Prospective Monitoring of Newly Marketed Drugs in Frail Older Adults Using Real-World Databases

In recent years several new drugs have been approved for treatment of heart failure and type 2 diabetes. Despite their life-prolonging benefits, uptake of new drugs is often slow among older patients with frailty due to under-representation of frail older adults in pivotal clinical trials and concerns for adverse events. To optimize pharmacotherapy, timely evaluation of the drug benefits and risks is urgently needed. We propose a novel drug monitoring framework that prospectively evaluates the effectiveness and safety of newly marketed drugs for frail and non-frail patients in real-world databases. This framework utilizes a validated claims-based frailty index (CFI) (range: 0-1; frail if ≥0.20) to find early signals for effectiveness and safety of new drugs by updating the analysis at regular intervals as new data become available. In this symposium, we present early results of this prospective monitoring framework for 2 new drug classes using Medicare claims data from the approval date until the end of 2017: 1) angiotensin receptor-neprilysin inhibitor (ARNI) (approved in July 2015) for heart failure with reduced ejection fraction (HFrEF) and 2) sodium-glucose cotransporter-2 inhibitors (SGLT2i) (approved in March 2013) for type 2 diabetes. We first show the uptake of ARNI and SGLT2i over time among the eligible Medicare beneficiaries by clinical characteristics, including frailty. Subsequently we present the results of sequential cohort analysis for the effectiveness and safety results of ARNI and SGLT2i. After these presentations, the panel will discuss the strengths, limitations, and challenges of implementing our monitoring framework in real-world databases.

OP440 Comparison Of Evidence Supporting Cancer Drug Approvals And Prices In The US And Brazil

IntroductionCancer drug prices are high on the policy agenda worldwide. Previous research found no association between cancer drug benefits and prices at the time of regulatory approval. Drugs approved in the US with uncertain benefits may have spill-over effects in other settings. Our objective was to compare the evidence supporting cancer drug approvals in the US and Brazil, and to examine the association between cancer drug prices and availability of added therapeutic benefit.MethodsWe matched all novel cancer drugs approved in the US from 2010–2019 to approvals in Brazil. We extracted data on pivotal study design characteristics and outcomes in the US and Brazil, and evidence supporting price approval in Brazil, including availability of added therapeutic benefit.ResultsFrom 2010–2019, fifty-six cancer drugs with matching indications were approved in US and Brazil and had their prices authorized in Brazil by December 2020. Drug were available in Brazil following a median 522 days after US approval (IQR: 351–932). In the US, thirty-four (60.7 percent) of the drugs had pivotal randomized controlled trials (RCTs) and Twelve (21.4 percent) had overall survival benefit. By the time of Brazilian approval, forty-one (73.2 percent) drugs had pivotal RCTs and twenty-two (39.3 percent) had overall survival benefit. A total of twenty-eight (50 percent) drugs did not demonstrate added therapeutic benefit over other authorized drugs for the same indication and had a median reduction from requested to approved price of 6.1 percent (IQR: 0–27.8 percent) in Brazil. The twenty-seven (48.2 percent) drugs with added therapeutic benefit had a median price reduction of 2.0 percent (IQR: 0–9.2 percent).ConclusionsHalf of new cancer drugs approved in Brazil failed to demonstrate added therapeutic benefit. The Brazilian pricing system secured considerable price reductions, ensuring that prices for medicines with no added therapeutic benefit were not higher than existing treatments for the same approved indication. Although evidence was more mature by the time of Brazilian review, pivotal studies often lacked randomization and overall survival endpoints.

