Current state-of-the-art and gaps in platform trials: 10 things you should know, insights from EU-PEARL

Platform trials bring the promise of making clinical research more efficient and more patient centric. While their use has become more widespread, including their prominent role during the COVID-19 pandemic response, broader adoption of platform trials has been limited by the lack of experience and tools to navigate the critical upfront planning required to launch such collaborative studies. The European Union-Patient-cEntric clinicAl tRial pLatform (EU-PEARL) initiative has produced new methodologies to expand the use of platform trials with an overarching infrastructure and services embedded into Integrated Research Platforms (IRPs), in collaboration with patient representatives and through consultation with U.S. Food and Drug Administration and European Medicines Agency stakeholders. In this narrative review, we discuss the outlook for platform trials in Europe, including challenges related to infrastructure, design, adaptations, data sharing and regulation. Documents derived from the EU-PEARL project, alongside a literature search including PubMed and relevant grey literature (e.g., guidance from regulatory agencies and health technology agencies) were used as sources for a multi-stage collaborative process through which the 10 more important points based on lessons drawn from the EU-PEARL project were developed and summarised as guidance for the setup of platform trials. We conclude that early involvement of critical stakeholder such as regulatory agencies or patients are critical steps in the implementation and later acceptance of platform trials. Addressing these gaps will be critical for attaining the full potential of platform trials for patients.

Funding

Innovative Medicines Initiative 2 Joint Undertaking with support from the European Union's Horizon 2020 research and innovation programme and EFPIA.

Adaptive clinical trial designs with blinded selection of binary composite endpoints and sample size reassessment

For randomized clinical trials where a single, primary, binary endpoint would require unfeasibly large sample sizes, composite endpoints (CEs) are widely chosen as the primary endpoint. Despite being commonly used, CEs entail challenges in designing and interpreting results. Given that the components may be of different relevance and have different effect sizes, the choice of components must be made carefully. Especially, sample size calculations for composite binary endpoints depend not only on the anticipated effect sizes and event probabilities of the composite components but also on the correlation between them. However, information on the correlation between endpoints is usually not reported in the literature which can be an obstacle for designing future sound trials. We consider two-arm randomized controlled trials with a primary composite binary endpoint and an endpoint that consists only of the clinically more important component of the CE. We propose a trial design that allows an adaptive modification of the primary endpoint based on blinded information obtained at an interim analysis. Especially, we consider a decision rule to select between a CE and its most relevant component as primary endpoint. The decision rule chooses the endpoint with the lower estimated required sample size. Additionally, the sample size is reassessed using the estimated event probabilities and correlation, and the expected effect sizes of the composite components. We investigate the statistical power and significance level under the proposed design through simulations. We show that the adaptive design is equally or more powerful than designs without adaptive modification on the primary endpoint. Besides, the targeted power is achieved even if the correlation is misspecified at the planning stage while maintaining the type 1 error. All the computations are implemented in R and illustrated by means of a peritoneal dialysis trial.

On the use of non-concurrent controls in platform trials: a scoping review

BACKGROUND

Platform trials gained popularity during the last few years as they increase flexibility compared to multi-arm trials by allowing new experimental arms entering when the trial already started. Using a shared control group in platform trials increases the trial efficiency compared to separate trials. Because of the later entry of some of the experimental treatment arms, the shared control group includes concurrent and non-concurrent control data. For a given experimental arm, non-concurrent controls refer to patients allocated to the control arm before the arm enters the trial, while concurrent controls refer to control patients that are randomised concurrently to the experimental arm. Using non-concurrent controls can result in bias in the estimate in case of time trends if the appropriate methodology is not used and the assumptions are not met.

METHODS

We conducted two reviews on the use of non-concurrent controls in platform trials: one on statistical methodology and one on regulatory guidance. We broadened our searches to the use of external and historical control data. We conducted our review on the statistical methodology in 43 articles identified through a systematic search in PubMed and performed a review on regulatory guidance on the use of non-concurrent controls in 37 guidelines published on the EMA and FDA websites.

RESULTS

Only 7/43 of the methodological articles and 4/37 guidelines focused on platform trials. With respect to the statistical methodology, in 28/43 articles, a Bayesian approach was used to incorporate external/non-concurrent controls while 7/43 used a frequentist approach and 8/43 considered both. The majority of the articles considered a method that downweights the non-concurrent control in favour of concurrent control data (34/43), using for instance meta-analytic or propensity score approaches, and 11/43 considered a modelling-based approach, using regression models to incorporate non-concurrent control data. In regulatory guidelines, the use of non-concurrent control data was considered critical but was deemed acceptable for rare diseases in 12/37 guidelines or was accepted in specific indications (12/37). Non-comparability (30/37) and bias (16/37) were raised most often as the general concerns with non-concurrent controls. Indication specific guidelines were found to be most instructive.

CONCLUSIONS

Statistical methods for incorporating non-concurrent controls are available in the literature, either by means of methods originally proposed for the incorporation of external controls or non-concurrent controls in platform trials. Methods mainly differ with respect to how the concurrent and non-concurrent data are combined and temporary changes handled. Regulatory guidance for non-concurrent controls in platform trials are currently still limited.

Review article: The need for more efficient and patient-oriented drug development pathways in NASH-setting the scene for platform trials

BACKGROUND AND AIMS

Non-alcoholic steatohepatitis (NASH) constitutes a significant unmet medical need with a burgeoning field of clinical research and drug development. Platform trials (PT) might help accelerate drug development while lowering overall costs and creating a more patient-centric environment. This review provides a comprehensive and nuanced assessment of the NASH clinical development landscape.

METHODS

Narrative review and expert opinion with insight gained during the EU Patient-cEntric clinicAl tRial pLatforms (EU-PEARL) project.

RESULTS

Although NASH represents an opportunity to use adaptive trial designs, including master protocols for PT, there are barriers that might be encountered owing to distinct and sometimes opposing priorities held by these stakeholders and potential ways to overcome them. The following aspects are critical for the feasibility of a future PT in NASH: readiness of the drug pipeline, mainly from large drug companies, while there is not yet an FDA/EMA-approved treatment; the most suitable design (trial Phase and type of population, e.g., Phase 2b for non-cirrhotic NASH patients); the operational requirements such as the scope of the clinical network, the use of concurrent versus non-concurrent control arms, or the re-allocation of participants upon trial adaptations; the methodological appraisal (i.e. Bayesian vs. frequentist approach); patients' needs and patient-centred outcomes; main regulatory considerations and the funding and sustainability scenarios.

CONCLUSIONS

PT represent a promising avenue in NASH but there are a number of conundrums that need addressing. It is likely that before a global NASH PT becomes a reality, 'proof-of-platform' at a smaller scale needs to be provided.

