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What is an Intent-to-Treat Analysis? A Comprehensive Guide
Introduction:
Are you struggling to understand the nuances of clinical trial data analysis? Lost in the complexities of missing data and its impact on your research conclusions? Then you've come to the right place. This comprehensive guide will demystify intent-to-treat (ITT) analysis, a crucial method for analyzing data in clinical trials and observational studies. We'll explore what ITT analysis is, why it's important, how it's conducted, and its limitations. By the end, you'll be equipped to confidently interpret and utilize ITT analysis in your own work.
What is Intent-to-Treat Analysis?
Intent-to-treat (ITT) analysis is a statistical approach used in clinical trials and other research settings to analyze data based on the original treatment assignment, regardless of whether participants completed the treatment as planned. This means that all participants assigned to a particular treatment group are included in the analysis for that group, even if they didn't adhere to the treatment protocol, dropped out prematurely, or switched to a different treatment. The core principle is to maintain the integrity of the randomization process and preserve the initial treatment allocation.
Why is Intent-to-Treat Analysis Important?
ITT analysis offers several crucial advantages:
Preserves Randomization: By including all participants according to their initial assignment, ITT analysis maintains the balance of baseline characteristics between treatment groups that randomization intended to create. This helps prevent bias and enhances the validity of the results.
Provides a Realistic Assessment of Treatment Effects: In real-world settings, patients may not always adhere perfectly to treatment protocols. ITT analysis reflects this reality, providing a more conservative and generalizable estimate of treatment effectiveness. It accounts for the fact that some participants might not fully benefit from the treatment due to non-compliance or other factors.
Reduces Bias: Methods that exclude participants who didn't complete the treatment (e.g., per-protocol analysis) can introduce bias, potentially overestimating the treatment effect. ITT analysis minimizes this bias by accounting for all participants.
Provides a More Conservative Estimate: The inclusion of non-compliant patients often results in a less dramatic treatment effect than analyses that only consider compliant participants. This conservative estimate can be more realistic and less susceptible to over-interpretation.
How is Intent-to-Treat Analysis Conducted?
The specific methods for conducting ITT analysis can vary depending on the study design and the type of outcome measure. However, the general steps typically include:
1. Defining the Intent-to-Treat Population: This involves clearly specifying which participants are included in the ITT analysis based on their initial treatment assignment.
2. Handling Missing Data: Missing data is a common challenge in ITT analysis. Strategies for handling missing data include:
Last Observation Carried Forward (LOCF): This method uses the last observed value for a participant to represent their outcome for the remainder of the study.
Multiple Imputation: This sophisticated statistical technique creates multiple plausible datasets to account for missing data, allowing for more robust inferences.
Mixed-effects models: These models can effectively incorporate both complete and incomplete data.
3. Statistical Analysis: Once the missing data is handled, appropriate statistical tests are applied to compare the outcomes between the treatment groups. The choice of test depends on the type of outcome variable (continuous, binary, etc.).
Limitations of Intent-to-Treat Analysis
While ITT analysis offers significant advantages, it also has limitations:
Diluted Treatment Effects: The inclusion of non-compliant patients can dilute the observed treatment effect, potentially leading to a failure to detect a true effect if the treatment is highly effective for compliant patients.
Dependence on Missing Data Handling: The results of ITT analysis can be sensitive to the method used for handling missing data. Different methods can produce different results, making it essential to carefully justify the chosen approach.
Difficult Interpretation: Interpreting the results of ITT analysis can be challenging, especially when there is high non-compliance or substantial missing data.
When to Use Intent-to-Treat Analysis
ITT analysis is particularly appropriate in situations where:
High non-compliance is expected: When it's anticipated that a significant proportion of participants will not adhere strictly to the treatment protocol.
The primary goal is to evaluate the effectiveness of an intervention under real-world conditions: ITT analysis provides a more realistic assessment of effectiveness compared to analyses that exclude non-compliant patients.
Maintaining the integrity of randomization is paramount: Preserving the initial randomization is crucial for unbiased conclusions.
Alternatives to Intent-to-Treat Analysis
While ITT analysis is frequently preferred, other analytical approaches exist, including:
Per-protocol analysis: This analysis only includes participants who completed the treatment as planned, providing a potentially biased but more focused assessment of treatment efficacy under ideal conditions.
As-treated analysis: This approach analyzes participants based on the treatment they actually received, regardless of their initial assignment.
