Hospitalizations and Mortality From Myasthenia Gravis: Trends From 2 US National Datasets

BACKGROUND AND OBJECTIVES: Myasthenia gravis (MG) is a rare neuromuscular disorder where IgG antibodies damage the communication between nerves and muscles, leading to muscle weakness that can be severe and have a significant impact on patients' lives. MG exacerbations include myasthenic crisis with respiratory failure, the most serious manifestation of MG. Recent studies have found MG prevalence increasing, especially in older patients. This study examined trends in hospital admissions and in-hospital mortality for adult patients with MG and readmissions and postdischarge mortality in older (65 years or older) adults with MG. METHODS: Data from the Nationwide Inpatient Sample (NIS), an all-payer national database of hospital discharges, were used to characterize trends in hospitalizations and in-hospital mortality related to MG exacerbations and MG crisis among adult patients aged 18 years or older. The Medicare Limited Data Set, a deidentified, longitudinal research database with demographic, enrollment, and claims data was used to assess hospitalizations, length of stay (LOS), readmissions, and 30-day postdischarge mortality among fee-for-service Medicare beneficiaries aged 65 years or older. The study period was 2010-2019. Multinomial logit models and Poisson regression were used to test for significance of trends. RESULTS: Hospitalization rates for 19,715 unique adult patients and 56,822 admissions increased from 2010 to 2019 at an average annualized rate of 4.9% (MG noncrisis: 4.4%; MG crisis: 6.8%; all p < 0.001). Readmission rates were approximately 20% in each study year for both crisis and noncrisis hospitalizations; the in-hospital mortality rate averaged 1.8%. Among patients aged 65 years or older, annualized increases in hospitalizations were estimated at 5.2%, 4.2%, and 7.7% for all, noncrisis, and crisis hospitalizations, respectively (all p < 0.001). The average LOS was stable over the study period, ranging from 11.3 to 13.1 days, but was consistently longer for MG crisis admissions. Mortality among patients aged 65 years or older was higher compared with that in all patients, averaging 5.0% across each of the study years. DISCUSSION: Increasing hospitalization rates suggest a growing burden associated with MG, especially among older adults. While readmission and mortality rates have remained stable, the increasing hospitalization rates indicate that the raw numbers of readmissions-and deaths-are also increasing. Mortality rates are considerably higher in older patients hospitalized with MG.

Quantifying spillover benefits in value assessment: a case study of increased graft survival on the US kidney transplant waitlist.

AIM: To quantify the wider impacts of increased graft survival on the size of the kidney transplant waitlist and health and economic outcomes. MATERIALS AND METHODS: The analysis employed known steady-state solutions to a double-queueing system as well as simulations of this system. Baseline input parameters were sourced from the Organ Procurement and Transplant Network and the United States Renal Data System. Three increased graft survival scenarios were modeled: decreases in repeat transplant candidates joining the waitlist of 25%, 50%, and 100%. RESULTS: Under the three scenarios, we estimated that the US waitlist size would decrease from 91,822 to 85,461 (6.9% decrease), 80,073 (12.8% decrease), and 69,340 (24.4% decrease), respectively. Patient outcomes improved, with lifetime quality-adjusted life years (QALYs) for a 1-year cohort of transplant recipients increasing by 10,010, 16,888, and 43,345 over the three scenarios. Discounted lifetime costs for the cohort in the new steady state were lower by $1.6 billion, $2.3 billion, and $9.0 billion for each scenario, respectively. Spillover impacts (i.e. benefits that accrued beyond the patients who directly experienced increased graft survival) accounted for 41-48% of the QALY gains and ranged from cost increases of 3.3% to decreases of 5.5%. LIMITATIONS: The model is a simplification of reality and does not account for the full degree of patient heterogeneity occurring in the real world. Health economic outcomes are extrapolated based on the assumption that the median patient is representative of the overall population. CONCLUSIONS: Increasing graft survival reduces demand from repeat transplants candidates, allowing additional candidates to receive transplants. These spillover impacts decrease waitlist size and shorten wait times, leading to improvements in graft and patient survival as well as quality-of-life. Cost-effectiveness analyses of treatments that increase kidney graft survival should incorporate spillover benefits that accrue beyond the direct recipient of an intervention.

