The impact of the Oncotype Dx (ODX) breast cancer assay on adjuvant chemotherapy (ACT) treatment decisions has been evaluated in many previous studies. However, it can be difficult to interpret the ...collective findings, which were conducted in diverse settings with limited sample sizes. We conducted a systematic review and meta-analysis to synthesize the results and provide insights about ODX utility. Studies, identified from PubMed, Embase, ASCO, and SABCS, were included if patients had ER+, node −, early-stage breast cancer, reported use of ODX to inform actual ACT decisions. Information was summarized and pooled according to: (1) distribution of ODX recurrence scores (RS), (2) impact of ODX on ACT recommendations, (3) impact of ODX on ACT use, and (4) proportion of patients following the treatment suggested by the ODX RS. A total of 23 studies met inclusion criteria. The distribution of RS categories was 48.8 % low, 39.0 % intermediate, and 12.2 % high (21 studies, 4,156 patients). ODX changed the clinical-pathological ACT recommendation in 33.4 % of patients (8 studies, 1,437 patients). In patients receiving ODX, receipt of ACT were: 28.2 % overall, 5.8 % low, 37.4 % intermediate, and 83.4 % high. High RS patients were significantly more likely to follow the treatment suggested by ODX versus low RS patients RR: 1.07 (1.01–1.14). The pooled results are consistent with most individual studies to date. The increased proportion of intermediate scores relative to original estimates may have implications for the clinical utility and cost impacts of testing. In addition, low versus high RS patients were significantly more likely to follow the ODX results, suggesting a tendency toward less aggressive treatment, despite a high ODX RS. Finally, there was a lack of studies on the impact of ODX on ACT use versus standard approaches, suggesting that additional studies are warranted.
The Institute for Clinical and Economic Review (ICER) has gained recognition for performing independent health technology assessments (HTAs) that include the cost-effectiveness of selected new ...technologies in the United States. ICER has similarities with the National Institute for Health and Care Excellence (NICE) in England and Wales, but the amount of overlap and new methods adopted to meet stakeholder needs in the complex U.S. health care system have not been fully analyzed.
To perform a comprehensive comparison of ICER and NICE.
We compared ICER and NICE using the same framework as Drummond et al. (2008), which suggests 4 dimensions for comparison of HTA organizations: structure of HTA programs, methods of HTA, processes for conduct of HTA, and use of HTAs in decision making.
We found differences between ICER and NICE in the structure of HTA programs (setup of the organizations, governance issues, and funding); methods (perspective, costs, utilities, discounting, and thresholds); process (relationship with relevant stakeholders, deliberative decision-making processes, and timelines); and the use of HTA in decision making (the format and type of evidence generated, how the evidence is considered, and the format of the recommendations).
ICER uses a different approach for clinical review but performs cost-effectiveness analysis using methods similar to NICE. The key differences between NICE and ICER arise because of important differences between the United Kingdom's "single payer" health care system and the United States's pluralistic system. ICER's lack of mandatory power translates to substantial differences in terms of its processes and type of recommendations.
No outside funding supported this study. Thokala has received grants from the Institute for Clinical and Economic Review (ICER) for modeling projects. Carlson has received grants from ICER, unrelated to this study. Drummond has nothing to disclose.
Enthusiasm for performance-based risk-sharing arrangements (PBRSAs) continues but at variable pace across countries. Our objective was to identify and characterize publicly available cases and ...related trends for these arrangements. We performed a review of PBRSAs from 1993 to 2016 using the University of Washington PBRSA Database. Arrangements were categorized according to a previously published taxonomy. Macro-level trends were identified related to the timing of adoption, countries involved, types of arrangements, and disease areas. Our search yielded 437 arrangements. Among these, 183 (41.9%) were categorized as currently active, while 58.1% have expired. Five main types of arrangements have been identified, namely coverage with evidence development (149 cases, 34.1%), performance-linked reimbursement (104 cases, 23.8%), conditional treatment continuation (78 cases, 17.8%), financial or utilization (71 cases, 16.2%), and hybrid schemes with multiple components (35 cases, 8.0%). The pace of adoption varies across countries but has renewed an upward trend after a lull in 2012/2013. Conditions in the USA may be changing toward a more favorable environment of PBRSAs. Interest in PBRSAs remains high, suggesting they are a viable coverage and reimbursement mechanism for a wide range of medical products.
Performance-based risksharing arrangements (PBRSAs) have continued to emerge and evolve over the last 2 decades. To date, most of the attention and available literature have focused on ...pharmaceuticals.
To assess the current status and trends regarding the use of PBRSAs for diagnostics and devices in the United States.
