Impact of Ivacaftor on Medication Use, Hospital and Outpatient Provider Visits and Associated Costs in a Medicaid Population

BACKGROUND: Ivacaftor is the first Food and Drug Administration-approved medication to treat an underlying genetic defect in patients with cystic fibrosis (CF). With an approximate annual cost of $300,000 per patient, ivacaftor may have a profound financial impact on health systems, even when utilized by a small population. Clinical data has demonstrated that treatment with ivacaftor may reduce pulmonary exacerbations (PE) and associated hospitalizations. As a result, patients receiving ivacaftor may need less outpatient care and fewer medications to treat CF complications. Evaluating the impact of ivacaftor therapy on medication utilization, PEs and hospital/outpatient visits can aid formulary decision makers in its effective management. OBJECTIVES: The primary objective is to examine the effects of ivacaftor on patients’ overall medication regimen and associated costs within a Medicaid population. The secondary objective is to examine its effect on the rates of PEs and hospital/outpatient visits. METHODS: Pharmacy and medical claims data for Medicaid members ≥ six years of age was collected for six months before and after the first reported pharmacy claim of ivacaftor. Data included: total number of unique claims, days supply, dose, and total cost for each medication, number of short-term antibiotic and/or steroid courses, outpatient provider visits, hospitalizations, ER visits and corresponding diagnosis codes. Diagnosis codes and short-term antibiotic and/or steroid courses were reviewed to determine if a PE may have occurred. RESULTS: Ivacaftor treatment did not decrease the utilization of medications used to treat patients with CF and resulted in increased pharmacy expenditures for other medications. However, a 65% reduction in PEs as well as a reduction in hospitalizations/ER visits was observed in members receiving ivacaftor. CONCLUSIONS: This study found that while ivacaftor treatment may not decrease total medication utilization or associated costs, it may decrease the number of PEs and associated hospitalizations in patients with CF

Molecular Implication of PP2A and Pin1 in the Alzheimer's Disease Specific Hyperphosphorylation of Tau

Tau phosphorylation and dephosphorylation regulate in a poorly understood manner its physiological role of microtubule stabilization, and equally its integration in Alzheimer disease (AD) related fibrils. A specific phospho-pattern will result from the balance between kinases and phosphatases. The heterotrimeric Protein Phosphatase type 2A encompassing regulatory subunit PR55/Bα (PP2A(T55α)) is a major Tau phosphatase in vivo, which contributes to its final phosphorylation state. We use NMR spectroscopy to determine the dephosphorylation rates of phospho-Tau by this major brain phosphatase, and present site-specific and kinetic data for the individual sites including the pS202/pT205 AT8 and pT231 AT180 phospho-epitopes.We demonstrate the importance of the PR55/Bα regulatory subunit of PP2A within this enzymatic process, and show that, unexpectedly, phosphorylation at the pT231 AT180 site negatively interferes with the dephosphorylation of the pS202/pT205 AT8 site. This inhibitory effect can be released by the phosphorylation dependent prolyl cis/trans isomerase Pin1. Because the stimulatory effect is lost with the dimeric PP2A core enzyme (PP2A(D)) or with a phospho-Tau T231A mutant, we propose that Pin1 regulates the interaction between the PR55/Bα subunit and the AT180 phospho-epitope on Tau.Our results show that phosphorylation of T231 (AT180) can negatively influence the dephosphorylation of the pS202/pT205 AT8 epitope, even without an altered PP2A pool. Thus, a priming dephosphorylation of pT231 AT180 is required for efficient PP2A(T55α)-mediated dephosphorylation of pS202/pT205 AT8. The sophisticated interplay between priming mechanisms reported for certain Tau kinases and the one described here for Tau phosphatase PP2A(T55α) may contribute to the hyperphosphorylation of Tau observed in AD neurons

Coefficients of full model for new-onset atrial arrhythmia.

Coefficients of full model for new-onset atrial arrhythmia.</p

Performance of potassium for in-hospital mortality and atrial arrhythmia.

Performance of potassium for in-hospital mortality and atrial arrhythmia.</p

Coefficients of biomarker-only model for new-onset atrial arrhythmia.

Coefficients of biomarker-only model for new-onset atrial arrhythmia.</p

ROC for model adjusting for type of atrial arrhythmia.

ROC for model adjusting for type of atrial arrhythmia.</p

Baseline demographic, biomarker, and hospital event characteristics.

Baseline demographic, biomarker, and hospital event characteristics.</p

ROC for ICU admission.

Hospitalized patients with Coronavirus disease 2019 (COVID-19) are highly susceptible to in-hospital mortality and cardiac complications such as atrial arrhythmias (AA). However, the utilization of biomarkers such as potassium, B-type natriuretic peptide, albumin, and others for diagnosis or the prediction of in-hospital mortality and cardiac complications has not been well established. The study aims to investigate whether biomarkers can be utilized to predict mortality and cardiac complications among hospitalized COVID-19 patients. Data were collected from 6,927 hospitalized COVID-19 patients from March 1, 2020, to March 31, 2021 at one quaternary (Henry Ford Health) and five community hospital registries (Trinity Health Systems). A multivariable logistic regression prediction model was derived using a random sample of 70% for derivation and 30% for validation. Serum values, demographic variables, and comorbidities were used as input predictors. The primary outcome was in-hospital mortality, and the secondary outcome was onset of AA. The associations between predictor variables and outcomes are presented as odds ratio (OR) with 95% confidence intervals (CIs). Discrimination was assessed using area under ROC curve (AUC). Calibration was assessed using Brier score. The model predicted in-hospital mortality with an AUC of 90% [95% CI: 88%, 92%]. In addition, potassium showed promise as an independent prognostic biomarker that predicted both in-hospital mortality, with an AUC of 71.51% [95% Cl: 69.51%, 73.50%], and AA with AUC of 63.6% [95% Cl: 58.86%, 68.34%]. Within the test cohort, an increase of 1 mEq/L potassium was associated with an in-hospital mortality risk of 1.40 [95% CI: 1.14, 1.73] and a risk of new onset of AA of 1.55 [95% CI: 1.25, 1.93]. This cross-sectional study suggests that biomarkers can be used as prognostic variables for in-hospital mortality and onset of AA among hospitalized COVID-19 patients.</div