The von Willebrand factor-binding aptamer rondaptivon pegol as a treatment for severe and nonsevere hemophilia A

Factor VIII (FVIII) circulates in a noncovalent complex with von Willebrand Factor (VWF), the latter determining FVIII half-life. The VWF-binding aptamer rondaptivon pegol (BT200) increases plasma levels of VWF/FVIII in healthy volunteers. This trial assessed its safety, pharmacokinetics, and pharmacodynamics in hemophilia A. Nineteen adult patients (ages 20-62 years, 4 women) with hemophilia A (8 mild, 2 moderate, and 9 severe) received subcutaneous injections of rondaptivon pegol. After an initial fixed dose of 3 mg on days 0 and 4, patients received weekly doses of 2 to 9 mg until day 28. Severe hemophilia A patients underwent sparse-sampling population pharmacokinetics individual profiling after the final dose of rondaptivon pegol. Adverse events, pharmacokinetics, and pharmacodynamics were assessed. FVIII activity and VWF levels were measured. All patients tolerated rondaptivon pegol well. The geometric mean half-life of rondaptivon pegol was 5.4 days and rondaptivon pegol significantly increased VWF levels. In severe hemophilia A, 6 doses of rondaptivon pegol increased the half-lives of 5 different FVIII products from a median of 10.4 hours to 31.1 hours (range, 20.8-56.0 hours). Median FVIII increased from 22% to 48% in mild hemophilia A and from 3% to 7.5% in moderate hemophilia A. Rondaptivon pegol is a first-in-class prohemostatic molecule that extended the half-life of substituted FVIII approximately 3-fold and increased endogenous FVIII levels approximately 2-fold in hemophilia patients. This trial was registered at www.clinicaltrials.gov as #NCT04677803.

Platform trials to overcome major shortcomings of traditional clinical trials in non-alcoholic steatohepatitis? Pros and cons

Non-alcoholic fatty liver disease is a condition that affects 25% of the population. Non-alcoholic steatohepatitis (NASH) is a progressive form of the disease that can lead to severe complications such as cirrhosis and hepatocellular carcinoma. Despite its high prevalence, no drugs are currently approved for the treatment of NASH. The drug development pipeline in NASH is very active, yet most assets do not progress to phase III trials and those that do reach phase III often fail to achieve the endpoints necessary for approval by regulatory agencies. Amongst other reasons, the methodological and operational features of traditional clinical trials in NASH might impede optimal drug development. In this regard, platform trials might be an attractive complement or alternative to conventional clinical trials. Platform trials use a master protocol which enables evaluation of multiple investigational medicinal products concurrently or sequentially with a single, shared control arm. Through Bayesian interim analyses, these trials allow for early exit of drugs from the trial based on success or futility, while providing participants better chances of receiving active compounds through adaptive randomisation. Overall, platform trials represent an alternative for patients, pharmaceutical companies, and clinicians in the quest to accelerate the approval of pharmacologic treatments for NASH.

Online control of the False Discovery Rate in group-sequential platform trials

When testing multiple hypotheses, a suitable error rate should be controlled even in exploratory trials. Conventional methods to control the False Discovery Rate assume that all p-values are available at the time point of test decision. In platform trials, however, treatment arms enter and leave the trial at different times during its conduct. Therefore, the actual number of treatments and hypothesis tests is not fixed in advance and hypotheses are not tested at once, but sequentially. Recently, for such a setting the concept of online control of the False Discovery Rate was introduced. We propose several heuristic variations of the LOND procedure (significance Levels based On Number of Discoveries) that incorporate interim analyses for platform trials, and study their online False Discovery Rate via simulations. To adjust for the interim looks spending functions are applied with O'Brien-Fleming or Pocock type group-sequential boundaries. The power depends on the prior distribution of effect sizes, for example, whether true alternatives are uniformly distributed over time or not. We consider the choice of design parameters for the LOND procedure to maximize the overall power and investigate the impact on the False Discovery Rate by including both concurrent and non-concurrent control data.

On model-based time trend adjustments in platform trials with non-concurrent controls

BACKGROUND

Platform trials can evaluate the efficacy of several experimental treatments compared to a control. The number of experimental treatments is not fixed, as arms may be added or removed as the trial progresses. Platform trials are more efficient than independent parallel group trials because of using shared control groups. However, for a treatment entering the trial at a later time point, the control group is divided into concurrent controls, consisting of patients randomised to control when that treatment arm is in the platform, and non-concurrent controls, patients randomised before. Using non-concurrent controls in addition to concurrent controls can improve the trial's efficiency by increasing power and reducing the required sample size, but can introduce bias due to time trends.

METHODS

We focus on a platform trial with two treatment arms and a common control arm. Assuming that the second treatment arm is added at a later time, we assess the robustness of recently proposed model-based approaches to adjust for time trends when utilizing non-concurrent controls. In particular, we consider approaches where time trends are modeled either as linear in time or as a step function, with steps at time points where treatments enter or leave the platform trial. For trials with continuous or binary outcomes, we investigate the type 1 error rate and power of testing the efficacy of the newly added arm, as well as the bias and root mean squared error of treatment effect estimates under a range of scenarios. In addition to scenarios where time trends are equal across arms, we investigate settings with different time trends or time trends that are not additive in the scale of the model.

RESULTS

A step function model, fitted on data from all treatment arms, gives increased power while controlling the type 1 error, as long as the time trends are equal for the different arms and additive on the model scale. This holds even if the shape of the time trend deviates from a step function when patients are allocated to arms by block randomisation. However, if time trends differ between arms or are not additive to treatment effects in the scale of the model, the type 1 error rate may be inflated.

CONCLUSIONS

The efficiency gained by using step function models to incorporate non-concurrent controls can outweigh potential risks of biases, especially in settings with small sample sizes. Such biases may arise if the model assumptions of equality and additivity of time trends are not satisfied. However, the specifics of the trial, scientific plausibility of different time trends, and robustness of results should be carefully considered.

Camostat Mesylate Versus Lopinavir/Ritonavir in Hospitalized Patients With COVID-19—Results From a Randomized, Controlled, Open Label, Platform Trial (ACOVACT)

Background: To date, no oral antiviral drug has proven to be beneficial in hospitalized patients with COVID-19.

Methods: In this randomized, controlled, open-label, platform trial, we randomly assigned patients ≥18 years hospitalized with COVID-19 pneumonia to receive either camostat mesylate (CM) (considered standard-of-care) or lopinavir/ritonavir (LPV/RTV). The primary endpoint was time to sustained clinical improvement (≥48 h) of at least one point on the 7-category WHO scale. Secondary endpoints included length of stay (LOS), need for mechanical ventilation (MV) or death, and 29-day mortality.

Results: 201 patients were included in the study (101 CM and 100 LPV/RTV) between 20 April 2020 and 14 May 2021. Mean age was 58.7 years, and 67% were male. The median time from symptom onset to randomization was 7 days (IQR 5–9). Patients in the CM group had a significantly shorter time to sustained clinical improvement (HR = 0.67, 95%-CI 0.49–0.90; 9 vs. 11 days, p = 0.008) and demonstrated less progression to MV or death [6/101 (5.9%) vs. 15/100 (15%), p = 0.036] and a shorter LOS (12 vs. 14 days, p = 0.023). A statistically nonsignificant trend toward a lower 29-day mortality in the CM group than the LPV/RTV group [2/101 (2%) vs. 7/100 (7%), p = 0.089] was observed.

Conclusion: In patients hospitalized for COVID-19, the use of CM was associated with shorter time to clinical improvement, reduced need for MV or death, and shorter LOS than the use of LPV/RTV. Furthermore, research is needed to confirm the efficacy of CM in larger placebo-controlled trials.

Systematic Review Registration: [https://clinicaltrials.gov/ct2/show/NCT04351724, https://www.clinicaltrialsregister.eu/ctr-search/trial/2020-001302-30/AT], identifier [NCT04351724, EUDRACT-NR: 2020–001302-30].

