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Clinical Performance Assessment: Considerations for Computer
Contains Nonbinding Recommendations Clinical Performance Assessment: Considerations for Computer-Assisted Detection Devices Applied to Radiology Images and Radiology Device Data in - Premarket Notification (510(k)) Submissions Guidance for Industry and FDA Staff Document issued on: January 22, 2020 Document originally issued on July 3, 2012 For questions regarding this guidance document, contact Nicholas Petrick at 301-796-2563, or by e- mail at [email protected]; or Robert Ochs at 301-796-6661, or by e-mail at [email protected]. U.S. Department of Health and Human Services Food and Drug Administration Center for Devices and Radiological Health Contains Nonbinding Recommendations Preface Public Comment You may submit electronic comments and suggestions at any time for Agency consideration to https://www.regulations.gov. Submit written comments to the Dockets Management Staff, Food and Drug Administration, 5630 Fishers Lane, Room 1061, (HFA-305), Rockville, MD 20852. Identify all comments with the docket number FDA-2009-D-0503. Comments may not be acted upon by the Agency until the document is next revised or updated. Additional Copies Additional copies are available from the Internet. You may also send an e-mail request to CDRH- [email protected] to receive a copy of the guidance. Please use the document number (1698) to identify the guidance you are requesting. Table of Contents 1. INTRODUCTION .................................................................................................................... 4 2. -
FDA Guidance: “Design Considerations for Pivotal Clinical Investigations for Medical Devices”
FDA Guidance: “Design Considerations for Pivotal Clinical Investigations for Medical Devices” Greg Campbell, Ph.D. Director, Division of Biostatistics Center for Devices and Radiological Health U.S. Food and Drug Administration [email protected] FDA Stakeholder Webinar December 4, 2013 Design Considerations for Pivotal Clinical Investigations • http://www.fda.gov/medicaldevices/deviceregulation andguidance/guidancedocuments/ucm373750.htm • Draft issued Aug. 15, 2011; Final issued Nov. 7, 2013. • It is guidance for industry, clinical investigators, institutional review boards and FDA staff. 2 Design Considerations for Pivotal Clinical Investigations • Guidance should help manufacturers select appropriate trial design. • Better trial design and improve the quality of data that may better support the safety and effectiveness of a device. • Better quality data may lead to timelier FDA approval or clearance of premarket submissions and speed U.S. patient access to new devices. 3 Outline • Regulatory Considerations • Principles for the Choice of Clinical Study Design • Clinical Outcome Studies – RCTs – Controls – Non-Randomized Controls – Observational Uncontrolled One-Arm Studies • OPCs and Performance Goals – Diagnostic Clinical Outcome Studies • Diagnostic Clinical Performance Studies • Sustaining the Level of Evidence of Studies • Protocol and Statistical Analysis Plan • Closing Remarks 4 Stages of Medical Device Clinical Studies 1) Exploratory Stage – first-in-human and feasibility/pilot studies, iterative learning and product development. 2) Pivotal Stage – definitive study to support the safety and effectiveness evaluation of the medical device for its intended use. 3) Postmarket Stage – includes studies intended to better understand the long-term effectiveness and safety of the device, including rare adverse events. Not all products will go through all stages. -
Data Management and Data Sharing in Science and Technology Studies
Article Science, Technology, & Human Values 1-18 ª The Author(s) 2018 Data Management Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0162243918798906 and Data Sharing journals.sagepub.com/home/sth in Science and Technology Studies Katie Jane Maienschein1, John N. Parker2, Manfred Laubichler1 and Edward J. Hackett3 Abstract This paper presents reports on discussions among an international group of science and technology studies (STS) scholars who convened at the US National Science Foundation (January 2015) to think about data sharing and open STS. The first report, which reflects discussions among members of the Society for Social Studies of Science (4S), relates the potential benefits of data sharing and open science for STS. The second report, which reflects dis- cussions among scholars from many professional STS societies (i.e., European Association for the Study of Science and Technology [EASST], 4S, Society for the History of Technology [SHOT], History of Science Society [HSS], and Philosophy of Science Association [PSA]), focuses on practical and conceptual issues related to managing, storing, and curating STS data. As is the case for all reports of such open discussions, a scholar’s presence at the meeting does not necessarily mean that they agree with all aspects of the text to follow. 1Center for Biology and Society, School of Life Sciences, Arizona State University, Tempe, AZ, USA 2Barrett, The Honors College, Arizona State University, Tempe, AZ, USA 3Heller School for Social Policy and Management, Brandeis University, Waltham, MA, USA Corresponding Author: John N. Parker, Barrett, The Honors College, Arizona State University, PO Box 871612, Tempe, AZ 85287, USA. -
Missing Data in Clinical Studies
