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This manuscript introduces the convergence Epidemic Volatility Index (cEVI), a modification of the recently introduced Epidemic Volatility Index (EVI), as an early warning tool for emerging epidemic waves. cEVI has a similar architectural structure as EVI, but with an optimization process inspired by a Geweke diagnostic-type test. Our approach triggers an early warning based on a comparison of the most recently available window of data samples and a window based on the previous time frame. Application of cEVI to data from the COVID-19 pandemic data revealed steady performance in predicting early, intermediate epidemic waves and retaining a warning during an epidemic wave. Furthermore, we present two basic combinations of EVI and cEVI: (1) their disjunction cEVI þ that respectively identifies waves earlier than the original index, (2) their conjunction cEVIthat results in higher accuracy. Combination of multiple warning systems could potentially create a surveillance umbrella that would result in early implementation of optimal outbreak interventions. [ABSTRACT FROM AUTHOR]

Background: Tests have false positive or false negative results, which, if not properly accounted for, may provide misleading apparent prevalence estimates based on the observed rate of positive tests and not the true disease prevalence estimates. Methods to estimate the true prevalence of disease, adjusting for the sensitivity and the specificity of the diagnostic tests are available and can be applied, though, such procedures can be cumbersome to researchers with or without a solid statistical background. This manuscript introduces a web-based application that integrates statistical methods for Bayesian inference of true disease prevalence based on prior elicitation for the accuracy of the diagnostic tests. This tool allows practitioners to simultaneously analyse and visualize results while using interactive sliders and output prior/posterior plots. Methods - implementation: Three methods for prevalence prior elicitation and four core families of Bayesian methods have been combined and incorporated in this web tool. |tPRiors| user interface has been developed with R and Shiny and may be freely accessed on-line. Results: |tPRiors| allows researchers to use preloaded data or upload their own datasets and perform analysis on either single or multiple population groups clusters, allowing, if needed, for excess zero prevalence. The final report is exported in raw parts either as.rdata or.png files and can be further analysed. We utilize a real multiple-population and a toy single-population dataset to demonstrate the robustness and capabilities of |tPRiors|. Conclusions: We expect |tPRiors| to be helpful for researchers interested in true disease prevalence estimation and who are keen on accounting for prior information. |tPRiors| acts both as a statistical tool and a simplified step-by-step statistical framework that facilitates the use of complex Bayesian methods. The application of |tPRiors| is expected to aid standardization of practices in the field of Bayesian modelling on subject and multiple group-based true prevalence estimation. [ABSTRACT FROM AUTHOR]

Background: Tests have false positive or false negative results, which, if not properly accounted for, may provide misleading apparent prevalence estimates based on the observed rate of positive tests and not the true disease prevalence estimates. Methods to estimate the true prevalence of disease, adjusting for the sensitivity and the specificity of the diagnostic tests are available and can be applied, though, such procedures can be cumbersome to researchers with or without a solid statistical background. This manuscript introduces a web-based application that integrates statistical methods for Bayesian inference of true disease prevalence based on prior elicitation for the accuracy of the diagnostic tests. This tool allows practitioners to simultaneously analyse and visualize results while using interactive sliders and output prior/posterior plots.Methods- Implementation: Three methods for prevalence prior elicitation and four core families of Bayesian methods have been combined and incorporated in this web tool. |tPRiors| user interface has been developed with R and Shiny and may be freely accessed on-line.Results: |tPRiors| allows researchers to use preloaded data or upload their own datasets and perform analysis on either single or multiple population groups clusters, allowing, if needed, for excess zero prevalence. The final report is exported in raw parts either as.rdata or.png files and can be further analysed. We utilize a real multiple-population and a toy single-population dataset to demonstrate the robustness and capabilities of |tPRiors|.Conclusions: We expect |tPRiors| to be helpful for researchers interested in true disease prevalence estimation and who are keen on accounting for prior information. |tPRiors| acts both as a statistical tool and a simplified step-by-step statistical framework that facilitates the use of complex Bayesian methods. The application of |tPRiors| is expected to aid standardization of practices in the field of Bayesian modelling on subject and multiple group-based true prevalence estimation. [ABSTRACT FROM AUTHOR]

