Two-stage group-sequential designs with delayed responses - what is the point of applying corresponding methods?

Background: In group-sequential designs, it is typically assumed that there is no time gap between patient enrollment and outcome measurement in clinical trials. However, in practice, there is usually a lag between the two time points. This can affect the statistical analysis of the data, especially in trials with interim analyses.

A two-stage group-sequential design for delayed treatment responses with the possibility of trial restart.

Common statistical theory applicable to confirmatory phase III trial designs usually assumes that patients are enrolled simultaneously and there is no time gap between enrollment and outcome observation. However, in practice, patients are enrolled successively and there is a lag between the enrollment of a patient and the measurement of the primary outcome. For single-stage designs, the difference between theory and practice only impacts on the trial duration but not on the statistical analysis and its interpretation.

Using short-term endpoints to improve interim decision making and trial duration in two-stage phase II trials with nested binary endpoints.

In oncology, phase II clinical trials are often planned as single-arm two-stage designs with a binary endpoint, for example, progression-free survival after 12 months, and the option to stop for futility after the first stage. Simon's two-stage design is a very popular approach but depending on the follow-up time required to measure the patients' outcomes the trial may have to be paused undesirably long. To shorten this forced interruption, it was proposed to use a short-term endpoint for the interim decision, such as progression-free survival after 3 months.

Should the two-trial paradigm still be the gold standard in drug assessment?

Two significant pivotal trials are usually required for a new drug approval by a regulatory agency. This standard requirement is known as the two-trial paradigm. However, several authors have questioned why we need exactly two pivotal trials, what statistical error the regulators are trying to protect against, and potential alternative approaches.

Clinical Trials Impacted by the COVID-19 Pandemic: Adaptive Designs to the Rescue?

Very recently the new pathogen severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified and the coronavirus disease 2019 (COVID-19) declared a pandemic by the World Health Organization. The pandemic has a number of consequences for ongoing clinical trials in non-COVID-19 conditions. Motivated by four current clinical trials in a variety of disease areas we illustrate the challenges faced by the pandemic and sketch out possible solutions including adaptive designs.

Interim analysis incorporating short- and long-term binary endpoints.

Designs incorporating more than one endpoint have become popular in drug development. One of such designs allows for incorporation of short-term information in an interim analysis if the long-term primary endpoint has not been yet observed for some of the patients. At first we consider a two-stage design with binary endpoints allowing for futility stopping only based on conditional power under both fixed and observed effects.

Confidence regions for treatment effects in subgroups in biomarker stratified designs.

Subgroup analysis has important applications in the analysis of controlled clinical trials. Sometimes the result of the overall group fails to demonstrate that the new treatment is better than the control therapy, but for a subgroup of patients, the treatment benefit may exist; or sometimes, the new treatment is better for the overall group but not for a subgroup. Hence we are interested in constructing a simultaneous confidence interval for the difference of the treatment effects in a subgroup and the overall group.

An alternative method to analyse the biomarker-strategy design.

Recent developments in genomics and proteomics enable the discovery of biomarkers that allow identification of subgroups of patients responding well to a treatment. One currently used clinical trial design incorporating a predictive biomarker is the so-called biomarker strategy design (or marker-based strategy design). Conventionally, the results from this design are analysed by comparing the mean of the biomarker-led arm with the mean of the randomised arm.

Blinded versus unblinded estimation of a correlation coefficient to inform interim design adaptations.

Regulatory authorities require that the sample size of a confirmatory trial is calculated prior to the start of the trial. However, the sample size quite often depends on parameters that might not be known in advance of the study. Misspecification of these parameters can lead to under- or overestimation of the sample size.

Flexible selection of a single treatment incorporating short-term endpoint information in a phase II/III clinical trial.

Seamless phase II/III clinical trials in which an experimental treatment is selected at an interim analysis have been the focus of much recent research interest. Many of the methods proposed are based on the group sequential approach. This paper considers designs of this type in which the treatment selection can be based on short-term endpoint information for more patients than have primary endpoint data available.

Two-stage phase II oncology designs using short-term endpoints for early stopping.

Phase II oncology trials are conducted to evaluate whether the tumour activity of a new treatment is promising enough to warrant further investigation. The most commonly used approach in this context is a two-stage single-arm design with binary endpoint. As for all designs with interim analysis, its efficiency strongly depends on the relation between recruitment rate and follow-up time required to measure the patients' outcomes.

Data-driven treatment selection for seamless phase II/III trials incorporating early-outcome data.

Seamless phase II/III clinical trials are conducted in two stages with treatment selection at the first stage. In the first stage, patients are randomized to a control or one of k > 1 experimental treatments. At the end of this stage, interim data are analysed, and a decision is made concerning which experimental treatment should continue to the second stage.

A comparison of methods for treatment selection in seamless phase II/III clinical trials incorporating information on short-term endpoints.

