Outlook for tuberculosis elimination in California: An individual-based stochastic model.

RationaleAs part of the End TB Strategy, the World Health Organization calls for low-tuberculosis (TB) incidence settings to achieve pre-elimination (<10 cases per million) and elimination (<1 case per million) by 2035 and 2050, respectively. These targets require testing and treatment for latent tuberculosis infection (LTBI).ObjectivesTo estimate the ability and costs of testing and treatment for LTBI to reach pre-elimination and elimination targets in California.MethodsWe created an individual-based epidemic model of TB, calibrated to historical cases. We evaluated the effects of increased testing (QuantiFERON-TB Gold) and treatment (three months of isoniazid and rifapentine). We analyzed four test and treat targeting strategies: (1) individuals with medical risk factors (MRF), (2) non-USB, (3) both non-USB and MRF, and (4) all Californians. For each strategy, we estimated the effects of increasing test and treat by a factor of 2, 4, or 10 from the base case. We estimated the number of TB cases occurring and prevented, and net and incremental costs from 2017 to 2065 in 2015 U.S. dollars. Efficacy, costs, adverse events, and treatment dropout were estimated from published data. We estimated the cost per case averted and per quality-adjusted life year (QALY) gained.Measurements and main resultsIn the base case, 106,000 TB cases are predicted to 2065. Pre-elimination was achieved by 2065 in three scenarios: a 10-fold increase in the non-USB and persons with MRF (by 2052), and 4- or 10-fold increase in all Californians (by 2058 and 2035, respectively). TB elimination was not achieved by any intervention scenario. The most aggressive strategy, 10-fold in all Californians, achieved a case rate of 8 (95% UI 4-16) per million by 2050. Of scenarios that reached pre-elimination, the incremental net cost was $20 billion (non-USB and MRF) to$48 billion. These had an incremental cost per QALY of $657,000 to$3.1 million. A more efficient but somewhat less effective single-lifetime test strategy reached as low as $80,000 per QALY.ConclusionsSubstantial gains can be made in TB control in coming years by scaling-up current testing and treatment in non-USB and those with medical risks

Increasing the information provided by probabilistic sensitivity analysis:The relative density plot

Background Results of probabilistic sensitivity analyses (PSA) are frequently visualized as a scatterplot, which is limited through overdrawing and a lack of insight in relative density. To overcome these limitations, we have developed the Relative Density plot (PSA-ReD). Methods The PSA-ReD combines a density plot and a contour plot to visualize and quantify PSA results. Relative density, depicted using a color gradient, is transformed to a cumulative probability. Contours are then plotted over regions with a specific cumulative probability. We use two real-world case studies to demonstrate the value of the PSA-ReD plot. Results The PSA-ReD method demonstrates proof-of-concept and feasibility. In the real-world case-studies, PSA-ReD provided additional visual information that could not be understood from the traditional scatterplot. High density areas were identified by color-coding and the contour plot allowed for quantification of PSA iterations within areas of the cost-effectiveness plane, diminishing overdrawing and putting infrequent iterations in perspective. Critically, the PSA-ReD plot informs modellers about non-linearities within their model. Conclusions The PSA-ReD plot is easy to implement, presents more of the information enclosed in PSA data, and prevents inappropriate interpretation of PSA results. It gives modelers additional insight in model functioning and the distribution of uncertainty around the cost-effectiveness estimate

Reported Challenges in Health Technology Assessment of Complex Health Technologies

Objectives: With complex health technologies entering the market, methods for health technology assessment (HTA) may require changes. This study aimed to identify challenges in HTA of complex health technologies.  Methods: A survey was sent to European HTA organizations participating in European Network for HTA (EUnetHTA). The survey contained open questions and used predefined potentially complex health technologies and 7 case studies to identify types of complex health technologies and challenges faced during HTA. The survey was validated, tested for reliability by an expert panel, and pilot tested before dissemination.  Results: A total of 22 HTA organizations completed the survey (67%). Advanced therapeutic medicinal products (ATMPs) and histology-independent therapies were considered most challenging based on the predefined complex health technologies and case studies. For the case studies, more than half of the reported challenges were “methodological,” equal in relative effectiveness assessments as in cost-effectiveness assessments. Through the open questions, we found that most of these challenges actually rooted in data unavailability. Data were reported as “absent,” “insufficient,” “immature,” or “low quality” by 18 of 20 organizations (90%), in particular data on quality of life. Policy and organizational challenges and challenges because of societal or political pressure were reported by 8 (40%) and 4 organizations (20%), respectively. Modeling issues were reported least often (n = 2, 4%).  Conclusions: Most challenges in HTA of complex health technologies root in data insufficiencies rather than in the complexity of health technologies itself. As the number of complex technologies grows, the urgency for new methods and policies to guide HTA decision making increases

