18 years who reported being diagnosed with MS by a healthcare provider (HCP) and reported having RRMS. Non-MS controls included respondents aged ≥18 years who did not report being diagnosed with MS by an HCP. Fatigue was measured using the Modified Fatigue Impact Scale-5 (MFIS-5). Outcomes included HCRU (HCP visits, emergency department visits, and hospitalizations in the past 12 months), labor force participation (yes vs no), WPAI (absenteeism, presenteeism, total work productivity impairment, and activity impairment), and annualized costs (direct medical, indirect, and total). Respondents with RRMS were propensity-score matched to non-MS controls (ratio 1:3). RRMS respondents were categorized as having LF (MFIS-5<15; RRMS+LF) and HF (MFIS-5≥15; RRMS+HF). Bivariate analysis compared matched non-MS controls, RRMS+LF, and RRMS+HF. Multivariable analyses were conducted among RRMS to evaluate associations between fatigue (continuous variable) and outcomes. RESULTS: Overall, 498 respondents with RRMS (RRMS+LF, n=375; RRMS+HF, n=123) and 1494 matched non-MS controls were included. RRMS+HF and RRMS+LF had more HCRU in the past 12 months than non-MS controls, whereas RRMS+HF had greater HCRU than RRMS+LF (all p<0.05). WPAI was also higher among RRMS+HF and RRMS+LF, compared with non-MS controls, as well as higher in RRMS+HF vs RRMS+LF (all p<0.001). RRMS+HF had significantly higher annualized direct medical costs than RRMS+LF and matched non-MS controls ($19,978 vs $10,656, p=0.007; vs $8,048, p<0.001). Among employed respondents, RRMS+HF and RRMS+LF had higher annualized indirect costs than non-MS controls, with RRMS+HF also having higher annualized indirect costs than RRMS+LF ($23,647 vs $13,738 vs $8,001; all p<0.01); total annualized costs were higher in RRMS+HF and RRMS+LF, compared with non-MS controls, as well as RRMS+HF vs RRMS+LF (all p<0.01). In multivariable models, fatigue was significantly and positively associated with the number of HCP visits in the past 12 months (p=0.002); not participating in the labor force (p<0.001); and absenteeism, presenteeism, total work productivity impairment, and activity impairment (all p<0.001). CONCLUSION: RRMS poses a substantial economic burden on patients and society, and this burden is disproportionately associated with HF.

Assessing Rural Health Coalitions Using the Public Health Logic Model: A Systematic Review.

CONTEXT: Rural communities face unique challenges including fewer healthcare providers and restricted access to nutritious foods, likely leading to poor health outcomes. Community health coalitions are groups of local organizations partnering to address local health needs. Employing such coalitions is one strategy for implementing policy-system-environment changes for improving rural health. However, their success is variable without standardized evaluation. In this review, rural community health coalitions were retrospectively assessed using the W.K. Kellogg Foundation Logic Model. Community health coalition-reported pathways through this model were explored using market basket analysis. EVIDENCE ACQUISITION: During Spring 2018, PubMed, Web of Science, ScienceDirect, CINAHL, and PsycINFO were searched for (coalition) AND (rural) AND (health) AND (effectiveness OR impact OR outcome OR logic model). Full-text, peer-reviewed, English articles meeting PICOS criteria (Population, rural communities; Intervention, presence of a community health coalition; Comparator, the coalition over time; Outcomes, logic model pathways) were reviewed. During Summer and Fall 2018, coalition-reported pathways were categorized according to logic model inputs and resources; internal and external activities; outputs; short-, medium-, and long-term outcomes; and impact. Market basket analysis was conducted during Winter 2018. EVIDENCE SYNTHESIS: The 10 most frequently reported pathway items were partner diversity; organizational structures; implementing pilot studies, programs, and interventions; funding; community engagement and outreach; university partners; holding regular meetings; having working groups and subcommittees; operating under or partnering with a regional research initiative; and conducting a community health and needs assessment. Half of community health coalitions reported 4 or more of the following: funding; partner diversity; university partners; organizational structures; community engagement and outreach; and implementing pilot studies, programs, and interventions. CONCLUSIONS: Many rural community health coalitions reported inputs and capacity building; few impacted health. Recommending common early phase logic model pathways may facilitate downstream success.

A mixed-methods evaluation using effectiveness perception surveys, social network analysis, and county-level health statistics: A pilot study of eight rural Indiana community health coalitions.

Community health coalitions (CHCs) are a promising approach for addressing disparities in rural health statistics. However, their effectiveness has been variable, and evaluation methods have been insufficient and inconsistent. Thus, we propose a mixed-methods evaluation framework and discuss pilot study findings. CHCs in our pilot study partnered with Purdue Extension. Extension links communities and land grant universities, providing programming and support for community-engaged research. We conducted social network analysis and effectiveness perception surveys in CHCs in 8 rural Indiana counties during summer 2017 and accessed county-level health statistics from 2015-16. We compared calculated variables (i.e., effectiveness survey k-means clusters, network measures, health status/outcomes) using Pearson's correlations. CHC members' positive perceptions of their leadership and functioning correlated with interconnectedness in their partnership networks, while more centralized partnership networks correlated with CHC members reporting problems in their coalitions. CHCs with highly rated leadership and functioning developed in counties with poor infant/maternal health and opioid outcomes. Likewise, CHCs reporting fewer problems for participation developed in counties with poor infant/maternal health, poor opioid outcomes, and more people without healthcare coverage. This pilot study provides a framework for iterative CHC evaluation. As the evidence grows, we will make recommendations for best practices that optimize CHC partnerships to improve local health in rural areas.