Use of win time for ordered composite endpoints in clinical trials.

Consider the choice of outcome for overall treatment benefit in a clinical trial which measures the first time to each of several clinical events. We describe several new variants of the win ratio that incorporate the time spent in each clinical state over the common follow-up, where clinical state means the worst clinical event that has occurred by that time. One version allows restriction so that death during follow-up is most important, while time spent in other clinical states is still accounted for. Three other variants are described; one is based on the average pairwise win time, one creates a continuous outcome for each participant based on expected win times against a reference distribution and another that uses the estimated distributions of clinical state to compare the treatment arms. Finally, a combination testing approach is described to give robust power for detecting treatment benefit across a broad range of alternatives. These new methods are designed to be closer to the overall treatment benefit/harm from a patient's perspective, compared to the ordinary win ratio. The new methods are compared to the composite event approach and the ordinary win ratio. Simulations show that when overall treatment benefit on death is substantial, the variants based on either the participants' expected win times (EWTs) against a reference distribution or estimated clinical state distributions have substantially higher power than either the pairwise comparison or composite event methods. The methods are illustrated by re-analysis of the trial heart failure: a controlled trial investigating outcomes of exercise training.

Development of a Core Outcome Set for Dysphagia Interventions in Parkinson's disease (COS-DIP): study protocol.

INTRODUCTION: Current clinical trials on swallowing disorders (dysphagia) in Parkinson's disease (PD) apply a high variety of outcomes and different outcome measures making comparative effectiveness research challenging. Furthermore, views of patients and dysphagia clinicians when selecting trial outcomes have not been considered in the past, thus study results may have little importance to them. This study aims to develop an agreed standardised Core Outcome Set for Dysphagia Interventions in Parkinson's disease (COS-DIP), systematically measured and reported as a minimum for all clinical trials. It will also comprise guidance on outcome definitions, outcome measures and time points of measurement. METHODS AND ANALYSIS: The COS-DIP development will comprise five stages following established methodology: (1) a recent scoping review on all applied outcomes, their definitions, methods and time points of measurement in clinical trials in dysphagia in PD, (2) online surveys and focus groups with clinicians, patients, caregivers and family members to identify outcomes that are important to them, (3) an identified list of outcomes based on results of stage 1 and 2, (4) three round online Delphi survey with up to 200 key stakeholders to determine core outcomes and (5) two online consensus meetings with up to 40 representative key stakeholders to agree on all outcomes, definitions, methods and time points of measurement in the final COS-DIP. ETHICS AND DISSEMINATION: Full ethical approval was obtained from the Research Ethics Committee, School of Linguistic, Speech and Communication Sciences, Trinity College Dublin, on 15 May 2023 (HT27). Dissemination of the COS-DIP will be enhanced through presentations at (inter-) national conferences and through peer-reviewed, open access publications of related manuscripts. Lay and professional information sheets and infographics will be circulated through relevant patient and professional organisations and networks. TRIAL REGISTRATION NUMBER: The COS-DIP study was registered prospectively with the Core Outcome Measures in Effectiveness Trials (COMET) database on 24 September 2021 (www.comet-initiative.org/Studies/Details/1942).

An information-theoretic approach for the assessment of a continuous outcome as a surrogate for a binary true endpoint based on causal inference: Application to vaccine evaluation.

Within the causal association paradigm, a method is proposed to assess the validity of a continuous outcome as a surrogate for a binary true endpoint. The methodology is based on a previously introduced information-theoretic definition of surrogacy and has two main steps. In the first step, a new model is proposed to describe the joint distribution of the potential outcomes associated with the putative surrogate and the true endpoint of interest. The identifiability issues inherent to this type of models are handled via sensitivity analysis. In the second step, a metric of surrogacy new to this setting, the so-called individual causal association is presented. The methodology is studied in detail using theoretical considerations, some simulations, and data from a randomized clinical trial evaluating an inactivated quadrivalent influenza vaccine. A user-friendly R package Surrogate is provided to carry out the evaluation exercise.

Assessment highlights need for improvement in standards of development of core outcome sets for rare genetic diseases.

