Statistical Issues Arising in the Women's Health Initiative
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Drug Exposure Definition and Healthy User Bias Impacts on the Evaluation of Oral Anti Hyperglycemic Therapies
Drug Exposure Definition and Healthy User Bias Impacts on the Evaluation of Oral Anti Hyperglycemic Therapies by Maxim Eskin A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Health Policy Research School of Public Health University of Alberta © Maxim Eskin, 2017 ABSTRACT Accurate estimation of medication use is an essential component of any pharmacoepidemiological research as exposure misclassification will threaten study validity and lead to spurious associations. Many pharmacoepidemiological studies use simple definitions, such as the categorical “any versus no use” to classify oral antihyperglycemic medications exposure, which has potentially serious drawbacks. This approach has led to numerous highly publicized observational studies of metformin effect on health outcomes reporting exaggerated relationships that were later contradicted by randomized controlled trials. Although selection bias, unmeasured confounding, and many other factors contribute to the discrepancies, one critical element, which is often overlooked, is the method used to define exposure. Another factor that may provide additional explanation for the discrepancy between randomized controlled trials and observational study results of the association between metformin use and various health outcomes is the healthy user effect. Aspects of a healthy lifestyle such as following a balanced diet, exercising regularly, avoiding tobacco use, etc., are not recorded in typical administrative databases and failure to account for these factors in observational studies may introduce bias and produce spurious associations. The influence of a healthy user bias has not been fully examined when evaluating the effect of oral antihyperglycemic therapies in observational studies. It is possible that some, if not all, of the benefit, observed with metformin in observational studies may be related to analytic design and exposure definitions. -
10. Sample Bias, Bias of Selection and Double-Blind
SEC 4 Page 1 of 8 10. SAMPLE BIAS, BIAS OF SELECTION AND DOUBLE-BLIND 10.1 SAMPLE BIAS: In statistics, sampling bias is a bias in which a sample is collected in such a way that some members of the intended population are less likely to be included than others. It results in abiased sample, a non-random sample[1] of a population (or non-human factors) in which all individuals, or instances, were not equally likely to have been selected.[2] If this is not accounted for, results can be erroneously attributed to the phenomenon under study rather than to the method of sampling. Medical sources sometimes refer to sampling bias as ascertainment bias.[3][4] Ascertainment bias has basically the same definition,[5][6] but is still sometimes classified as a separate type of bias Types of sampling bias Selection from a specific real area. For example, a survey of high school students to measure teenage use of illegal drugs will be a biased sample because it does not include home-schooled students or dropouts. A sample is also biased if certain members are underrepresented or overrepresented relative to others in the population. For example, a "man on the street" interview which selects people who walk by a certain location is going to have an overrepresentation of healthy individuals who are more likely to be out of the home than individuals with a chronic illness. This may be an extreme form of biased sampling, because certain members of the population are totally excluded from the sample (that is, they have zero probability of being selected). -
Chu Chen, MS, Phd, NRCC, DABCC Full Member Fred Hutchinson Cancer Research Center 1100 Fairview Avenue North, Mail Stop M5-C800 P.O
CHU CHEN, MS, PhD, NRCC, DABCC PERSONAL DATA Address: Chu Chen, MS, PhD, NRCC, DABCC Full Member Fred Hutchinson Cancer Research Center 1100 Fairview Avenue North, Mail Stop M5-C800 P.O. Box 19024 Seattle, Washington 98109-1024 Tel: (206) 667–6644 Fax: (206) 667–2537 E–mail: [email protected] Citizenship: USA Gender: Female EDUCATION 2003 Fifth Annual Seattle Epidemiology & Biostatistics Summer Section at University of Washington, sponsored by Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs, and Department of Epidemiology and Department of Biostatistics, University of Washington. 2000 New England Epidemiology Institute Summer Course, Tufts University. 1990-1992 Senior Fellow, Division of Clinical Chemistry, Department of Laboratory Medicine, University of Washington, Seattle, Washington. Second Year Specialty Training: Clinical Toxicology. 1987-1990 Postdoctoral Research Associate, Laboratory of Maxine Linial, Ph.D., Member, Program in Molecular Virology, Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington. 1983-1986 Individual National Research Service Award Postdoctoral Fellow, Laboratory of Sen–itiroh Hakomori, M.D., Ph.D., Member, Program in Biochemical Oncology, Division of Basic Sciences, Fred Hutchinson Cancer Research Center, Seattle, Washington and Professor, Department of Pathobiology, University of Washington. 1982 Ph.D. in Biochemistry, University of Washington, Seattle, Washington. Dissertation: "Structure and Reactivity of the Small Spherical High Density Lipoproteins in Familial Lecithin: Cholesterol Acyltransferase Deficiency as Compared with the Structure and Reactivity of Artificially Formed Lipoproteins." Dissertation Advisor: John A. Glomset, M.D., PhD., Professor, Department of Biochemistry and Investigator, Howard Hughes Medical Institute, University of Washington. 1971 M.S. in Botany, Specialization: Medical Mycology, Ohio State University, Columbus, Ohio. -