We reviewed publicly available PBRSAs for diagnostics and devices using the University of Washington Performance Based Risk Sharing Database. We augmented the review using PubMed, Google, and payer and industry websites. Key words and phrases such as
and
were used in combination with
or
To characterize arrangements in terms of product and market attributes, we extracted data for each product, including arrangement descriptions, arrangement type, year, therapeutic area, product manufacturer, payer, and product type. Arrangements were analyzed using descriptive statistics.
Fifty-two arrangements were identified between the years 2001 and 2019, with 30 (57.7%) for devices and 22 (42.3%) for diagnostic tests. Among these, 23 (44.2%) were coverage with evidence development (CED), only in research; 17 (32.7%) were performance-linked reimbursement (PLR); and 12 (23.1%) were CED, only with research. The majority of arrangements for devices were developed in cardiology (12, 40%), endocrinology (4, 13.3%), and radiology (3, 10%). Most of arrangements for identified diagnostic tests were in oncology (17, 77.3%). Over time, there has been a trend towards increasing adoption of PLR and CED, only with research, especially since 2014.
This is the first study to comprehensively review PBRSA arrangements for diagnostics and devices in the United States. Our findings demonstrated that there is substantial PBRSA activity for devices and diagnostics, and the pace of PBRSA adoption appears to be increasing in terms of frequency and variety. These arrangements have implications for managed care into the future as the health care system shifts towards value-based care and value-based pricing to contain cost for payers and ensure value in the patient populations.
No funding supported this study. The authors have nothing to disclose.
This systematic review aims to summarize and qualitatively assess published evaluations on the US public’s preferences for health equity and their willingness to trade-off efficiency for equity.
...Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses literature search extension guidelines, we searched MEDLINE and Embase for relevant peer-reviewed publications on this topic before February 2021. We included English-language articles that solicited US preferences regarding efficiency-equity trade-offs and prioritizing healthcare resources based on socioeconomic status, race, disability, or burden of disease. Quantitative and qualitative data captured were decided a priori and iteratively adapted as themes emerged.
Fourteen studies were found over a 25-year span. Only 4 focused on resource allocation across social groups. Three distinct notions of fairness were studied: equal distribution of resources, priority to the worse-off, and equal health achieved. We found modest support for equal distribution of resources and willingness to sacrifice efficiency for equity in the United States. Prioritizing the underserved was relatively less studied and received less support and was more preferred when resources were scarce, when allocating resources between social groups, or when participants were informed about the fundamental origins of health inequities. Equal health was the least studied, but received nontrivial support.
The existing literature evaluating the US public’s understanding and preferences toward equity was severely limited by the lack of rigorous quantitative studies and heterogeneous attribute selection and fairness definitions. High-quality studies that clearly define fairness, focus on social groups, and apply rigorous methods to quantify equity preferences are needed to integrate the public’s value on equity into healthcare decisions.
•There is a demand to formally incorporate societal preferences for health equity in healthcare decision making in the United States. Nevertheless, it is unclear what health equity means to the US public and to what extent the US public values equity in health.•This systematic review summarized and qualitatively assessed studies that evaluated the preference for health equity in the United States and found some evidence that Americans were willing to sacrifice efficiency to achieve more equitable distributions of health in varying degrees.•More high-quality studies are needed to generate equity estimates that can be incorporated into traditionally efficiency-driven healthcare decision frameworks.
The rise in pharmaceutical expenditures in recent years has increased health care payer interest in ensuring good value for the money. Indication-based pricing (IBP) sets separate, ...indication-specific prices paid to the manufacturer according to the expected efficacy of a drug in each of its indications. IBP allows payers to consistently pay for value across indications. While promising, a limitation of IBP as originally conceived is that efficacy estimates are typically based on clinical trial data, which may differ from real-world effectiveness. An outcomes guarantee is a type of performance-based risk-sharing arrangement that adjusts payments according to prospectively tracked outcomes. We suggest that an outcomes guarantee contract, which has been used by some payers, may be adapted to achieve indication-based prices supported by real-world effectiveness.
To illustrate the potential of an outcomes guarantee to achieve indication-based prices aligned with real-world value, using a case study of trastuzumab for the treatment of metastatic breast and advanced gastric cancers.
We estimated costs and outcomes under traditional IBP (i.e., expected value IBP) and outcomes guarantee frameworks and calculated incremental cost-effectiveness ratios (ICERs) comparing treatment with and without trastuzumab. Efficacy data came from pivotal trials, whereas effectiveness data came from observational studies. We adjusted trastuzumab prices in order to achieve target ICERs of $150,000 per quality-adjusted life-year under each framework and for each indication.