OBJECTIVES: A rare disease is classified as such if it affects less than one person in 2,000. The Core Outcome Set STandards for Development (COS-STAD) is a set of standards that represent the minimum recommendations to be considered in the process of core outcome set (COS) development. The aim of this study was to provide a baseline assessment of COS development standards for rare genetic diseases. STUDY DESIGN AND SETTING: Core Outcome Measures in Effectiveness Trials (COMET) database contains nearly 400 published COS studies according to the latest systematic review. Studies focusing on COS development for rare genetic diseases were eligible for inclusion and were assessed by two independent evaluators. RESULTS: Nine COS studies were included in the analysis. Eight different rare genetic diseases were investigated. None of the studies met all the standards for development. The number of standards met ranged from 6 to 10, and the median was 7. CONCLUSION: This study is the first study to assess COS-STAD for rare genetic diseases, and it highlights a great need for improvement. First in terms of numbers of rare diseases considered for COS developments, second in methodology, particularly regarding the consensus process, and third in reporting of the COS development studies.

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. We show that if the assumptions for the short-term endpoint are misspecified, the decision-making in the interim can be misleading, resulting in a great loss of statistical power. For the setting of a binary endpoint with nested measurements, such as progression-free survival, we propose two approaches that utilize all available short-term and long-term assessments of the endpoint to guide the interim decision. One approach is based on conditional power and the other is based on Bayesian posterior predictive probability of success. In extensive simulations, we show that both methods perform similarly, when appropriately calibrated, and can greatly improve power compared to the existing approach in settings with slow patient recruitment. Software code to implement the methods is made publicly available.

The development of a core outcome set for clinical effectiveness studies of bordered foam dressings in the treatment of complex wounds.

AIM: The aim of this project was to develop a core outcome set (COS) for clinical effectiveness studies of bordered foam dressings in the treatment of complex wounds. METHODS: The research project followed the Core Outcome Measures in Effectiveness Trials (COMET) initiative and consisted of two phases. The first phase prepared the background and process, while the second phase had three steps: outcome list generation via systematic review and qualitative study, Delphi consensus study, and consensus meeting. The study has been registered in the Core Outcome Measures in Effectiveness Trials database. RESULTS: The systematic review resulted in 82 outcomes and 20 additional outcomes were obtained during the interviews. After refinement, 111 panellists from 23 countries rated a list of 51 outcomes. In the following consensus meeting, six outcomes were prioritized to be included in the core outcome set. After the consensus meeting, a patient-reported outcome was added to the core outcome set. CONCLUSION: The COS for evaluating the effectiveness of bordered foam dressings in treating complex wounds includes 7 outcomes: "ability to stay in place", "leakage", "pain", "dressing related periwound skin changes", "change in wound size over time", and "overall satisfaction". These identified outcomes are correlated with contemporary bioengineering testing and evaluation methods for dressing performance, which underpins the need for a close multidisciplinary collaboration to advance the field of wound dressings. The outcome 'overall satisfaction' reflects the impact of complex wounds and their treatment on a patient's daily life. The use of these outcomes is recommended to improve data synthesis and promote evidence-based practice. Future developments in COS development involve creating measurement instruments and relevant endpoints for these outcomes.

Omnibus test for restricted mean survival time based on influence function.

The restricted mean survival time (RMST), which evaluates the expected survival time up to a pre-specified time point τ, has been widely used to summarize the survival distribution due to its robustness and straightforward interpretation. In comparative studies with time-to-event data, the RMST-based test has been utilized as an alternative to the classic log-rank test because the power of the log-rank test deteriorates when the proportional hazards assumption is violated. To overcome the challenge of selecting an appropriate time point τ, we develop an RMST-based omnibus Wald test to detect the survival difference between two groups throughout the study follow-up period. Treating a vector of RMSTs at multiple quantile-based time points as a statistical functional, we construct a Wald χ2 test statistic and derive its asymptotic distribution using the influence function. We further propose a new procedure based on the influence function to estimate the asymptotic covariance matrix in contrast to the usual bootstrap method. Simulations under different scenarios validate the size of our RMST-based omnibus test and demonstrate its advantage over the existing tests in power, especially when the true survival functions cross within the study follow-up period. For illustration, the proposed test is applied to two real datasets, which demonstrate its power and applicability in various situations.

Development of core outcome sets of Food for Special Medical Purposes designed for type 2 diabetes mellitus: a study protocol.

