{"title":"Acceptance of Evidence Transfer Within German Early Benefit Assessment of New Drugs for Pediatric and Adolescents Target Populations.","authors":"Georgia Pick, Dirk Müller, Charalabos-Markos Dintsios","doi":"10.1007/s40273-024-01467-8","DOIUrl":null,"url":null,"abstract":"<p><strong>Background and objective: </strong>In Germany, all new drugs undergo an early benefit assessment (EBA) by the decision-making body (G-BA). Due to limited access to clinical data in pediatric healthcare since 2017, evidence transfer has allowed for data from adult studies to be used in the EBA of pediatric drugs. This study examines the acceptance of evidence transfer, aiming to understand its correlation with granted added benefit.</p><p><strong>Methods: </strong>By searching the G-BA database, relevant EBAs were identified. In addition to descriptive statistics, agreement statistics regarding binary and ordinal extent of added benefit and binary logistic regression with and without intercept were performed to investigate acceptance of evidence transfer, juxtaposing it with manufacturers' claims, and to evaluate the impact of identified factors on evidence transfer.</p><p><strong>Results: </strong>In 14 of 36 identified EBAs, the evidence transfer was accepted by the G-BA. They referred to four therapeutic areas, received a non-quantifiable added benefit and were subject to a pediatric investigation program. Non-quantifiable added benefit implies an added value in itself which can range from minor to major added benefit and is considering the genuine uncertainty mainly induced in theese EBAs due to evidence transfer, which is not allowing a quantification of an added benefit. The binary agreement between manufacturers' claims and G-BA's appraisals was less than by chance [kappa - 0.054 (- 0.158 to 0.050)] whereas the ordinal agreement became fair [kappa 0.333 (0.261-0.406)]. Congruence of the mechanism of action, alignment of disease pattern, transferability of efficacy and safety, and same comparator were fundamental for evidence transfer. Additionally, supportive evidence, therapeutic breakthroughs, and small-scale approval enhanced the acceptance of evidence transfer. The regression models yielded similar results showing different model fit and explained variance.</p><p><strong>Conclusions: </strong>Evidence transfer hinges upon fulfilling various minimum criteria and additional supportive evidence. Availability of study data from adult or older patients and the pediatric group under evaluation is crucial.</p>","PeriodicalId":19807,"journal":{"name":"PharmacoEconomics","volume":" ","pages":""},"PeriodicalIF":4.4000,"publicationDate":"2025-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"PharmacoEconomics","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s40273-024-01467-8","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0
Abstract
Background and objective: In Germany, all new drugs undergo an early benefit assessment (EBA) by the decision-making body (G-BA). Due to limited access to clinical data in pediatric healthcare since 2017, evidence transfer has allowed for data from adult studies to be used in the EBA of pediatric drugs. This study examines the acceptance of evidence transfer, aiming to understand its correlation with granted added benefit.
Methods: By searching the G-BA database, relevant EBAs were identified. In addition to descriptive statistics, agreement statistics regarding binary and ordinal extent of added benefit and binary logistic regression with and without intercept were performed to investigate acceptance of evidence transfer, juxtaposing it with manufacturers' claims, and to evaluate the impact of identified factors on evidence transfer.
Results: In 14 of 36 identified EBAs, the evidence transfer was accepted by the G-BA. They referred to four therapeutic areas, received a non-quantifiable added benefit and were subject to a pediatric investigation program. Non-quantifiable added benefit implies an added value in itself which can range from minor to major added benefit and is considering the genuine uncertainty mainly induced in theese EBAs due to evidence transfer, which is not allowing a quantification of an added benefit. The binary agreement between manufacturers' claims and G-BA's appraisals was less than by chance [kappa - 0.054 (- 0.158 to 0.050)] whereas the ordinal agreement became fair [kappa 0.333 (0.261-0.406)]. Congruence of the mechanism of action, alignment of disease pattern, transferability of efficacy and safety, and same comparator were fundamental for evidence transfer. Additionally, supportive evidence, therapeutic breakthroughs, and small-scale approval enhanced the acceptance of evidence transfer. The regression models yielded similar results showing different model fit and explained variance.
Conclusions: Evidence transfer hinges upon fulfilling various minimum criteria and additional supportive evidence. Availability of study data from adult or older patients and the pediatric group under evaluation is crucial.
期刊介绍:
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