Journal of managed care & specialty pharmacy最新文献

Background: On or before November 1, 2025, the Centers for Medicare & Medicaid Services (CMS) will report the agreed-upon negotiated prices (maximum fair prices [MFPs]) for the second round of up to 15 Medicare Part D drugs selected for price negotiation (Initial Price Applicability Year 2027).

Objective: To propose guideline-recommended therapeutic alternatives and estimate price benchmarks that may be considered by CMS for negotiation.

Methods: We identified US Food and Drug Administration (FDA)-approved indications for the 15 drugs selected for negotiation. We used 2022 Medicare claims data to identify drug-specific beneficiary utilization. Medical claims with International Classification of Diseases, Tenth Revision, Clinical Modification diagnosis codes for each indication were evaluated to estimate relative indication-specific utilization. We examined published clinical guidelines to identify and propose therapeutic alternatives for each drug and the most prevalent, FDA-approved indication. For negotiation price benchmarks, we report (1) the list price, (2) the estimated net price after manufacturer discounts, (3) the minimum statutory discount, and (4) the ceiling of the MFP. All price benchmarks were estimated at the product level, for a 30-day equivalent dosing, using Medicare Part D dashboard and IQVIA data. We also estimated net prices for the proposed therapeutic alternatives.

Results: Four drugs were identified to have 1 (deutetrabenazine, linaclotide, and nintedanib-esylate) or no (rifaximin) therapeutic alternative. Eight of the 15 selected drugs will have the ceiling price set by the minimum statutory discount. Four products (acalabrutinib, semaglutide, linagliptin, and sitagliptin/metformin) will include therapeutic alternatives and MFPs from the first round of negotiation. The selection of therapeutic alternatives and estimation of price benchmarks by CMS will set the initial conditions for subsequent price negotiation.

Conclusions: These analyses identify the likely ceiling price and various initial price offer scenarios for the second round of Medicare price negotiation. We report price benchmarks and likely therapeutic alternatives to improve transparency around the opaque CMS negotiation process.

Background: Real option value (ROV) offers an innovative paradigm to evaluate the dynamic value of medical technologies, particularly in cancer, by capturing the value of extending patient survival to access future innovations. Despite its potential, the application of ROV in medical technologies in oncology remains underexplored.

Objective: To synthesize existing evidence on the application of ROV in medical technologies in oncology.

Methods: A comprehensive search of PubMed, ScienceDirect, and Web of Science was conducted to identify peer-reviewed studies published in English from January 2000 to May 2024. In the search query, a combination of keywords related to "real option value" and "cancer" was used. Key data extracted included study characteristics, objectives, ROV modeling technique, and primary findings. The Consolidated Health Economic Evaluation Reporting Standards 2022 checklist was used for quality assessment of the studies.

Results: A total of 13 of 165 studies assessed the ROV of medical therapies, with a primary focus on melanoma, lung cancer, and prostate cancer. ROV was modeled from the ex post and ex ante perspectives. The methodologies employed vary, with common forecasting approaches including the Lee-Carter model to project future decreases in mortality rates, fitting Cox proportional regression models on administrative claims data, or estimating the approval likelihood of early pipeline drugs based on data from early randomized clinical trials.

Conclusions: The ROV represents a critical dimension in evaluating medical technologies in oncology, where innovation is rapid. The implications of ROV extend beyond oncology, with the potential to influence funding, pricing, and access decisions in other disease areas as well. However, challenges such as oversimplification of assumptions for forecasting, methodological consistency, and lack of standardized framework remain pervasive. This systematic review underscores the need to integrate ROV into Health Technology Assessment practices to inform resource allocation and policy decisions.

Background: Individuals with obesity-associated asthma (OAA) have worse health outcomes than those with asthma and healthy weight (no OAA). The impact of cost barriers on medication use and how it varies by racial and ethnic groups is unclear.

Objective: To assess the impact of cost barriers on medication use in OAA across racial and ethnic groups.

Methods: This cross-sectional study included adults with asthma who participated in the All of Us program between May 2017 and August 2024. OAA was defined as having both asthma (confirmed by the electronic health record) and obesity (body mass index [BMI]≥30 kg/m²). Main measures included self-reported cost-related barriers to medication use.