BACKGROUND: The Chinese government stipulates all food for special medical purposes (FSMP) designed for specific diseases to be tested in clinical trials before approving it for registration. The process of developing core outcome sets (COSs), the minimum sets of outcomes supposed to be measured and reported, provides an economical and practical option for stakeholders to communicate and cooperate in conducting clinical trials as well as in reporting FSMP outcomes. This study uses type 2 diabetes mellitus (T2DM) as an example to develop COS for clinical trials of FSMP. METHODS: The COS for FSMP-T2DM will be divided into 3 phases and developed following COS-STAP and COS-STAD: (1) Generate a list of relevant outcomes identified from a systematic review, in which information sources will mainly include published studies, regulatory documentation, and qualitative interviews of stakeholders. The identified outcomes will be categorized using a conceptual framework and formatted into the first round of the Delphi survey questionnaire items. (2) At least 2 rounds of Delphi surveys will be performed among stakeholders to create the COS for FSMP-T2DM. Patients, clinical dietitians, physicians, COS researchers, journal editors, FSMP manufacturers, and regulatory representatives will be invited to score each outcome from aspects of importance. (3) Hold a face-to-face or online consensus meeting to refine the content of the COS for FSMP-T2DM. Key stakeholders will be invited to attend the meeting to discuss and agree on the final COS. DISCUSSION: We have prepared an alternative solution of the Likert scale selection, Delphi survey rounds, scoring group, and consensus definitions in case of an unexpected situation. TRIAL REGISTRATION: COMET (1547). Registered on March 23, 2020.

A note on familywise error rate for a primary and secondary endpoint.

Hung et al. (2007) considered the problem of controlling the type I error rate for a primary and secondary endpoint in a clinical trial using a gatekeeping approach in which the secondary endpoint is tested only if the primary endpoint crosses its monitoring boundary. They considered a two-look trial and showed by simulation that the naive method of testing the secondary endpoint at full level α at the time the primary endpoint reaches statistical significance does not control the familywise error rate at level α. Tamhane et al. (2010) derived analytic expressions for familywise error rate and power and confirmed the inflated error rate of the naive approach. Nonetheless, many people mistakenly believe that the closure principle can be used to prove that the naive procedure controls the familywise error rate. The purpose of this note is to explain in greater detail why there is a problem with the naive approach and show that the degree of alpha inflation can be as high as that of unadjusted monitoring of a single endpoint.

Design of paediatric trials with benefit-risk endpoints using a composite score of adverse events of interest (AEI) and win-statistics.

A fundamental problem in the regulatory evaluation of a therapy is assessing whether the benefit outweighs the associated risks. This work proposes designing a trial that assesses a composite endpoint consisting of benefit and risk, hence, making the core of the design of the study, to assess benefit and risk. The proposed benefit risk measure consists of efficacy measure(s) and a risk measure that is based on a composite score obtained from pre-defined adverse events of interest (AEI). This composite score incorporates full aspects of adverse events of interest (i.e. the incidence, severity, and duration of the events). We call this newly proposed score the AEI composite score. After specifying the priorities between the components of the composite endpoint, a win-statistic (i.e. win ratio, win odds, or net benefit) is used to assess the difference between treatments in this composite endpoint. The power and sample size requirements of such a trial design are explored via simulation. Finally, using Dupixent published adult study results, we show how we can design a paediatric trial where the primary outcome is a composite of prioritized outcomes consisting of efficacy endpoints and the AEI composite score endpoint. The resulting trial design can potentially substantially reduce sample size compared to a trial designed to assess the co-primary efficacy endpoints, therefore it may address the challenge of slow enrollment and patient availability for paediatric studies.

Pediatric core outcome sets had deficiencies and lacked child and family input: A methodological review.

OBJECTIVES: The Core Outcome Set-STAndards for Development (COS-STAD), published in 2017, contains 11 standards (12 criteria) describing minimum design criteria for core outcome set (COS) development. We aimed to identify and appraise all pediatric COS published prior to COS-STAD, and assess methods of child and family involvement in their development. STUDY DESIGN AND SETTING: This methodological review included documents that described the development of pediatric COS up to and including 2017. Reviewers independently assessed each COS against COS-STAD criteria, and methods of involvement were synthesized. RESULTS: A total of 56 pediatric COS were identified, meeting a median of five COS-STAD criteria. Nearly all met criteria on COS scope specification for setting, health condition, and population; 41% met criteria for intervention. Standards were more often met for the involvement of researchers/health professionals (64%) than for patients or their representatives (29%). Few met standards for achieving COS consensus (4-23%). Methods of child and family engagement varied and were limited. CONCLUSION: A large proportion of pediatric COS developed prior to COS-STAD recommendations show gaps in design methodology. Updated and newly developed pediatric COS would benefit from the inclusion of the child and family voice, implementing a priori criteria for COS consensus, and clear reporting.