Cost-related Medication Nonadherence among Medicare Beneficiaries with Cardiovascular Disease Risk Factors: The Role of Comprehension of the Medicare Program and its Prescription Drug Benefits

RATIONALE, AIMS, AND OBJECTIVES: This study aims to investigate how reported comprehension of the Medicare program and its prescription drug benefits affects cost-related medication nonadherence (CRN) among Medicare beneficiaries with cardiovascular disease (CVD) risk factors. METHODS: This cross-sectional study used the 2017 Medicare Current Beneficiary Survey Public Use File data and included Medicare beneficiaries aged ≥ 65 years who reported having at least one CVD risk factor (i.e., hypertension, hyperlipidemia, diabetes, smoking, and obesity) (n=2,821). A survey-weighted logistic model was used to examine associations between lack of difficulty understanding the Medicare program and its prescription drug benefits and CRN, controlling for beneficiaries’ demographic (e.g., age) and clinical characteristics (e.g, comorbidities). This study further analyzed five subgroups based on the type of CVD risk factors involved. RESULTS: Among Medicare beneficiaries with CVD risk factors, 14.4% reported CRN. Medicare beneficiaries with CVD risk factors who reported difficulty understanding the overall Medicare program and its prescription drug benefits were more likely to report CRN, compared to those who reported easy understanding of the overall Medicare program (OR=1.49; 95% CI=1.09, 2.04; p<0.001) and its prescription drug benefits (OR=2.01; 95% CI=1.51, 2.67; p<0.001). Similar results were obtained for the subgroups with obesity, hypertension, or hyperlipidemia. CONCLUSIONS: Perceived lack of difficulty understanding the Medicare Program and its prescription drug benefits has a positive impact on CRN reduction among Medicare beneficiaries with CVD risk factors, especially those with obesity, hypertension or hyperlipidemia. Monitoring and enhancing Medicare beneficiaries’ overall understanding of the Medicare program may reduce CRN.

Advanced Therapy Medicines Based on Oncolytic Viruses (Part II: Development and Authorisation of IMLYGIC®)

The only oncolytic virus-based product authorised in the US and EU—IMLYGIC®, a genetically modified herpes simplex virus type 1 (by BioVex Inc., a subsidiary of Amgen, Inc.)—was developed and approved for clinical use as monotherapy for recurrent unresectable melanoma. The aim of the study was to analyse materials on IMLYGIC® development and authorisation in order to be able to use the data on specific aspects of preclinical and clinical trials of oncolytic virus-based products in the development of regulatory framework for Russia and the EAEU. The publicly available preclinical and clinical trial results demonstrate a decrease in the size of both tumours being injected and remote tumours/skin lesions, which supports the local and systemic effects of IMLYGIC® due to the lysis effect of the virus on the tumour cells. The clinical trials of IMLYGIC® were the first to use the durable response rate, and not the overall survival, as the primary endpoint of the efficacy of the anticancer drug. Benefits of IMLYGIC® therapy were observed across all the secondary endpoints, except overall survival. Significant efficacy of the drug therapy was demonstrated only in patients without visceral lesions, which resulted in limitations of indications for use. There have been no serious or severe adverse effects associated with IMLYGIC®. If symptoms of viral infection develop, they can be neutralized thanks to the product’s sensitivity to acyclovir. At present, advanced therapy medicinal products derived from an oncolytic virus may be authorised in Russia for clinical use as monotherapy or combination therapy, according to the EAEU regulations.

Blood Genomics Identifies Three Subtypes of Systemic Lupus Erythematosus: “IFN-High,” “NE-High,” and “Mixed”

Purpose. Systemic lupus erythematosus (SLE) is a systemic and multifactorial autoimmune disease, and its diverse clinical manifestations affect molecular diagnosis and drug benefits. Our study was aimed at defining the SLE subtypes based on blood transcriptome data, analyzing functional patterns, and elucidating drug benefits. Methods. Three data sets were used in this paper that were collected from the Gene Expression Omnibus (GEO) database, which contained two published data sets of pediatric and adult SLE patients (GSE65391, GSE49454) and public longitudinal data (GSE72754) from a cohort of SLE patients treated with IFN-α Kinoid (IFN-K). Based on disease activity scores and gene expression data, we defined a global SLE signature and merged three clustering algorithms to develop a single-sample subtype classifier (SSC). Systematic analysis of coexpression networks based on modules revealed the molecular mechanism for each subtype. Results. We identified 92 genes as a signature of the SLE subtypes and three intrinsic subsets (“IFN-high,” “NE-high,” and “mixed”), which varied in disease severity. We speculated that IFN-high might be due to the overproduction of interferons (IFNs) caused by viral infection, leading to the formation of autoantibodies. NE-high might primarily result from bacterial and fungal infections that stimulated neutrophils (NE) to produce neutrophil extracellular traps (NETs) and induced individual autoimmune responses. The mixed type contained both of these molecular mechanisms and showed an intrinsic connection. Conclusions. Our research results indicated that identifying the molecular mechanism associated with different SLE subtypes would benefit the molecular diagnosis and stratified therapy. Moreover, repositioning of IFN-K based on subtypes also revealed an improved therapeutic effect, providing a new direction for disease treatment and drug development.

