bluuebunny/crossref_metadata_2025_split huggingface dataset:
PP13 Development Of Recommendations And Proposal For A Value-Based Managed Entry Agreement For Italian Setting
Authors: Cicchetti Americo , Xoxi Entela , Rumi Filippo 
Published: December 2022

IntroductionThe continuous and pressing challenge that the drug regulatory authorities in Italy and in Europe are facing is that of guaranteeing patients’ quick access to new drugs, ensuring the economic sustainability of the system at the same time. In recent years, flexible and diversified approaches have been developed known as Managed Entry Agreements (MEA).MethodsWe performed an analysis of the Italian legislative and regulatory aspects in reference to a new Value-based Managed Entry Agreement (VBMEA) pathway. Thus, we tried to investigate the rationale for a new pathway analyzing three main dimensions related to the new medical product (MP): value; time to entry access; and, data quality and registry design. Moreover, we shared the discussion of the proposal with an international experts’ panel.ResultsThe proposal for a new pathway of VBMEA from a procedural point of view shows the novelty related to the possibility to organize joint CTS (Technical Scientific Committee) and CPR (Price and Reimbursement Committee) assessment. A 24-month contract with an ex-factory price (PP) equal to X EUR per dose and a transfer price to the National Public Health System (NPHS), following application of a confidential discount for public structures (-X%), of X EUR per dose. After 24-months, an analysis of VBMEA is carried out. The price of the MP is therefore established based on AIFA registries and VBMEA results. The cost value incurred by the NPHS, intended as the difference between the price in market (entry) access phase and the price negotiated (PVB) in the light of the VBMEA results, shall be returned by the pharmaceutical company in the form of a payback.ConclusionsCurrently, MEAs represent one of the main topics of discussion between the European National Payers Authorities. There is very little information on product performance that results from MEAs. This research project could provide advice to policy makers to decrease negotiation time by ensuring earlier access to innovation for patients.
PP15 The National Pricing And Reimbursement Process In China, A 2021 Update
Authors: Song Xirong , Kodabuckus Shahela , Patel Preeti 
Published: December 2022

IntroductionThe Chinese National Reimbursement Drug List (NRDL) was established in the early 2000’s and includes the drugs both fully and partially covered by National Basic Medicine Insurance. As China’s health system has been reformed over the past decade, it is important for manufacturers to understand the ever-changing reimbursement process and its implications on newly launched drugs. This study provides an updated overview of the process based on research conducted in 2021.MethodsTargeted secondary research was undertaken to evaluate the pricing and reimbursement landscape in China. Primary research was conducted to assess the perspectives of three payers and one policy expert.ResultsNational listing remains the most viable and exclusive pathway to get a product reimbursed by public health insurance in China. Since 2017, the NRDL has been updated annually, and revisions are managed by the National Healthcare Security Administration (NHSA). Insights from 2021 suggests that the process of listing a new product on the NRDL lasts five months (July to November). Manufacturers should ensure that submissions are made when the annual NRDL process formally begins, and clinical and health economic evidence is compulsory. If a successful opinion is made by the assessment board, the manufacturer will be invited to negotiate a price with the NHSA. Data from the NHSA indicated that a total of 704 applications were made in 2020. In addition, 138 exclusive drugs were eligible for price negotiation, of which 96 drugs were successful and added to the NRDL. Findings also suggested that the average discount rate increased from 44.0 percent in 2017 to 50.6 percent in 2020.ConclusionsThe national reimbursement process in China has become more transparent overtime. Even so, NRDL listing remains a challenge, with decisions driven by clinical and pharmacoeconomic evidence, and price. Significant price cuts should be considered and anticipated to ensure successful negotiation outcomes.
PP18 Horizon Scanning For Clinical Biosimilar Medicines: Informing The Lifecycle Of Health Technology Assessment And Market Access
Authors: Hussain Amy , Fairbairn Ross , Ogunbayo Dapo 
Published: December 2022