Hospitalization Risk for Adults with Bipolar I Disorder Treated with Oral Atypical Antipsychotics as Adjunctive Therapy with Mood Stabilizers: A Retrospective Analysis of Medicaid Claims Data.

Background: Atypical antipsychotics (AAPs) with mood stabilizers are recommended as a first-line treatment for patients with bipolar disorder. No studies have compared the inpatient health care resource utilization for patients with bipolar disorder treated with lurasidone as adjunctive therapy with mood stabilizers compared with other oral AAPs. Objective: To compare the risk of hospitalization for adult Medicaid beneficiaries with bipolar I disorder when treated with lurasidone compared with other oral AAPs as adjunctive therapy with mood stabilizers. Methods: This retrospective cohort study used the MarketScan Research Databases Multi-State Medicaid Database (IBM, Armonk, NY) claims data to assess patients with bipolar I disorder between January 1, 2014, and June 30, 2019. Adult patients who initiated oral AAP treatment with mood stabilizers (index date) and who were continuously enrolled 12 months before (pre-index) and 24 months after (post-index) the index date were included. Treatment categories assigned by patient-month included lurasidone, aripiprazole, olanzapine, quetiapine, risperidone, or ziprasidone with mood stabilizers; no/minimal treatment; AAP monotherapy; and other. Marginal structural models were performed to estimate the all-cause and psychiatric hospitalization rates and hospital length of stay associated with each adjunctive AAP therapy by controlling for both time-invariant and time-varying confounders. Results: Adults with bipolar I disorder (N = 11,426; mean age = 39.4 years; female=73%) treated with an adjunctive oral AAP with mood stabilizers during the index month were categorized into lurasidone (12%), aripiprazole (17%), olanzapine (7%), quetiapine (32%), risperidone (11%), ziprasidone (7%), or other (15%) treatment groups. The adjusted odds of all-cause and psychiatric hospitalization were significantly higher for olanzapine (all causes: adjusted odds ratio [aOR] = 1.59; 95% CI, 1.13-2.25; psychiatric: aOR = 1.61, 95% CI, 1.12-2.32), quetiapine (all-causes: aOR = 1.27, 95% CI, 1.01-1.58; psychiatric: aOR = 1.28, 95% CI, 1.02-1.59), and ziprasidone (all-causes: aOR = 1.68, 95% CI, 1.05-2.66; psychiatric: aOR = 1.55, 95% CI, 1.02-2.35) compared with lurasidone with mood stabilizers. The adjusted odds of all-cause and psychiatric hospitalizations were numerically lower for lurasidone compared with aripiprazole. The all-cause hospital length of stay per 100 patient-months was significantly higher for olanzapine (20.3 days) and quetiapine (16.0 days) compared with lurasidone (12.2 days, both P values < 0.05). Conclusions: In a Medicaid population, adults with bipolar I disorder treated with lurasidone as adjunctive therapy with mood stabilizers had significantly lower all-cause and psychiatric hospitalization rates compared with olanzapine, quetiapine, and ziprasidone. Fewer hospitalizations may reduce the economic burden associated with bipolar disorder. (Curr Ther Res Clin Exp. 2021; 82:XXX-XXX).

Hospitalization risk among adults with bipolar I disorder treated with lurasidone versus other oral atypical antipsychotics: a retrospective analysis of Medicaid claims data.