In drug development programs, proof-of-concept Phase II clinical trials typically have a biomarker as a primary outcome, or an outcome that can be observed with relatively short follow-up. Subsequently, the Phase III clinical trials aim to demonstrate the treatment effect based on a clinical outcome that often needs a longer follow-up to be assessed. Early-phase outcomes or biomarkers are typically associated with late-phase outcomes and they are often included in Phase III trials. The decision to proceed to Phase III development is based on analysis of the early-Phase II outcome data. In rare diseases, it is likely that only one Phase II trial and one Phase III trial are available. In such cases and before drug marketing authorization requests, positive results of the early-phase outcome of Phase II trials are then likely seen as supporting (or even replicating) positive Phase III results on the late-phase outcome, without a formal retrospective combined assessment and without accounting for between-study differences. We used double-regression modeling applied to the Phase II and Phase III results to numerically mimic this informal retrospective assessment. We provide an analytical solution for the bias and mean square error of the overall effect that leads to a corrected double-regression. We further propose a flexible Bayesian double-regression approach that minimizes the bias by accounting for between-study differences via discounting the Phase II early-phase outcome when they are not in line with the Phase III biomarker outcome results. We illustrate all methods with an orphan drug example for Fabry disease. [ABSTRACT FROM AUTHOR]

Summary: In rare diseases, typically only a small number of patients are available for a randomized clinical trial. Nevertheless, it is not uncommon that more than one study is performed to evaluate a (new) treatment. Scarcity of available evidence makes it particularly valuable to pool the data in a meta‐analysis. When the primary outcome is binary, the small sample sizes increase the chance of observing zero events. The frequentist random‐effects model is known to induce bias and to result in improper interval estimation of the overall treatment effect in a meta‐analysis with zero events. Bayesian hierarchical modeling could be a promising alternative. Bayesian models are known for being sensitive to the choice of prior distributions for between‐study variance (heterogeneity) in sparse settings. In a rare disease setting, only limited data will be available to base the prior on, therefore, robustness of estimation is desirable. We performed an extensive and diverse simulation study, aiming to provide practitioners with advice on the choice of a sufficiently robust prior distribution shape for the heterogeneity parameter. Our results show that priors that place some concentrated mass on small τ values but do not restrict the density for example, the Uniform(−10, 10) heterogeneity prior on the log(τ2) scale, show robust 95% coverage combined with less overestimation of the overall treatment effect, across varying degrees of heterogeneity. We illustrate the results with meta‐analyzes of a few small trials. [ABSTRACT FROM AUTHOR]

Aim: To investigate the associations of blood pressure variability (BPV), expressed as long‐term (visit‐to‐visit) and short‐term (ambulatory blood pressure monitoring [ABPM] and home blood pressure monitoring [HBPM]) and all‐cause mortality, major adverse cardiovascular events (MACEs), extended MACEs, microvascular complications (MiCs) and hypertension‐mediated organ damage (HMOD) in adult patients with type 2 diabetes. Materials and methods: PubMed, Medline, Embase, Cinahl, Web of Science, ClinicalTrials.gov and grey literature databases were searched for studies including patients with type 2 diabetes, at least one variable of BPV (visit‐to‐visit, HBPM, ABPM) and evaluation of the incidence of at least one of the following outcomes: all‐cause mortality, MACEs, extended MACEs and/or MiCs and/or HMOD. The extracted information was analyzed using random effects meta‐analysis and meta‐regression. Results: Data from a total of 377 305 patients were analyzed. Systolic blood pressure (SBP) variability was associated with a significantly increased risk of all‐cause mortality (HR 1.12, 95% CI 1.04–1.21), MACEs (HR 1.01, 95% CI 1.04–1.17), extended MACEs (HR 1.07, 95% CI 1.03–1.11) and MiCs (HR 1. 12, 95% CI 1.01–1.24), while diastolic blood pressure was not. Associations were mainly driven from studies on long‐term SBP variability. Qualitative analysis showed that BPV was associated with the presence of HMOD expressed as carotid intima‐media thickness, pulse wave velocity and left ventricular hypertrophy. Results were independent of mean blood pressure, glycaemic control and serum creatinine levels. Conclusions: Our results suggest that BPV might provide additional information rather than mean blood pressure on the risk of cardiovascular disease in patients with type 2 diabetes. [ABSTRACT FROM AUTHOR]