MO679: Peritonitis May Disrupt Cyclic Periodicity of Ultrafiltration in Peritoneal Dialysis

BACKGROUND AND AIMS

Due to chronic damage of the peritoneal membrane on long-term treatment, peritoneal dialysis (PD) is a time-limited therapy. Effective PD is achieved by adequate peritoneal ultrafiltration (UF) and small solute clearance while maintaining an appropriate fluid and salt homeostasis. Availability of remote patient monitoring on automated PD (APD) allows clinicians to remotely retrieve data for treatment analysis, proposed to improve clinical outcomes. However, machine-derived data are vastly different from traditionally observed data (e.g. quantity, noise, missing normative values). Recently correlation of daily UF changes on APD with changing peritoneal membrane function in association with clinical risk factors and outcomes has been observed. High intra- and interpatient variability of UF remains not fully explained. We aim at a better understanding of UF variability by submitting APD machine readouts to spectral analysis in association with clinical risk factors of membrane dysfunction.

METHOD

This was a secondary analysis of the Medical University of Vienna APD cycler treatment data from patients using Homechoice Pro cyclers (Baxter, IL, USA), extracted from the cycler management software (PD link, Baxter). Analysis was conducted using R software (R Core Team 2020). Daily UF was processed using the Lomb-Scargle periodogram (LSP), a method commonly used in astrophysics and neurophysiology to detect rhythms in (unevenly sampled) time series. Peaks of power spectrum, frequencies, and periodicities were compared between patients with and without peritonitis episodes during their PD treatment utilizing a Mann–Whitney U-test and associated with the total number of peritonitis episodes using Kendall rank correlation. A P-value < 0.05 was considered significant; all tests were two-sided.

RESULTS

LSP analysis was performed on daily UF data from n = 129 APD patients with a mean observation time of 598 days (SD ± 517), male: female 61:39% (n = 79:50), incident: prevalent patients 77:23% (n = 99:30), and diabetic: non-diabetic patients 25:75% (n = 32:97). Observation time extended from the introduction of APD until kidney transplantation (43%, n = 55), transfer to hemodialysis (23%, n = 29), death (27%, n = 35), kidney function recovery (8%, n = 1), or loss to follow-up (7%, n = 9). After inspection of LSPs n = 9 patients were excluded from further analysis as their periodicity matched the time of their clinical endpoint. A total of 45 of the remaining 120 patients (38%) never experienced a peritonitis episode, and a total of 0.3 (SD ± 0.7) peritonitis episodes/patient-year were observed. LSP computation revealed cyclic periodicity in UF in all patients with an overall median peak period length of 329 days (IQR 62–882 days), median peak power of 21 (IQR 7–91), and median peak frequency of 0.42 (IQR 0.36–0.46). Differences between patients with and without peritonitis episodes during PD treatment are displayed in Table 1. Correlation analysis revealed significant association between the number of peritonitis episodes and peak periodicity of UF (tau=0.14, P = 0.04), and peak power (tau = 0.21, P = 0.003). Peak frequency of UF was not significantly correlated.

CONCLUSION

Patients on APD cycler treatment seem to display cyclic periodicity of UF, being significantly associated with the number of peritonitis episodes and significantly different between patients with and without peritonitis episodes. Smaller-scale periodicity (median 216 days) in patients without peritonitis seems to be disrupted by peritonitis resulting in significantly higher periodicity (median 670 days). The causes and implications of these results remain unclear and need further investigation. However, as peritonitis is a known risk factor for peritoneal membrane dysfunction, prolongation of UF periodicity might reflect disruption of peritoneal membrane function.

Early administration of remdesivir may reduce mortality in hospitalized COVID-19 patients : A propensity score matched analysis

BACKGROUND

Remdesivir is the only antiviral agent approved for the treatment of hospitalized coronavirus disease 2019 (COVID-19) patients requiring supplemental oxygen. Studies show conflicting results regarding its effect on mortality.

METHODS

In this single center observational study, we included adult hospitalized COVID-19 patients. Patients who were treated with remdesivir were compared to controls. Remdesivir was administered for 5 days. To adjust for any imbalances in our cohort, a propensity score matched analysis was performed. The aim of our study was to analyze the effect of remdesivir on in-hospital mortality and length of stay (LOS).

RESULTS

After propensity score matching, 350 patients (175 remdesivir, 175 controls) were included in our analysis. Overall, in-hospital mortality was not significantly different between groups remdesivir 5.7% [10/175] vs. control 8.6% [15/175], hazard ratio 0.50, 95% confidence interval (CI) 0.22-1.12, p = 0.091. Subgroup analysis showed a significant reduction of in-hospital mortality in patients who were treated with remdesivir ≤ 7 days of symptom onset remdesivir 4.2% [5/121] vs. control 10.4% [13/125], hazard ratio 0.26, 95% CI 0.09 to 0.75, p = 0.012 and in female patients remdesivir 2.9% [2/69] vs. control 12.2% [9/74], hazard ratio 0.18 95%CI 0.04 to 0.85, p = 0.03. Patients in the remdesivir group had a significantly longer LOS (11 days vs. 9 days, p = 0.046).

CONCLUSION

Remdesivir did not reduce in-hospital mortality in our whole propensity score matched cohort, but subgroup analysis showed a significant mortality reduction in female patients and in patients treated within ≤ 7 days of symptom onset. Remdesivir may reduce mortality in patients who are treated in the early stages of illness.

COVID-19 is not "just another flu": a real-life comparison of severe COVID-19 and influenza in hospitalized patients in Vienna, Austria

Background

COVID-19 is regularly compared to influenza. Mortality and case-fatality rates vary widely depending on incidence of COVID-19 and the testing policy in affected countries. To date, data comparing hospitalized patients with COVID-19 and influenza is scarce.

Methods

Data from patients with COVID-19 were compared to patients infected with influenza A (InfA) and B (InfB) virus during the 2017/18 and 2018/19 seasons. All patients were ≥ 18 years old, had PCR-confirmed infection and needed hospital treatment. Demographic data, medical history, length-of-stay (LOS), complications including in-hospital mortality were analyzed.

Results

In total, 142 patients with COVID-19 were compared to 266 patients with InfA and 300 with InfB. Differences in median age (COVID-19 70.5 years vs InfA 70 years and InfB 77 years, p < 0.001) and laboratory results were observed. COVID-19 patients had fewer comorbidities, but complications (respiratory insufficiency, pneumonia, acute kidney injury, acute heart failure and death) occurred more frequently.

Median length-of-stay (LOS) was longer in COVID-19 patients (12 days vs InfA 7 days vs. InfB 7 days, p < 0.001). There was a fourfold higher in-hospital mortality in COVID-19 patients (23.2%) when compared with InfA (5.6%) or InfB (4.7%; p < 0.001).

Conclusion

In hospitalized patients, COVID-19 is associated with longer LOS, a higher number of complications and higher in-hospital mortality compared to influenza, even in a population with fewer co-morbidities. This data, a high reproduction number and limited treatment options, alongside excess mortality during the SARS-CoV-2 pandemic, support the containment strategies implemented by most authorities.