Uptake of core outcome sets by clinical trialists in China: a protocol.

Background: The concept of core outcome sets (COS) has been introduced in China for about 10 years. In recent years, some Chinese researchers also committed to developing COS, though the majority of COS are ongoing. However, there were more than 500 published COS for research in the COMET database by 2020. The extent of availability of COS for the top 25 diseases with the highest burden in China is unknown. In addition, the uptake of COS in clinical trials for these diseases is unknown, along with the knowledge, perceptions, and views of the clinical trialist community in China on the use of COS in relation to choosing outcomes for their research. Methods: The main burden of disease in China will be identified. Then we will search the COMET database to identify if there are ongoing or completed relevant COS research A COS published since 2012 would be preferred to one published before 2012 for the analysis of COS uptake if one meets the eligibility criteria. We will extract scopes of published eligible COS, including condition, population, interventions, and core outcomes. Then we will search the Chinese Clinical Trial Registry using disease names for each disease that has a published COS. We will assess the overlap in scope between clinical trials and COS. Then we will conduct an online survey and semi-structured interviews to identify the knowledge and perceptions of COS among primary investigators of included clinical trials. Discussion: This research will fill in gaps between COS and the burden of disease in China. Understanding clinical trialists'knowledge and perceptions of COS may help dissemination and application of COS in the future. Trial registration: This research is registered in Core Outcome Measures in Effectiveness: https://www.comet-initiative.org/Studies/Details/2563.

Core Outcome Sets in Child Health: A Systematic Review.

Importance: Developing core outcome sets is essential to ensure that results of clinical trials are comparable and useful. A number of core outcome sets in pediatrics have been published, but a comprehensive in-depth understanding of core outcome sets in this field is lacking. Objective: To systematically identify core outcome sets in child health, collate the diseases to which core outcome sets have been applied, describe the methods used for development and stakeholder participation, and evaluate the methodological quality of existing core outcome sets. Evidence Review: MEDLINE, SCOPUS, Cochrane Library, and CINAHL were searched using relevant search terms, such as clinical trials, core outcome, and children, along with relevant websites, such as Core Outcome Measures in Effectiveness Trials (COMET). Four researchers worked in teams of 2, performed literature screening and data extraction, and evaluated the methodological quality of core outcome sets using the Core Outcome Set-Standards for Development (COS-STAD). Findings: A total of 77 pediatric core outcome sets were identified, mainly developed by organizations or researchers in Europe, North America, and Australia and mostly from the UK (22 [29%]) and the US (22 [29%]). A total of 77 conditions were addressed; the most frequent International Classification of Diseases, 11th Revision category was diseases of the digestive system (14 [18%]). Most of the outcomes in pediatric core outcome sets were unordered (34 [44%]) or presented in custom classifications (29 [38%]). Core outcome sets used 1 or more of 8 development methods; the most frequent combination of methods was systematic review/literature review/scoping review, together with the Delphi approach and consensus for decision-making (10 [14%]). Among the 6 main types of stakeholders, clinical experts were the most frequently involved (74 [100%]), while industry representatives were rarely involved (4 [5%]). Only 6 core outcome sets (8%) met the 12 criteria of COS-STAD. Conclusions and Relevance: Future quality of pediatric core outcome sets should be improved based on the standards proposed by the COMET initiative, while core outcome sets methodology and reporting standards should be extended to pediatric populations to help improve the quality of core outcome sets in child health. In addition, the COMET outcome taxonomy should also add items applicable to children.

Core outcomes for pressure ulcer prevention trials: results of an international consensus study: Classification: Outcomes and qualitative research.