Aim: To investigate the associations of blood pressure variability (BPV), expressed as long‐term (visit‐to‐visit) and short‐term (ambulatory blood pressure monitoring [ABPM] and home blood pressure monitoring [HBPM]) and all‐cause mortality, major adverse cardiovascular events (MACEs), extended MACEs, microvascular complications (MiCs) and hypertension‐mediated organ damage (HMOD) in adult patients with type 2 diabetes. Materials and methods: PubMed, Medline, Embase, Cinahl, Web of Science, ClinicalTrials.gov and grey literature databases were searched for studies including patients with type 2 diabetes, at least one variable of BPV (visit‐to‐visit, HBPM, ABPM) and evaluation of the incidence of at least one of the following outcomes: all‐cause mortality, MACEs, extended MACEs and/or MiCs and/or HMOD. The extracted information was analyzed using random effects meta‐analysis and meta‐regression. Results: Data from a total of 377 305 patients were analyzed. Systolic blood pressure (SBP) variability was associated with a significantly increased risk of all‐cause mortality (HR 1.12, 95% CI 1.04–1.21), MACEs (HR 1.01, 95% CI 1.04–1.17), extended MACEs (HR 1.07, 95% CI 1.03–1.11) and MiCs (HR 1. 12, 95% CI 1.01–1.24), while diastolic blood pressure was not. Associations were mainly driven from studies on long‐term SBP variability. Qualitative analysis showed that BPV was associated with the presence of HMOD expressed as carotid intima‐media thickness, pulse wave velocity and left ventricular hypertrophy. Results were independent of mean blood pressure, glycaemic control and serum creatinine levels. Conclusions: Our results suggest that BPV might provide additional information rather than mean blood pressure on the risk of cardiovascular disease in patients with type 2 diabetes. [ABSTRACT FROM AUTHOR]

Simulation studies to evaluate performance of statistical methods require a well-specified data-generating model. Details of these models are essential to interpret the results and arrive at proper conclusions. A case in point is random-effects meta-analysis of dichotomous outcomes. We reviewed a number of simulation studies that evaluated approximate normal models for meta-analysis of dichotomous outcomes, and we assessed the data-generating models that were used to generate events for a series of (heterogeneous) trials. We demonstrate that the performance of the statistical methods, as assessed by simulation, differs between these 3 alternative data-generating models, with larger differences apparent in the small population setting. Our findings are relevant to multilevel binomial models in general. [ABSTRACT FROM AUTHOR]

Early warning tools are crucial for the timely application of intervention strategies and the mitigation of the adverse health, social and economic effects associated with outbreaks of epidemic potential such as COVID-19. This paper introduces, the Epidemic Volatility Index (EVI), a new, conceptually simple, early warning tool for oncoming epidemic waves. EVI is based on the volatility of newly reported cases per unit of time, ideally per day, and issues an early warning when the volatility change rate exceeds a threshold. Data on the daily confirmed cases of COVID-19 are used to demonstrate the use of EVI. Results from the COVID-19 epidemic in Italy and New York State are presented here, based on the number of confirmed cases of COVID-19, from January 22, 2020, until April 13, 2021. Live daily updated predictions for all world countries and each of the United States of America are publicly available online. For Italy, the overall sensitivity for EVI was 0.82 (95% Confidence Intervals: 0.75; 0.89) and the specificity was 0.91 (0.88; 0.94). For New York, the corresponding values were 0.55 (0.47; 0.64) and 0.88 (0.84; 0.91). Consecutive issuance of early warnings is a strong indicator of main epidemic waves in any country or state. EVI's application to data from the current COVID-19 pandemic revealed a consistent and stable performance in terms of detecting new waves. The application of EVI to other epidemics and syndromic surveillance tasks in combination with existing early warning systems will enhance our ability to act swiftly and thereby enhance containment of outbreaks. [ABSTRACT FROM AUTHOR]