IntroductionThe National Institute for Health and Care Research (NIHR) Innovation Observatory (IO) national horizon scanning research centre, has a remit to notify its stakeholders, including the National Institute for Health and Care Excellence (NICE), about innovative interventions; including biosimilar medicines in the pipeline. Biosimilar medicines bypass many developmental steps, making them substantially cheaper to manufacture for providers, which increases market availability and improves treatment access for patients.MethodsSince 2017, the NIHR IO has monitored biosimilars in clinical development that align to the NICE health technology assessment remit. The data set explored was exported from our internal medicines innovation database - MInD.Data sets were created that included information on the characteristics of biosimilars and their associated clinical trials. Analyses and visualization creation were carried out using Microsoft Excel and Microsoft Power BI.ResultsA total of 100 unique biosimilar medicines in 136 clinical trials were included in the MInD since April 2017. Of these, 44 percent of biosimilars are currently EMA-approved (Nov 2021). Adalimumab was the reference medicine with the most unique biosimilars identified (12%). Seventy-two percent of the biosimilars in MInD were indicated for non-oncology conditions, twenty percent for oncology condition and eight percent for both.There were 46 biosimilars unapproved, which were in active development. Of these biosimilars 17.4 percent are indicated for an oncology condition, 78.3 percent for non-oncology conditions, and 4.3 percent for biosimilars for both. Aflibercept was the reference product with the most (eight) biosimilars in active development.There were 56 individual clinical trials in the MInD that list a biosimilar in development. For 26 trials, the primary completion date (PCD) was prior to 2021, whilst 28 trials listed a PCD post-2021, and 2 PCD’s were unavailableConclusionsOur analysis identified high levels of active clinical development for biosimilars. The majority of biosimilars being developed are indicated for non-oncology conditions, with many in trials due to readout in the near future. Early identification, monitoring and reporting of biosimilars allows for expedited patient access and benefits, including cost-savings for health services.This study is funded by the National Institute for Health Research (NIHR) [(HSRIC-2016-10009)/Innovation Observatory].
PP19 Reimbursable Health Apps (DiGA) In Germany: Which Factors Impact The BfArM’s Assessment And Directory Listing? – Updated Research
Authors: Drews Janika , Bonduelle Doreen , Schuller Johanna 
Published: December 2022

IntroductionSince May 2020, reimbursement can be requested for Digital healthcare applications (DIGAs) in Germany. The prerequisite for reimbursement is a listing in the Federal Institute for Drugs and Medical Devices (BfArM) DiGA-directory, granted after successful completion of an assessment process. In June 2021, IQVIA first evaluated the BfArM’s decision-making and identified criteria that may positively impact a directory listing. In November 2021, the research was updated to consider the latest developments.MethodsPublished information for each app in the DiGA-directory was qualitatively compared according to pre-specified criteria by two independent reviewers. With no data available for denied apps, only DiGAs with permanent or preliminary listings were compared.ResultsBy 26 November 2021, twenty-four apps had received a positive assessment. Permanently listed apps (n=6) focused on health status improvements and/or patients’ health competency. None claimed to improve patients’ quality of life. Results from at least one randomized controlled trial (RCT) showed efficacy with medium or strong significant effect sizes (Cohen’s d > 0.4) versus standard of care (SOC). For preliminarily listed DiGAs (n=18), final results of positive care effects were not yet provided, but applications included study designs for RCTs including definitions of primary endpoints. The BfArM accepted the trial designs to be suitable to measure an app’s positive effects on health care within twelve months after listing. Since the last analysis, no preliminarily listed apps have been granted permanent DiGA-status. Evaluation periods were extended by up to five months for three apps. With none of the trials for preliminary apps being completed, possibilities for assessment remain limited. Claims for either medical benefit and/or patient-relevant structural/procedural improvements do not seem to impact the type of listing.ConclusionsUpdated research confirmed previous findings. For a DiGA-directory listing DiGA, the (planned) provision of RCT data seems to be gold standard. Medium to strong effects on the improvement of health status compared to SOC appear to be important for a permanent listing. Evaluation periods of five preliminarily listed apps are expected to be completed in December 2021, allowing for further analyses in the future.
PP25 Brazilian Collaborative Network For COVID-19 Modeling: Successful Experience Of Using Real-Time Science To Support Evidence-Based Decision-Making
Authors: Bagattini Ângela Maria , Rosa Michelle , Simon Lorena Mendes , Berg de Almeida Gabriel , Ferreira Leonardo Souto , Borges Marcelo Eduardo , Kraenkel Roberto André , Coutinho Renato Mendes , Diniz Filho José Alexandre Felizola , Camey Suzi Alves , de Souza Kuchenbecker Ricardo , Toscano Cristiana Maria 
Published: December 2022