Efficient Adaptive Designs for Clinical Trials of Interventions for COVID-19

The COVID-19 pandemic has led to an unprecedented response in terms of clinical research activity. An important part of this research has been focused on randomized controlled clinical trials to evaluate potential therapies for COVID-19. The results from this research need to be obtained as rapidly as possible. This presents a number of challenges associated with considerable uncertainty over the natural history of the disease and the number and characteristics of patients affected, and the emergence of new potential therapies. These challenges make adaptive designs for clinical trials a particularly attractive option. Such designs allow a trial to be modified on the basis of interim analysis data or stopped as soon as sufficiently strong evidence has been observed to answer the research question, without compromising the trial's scientific validity or integrity. In this article, we describe some of the adaptive design approaches that are available and discuss particular issues and challenges associated with their use in the pandemic setting. Our discussion is illustrated by details of four ongoing COVID-19 trials that have used adaptive designs.

Endpoints for randomized controlled clinical trials for COVID-19 treatments

BACKGROUND

Endpoint choice for randomized controlled trials of treatments for novel coronavirus-induced disease (COVID-19) is complex. Trials must start rapidly to identify treatments that can be used as part of the outbreak response, in the midst of considerable uncertainty and limited information. COVID-19 presentation is heterogeneous, ranging from mild disease that improves within days to critical disease that can last weeks to over a month and can end in death. While improvement in mortality would provide unquestionable evidence about the clinical significance of a treatment, sample sizes for a study evaluating mortality are large and may be impractical, particularly given a multitude of putative therapies to evaluate. Furthermore, patient states in between "cure" and "death" represent meaningful distinctions. Clinical severity scores have been proposed as an alternative. However, the appropriate summary measure for severity scores has been the subject of debate, particularly given the variable time course of COVID-19. Outcomes measured at fixed time points, such as a comparison of severity scores between treatment and control at day 14, may risk missing the time of clinical benefit. An endpoint such as time to improvement (or recovery) avoids the timing problem. However, some have argued that power losses will result from reducing the ordinal scale to a binary state of "recovered" versus "not recovered."

METHODS

We evaluate statistical power for possible trial endpoints for COVID-19 treatment trials using simulation models and data from two recent COVID-19 treatment trials.

RESULTS

Power for fixed time-point methods depends heavily on the time selected for evaluation. Time-to-event approaches have reasonable statistical power, even when compared with a fixed time-point method evaluated at the optimal time.

DISCUSSION

Time-to-event analysis methods have advantages in the COVID-19 setting, unless the optimal time for evaluating treatment effect is known in advance. Even when the optimal time is known, a time-to-event approach may increase power for interim analyses.

Hypothyroidism correlates with favourable survival prognosis in patients with brain metastatic cancer

BACKGROUND

Several preclinical and epidemiologic studies have indicated tumour-promoting effects of thyroid hormones (THs). However, very limited knowledge exists on the prognostic impact of thyroid function in metastatic cancer.

METHODS

We compiled a discovery cohort of 1692 patients with newly diagnosed brain metastases (BMs) of solid cancers treated at the Medical University of Vienna and an independent validation cohort of 191 patients with newly diagnosed BMs treated at the University Hospital Zurich.

RESULTS

Hypothyroidism before diagnosis of cancer was evident in 133 of 1692 (7.9%) patients of the discovery, and in 18 of 191 (9.4%) patients of the validation cohort. In the discovery cohort, hypothyroidism was statistically significantly associated with favourable survival prognosis from diagnosis of cancer (31 vs. 21 months; p = 0.0026) and with survival prognosis from diagnosis of BMs (12 vs. 7 months; p = 0.0079). In multivariate analysis including the diagnosis-specific graded prognostic assessment score, primary tumour type and sex, hypothyroidism was an independent factor associated with survival after diagnosis of BMs (hazard ratio: 0.76; 95% confidence interval [CI]: (0.63; 0.91; p = 0.0034). In the validation cohort, the association of hypothyroidism and favourable survival prognosis from diagnosis of cancer (55 vs. 11 months; p = 0.00058), as well as from diagnosis of BMs (40 vs. 10 months; p = 0.0036) was confirmed.

CONCLUSION

Pre-existing hypothyroidism was strongly and independently associated with prognosis in patients with newly diagnosed BMs, supporting the evidence from preclinical data that THs may indeed have a tumour-promoting effect. Further investigation of the underlying pathobiological mechanism and potential therapeutic implications are required.

The adaptive designs CONSORT extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design

Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits. In order to encourage its wide dissemination this article is freely accessible on the BMJ and Trials journal websites."To maximise the benefit to society, you need to not just do research but do it well" Douglas G Altman.

The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design

Adaptive designs (ADs) allow pre-planned changes to an ongoing trial without compromising the validity of conclusions and it is essential to distinguish pre-planned from unplanned changes that may also occur. The reporting of ADs in randomised trials is inconsistent and needs improving. Incompletely reported AD randomised trials are difficult to reproduce and are hard to interpret and synthesise. This consequently hampers their ability to inform practice as well as future research and contributes to research waste. Better transparency and adequate reporting will enable the potential benefits of ADs to be realised.This extension to the Consolidated Standards Of Reporting Trials (CONSORT) 2010 statement was developed to enhance the reporting of randomised AD clinical trials. We developed an Adaptive designs CONSORT Extension (ACE) guideline through a two-stage Delphi process with input from multidisciplinary key stakeholders in clinical trials research in the public and private sectors from 21 countries, followed by a consensus meeting. Members of the CONSORT Group were involved during the development process.The paper presents the ACE checklists for AD randomised trial reports and abstracts, as well as an explanation with examples to aid the application of the guideline. The ACE checklist comprises seven new items, nine modified items, six unchanged items for which additional explanatory text clarifies further considerations for ADs, and 20 unchanged items not requiring further explanatory text. The ACE abstract checklist has one new item, one modified item, one unchanged item with additional explanatory text for ADs, and 15 unchanged items not requiring further explanatory text.The intention is to enhance transparency and improve reporting of AD randomised trials to improve the interpretability of their results and reproducibility of their methods, results and inference. We also hope indirectly to facilitate the much-needed knowledge transfer of innovative trial designs to maximise their potential benefits.

Are Novel, Nonrandomized Analytic Methods Fit for Decision Making? The Need for Prospective, Controlled, and Transparent Validation

Real-world data and patient-level data from completed randomized controlled trials are becoming available for secondary analysis on an unprecedented scale. A range of novel methodologies and study designs have been proposed for their analysis or combination. However, to make novel analytical methods acceptable for regulators and other decision makers will require their testing and validation in broadly the same way one would evaluate a new drug: prospectively, well-controlled, and according to a pre-agreed plan. From a European regulators' perspective, the established methods qualification advice procedure with active participation of patient groups and other decision makers is an efficient and transparent platform for the development and validation of novel study designs.