Clinical evidence is limited regarding palliative radiation therapy for relieving pancreatic cancer-related pain. We prospectively investigated pain response after short-course palliative radiation therapy in patients with moderate-to-severe pancreatic cancer-related pain. In this prospective phase 2 single center nonrandomized trial, 30 patients with moderate-to-severe pain (5-10, on a 0-10 scale) of pancreatic cancer refractory to pain medication, were treated with a short-course palliative radiation therapy; 24 Gy in 3 weekly fractions (2015-2018). Primary endpoint was defined as a clinically relevant average decrease of ≥2 points in pain severity, compared with baseline, within 7 weeks after the start of treatment. Secondary endpoint was global quality of life (QoL), with a clinically relevant increase of 5 to 10 points (0-100 scale). Pain severity reduction and QoL were assessed 9 times using the Brief Pain Inventory and European Organization for Research and Treatment of Cancer Quality of Life Questionnaire-C15-PAL, respectively. Both outcomes were analyzed using joint modeling. In addition, acute toxicity based on clinician reporting and overall survival (OS) were assessed. Overall, 29 of 30 patients (96.7%) received palliative radiation therapy. At baseline, the median oral morphine equivalent daily dose was 129.5 mg (range, 20.0-540.0 mg), which decreased to 75.0 mg (range, 15.0-360.0 mg) after radiation (P =.021). Pain decreased on average 3.15 points from baseline to 7 weeks (one-sided P =.045). Patients reported a clinically relevant mean pain severity reduction from 5.9 to 3.8 points (P =.011) during the first 3 weeks, which further decreased to 3.2 until week 11, ending at 3.4 (P =.006) in week 21 after the first radiation therapy fraction. Global QoL significantly improved from 50.5 to 60.8 during the follow-up period (P =.001). Grade 3 acute toxicity occurred in 3 patients and no grade 4 to 5 toxicity was observed. Median OS was 11.8 weeks, with a 13.3% 1-year actuarial OS rate. Short-course palliative radiation therapy for pancreatic cancer-related pain was associated with rapid, clinically relevant reduction in pain severity, and clinically relevant improvement in global QoL, with mostly mild toxicity. [ABSTRACT FROM AUTHOR]

Objectives: To investigate the implications of addressing informative missing binary outcome data (MOD) on network meta-analysis (NMA) estimates while applying the missing at random (MAR) assumption under different prior structures of the missingness parameter.Methods: In three motivating examples, we compared six different prior structures of the informative missingness odds ratio (IMOR) parameter in logarithmic scale under pattern-mixture and selection models. Then, we simulated 1000 triangle networks of two-arm trials assuming informative MOD related to interventions. We extended the Bayesian random-effects NMA model for binary outcomes and node-splitting approach to incorporate these 12 models in total. With interval plots, we illustrated the posterior distribution of log OR, common between-trial variance (τ2 ), inconsistency factor and probability of being best per intervention under each model.Results: All models gave similar point estimates for all NMA estimates regardless of simulation scenario. For moderate and large MOD, intervention-specific prior structure of log IMOR led to larger posterior standard deviation of log ORs compared to trial-specific and common-within-network prior structures. Hierarchical prior structure led to slightly more precise τ2 compared to identical prior structure, particularly for moderate inconsistency and large MOD. Pattern-mixture and selection models agreed for all NMA estimates.Conclusions: Analyzing informative MOD assuming MAR with different prior structures of log IMOR affected mainly the precision of NMA estimates. Reviewers should decide in advance on the prior structure of log IMOR that best aligns with the condition and interventions investigated. [ABSTRACT FROM AUTHOR]