Conclusion:
Intent-to-treat analysis is a cornerstone of clinical trial and observational study analysis. Its emphasis on preserving randomization and providing a more realistic assessment of treatment effects makes it a powerful tool. However, it's crucial to be aware of its limitations and to select the most appropriate analytic approach based on the specific research question and study design. By understanding the strengths and weaknesses of ITT analysis, researchers can draw more valid and reliable conclusions from their data.
Article Outline: "Understanding Intent-to-Treat Analysis in Clinical Trials"
Introduction: Define ITT analysis and its importance.
Chapter 1: The Principles of ITT Analysis: Explain the core concept, preserving randomization, and minimizing bias.
Chapter 2: Conducting ITT Analysis: Detail the steps involved, including handling missing data (LOCF, multiple imputation).
Chapter 3: Strengths and Weaknesses of ITT Analysis: Discuss the advantages (realistic assessment, reduced bias) and disadvantages (diluted effects, dependence on missing data handling).
Chapter 4: When to Use ITT Analysis and Alternatives: Provide guidance on when ITT is most suitable and explore alternatives (per-protocol, as-treated).
Conclusion: Summarize key takeaways and emphasize the importance of thoughtful application.
(Detailed explanations for each chapter would follow here, mirroring the content already provided in the main article.)
FAQs:
1. What is the difference between ITT and per-protocol analysis? ITT includes all randomized participants, while per-protocol only includes those who adhered to the protocol.
2. How does ITT analysis handle missing data? Common methods include LOCF, multiple imputation, and mixed-effects models.
3. Is ITT analysis always the best approach? No, the best approach depends on the research question and study design.
4. Can ITT analysis overestimate or underestimate treatment effects? It is more likely to underestimate effects due to inclusion of non-compliant patients.
5. What are the ethical considerations of ITT analysis? Ensuring transparency and accurate reporting of missing data is crucial.
6. How does ITT analysis relate to the concept of blinding? Blinding helps to reduce bias, which ITT analysis also aims to minimize.
7. What statistical tests are typically used in ITT analysis? This depends on the outcome variable (t-tests, ANOVA, chi-squared tests, etc.).
8. Can ITT analysis be used in observational studies? Yes, the principles of ITT can be applied to observational studies as well.
9. What software packages can be used to perform ITT analysis? Many statistical software packages, such as R, SAS, and SPSS, can handle ITT analysis.
Related Articles:
1. Per-Protocol Analysis vs. Intent-to-Treat Analysis: A comparison of these two analytical approaches and their respective strengths and weaknesses.
2. Handling Missing Data in Clinical Trials: A guide to various methods for addressing missing data in clinical trials, including their impact on ITT analysis.
3. The Importance of Randomization in Clinical Trials: Explaining the role of randomization in ensuring the validity of clinical trial results, and how ITT analysis preserves it.
4. Bias in Clinical Trials: Types and Mitigation Strategies: Discussing different types of bias and strategies to minimize them, including the role of ITT analysis.
5. Statistical Power in Clinical Trials: Exploring the concept of statistical power and how it relates to sample size and the interpretation of ITT analysis results.
6. Clinical Trial Design and Methodology: A comprehensive overview of clinical trial design, including the importance of appropriate analytical techniques like ITT.
7. Multiple Imputation for Missing Data: A detailed explanation of multiple imputation and its application in ITT analysis.
8. Mixed-Effects Models in Clinical Trials: Exploring the use of mixed-effects models for analyzing longitudinal data and handling missing data.
9. Interpreting Results from Clinical Trials: A guide to interpreting the findings of clinical trials, with specific attention to understanding the implications of ITT analysis.
