Improving Lung Cancer Survival Time to Move On
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INDEX A information bias .........................................................29 loss to follow-up bias ....................................... 175, 181 Accuracy minimizing methods of ................................... 181–182 clinical research data ................................................309 nonresponse bias ..............................................175, 181 diagnostic tests .................................................132–133 overmatching bias ....................................................176 Additive models, interaction in. See Interaction recall/memory bias ...........................................176–177 Address transparency .....................................................256 sampling bias ......................................................... 6, 29 ADL and Barthel index .................................................156 types of Alignment of research questions .................................... 300 confounding bias ................................................180 Allele-sharing method ...........................................191–194 information bias .........................................176–179 Allocation concealment ............................................... 6, 98 intervention (exposure) bias ................173, 179–180 Allocative efficiency ........................................237–239, 241 selection bias ...................................24, 25, 173–176 Alpha spending.............................................................. 117 Biomarkers Analyses confounding .................................................... -
Working Memory, Cognitive Miserliness and Logic As Predictors of Performance on the Cognitive Reflection Test
Working Memory, Cognitive Miserliness and Logic as Predictors of Performance on the Cognitive Reflection Test Edward J. N. Stupple ([email protected]) Centre for Psychological Research, University of Derby Kedleston Road, Derby. DE22 1GB Maggie Gale ([email protected]) Centre for Psychological Research, University of Derby Kedleston Road, Derby. DE22 1GB Christopher R. Richmond ([email protected]) Centre for Psychological Research, University of Derby Kedleston Road, Derby. DE22 1GB Abstract Most participants respond that the answer is 10 cents; however, a slower and more analytic approach to the The Cognitive Reflection Test (CRT) was devised to measure problem reveals the correct answer to be 5 cents. the inhibition of heuristic responses to favour analytic ones. The CRT has been a spectacular success, attracting more Toplak, West and Stanovich (2011) demonstrated that the than 100 citations in 2012 alone (Scopus). This may be in CRT was a powerful predictor of heuristics and biases task part due to the ease of administration; with only three items performance - proposing it as a metric of the cognitive miserliness central to dual process theories of thinking. This and no requirement for expensive equipment, the practical thesis was examined using reasoning response-times, advantages are considerable. There have, moreover, been normative responses from two reasoning tasks and working numerous correlates of the CRT demonstrated, from a wide memory capacity (WMC) to predict individual differences in range of tasks in the heuristics and biases literature (Toplak performance on the CRT. These data offered limited support et al., 2011) to risk aversion and SAT scores (Frederick, for the view of miserliness as the primary factor in the CRT. -
3. Studies of Colorectal Cancer Screening
IARC HANDBOOKS COLORECTAL CANCER SCREENING VOLUME 17 This publication represents the views and expert opinions of an IARC Working Group on the Evaluation of Cancer-Preventive Strategies, which met in Lyon, 14–21 November 2017 LYON, FRANCE - 2019 IARC HANDBOOKS OF CANCER PREVENTION 3. STUDIES OF COLORECTAL CANCER SCREENING 3.1 Methodological considerations end-point of the RCT can be the incidence of the cancer of interest. Methods for colorectal cancer (CRC) screen- The observed effect of screening in RCTs is ing include endoscopic methods and stool-based dependent on, among other things, the partic- tests for blood. The two primary end-points for ipation in the intervention group and the limi- endoscopic CRC screening are (i) finding cancer tation of contamination of the control group. at an early stage (secondary prevention) and Low participation biases the estimate of effect (ii) finding and removing precancerous lesions towards its no-effect value, and therefore it must (adenomatous polyps), to reduce the incidence be evaluated and reported. Screening of controls of CRC (primary prevention). The primary by services outside of the RCT also dilutes the end-point for stool-based tests is finding cancer effect of screening on CRC incidence and/or at an early stage. Stool-based tests also have some mortality. If the screening modality being eval- ability to detect adenomatous polyps; therefore, a uated is widely used in clinical practice in secondary end-point of these tests is reducing the the region or regions where the RCT is being incidence of CRC. conducted, then contamination may be consid- erable, although it may be difficult and/or costly 3.1.1 Randomized controlled trials of to estimate its extent. -
