Making Drug Approval Decisions in the Face of Uncertainty: Cumulative Evidence versus Value of Information.

BACKGROUND: The COVID-19 pandemic underscored the criticality and complexity of decision making for novel treatment approval and further research. Our study aims to assess potential decision-making methodologies, an evaluation vital for refining future public health crisis responses. METHODS: We compared 4 decision-making approaches to drug approval and research: the Food and Drug Administration's policy decisions, cumulative meta-analysis, a prospective value-of-information (VOI) approach (using information available at the time of decision), and a reference standard (retrospective VOI analysis using information available in hindsight). Possible decisions were to reject, accept, provide emergency use authorization, or allow access to new therapies only in research settings. We used monoclonal antibodies provided to hospitalized COVID-19 patients as a case study, examining the evidence from September 2020 to December 2021 and focusing on each method's capacity to optimize health outcomes and resource allocation. RESULTS: Our findings indicate a notable discrepancy between policy decisions and the reference standard retrospective VOI approach with expected losses up to $269 billion USD, suggesting suboptimal resource use during the wait for emergency use authorization. Relying solely on cumulative meta-analysis for decision making results in the largest expected loss, while the policy approach showed a loss up to $16 billion and the prospective VOI approach presented the least loss (up to $2 billion). CONCLUSION: Our research suggests that incorporating VOI analysis may be particularly useful for research prioritization and treatment implementation decisions during pandemics. While the prospective VOI approach was favored in this case study, further studies should validate the ideal decision-making method across various contexts. This study's findings not only enhance our understanding of decision-making strategies during a health crisis but also provide a potential framework for future pandemic responses. HIGHLIGHTS: This study reviews discrepancies between a reference standard (retrospective VOI, using hindsight information) and 3 conceivable real-time approaches to research-treatment decisions during a pandemic, suggesting suboptimal use of resources.Of all prospective decision-making approaches considered, VOI closely mirrored the reference standard, yielding the least expected value loss across our study timeline.This study illustrates the possible benefit of VOI results and the need for evidence accumulation accompanied by modeling in health technology assessment for emerging therapies.

Second-Line Chimeric Antigen Receptor T-Cell Therapy in Diffuse Large B-Cell Lymphoma : A Cost-Effectiveness Analysis.

BACKGROUND: First-line treatment of diffuse large B-cell lymphoma (DLBCL) achieves durable remission in approximately 60% of patients. In relapsed or refractory disease, only about 20% achieve durable remission with salvage chemoimmunotherapy and consolidative autologous stem cell transplantation (ASCT). The ZUMA-7 (axicabtagene ciloleucel [axi-cel]) and TRANSFORM (lisocabtagene maraleucel [liso-cel]) trials demonstrated superior event-free survival (and, in ZUMA-7, overall survival) in primary-refractory or early-relapsed (high-risk) DLBCL with chimeric antigen receptor T-cell therapy (CAR-T) compared with salvage chemoimmunotherapy and consolidative ASCT; however, list prices for CAR-T exceed $400 000 per infusion. OBJECTIVE: To determine the cost-effectiveness of second-line CAR-T versus salvage chemoimmunotherapy and consolidative ASCT. DESIGN: State-transition microsimulation model. DATA SOURCES: ZUMA-7, TRANSFORM, other trials, and observational data. TARGET POPULATION: "High-risk" patients with DLBCL. TIME HORIZON: Lifetime. PERSPECTIVE: Health care sector. INTERVENTION: Axi-cel or liso-cel versus ASCT. OUTCOME MEASURES: Incremental cost-effectiveness ratio (ICER) and incremental net monetary benefit (iNMB) in 2022 U.S. dollars per quality-adjusted life-year (QALY) for a willingness-to-pay (WTP) threshold of $200 000 per QALY. RESULTS OF BASE-CASE ANALYSIS: The increase in median overall survival was 4 months for axi-cel and 1 month for liso-cel. For axi-cel, the ICER was $684 225 per QALY and the iNMB was -$107 642. For liso-cel, the ICER was $1 171 909 per QALY and the iNMB was -$102 477. RESULTS OF SENSITIVITY ANALYSIS: To be cost-effective with a WTP of $200 000, the cost of CAR-T would have to be reduced to $321 123 for axi-cel and $313 730 for liso-cel. Implementation in high-risk patients would increase U.S. health care spending by approximately $6.8 billion over a 5-year period. LIMITATION: Differences in preinfusion bridging therapies precluded cross-trial comparisons. CONCLUSION: Neither second-line axi-cel nor liso-cel was cost-effective at a WTP of $200 000 per QALY. Clinical outcomes improved incrementally, but costs of CAR-T must be lowered substantially to enable cost-effectiveness. PRIMARY FUNDING SOURCE: No research-specific funding.