| what is an intent to treat analysis: The Prevention and Treatment of Missing Data in Clinical Trials National Research Council, Division of Behavioral and Social Sciences and Education, Committee on National Statistics, Panel on Handling Missing Data in Clinical Trials, 2010-12-21 Randomized clinical trials are the primary tool for evaluating new medical interventions. Randomization provides for a fair comparison between treatment and control groups, balancing out, on average, distributions of known and unknown factors among the participants. Unfortunately, these studies often lack a substantial percentage of data. This missing data reduces the benefit provided by the randomization and introduces potential biases in the comparison of the treatment groups. Missing data can arise for a variety of reasons, including the inability or unwillingness of participants to meet appointments for evaluation. And in some studies, some or all of data collection ceases when participants discontinue study treatment. Existing guidelines for the design and conduct of clinical trials, and the analysis of the resulting data, provide only limited advice on how to handle missing data. Thus, approaches to the analysis of data with an appreciable amount of missing values tend to be ad hoc and variable. The Prevention and Treatment of Missing Data in Clinical Trials concludes that a more principled approach to design and analysis in the presence of missing data is both needed and possible. Such an approach needs to focus on two critical elements: (1) careful design and conduct to limit the amount and impact of missing data and (2) analysis that makes full use of information on all randomized participants and is based on careful attention to the assumptions about the nature of the missing data underlying estimates of treatment effects. In addition to the highest priority recommendations, the book offers more detailed recommendations on the conduct of clinical trials and techniques for analysis of trial data. |
| what is an intent to treat analysis: Principles and Practice of Clinical Trials Steven Piantadosi, Curtis L. Meinert, 2022-07-19 This is a comprehensive major reference work for our SpringerReference program covering clinical trials. Although the core of the Work will focus on the design, analysis, and interpretation of scientific data from clinical trials, a broad spectrum of clinical trial application areas will be covered in detail. This is an important time to develop such a Work, as drug safety and efficacy emphasizes the Clinical Trials process. Because of an immense and growing international disease burden, pharmaceutical and biotechnology companies continue to develop new drugs. Clinical trials have also become extremely globalized in the past 15 years, with over 225,000 international trials ongoing at this point in time. Principles in Practice of Clinical Trials is truly an interdisciplinary that will be divided into the following areas: 1) Clinical Trials Basic Perspectives 2) Regulation and Oversight 3) Basic Trial Designs 4) Advanced Trial Designs 5) Analysis 6) Trial Publication 7) Topics Related Specific Populations and Legal Aspects of Clinical Trials The Work is designed to be comprised of 175 chapters and approximately 2500 pages. The Work will be oriented like many of our SpringerReference Handbooks, presenting detailed and comprehensive expository chapters on broad subjects. The Editors are major figures in the field of clinical trials, and both have written textbooks on the topic. There will also be a slate of 7-8 renowned associate editors that will edit individual sections of the Reference. |
| what is an intent to treat analysis: Clinical Trials Tom Brody, 2016-02-19 Clinical Trials, Second Edition, offers those engaged in clinical trial design a valuable and practical guide. This book takes an integrated approach to incorporate biomedical science, laboratory data of human study, endpoint specification, legal and regulatory aspects and much more with the fundamentals of clinical trial design. It provides an overview of the design options along with the specific details of trial design and offers guidance on how to make appropriate choices. Full of numerous examples and now containing actual decisions from FDA reviewers to better inform trial design, the 2nd edition of Clinical Trials is a must-have resource for early and mid-career researchers and clinicians who design and conduct clinical trials. - Contains new and fully revised material on key topics such as biostatistics, biomarkers, orphan drugs, biosimilars, drug regulations in Europe, drug safety, regulatory approval and more - Extensively covers the study schema and related features of study design - Incorporates laboratory data from studies on human patients to provide a concrete tool for understanding the concepts in the design and conduct of clinical trials - Includes decisions made by FDA reviewers when granting approval of a drug as real world learning examples for readers |
| what is an intent to treat analysis: Developing a Protocol for Observational Comparative Effectiveness Research: A User's Guide Agency for Health Care Research and Quality (U.S.), 2013-02-21 This User’s Guide is a resource for investigators and stakeholders who develop and review observational comparative effectiveness research protocols. It explains how to (1) identify key considerations and best practices for research design; (2) build a protocol based on these standards and best practices; and (3) judge the adequacy and completeness of a protocol. Eleven chapters cover all aspects of research design, including: developing study objectives, defining and refining study questions, addressing the heterogeneity of treatment effect, characterizing exposure, selecting a comparator, defining and measuring outcomes, and identifying optimal data sources. Checklists of guidance and key considerations for protocols are provided at the end of each chapter. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. More more information, please consult the Agency website: www.effectivehealthcare.ahrq.gov) |
