7 research outputs found

    A modified weighted log-rank test for confirmatory trials with a high proportion of treatment switching

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    In confirmatory cancer clinical trials, overall survival (OS) is normally a primary endpoint in the intention-to-treat (ITT) analysis under regulatory standards. After the tumor progresses, it is common that patients allocated to the control group switch to the experimental treatment, or another drug in the same class. Such treatment switching may dilute the relative efficacy of the new drug compared to the control group, leading to lower statistical power. It would be possible to decrease the estimation bias by shortening the follow-up period but this may lead to a loss of information and power. Instead we propose a modified weighted log-rank test (mWLR) that aims at balancing these factors by down-weighting events occurring when many patients have switched treatment. As the weighting should be pre-specified and the impact of treatment switching is unknown, we predict the hazard ratio function and use it to compute the weights of the mWLR. The method may incorporate information from previous trials regarding the potential hazard ratio function over time. We are motivated by the RECORD-1 trial of everolimus against placebo in patients with metastatic renal-cell carcinoma where almost 80\% of the patients in the placebo group received everolimus after disease progression. Extensive simulations show that the new test gives considerably higher efficiency than the standard log-rank test in realistic scenarios

    Serum kidney injury molecule 1 and ÎČ2-microglobulin perform as well as larger biomarker panels for prediction of rapid decline in renal function in type 2 diabetes

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    Aims/hypothesis: As part of the Surrogate Markers for Micro- and Macrovascular Hard Endpoints for Innovative Diabetes Tools (SUMMIT) programme we previously reported that large panels of biomarkers derived from three analytical platforms maximised prediction of progression of renal decline in type 2 diabetes. Here, we hypothesised that smaller (n ≀ 5), platform-specific combinations of biomarkers selected from these larger panels might achieve similar prediction performance when tested in three additional type 2 diabetes cohorts. Methods: We used 657 serum samples, held under differing storage conditions, from the Scania Diabetes Registry (SDR) and Genetics of Diabetes Audit and Research Tayside (GoDARTS), and a further 183 nested case–control sample set from the Collaborative Atorvastatin in Diabetes Study (CARDS). We analysed 42 biomarkers measured on the SDR and GoDARTS samples by a variety of methods including standard ELISA, multiplexed ELISA (Luminex) and mass spectrometry. The subset of 21 Luminex biomarkers was also measured on the CARDS samples. We used the event definition of loss of >20% of baseline eGFR during follow-up from a baseline eGFR of 30–75 ml min−1 [1.73 m]−2. A total of 403 individuals experienced an event during a median follow-up of 7 years. We used discrete-time logistic regression models with tenfold cross-validation to assess association of biomarker panels with loss of kidney function. Results: Twelve biomarkers showed significant association with eGFR decline adjusted for covariates in one or more of the sample sets when evaluated singly. Kidney injury molecule 1 (KIM-1) and ÎČ2-microglobulin (B2M) showed the most consistent effects, with standardised odds ratios for progression of at least 1.4 (p < 0.0003) in all cohorts. A combination of B2M and KIM-1 added to clinical covariates, including baseline eGFR and albuminuria, modestly improved prediction, increasing the area under the curve in the SDR, Go-DARTS and CARDS by 0.079, 0.073 and 0.239, respectively. Neither the inclusion of additional Luminex biomarkers on top of B2M and KIM-1 nor a sparse mass spectrometry panel, nor the larger multiplatform panels previously identified, consistently improved prediction further across all validation sets. Conclusions/interpretation: Serum KIM-1 and B2M independently improve prediction of renal decline from an eGFR of 30–75 ml min−1 [1.73 m]−2 in type 2 diabetes beyond clinical factors and prior eGFR and are robust to varying sample storage conditions. Larger panels of biomarkers did not improve prediction beyond these two biomarkers

    Peritoneal Dialysis International / Composite Outcome Improves Feasibility of Clinical Trials in Peritoneal Dialysis

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    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.(VLID)491884

    Social Attitude to COVID-19 and Influenza Vaccinations after the Influenza Vaccination Season and between the Second and Third COVID-19 Wave in Poland, Lithuania, and Ukraine

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    The SARS-CoV-2 pandemic affected the entire world and contributed to severe health and economic consequences. A safe and effective vaccine is a tool allowing the pandemic to be controlled. Hence, we aimed to conduct a survey on vaccinations against seasonal influenza and COVID-19 in Poland, Lithuania, and Ukraine. We also evaluated societal attitudes towards influenza and COVID-19 vaccinations. Materials and methods: We conducted the study between December 2020 and May 2021. At the time, the countries subject to the research were between the second and third waves of the COVID-19 pandemic. We used an anonymous and self-designed questionnaire comprised of eleven closed-ended questions and a short socio-demographic section. The questionnaire was administered by direct contact or mainly (due to the COVID-19 pandemic) by e-mail or Facebook. Finally, we included 2753 answers from Poland, 1852 from Ukraine, and 213 from Lithuania. Results: Between 61% (Poland) and 72.9% (Ukraine) of the study participants have never been vaccinated against influenza (p &lt; 0.05). Totals of 67.6% of the respondents in Poland, 73.71% in Lithuania, and 29.5% in Ukraine responded that they want to be vaccinated against COVID-19 (p &lt; 0.05). Vaccine hesitancy was mainly related to worries about its side effects. There were also vaccine non-adopters in the study. In Ukraine, 67% of the respondents were clearly opposed to mandatory COVID-19 vaccines, compared to 41.7% in Poland and 30.99% in Lithuania (p &lt; 0.05). Conclusions: There are still many people who present vaccine hesitancy or are opposed to vaccines. Thus, societal education about vaccination and the pandemic is crucial. Vaccine hesitancy or refusal might be related to vaccine origin. Shortages of influenza vaccines made it impossible to vaccinate those who were determined to be vaccinated. There is room for discussion of mandatory COVID-19 vaccinations

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

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    Summary: 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
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