IntroductionModeling is important for guiding policy during epidemics. The objective of this work was to describe the experience of structuring a multidisciplinary collaborative network in Brazil for modeling coronavirus disease 2019 (COVID-19) to support decision-making throughout the pandemic.MethodsResponding to a national call in June 2020 for proposals on COVID-19 mitigation projects, we established a team of investigators from public universities located in various regions throughout Brazil. The team’s main objective was to model severe acute respiratory syndrome coronavirus 2 transmission dynamics in various demographic and epidemiologic settings in Brazil using different types of models and mitigation interventions. The modeling results aimed to provide information to support policy making. This descriptive study outlines the processes, products, challenges, and lessons learned from this innovative experience.ResultsThe network included 18 researchers (epidemiologists, infectious diseases experts, statisticians, and modelers) from various backgrounds, including ecology, geography, physics, and mathematics. The criteria for joining the network were having a communication channel with public health decision-makers and being involved in generating evidence for public policy. During a 24-month period, the following sub-projects were established: (i) development of a susceptible-exposed-infected-recovered-like, individual-based meta-population and Markov chain model; (ii) projection of COVID-19 transmission and impact over time with respect to cases, hospitalizations, and deaths; (iii) assessment of the impact of non-pharmacological interventions for COVID-19; (iv) evaluation of the impact of reopening schools; and (v) determining optimal strategies for COVID-19 vaccination. In addition, we mapped existing COVID-19 modeling groups nationwide and conducted a systematic review of relevant published research literature from Brazil.ConclusionsInfectious disease modeling for guiding public health policy requires interaction between epidemiologists, public health specialists, and modelers. Communicating modeling results in a non-academic format is an additional challenge, so close interaction with policy makers is essential to ensure that the information is useful. Establishing a network of modeling groups will be useful for future disease outbreaks.
PP33 Molecular Markers For The Detection Of Clinically Significant Prostate Cancer
Authors: del Pino-Sedeño Tasmania , García-Pérez Lidia , Infante-Ventura Diego , Hernández-Yumar Aránzazu , Rodríguez-Rodríguez Leticia , de Armas-Castellano Aythami , Serrano-Aguilar Pedro , del Mar Trujillo-Martín María 
Published: December 2022

IntroductionIt is estimated that approximately 1.1 million cases of prostate cancer (PCa) are diagnosed in the world every year. In general, PCa is a slow-onset cancer and less than 10 percent of cases are detected in the metastatic phase. In order to identify patients at risk of suffering from clinically significant prostate cancer (csPCa), as well as to avoid unnecessary biopsies, overdiagnosis and overtreatment, a variety of molecular biomarker detection tests have been developed.MethodsWe undertook a systematic review with meta-analyses on the effectiveness of diagnostic tests based on biomarkers in blood or urine samples for the identification of men at risk of csPCa. A cost-effectiveness analysis was conducted using a decision tree model for the short term and a Markov model for the long term, both from the social and the National Health System perspectives. The effectiveness measure was quality-adjusted life years (QALYs). We ran extensive sensitivity analyses, including a probabilistic sensitivity analysis.ResultsSixty-five studies were included with a total of 34,287 participants. The diagnostic tests analyzed were: PHI, Progensa® PCA3, SelectMDx, MyProstateScore, 4Kscore®, TMPRSS2: ERG, Stockholm3, ExoDx Prostate IntelliScore and Proclarix®. All studies included biopsy as comparator. The sensitivity and specificity of diagnostic tests depended on the test itself and the threshold chosen, and ranged from 42 percent to 99 percent and from 13 percent to 87 percent, respectively. In the cost-effectiveness analysis, the alternative that includes the biomarker, specifically the SelectMDx, led to higher QALYs and healthcare costs with an estimated incremental cost-effectiveness ratio (ICER) of 6,640.21 EUR per QALY. The sensitivity analyses confirmed that the results were robust.ConclusionsBiomarker testing to select men at risk of csPCa who should undergo prostate biopsy can be a cost-effective strategy depending on its cost per determination and its sensitivity/specificity. The analyses carried out indicate that the SelectMDx biomarker is cost-effective at a cost of EUR 375 per determination.
PP34 Next Generation Sequencing For Informing Lung Cancer Therapy In Europe – Hospital Impact With A Lifecycle Perspective
Authors: Saunders Rhodri , Hedblom Amanda Hansson , Quagliata Luca , Costa Jose Luis , Dumanois Robert 
Published: December 2022

IntroductionNext-generation sequencing (NGS) can be run in-house or outsourced to an independent laboratory. It has enabled wider use of deoxyribonucleic acid/ribonucleic acid (DNA + RNA) sequencing in clinical practice. Within oncology, NGS has paved the way for more effective treatment, including personalized medicine. There are, however, large variations in access and reimbursement across Europe. The aim is to understand the European NGS landscape and barriers to access.MethodsStructured telephone interviews covered topics on NGS perception, guidelines, use-cases, benefits, costs, and future expectations. Twelve experts per country (France, Germany, Italy, Spain): two payers, five oncologists, and five pathologists were interviewed between June and August 2021. Responses were translated into English for qualitative analysis.ResultsNGS was considered most useful when there were approved, targeted treatments. Although often noted that there was a lack of published evidence to support a beneficial link, respondents perceived that NGS has the potential to improve patient quality of life (QoL) and reduce resource use through avoiding suboptimal treatment. All of the payer respondents expected the role of NGS to increase, though it may be held back by lack of reimbursement. Respondents favored in-house NGS over outsourcing in terms of clinical benefit: “Advantages of in-house NGS are turnaround time, results and lean processes” … “you build the expertise in-house. If you have urgent samples, it’s easy to prioritize them”. Reasons for not having in-house NGS included “costs, lack of personnel. Basically, organizational and financial issues.” In-house NGS was perceived to be associated with high setup-costs (acquisition, setup, training), but lower running costs (per-test costs). There was a view that in-house solutions are mainly suitable in larger centers undertaking many tests.ConclusionsNGS can save costs and provide QoL benefit through enabling optimized, personalized therapy, but published evidence establishing the outcomes link is lacking. From the hospital perspective, investing in NGS requires understanding the cost of NGS over its entire lifecycle, likely entailing a health-technology assessment including health-economic analysis.
PP39 Evidence Generation For Reimbursement Of Digital Health Applications (DiGAs) In Germany
Authors: Fujita-Rohwerder Naomi , Sauerland Stefan 
Published: December 2022