Regulatory reliance pathways during health emergencies: enabling timely authorizations for COVID-19 vaccines in Latin America

Objectives: To map the timing and nature of regulatory reliance pathways used to authorize COVID-19 vaccines in Latin America. Methods: An observational study was conducted assessing the characteristics of all COVID-19 vaccine authorizations in Latin America. For every authorization it was determined whether reliance was used in the authorization process. Subgroups of reference national regulatory authorities (NRAs) and non-reference NRAs were compared. Results: 56 authorizations of 10 different COVID-19 vaccines were identified in 18 countries, of which 25 (44.6%) used reliance and 12 (21.4%) did not. For the remaining 19 (33.0%) it was not possible to determine whether reliance was used. Reference agencies used reliance less often (40% of authorizations with a known pathway) compared to non-reference agencies (100%). The median review time was just 15 days and does not meaningfully differ between reliance and non-reliance authorizations. Conclusions: This study demonstrated that for these vaccines, despite reliance pathways being associated with numerous rapid authorizations, independent authorization review times were not considerably longer than reliance reviews; reliance pathways were not a prerequisite for rapid authorization. Nevertheless, reliance pathways provided rapid authorizations in response to the COVID-19 emergency

When Reality Does Not Meet Expectations-Experiences and Perceived Attitudes of Dutch Stakeholders Regarding Payment and Reimbursement Models for High-Priced Hospital Drugs

This study aimed to identify the current experiences with and future preferences for payment and reimbursement models for high-priced hospital therapies in the Netherlands, where the main barriers lie and assess how policy structures facilitate these models. A questionnaire was sent out to Dutch stakeholders (in)directly involved in payment and reimbursement agreements. The survey contained statements assessed with Likert scales, rankings and open questions. The results were analyzed using descriptive statistics. Thirty-nine stakeholders (out of 100) (in)directly involved with reimbursement decision-making completed the survey. Our inquiry showed that currently financial-based reimbursement models are applied most, especially discounts were perceived best due to their simplicity. For the future, outcome-based reimbursement models were preferred, particularly pay-for-outcome models. The main stated challenge for implementation was generating evidence in practice. According to the respondents, upfront payments are currently implemented most often, whereas delayed payment models are preferred to be applied more frequently in the future. Particularly payment-at-outcome-achieved models are preferred; however, they were stated as administratively challenging to arrange. The respondents were moderately satisfied with the payment and reimbursement system in the Netherlands, arguing that the transparency of the final agreements and mutual trust could be improved. These insights can provide stakeholders with future direction when negotiating and implementing innovative reimbursement and payment models. Attention should be paid to the main barriers that are currently perceived as hindering a more frequent implementation of the preferred models and how national policy structures can facilitate a successful implementation

Reimbursement and payment models in Central and Eastern European as well as Middle Eastern countries: A survey of their current use and future outlook

There is growing interest in innovative reimbursement and payment models in Central and Eastern European (CEE) and Middle Eastern (ME) countries. A questionnaire was sent to payers from CEE and ME countries regarding the current use of, future preferences for and perceived barriers with these models. Twenty-seven healthcare payers from 11 countries completed the survey. Results showed participants preferred using outcome-based reimbursement models and delayed payment models more often; however, currently they are rarely applied. Barriers hindering implementation were mostly related to IT and data infrastructure, measurement issues, transaction costs and the administrative burden. Given these barriers highlighted in our study, policymakers should focus on the development of an implementation framework with contract templates for the preferred reimbursement and payment schemes to aid the feasibility of a successful implementation

