A review of Bayesian perspectives on sample size derivation for confirmatory trials

Sample size derivation is a crucial element of the planning phase of any confirmatory trial. A sample size is typically derived based on constraints on the maximal acceptable type I error rate and a minimal desired power. Here, power depends on the unknown true effect size. In practice, power is typically calculated either for the smallest relevant effect size or a likely point alternative. The former might be problematic if the minimal relevant effect is close to the null, thus requiring an excessively large sample size. The latter is dubious since it does not account for the a priori uncertainty about the likely alternative effect size. A Bayesian perspective on the sample size derivation for a frequentist trial naturally emerges as a way of reconciling arguments about the relative a priori plausibility of alternative effect sizes with ideas based on the relevance of effect sizes. Many suggestions as to how such `hybrid' approaches could be implemented in practice have been put forward in the literature. However, key quantities such as assurance, probability of success, or expected power are often defined in subtly different ways in the literature. Starting from the traditional and entirely frequentist approach to sample size derivation, we derive consistent definitions for the most commonly used `hybrid' quantities and highlight connections, before discussing and demonstrating their use in the context of sample size derivation for clinical trials

Особенности моделирования прогнозных оценок экономических объектов

Теория и практика экономических исследований свидетельствует о том, что моделирование прогнозных оценок будущего состояния экономических объектов является наиболее успешным только в тех случаях, когда модель в полной мере отражает как природу процесса управления, так и специфику деловой среды, то есть речь идет, по сути, об адекватности используемой модели

A Review of Bayesian Perspectives on Sample Size Derivation for Confirmatory Trials.

Funder: Biometrika TrustSample size derivation is a crucial element of planning any confirmatory trial. The required sample size is typically derived based on constraints on the maximal acceptable Type I error rate and minimal desired power. Power depends on the unknown true effect and tends to be calculated either for the smallest relevant effect or a likely point alternative. The former might be problematic if the minimal relevant effect is close to the null, thus requiring an excessively large sample size, while the latter is dubious since it does not account for the a priori uncertainty about the likely alternative effect. A Bayesian perspective on sample size derivation for a frequentist trial can reconcile arguments about the relative a priori plausibility of alternative effects with ideas based on the relevance of effect sizes. Many suggestions as to how such "hybrid" approaches could be implemented in practice have been put forward. However, key quantities are often defined in subtly different ways in the literature. Starting from the traditional entirely frequentist approach to sample size derivation, we derive consistent definitions for the most commonly used hybrid quantities and highlight connections, before discussing and demonstrating their use in sample size derivation for clinical trials

Concordance of KRAS/BRAF Mutation Status in Metastatic Colorectal Cancer before and after Anti-EGFR Therapy

Anti-EGFR targeted therapy is a potent strategy in the treatment of metastatic colorectal cancer (mCRC) but activating mutations in the KRAS gene are associated with poor response to this treatment. Therefore, KRAS mutation analysis is employed in the selection of patients for EGFR-targeted therapy and various studies have shown a high concordance between the mutation status in primary CRC and corresponding metastases. However, although development of therapy related resistance occurs also in the context of novel drugs such as tyrosine kinase-inhibitors the effect of the anti-EGFR treatment on the KRAS/BRAF mutation status itself in recurrent mCRC has not yet been clarified. Therefore, we analyzed 21 mCRCs before/after anti-EGFR therapy and found a pre-/posttherapeutic concordance of the KRAS/BRAF mutation status in 20 of the 21 cases examined. In the one discordant case, further analyses revealed that a tumor mosaicism or multiple primary tumors were present, indicating that anti-EGFR therapy has no influence on KRAS/BRAF mutation status in mCRC. Moreover, as the preselection of patients with a KRASwt genotype for anti-EGFR therapy has become a standard procedure, sample sets such ours might be the basis for future studies addressing the identification of potential anti-EGFR therapy induced genetic alterations apart from KRAS/BRAF mutations

Mobile Robot Localization using Panoramic Vision and Combinations of Feature Region Detectors

IEEE International Conference on Robotics and Automation (ICRA 2008, Pasadena, California, May 19-23, 2008), pp. 538-543.This paper presents a vision-based approach for mobile robot localization. The environmental model is topological. The new approach uses a constellation of different types of affine covariant regions to characterize a place. This type of representation permits a reliable and distinctive environment modeling. The performance of the proposed approach is evaluated using a database of panoramic images from different rooms. Additionally, we compare different combinations of complementary feature region detectors to find the one that achieves the best results. Our experimental results show promising results for this new localization method. Additionally, similarly to what happens with single detectors, different combinations exhibit different strengths and weaknesses depending on the situation, suggesting that a context-aware method to combine the different detectors would improve the localization results.This work was partially supported by USC Women in Science and Engineering (WiSE), the FI grant from the Generalitat de Catalunya, the European Social Fund, and the MID-CBR project grant TIN2006-15140-C03-01 and FEDER funds and the grant 2005-SGR-00093

Impact of Borderline Resectability in Pancreatic Head Cancer on Patient Survival: Biology Matters According to the New International Consensus Criteria

Background: International consensus criteria (ICC) have redefined borderline resectability for pancreatic ductal adenocarcinoma (PDAC) according to three dimensions: anatomical (BR-A), biological (BR-B), and conditional (BR-C). The present definition acknowledges that resectability is not just about the anatomic relationship between the tumour and vessels but that biological and conditional dimensions also are important. Methods: Patients’ tumours were retrospectively defined b

Companion Animals in Zoonoses Research – Ethical Considerations

Non-human animals are commonly classified according to their "role", such as "livestock", "wild" or "companion" animals. But what if those classifications overlap? This article presents a report of the retreat week "ZooCan – Zoonoses of companion animals as case study for animal ethics" at the University of Veterinary Medicine Hannover, Germany, in November 2022. The workshop included participants from different European countries with interdisciplinary backgrounds (animal law, bioethics, epidemiology, philosophy, biology and veterinary medicine). We address ethically relevant issues that emerge when companion animals are used as research animals, particularly in zoonoses research. The outcomes of the multi-disciplinary approach are used to i) define criteria to classify "companion" and "research" animals, ii) provide guidance to overcome the challenges with classificational overlaps, iii) give insights into cutting-edge zoonoses research with an example of SARS-CoV-2 in cats, and iv) discuss animal ethics approaches with regard to classifications