To achieve the ICER target under traditional IBP, the unit price of trastuzumab using efficacy evidence was adjusted for metastatic breast and advanced gastric cancers from an average sales price of $9.17 per mg to $3.50 per mg and $0.93 per mg, respectively. Under an outcomes guarantee, the unit price of trastuzumab using effectiveness evidence was adjusted for metastatic breast cancer and advanced gastric cancer to $8.66 per mg and $0.20 per mg, respectively.
Like expected value IBP, outcomes guarantee contracts can also vary payment based on indication. In addition, an outcomes guarantee can also reduce uncertainty regarding effectiveness and better align payment with the actual value of a treatment.
No funding supported this study. Carlson reports consulting fees from Genentech, Pfizer, and Seattle Genetics. The other authors have no conflicts of interest to disclose. Study concept and design were contributed by Carlson, Yeung, and Li. Yeung, Carlson, and Li collected and analyzed the data. The manuscript was written primarily by Yeung, along with Carlson and Li, and revised by all the authors.
As genome sequencing becomes better integrated into scientific research, government policy, and personalized medicine, the primary challenge for researchers is shifting from generating raw data to ...analyzing these vast datasets. Although much work has been done to reduce compute times using various configurations of traditional CPU computing infrastructures, Graphics Processing Units (GPUs) offer opportunities to accelerate genomic workflows by orders of magnitude. Here we benchmark one GPU-accelerated software suite called NVIDIA Parabricks on Amazon Web Services (AWS), Google Cloud Platform (GCP), and an NVIDIA DGX cluster. We benchmarked six variant calling pipelines, including two germline callers (HaplotypeCaller and DeepVariant) and four somatic callers (Mutect2, Muse, LoFreq, SomaticSniper).
We achieved up to 65 × acceleration with germline variant callers, bringing HaplotypeCaller runtimes down from 36 h to 33 min on AWS, 35 min on GCP, and 24 min on the NVIDIA DGX. Somatic callers exhibited more variation between the number of GPUs and computing platforms. On cloud platforms, GPU-accelerated germline callers resulted in cost savings compared with CPU runs, whereas some somatic callers were more expensive than CPU runs because their GPU acceleration was not sufficient to overcome the increased GPU cost.
Germline variant callers scaled well with the number of GPUs across platforms, whereas somatic variant callers exhibited more variation in the number of GPUs with the fastest runtimes, suggesting that, at least with the version of Parabricks used here, these workflows are less GPU optimized and require benchmarking on the platform of choice before being deployed at production scales. Our study demonstrates that GPUs can be used to greatly accelerate genomic workflows, thus bringing closer to grasp urgent societal advances in the areas of biosurveillance and personalized medicine.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Assessing the value of tumor-agnostic drugs (TAD) is challenging given the potential variability in treatment effects, trials with small sample sizes, different standards of care (SoC), and lack of ...comparative data from single-arm basket trials. Our study developed and applied novel methods to assess the value of pembrolizumab compared with SoC to inform coverage decisions.
We developed a partitioned survival model to evaluate the cost-utility of pembrolizumab for previously treated patients with 8 advanced or metastatic microsatellite instability-high or mismatch repair-deficient cancers from a US commercial payer perspective. Efficacy of pembrolizumab was based on data from trials directly or with adjustment using Bayesian hierarchical models. Eight chemotherapy-based external control arms were constructed from the TriNetX electronic health record databases. Tumor-specific health-state utility values were applied. All costs were adjusted to 2022 US dollars.
At a lifetime horizon, pembrolizumab was associated with increased effectiveness compared with chemotherapies in colorectal (quality-adjusted life years QALYs: +0.64, life years LYs: +0.64), endometrial (QALYs: +3.79, LYs: +5.47), and small intestine cancers (QALYs: +1.73, LYs: +2.48), but not for patients with metastatic gastric, cholangiocarcinoma, pancreatic, ovarian, and brain cancers. Incremental cost-effectiveness ratios varied substantially across tumor types. Pembrolizumab was found to be cost-effective in treating colorectal and endometrial cancers (incremental cost-effectiveness ratios: $121 967 and $139 257, respectively), and not cost-effective for other assessed cancers at a $150 000 willingness-to-pay/QALY threshold, compared with SoC chemotherapies.
The cost-effectiveness of TADs can vary by cancers. Using analytic tools such as external controls and Bayesian hierarchical models can tackle several challenges in assessing the value of TADs and uncertainties from basket trials.