Group sequential adaptive designs in series of time-to-event randomised trials in rare diseases: A simulation study

In rare diseases, fully powered large trials may not be doable in a reasonable time frame even with international collaborations. In a previous work, we proposed an approach based on a series of smaller parallel group two-arm randomised controlled trials (RCT) performed over a long research horizon. Within the series of trials, the treatment selected after each trial becomes the control treatment of the next one. We concluded that running more trials with smaller sample sizes and relaxed α-levels leads in the long term and under reasonable assumptions to larger survival benefits with a moderate increase of risk as compared to traditional designs based on larger but fewer trials designed to meet stringent evidence criteria. We now extend this quantitative framework with more 'flexible' designs including interim analyses for futility and/or efficacy, and three-arm adaptive designs with treatment selection at interim. In the simulation study, we considered different disease severities, accrual rates, and hypotheses of how treatments improve over time. For each design, we estimated the long-term survival benefit as the relative difference in hazard rates between the end and the start of the research horizon, and the risk defined as the probability of selecting at the end of the research horizon a treatment inferior to the initial control. We assessed the impact of the α-level and the choice of the stopping rule on the operating characteristics. We also compared the performance of series based on two- vs. three-arm trials. We show that relaxing α-levels within the limit of 0.1 is associated with larger survival gains and moderate increase of risk which remains within acceptable ranges. Including an interim analysis with a futility rule is associated with an additional survival gain and a better risk control as compared to series with no interim analysis, when the α-level is below or equal to 0.1, whereas the benefit of including an interim analysis is rather small for higher α-levels. Including an interim analysis for efficacy yields almost no additional gain. Series based on three-arm trials are associated with a systematic improvement in terms of survival gain and risk control as compared to series of two-arm trials.

Metagenomic sequencing at the epicenter of the Nigeria 2018 Lassa fever outbreak

The 2018 Nigerian Lassa fever season saw the largest ever recorded upsurge of cases, raising concerns over the emergence of a strain with increased transmission rate. To understand the molecular epidemiology of this upsurge, we performed, for the first time at the epicenter of an unfolding outbreak, metagenomic nanopore sequencing directly from patient samples, an approach dictated by the highly variable genome of the target pathogen. Genomic data and phylogenetic reconstructions were communicated immediately to Nigerian authorities and the World Health Organization to inform the public health response. Real-time analysis of 36 genomes and subsequent confirmation using all 120 samples sequenced in the country of origin revealed extensive diversity and phylogenetic intermingling with strains from previous years, suggesting independent zoonotic transmission events and thus allaying concerns of an emergent strain or extensive human-to-human transmission.

Composite Outcome Improves Feasibility of Clinical Trials in Peritoneal Dialysis

Background:Peritoneal dialysis (PD) is complicated by a high rate of adverse events that might be attributed to cytotoxicity of currently used PD fluids. However, clinical development of novel PD fluids is virtually non-existent, in part due to difficulties in recruiting sufficiently large populations for adequately powered trials. The aim of this study is to understand the potential impact of introducing composite outcomes on clinical trial feasibility in PD.Methods:A composite outcome "major adverse peritoneal events (MAPE)" was designed to combine clinically relevant complications of PD, such as (1) technical failure (cause-specific for peritonitis and/or insufficient dialysis), (2) peritonitis, and (3) peritoneal membrane deterioration. Incidence rates of individual endpoints were obtained from the literature and expert panel estimations, and population sizes were computed based on Chi-square test for adequately powered confirmatory randomized controlled clinical trials with 2 parallel arms.Results:Incidence rates for technical failure, peritonitis, and peritoneal membrane deterioration were estimated at 15%, 50%, and 23%, respectively, at 2 years follow-up, with adequate agreement between the literature and expert opinion. Assuming that a given intervention reduces adverse outcomes by 30%, an adequately powered clinical trial needs to recruit up to 1,720 patients when studying individual outcomes. Combining endpoints increases power in simulated trials despite considerable overlap, and the composite outcome MAPE reduces the required population to 202 patients aiming for 80% power.Conclusion:Introduction of the composite outcome MAPE, covering relevant major adverse peritoneal events, may improve the feasibility of clinical trials to adequately test novel PD fluids.

Adaptive designs in clinical trials: from scientific advice to marketing authorisation to the European Medicine Agency

Background

In recent years, experience on the application of adaptive designs in confirmatory clinical trials has accumulated. Although planning such trials comes at the cost of additional operational complexity, adaptive designs offer the benefit of flexibility to update trial design and objectives as data accrue. In 2007, the European Medicines Agency (EMA) provided guidance on confirmatory clinical trials with adaptive (or flexible) designs. In order to better understand how adaptive trials are implemented in practice and how they may impact medicine approval within the EMA centralised procedure, we followed on 59 medicines for which an adaptive clinical trial had been submitted to the EMA Scientific Advice (SA) and analysed previously in a dedicated EMA survey of scientific advice letters. We scrutinized in particular the submission of the corresponding medicines for a marketing authorisation application (MAA). We also discuss the current regulatory perspective as regards the implementation of adaptive designs in confirmatory clinical trials.

Methods

Using the internal EMA MAA database, the AdisInsight database and related trial registries, we analysed how many of these 59 trials actually started, the completion status, results, the time to trial start, the adaptive elements finally implemented after SA, their possible influence on the success of the trial and corresponding product approval.

Results

Overall 31 trials out of 59 (53%) were retrieved. Thirty of them (97%) have been started and 23 (74%) concluded. Nine of these trials (39% out of 23) demonstrated a significant treatment effect on their primary endpoint and 4 (17% out of 23) supported a marketing authorisation (MA). An additional two trials were stopped using pre-defined criteria for futility, efficiently identifying trials on which further resources should not be spent. Median time to trial start after SA letter was given by EMA was 5 months. In the investigated trial registries, at least 18 trial (58% of 31 retrieved trials) designs were implemented with adaptive elements, which were predominantly dose selection, sample size reassessment (SSR) and stopping for futility (SFF). Among the 11 completed trials including adaptive elements, 6 demonstrated a significant treatment effect on their primary endpoint (55%).

Conclusions

Adaptive designs are now well established in the drug development landscape. If properly pre-planned, adaptations can play a key role in the success of some of these trials, for example to help successfully select the most promising dose regimens for phase II/III trials. Interim analyses can also enable stopping of trials for futility when they do not hold their promises. Type I error rate control, trial integrity and results consistency between the different stages of the analyses are fundamental aspects to be discussed thoroughly. Engaging early dialogue with regulators and implementing the scientific advice received is strongly recommended, since much experience in discussing adaptive designs and assessing their results has been accumulated.

Development process of a consensus-driven CONSORT extension for randomised trials using an adaptive design

BACKGROUND

Adequate reporting of adaptive designs (ADs) maximises their potential benefits in the conduct of clinical trials. Transparent reporting can help address some obstacles and concerns relating to the use of ADs. Currently, there are deficiencies in the reporting of AD trials. To overcome this, we have developed a consensus-driven extension to the CONSORT statement for randomised trials using an AD. This paper describes the processes and methods used to develop this extension rather than detailed explanation of the guideline.

METHODS

We developed the guideline in seven overlapping stages: 1) Building on prior research to inform the need for a guideline; 2) A scoping literature review to inform future stages; 3) Drafting the first checklist version involving an External Expert Panel; 4) A two-round Delphi process involving international, multidisciplinary, and cross-sector key stakeholders; 5) A consensus meeting to advise which reporting items to retain through voting, and to discuss the structure of what to include in the supporting explanation and elaboration (E&E) document; 6) Refining and finalising the checklist; and 7) Writing-up and dissemination of the E&E document. The CONSORT Executive Group oversaw the entire development process.

