Trends of Azole Antifungal Prescription in the United States: Medicare Part D Provider Utilization and Payment Data Analysis

BACKGROUND: Invasive fungal infections carry a substantial risk of mortality and morbidity. Azole antifungals are used in the treatment of such infections; however, their extensive use can lead to the emergence of antifungal resistance and increased costs to patients and healthcare systems. The aim of this study is to evaluate trends in these antifungals use and costs. METHODS: The secular and regional trends of outpatient azole antifungals were analyzed using Medicare Part D Prescriber Public Use Files for the years 2013-2020. The total days supply (TDS), total drug cost (TDC) per 100 000 enrollees, and cost per day (CPD) were evaluated. RESULTS: The azole antifungal TDS for Medicare Part D enrollees increased by 12% between 2013 and 2020, and increases were noted for each azole. Southern US regions had the highest TDS, with Arizona having the highest TDS among US states in 2020. Cost analysis showed that TDC of all azoles has increased by 93% over the years, going up from $123 316 in 2013 to$238 336 per 100 000 enrollees in 2020. However, CPD showed an increase only for fluconazole and isavuconazole, with CPD of $1.62 per day and$188.30 per day, respectively. CONCLUSIONS: Combined azole antifungal prescriptions TDS increased among Medicare Part D enrollees. The trend in CPD was mixed, whereas overall costs consistently increased over the same period. Such findings provide an insight into the impact of azole antifungal prescriptions, and increasing use could foreshadow more antifungal resistance. Continued studies to evaluate different prescribers\u27 trends are warranted

The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics

Analysis of trends in health data collected over time can be affected by instantaneous changes in coding that cause sudden increases/decreases, or “jumps,” in data. Despite these sudden changes, the underlying continuous trends can present valuable information related to the changing risk profile of the population, the introduction of screening, new diagnostic technologies, or other causes. The joinpoint model is a well-established methodology for modeling trends over time using connected linear segments, usually on a logarithmic scale. Joinpoint models that ignore data jumps due to coding changes may produce biased estimates of trends. In this article, we introduce methods to incorporate a sudden discontinuous jump in an otherwise continuous joinpoint model. The size of the jump is either estimated directly (the Joinpoint-Jump model) or estimated using supplementary data (the Joinpoint-Comparability Ratio model). Examples using ICD-9/ICD-10 cause of death coding changes, and coding changes in the staging of cancer illustrate the use of these models

The Joinpoint-Jump and Joinpoint-Comparability Ratio Model for Trend Analysis with Applications to Coding Changes in Health Statistics

Analysis of trends in health data collected over time can be affected by instantaneous changes in coding that cause sudden increases/decreases, or “jumps,” in data. Despite these sudden changes, the underlying continuous trends can present valuable information related to the changing risk profile of the population, the introduction of screening, new diagnostic technologies, or other causes. The joinpoint model is a well-established methodology for modeling trends over time using connected linear segments, usually on a logarithmic scale. Joinpoint models that ignore data jumps due to coding changes may produce biased estimates of trends. In this article, we introduce methods to incorporate a sudden discontinuous jump in an otherwise continuous joinpoint model. The size of the jump is either estimated directly (the Joinpoint-Jump model) or estimated using supplementary data (the Joinpoint-Comparability Ratio model). Examples using ICD-9/ICD-10 cause of death coding changes, and coding changes in the staging of cancer illustrate the use of these models

Multicenter Collaborative Study of the Interaction of Antifungal Combinations against BrowZine Journal Cover Candida Spp. by Loewe Additivity and Bliss Independence-Based Response Surface Analysis

Combination antifungal therapy is widely used but not well understood. We analyzed the spectrophotometric readings from a multicenter study conducted by the New York State Department of Health to further characterize the in vitro interactions of the major classes of antifungal agents against Candida spp. Loewe additivity-based fractional inhibitory concentration index (FICi) analysis and Bliss independence-based response surface (BIRS) analysis were used to analyze two-drug inter- and intraclass combinations of triazoles (AZO) (voriconazole, posaconazole), echinocandins (ECH) (caspofungin, micafungin, anidulafungin), and a polyene (amphotericin B) against Candida albicans, C. parapsilosis, and C. glabrata. Although mean FIC indices did not differ statistically significantly from the additivity range of 0.5−4, indicating no significant pharmacodynamic interactions for all of the strain−combinations tested, BIRS analysis showed that significant pharmacodynamic interactions with the sum of percentages of interactions determined with this analysis were strongly associated with the FIC indices (Χ2 646, p \u3c 0.0001). Using a narrower additivity range of 1−2 FIC index analysis, statistically significant pharmacodynamic interactions were also found with FICi and were in agreement with those found with BIRS analysis. All ECH+AB combinations were found to be synergistic against all Candida strains except C. glabrata. For the AZO+AB combinations, synergy was found mostly with the POS+AB combination. All AZO+ECH combinations except POS+CAS were synergistic against all Candida strains although with variable magnitude; significant antagonism was found for the POS+MIF combination against C. albicans. The AZO+AZO combination was additive for all strains except for a C. parapsilosis strain for which antagonism was also observed. The ECH+ECH combinations were synergistic for all Candida strains except C. glabrata for which they were additive; no antagonism was found

The CTSA University of Texas Health Science Center (UTHSC) Northeast—Tyler and Rio Grande Valley Success Story: How Rural, Underserved Academic Communities Rapidly Built a Robust Engine for Collaborative COVID-19 Clinical Research

In 2018, The University of Texas Health Science Center– Tyler and University of Texas Rio Grande Valley were invited to develop clinical research units for an existing Clinical and Translational Science Award (CTSA) consortium with the objective to equip medically underserved, economically disadvantaged communities and subsequently to deploy COVID-19 clinical trials in response to a public health emergency

Clinical Practice Guidelines for the Management Candidiasis: 2009 Update by the Infectious Diseases Society of America

Guidelines for the management of patients with invasive candidiasis and mucosal candidiasis were prepared by an Expert Panel of the Infectious Diseases Society of America. These updated guidelines replace the previous guidelines published in the 15 January 2004 issue of Clinical Infectious Diseases and are intended for use by health care providers who care for patients who either have or are at risk of these infections. Since 2004, several new antifungal agents have become available, and several new studies have been published relating to the treatment of candidemia, other forms of invasive candidiasis, and mucosal disease, including oropharyngeal and esophageal candidiasis. There are also recent prospective data on the prevention of invasive candidiasis in high-risk neonates and adults and on the empiric treatment of suspected invasive candidiasis in adults. This new information is incorporated into this revised documen