Real World Data in Health Technology Assessment of Complex Health Technologies

The available evidence on relative effectiveness and risks of new health technologies is often limited at the time of health technology assessment (HTA). Additionally, a wide variety in real-world data (RWD) policies exist among HTA organizations. This study assessed which challenges, related to the increasingly complex nature of new health technologies, make the acceptance of RWD most likely. A questionnaire was disseminated among 33 EUnetHTA member HTA organizations. The questions focused on accepted data sources, circumstances that allowed for RWD acceptance and barriers to acceptance. The questionnaire was validated and tested for reliability by an expert panel, and pilot-tested before dissemination via LimeSurvey. Twenty-two HTA organizations completed the questionnaire (67%). All reported accepting randomized clinical trials. The most accepted RWD source were patient registries (19/22, 86%), the least accepted were editorials and expert opinions (8/22, 36%). With orphan treatments or companion diagnostics, organizations tended to be most likely to accept RWD sources, 4.3-3.2 on a 5-point Likert scale, respectively. Additional circumstances were reported to accept RWD (e.g., a high disease burden). The two most important barriers to accepting RWD were lacking necessary RWD sources and existing policy structures. European HTA organizations seem positive toward the (wider) use of RWD in HTA of complex therapies. Expanding the use of patient registries could be potentially useful, as a large share of the organizations already accepts this source. However, many barriers still exist to the widespread use of RWD. Our results can be used to prioritize circumstances in which RWD might be accepted

A novel method for predicting the budget impact of innovative medicines:validation study for oncolytics

Background High budget impact (BI) estimates of new drugs have led to decision-making challenges potentially resulting in restrictions in patient access. However, current BI predictions are rather inaccurate and short term. We therefore developed a new approach for BI prediction. Here, we describe the validation of our BI prediction approach using oncology drugs as a case study. Methods We used Dutch population-level data to estimate BI where BI is defined as list price multiplied by volume. We included drugs in the antineoplastic agents ATC category which the European Medicines Agency (EMA) considered a New Active Substance and received EMA marketing authorization (MA) between 2000 and 2017. A mixed-effects model was used for prediction and included tumor site, orphan, first in class or conditional approval designation as covariates. Data from 2000 to 2012 were the training set. BI was predicted monthly from 0 to 45 months after MA. Cross-validation was performed using a rolling forecasting origin with e|Ln(observed BI/predicted BI)| as outcome. Results The training set and validation set included 25 and 44 products, respectively. Mean error, composed of all validation outcomes, was 2.94 (median 1.57). Errors are higher with less available data and at more future predictions. Highest errors occur without any prior data. From 10 months onward, error remains constant. Conclusions The validation shows that the method can relatively accurately predict BI. For payers or policymakers, this approach can yield a valuable addition to current BI predictions due to its ease of use, independence of indications and ability to update predictions to the most recent data

Decision making under uncertainty: comparing regulatory and health technology assessment reviews of medicines in the United States and Europe

Assessments of clinical evidence vary between regulators and health technology assessment bodies, but precise differences remain unclear. To compare uncertainties raised on the clinical evidence of approved drugs, we analyzed assessments of regulators and health technology assessment (HTA) bodies in the United States and Europe. We found that US and European regulators report uncertainties related to safety for almost all drugs (85–94%), whereas HTA bodies reported these less (53–59%). By contrast, HTA bodies raised uncertainties related to effects against relevant comparators for almost all drugs (88–100%), whereas this was infrequently addressed by regulators (12–32%). Regulators as well as HTA bodies reported uncertainties related to the patient population for 60–95% of drugs. The patterns of regulator-HTA misalignment were comparable between the United States and Europe. Our results indicate that increased coordination between these complementary organizations is necessary to facilitate the collection of necessary evidence in an efficient and timely manner

Phase I/II Clinical Trial-Based Early Economic Evaluation of Acalabrutinib for Relapsed Chronic Lymphocytic Leukaemia

Objectives: The objective of this study was to construct an early economic evaluation for acalabrutinib for relapsed chronic lymphocytic leukaemia (CLL) to assist early reimbursement decision making. Scenarios were assessed to find the relative impact of critical parameters on incremental costs and quality-adjusted life-years (QALYs). Methods: A partitioned survival model was constructed comparing acalabrutinib and ibrutinib from a UK national health service perspective. This model included states for progression-free survival (PFS), post-progression survival (PPS) and death. PFS and overall survival (OS) were parametrically extrapolated from ibrutinib publications and a preliminary hazard ratio based on phase I/II data was applied for acalabrutinib. Deterministic and probabilistic sensitivity analyses were performed, and 1296 scenarios were assessed. Results: The base-case inc