RESULTS

Delphi survey response rates were 94/143 (66%), 114/156 (73%), and 79/143 (55%) in rounds 1, 2, and across both rounds, respectively. Twenty-seven delegates from Europe, the USA, and Asia attended the consensus meeting. The main checklist has seven new and nine modified items and six unchanged items with expanded E&E text to clarify further considerations for ADs. The abstract checklist has one new and one modified item together with an unchanged item with expanded E&E text. The E&E document will describe the scope of the guideline, the definition of an AD, and some types of ADs and trial adaptations and explain each reporting item in detail including case studies.

CONCLUSIONS

We hope that making the development processes, methods, and all supporting information that aided decision-making transparent will enhance the acceptability and quick uptake of the guideline. This will also help other groups when developing similar CONSORT extensions. The guideline is applicable to all randomised trials with an AD and contains minimum reporting requirements.

A proposal for a new PhD level curriculum on quantitative methods for drug development

This paper provides an overview of "Improving Design, Evaluation and Analysis of early drug development Studies" (IDEAS), a European Commission-funded network bringing together leading academic institutions and small- to large-sized pharmaceutical companies to train a cohort of graduate-level medical statisticians. The network is composed of a diverse mix of public and private sector partners spread across Europe, which will host 14 early-stage researchers for 36 months. IDEAS training activities are composed of a well-rounded mixture of specialist methodological components and generic transferable skills. Particular attention is paid to fostering collaborations between researchers and supervisors, which span academia and the private sector. Within this paper, we review existing medical statistics programmes (MSc and PhD) and highlight the training they provide on skills relevant to drug development. Motivated by this review and our experiences with the IDEAS project, we propose a concept for a joint, harmonised European PhD programme to train statisticians in quantitative methods for drug development.

Design and estimation in clinical trials with subpopulation selection

Population heterogeneity is frequently observed among patients' treatment responses in clinical trials because of various factors such as clinical background, environmental, and genetic factors. Different subpopulations defined by those baseline factors can lead to differences in the benefit or safety profile of a therapeutic intervention. Ignoring heterogeneity between subpopulations can substantially impact on medical practice. One approach to address heterogeneity necessitates designs and analysis of clinical trials with subpopulation selection. Several types of designs have been proposed for different circumstances. In this work, we discuss a class of designs that allow selection of a predefined subgroup. Using the selection based on the maximum test statistics as the worst‐case scenario, we then investigate the precision and accuracy of the maximum likelihood estimator at the end of the study via simulations. We find that the required sample size is chiefly determined by the subgroup prevalence and show in simulations that the maximum likelihood estimator for these designs can be substantially biased.

An update on the clinical evidence that supports biosimilar approvals in Europe

AIM

Sponsors and regulators have more than 10 years of experience with the development of biosimilars in Europe. However, the regulatory pathway is still evolving. The present article provides an update on biosimilar development in practice by reviewing the clinical development programmes of recently approved biosimilars in Europe.

METHODS

We used the European public assessment reports (EPARs) which are published by the European Medicines Agency (EMA) for a comparison of the clinical development programmes of the 37 approved biosimilars in Europe. Here, we present novel strategies in the development of biosimilars by focusing specifically on the 17 biosimilars that have gained approval in the last year, but we also compare additional key characteristics for all approved biosimilars.

RESULTS

The high variability of the clinical development strategies that we found previously was confirmed in the present analysis. Compared with earlier biosimilar applications, more nonstandard development strategies have been used recently. This includes, for example, applications without any studies in patients, and more complex study designs. During this study, we found that the EPARs for biosimilars seem to be improving; however, we identified important details which were still often missing. We provide a proposal for a checklist of the minimum information that should be included in biosimilar EPARs for giving the general public insights into the rationale for the approval of biosimilars.

CONCLUSIONS

European regulators still seem to be open to consider approaches that differ from the guidelines or previous applications, as long as justification is provided.

Flexible alpha allocation strategies for confirmatory adaptive enrichment clinical trials with a prespecified subgroup

Adaptive enrichment designs have recently received considerable attention as they have the potential to make drug development process for personalized medicine more efficient. Several statistical approaches have been proposed so far in the literature and the operating characteristics of these approaches are extensively investigated using simulation studies. In this paper, we improve on existing adaptive enrichment designs by assigning unequal weights to the significance levels associated with the hypotheses of the overall population and a prespecified subgroup. More specifically, we focus on the standard combination test, a modified combination test, the marginal combination test, and the partial conditional error rate approach and explore the operating characteristics of these approaches by a simulation study. We show that these approaches can lead to power gains, compared to existing approaches, if the weights are chosen carefully.

Many-to-one comparisons after safety selection in multi-arm clinical trials

In phase II platform trials, ‘many-to-one’ comparisons are performed when K experimental treatments are compared with a common control to identify the most promising treatment(s) to be selected for Phase III trials. However, when sample sizes are limited, such as when the disease of interest is rare, only a single Phase II/III trial addressing both treatment selection and confirmatory efficacy testing may be feasible. In this paper, we suggest a two-step safety selection and testing procedure for such seamless trials. At the end of the study, treatments are first screened on the basis of safety, and those deemed to be sufficiently safe are then taken forwards for efficacy testing against a common control. All safety and efficacy evaluations are therefore performed at the end of the study, when for each patient all safety and efficacy data are available. If confirmatory conclusions are to be drawn from the trial, strict control of the family-wise error rate (FWER) is essential. However, to avoid unnecessary losses in power, no type I error rate should be “wasted” on comparisons which are no longer of interest because treatments have been dropped due to safety concerns. We investigate the impact on power and FWER control of multiplicity adjustments which correct efficacy tests only for the number of safe selected treatments instead of adjusting for all K null hypotheses the trial begins testing. We derive conditions under which strict control of the FWER can be achieved. Procedures using the estimated association between safety and efficacy outcomes are developed for the case when the correlation between endpoints is unknown. The operating characteristics of the proposed procedures are assessed via simulation.

"Threshold-crossing": A Useful Way to Establish the Counterfactual in Clinical Trials?

A central question in the assessment of benefit/harm of new treatments is: how does the average outcome on the new treatment (the factual) compare to the average outcome had patients received no treatment or a different treatment known to be effective (the counterfactual)? Randomized controlled trials (RCTs) are the standard for comparing the factual with the counterfactual. Recent developments necessitate and enable a new way of determining the counterfactual for some new medicines. For select situations, we propose a new framework for evidence generation, which we call "threshold-crossing." This framework leverages the wealth of information that is becoming available from completed RCTs and from real world data sources. Relying on formalized procedures, information gleaned from these data is used to estimate the counterfactual, enabling efficacy assessment of new drugs. We propose future (research) activities to enable "threshold-crossing" for carefully selected products and indications in which RCTs are not feasible.

Clinical trials for authorized biosimilars in the European Union: a systematic review

Aim

In 2006, Omnitrope (by Sandoz) was the first approved biosimilar in Europe. To date, 21 biosimilars for seven different biologics are on the market. The present study compared the clinical trials undertaken to obtain market authorization.

Methods

We summarized the findings of a comprehensive review of all clinical trials up to market authorization of approved biosimilars, using the European public assessment reports (EPARs) published by the European Medicines Agency (EMA). The features compared were, among others, the number of patients enrolled, the number of trials, the types of trial design, choice of endpoints and equivalence margins for pharmacokinetic (PK)/pharmacodynamic (PD) and phase III trials.