| what is an intent to treat analysis: An Approach to Evaluate the Effects of Concomitant Prescribing of Opioids and Benzodiazepines on Veteran Deaths and Suicides National Academies of Sciences, Engineering, and Medicine, Health and Medicine Division, Board on Health Care Services, Committee on Developing a Protocol to Evaluate the Concomitant Prescribing of Opioids and Benzodiazepine Medications and Veteran Deaths and Suicides, 2019-10-16 Opioid prescriptions for acute and chronic pain increased dramatically from the late 1990s into the current decade in both the civilian and the Department of Veterans Affairs and Department of Defense treatment environments. Similarly, prescriptions for benzodiazepines also increased significantly for anxiety and insomnia. Combinations of opioid and benzodiazepines have proven fatal when taken concurrently, with research demonstrating this phenomenon for nearly 40 years. This issue is exacerbated within the veteran population because of higher rates of pain, anxiety and other related health issues due to military life. An evaluation of the relationship between opioid and benzodiazepine medication practices at the VA is necessary to improve treatment for mental health and combat-related trauma for veterans. An Approach to Evaluate the Effects of Concomitant Prescribing of Opioids and Benzodiazepines on Veteran Deaths and Suicides investigates the effects of opioid initiation and tapering strategies in the presence of benzodiazepines in veterans. This report explores neurobiology and the principles of addiction and tolerance, in addition to the current use of opioids and benzodiazepines for treating pain and anxiety in both the veteran and general population. It also provides a protocol to evaluate the relationship between opioid and benzodiazepine medication practices. This framework is a critical foundation for further research to improve concomitant opioid and benzodiazepine medication practices for veterans and the general population. |
| what is an intent to treat analysis: Missing Data in Clinical Studies Geert Molenberghs, Michael Kenward, 2007-04-04 Missing Data in Clinical Studies provides a comprehensive account of the problems arising when data from clinical and related studies are incomplete, and presents the reader with approaches to effectively address them. The text provides a critique of conventional and simple methods before moving on to discuss more advanced approaches. The authors focus on practical and modeling concepts, providing an extensive set of case studies to illustrate the problems described. Provides a practical guide to the analysis of clinical trials and related studies with missing data. Examines the problems caused by missing data, enabling a complete understanding of how to overcome them. Presents conventional, simple methods to tackle these problems, before addressing more advanced approaches, including sensitivity analysis, and the MAR missingness mechanism. Illustrated throughout with real-life case studies and worked examples from clinical trials. Details the use and implementation of the necessary statistical software, primarily SAS. Missing Data in Clinical Studies has been developed through a series of courses and lectures. Its practical approach will appeal to applied statisticians and biomedical researchers, in particular those in the biopharmaceutical industry, medical and public health organisations. Graduate students of biostatistics will also find much of benefit. |
| what is an intent to treat analysis: Clinical Trials in Neurology Bernard Ravina, Michael McDermott, 2012-04-12 Comprehensive book that suggests ways to improve the efficiency of clinical trials and the development of interventions in the neurosciences. |
| what is an intent to treat analysis: Cochrane Handbook for Systematic Reviews of Interventions Julian P. T. Higgins, Sally Green, 2008-11-24 Healthcare providers, consumers, researchers and policy makers are inundated with unmanageable amounts of information, including evidence from healthcare research. It has become impossible for all to have the time and resources to find, appraise and interpret this evidence and incorporate it into healthcare decisions. Cochrane Reviews respond to this challenge by identifying, appraising and synthesizing research-based evidence and presenting it in a standardized format, published in The Cochrane Library (www.thecochranelibrary.com). The Cochrane Handbook for Systematic Reviews of Interventions contains methodological guidance for the preparation and maintenance of Cochrane intervention reviews. Written in a clear and accessible format, it is the essential manual for all those preparing, maintaining and reading Cochrane reviews. Many of the principles and methods described here are appropriate for systematic reviews applied to other types of research and to systematic reviews of interventions undertaken by others. It is hoped therefore that this book will be invaluable to all those who want to understand the role of systematic reviews, critically appraise published reviews or perform reviews themselves. |