Bias and Politics
Bias and politics Luc Bonneux Koninklijke Nederlandse Academie van Wetenschappen NIDI / Den Haag What is bias? ! The assymmetry of a bowling ball. The size and form of the assymmetry will determine its route ! A process at any state of inference tending to produce results that depart systematically from the true values (Fletcher et al, 1988) ! Bias is SYSTEMATIC error Random versus systematic ! Random errors will cancel each other out in the long run (increasing sample size) ! Random error is imprecise ! Systematic errors will not cancel each other out whatever the sample size. Indeed, they will only be strenghtened ! Systematic error is inaccurate Types of bias ! Selection ! Intervention arm is systematically different from control arm ! Information (misclassification) ! Differential errors in measurement of exposure or outcome ! Confounding ! Distortion of exposure - case relation by third factor Experiment vs observation ! Randomisation disperses unknown variables at random between comparison groups ! Observational studies are ALLWAYS biased by known and unknown factors ! But you can understand and MITIGATE their effects Selection bias ! “Selective differences between comparison groups that impacts on relationship between exposure and outcome” Selection bias 1: Reverse causation ! “People engaging in vigorous activities are healthier than lazy ones.” ! “Bedridden people are less healthy than the ones engaging in vigorous activity” Lazy people include those that are unable to exercise because they are unhealthy Selection bias 2 ! Publicity -
Lecture Notes 2018
USMLE ® • UP-TO-DATE ® STEP 2 CK STEP Updated annually by Kaplan’s all-star faculty STEP2 CK • INTEGRATED Lecture Notes 2018 Notes Lecture Packed with bridges between specialties and basic science Lecture Notes 2018 • TRUSTED Psychiatry, Epidemiology, Ethics, Used by thousands of students each year to ace the exam USMLE Patient Safety Psychiatry, Epidemiology, Ethics, Patient Ethics, Epidemiology, Psychiatry, Safety Tell us what you think! Visit kaptest.com/booksfeedback and let us know about your book experience. ISBN: 978-1-5062-2821-1 kaplanmedical.com 9 7 8 1 5 0 6 2 2 8 2 1 1 USMLE® is a joint program of The Federation of State Medical Boards of the United States, Inc. and the National Board of Medical Examiners. USMLE® is a joint program of the Federation of State Medical Boards (FSMB) and the National Board of Medical Examiners (NBME), neither of which sponsors or endorses this product. 978-1-5062-2821-1_USMLE_Step2_CK_Psychiatry_Course_CVR.indd 1 6/15/17 10:24 AM ® STEP 2 CK Lecture Notes 2018 USMLE Psychiatry, Epidemiology, Ethics, Patient Safety USMLE® is a joint program of The Federation of State Medical Boards of the United States, Inc. and the National Board of Medical Examiners. USMLE Step 2 CK Psychiatry.indb 1 6/13/17 3:30 PM USMLE® is a joint program of the Federation of State Medical Boards (FSMB) and the National Board of Medical Examiners (NBME), neither of which sponsors or endorses this product. This publication is designed to provide accurate information in regard to the subject matter covered as of its publication date, with the understanding that knowledge and best practice constantly evolve. -
BMJ Open Is Committed to Open Peer Review. As Part of This Commitment We Make the Peer Review History of Every Article We Publish Publicly Available
BMJ Open: first published as 10.1136/bmjopen-2019-035678 on 31 October 2020. Downloaded from BMJ Open is committed to open peer review. As part of this commitment we make the peer review history of every article we publish publicly available. When an article is published we post the peer reviewers’ comments and the authors’ responses online. We also post the versions of the paper that were used during peer review. These are the versions that the peer review comments apply to. The versions of the paper that follow are the versions that were submitted during the peer review process. They are not the versions of record or the final published versions. They should not be cited or distributed as the published version of this manuscript. BMJ Open is an open access journal and the full, final, typeset and author-corrected version of record of the manuscript is available on our site with no access controls, subscription charges or pay-per-view fees (http://bmjopen.bmj.com). If you have any questions on BMJ Open’s open peer review process please email [email protected] http://bmjopen.bmj.com/ on September 28, 2021 by guest. Protected copyright. BMJ Open BMJ Open: first published as 10.1136/bmjopen-2019-035678 on 31 October 2020. Downloaded from Primary care practitioner diagnostic action when the patient may have cancer: a vignette survey in 20 European countries ForJournal: peerBMJ Open review only Manuscript ID bmjopen-2019-035678 Article Type: Original research Date Submitted by the 20-Nov-2019 Author: Complete List of Authors: Harris, Michael; -
Bias and Confounding • Describe the Key Types of Bias