The perils of the unknown: Missing data in clinical studies Helen Bridge1 andThomas M. Schindler2 1 AstraZeneca, Cambridge, UK 2 Boehringer Ingelheim Pharma, Biberach, Germany Visit 1 Correspondence to: Visit 2 Helen Bridge or Thomas M. Schindler Medical Writing Europe Boehringer Ingelheim Pharma Birkendorfer Str. 65 Visit 3 88307 Biberach an der Riß, Germany Thomas.Schindler@ boehringer-ingelheim.com Visit 4 Abstract The phenomenon of missing data is ubiquitous in clinical studies. Both the extent Visit 5 of missing data and the structure of missing data can introduce bias into study results and All rights reserved Schindler ©TM lead to wrong conclusions. Medical writers Figure 1. A depiction of missing data in clinical trials. should be aware of the extent of missing data All rights reserved ©TM Schindler and should describe the methods used to deal with the issue. This article outlines some of consequences. The complexity of clinical studies writer be absolved of having to talk about missing the most commonly used statistical methods means that everything is related to everything data. But as seen from this non-exhaustive list, in for handling missing data. The traditionally else, so the issue of missing data is linked to many the real world things are never perfect, and used last-observation-carried-forward (LOCF) other aspects, from study design to patient the issue of missing data will invariably arise. method to fill data gaps is problematic in retention, data analysis, and the conclusions that many ways. It is better to employ a method can be drawn. Because of this, every scientific What are the issues? that reduces bias, such as multiple imputation report about a clinical study must take note of the We cannot assume that we will obtain all the data (MI) or mixed-effects models for repeated extent to which data are missing and how this for all patients in a clinical study. -
ICH Guideline E8 (R1) on General Considerations for Clinical Studies Step 2B
08 May 2019 EMA/CHMP/ICH/544570/1998 Committee for Human Medicinal Products ICH guideline E8 (R1) on general considerations for clinical studies Step 2b Transmission to CHMP 25 April 2019 Adoption by CHMP 25 April 2019 Release for public consultation 10 May 2019 Deadline for comments 30 September 2019 Comments should be provided using this template. The completed comments form should be sent to [email protected] Official address Domenico Scarlattilaan 6 ● 1083 HS Amsterdam ● The Netherlands Address for visits and deliveries Refer to www.ema.europa.eu/how-to-find-us Send us a question Go to www.ema.europa.eu/contact Telephone +31 (0)88 781 6000 An agency of the European Union © European Medicines Agency, 2019. Reproduction is authorised provided the source is acknowledged. INTERNATIONAL COUNCIL FOR HARMONISATION OF TECHNICAL REQUIREMENTS FOR PHARMACEUTICALS FOR HUMAN USE ICH HARMONISED GUIDELINE GENERAL CONSIDERATIONS FOR CLINICAL STUDIES E8(R1) Draft version Currently under public consultation At Step 2 of the ICH Process, a consensus draft text or guideline, agreed by the appropriate ICH Expert Working Group, is transmitted by the ICH Assembly to the regulatory authorities of the ICH regions for internal and external consultation, according to national or regional procedures E8(R1) Document History Code History Date E8(R1) Endorsement by the Members of the ICH Assembly under Step 2 and release for public consultation (document dated 25 March 2019). Legal notice: This document is protected by copyright and may, with the exception of the ICH logo, be used, reproduced, incorporated into other works, adapted, modified, translated or distributed under a public license provided that ICH's copyright in the document is acknowledged at all times. -
Sharing Is Caring—Data Sharing Initiatives in Healthcare
International Journal of Environmental Research and Public Health Review Sharing Is Caring—Data Sharing Initiatives in Healthcare Tim Hulsen Department of Professional Health Solutions & Services, Philips Research, 5656AE Eindhoven, The Netherlands; [email protected] Received: 28 February 2020; Accepted: 24 April 2020; Published: 27 April 2020 Abstract: In recent years, more and more health data are being generated. These data come not only from professional health systems, but also from wearable devices. All these ‘big data’ put together can be utilized to optimize treatments for each unique patient (‘precision medicine’). For this to be possible, it is necessary that hospitals, academia and industry work together to bridge the ‘valley of death’ of translational medicine. However, hospitals and academia often are reluctant to share their data with other parties, even though the patient is actually the owner of his/her own health data. Academic hospitals usually invest a lot of time in setting up clinical trials and collecting data, and want to be the first ones to publish papers on this data. There are some publicly available datasets, but these are usually only shared after study (and publication) completion, which means a severe delay of months or even years before others can analyse the data. One solution is to incentivize the hospitals to share their data with (other) academic institutes and the industry. Here, we show an analysis of the current literature around data sharing, and we discuss five aspects of data sharing in the medical domain: publisher requirements, data ownership, growing support for data sharing, data sharing initiatives and how the use of federated data might be a solution. -
Phase III Clinical Trials, What Are They Good For?