BACKGROUND: There is substantial heterogeneity between trial outcomes in pressure ulcer prevention research. The development of core outcome sets is one strategy to improve comparability between trial results and thus increase the quality of evidence. OBJECTIVES: To identify core outcomes for pressure ulcer prevention trials. METHODS: A workshop was held with service users to discuss their views and understanding of the outcomes identified by a scoping review and to identify any missing outcomes. In a next step, a Delphi survey comprising three rounds was conducted to evaluate a compiled list of outcomes by their importance. Afterwards the preselection from the Delphi survey was discussed in a virtual consensus meeting with the aim of agreeing on a final set of core outcomes. Individuals who had completed all three rounds of the Delphi survey were eligible to participate in this meeting. Participants included practitioners, service users, researchers and industry representatives. The OUTPUTs project is registered in the COMET database and is part of the Cochrane Skin Core Outcome Set Initiative. RESULTS: The workshop did not reveal any missing outcomes, but highlighted the need for further efforts to make lay people understand what an outcome is in a study setting. The Delphi survey took place between December 2020 and June 2021. After the three rounds, 18 out of 37 presented outcomes were rated to be critically important. In the following consensus meeting, six outcomes were prioritized to be included in the core outcome set for pressure ulcer prevention trials: (i) pressure ulcer occurrence; (ii) pressure ulcer precursor signs and symptoms; (iii) mobility; (iv) acceptability and comfort of intervention; (v) adherence/compliance; and (vi) adverse events/safety. CONCLUSIONS: Based on a comprehensive list of outcomes in pressure ulcer prevention research, there was clear agreement on the six identified core outcomes in three international Delphi rounds and in the consensus meeting. Although outcome measurement instruments need to be identified next, the six identified core outcomes should already be considered in future trials, as service users, practitioners, researchers and industry representatives have agreed that they are critically important. What is already known about this topic? There are numerous trials on pressure ulcer prevention, but evidence on the effectiveness of preventive measures is limited due to heterogeneity between trial outcomes. The development of a core outcome set is one strategy to improve comparability between trial results. What does this study add? A service user workshop, a three-round Delphi survey and an online consensus meeting with practitioners, service users, researchers and industry representatives were conducted to identify core outcomes for pressure ulcer prevention trials. Six core outcomes were defined: (i) pressure ulcer occurrence, (ii) pressure ulcer precursor signs and symptoms, (iii) mobility, (iv) acceptability and comfort of intervention, (v) adherence/compliance and (vi) adverse events/safety. What are the clinical implications of this work? Better evidence of interventions for pressure ulcer prevention will help health professionals and service users to decide which interventions are most appropriate and effective. Better evidence may contribute to better pressure ulcer prevention.

Win ratio approach for analyzing composite time-to-event endpoint with opposite treatment effects in its components.

There is an increasing interest in the use of win ratio with composite time-to-event due to its flexibility in combining component endpoints. Exploring this flexibility further, one interesting question is in assessing the impact when there is a difference in treatment effect in the component endpoints. For example, the active treatment may prolong the time to occurrence of the negative event such as death or ventilation; meanwhile, the treatment effect may also shorten the time to achieving positive events, such as recovery or improvement. Notably, this portrays a situation where the treatment effect on time to recovery is in a different direction of benefit compared to the time to ventilation or death. Under such circumstances, if a single endpoint is used, the benefit gained for other individual outcomes is not counted and is diminished. As consequence, the study may need a larger sample size to detect a significant effect of treatment. Such a scenario can be handled by win ratio in a novel way by ranking component events, which is different from the usual composite endpoint approach such as time-to-first event. To evaluate how the different directions of treatment effect on component endpoints will impact the win ratio analysis, we use a Clayton copula-based bivariate survival simulation to investigate the correlation of component time-to-event. Through simulation, we found that compared to the marginal model using single endpoints, the win ratio analysis on composite endpoint performs better, especially when the correlation between two events is weak. Then, we applied the methodology to an infectious disease progression simulated study motivated by COVID-19. The application demonstrates that the win ratio approach offers advantages in empirical power compared to the traditional Cox proportional hazard approach when there is a difference in treatment effect in the marginal events.

Calculating power for the Finkelstein and Schoenfeld test statistic for a composite endpoint with two components.

The Finkelstein and Schoenfeld (FS) test is a popular generalized pairwise comparison approach to analyze prioritized composite endpoints (eg, components are assessed in order of clinical importance). Power and sample size estimation for the FS test, however, are generally done via simulation studies. This simulation approach can be extremely computationally burdensome, compounded by increasing number of composite endpoints and with increasing sample size. Here we propose an analytical solution to calculate power and sample size for commonly encountered two-component hierarchical composite endpoints. The power formulas are derived assuming underlying distributions in each of the component outcomes on the population level, which provide a computationally efficient and practical alternative to the standard simulation approach. Monte Carlo simulation results demonstrate that performance of the proposed power formulas are consistent with that of the simulation approach, and have generally desirable objective properties including robustness to mis-specified distributional assumptions. We demonstrate the application of the proposed formulas by calculating power and sample size for the Transthyretin Amyloidosis Cardiomyopathy Clinical Trial.