Background Difficult cannulation represents a common obstacle during endoscopic retrograde cholangiopancreatography (ERCP). We assessed the efficacy and adverse events of transpancreatic sphincterotomy (TPS), and investigated potential associated confounders. Methods All patients referred to our department for ERCP during 2015-2020 were eligible if they had intact papilla and visceral anatomy. In addition to standard measures, TPS was combined with pancreatic stent placement. Apart from demographics, we retrieved data related to the indication, periampullary anatomy, necessity for TPS or fistulotomy, their outcomes and complications. Chi-square test was employed to investigate associations between TPS and independent variables. When significance was observed, the respective variables were inserted into a regression model. Results A total of 1082 individual patients were eligible, with an equal female: male ratio and a mean age of 72.7±15.82 years. Seventy-three patients (6.7%) underwent TPS, with a 95.9% successful cannulation rate. Papilla morphology or regional diverticulum did not affect the decision to perform TPS, though it was significantly associated with malignant common bile duct (CBD) obstruction as the ERCP indication (P=0.001). Considering adverse events, TPS did not increase the incidence of post-ERCP pancreatitis (PEP), though it affected bleeding (P=0.005). Regression analysis revealed a protective role of TPS against PEP (risk ratio [RR] 0.015, 95% confidence interval [CI] 0.23-5.05; P<0.001), while the aforementioned risk of hemorrhage was attributed to previous precut attempts (RR 3.02, 95%CI 1.42-6.43; P=0.004). Conclusion TPS combined with pancreatic stenting is an effective and safe modality in difficult cannulation cases and could be the first-choice alternative in malignant CBD obstruction. [ABSTRACT FROM AUTHOR]

Background: The study was aimed to estimate the true prevalence of human tuberculosis (TB); identify risk factors and clinical symptoms of TB; and detect rifampicin (RIF) sensitivity in three study areas of Bangladesh. Methods: The cross-sectional study was conducted in three Bangladesh districts during 2018. Potential risk factors, clinical symptoms, and comorbidities were collected from 684 TB suspects. Sputum specimens were examined by LED microscopy. TB hierarchical true prevalence, risk factors and clinical symptoms were estimated and identified using a Bayesian analysis framework. Rifampicin sensitivity of M. tuberculosis (MTB) was detected by GeneXpert MTB/RIF assay. Results: The median TB true prevalence was 14.2% (3.8; 34.5). Although overall clustering of prevalence was not found, several DOTS centers were identified with high prevalence (22.3% to 43.7%). Risk factors for TB identified (odds ratio) were age (> 25 to 45 years 2.67 (1.09; 6.99), > 45 to 60 years 3.43 (1.38; 9.19) and individuals in families/neighborhoods where a TB patient(s) has (ve) already been present (12.31 (6.79; 22.60)). Fatigue, night sweat, fever and hemoptysis were identified as important clinical symptoms. Seven of the GeneXpert MTB/RIF positive sputum specimens (65) were resistant to rifampicin. Conclusions: About one in every seven TB suspects was affected with TB. A number of the TB patients carry multi drug resistant MTB. Hierarchical true prevalence estimation allowed identifying DOTS centers with high TB burden. Insights from this study will enable more efficient use of DOTScenters-based TB surveillance to end the TB epidemic in Bangladesh by 2035. [ABSTRACT FROM AUTHOR]