| what is an intent to treat analysis: Heart Failure: A Companion to Braunwald's Heart Disease E-Book G. Michael Felker, Douglas L. Mann, 2019-02-06 Up-to-date, authoritative and comprehensive, Heart Failure, 4th Edition, provides the clinically relevant information you need to effectively manage and treat patients with this complex cardiovascular problem. This fully revised companion to Braunwald's Heart Disease helps you make the most of new drug therapies such as angiotensin receptor neprilysin inhibitors (ARNIs), recently improved implantable devices, and innovative patient management strategies. Led by internationally recognized heart failure experts Dr. G. Michael Felker and Dr. Douglas Mann, this outstanding reference gives health care providers the knowledge to improve clinical outcomes in heart failure patients. - Focuses on a clinical approach to treating heart failure, resulting from a broad variety of cardiovascular problems. - Covers the most recent guidelines and protocols, including significant new updates to ACC, AHA, and HFSA guidelines. - Covers key topics such as biomarkers and precision medicine in heart failure and new data on angiotensin receptor neprilysin inhibitors (ARNIs). - Contains four new chapters: Natriuretic Peptides in Heart Failure; Amyloidosis as a Cause of Heart Failure; HIV and Heart Failure; and Neuromodulation in Heart Failure. - Covers the pathophysiological basis for the development and progression of heart failure. - Serves as a definitive resource to prepare for the ABIM's Heart Failure board exam. - 2016 British Medical Association Award: First Prize, Cardiology (3rd Edition). |
| what is an intent to treat analysis: A mixed model approach for intent-to-treat analysis in longitudinal clinical trials with missing values Hrishikesh Chakraborty, Hong Gu, 2009-02-28 Missing values and dropouts are common issues in longitudinal studies in all areas of medicine and public health. Intent-to-treat (ITT) analysis has become a widely accepted method for the analysis of controlled clinical trials. In most controlled clinical trials, some patients do not complete their intended followup according to the protocol for a variety of reasons; this problem generates missing values. Missing values lead to concern and confusion in identifying the ITT population, which makes the data analysis more complex and challenging. No adequate strategy exists for ITT analyses of longitudinal controlled clinical trial data with missing values. Several ad hoc strategies for dealing with missing values for an ITT analysis are common in the practice of controlled clinical trials. We performed a detailed investigation based on simulation studies to develop recommendations for this situation. We compared sizes (type I errors) and power between some popular ad hoc approaches and the linear mixed model approach under different missing value scenarios. Our results suggest that, for studies with a high percentage of missing values, the mixed model approach without any ad hoc imputation is more powerful than other options. |
| what is an intent to treat analysis: Introduction to Statistical Methods for Clinical Trials Thomas D. Cook, David L DeMets, 2007-11-19 Clinical trials have become essential research tools for evaluating the benefits and risks of new interventions for the treatment and prevention of diseases, from cardiovascular disease to cancer to AIDS. Based on the authors’ collective experiences in this field, Introduction to Statistical Methods for Clinical Trials presents various statistical topics relevant to the design, monitoring, and analysis of a clinical trial. After reviewing the history, ethics, protocol, and regulatory issues of clinical trials, the book provides guidelines for formulating primary and secondary questions and translating clinical questions into statistical ones. It examines designs used in clinical trials, presents methods for determining sample size, and introduces constrained randomization procedures. The authors also discuss how various types of data must be collected to answer key questions in a trial. In addition, they explore common analysis methods, describe statistical methods that determine what an emerging trend represents, and present issues that arise in the analysis of data. The book concludes with suggestions for reporting trial results that are consistent with universal guidelines recommended by medical journals. Developed from a course taught at the University of Wisconsin for the past 25 years, this textbook provides a solid understanding of the statistical approaches used in the design, conduct, and analysis of clinical trials. |
| what is an intent to treat analysis: Principles and Practice of Clinical Trial Medicine Richard Chin, Bruce Y Lee, 2008-07-25 Clinical trials are an important part of medicine and healthcare today, deciding which treatments we use to treat patients. Anyone involved in healthcare today must know the basics of running and interpreting clinical trial data. Written in an easy-to-understand style by authors who have considerable expertise and experience in both academia and industry, Principles and Practice of Clinical Trial Medicine covers all of the basics of clinical trials, from legal and ethical issues to statistics, to patient recruitment and reporting results. - Jargon-free writing style enables those with less experience to run their own clinical trials and interpret data - Book contains an ideal mix of theory and practice so researchers will understand both the rationale and logistics to clinical trial medicine - Expert authorship whose experience includes running clinical trials in an academic as well as industry settings - Numerous illustrations reinforce and elucidate key concepts and add to the book's overall pedagogy |
