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Health Technology Assessment is one of the standard instruments in support of the decision-making to define the public health services both internationally and in the German health care system. Besides systematic reviews, benefit-harm-analyses, health economic evaluations, and, decision-analytic modelling, especially epidemiological and biometrical questions and methods play a key role. From this perspective discussions on increased European cooperation including calls for wider harmonization are attracting greater interests.The overall aim is, to present at the GMDS workshop relevant information on this emerging field of harmonization in Europe across similarities and differences in the HTA process. Current developments around the composition of the EU-HTA Network are provided. This network accepts the challenge to define and establish a “Joint Work” across Europe. Special emphasis was placed on the discussion on “Harmonization of HTA: is it a threat or does it mean support?”. Furthermore, methodological discussions and questions are being addressed: “Are Real World Data and Surrogates possible parameters for decision-making or HTA?”

Background: Progression-free survival (PFS) is often used instead of the patient-relevant endpoint overall survival (OS) in cancer clinical trials. In order for PFS to be accepted as a patient-relevant outcome within the benefit assessment of pharmaceuticals in accordance with the German Social Code, Book Five (SGB V), section 35a, it has to be validated as a surrogate endpoint for OS in the relevant indication. As part of a rapid report the Institute for Quality and Efficiency in Health Care (Institut für Qualität und Wirtschaftlichkeit im Gesundheitswesen – IQWiG) presented methods for surrogate endpoints validation and recommendations for correlation-based procedures. These methods include the evaluation of the certainty of conclusion of study results and the correlation between estimates of surrogate outcome and patient-relevant outcome on trial-level. The correlation is estimated by sample Pearson correlation coefficient or coefficient of determination and respective confidence interval (CI). Requirements for surrogate validation are a high correlation and a high certainty of conclusion of the study results. In case of medium correlation IQWiG methods propose applying the concept of surrogate threshold effect (STE) to determine thresholds for the estimate of the surrogate endpoint.Methods: In simulation studies we investigate the requirements for a successful surrogate validation when applying a correlation-based approach. Simulation parameters are the estimates of the surrogate and the patient-relevant outcome, the correlation between them, the number of patients and the number of studies. We analyzed different scenarios in order to figure out parameters contributing to high correlation. Furthermore, we investigate requirements of the STE method, allowing conclusions on patient-relevant endpoints by means of surrogate endpoints. Finally, in consideration of IQWiG methods we analyze the challenges of surrogate validation in practical use.Results: Both, simulations of the surrogate validation using correlation-based procedure as well as an analytical derivation show low statistical power despite a medium-sized number of studies and a high true correlation. The power for =5 studies and correlation =0.9 is below 6%. A very high true correlation of =0.95 in at least =25 studies would be required in order to preserve a power of 80%, however this scenario is considered implausible in practice. Further simulations investigating the power of the method of STE showed that only one fifth of the considered scenarios have power above 80%. However, these scenarios included parameter constellations with impractical values regarding number of studies, number of patients and effect estimate of OS. The correlation parameter as well as the parameter of the estimate of PFS barely have an impact on the power of the STE procedure.Conclusion: Our simulations show that in practical use it is quite unlikely to fulfill the condition of high correlation as defined in the rapid report of IQWiG, proposing the lower limit of confidence interval to be crucial. Despite setting the true correlation in the model to a high value, statistical power will be quite small as long as the number of studies remains low or medium which is a realistic assumption in validation of surrogate endpoints within the framework of early benefit assessment. Besides, recommendation to involve certainty of studies in the analysis remains problematic. On closer inspection of the density function of sample correlation coefficient and assuming a given true correlation we can conclude that sample correlation does not depend on the variance of the single estimates but only on sample size (representing the number of studies in the model). Therefore, patient number does not have an impact on the confidence interval of the correlation whether using weight vectors for studies or not. Application of the STE concept according to the requirements described in the rapid report appears to be rather complicated as well. We propose an alternative solution of comparing the value of STE with point estimate of the surrogate endpoint instead of its lower level of confidence interval showing low α-errors in realistic scenarios.