Cost-effectiveness of postoperative imaging surveillance strategies for nonfunctional pituitary adenomas after resection with curative intent.

OBJECTIVE: The aim of this study was to determine an optimal follow-up imaging surveillance strategy in terms of cost-effectiveness after resection of nonfunctioning pituitary adenomas with curative intent. METHODS: An individual-level state-transition microsimulation model was used to simulate costs and outcomes associated with three postoperative imaging strategies over a lifetime time horizon: 1) annual MRI surveillance, 2) tapered MRI surveillance (annual surveillance for 5 years followed by surveillance every 2 years), and 3) personalized surveillance (annual surveillance for 5 years followed by surveillance every 2 years when MRI shows remnant disease/postoperative changes, and surveillance at 7, 10, and 15 years for disease-free MRI). Transition probabilities, utilities, and costs were estimated from recent published data and discounted by 3% annually. Model outcomes included lifetime costs (2022 US dollars), quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios (ICERs). RESULTS: Under base case assumptions, annual surveillance yielded higher costs and lower health effects (QALYs) compared with the tapered and personalized surveillance strategies (dominated). Personalized surveillance demonstrated an additional 0.1 QALY at additional cost ($1298) compared with tapered surveillance (7.7 QALYs at a cost of $12,862). The ICER was $11,793/QALY. The optimal decision was most sensitive to the probability of postoperative changes on MRI after surgery and MRI cost. Accounting for parameter uncertainty, personalized surveillance had a higher probability of being a cost-effective surveillance option compared with the alternative strategies at 79%. CONCLUSIONS: Using standard cost-effectiveness thresholds in the US ($100,000/QALY), personalized surveillance that accounted for remnant disease or postoperative changes on MRI was cost-effective compared with alternative surveillance strategies.

Emerging Therapies for COVID-19: The Value of Information From More Clinical Trials.

OBJECTIVES: The COVID-19 pandemic necessitates time-sensitive policy and implementation decisions regarding new therapies in the face of uncertainty. This study aimed to quantify consequences of approving therapies or pursuing further research: immediate approval, use only in research, approval with research (eg, emergency use authorization), or reject. METHODS: Using a cohort state-transition model for hospitalized patients with COVID-19, we estimated quality-adjusted life-years (QALYs) and costs associated with the following interventions: hydroxychloroquine, remdesivir, casirivimab-imdevimab, dexamethasone, baricitinib-remdesivir, tocilizumab, lopinavir-ritonavir, interferon beta-1a, and usual care. We used the model outcomes to conduct cost-effectiveness and value of information analyses from a US healthcare perspective and a lifetime horizon. RESULTS: Assuming a $100 000-per-QALY willingness-to-pay threshold, only remdesivir, casirivimab-imdevimab, dexamethasone, baricitinib-remdesivir, and tocilizumab were (cost-) effective (incremental net health benefit 0.252, 0.164, 0.545, 0.668, and 0.524 QALYs and incremental net monetary benefit $25 249, $16 375, $54 526, $66 826, and $52 378). Our value of information analyses suggest that most value can be obtained if these 5 therapies are approved for immediate use rather than requiring additional randomized controlled trials (RCTs) (net value $20.6 billion, $13.4 billion, $7.4 billion, $54.6 billion, and $7.1 billion), hydroxychloroquine (net value $198 million) is only used in further RCTs if seeking to demonstrate decremental cost-effectiveness and otherwise rejected, and interferon beta-1a and lopinavir-ritonavir are rejected (ie, neither approved nor additional RCTs). CONCLUSIONS: Estimating the real-time value of collecting additional evidence during the pandemic can inform policy makers and clinicians about the optimal moment to implement therapies and whether to perform further research.