OBJECTIVE: To compare the risk of hospitalization for adult Medicaid beneficiaries with bipolar I disorder treated with lurasidone vs. other oral atypical antipsychotics (AAPs) as monotherapy. METHODS: A retrospective cohort study of the IBM MarketScan Multi-State Medicaid Claims database identified adults with bipolar I disorder who initiated an AAP (index date) between 1 January 2014 and 30 June 2019. Patients were continuously enrolled 12 months pre- and 24 months post-index date. Each month during the post-index period was categorized as monotherapy with lurasidone, aripiprazole, olanzapine, quetiapine or risperidone, no/minimal treatment, or other. Marginal structural models were performed to estimate hospitalization risk and length of stay (LOS) (all-cause and bipolar I disorder-related) compared to lurasidone. RESULTS: The analysis included 8262 adults. Compared to lurasidone, the adjusted odds ratios (aORs) of all-cause hospitalization were significantly higher for olanzapine (aOR = 1.60, 95% CI = 1.09-2.10) and quetiapine (aOR = 1.54, 95% CI = 1.18-1.89). The risk was significantly higher for bipolar I disorder-related hospitalization for quetiapine (aOR = 1.57, 95% CI = 1.10-2.04) and risperidone (aOR = 1.80, 95% CI = 1.04-2.56) compared to lurasidone. The bipolar I disorder-related LOS per 100 patient-months was more than twice as long for quetiapine (8.42 days) compared to lurasidone (3.97 days, p < .01). CONCLUSIONS: Lurasidone-treated adult Medicaid patients with bipolar I disorder had significantly lower risk of all-cause hospitalization than those treated with olanzapine and quetiapine and lower risk of bipolar I disorder-related hospitalization than quetiapine and risperidone. Bipolar I disorder-related hospital LOS was significantly shorter for patients treated with lurasidone compared to quetiapine.

For which diseases do broader value elements matter most? An evaluation across 20 ICER evidence reports.

BACKGROUND: U.S. value framework developers such as the Institute for Clinical and Economic Review (ICER) use cost-effectiveness analysis to value new health care technologies. Often, these value assessment frameworks use a health system perspective without fully accounting for societal and broader benefits and costs of an intervention. Although there is ongoing debate about the most appropriate methods for including broader value elements in value assessment, it remains unclear whether the inclusion of these value elements is likely to affect the quantitative estimates of treatment value. OBJECTIVE: To assess variations in the relevance of broader value elements to cost-effectiveness analysis across diseases. METHODS: Thirty-two broader value elements (e.g., caregiver burden, health equity, real option value, productivity) not traditionally included in health technology assessments were identified through a targeted literature review. Evidence reports published by ICER between July 2017 and January 2020 were evaluated to identify which broader value elements were discussed as relevant to each disease in the report text. The study examined whether there were associations among ICER's discussion of broader value elements, rare disease status, treatment cost, estimated treatment cost-effectiveness, and ICER committee voting results for contextual considerations and additional benefits/disadvantages. RESULTS: The most commonly cited broader value element category in the ICER evidence reports was household and leisure (e.g., absenteeism from normal activities and caregiver burden). More value elements were cited for inherited retinal disease (19 elements) and sickle cell disease (18 elements) than for other diseases. Cardiovascular disease and diabetes had the fewest number of value elements cited (7 elements). Rare diseases were more likely to have broader value elements cited compared with nonrare diseases (15.9 vs. 11.5, P < 0.001). Treatments with higher (i.e., less favorable) incremental cost-effectiveness ratios were more likely to have a greater number of broader value elements cited (ρ = 0.625, P < 0.001). CONCLUSIONS: The presence of broader value elements varied across diseases, with less cost-effective treatments more likely to have a higher number of relevant broader value elements. Inclusion of all relevant value elements in value assessments will more appropriately incentivize innovation and improve allocation of research funding. DISCLOSURES: This study was sponsored by Novartis Pharmaceutical Corporation. At the time of this study, Shafrin was employed by PRECISIONheor, a consultancy to the life sciences industry that received financial support from Novartis to conduct this study. Dennen, Pednekar, and Birch are employed by PRECISIONheor. Bhor was an employee of Novartis Pharmaceutical Corporation at the time this research was conducted and manuscript was developed and reports grants from Novartis, unrelated to this work. Kanter has served on scientific advisory boards and steering committees for and reports receiving consulting fees from Novartis Pharmaceutical Corporation and is a site principal investigator on studies funded by Novartis Pharmaceutical Corporation. Kantar also reports support from Sickle Cell Disease Association of America Inc. and National Heart, Lung, and Blood Institute, unrelated to this work. Neumann reports advisory boards or consulting fees from Novartis Pharmaceutical Corporation and PRECISIONheor, as well as advisory boards or consulting fees unrelated to this study from AbbVie, Amgen, Avexis, Bayer, Congressional Budget Office, Janssen, Merck, Novartis, Novo Nordisk, Precision Health Economics, Veritech, Vertex; funding from The CEA Registry Sponsors by various pharmaceutical and medical device companies; and grants from Amgen, Lundbeck, Bill and Melinda Gates Foundation, National Pharmaceutical Council, Alzheimer's Association, and the National Institutes for Health.