The article "Questioning Conclusions and Statements on the German HTA System: A Critical Perspective" by Oriol Sola‐Morales et al. provides insights on health technology assessments (HTA) in Germany, emphasizing the importance of early engagement with agencies, addressing missing data, and selecting real‐world endpoints. The analysis criticizes inaccuracies and omissions in G‐BA assessments, highlighting discrepancies between IQWiG and G‐BA ratings for certain drugs. The article also discusses the differences in incorporating real-world evidence (RWE) between G‐BA and NICE, noting NICE's higher acceptance rate of RWE for reimbursement recommendations. [Extracted from the article]

Background: Little information on the current burden of community-acquired pneumonia (CAP) in adults in Germany is available. Methods: We conducted a retrospective cohort study using a representative healthcare claims database of approx. 4 million adults to estimate the incidence rates (IR) and associated mortality of CAP in 2015. IR and mortality were stratified by treatment setting, age group, and risk group status. A pneumonia coded in the primary diagnosis position or in the second diagnosis position with another pneumonia-related condition coded in the primary position was used as the base cases definition for the study. Sensitivity analyses using broader and more restrictive case definitions were also performed. Results: The overall IR of CAP in adults ≥18 years was 1,054 cases per 100,000 person-years of observation. In adults aged 16 to 59 years, IR for overall CAP, hospitalized CAP and outpatient CAP was 551, 96 and 466 (with a hospitalization rate of 17%). In adults aged ≥60 years, the respective IR were 2,032, 1,061 and 1,053 (with a hospitalization rate of 52%). If any pneumonia coded in the primary or secondary diagnosis position was considered for hospitalized patients, the IR increased 1.5-fold to 1,560 in the elderly ≥60 years. The incidence of CAP hospitalizations was substantially higher in adults ≥18 years with at-risk conditions and high-risk conditions (IR of 608 and 1,552, respectively), compared to adults without underlying risk conditions (IR 108). High mortality of hospitalized CAP in adults ≥18 was observed in-hospital (18.5%), at 30 days (22.9%) and at one-year (44.5%) after CAP onset. Mortality was more than double in older adults in comparison to younger patients. Conclusion: CAP burden in older adults and individuals with underlying risk conditions was high. Maximizing uptake of existing vaccines for respiratory diseases may help to mitigate the disease burden, especially in times of strained healthcare resources. [ABSTRACT FROM AUTHOR]

The assessment of safety is an important aspect of the evaluation of new therapies in clinical trials, with analyses of adverse events being an essential part of this. Standard methods for the analysis of adverse events such as the incidence proportion, that is the number of patients with a specific adverse event out of all patients in the treatment groups, do not account for both varying follow‐up times and competing risks. Alternative approaches such as the Aalen–Johansen estimator of the cumulative incidence function have been suggested. Theoretical arguments and numerical evaluations support the application of these more advanced methodology, but as yet there is to our knowledge only insufficient empirical evidence whether these methods would lead to different conclusions in safety evaluations. The Survival analysis for AdVerse events with VarYing follow‐up times (SAVVY) project strives to close this gap in evidence by conducting a meta‐analytical study to assess the impact of the methodology on the conclusion of the safety assessment empirically. Here we present the rationale and statistical concept of the empirical study conducted as part of the SAVVY project. The statistical methods are presented in unified notation, and examples of their implementation in R and SAS are provided. [ABSTRACT FROM AUTHOR]

The analysis of adverse events (AEs) is a key component in the assessment of a drug's safety profile. Inappropriate analysis methods may result in misleading conclusions about a therapy's safety and consequently its benefit‐risk ratio. The statistical analysis of AEs is complicated by the fact that the follow‐up times can vary between the patients included in a clinical trial. This paper takes as its focus the analysis of AE data in the presence of varying follow‐up times within the benefit assessment of therapeutic interventions. Instead of approaching this issue directly and solely from an analysis point of view, we first discuss what should be estimated in the context of safety data, leading to the concept of estimands. Although the current discussion on estimands is mainly related to efficacy evaluation, the concept is applicable to safety endpoints as well. Within the framework of estimands, we present statistical methods for analysing AEs with the focus being on the time to the occurrence of the first AE of a specific type. We give recommendations which estimators should be used for the estimands described. Furthermore, we state practical implications of the analysis of AEs in clinical trials and give an overview of examples across different indications. We also provide a review of current practices of health technology assessment (HTA) agencies with respect to the evaluation of safety data. Finally, we describe problems with meta‐analyses of AE data and sketch possible solutions. [ABSTRACT FROM AUTHOR]

