Value in Health最新文献

Objectives

The results of a recent single-arm trial (ZUMA-5) of axicabtagene ciloleucel (axi-cel) for relapsed/refractory (r/r) follicular lymphoma (FL) demonstrated high rates of durable response and tolerable toxicity among treated patients. To quantify the value of axi-cel compared with standard of care (SOC) to manage r/r FL patients who have had at least 2 prior lines of systemic therapy (3L+), a cost-effectiveness model was developed from a US third-party payer perspective.

Methods

A 3-state partitioned-survival cost-effectiveness model was developed with a lifetime horizon. Patient-level analyses of the 36-month ZUMA-5 (axi-cel) and SCHOLAR-5 (SOC) studies were used to extrapolate progression-free and overall survivals. After 5 years of survival, an estimated 40% of the modeled population was assumed to experience long-term remission based on literature. Results include the incremental cost-effectiveness ratio (ICER) measured as incremental cost per quality-adjusted life year (QALY) gained. One-way sensitivity analysis, probabilistic sensitivity analysis, and scenario analyses were performed. All outcomes were discounted 3% per year.

Results

Axi-cel led to an increase of 4.28 life-years, 3.64 QALYs, and a total cost increase of $321 192 relative to SOC, resulting in an ICER of $88 300 per QALY. Across all parameters varied in the one-way sensitivity analysis, the ICER varied between $133 030 and $67 277. In the probabilistic sensitivity analysis, axi-cel had a 99% probability of being cost-effective across 5000 iterations using a $150 000 willingness-to-pay threshold.

Conclusions

Given the robustness of the model results and sensitivity analyses, axi-cel is expected to be a cost-effective treatment in 3L+ r/r FL.

Objectives

The primary focus of this research is the proposition of a methodological framework for the clinical application of the long COVID symptoms and severity score (LC-SSS). This tool is not just a self-reported assessment instrument developed and validated but serves as a standardized, quantifiable means to monitor the diverse and persistent symptoms frequently observed in individuals with long COVID.

Methods

A 3-stage process was used to develop, validate, and establish scoring standards for the LC-SSS. Validation measures included correlations with other patient-reported measures, confirmatory factor analysis, Cronbach’s α for internal consistency, and test-retest reliability. Scoring standards were determined using K-means clustering, with comparative assessments made against hierarchical clustering and the Gaussian Mixture Model.

Results

The LC-SSS showed correlations with EuroQol 5-Dimension 5-Level (r_s = −0.55), EuroQol visual analog scale (r_s = −0.368), Patient Health Questionnaire-9 (r_s = 0.538), Beck Anxiety Inventory (r_s = 0.689), and Insomnia Severity Index (r_s = 0.516), confirming its construct validity. Structural validity was good with a comparative fit index of 0.969, with Cronbach’s α of 0.93 indicating excellent internal consistency. Test-retest reliability was also satisfactory (intraclass correlation coefficient 0.732). K-means clustering identified 3 distinct severity categories in individuals living with long COVID, providing a basis for personalized treatment strategies.

Conclusions

The LC-SSS provides a robust and valid tool for assessing long COVID. The severity categories established via K-means clustering demonstrate significant variation in symptom severity, informing personalized treatment and improving care quality for patients with long COVID.

Objectives

Between 2013 to 2019, several all-oral direct-acting antivirals (DAAs) were launched with the potential to cure patients with hepatitis C virus (HCV). They generated economic value in terms of the health gains for patients and cost-savings for the US healthcare system. We estimated the share of this value allocated to 4 manufacturers vs society.

Methods

For 2015 to 2019, we estimated the incremental impact of DAAs on HCV health outcomes and costs. We used the Center for Disease Analysis Foundation Polaris Observatory database to estimate utilization. Per-patient projections of lifetime quality-adjusted life-years (QALYs) gained and medical costs avoided were based on a standard 9-state HCV disease-progression model for DAA treatment vs alternatives. Annual QALY gains were valued at $114 000 per QALY. Outcomes and costs were discounted at 3%. Estimated revenues were based on reported sales.

Results

An estimated 1 080 000 patients received DAAs: 81.5% would not have received the pre-DAA standard of care. On average, these patients were projected to gain 4.4 QALYs and save $104 400 in lifetime healthcare costs, generating $531.8 billion in value. Those who would have received treatment gained 1.7 QALYs and saved $41 500 in lifetime costs, generating $47.4 billion in economic value. As treatment costs fell nearly 75%, the 4 manufacturers reported $37.4 billion from DAA sales—an allocation of 6.5% of the total value.