Phase III Clinical Trials, what are they good for? Session 4: Clinical Trials Tuesday 12th February 2019 Professor Alan Boyd FRCP FFPM Immediate Past President, Faculty of Pharmaceutical Medicine, RCP CEO, Boyd Consultants Ltd Standard Drug Development Process Risk Management Plan - Decision to Pharmacovigilance Develop Product: Research & IMPD/CTA Phase Phase File MMA Post-Approval Selection of Pre-Clinical Phase Filing I II + NDA Clinical Studies Compound Research & III Toxicology, Manufacturing Health Technology Assessments 20-100 Healthy 100-300 300-3000+ Volunteers &/or Patients: Patients: Patients: Assess Safety & Assess/Confirm Assess Safety Efficacy Safety, Efficacy & Effectiveness Origin of Phase III Clinical Trials • Phase III Clinical Trial is typically a prospective Randomised Controlled Trial that investigates the effects of an experimental treatment compared with a control treatment (an approved therapy, standard care or placebo) • Concept of RCTs not established till 1948 – MRC Study of Streptomycin in TB – Austin Bradford Hill credited with establishing RCTs as quoted in the BMJ ‘need for adequately controlled clinical trials’ • RCTs now recognised as the standard approach for determining therapeutic safety and efficacy of new medicinal products RCTs & Phase III Clinical Trials • By 2004 Cochrane Library contained over 150,000 RCTs • Plus procedures & guidelines around the conduct and reporting of RCTs have been developed and refined • Example – CONSORT Statement for reporting RCTs – 1996, 2001 & 2010 • ClinicalTrials.gov -
ORION OPEN SCIENCE FACTSHEETS Brief, Informative, and Easy-To-Understand One-Page Factsheets on Open Science Topics
ORION OPEN SCIENCE FACTSHEETS Brief, informative, and easy-to-understand one-page factsheets on Open Science topics Created by the Max-Delbrück-Centre for Molecular Medicine in the Helmholtz Association Design by Vetenskap & Allmänhet This project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement No. 741527 and runs from May 2017 to April 2021. CONTENTS 1. Biohacking and DIYBio Research .......................................................................................... 3 2. Career Benefits of Open Science ......................................................................................... 4 3. Citizen Science ....................................................................................................................... 5 4. Commercialisation of Research ............................................................................................ 6 5. Communicating Animal Research ......................................................................................... 7 6. Crowd Science ....................................................................................................................... 8 7. Research Data Management ................................................................................................. 9 8. Open Access ......................................................................................................................... 10 9. Open Research Data ........................................................................................................... -
Reports of Uncontrolled Clinical Trials for Directly Placed Restorations in Vital Teeth
ORIGINAL RESEARCH Dentistry Reports of uncontrolled clinical trials for directly placed restorations in vital teeth Steffen MICKENAUTSCH(a), Abstract: Uncontrolled trials are criticized as unreliable. This study aimed (a) Veerasamy YENGOPAL to establish how the number of published reports from uncontrolled clinical trials compares to that of controlled trials for directly placed (a) University of the Witwatersrand, Department restorations in vital teeth and whether their annual number is increasing, of Community Dentistry, Faculty of Health stable or decreasing. PubMed was searched and suitable citations of Science, Johannesburg, South Africa. uncontrolled and controlled trial reports published between 1990–2016 were included. Reference check and hand searching were conducted. The median annual report number with 25 and 75% percentile was calculated for both types of trials. 695 reports were found. The median number of reports per year was 4 (3–7) and 22 (15–26) from uncontrolled and controlled trials, respectively. A statistically significant decreasing ratio of uncontrolled to controlled trial reports was observed (p = 0.01) by linear regression analysis. The number of reports of uncontrolled clinical trials listed in PubMed over the last 27 years appears at least five times smaller than that of controlled clinical trials and its number in relation to that of controlled trials seems to decrease over time. Keywords: Clinical Trial; Research Design; Dentistry. Introduction Declaration of Interest:The authors certify that they have no commercial or associative Uncontrolled clinical trials are defined as trials with one single interest that represents a conflict of interest in treatment arm during which all patients receive the same intervention connection with the manuscript. -
Practical Help for Specifying the Target Difference in Sample Size Calculations for Rcts : the DELTA2 Five-Stage Study, Including a Workshop