M1 - PopMed OBJECTIVES Bias and Confounding • Describe the key types of bias • Identify sources of bias in study design, data collection and analysis Saba Masho, MD, MPH, DrPH Department of Epidemiology and Community Health • Identify confounders and methods for [email protected] controlling confounders 1 2 Bias Types: • Bias is any systematic error in an epidemiologic study that results in an 1. Selection incorrect estimate of association between risk factor and outcome. 2. Information/measurement • It is introduced in the design of the study including, data collection, analysis, 3. Confounding interpretation, publication or review of data. • It is impossible to correct for bias during the analysis and may also be hard to evaluate. Thus, studies need to be carefully designed. 3 4 SELECTION BIAS SELECTION BIAS • A systematic error that arises in the process of selecting the study populations • May also occur when membership in one group differs systematically from the general population or • May occur when different criteria is used to select control group, called membership bias cases/controls or exposed/non exposed – E.g. selecting cases from inner hospitals and controls from – E.g. A study in uterine cancer excluding patients with sub-urban hospitals hysterectomy from cases but not from control • The differences in hospital admission between cases • Detection bias: occurs when the risk factor under and controls may conceal an association in a study, investigation requires thorough diagnostic this is called “Berkson’s bias” or “admission -
Education, Faculty of Medicine, Thinking and Decision Making
J R Coll Physicians Edinb 2011; 41:155–62 Symposium review doi:10.4997/JRCPE.2011.208 © 2011 Royal College of Physicians of Edinburgh Better clinical decision making and reducing diagnostic error P Croskerry, GR Nimmo 1Clinical Consultant in Patient Safety and Professor in Emergency Medicine, Dalhousie University, Halifax, Nova Scotia, Canada; 2Consultant Physician in Intensive Care Medicine, Western General Hospital, Edinburgh, UK This review is based on a presentation given by Dr Nimmo and Professor Croskerry Correspondence to P Croskerry, at the RCPE Patient Safety Hot Topic Symposium on 19 January 2011. Department of Emergency Medicine and Division of Medical ABSTRACT A major amount of our time working in clinical practice involves Education, Faculty of Medicine, thinking and decision making. Perhaps it is because decision making is such a Dalhousie University, QE II – commonplace activity that it is assumed we can all make effective decisions. Health Sciences Centre, Halifax Infirmary, Suite 355, 1796 Summer However, this is not the case and the example of diagnostic error supports this Street, Halifax, Nova Scotia B3H assertion. Until quite recently there has been a general nihilism about the ability 2Y9, Canada to change the way that we think, but it is now becoming accepted that if we can think about, and understand, our thinking processes we can improve our decision tel. +1 902 225 0360 making, including diagnosis. In this paper we review the dual process model of e-mail [email protected] decision making and highlight ways in which decision making can be improved through the application of this model to our day-to-day practice and by the adoption of de-biasing strategies and critical thinking. -
Screening for Disease Stanley H
Screening for Disease Stanley H. Weiss, MD, FACP, FACE Professor of Medicine at Rutgers New Jersey Medical School Professor of Epidemiology at Rutgers School of Public Health PI & Director, Essex-Passaic Wellness Coalition Immediate Past Chair, International Joint Policy Committee of the Societies of Epidemiology Cancer Liaison Physician and Oncology Committee Vice-chair, University Hospital, Newark, NJ Executive Board, New Jersey Public Health Association Due Diligence In medicine as in life, it is essential to critically assess what you are told. Statements that on their face may seem reasonable, and indeed even may be true, can be misleading… Those who know me, are well aware that I am quite allergic to furry animals. This led to a problem with having pets in our home, despite my wife and children being animal lovers. As a child, my daughter was very much in love with the following wonderful and adorable creature, to which I have never demonstrated any allergic reaction… So, let me re-state this quite plainly: (Image of unicorns A live unicorn has deleted due to never led me to copyright.) sneeze. I think we can all concur on the (likely) truth of this statement. Why not just test/screen everyone for everything? 1. The test must provide useful information, that is actionable. 2. Harm may be caused, not just benefit. 3. There are costs, even for something that appears trivial. 4. Society makes decisions on resource allocation. 5. Individuals may have different preferences, and come to different conclusions – esp. wrt what is worthwhile for them (such as when they must pay out-of-pocket for non-covered tests). -
Bias Miguel Delgado-Rodrı´Guez, Javier Llorca