| what is an intent to treat analysis: Statistical Analysis with Missing Data Roderick J. A. Little, Donald B. Rubin, 2019-04-23 An up-to-date, comprehensive treatment of a classic text on missing data in statistics The topic of missing data has gained considerable attention in recent decades. This new edition by two acknowledged experts on the subject offers an up-to-date account of practical methodology for handling missing data problems. Blending theory and application, authors Roderick Little and Donald Rubin review historical approaches to the subject and describe simple methods for multivariate analysis with missing values. They then provide a coherent theory for analysis of problems based on likelihoods derived from statistical models for the data and the missing data mechanism, and then they apply the theory to a wide range of important missing data problems. Statistical Analysis with Missing Data, Third Edition starts by introducing readers to the subject and approaches toward solving it. It looks at the patterns and mechanisms that create the missing data, as well as a taxonomy of missing data. It then goes on to examine missing data in experiments, before discussing complete-case and available-case analysis, including weighting methods. The new edition expands its coverage to include recent work on topics such as nonresponse in sample surveys, causal inference, diagnostic methods, and sensitivity analysis, among a host of other topics. An updated “classic” written by renowned authorities on the subject Features over 150 exercises (including many new ones) Covers recent work on important methods like multiple imputation, robust alternatives to weighting, and Bayesian methods Revises previous topics based on past student feedback and class experience Contains an updated and expanded bibliography The authors were awarded The Karl Pearson Prize in 2017 by the International Statistical Institute, for a research contribution that has had profound influence on statistical theory, methodology or applications. Their work has been no less than defining and transforming. (ISI) Statistical Analysis with Missing Data, Third Edition is an ideal textbook for upper undergraduate and/or beginning graduate level students of the subject. It is also an excellent source of information for applied statisticians and practitioners in government and industry. |
| what is an intent to treat analysis: Principles of Research Design and Drug Literature Evaluation Rajender R. Aparasu, John P. Bentley, 2014-03-07 Principles of Research Design and Drug Literature Evaluation is a unique resource that provides a balanced approach covering critical elements of clinical research, biostatistical principles, and scientific literature evaluation techniques for evidence-based medicine. This accessible text provides comprehensive course content that meets and exceeds the curriculum standards set by the Accreditation Council for Pharmacy Education (ACPE). Written by expert authors specializing in pharmacy practice and research, this valuable text will provide pharmacy students and practitioners with a thorough understanding of the principles and practices of drug literature evaluation with a strong grounding in research and biostatistical principles. Principles of Research Design and Drug Literature Evaluation is an ideal foundation for professional pharmacy students and a key resource for pharmacy residents, research fellows, practitioners, and clinical researchers. FEATURES * Chapter Pedagogy: Learning Objectives, Review Questions, References, and Online Resources * Instructor Resources: PowerPoint Presentations, Test Bank, and an Answer Key * Student Resources: a Navigate Companion Website, including Crossword Puzzles, Interactive Flash Cards, Interactive Glossary, Matching Questions, and Web Links From the Foreword: This book was designed to provide and encourage practitioner’s development and use of critical drug information evaluation skills through a deeper understanding of the foundational principles of study design and statistical methods. Because guidance on how a study’s limited findings should not be used is rare, practitioners must understand and evaluate for themselves the veracity and implications of the inherently limited primary literature findings they use as sources of drug information to make evidence-based decisions together with their patients. The editors organized the book into three supporting sections to meet their pedagogical goals and address practitioners’ needs in translating research into practice. Thanks to the editors, authors, and content of this book, you can now be more prepared than ever before for translating research into practice. L. Douglas Ried, PhD, FAPhA Editor-in-Chief Emeritus, Journal of the American Pharmacists Association Professor and Associate Dean for Academic Affairs, College of Pharmacy, University of Texas at Tyler, Tyler, Texas |
| what is an intent to treat analysis: Multiple Imputation for Nonresponse in Surveys Donald B. Rubin, 2009-09-25 Demonstrates how nonresponse in sample surveys and censuses can be handled by replacing each missing value with two or more multiple imputations. Clearly illustrates the advantages of modern computing to such handle surveys, and demonstrates the benefit of this statistical technique for researchers who must analyze them. Also presents the background for Bayesian and frequentist theory. After establishing that only standard complete-data methods are needed to analyze a multiply-imputed set, the text evaluates procedures in general circumstances, outlining specific procedures for creating imputations in both the ignorable and nonignorable cases. Examples and exercises reinforce ideas, and the interplay of Bayesian and frequentist ideas presents a unified picture of modern statistics. |