Results: A total of 21,108 patients (mean age 58.9 years, 73.6% female, 11.9% Hispanic/Latinx, 67.2% non-Hispanic White, 13.0% non-Hispanic Black, 1.5% non-Hispanic Asian, and 6.3% other) were included, with 51.7% having OAA (mean BMI of 38.6 kg/m²). Individuals with OAA had higher odds of experiencing cost-related barriers (adjusted odds ratio [aOR] range = 1.12-1.31, all P < 0.05) vs those without OAA. Despite greater affordability challenges, non-Hispanic Black (aOR = 0.82, 95% CI = 0.69-0.96, P = 0.013) and Hispanic individuals (aOR = 0.80, 95% CI = 0.65-0.98, P = 0.033) with OAA were less likely to skip medications compared with non-Hispanic White individuals. Both groups were also less likely to request lower-cost alternatives (aOR = 0.72, 95% CI = 0.64-0.82, P < 0.001; aOR = 0.65, 95% CI = 0.55-0.77, P < 0.001, respectively).

Conclusions: Significant disparities exist in cost-related barriers among individuals with OAA from different ethnic backgrounds. This highlights the need for tailored health care interventions that address the specific needs of diverse populations, aiming to reduce health disparities and improve asthma outcomes.

Drug manufacturers often use disease analogs to describe diseases-particularly rare diseases-to payers, policymakers, and stakeholders. However, these comparisons are typically anecdotal. We propose a 4-step, systematic approach to identify disease analogs based on prespecified metrics and apply it to a rare disease, pulmonary arterial hypertension (PAH), as a case study. When there is limited knowledge of a rare disease, such as PAH, the application of the systematic disease analog approach presented can help managed care pharmacists leverage their existing knowledge and perspectives applied to other conditions to inform coverage, tier placement, and pricing decisions.

Background: Capivasertib has gained US Food and Drug Administration approval in combination with a hormonal-based regimen (eg, fulvestrant) for managing hormone receptor-positive (HR+) and human epidermal growth factor receptor 2-negative (HER2-) advanced breast cancer, with results from the CapiTello-291 trial showing Capivasertib plus fulvestrant to have superior efficacy compared with fulvestrant alone.

Objective: To examine the cost-effectiveness of capivasertib plus fulvestrant vs fulvestrant alone for treating HR+/HER2- advanced breast cancer in the United States from a payer's perspective.

Methods: A Markov model of 708 participants with 3 health states (progression-free, progressive disease, death) from CapiTello-291 trial data was used to compare the costs and efficacy of the two treatment strategies on TreeAge Pro software. This model adopted a willingness-to-pay (WTP) threshold of $100,000 per quality-adjusted life-year (QALY) from a US health care perspective. A 10-year lifetime horizon with a monthly cycle length was used with a 3% discount on costs and utilities derived from previously published resources. To assess our model's uncertainty, multiple one-way sensitivity analyses and probabilistic sensitivity analyses using various distribution ranges of our model parameters were conducted.

Results: In the base model, capivasertib plus fulvestrant treatment was expected to generate an incremental 0.62 QALYs at an incremental cost of $79,117.66, which resulted in an incremental cost-effectiveness ratios of $128,283.61/QALY. Our sensitivity analysis shows that at willingness-to-pay levels of $130,000/QALY and $500,100/QALY, the likelihood of capivasertib plus fulvestrant being cost-effective compared with fulvestrant monotherapy was 50% and 100%, respectively.

Conclusions: The findings from this study suggest that adding capivasertib to fulvestrant treatment is not cost-effective when compared with fulvestrant alone, from the perspective of the US health care system. Considering the notable therapeutic impact that the inclusion of this medication in standard treatment plans can have, it is necessary to engage in more extensive talks and negotiations over the pricing of this newly approved medication.

Idiopathic hypersomnia (IH) is a chronic, neurologic disorder with a primary symptom of excessive daytime sleepiness. There are challenges to timely, accurate diagnosis of IH and, therefore, to optimal management. To better understand these challenges and identify opportunities, AMCP Market Insights virtually convened an expert panel of managed care stakeholders in April 2024. Key insights from the discussion related to addressing diagnostic challenges in IH, making coverage decisions for medications used in IH, and implementing coverage criteria for medications used in IH. Suggested payer best practices in IH also emerged from the discussion.