IntroductionIn 2019, the German government established a new evaluation procedure for digital health applications (DiGAs) to facilitate their reimbursement by statutory health insurance. The procedure involves the assessment of a DiGA’s “positive healthcare effect”, which is defined as a medical benefit and/or “a patient-relevant improvement of structure and processes”. If the available clinical evidence is insufficient to prove the manufacturer’s claim on the positive healthcare effect, but the claim seems plausible, the DiGA is provisionally reimbursed, and further clinical evidence within twelve months must be generated. DiGAs eligible for provisional or permanent reimbursement are publicly listed in the DiGA directory.In contrast to the usual pathways for reimbursement of healthcare technologies which involve IQWiG as the national HTA agency and the G-BA (Federal Joint Committee) as the decision-making body, the DiGA procedure is currently carried out by the national competent authority (BfArM) and thus outside the joint self-government. Furthermore, legal evidence requirements for DiGAs are comparatively low.MethodsThis work analyzed the suitability of clinical studies that intended to prove a DiGA’s medical benefit. For this purpose, the key elements for clinical studies published in the DiGA directory and clinical trial registries were extracted and compared with the usual evidence requirements in the reimbursement context.ResultsAs of October 2020, 20 DiGAs have successfully undergone the application procedure. Fourteen DiGAs (70%) were provisionally accepted. A randomized controlled study (RCT) design was chosen for all clinical studies to be conducted for further evidence generation. However, in four cases (28%), it is questionable whether the clinical study is suitable to demonstrate a medical benefit mainly due to the choice or operationalization of the primary endpoint (n=2), the timing of the endpoint survey (n=2) and/or the choice of the control intervention (n=1).ConclusionsEven though all currently ongoing or planned clinical studies with DiGAs are RCTs, not all of them are adequate to demonstrate a medical benefit according to the usual evidence requirements.
PP41 COVID-19 Modeling To Support Decision Making In Brazil: A Scoping Review
Authors: Rosa Michelle , Bagattini Angela Maria , Simon Lorena Mendes , de Almeida Gabriel Berg , da Rosa Isabella Inês Rodrigues , Toscano Cristiana Maria 
Published: December 2022

IntroductionIn the context of the COVID-19 pandemic, which required urgent responses from health systems, and ongoing decision making in a context of limited and evolving evidence, modeling played a significant role in supporting public policy making. Nonetheless, particularly in low and middle-income countries, modeling groups are scarce, and usually not routinely involved in supporting public health policy making. We aimed to appraise COVID-19 modeling work in Brazil during the pandemic.MethodsWe performed a scoping review following PRISMA guidelines to identify groups conducting COVID-19 modeling to support health decision-making in Brazil. Search strategies were applied to MEDLINE, LILACS, Embase, ArXiv, and also included National data repositories and gray literature. We excluded reports of models without modeling results. Titles, abstracts, data repository descriptions and full-text articles identified were read and selected by two reviewers. Data extracted included modeling questions, model characteristics (structure, type, and programming), epidemiologic data sources, main outcomes reported, and parameters. To further identify modeling groups that might have not yet published results, snowball sampling was performed, and a short survey was sent electronically. Investigators and policymakers were invited to an online interview, to obtain further information on how they interacted, communicated, and used modeling results.ResultsWe retrieved 1,061 references. After removing duplicates (127), 1,016 abstracts and titles were screened. From an initial selection of 142 abstracts, 133 research groups were identified, of which 67 didn’t meet the eligibility criteria. Of these, 66 groups were invited for an interview, of which 24 were available, including 18 modeling groups from academic institutions, and four groups from State Health departments. Most models assessed the impact of mitigation measures in cases/hospitalization/deaths and healthcare service demand. Interaction and communication with decision-makers were not well established in most groups.ConclusionsDespite a large number of modeling groups in Brazil, we observed a significant gap in modeling demand and communicating its results to support the decision-making process during the COVID-19 pandemic.