A User's Guide to Debiasing
A USER’S GUIDE TO DEBIASING Jack B. Soll Fuqua School of Business Duke University Katherine L. Milkman The Wharton School The University of Pennsylvania John W. Payne Fuqua School of Business Duke University Forthcoming in Wiley-Blackwell Handbook of Judgment and Decision Making Gideon Keren and George Wu (Editors) Improving the human capacity to decide represents one of the great global challenges for the future, along with addressing problems such as climate change, the lack of clean water, and conflict between nations. So says the Millenium Project (Glenn, Gordon, & Florescu, 2012), a joint effort initiated by several esteemed organizations including the United Nations and the Smithsonian Institution. Of course, decision making is not a new challenge—people have been making decisions since, well, the beginning of the species. Why focus greater attention on decision making now? Among other factors such as increased interdependency, the Millenium Project emphasizes the proliferation of choices available to people. Many decisions, ranging from personal finance to health care to starting a business, are more complex than they used to be. Along with more choices comes greater uncertainty and greater demand on cognitive resources. The cost of being ill-equipped to choose, as an individual, is greater now than ever. What can be done to improve the capacity to decide? We believe that judgment and decision making researchers have produced many insights that can help answer this question. Decades of research in our field have yielded an array of debiasing strategies that can improve judgments and decisions across a wide range of settings in fields such as business, medicine, and policy. -
An Analytics Approach to Debiasing Asset- Management Decisions
An analytics approach to debiasing asset- management decisions Wealth & Asset Management December 2017 Nick Hoffman Martin Huber Magdalena Smith An analytics approach to debiasing asset-management decisions Asset managers can find a competitive edge in debiasing techniques— accelerated with advanced analytics. Investment managers are pursuing analytics- Richard H. Thaler, one of the leaders in this field aided improvements in many different areas of (see sidebar, “The debiasing nudge”). the business, from customer and asset acquisition to operations and overhead costs. The change Asset management: An industry facing area we focus on in this discussion is investment challenges performance improvement, specifically the Investment managers are facing significant debiasing of investment decisions. With the challenges to profitability. Demonstrating the help of more advanced analytics than they are value of active management has become more already using, funds have been able to measure difficult in a market where returns are narrowing. the role played by bias in suboptimal trading Dissatisfaction with active performance is causing decisions, connecting particular biases customers to migrate toward cheaper passive to particular decisions. Such discoveries funds (Exhibit 1). Actions active funds are taking in provide the necessary foundation for effective response include reducing fees, which has created countermeasures—the debiasing methods that can a competitive cycle that is compressing margins. bring significant performance improvements to a Some funds (such as Allianz Global Investors pressured industry. and Fidelity) are changing their fee and pricing structures to make them more dependent on Business leaders are increasingly recognizing the outperformance through the use of fulcrum-type risk of bias in business decision making. -
National Science Advisory Board for Biosecurity
NATIONAL SCIENCE ADVISORY BOARD FOR BIOSECURITY Written Public Comments (Dec. 13, 2015 – Jan 8 . , 2016) The following are written comments submitted to the National Science Advisory Board for Biosecurity (NSABB) for the period December 13, 2015 – January 8, 2016. Interested persons may file written comments with the Board at any time via an email sent to [email protected]. Written statements should include the name, contact information, and when applicable, the professional affiliation of the interested person. From: David Fedson Sent: Sunday, December 13, 2015 9:35 AM To: Viggiani, Christopher (NIH/OD) [E] Cc: Opal, Steven Subject: NSABB Meeting on GOF research on January 7-8, 2016 Christopher Viggiani, Ph. D. Executive Director, NSABB NIH Office of Science Policy Dear Dr. Viggiani, I have reviewed the agenda of the NSABB meeting on January 7-8, 2016. At this meeting, the NSABB will discuss its Working Group's overview of progress, preliminary findings and draft working paper on Gain-of-Function (GOF) studies. The Gryphon Scientific report - "Risk and Benefit Analysis of Gain of Function Research, Final Report - December 2015" - will be presented at this meeting. I would like to bring to your attention and that of the NSABB several important points. 1. If GOF research accidentally or deliberately creates a new highly virulent and highly transmissible influenza virus, it will spread throughout the world in a matter of months. The ensuing pandemic will be a global event, and it will require a global response. 2. Ron Fouchier has said that Mother Nature is the biggest bioterrorist. Pandemic influenza viruses can arise not only in nature but also in experimental circumstances. -