Conclusions

The significant majority (∼90%) of the economic value of curing HCV with DAAs were health benefits to patients and net cost-savings to society. DAA manufacturers received a minority share (6.5%) of the aggregate economic value generated.

Objectives

We compared the Institute for Clinical and Economic Review’s (ICER) ratings of comparative clinical effectiveness with the German Federal Joint Committee’s (G-BA) added benefit ratings, and explored what factors may explain the disagreement between the 2 organizations.

Methods

We included drugs if they were assessed by ICER under its 2020 to 2023 Value Assessment Framework and had a corresponding assessment by G-BA as of January 2024 for the same indication, patient population, and comparator drug. To compare assessments, we modified ICER’s proposed crosswalk between G-BA and ICER benefit ratings to account for G-BA’s certainty ratings. We also determined whether each pair was based on similar evidence. Assessment pairs exhibiting disagreement based on the modified crosswalk despite a similar evidence base were qualitatively analyzed to identify reasons for disagreement.

Results

Out of 15 drug assessment pairs matched on indication, patient subgroup, and comparator, none showed agreement in their assessments when based on similar evidence. Disagreement was attributed to differences in evidence evaluation, including evaluations of safety, generalizability, and study design, as well as G-BA’s rejection of the available evidence in 4 cases as unsuitable.

Conclusions

The findings demonstrate that even under conditions where populations and comparators are identical and the evidence base is consistent, different assessors may arrive at divergent conclusions about comparative effectiveness, thus underscoring the presence of value judgments within assessments of clinical effectiveness. To support initiatives that seek to facilitate the exchange of value assessments between countries, these value judgments should always be transparently presented and justified in assessment summaries.

Objectives

To quantify health fluctuations, identify affected health-related quality of life (HRQoL) dimensions, and evaluate if fluctuations affect the HRQoL instruments recall period adherence in people living with dementia (PlwD).

Methods

Caregivers of PlwD completed a daily diary for 14 days, documenting if PlwD’s health was better or worse than the day before and the affected HRQoL dimensions. Health fluctuation was categorized into low (0-4 fluctuations in 14 days), moderate (5-8), and high (9-14). Also, caregivers and PlwD completed the EQ-5D-5L (proxy- and self-reported) on days 1, 7, and 14. Subsequently, caregivers were interviewed to determine whether recurrent fluctuations were considered in the EQ-5D-5L assessment of today’s health (recall period adherence).

Results

Fluctuations were reported for 96% of PlwD, on average, for 7 of the 14 days. Dimensions most frequently triggering fluctuations included memory, mobility, concentration, sleep, pain, and usual activities. Fluctuations were associated with higher EQ-5D-5L health-states variation and nonadherence to the EQ-5D-5L recall period “today.” PlwD with moderate to high fluctuation had the highest EQ-5D-5L utility change between day 1 and 14 (0.157 and 0.134) and recall period nonadherence (31% and 26%) compared with PlwD with low fluctuation (0.010; 17%). Recall period nonadherence was higher in PlwD with improved compared with those with deteriorated health in the diary (37% vs 9%).

Conclusions

Health fluctuations frequently occur in dementia and strongly affect HRQoL assessments. Further research is needed to evaluate if more extended recall periods and multiple, consecutive assessments could capture health fluctuations more appropriately in dementia.

Objectives

Health economic (HE) models are often considered as “black boxes” because they are not publicly available and lack transparency, which prevents independent scrutiny of HE models. Additionally, validation efforts and validation status of HE models are not systematically reported. Methods to validate HE models in absence of their full underlying code are therefore urgently needed to improve health policy making.

This study aimed to develop and test a generic dashboard to systematically explore the workings of HE models and validate their model parameters and outcomes.

Methods

The Probabilistic Analysis Check dashBOARD (PACBOARD) was developed using insights from literature, health economists, and a data scientist.

Functionalities of PACBOARD are (1) exploring and validating model parameters and outcomes using standardized validation tests and interactive plots, (2) visualizing and investigating the relationship between model parameters and outcomes using metamodeling, and (3) predicting HE outcomes using the fitted metamodel.

To test PACBOARD, 2 mock HE models were developed, and errors were introduced in these models, eg, negative costs inputs, utility values exceeding 1. PACBOARD metamodeling predictions of incremental net monetary benefit were validated against the original model’s outcomes.

Results

PACBOARD automatically identified all errors introduced in the erroneous HE models. Metamodel predictions were accurate compared with the original model outcomes.

Conclusions

PACBOARD is a unique dashboard aiming at improving the feasibility and transparency of validation efforts of HE models. PACBOARD allows users to explore the working of HE models using metamodeling based on HE models’ parameters and outcomes.