Sample size estimation using a latent variable model for mixed outcome co-primary, multiple primary and composite endpoints.

Mixed outcome endpoints that combine multiple continuous and discrete components are often employed as primary outcome measures in clinical trials. These may be in the form of co-primary endpoints, which conclude effectiveness overall if an effect occurs in all of the components, or multiple primary endpoints, which require an effect in at least one of the components. Alternatively, they may be combined to form composite endpoints, which reduce the outcomes to a one-dimensional endpoint. There are many advantages to joint modeling the individual outcomes, however in order to do this in practice we require techniques for sample size estimation. In this article we show how the latent variable model can be used to estimate the joint endpoints and propose hypotheses, power calculations and sample size estimation methods for each. We illustrate the techniques using a numerical example based on a four-dimensional endpoint and find that the sample size required for the co-primary endpoint is larger than that required for the individual endpoint with the smallest effect size. Conversely, the sample size required in the multiple primary case is similar to that needed for the outcome with the largest effect size. We show that the empirical power is achieved for each endpoint and that the FWER can be sufficiently controlled using a Bonferroni correction if the correlations between endpoints are less than 0.5. Otherwise, less conservative adjustments may be needed. We further illustrate empirically the efficiency gains that may be achieved in the composite endpoint setting.

Weighted composite time to event endpoints with recurrent events: comparison of three analytical approaches.

BACKGROUND: In clinical trials the study interest often lies in the comparison of a treatment to a control regarding a time to event endpoint. A composite endpoint allows to consider several time to event endpoints at once. Usually, only the time to the first occurring event for a patient is thereby analyzed. However, an individual may experience more than one non-fatal event. Including all observed events in the analysis can increase the power and provides a more complete picture of the disease. Thus, analytical methods for recurrent events are required. A challenge is that the different event types belonging to the composite often are of different clinical relevance. In this case, weighting the event types according to their clinical relevance is an option. Different weight-based methods for composite time to event endpoints were proposed. So far, there exists no systematic comparison of these methods. METHODS: Within this work we provide a systematic comparison of three methods proposed for weighted composite endpoints in a recurrent event setting combining non-fatal and fatal events of different clinical relevance. We consider an extension of an approach proposed by Wei and Lachin, an approach by Rauch et al., and an approach by Bakal et al.. Comparison is done based on a simulation study and based on a clinical study example. RESULTS: For all three approaches closed formula test statistics are available. The Wei-Lachin approach and the approach by Rauch et al. show similar results in mean squared error. For the approach by Wei and Lachin confidence intervals are provided. The approach by Bakal et al. is not related to a quantifiable estimand. The relevance weights of the different approaches work on different level, i.e. either on cause-specific hazard ratios or on event count. CONCLUSION: The provided comparison and simulations can help to guide applied researchers to choose an adequate method for the analysis of composite endpoints combining (recurrent) events of different clinical relevance. The approach by Wei and Lachin and Rauch et al. can be recommended in scenarios where the composite effect is time-independent. The approach by Bakal et al. should be applied carefully.

Confirmatory adaptive group sequential designs for single-arm phase II studies with multiple time-to-event endpoints.

Existing methods concerning the assessment of long-term survival outcomes in one-armed trials are commonly restricted to one primary endpoint. Corresponding adaptive designs suffer from limitations regarding the use of information from other endpoints in interim design changes. Here we provide adaptive group sequential one-sample tests for testing hypotheses on the multivariate survival distribution derived from multi-state models, while making provision for data-dependent design modifications based on all involved time-to-event endpoints. We explicitly elaborate application of the methodology to one-sample tests for the joint distribution of (i) progression-free survival (PFS) and overall survival (OS) in the context of an illness-death model, and (ii) time to toxicity and time to progression while accounting for death as a competing event. Large sample distributions are derived using a counting process approach. Small sample properties are studied by simulation. An already established multi-state model for non-small cell lung cancer is used to illustrate the adaptive procedure.