635 J Epidemiol Community Health: first published as 10.1136/jech.2003.008466 on 13 July 2004. Downloaded from GLOSSARY Bias Miguel Delgado-Rodrı´guez, Javier Llorca ............................................................................................................................... J Epidemiol Community Health 2004;58:635–641. doi: 10.1136/jech.2003.008466 The concept of bias is the lack of internal validity or Ahlbom keep confounding apart from biases in the statistical analysis as it typically occurs when incorrect assessment of the association between an the actual study base differs from the ‘‘ideal’’ exposure and an effect in the target population in which the study base, in which there is no association statistic estimated has an expectation that does not equal between different determinants of an effect. The same idea can be found in Maclure and the true value. Biases can be classified by the research Schneeweiss.5 stage in which they occur or by the direction of change in a In this glossary definitions of the most com- estimate. The most important biases are those produced in mon biases (we have not been exhaustive in defining all the existing biases) are given within the definition and selection of the study population, data the simple classification by Kleinbaum et al.2 We collection, and the association between different have added a point for biases produced in a trial determinants of an effect in the population. A definition of in the execution of the intervention. Biases in data interpretation, writing, and citing will not the most common biases occurring in these stages is given. be discussed (see for a description of them by .......................................................................... -
Phenomenon of Disease
4. The Phenomenon of Disease Concepts in defining, classifying, detecting, and tracking disease and other health states. The concept of natural history – the spectrum of development and manifestations of pathological conditions in individuals and populations. Definition and classification of disease Although the public health profession is sometimes inclined to refer to the health care system as a "disease care system", others have observed that public health also tends to be preoccupied with disease. One problem with these charges is that both "health" and "disease" are elusive concepts. Defining health and disease Rene Dubos (Man Adapting, p348) derided dictionaries and encyclopedias of the mid-20th century for defining "disease as any departure from the state of health and health as a state of normalcy free from disease or pain". In their use of the terms "normal" and "pathological", contemporary definitions (see table) have not entirely avoided an element of circularity. Rejecting the possibility of defining health and disease in the abstract, Dubos saw the criteria for health as conditioned by the social norms, history, aspirations, values, and the environment, a perspective that remains the case today (Temple et al., 2001). Thus diseases that are very widespread may come to be considered as "normal" or an inevitable part of life. Dubos observed that in a certain South American tribe, pinta (dyschromic spirochetosis) was so common that the Indians regarded those without it as being ill. Japanese physicians have regarded chronic bronchitis and asthma as unavoidable complaints, and in the mid-19th century U.S., Lemuel Shattuck wrote that tuberculosis created little alarm because of its constant presence (Dubos, 251). -
Chapter C: Presenting Probabilities
Presenting Probabilities 2012 UPDATED CHAPTER C: PRESENTING PROBABILITIES SECTION 1: AUTHORS/AFFILIATIONS Lyndal Trevena University of Sydney Australia (co-lead) Brian Zikmund- University of Michigan USA Fisher (co-lead) Adrian Edwards Cardiff University School of Medicine UK Danielle Vrije Universiteit (Free University) Medical Center The Timmermans Netherlands Ellen Peters The Ohio State University USA Isaac Lipkus Duke University School of Nursing USA John King University of Vermont USA Margaret Lawson Children’s Hospital of Eastern Ontario Canada Mirta Galesic Max Planck Institute for Human Development Germany Paul Han Maine Medical Center Research Institute USA StevenWoloshin Dartmouth Institute for Health Policy and Clinical USA Practice Suzanne Linder The University of Texas MD Anderson Cancer Center USA Wolfgang Max Planck Institute for Human Development Germany Gaissmaier Elissa Ozanne University of California USA Suggested Citation: Trevena L, Zikmund-Fisher B, Edwards A, Gaissmaier W, Galesic M, Han P, King J, Lawson M, Linder S, Lipkus I, Ozanne E, Peters E, Timmermans D, Woloshin S. (2012). Presenting probabilities. In Volk R & Llewellyn-Thomas H (editors). 2012 Update of the International Patient Decision Aids Standards (IPDAS) Collaboration's Background Document. Chapter C. http://ipdas.ohri.ca/resources.html. Presenting Probabilities SECTION 2: CHAPTER SUMMARY What is this quality dimension? Medical decisions have outcomes that may have been quantified through research. To assist patients and health professionals in balancing the benefits and harms of these options, decision aids aim to communicate estimates of the likelihoods of these outcomes based on the best available evidence. What is the theoretical rationale for including this quality dimension? When considering decision options and the likelihoods of their outcomes, estimates of both the changes and the outcome frequencies associated with each option need to be conveyed in a way that maximizes patients’ understanding and thereby facilitates informed decision making.