Background: Alectinib, brigatinib, and lorlatinib are all preferred first-line (1L) therapies for anaplastic lymphoma kinase (ALK)-positive non-small cell lung cancer (NSCLC) in National Comprehensive Cancer Network (NCCN) guidelines. Although clinical trials have demonstrated their efficacy, real-world evidence on treatment patterns, costs, and outcomes may help differentiate these therapies and inform optimal 1L treatment selection in the absence of head-to-head comparisons.

Objective: To evaluate real-world outcomes for patients with ALK+ NSCLC receiving 1L ALK tyrosine kinase inhibitors (TKIs), focusing on drug acquisition costs, health care utilization, and clinical outcomes.

Methods: This retrospective observational cohort study used data from Optum's deidentified Clinformatics Data Mart Database (2016-2021). Patients were identified using International Classification of Diseases, Tenth Revision codes for lung cancer and ALK TKI pharmacy claims. Eligible patients were aged 18 years, with at least 6 months of continuous enrollment prior to the index date and at least 1 ALK TKI prescription fill. Health care resource utilization (proxied by claim counts) and associated costs (2024 US dollars) were measured per-patient-per-month (PPPM). Time to treatment discontinuation or death (TTD) and overall survival (OS) were assessed using the Kaplan-Meier method.

Results: Among 696 patients, the 1L therapy distribution was crizotinib (n = 366), alectinib (n = 267), brigatinib (n = 22), ceritinib (n = 25), and lorlatinib (n = 16). Total PPPM costs were $28,216 (SD: $29,017). Average 30-day supply costs for ALK TKIs were $17,766 (SD: $2,797). Median OS was 25.5 months (95% CI: 21.1-32.5), and median TTD for 1L therapy was 8.0 months (95% CI: 6.4-9.6). Only 24.3% of patients transitioned to another ALK TKI in a second-line (2L) setting, highlighting high discontinuation rates. Alectinib and lorlatinib were the most common 2L therapies.

Conclusions: This study highlights the economic burden and variable clinical outcomes among patients with advanced ALK+ NSCLC. These real-world estimates inform cost-effectiveness analyses and clinical decision-making regarding treatment sequencing, particularly given uncertainty surrounding multiple preferred 1L options in clinical guidelines.

Background: US Food and Drug Administration (FDA) expedited regulatory pathways (ERPs) accelerate the availability of drugs and diagnostic tests for severe conditions and fill unmet medical needs. ERPs accelerate access to new therapeutics but also increase the uncertainty of the benefits of available treatments.

Objective: To examine how ERPs have influenced the landscape of pharmaceutical treatments for colorectal cancer (CRC), one of the most common forms of cancer in the United States.

Methods: This cross-sectional study used data from public FDA records on all CRC drug approvals before and after the passage of the FDA Safety and Innovation Act in 2012. Descriptive analyses were performed to characterize FDA approval trends by ERP. Primary outcomes included the number and timing of FDA-approved CRC drugs, the use of ERPs, outstanding postmarketing requirements, and the availability of molecular diagnostic tests associated with these treatments.

Results: Of the 24 FDA-approved CRC drugs on the market, 75% were approved through at least 1 ERP. The use of ERPs for FDA approvals increased by 18 percentage points (from 63% to 81%) pre-to-post 2012 or 30% relative to baseline. The most common pathway was Accelerated Approval, which accounted for 72% of ERP-approved drugs. CRC treatments have become increasingly targeted using molecular diagnostics, with 25% of CRC drugs approved before 2012 having associated molecular diagnostics, increasing to 75% after 2012 and 100% after 2018.

Conclusions: ERPs have expedited approvals for new and increasingly targeted CRC treatments. All CRC treatments approved through Accelerated Approval or Breakthrough Therapy Designation after 2018 still await confirmatory trial results. These findings highlight the complexity of available drugs and diagnostic tests and the challenges facing managed care pharmacists in formulary management, diagnostic test coordination, and the development of utilization criteria given limited long-term clinical evidence.