This is a repository copy of Practical help for specifying the target difference in sample size calculations for RCTs : the DELTA2 five-stage study, including a workshop. White Rose Research Online URL for this paper: http://eprints.whiterose.ac.uk/152823/ Version: Published Version Article: Cook, J.A., Julious, S.A., Sones, W. et al. (18 more authors) (2019) Practical help for specifying the target difference in sample size calculations for RCTs : the DELTA2 five-stage study, including a workshop. Health Technology Assessment, 23 (60). pp. 1-88. ISSN 1366-5278 https://doi.org/10.3310/hta23600 © Queen’s Printer and Controller of HMSO 2019. This work was produced by Cook et al. under the terms of a commissioning contract issued by the Secretary of State for Health and Social Care. This issue may be freely reproduced for the purposes of private research and study and extracts (or indeed, the full report) may be included in professional journals provided that suitable acknowledgement is made and the reproduction is not associated with any form of advertising. Applications for commercial reproduction should be addressed to: NIHR Journals Library, National Institute for Health Research, Evaluation, Trials and Studies Coordinating Centre, Alpha House, University of Southampton Science Park, Southampton SO16 7NS, UK. Reuse Items deposited in White Rose Research Online are protected by copyright, with all rights reserved unless indicated otherwise. They may be downloaded and/or printed for private study, or other acts as permitted by national copyright laws. The publisher or other rights holders may allow further reproduction and re-use of the full text version. -
Optimal Adaptive Designs and Adaptive Randomization Techniques for Clinical Trials
UPPSALA DISSERTATIONS IN MATHEMATICS 113 Optimal adaptive designs and adaptive randomization techniques for clinical trials Yevgen Ryeznik Department of Mathematics Uppsala University UPPSALA 2019 Dissertation presented at Uppsala University to be publicly examined in Ång 4101, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, Friday, 26 April 2019 at 09:00 for the degree of Doctor of Philosophy. The examination will be conducted in English. Faculty examiner: Associate Professor Franz König (Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna). Abstract Ryeznik, Y. 2019. Optimal adaptive designs and adaptive randomization techniques for clinical trials. Uppsala Dissertations in Mathematics 113. 94 pp. Uppsala: Department of Mathematics. ISBN 978-91-506-2748-0. In this Ph.D. thesis, we investigate how to optimize the design of clinical trials by constructing optimal adaptive designs, and how to implement the design by adaptive randomization. The results of the thesis are summarized by four research papers preceded by three chapters: an introduction, a short summary of the results obtained, and possible topics for future work. In Paper I, we investigate the structure of a D-optimal design for dose-finding studies with censored time-to-event outcomes. We show that the D-optimal design can be much more efficient than uniform allocation design for the parameter estimation. The D-optimal design obtained depends on true parameters of the dose-response model, so it is a locally D-optimal design. We construct two-stage and multi-stage adaptive designs as approximations of the D-optimal design when prior information about model parameters is not available. Adaptive designs provide very good approximations to the locally D-optimal design, and can potentially reduce total sample size in a study with a pre-specified stopping criterion. -
Health Outcomes Research HIM 6810 Health Outcomes Research (HIM 6810)
Graduate and Postdoctoral Affairs School of Biomedical Sciences Morsani College of Medicine Health Outcomes Research HIM 6810 Health Outcomes Research (HIM 6810) Course Director: Michael J. Barber, M.Sc., D.Phil. (813) 974-4181 (813) 974-4317 Canvas integrated email system Course Format: This course is delivered online through the USF Health Online Portal (http://www.usfhealthonline.com/). Course Objectives: ealth Outcomes Research (HIM 6810) is a graduate-level course designed to introduce students to fundamentals of H health outcome and clinical trial research. It explores the principles and methods used to obtain quantitative evidence on the effects of interventions on the diagnosis, etiology, and prognosis of disease. Health outcomes research is a broad term used to categorize research concerned with the effectiveness of public health interventions and health services. According to the US Agency for Healthcare Research and Quality, outcomes research seeks to understand the end results of particular health care practices and interventions. End results include effects that people experience and care about, such as change in the ability to function. In particular, for individuals with chronic conditions, where cure is not always possible, end results include quality of life as well as mortality. By linking the care that people get to the outcomes they experience, outcomes research has become the key to developing better ways to monitor and improve the quality of care. Outcomes research is an integrated, multidisciplinary field that aims at improving the safety, effectiveness, equity, efficiency, timeliness, and patient-centeredness of practice and policy associated with healthcare research. It synthesizes aspects of other scientific and applied disciplines to solve clinical and policy research problems.