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On March 4, 2022, the American Medical Association (AMA) released a statement in response to the Biden administration's plan of a test-to-treat plan allowing pharmacists to serve as locations to test and provide prescriptions for oral antiviral therapies for the treatment of coronavirus disease 2019 (COVID-19) after a positive test result. The statement by AMA contradicts and underrepresents the impact pharmacists have on clinical practice. Pharmacists have been a crucial part of many efforts including mass vaccination efforts and furnishing of prescriptions for other complex disease states (e.g., pre-exposure prophylaxis and postexposure prophylaxis therapy). Furthermore, health systems have proven that novel approaches to mitigate operational and clinical barriers to COVID-19 therapies may offset the increased demand needed by communities. Herein, this commentary will discuss a viewpoint and counterpoint to the statement put out by AMA, with a focus on pharmacists. [ABSTRACT FROM AUTHOR]

Immune checkpoint inhibitors (ICIs) are an effective therapy for various cancers; however, they can induce immune-related adverse events (irAEs) as a side effect. Myocarditis is an uncommon, but fatal, irAE caused after ICI treatments. Currently, the mechanism of ICI-associated myocarditis is unclear. Here, we show the development of myocarditis in A/J mice induced by anti-PD-1 monoclonal antibody (mAb) administration alone without tumor cell inoculation, immunization, or viral infection. Mice with myocarditis have increased cardiac infiltration, elevated cardiac troponin levels, and arrhythmia. Anti-PD-1 mAb treatment also causes irAEs in other organs. Autoimmune T cells recognizing cardiac myosin are activated and increased in mice with myocarditis. Notably, cardiac myosin-specific T cells are present in naive mice, showing a phenotype of antigen-experienced T cells. Collectively, we establish a clinically relevant mouse model for ICI-associated myocarditis and find a contribution of cardiac myosin-specific T cells to ICI-associated myocarditis development and pathogenesis. [Display omitted] • PD-1 inhibitor treatment alone causes myocarditis development in A/J mice • Cardiac-myosin-specific T cells drive PD-1 inhibitor-induced myocarditis in mice • Cardiac-myosin-specific autoimmune T cells are present in naive mouse hearts • Cardiac-myosin-specific autoimmune T cells express PD-1 during naive conditions Won et al. demonstrate that PD-1 inhibitor treatment alone induces myocarditis in A/J mice, creating a mouse model for immune-checkpoint-inhibitor-associated myocarditis. Cardiac myosin-specific autoreactive T cells drive the pathogenesis of PD-1 inhibitor-induced myocarditis in mice. PD-1-expressing cardiac myosin-specific T cells are present in the heart during naive conditions. [ABSTRACT FROM AUTHOR]

Osteoarthritis (OA) is a progressive disease for which there is no disease modifying therapy. Vitamin K levels and vitamin K antagonism have been associated with risk and progression of OA which may have direct implications for clinical management, but these observational findings are susceptible to confounding. We aimed to estimate the causal association between vitamin K and OA risk using Mendelian randomisation (MR). We used data from the largest genome-wide association study (GWAS) of OA to date (up to 826,690 individuals) to estimate the effect of genetically predicted vitamin K level (instrumented using four variants derived from a GWAS of 2,138 individuals) on risk of all OA types, knee, hip, spine, hand OA, and total joint replacement. We employed the inverse-variance weighted method for the primary analysis and, in a series of sensitivity analyses, adjusted for sub-genome wide significant instruments and tested for potential bias from pleiotropy. We showed that genetically predicted vitamin K levels were not causally associated with risk of OA overall (OR 0.98 per unit increase in log-transformed vitamin K1; 95%CI 0.96-1.01), knee (OR 0.98; 0.92-1.03), hip (OR 0.97; 0.88-1.07), spine (OR 0.97; 0.90-1.04), hand OA (OR 0.97; 0.91-1.04) or joint replacement (OR 0.96; 0.89-1.04). Results were similar across all sensitivity analyses. We found little evidence of a causal association between genetically predicted vitamin K and OA risk. Larger genetic and interventional studies of vitamin K are required to confirm our findings. [ABSTRACT FROM AUTHOR]

Ultrasound (US)-based screening has been recommended for patients with an increased risk of hepatocellular carcinoma (HCC). US analysis, however, is limited in patients who are obese or have small tumors. The addition of serum level of α-fetoprotein (AFP) measurements to US analysis can increase detection of HCC. We analyzed data from patients with chronic liver disease, collected over 15 years in an HCC surveillance program, to develop a model to assess risk of HCC. We collected data from 3450 patients with chronic liver disease undergoing US surveillance in Japan from March 1998 through April 2014, and followed them up for a median of 8.83 years. We performed longitudinal discriminant analysis of serial AFP measurements (median number of observations/patient, 56; approximately every 3 months) to develop a model to determine the risk of HCC. We validated the model using data from 2 cohorts of patients with chronic liver disease in Japan (404 and 2754 patients) and 1 cohort in Scotland (1596 patients). HCC was detected in 413 patients (median tumor diameter, 1.8 cm), during a median follow-up time of 6.60 years. In the development data set, the model identified patients who developed HCC with an area under the curve of 0.78; it correctly identified 74.3% of patients who did develop HCC, and 72.9% of patients who did not. Overall, 73.1% of patients were classified correctly. The model could be used to assign patients to a high-risk group (27.5 HCCs/1000 patient-years) vs a low-risk group (4.9 HCCs/1000 patient-years). A similar performance was observed when the model was used to assess patients with cirrhosis. Analysis of the validation cohorts produced similar results. We developed and validated a model to identify patients with chronic liver disease who are at risk for HCC based on change in serum AFP level over time. The model could be used to assign patients to high-risk vs low-risk groups, and might be used to select patients for surveillance. [ABSTRACT FROM AUTHOR]