Results

The variability between the clinical development strategies is high. Some differences are explainable by the characteristics of the product; if, for example, the PD marker can be assumed to predict the clinical outcome, no efficacy trials might be necessary. However, even for products with the same reference product, the sample size, endpoints and statistical models are not always the same.

Conclusions

There seems to be flexibility for sponsors regarding the decision as to how best to prove biosimilarity.

Sample Size Reassessment and Hypothesis Testing in Adaptive Survival Trials

Mid-study design modifications are becoming increasingly accepted in confirmatory clinical trials, so long as appropriate methods are applied such that error rates are controlled. It is therefore unfortunate that the important case of time-to-event endpoints is not easily handled by the standard theory. We analyze current methods that allow design modifications to be based on the full interim data, i.e., not only the observed event times but also secondary endpoint and safety data from patients who are yet to have an event. We show that the final test statistic may ignore a substantial subset of the observed event times. An alternative test incorporating all event times is found, where a conservative assumption must be made in order to guarantee type I error control. We examine the power of this approach using the example of a clinical trial comparing two cancer therapies.

Evidence, eminence and extrapolation

A full independent drug development programme to demonstrate efficacy may not be ethical and/or feasible in small populations such as paediatric populations or orphan indications. Different levels of extrapolation from a larger population to smaller target populations are widely used for supporting decisions in this situation. There are guidance documents in drug regulation, where a weakening of the statistical rigour for trials in the target population is mentioned to be an option for dealing with this problem. To this end, we propose clinical trials designs, which make use of prior knowledge on efficacy for inference. We formulate a framework based on prior beliefs in order to investigate when the significance level for the test of the primary endpoint in confirmatory trials can be relaxed (and thus the sample size can be reduced) in the target population while controlling a certain posterior belief in effectiveness after rejection of the null hypothesis in the corresponding confirmatory statistical test. We show that point‐priors may be used in the argumentation because under certain constraints, they have favourable limiting properties among other types of priors. The crucial quantity to be elicited is the prior belief in the possibility of extrapolation from a larger population to the target population. We try to illustrate an existing decision tree for extrapolation to paediatric populations within our framework. © 2016 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Adaptive designs for subpopulation analysis optimizing utility functions

If the response to treatment depends on genetic biomarkers, it is important to identify predictive biomarkers that define (sub-)populations where the treatment has a positive benefit risk balance. One approach to determine relevant subpopulations are subgroup analyses where the treatment effect is estimated in biomarker positive and biomarker negative groups. Subgroup analyses are challenging because several types of risks are associated with inference on subgroups. On the one hand, by disregarding a relevant subpopulation a treatment option may be missed due to a dilution of the treatment effect in the full population. Furthermore, even if the diluted treatment effect can be demonstrated in an overall population, it is not ethical to treat patients that do not benefit from the treatment when they can be identified in advance. On the other hand, selecting a spurious subpopulation increases the risk to restrict an efficacious treatment to a too narrow fraction of a potential benefiting population. We propose to quantify these risks with utility functions and investigate nonadaptive study designs that allow for inference on subgroups using multiple testing procedures as well as adaptive designs, where subgroups may be selected in an interim analysis. The characteristics of such adaptive and nonadaptive designs are compared for a range of scenarios.

Adaptive graph-based multiple testing procedures

Multiple testing procedures defined by directed, weighted graphs have recently been proposed as an intuitive visual tool for constructing multiple testing strategies that reflect the often complex contextual relations between hypotheses in clinical trials. Many well-known sequentially rejective tests, such as (parallel) gatekeeping tests or hierarchical testing procedures are special cases of the graph based tests. We generalize these graph-based multiple testing procedures to adaptive trial designs with an interim analysis. These designs permit mid-trial design modifications based on unblinded interim data as well as external information, while providing strong family wise error rate control. To maintain the familywise error rate, it is not required to prespecify the adaption rule in detail. Because the adaptive test does not require knowledge of the multivariate distribution of test statistics, it is applicable in a wide range of scenarios including trials with multiple treatment comparisons, endpoints or subgroups, or combinations thereof. Examples of adaptations are dropping of treatment arms, selection of subpopulations, and sample size reassessment. If, in the interim analysis, it is decided to continue the trial as planned, the adaptive test reduces to the originally planned multiple testing procedure. Only if adaptations are actually implemented, an adjusted test needs to be applied. The procedure is illustrated with a case study and its operating characteristics are investigated by simulations.

Adaptive clinical trial designs for European marketing authorization: a survey of scientific advice letters from the European Medicines Agency

Background

Since the first methodological publications on adaptive study design approaches in the 1990s, the application of these approaches in drug development has raised increasing interest among academia, industry and regulators. The European Medicines Agency (EMA) as well as the Food and Drug Administration (FDA) have published guidance documents addressing the potentials and limitations of adaptive designs in the regulatory context. Since there is limited experience in the implementation and interpretation of adaptive clinical trials, early interaction with regulators is recommended. The EMA offers such interactions through scientific advice and protocol assistance procedures.

Methods

We performed a text search of scientific advice letters issued between 1 January 2007 and 8 May 2012 that contained relevant key terms. Letters containing questions related to adaptive clinical trials in phases II or III were selected for further analysis. From the selected letters, important characteristics of the proposed design and its context in the drug development program, as well as the responses of the Committee for Human Medicinal Products (CHMP)/Scientific Advice Working Party (SAWP), were extracted and categorized. For 41 more recent procedures (1 January 2009 to 8 May 2012), additional details of the trial design and the CHMP/SAWP responses were assessed. In addition, case studies are presented as examples.

Results

Over a range of 5½ years, 59 scientific advices were identified that address adaptive study designs in phase II and phase III clinical trials. Almost all were proposed as confirmatory phase III or phase II/III studies. The most frequently proposed adaptation was sample size reassessment, followed by dropping of treatment arms and population enrichment. While 12 (20%) of the 59 proposals for an adaptive clinical trial were not accepted, the great majority of proposals were accepted (15, 25%) or conditionally accepted (32, 54%). In the more recent 41 procedures, the most frequent concerns raised by CHMP/SAWP were insufficient justifications of the adaptation strategy, type I error rate control and bias.

Conclusions

For the majority of proposed adaptive clinical trials, an overall positive opinion was given albeit with critical comments. Type I error rate control, bias and the justification of the design are common issues raised by the CHMP/SAWP.

Maximum type 1 error rate inflation in multiarmed clinical trials with adaptive interim sample size modifications

Sample size modifications in the interim analyses of an adaptive design can inflate the type 1 error rate, if test statistics and critical boundaries are used in the final analysis as if no modification had been made. While this is already true for designs with an overall change of the sample size in a balanced treatment-control comparison, the inflation can be much larger if in addition a modification of allocation ratios is allowed as well. In this paper, we investigate adaptive designs with several treatment arms compared to a single common control group. Regarding modifications, we consider treatment arm selection as well as modifications of overall sample size and allocation ratios. The inflation is quantified for two approaches: a naive procedure that ignores not only all modifications, but also the multiplicity issue arising from the many-to-one comparison, and a Dunnett procedure that ignores modifications, but adjusts for the initially started multiple treatments. The maximum inflation of the type 1 error rate for such types of design can be calculated by searching for the "worst case" scenarios, that are sample size adaptation rules in the interim analysis that lead to the largest conditional type 1 error rate in any point of the sample space. To show the most extreme inflation, we initially assume unconstrained second stage sample size modifications leading to a large inflation of the type 1 error rate. Furthermore, we investigate the inflation when putting constraints on the second stage sample sizes. It turns out that, for example fixing the sample size of the control group, leads to designs controlling the type 1 error rate.