Background: Radiofrequency catheter ablation remains the most effective management option for atrioventricular nodal reentry tachycardia (AVNRT). The risk of atrioventricular (AV) block requiring permanent pacemaker is substantial, but, currently, a reliable method to predict this complication is lacking. Methods: The electrophysiologic studies (EPS) and baseline characteristics of patients who underwent catheter ablation for the treatment of AVNRT were retrospectively analyzed to investigate predisposing factors for AV block after treatment. Patients were followed for AV block at one month and one year after hospital discharge. Results: Among 784 patients treated with catheter ablation for AVNRT between 1999 to 2019, 15 developed AV block. Patients with AV block were older (p =.001). Among the recorded EPS parameters, patients with AV block had significantly higher Atrial His interval (120 vs. 110 ms, p =.049), Wenckebach cycle length (WCL) (400 vs. 353 ms, p <.001) and tachycardia CL (400 vs. 387 ms, P =.01) during the ablation compared to their peers without AV block. Additionally, only WCL (OR = 1.1, 95% CI 1.02‐1.19, p =.017) remained significant after adjustment for age, gender, ERP, AH interval, and HR. This association was confirmed by comparing patients with (n = 15) and without (n = 15) AV block using propensity score‐matching. A WCL≥400ms was associated with a 4‐fold higher incidence of AV block (4.79% vs. 1.25%). Conclusion: Increased pre‐procedural WCL was associated with a high risk for AV block after catheter ablation treatment for AVNRT. These findings suggest that this readily available EPS‐derived parameter may be a novel marker of risk for severe complications in these patients. [ABSTRACT FROM AUTHOR]

In conclusion, the present systematic review and meta-analysis showed that in patients with previous cardiovascular events, the risk of stroke was significantly reduced in patients with and without previous stroke treated with PCSK9 inhibitors irrespective of the baseline LDL-C levels. Keywords: Lipid-lowering; Statin; PCSK9 inhibitor; Evolocumab; Alirocumab; Stroke EN Lipid-lowering Statin PCSK9 inhibitor Evolocumab Alirocumab Stroke 130 132 3 03/03/21 20210301 NES 210301 Dear Editor, over the last decades lipid-modifying strategies made a pivotal change in cardiovascular prevention especially in patients with previous coronary artery disease or ischemic stroke. The beneficial effect of PCSK9 inhibitors in patients with previous cardiovascular events and stroke was not related to an increase of hemorrhagic stroke rates, irrespectively of the LDL-C levels. [Extracted from the article]

Background: Amyloid-β (1-40) (Aβ40) is implicated in mechanisms related to plaque destabilization and correlates with adverse outcomes in stable coronary artery disease.Objective: To determine the prognostic and reclassification value of baseline circulating levels of Aβ40 after adjustment for the Global Registry of Acute Coronary Events (GRACE) score, which is widely recommended for risk stratification in non-ST-segment elevation acute coronary syndrome (NSTE-ACS).Design: Retrospective cohort study using data from 2 independent prospective cohorts, the Heidelberg study (n = 1145) and the validation multicenter international APACE (Advantageous Predictors of Acute Coronary Syndrome Evaluation) study (n = 734).Setting: Academic hospitals in 7 European countries.Participants: Patients with adjudicated NSTE-ACS followed for a median of 21.9 and 24.9 months in the Heidelberg and APACE studies, respectively.Measurements: All-cause mortality was the primary end point.Results: Amyloid-β (1-40) was associated with mortality after multivariate adjustment for age, sex, diabetes mellitus, high-sensitivity cardiac troponin T and C-reactive protein, revascularization, and ACS type (Heidelberg cohort hazard ratio [HR] for 80th vs. 20th percentiles, 1.66 [95% CI, 1.06 to 2.61; P = 0.026]; APACE cohort HR, 1.50 [CI, 1.15 to 1.96; P = 0.003]). It was also associated with mortality after adjustment for the GRACE score (Heidelberg cohort HR for 80th vs. 20th percentiles, 1.11 [CI, 1.04 to 1.18; P = 0.001]; APACE cohort HR, 1.39 [CI, 1.02 to 1.88; P = 0.036]). Amyloid-β (1-40) correctly reclassified risk for death over the GRACE score (net reclassification index, 33.4% and 47.1% for the Heidelberg and APACE cohorts, respectively) (P < 0.05).Limitation: At low concentrations of Aβ40, dose-response associations with mortality differed between cohorts, possibly because of varying blood preparations used to measure Aβ40.Conclusion: Circulating Aβ40 is a predictor of mortality and improves risk stratification of patients with NSTE-ACS over the GRACE score recommended by clinical guidelines. The clinical application of Aβ40 as a novel biomarker in NSTE-ACS should be further explored and validated.Primary Funding Source: German Cardiac Society. [ABSTRACT FROM AUTHOR]