Incidence of household catastrophic and impoverishing health expenditures among patients with Breast Cancer in Iran

Background Breast cancer disease is the most common cancer among Iranian women and imposing a significant financial burden on the households. This study calculated out-of-pocket (OOP), catastrophic health expenditure (CHE), and impoverishing health spending attributed to breast cancer in Iran. Methods In this cross-sectional household study, clinical and financial information on breast cancer and also household information (expenditures and income) were obtained through face-to-face interviews and completing a questionnaire by 138 women with this disease in 2019. We applied three non-food expenditure thresholds of 40, 20, and 10% to defining the CHE. Disease costs included periodical visits, diagnostic services, hospitalization care, treatment and rehabilitation services, home, and informal care. Households were disaggregated into socioeconomic status quintiles based on their Adult Equivalent values standardized monthly consumption expenditures. To identify the factors affecting these indicators, we performed the two different multivariate logistic regression models. Results This study finds that each patient had a monthly average OOP payment of $US 97.87 for the requested services, leading to impoverished of 5.07% and exposed 13.77% of their households to CHE. These indicators have been mainly concentrated among the poor, as they have spent a large part of their meager income on buying the needed services, and for this purpose, most of them forced to sell their assets, borrow, or take a bank loan. Conclusions The patients in lower SES quintiles can be protected from impoverishing and catastrophic health spending by expanding insurance coverage, providing financial risk protection programs, and increasing access to quality and effective public sector services. Alongside, expanding inpatient coverage and adding drug benefits for the poor can significantly decrease their OOP payments.

A Dose of Managed Care: Controlling Drug Spending in Medicaid

We study the effect of privatizing Medicaid drug benefits on drug prices and utilization. Drug spending would decrease by 21.3 percent if private insurers administered all drug benefits. One-third of the decrease is driven by private insurers’ ability to negotiate prices with pharmacies. The remaining two-thirds is driven by the greater use of lower cost drugs, such as generics, and is only realized in states that give private insurers the flexibility to design drug benefits. Privatization does not reduce prescriptions per enrollee and spending cuts are smaller for drugs that lower medical spending. (JEL G22, H51, I11, I13, I18, I38, L65)

Analytical approaches to minimizing immeasurable time bias in cohort studies

Background Immeasurable time bias exaggerates drug benefits in pharmacoepidemiological studies due to exposure misclassification arising from the inability to measure in-hospital medications in many health care databases. Methods To compare the ability of different methodological approaches to minimize immeasurable time bias, we conducted a cohort study of β-blocker use and all-cause mortality among patients with heart failure (HF), using a nationwide health care database which contains both in- and outpatient prescriptions. In our gold-standard analysis, we assessed exposure using a time-varying approach involving both in- and outpatient prescriptions. Cox proportional hazard models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs) of mortality, with exposure to β-blockers defined as a time-varying variable. To estimate the magnitude of the immeasurable time bias, we repeated the analyses using outpatient prescriptions only and compared 10 approaches to minimize the bias, which are categorized as restriction, adjustment, assumption and weighting. Results The HR for β-blocker use versus non-use was 0.76 (95% CI: 0.71 to 0.80) in our gold-standard analysis. When exposure assessment was restricted to outpatient prescriptions only, β-blocker use was substantially more protective (HR 0.43, 95% CI: 0.40 to 0.46). Of the 10 approaches examined, adjusting for hospitalization as a time-varying variable successfully minimized the bias (HR 0.75, 95% CI: 0.68 to 0.82). Conclusions The immeasurable time bias can result in substantial bias in pharmacoepidemiological studies. Time-varying adjustment for hospitalization appears to reduce the immeasurable time bias in the absence of inpatient medication data.