Background: With the Act on the Reform of the Market for Medicinal Products (AMNOG) in Germany, pharmaceutical manufacturers are obliged to submit a dossier demonstrating added benefit of a new drug compared to an appropriate comparator. Underlying evidence was planned for registration purposes and therefore often does not meet the appropriate comparator as defined by the Federal Joint Committee (G-BA). For this reason AMNOG allows indirect comparisons to assess the extent of added benefit.Objectives: The aim of this study is to evaluate the characteristics and applicability of adjusted indirect comparison described by Bucher and Matching-Adjusted Indirect Comparison (MAIC) in various situations within the early benefit assessment according to §35a Social Code Book 5. In particular, we consider time-to-event endpoints.Methods: We conduct a simulation study where we consider three different scenarios: I) similar study populations, II) dissimilar study populations without interactions and III) dissimilar study populations with interactions between treatment effect and effect modifiers. We simulate data from a Cox model with Weibull distributed survival times. Desired are unbiased effect estimates. We compare the power and the proportion of type 1 errors of the methods.Results: I) Bucher and MAIC perform equivalently well and yield unbiased effect estimates as well as proportions of type 1 errors below the significance level of 5 %. II) Both Bucher and MAIC yield unbiased effect estimates, but Bucher shows a higher power for detection of true added benefit than MAIC. III) Only MAIC, but not Bucher yields unbiased effect estimates. When using robust variance estimation MAIC yields a proportion of type 1 error close to 5 %. In general, power of all methods for indirect comparisons is low. An increasing loss of power for the indirect comparisons can be observed as the true treatment effects decrease.Conclusion: Due to the great loss of power and the potential bias for indirect comparisons, head-to-head trials using the appropriate comparator as defined by the Federal Joint Committee should be conducted whenever possible. However, indirect comparisons are needed if no such direct evidence is available. To conduct indirect comparisons in case of a present common comparator and similar study populations in the trials to be compared, both Bucher and MAIC can be recommended. In case of using adjusted effect measures (such as Hazard Ratio), the violation of the similarity assumption has no relevant effect on the Bucher approach as long as interactions between treatment effect and effect modifiers are absent. Therefore Bucher can still be considered appropriate in this specific situation. In the authors' opinion, MAIC can be considered as an option (at least as sensitivity analysis to Bucher) if such interactions are present or cannot be ruled out. Nevertheless, in practice MAIC is potentially biased and should always be considered with utmost care. [ABSTRACT FROM AUTHOR]

Simple descriptive listings and inference statistics based on 2×2 tables are still the most common way of summarizing and reporting adverse events data from randomized controlled trials, although these methods do not account for differences in observation times between treatment groups. Using standard methods from survival analysis such as the Cox model or Kaplan-Meier estimates would overcome this problem but limit the analysis to the first safety-related event of each subject. As an alternative, we discuss two models for recurrent events data-the Andersen-Gill and Prentice-Williams-Peterson model-regarding their applicability to safety data from randomized controlled trials. We argue that these models can be used to estimate two different quantities: a direct treatment effect on the risk of an event (Prentice-Williams-Peterson) and a total treatment effect as sum of the direct effect and the treatment's indirect effect via the event history (Anderson-Gill). Using simulated data, we illustrate the difference between these treatment effects and analyze the performance of both models in different scenarios. Because both models are limited to the analysis of cause-specific hazards if competing risks are present, we suggest to incorporate estimates of the mean frequency of events in the analysis to additionally allow the comparison of treatment effects on absolute event probabilities. We demonstrate the application of both models and the mean frequency function to safety endpoints with an illustrative analysis of data from a randomized phase-III study. Copyright © 2016 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In 2010, the Federal Parliament (Bundestag) of Germany passed a new law (Arzneimittelmarktneuordnungsgesetz, AMNOG) on the regulation of medicinal products that applies to all pharmaceutical products with active ingredients that are launched beginning January 1, 2011. The law describes the process to determine the price at which an approved new product will be reimbursed by the statutory health insurance system. The process consists of two phases. The first phase assesses the additional benefit of the new product versus an appropriate comparator (zweckmäßige Vergleichstherapie, zVT). The second phase involves price negotiation. Focusing on the first phase, this paper investigates requirements of benefit assessment of a new product under this law with special attention on the methods applied by the German authorities on issues such as the choice of the comparator, patient relevant endpoints, subgroup analyses, extent of benefit, determination of net benefit, primary and secondary endpoints, and uncertainty of the additional benefit. We propose alternative approaches to address the requirements in some cases and invite other researchers to help develop solutions in other cases. [ABSTRACT FROM AUTHOR]