•Tumor-agnostic or histology-independent therapies have the potential to greatly benefit patients with limited therapeutic alternatives. Health technology assessment (HTA) agencies across health systems have detailed major challenges for value assessments of tumor-agnostic drugs, such as the potential for heterogeneity in treatment effect, the lack of comparative data due to single-arm studies, variable standards of care (SoC) across tumor types, and large uncertainty in the evidence base available to inform coverage and reimbursement decisions.•This cost-effectiveness analysis of pembrolizumab against SoC chemotherapies in 8 microsatellite instability-high or mismatch repair-deficient metastatic cancers demonstrated varying incremental cost-effectiveness ratios across tumor types. Pembrolizumab was found to be cost-effective for previously treated colorectal and endometrial cancers, but not for other evaluated cancers, when compared to SoC chemotherapies, using a $150 000 willingness-to-pay/quality-adjusted life years threshold.•We demonstrated the potential to address several challenges in using evidence from single-arm basket trials in HTA by leveraging Bayesian Hierarchical Modeling approach and real-world data-based external controls. This approach informs future HTA methodology development and payer coverage decisions for tumor-agnostic indications.
Healthcare payers often implement coverage policies that restrict the utilization of costly new first-line treatments. Cost-effectiveness analysis can be conducted to inform these decisions by ...comparing the new treatment with an existing one. However, this approach may overlook important factors such as treatment effect heterogeneity and endogenous treatment selection, policy implementation costs, and diverse patient preferences across multiple treatment options. We aimed to develop a cost-effectiveness analysis framework that considers these real-world factors, facilitating the evaluation of alternative policies related to expanding or restricting first-line treatment choices.
We introduced a metric of incremental cost-effectiveness ratio (ICER) that compares an expanded choice set (CS) including the new first-line treatment with a restricted CS excluding the new treatment. ICER(CS) accounts for treatment selection influenced by heterogeneous treatment effects and policy implementation costs. We examined a basic scenario with 2 standard first-line treatment choices and a more realistic scenario involving diverse preferences toward multiple choices. To illustrate the framework, we conducted a retrospective evaluation of including versus excluding abiraterone acetate plus prednisone (AAP) (androgen deprivation therapy ADT + AAP) as a first-line treatment for metastatic hormone-sensitive prostate cancer.
The traditional ICERs for ADT + AAP versus ADT alone and ADT+ docetaxel were $104 269 and $206 324/quality-adjusted life-year, respectively. The ICER(CS) for comparing an expanded CS with ADT + AAP with a restricted CS without ADT + AAP was $123 179/quality-adjusted life-year.
The proposed framework provides decision makers with policy-relevant tools, enabling them to assess the cost-effectiveness of alternative policies of expanding versus restricting patients’ and physicians’ first-line treatment choices.
•Traditional cost-effectiveness analysis (CEA) may have limitations in evaluating the cost-effectiveness of alternative coverage policies that consider the inclusion or restriction of new treatment options. To overcome these limitations, we have developed a general framework that enables a comparison between expanded and restricted choice sets, analogous to comparing coverage policies.•The framework explicitly incorporates critical real-world factors, including heterogeneous treatment effects and endogenous treatment selection, policy implementation costs, and differential patient preferences toward multiple treatment options. The empirical case study demonstrates that the proposed framework can yield significantly different cost-effectiveness estimate compared with traditional CEA when these factors are considered.•Given that there is a growing interest in integrating CEA into value-based insurance design, our framework provides valuable insights for designing insurance policies that effectively reflect the value of innovative first-line treatments for patients.
Background
A limited evidence base and lack of clear clinical guidelines challenge healthcare systems’ adoption of precision medicine. The effect of these conditions on demand is not understood.
...Objective
This research estimated the public’s preferences and demand for precision medicine outcomes.
Methods
A discrete-choice experiment survey was conducted with an online sample of the US public who had recent healthcare experience. Statistical analysis was undertaken using an error components mixed logit model. The responsiveness of demand in the context of a changing evidence base was estimated through the price elasticity of demand. External validation was examined using real-world demand for the 21-gene recurrence score assay for breast cancer.
Results
In total, 1124 (of 1849) individuals completed the web-based survey. The most important outcomes were survival gains with statistical uncertainty, cost of testing, and medical expert agreement on changing care based on test results. The value ($US, year 2017 values) for a test where most (vs. few) experts agreed to changing treatment based on test results was $US1100 (95% confidence interval CI 916–1286). Respondents were willing to pay $US265 (95% CI 46–486) for a test that could result in greater certainty around life-expectancy gains. The predicted demand of the assay was 9% in 2005 and 66% in 2014, compared with real-world uptake of 7% and 71% (root-mean-square prediction error 0.11). Demand was sensitive to price (1% increase in price resulted in > 1% change in demand) when first introduced and insensitive to price (1% increase in price resulted in < 0.1% change in demand) as the evidence base became established.
Conclusions
Evidence of external validity was found. Demand was weak and responsive to price in the near term because of uncertainty and an immature evidence base. Clear communication of precision medicine outcomes and uncertainty is crucial in allowing healthcare to align with individual preferences.
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