Aims: The relationship between serum uric acid (SUA) and microvascular remodeling in humans remains largely unexplored. We assessed whether SUA provides additional information on the severity of microvascular remodeling than that obtained from the European Heart Score (HS), the patterns of microvascular remodeling associated with changes in SUA levels and the mediation by endothelial function and nitric oxide (NO) availability on this relationship. Methods: A total of 162 patients included in the microvascular dataset of the Italian Society of Hypertension with available information on SUA, media-to-lumen (M/L) ratio, media cross-sectional area (MCSA), endothelial function, NO availability and HS were included in the analysis. The top tertile of M/L ratio and MCSA were used to define severe microvascular remodeling. Results: A U-shaped association was observed between SUA and both M/L ratio and MCSA. Adjustment for HS did not affect these associations. SUA was able to reclassify a significant number of subjects without, and with, severe M/L ratio and MCSA remodeling over the HS alone. The microvascular remodeling associated with SUA levels presented a predominant hypertrophic pattern. SUA was inversely associated with endothelial function and NO availability. Structural equation modeling analysis controlling for the HS suggested that the association of SUA with M/L ratio and MCSA was mediated through changes in endothelial function and NO availability. Conclusions: The addition of SUA to the HS improves the identification of subjects with greater microvascular remodeling. The relationship between SUA and microvascular remodeling is mediated by endothelial function and NO availability. [ABSTRACT FROM AUTHOR]

Background: The ASTERIX project developed a number of novel methods suited to study small populations. The objective of this exercise was to evaluate the applicability and added value of novel methods to improve drug development in small populations, using real world drug development programmes as reported in European Public Assessment Reports.Methods: The applicability and added value of thirteen novel methods developed within ASTERIX were evaluated using data from 26 European Public Assessment Reports (EPARs) for orphan medicinal products, representative of rare medical conditions as predefined through six clusters. The novel methods included were 'innovative trial designs' (six methods), 'level of evidence' (one method), 'study endpoints and statistical analysis' (four methods), and 'meta-analysis' (two methods) and they were selected from the methods developed within ASTERIX based on their novelty; methods that discussed already available and applied strategies were not included for the purpose of this validation exercise. Pre-requisites for application in a study were systematized for each method, and for each main study in the selected EPARs it was assessed if all pre-requisites were met. This direct applicability using the actual study design was firstly assessed. Secondary, applicability and added value were explored allowing changes to study objectives and design, but without deviating from the context of the drug development plan. We evaluated whether differences in applicability and added value could be observed between the six predefined condition clusters.Results and Discussion: Direct applicability of novel methods appeared to be limited to specific selected cases. The applicability and added value of novel methods increased substantially when changes to the study setting within the context of drug development were allowed. In this setting, novel methods for extrapolation, sample size re-assessment, multi-armed trials, optimal sequential design for small sample sizes, Bayesian sample size re-estimation, dynamic borrowing through power priors and fall-back tests for co-primary endpoints showed most promise - applicable in more than 40% of evaluated EPARs in all clusters. Most of the novel methods were applicable to conditions in the cluster of chronic and progressive conditions, involving multiple systems/organs. Relatively fewer methods were applicable to acute conditions with single episodes. For the chronic clusters, Goal Attainment Scaling was found to be particularly applicable as opposed to other (non-chronic) clusters.Conclusion: Novel methods as developed in ASTERIX can improve drug development programs. Achieving optimal added value of these novel methods often requires consideration of the entire drug development program, rather than reconsideration of methods for a specific trial. The novel methods tested were mostly applicable in chronic conditions, and acute conditions with recurrent episodes. [ABSTRACT FROM AUTHOR]