Background: Chronic diseases such as diabetes are a major burden to the US health care system. High medication adherence helps improve diabetes outcomes and reduce cost. Cost of medications can contribute to nonadherence. Use of a formulary decision support system with e-prescribing may be associated with greater use of generic medications, leading to lower costs and better adherence. A real-time prescription benefit (RTPB) solution provides patient-specific drug pricing, benefit information, and therapeutic options to choose the most cost-effective and clinically appropriate treatment.

Objectives: To examine whether RTPB is associated with increased adherence measured by proportion of days covered, higher utilization of generics, and generic dispensing rate? Is RTPB associated with lower plan and patient out-of-pocket (OOP) per-user per-month costs?

Methods: This study used a retrospective, matched intervention-control analysis of commercial health plan members from a large pharmacy benefits manager. Members were eligible for inclusion if they initiated therapy between January and August 2021. Members were excluded if they were not continuously eligible for coverage over the study period. Members who initiated diabetes therapy with a prescriber using RTPB (intervention) were compared with those new to therapy with a prescriber not using RTPB (control). Index date for both samples was the first medication prescription in the index period. Members were matched on age and sex demographics. The evaluation period lasted 12 months after index date. Multivariable linear regression models were used to assess the impact of an RTPB program on adherence and proportion of prescriptions filled with a generic. A generalized linear model (gamma distribution, log link) estimated plan and OOP patient costs, whereas a generalized linear model model with the Poisson distribution was used to estimate the number of controlling for patient age, sex, social determinants of health score, and other patient- and plan-level covariates.

Results: 1,302 matched pairs were included in the analysis. Findings show the proportion of days covered was 68.7% for control and 71.4% for RTPB members (P < 0.05). The average number of generic prescriptions for control and RTPB samples were 4.06 and 5.66, respectively (P < 0.05) and the generic dispensing rates were 44.9% and 60.1%, respectively (P < 0.05). The mean plan cost per member per month for diabetes medications, for the non-RTPB group, was 32.3% higher than the RTPB sample (a difference of $81.69, P < 0.0001) and the mean patient cost per month was 88.8% higher than the RTPB sample (a difference of $9.71, P < 0.0001).

Conclusions: Access to RTPB tools provides prescribers with formulary benefit and therapeutic options that allow them to provide the lowest-cost clinical treatment, thu

Background: Selecting a Medicare Part D prescription drug plan can be challenging because of limited health insurance literacy and complex plan features. Existing online tools, such as the Medicare Plan Finder (MPF), often lack personalization.

Objective: To describe the conceptualization and development of a personalized Medicare Part D decision aid (DA) to supplement the MPF.

Methods: A user-centered, iterative design process informed by the Ottawa Decision Support Framework and International Patient Decision Aid Standards was used to develop a DA that helps older adults with Part D plan selection. First, a literature review and 1-hour interviews with Medicare-eligible individuals informed the development of a prototype. These individuals formed a stakeholder advisory board (SAB). The first prototype was then alpha tested with 2 SAB focus groups. Using focus group feedback, the final prototype was developed. Beta testing participants, including Medicare-eligible individuals and Medicare counselors, were recruited and completed an online version of the DA, alongside pre-DA and post-DA questionnaires to examine DA effectiveness using a modified Health Insurance Literacy Measure, a modified System Usability Scale, and a user satisfaction survey.

Results: Before the development of the prototype, SAB interviewees (n = 9) suggested that simplified explanations of insurance terminology and side-by-side comparisons of options would be important to the DA. Alpha testing (n = 7) feedback was used to modify the first prototype to improve usability and clarity. Among 25 beta testing participants, Health Insurance Literacy Measure scores increased from 19.76 (SD = 7.15) before using the aid to 24.13 (SD = 4.02) afterward (P = 0.0009). Approximately one-quarter of participants indicated that they would change to a new plan after the tool, whereas half affirmed that the DA validated their existing plan choice.

Conclusions: This pilot study shows that a user-centered, interactive DA can improve health insurance literacy and support Medicare Part D plan decisions.