In an adaptive seamless phase II/III clinical trial interim analysis, data are used for treatment selection, enabling resources to be focused on comparison of more effective treatment(s) with a control. In this paper, we compare two methods recently proposed to enable use of short-term endpoint data for decision-making at the interim analysis. The comparison focuses on the power and the probability of correctly identifying the most promising treatment.

Strategies for reducing potentially avoidable hospitalizations for ambulatory care-sensitive conditions.

Purpose: Hospitalizations for ambulatory care-sensitive conditions (ACSCs) are seen as potentially avoidable with optimal primary care. Little is known, however, about how primary care physicians rate these hospitalizations and whether and how they could be avoided. This study explores the complex causality of such hospitalizations from the perspective of primary care physicians.

The group-based social skills training SOSTA-FRA in children and adolescents with high functioning autism spectrum disorder--study protocol of the randomised, multi-centre controlled SOSTA--net trial.

Background: Group-based social skills training (SST) has repeatedly been recommended as treatment of choice in high-functioning autism spectrum disorder (HFASD). To date, no sufficiently powered randomised controlled trial has been performed to establish efficacy and safety of SST in children and adolescents with HFASD. In this randomised, multi-centre, controlled trial with 220 children and adolescents with HFASD it is hypothesized, that add-on group-based SST using the 12 weeks manualised SOSTA-FRA program will result in improved social responsiveness (measured by the parent rated social responsiveness scale, SRS) compared to treatment as usual (TAU).

Direct comparison of the FibroScan XL and M probes for assessment of liver fibrosis in obese and nonobese patients.

Background: A novel Fibroscan XL probe has recently been introduced and validated for obese patients, and has a diagnostic accuracy comparable with that of the standard M probe. The aim of this study was to analyze and understand the differences between these two probes in nonobese patients, to identify underlying causes for these differences, and to develop a practical algorithm to translate results for the XL probe to those for the M probe.

Methods And Results: Both probes were directly compared first in copolymer phantoms of varying stiffness (4.

Estimation of secondary endpoints in two-stage phase II oncology trials.

In the development of a new treatment in oncology, phase II trials play a key role. On the basis of the data obtained during phase II, it is decided whether the treatment should be studied further. Therefore, the decision to be made on the basis of the data of a phase II trial must be as accurate as possible.

Curtailment in single-arm two-stage phase II oncology trials.

Two-stage designs that allow for early stopping if the treatment is ineffective are commonly used in phase II oncology trials. A limitation of current designs is that early stopping is only allowed at the end of the first stage, even if it becomes evident during the trial that a significant result is unlikely. One way to overcome this limitation is to implement stochastic curtailment procedures that enable stopping the trial whenever the conditional power is below a pre-specified threshold θ.

Patterns of multimorbidity in primary care patients at high risk of future hospitalization.

Care management is seen as a promising approach to address the complex care needs of patients with multimorbidity. Predictive modeling based on insurance claims data is an emerging concept to identify patients likely to benefit from care management interventions. We aimed to identify and explore patterns of multimorbidity in primary care patients with high predicted risk of future hospitalizations in order to develop a primary care-based care management intervention.

Health related quality of life and comorbidity. A descriptive analysis comparing EQ-5D dimensions of patients in the German disease management program for type 2 diabetes and patients in routine care.

Background: The co-occurance of multiple medical conditions has a negative impact on health related quality of life (HRQoL) for patients with type 2 diabetes. These patients demand for intensified care programs. Participation in a disease management program (DMP) for type 2 diabetes has shown to counterbalance this effect.

Patient- and provider-related determinants of generic and specific health-related quality of life of patients with chronic systolic heart failure in primary care: a cross-sectional study.

Background: Identifying the determinants of health-related quality of life (HRQOL) in patients with systolic heart failure (CHF) is rare in primary care; studies often lack a defined sample, a comprehensive set of variables and clear HRQOL outcomes. Our aim was to explore the impactof such a set of variables on generic and disease-specific HRQOL.

Methods: In a cross-sectional study, we evaluated data from 318 eligible patients.

Measuring organizational attributes in primary care: a validation study in Germany.

Objective: Models for the structured delivery of care rely on organizational attributes of practice teams. The Survey of Organizational Attributes for Primary Care (SOAPC) is known to be a valid instrument to measure this aspect in the primary care setting. The aim of this study was to determine the validity of a translated and culturally adapted German version of the SOAPC.

Case management for patients with chronic systolic heart failure in primary care: the HICMan exploratory randomised controlled trial.

Background: Chronic (systolic) heart failure (CHF) represents a clinical syndrome with high individual and societal burden of disease. Multifaceted interventions like case management are seen as promising ways of improving patient outcomes, but lack a robust evidence base, especially for primary care. The aim of the study was to explore the effectiveness of a new model of CHF case management conducted by doctors' assistants (DAs, equivalent to a nursing role) and supported by general practitioners (GPs).