Cognitive Bias in Clinical Medicine ED O’Sullivan1, SJ Schofi Eld2
J R Coll Physicians Edinb 2018; 48: 225–232 | doi: 10.4997/JRCPE.2018.306 REVIEW Cognitive bias in clinical medicine ED O’Sullivan1, SJ Schofi eld2 ClinicalCognitive bias is increasingly recognised as an important source of medical Correspondence to: error, and is both ubiquitous across clinical practice yet incompletely ED O’Sullivan Abstract understood. This increasing awareness of bias has resulted in a surge in Department of Renal clinical and psychological research in the area and development of various Medicine ‘debiasing strategies’. This paper describes the potential origins of bias Royal Infi rmary of Edinburgh based on ‘dual process thinking’, discusses and illustrates a number of the 51 Little France Crescent important biases that occur in clinical practice, and considers potential strategies that might Edinburgh EH16 4SA be used to mitigate their effect. UK Keywords: cognitive bias, diagnostic error, heuristics, interventions Email: [email protected] Financial and Competing Interests: No fi nancial or competing interests declared Introduction Cognitive bias can lead to medical error The human brain is a complex organ with the wonderful An important concept in understanding error is that of power of enabling man to fi nd reasons for continuing to cognitive bias, and the infl uence this can have on our decision- believe whatever it is that he wants to believe. making.10–12 Cognitive biases, also known as ‘heuristics’, are cognitive short cuts used to aid our decision-making. – Voltaire A heuristic can be thought of as a cognitive ‘rule of thumb’ or cognitive guideline that one subconsciously applies to a Cognitive error is pervasive in clinical practice. -
Pharmacoepidemiological Evaluation in Prostate Cancer—Common Pitfalls and How to Avoid Them
cancers Review Pharmacoepidemiological Evaluation in Prostate Cancer—Common Pitfalls and How to Avoid Them Aino Siltari 1,2, Anssi Auvinen 3 and Teemu J. Murtola 1,4,* 1 Faculty of Medicine and Health Technology, Tampere University, 33520 Tampere, Finland; aino.siltari@helsinki.fi 2 Department of Pharmacology, Faculty of Medicine, University of Helsinki, 00014 Helsinki, Finland 3 Faculty of Social Sciences, Tampere University, 33014 Tampere, Finland; anssi.auvinen@tuni.fi 4 Department of Urology, TAYS Cancer Center, 33520 Tampere, Finland * Correspondence: teemu.murtola@tuni.fi Simple Summary: Pharmacoepidemiologic research provides opportunities to evaluate how com- monly used drug groups, such as cholesterol-lowering drugs, may affect the prostate cancer risk or mortality. However, such studies need to be carefully designed in order to avoid biases caused by systematic differences between medication users and non-users. Similarly, data must be carefully analyzed and interpreted while acknowledging possible biases that can lead to erroneous conclusions. Here, we review common pitfalls in such studies and describe ways to avoid them in an effort to aid future research. Abstract: Pharmacoepidemiologic research provides opportunities to evaluate how commonly used drug groups, such as cholesterol-lowering or antidiabetic drugs, may affect the prostate cancer Citation: Siltari, A.; Auvinen, A.; risk or mortality. This type of research is valuable in estimating real-life drug effects. Nonethe- Murtola, T.J. less, pharmacoepidemiological studies are prone to multiple sources of bias that mainly arise from Pharmacoepidemiological Evaluation systematic differences between medication users and non-users. If these are not appreciated and in Prostate Cancer—Common Pitfalls and How to Avoid Them. -
The Women's Health Initiative: History
DONNA J. BROGAN LECTURE IN BIOSTATISTICS “The Women’s Health Initiative: History, Contributions and Ongoing Research” Presented by: Donna J. Brogan, Ph.D. Emerita Professor Department of Biostatistics and Bioinformatics Rollins School of Public Health Donna J. Brogan received her Ph.D. in statistics from Iowa State University and was Assistant Professor of Biostatistics at UNC School of Public Health before joining Emory in 1971 as the first female faculty member in its Statistics/Biometry Department, later becoming only the fourth female full professor in its School of Medicine. In the Rollins School of Public Health, she was its first female full professor and its first female chair of the Department of Ross L. Prentice, Ph.D. Biostatistics. Dr. Brogan’s research interests, reflected in her 150 publications, Fred Hutchinson Cancer Research Center and include design and analysis of complex sample surveys and collaboration with University of Washington health scientists. Dr. Brogan’s honors include fellow of the American Statistical Association The Women’s Health Initiative was launched in 1992 following some years of developmental work. It enrolled 161,808 healthy postmenopausal women at (ASA), Emory University’s Thomas Jefferson Award, three distinguished alumni awards [Gettysburg College (BA), Purdue (MS), Iowa State (Ph.D.)], 40 U.S. clinical centers. A randomized, controlled trial among 68,132 such and the ASA’s Elizabeth Scott Award for significant contributions to the women examined the health effects of postmenopausal hormone therapy, a advancement of women within the statistics discipline. Dr. Brogan’s leadership low-fat dietary pattern, and calcium and vitamin D supplementation, in a partial talent in academic and government realms was applied to selected activism. -