In this paper, the association of gastric Campylobacter pylori (CP) colonization with histologic findings and gastric emptying of a mixed solid-liquid meal was prospectively investigated in 43 consecutive patients with essential non-ulcer dyspepsia (ENUD). Gastric emptying was also measured in 30 symptom-free control subjects. The frequency of CP infection in patients with ENUD was 44.2%. We found a strong association between gastric CP colonization and chronic antral type B gastritis. Although gastric emptying was significantly prolonged in patients with ENUD, compared with the control group (p < 0.05), we could not detect significant differences of gastric emptying between CP-negative and CP-positive ENUD patients, both groups disclosing a similar proportion of patients with significantly delayed gastric emptying (29.2% vs 31.6%). We therefore conclude that delayed gastric emptying of a mixed solid-liquid meal is not correlated with CP-positive chronic antral type B gastritis, and does not help to explain dyspeptic symptoms, which may possibly arise in relation to gastric CP colonization. [ABSTRACT FROM AUTHOR]

Introduction: In early 2020, the coronavirus disease 2019 (COVID-19) pandemic spread worldwide, overwhelming hospitals with severely ill patients and posing the urgent need for clinical evidence to guide patient care. First treatment options available were repurposed drugs to fight inflammation, coagulopathy, and viral replication. A vast number of clinical studies were launched globally to test their efficacy and safety. Our analysis describes the development of global evidence on repurposed drugs, in particular corticosteroids, anticoagulants, and (hydroxy)chloroquine in hospitalized COVID-19 patients based on different study types. We track the incorporation of clinical data in international and national treatment guidelines and identify factors that characterize studies and analyses with the greatest impact on treatment recommendations., Methods: A literature search in MEDLINE was conducted to assess the clinical evidence on treatment with corticosteroids, anticoagulants, and (hydroxy)chloroquine in hospitalized COVID-19 patients during the first year of the pandemic. Adoption of the evidence from this clinical data in treatment guidelines of the World Health Organization (WHO), Germany, and United States (US) was evaluated over time., Results: We identified 106 studies on corticosteroids, 141 studies on anticoagulants, and 115 studies on (hydroxy)chloroquine. Most studies were retrospective cohort studies; some were randomized clinical trials (RCTs), and a few were platform trials. These studies were compared to studies directly and indirectly referred to in WHO (7 versions), German (5 versions), and US (21 versions) guidelines. We found that initially large, well-adjusted, mainly retrospective cohort studies and ultimately large platform trials or coordinated meta-analyses of RCTs provided best available clinical evidence supporting treatment recommendations., Discussion: Particularly early in the pandemic, evidence for the efficacy and safety of repurposed drugs was of low quality, since time and scientific rigor seemed to be competing factors. Pandemic preparedness, coordinated efforts, and combined analyses were crucial to generating timely and robust clinical evidence that informed national and international treatment guidelines on corticosteroids, anticoagulants, and (hydroxy)chloroquine. Multi-arm platform trials with master protocols and coordinated meta-analyses proved particularly successful, with researchers joining forces to answer the most pressing questions as quickly as possible., Competing Interests: This study received funding from Pfizer Deutschland GmbH, Novartis Pharma GmbH, and Amgen GmbH. The funders had the following involvement with the study: FL (Pfizer) was involved in the conception of this analysis. FL (Pfizer), KS (Pfizer), AL (Amgen), DG-F (Novartis) discussed and agreed on the methods used for the analysis, revised the manuscript, and approved the final version. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wüstner, Hogger, Gartner-Freyer, Lebioda, Schley and Leverkus.)

Background: Venous thromboembolism (VTE) mainly manifests as deep vein thrombosis (TVT) or pulmonary embolism (LE), and is the third most common cardiovascular disease worldwide. However, robust evidence on the incidence of VTE in Germany is lacking., Objective: Estimation and comparison of the incidence of VTE based on different routine data sources of the German healthcare system., Methods: Estimates and comparisons of the incidence of VTE, TVT and LE were made using two databases that both covered the inpatient and the outpatient setting; the DaTraV database comprising information of all persons subject to compulsory health insurance, and the Health Risk Institute (HRI) database derived from approximately 70 statutory health insurance funds. In addition, IMS Disease Analyzer, a medical record database comprising information from the outpatient setting, was used as a data source., Results: Patterns of age- and sex-specific VTE incidence estimates were comparable between all databases used. However, estimates based on the medical record database were comparatively high. Analyses of DaTraV data led to a VTE incidence of 0.14%. Use of HRI data yielded comparable results (0.17-0.20%). VTE incidence based on data of the IMS Disease Analyzer was comparatively high (0.32%)., Discussion: Results on the VTE incidence based on DaTraV or HRI date are comparable to international evidence, whereas the use of the IMS Disease Analyzer data presumably led to an overestimation due to double-counting of VTE cases. Different types of routine healthcare data sources can therefore lead to very heterogeneous results. Thus, the selection of adequate data sources strongly depends on the study question and the quality of the dataset., (Copyright © 2018. Published by Elsevier GmbH.)