Changes in mortality associated with cancer drug approvals in the United States from 2000 to 2016.

AIMS: To estimate the extent to which the approvals of new pharmacological therapies were associated with cancer mortality in the USA between 2000 and 2016. MATERIALS AND METHODS: The analysis quantified cancer drug approvals across the 15 tumor types with the highest incidence. Number of approvals in a given time period for each tumor was translated into a treatment stock measure, defined as a weighted sum of new indication approvals since 1976. The primary outcome was the annual tumor-specific cancer mortality, defined as the number of deaths per 100,000 U.S. population. The analysis used a multivariable ordinary least squares and a fixed effects model, controlling for incidence (new cases per 100,000 U.S. population) and the primary exposure, the treatment stock measure by year. RESULTS: Between 2000 and 2016, deaths per 100,000 population across the 15 most common tumor types declined by 24%. Additionally, 10.2 new indications were approved per year across the 15 most common tumor types. Cancer drug approvals were associated with statistically significant deaths averted in 2016 for colorectal cancer (4,991, p = 0.004), lung cancer (33,825, p < 0.001), breast cancer (11,502, p < 0.001), non-Hodgkin's lymphoma (6,636, p < 0.001), leukemia (4,011, p < 0.001), melanoma (1,714, p < 0.001), gastric cancer (758, p = 0.019), and renal cancer (739, p < 0.001). Between 2000 and 2016, new cancer treatments were correlated with 1,291,769 (p < 0.001) total deaths prevented across the 15 most common tumor types. LIMITATIONS AND CONCLUSIONS: Cancer drug approvals between 2000 and 2016 were associated with significant reduction in deaths from the most common cancers in the USA. Mortality changes were largest in prevalent tumor types with relatively more approvals, i.e. lung cancer, breast cancer, melanoma, lymphoma and leukemia. Future research evaluating the relationship between drug approvals and cancer mortality post 2016 is needed.

Medicare's Bundled Payments For Care Improvement Initiative Maintained Quality Of Care For Vulnerable Patients.

The Bundled Payments for Care Improvement (BPCI) initiative established four models to test whether linking payments for an episode of care could reduce Medicare payments while maintaining or improving quality. Evaluations concluded that model 2, the largest, generally lowered payments without reducing quality for the average beneficiary, but these global results could mask adverse findings among vulnerable subpopulations. We analyzed changes in emergency department visits, unplanned hospital readmissions, and all-cause mortality within ninety days of hospital discharge among beneficiaries with one or more of three vulnerable characteristics-dementia, dual eligibility for Medicare and Medicaid, and recent institutional care-in 105,458 beneficiary episodes in the period October 2013-December 2016. The results for twelve types of medical and surgical BPCI episodes were evaluated relative to results in matched comparison groups. Our findings suggest that BPCI model 2 did not adversely affect care quality for beneficiaries with vulnerabilities. While this conclusion does not discourage the further development of bundled payment models, policy makers should support ongoing research to ensure that vulnerable populations are not adversely affected by these approaches.