Sharing clinical trial data on patient level: opportunities and challenges

In recent months one of the most controversially discussed topics among regulatory agencies, the pharmaceutical industry, journal editors, and academia has been the sharing of patient-level clinical trial data. Several projects have been started such as the European Medicines Agency´s (EMA) “proactive publication of clinical trial data”, the BMJ open data campaign, or the AllTrials initiative. The executive director of the EMA, Dr. Guido Rasi, has recently announced that clinical trial data on patient level will be published from 2014 onwards (although it has since been delayed). The EMA draft policy on proactive access to clinical trial data was published at the end of June 2013 and open for public consultation until the end of September 2013. These initiatives will change the landscape of drug development and publication of medical research. They provide unprecedented opportunities for research and research synthesis, but pose new challenges for regulatory authorities, sponsors, scientific journals, and the public. Besides these general aspects, data sharing also entails intricate biostatistical questions such as problems of multiplicity. An important issue in this respect is the interpretation of multiple statistical analyses, both prospective and retrospective. Expertise in biostatistics is needed to assess the interpretation of such multiple analyses, for example, in the context of regulatory decision-making by optimizing procedural guidance and sophisticated analysis methods.

Cephalometric assessment of craniofacial dysmorphologies in relation with Msx2 mutations in mouse

OBJECTIVES

To determine the role of Msx2 in craniofacial morphology and growth, we used a mouse model and performed a quantitative morphological characterization of the Msx2 (-/-) and the Msx2 (+/-) phenotype using a 2D cephalometric analysis applied on micrographs.

MATERIALS AND METHODS

Forty-four three-and-a-half-month-old female CD1 mice were divided into the following three groups: Msx2 (+/+) (n = 16), Msx2 (+/-) (n = 16), and Msx2 (-/-) (n = 12). Profile radiographs were scanned. Modified cephalometric analysis was performed to compare the three groups.

RESULTS

Compared with the wild-type mice, the Msx2 (-/-) mutant mice presented an overall craniofacial size decrease and modifications of the shape of the different parts of the craniofacial skeleton, namely the neurocranium, the viscerocranium, the mandible, and the teeth. In particular, dysmorphologies were seen in the cochlear apparatus and the teeth (taurodontism, reduced incisor curvature). Finally contrary to previous published results, we were able to record a specific phenotype of the Msx2 (+/-) mice with this methodology. This Msx2 (+/-) mouse phenotype was not intermediate between the Msx2 (-/-) and the wild-type animals.

CONCLUSION

Msx2 plays an important role in craniofacial morphogenesis and growth because almost all craniofacial structures were affected in the Msx2(-/-) mice including both intramembranous and endochondral bones, the cochlear apparatus, and the teeth. In addition, Msx2 haploinsufficiency involves a specific phenotype with subtle craniofacial structures modifications compared with human mutations.

Role of modeling and simulation in pediatric investigation plans

Ethical and practical constraints encourage the optimal use of resources in pediatric drug development. Modeling and simulation has emerged as a promising methodology acknowledged by industry, academia, and regulators. We previously proposed a paradigm in pediatric drug development, whereby modeling and simulation is used as a decision tool, for study optimization and/or as a data analysis tool. Three and a half years since the Paediatric Regulation came into force in 2007, the European Medicines Agency has gained substantial experience in the use of modeling and simulation in pediatric drug development. In this review, we present examples on how the proposed paradigm applies in real case scenarios of planned pharmaceutical developments. We also report the results of a pediatric database search to further 'validate' the paradigm. There were 47 of 210 positive pediatric investigation plan (PIP) opinions that made reference to modeling and simulation (data included all positive opinions issued up to January 2010). This reflects a major shift in regulatory thinking. The ratio of PIPs with modeling and simulation rose to two in five based on the summary reports. Population pharmacokinetic (POP-PK) and pharmacodynamics (POP-PD) and physiologically based pharmacokinetic models are widely used by industry and endorsed or even imposed by regulators as a way to circumvent some difficulties in developing medicinal products in children. The knowledge of the effects of age and size on PK is improving, and models are widely employed to make optimal use of this knowledge but less is known about the effects of size and maturation on PD, disease progression, and safety. Extrapolation of efficacy from different age groups is often used in pediatric medicinal development as another means to alleviate the burden of clinical trials in children, and this can be aided by modeling and simulation to supplement clinical data. The regulatory assessment is finally judged on clinical grounds such as feasibility, ethical issues, prioritization of studies, and unmet medical need. The regulators are eager to expand the use of modeling and simulation to elucidate safety issues, to evaluate the effects of disease (e.g., renal or hepatic dysfunction), and to qualify mechanistic models that could help shift the current medicinal development paradigm.

Comparison of three separate antiadhesive barriers for intraperitoneal onlay mesh hernia repair in an experimental model

Background

Adhesion formation is a common adverse effect in intraperitoneal onlay mesh (IPOM) surgery. Different methods of adhesion prevention have been developed, including coated meshes and separate antiadhesive barriers (SABs). In this study one type of mesh was tested with different SABs, which were fixed to the sutured mesh using fibrin sealant. The primary aim was to compare adhesion prevention between different SABs. Secondary aims were the assessment of tissue integration and evaluation of SAB fixation with fibrin sealant.

Methods

Thirty-two rats were randomized to one of three treatment groups (SurgiWrap®, Prevadh® and Seprafilm®) or a control group (no SAB). Animals were operated on with an open IPOM technique (8 per group). One macroporous polypropylene mesh per animal (2 × 2 cm) was fixed with four non-absorbable sutures. An antiadhesive barrier of 2·5 × 2·5 cm was fixed with fibrin sealant. After 30 days, adhesion formation, tissue integration, seroma formation, inflammation and vascularization were evaluated macroscopically and by histology.

Results

Prevadh® and Seprafilm® groups showed a significant reduction in adhesion formation compared with the control group. Tissue integration of the mesh was reduced in these groups. Fibrin sealant fixed the SAB to the mesh securely in all groups.

Conclusion

Prevadh® and Seprafilm® are potent materials for the reduction of adhesion formation. A potential relationship between effective adhesion prevention and impaired tissue integration of the implant was observed. Fibrin sealant proved an excellent agent for SAB fixation.

Selection and bias--two hostile brothers

We consider the situation where in a first stage of a clinical trial several treatments are compared with a single control and the 'best' treatment(s) are selected in an interim analysis to be carried on to the second stage. We quantify the mean bias and mean square error of the conventional estimates after selection depending on the number of treatments and the selection time during the trial. The cases without or with reshuffling the planned sample size of the dropped treatments to the selected ones are investigated. The mean bias shows very different patterns depending on the selection rule and the unknown parameter values. We stress the fact that the quantification of the bias is possible only in designs with planned adaptivity where the design allows reacting to new evidence, but the decision rules are laid down in advance. Finally, we calculate the mean bias which arises in a simple but influential regulatory selection rule, to register a new medical therapy only when two pivotal trials have both proven an effect by a statistical test.