Cohort Study, Tz Jay
世代追蹤 Cohort Study 國立成功大學 臨床藥學與藥物科技研究所 林子傑 博士後研究員 2014.10.23 Outline • Overview of pharmacoepidemiology (PE) • Design and structure of cohort studies What is pharmacoepidemiology? • The study of the use of and effects of drugs in large numbers of people. -- Brain L. Strom, editor Pharmacoepidemiology 4th edition • The study of the frequency, distribution, and determinants of diseases in humans, with “determinants” being drugs, vaccines or devices. -- Hartzema AG, Tilson HH, Chan KA, editors. Pharmacoepidemiology and Therapeutic Risk Management Pharmacoepidemiology is the study of the use of and effects of drugs in large numbers of people Pharmaco- Providing information about the epidemiology beneficial and harmful effects of any drug, thus permitting a better assessment of the risk/benefit balance for the use Borrow the research of any particular drug in any methods particular patient Marriage Clinical Epidemiology pharmacology Epidemiology is the study of the distribution Pharmacology is the study of the effects of drugs. and determinants of diseases in populations Clinical pharmacology is the study of the effects of drugs in humans. PHARMACOEPIDEMIOLOGY 4.Ed, edited by BRIAN L. STROM What is cohort study ? • Cohort studies → Studies that identify subsets of a defined population and follow them over time, looking for differences in their outcome --- BRIAN L. STROM • In PE: population-based What a cohort study can do in PE? • Causal-relationship Effectiveness and safety of drugs • Incidence rate, Number needed to treat / harm Risk difference, -
Hypothalamic Clock Involvement in Cluster Headache
Faculty of Health Sciences Department of Clinical Medicine Hypothalamic clock involvement in cluster headache A study of chronobiology, sleep, and cranial autonomic function in cluster headache — Hilde Karen Ofte A dissertation for the degree of Philosophiae Doctor – October 2016 Faculty of Health Science Department of Clinical Medicine UiT – The Arctic University of Tromsø Hypothalamic clock involvement in cluster headache A study of chronobiology, sleep, and cranial autonomic function in cluster headache Hilde Karen Ofte, MD A dissertation for the degree of Philosophiae Doctor - 2016 1 The anatomy lesson of Dr Nicolaes Tulp. Rembrandt van Rejn, 1632 [On the case of Isak van Halmaal, who:] “… in the beginning of the summer season, was afflicted with a severe headache, occurring and disappearing daily on fixed hours, with such an intensity that he often assured me that he could not bear the pain anymore or he would succumb shortly. For rarely, it lasted more than two hours. And the rest of the day there was no fever, nor indisposition of the urine, nor any infirmity of the pulse. But this recurring pain lasted until the fourteenth day..” Nicolaes Tulp, Observationes Medicae,1641 2 Table of contents Table of contents ..................................................................................................................... 3 Aknowledgements ................................................................................................................... 5 Abbreviations .......................................................................................................................... -
Primacy, Congruence and Confidence in Diagnostic Decision-Making
Primacy, Congruence and Confidence in Diagnostic Decision-Making Thomas Frotvedt1, Øystein Keilegavlen Bondevik1, Vanessa Tamara Seeligmann, Bjørn Sætrevik Department of psychosocial science, University of Bergen 1: These authors contributed equally to the manuscript Abstract Some heuristics and biases are assumed to be universal for human decision-making, and may thus be expected to appear consistently and need to be considered when planning for real-life decision-making. Yet results are mixed when exploring the biases in applied settings, and few studies have attempted to robustly measure the combined impact of various biases during a decision-making process. We performed three pre-registered classroom experiments in which trained medical students read case descriptions and explored follow-up information in order to reach and adjust mental health diagnoses (∑N = 224). We tested whether the order of presenting the symptoms led to a primacy effect, whether there was a congruence bias in selecting follow-up questions, and whether confidence increased during the decision process. Our results showed increased confidence for participants that did not change their decision or sought disconfirming information. There was some indication of a weak congruence bias in selecting follow-up questions. There was no indication of a stronger congruence bias when confidence was high, and there was no support for a primacy effect of the order of symptom presentation. We conclude that the biases are difficult to demonstrate in pre-registered analyses of