| what is an intent to treat analysis: Designing Clinical Research Stephen B. Hulley, 2007 This third edition sets the standard for providing a practical guide to planning, tabulating, formulating, and implementing clinical research, with an easy-to-read, uncomplicated presentation. This edition incorporates current research methodology and offers an updated syllabus for conducting a clinical research workshop. |
| what is an intent to treat analysis: Small Clinical Trials Institute of Medicine, Board on Health Sciences Policy, Committee on Strategies for Small-Number-Participant Clinical Research Trials, 2001-01-01 Clinical trials are used to elucidate the most appropriate preventive, diagnostic, or treatment options for individuals with a given medical condition. Perhaps the most essential feature of a clinical trial is that it aims to use results based on a limited sample of research participants to see if the intervention is safe and effective or if it is comparable to a comparison treatment. Sample size is a crucial component of any clinical trial. A trial with a small number of research participants is more prone to variability and carries a considerable risk of failing to demonstrate the effectiveness of a given intervention when one really is present. This may occur in phase I (safety and pharmacologic profiles), II (pilot efficacy evaluation), and III (extensive assessment of safety and efficacy) trials. Although phase I and II studies may have smaller sample sizes, they usually have adequate statistical power, which is the committee's definition of a large trial. Sometimes a trial with eight participants may have adequate statistical power, statistical power being the probability of rejecting the null hypothesis when the hypothesis is false. Small Clinical Trials assesses the current methodologies and the appropriate situations for the conduct of clinical trials with small sample sizes. This report assesses the published literature on various strategies such as (1) meta-analysis to combine disparate information from several studies including Bayesian techniques as in the confidence profile method and (2) other alternatives such as assessing therapeutic results in a single treated population (e.g., astronauts) by sequentially measuring whether the intervention is falling above or below a preestablished probability outcome range and meeting predesigned specifications as opposed to incremental improvement. |
| what is an intent to treat analysis: Registries for Evaluating Patient Outcomes Agency for Healthcare Research and Quality/AHRQ, 2014-04-01 This User’s Guide is intended to support the design, implementation, analysis, interpretation, and quality evaluation of registries created to increase understanding of patient outcomes. For the purposes of this guide, a patient registry is an organized system that uses observational study methods to collect uniform data (clinical and other) to evaluate specified outcomes for a population defined by a particular disease, condition, or exposure, and that serves one or more predetermined scientific, clinical, or policy purposes. A registry database is a file (or files) derived from the registry. Although registries can serve many purposes, this guide focuses on registries created for one or more of the following purposes: to describe the natural history of disease, to determine clinical effectiveness or cost-effectiveness of health care products and services, to measure or monitor safety and harm, and/or to measure quality of care. Registries are classified according to how their populations are defined. For example, product registries include patients who have been exposed to biopharmaceutical products or medical devices. Health services registries consist of patients who have had a common procedure, clinical encounter, or hospitalization. Disease or condition registries are defined by patients having the same diagnosis, such as cystic fibrosis or heart failure. The User’s Guide was created by researchers affiliated with AHRQ’s Effective Health Care Program, particularly those who participated in AHRQ’s DEcIDE (Developing Evidence to Inform Decisions About Effectiveness) program. Chapters were subject to multiple internal and external independent reviews. |
| what is an intent to treat analysis: Analysis of Observational Health Care Data Using SAS Douglas E. Faries, Andrew C. Leon, Josep Maria Haro, Robert L. Obenchain, 2010 This book guides researchers in performing and presenting high-quality analyses of all kinds of non-randomized studies, including analyses of observational studies, claims database analyses, assessment of registry data, survey data, pharmaco-economic data, and many more applications. The text is sufficiently detailed to provide not only general guidance, but to help the researcher through all of the standard issues that arise in such analyses. Just enough theory is included to allow the reader to understand the pros and cons of alternative approaches and when to use each method. The numerous contributors to this book illustrate, via real-world numerical examples and SAS code, appropriate implementations of alternative methods. The end result is that researchers will learn how to present high-quality and transparent analyses that will lead to fair and objective decisions from observational data. This book is part of the SAS Press program. |
| what is an intent to treat analysis: Dictionary of Pharmaceutical Medicine Gerhard Nahler, 2013-06-29 This dictionary is aimed primarily at the beginners entering the new discipline of Pharmaceutical Medicine, an area comprising aspects of toxicology, pharmacology, pharmaceutics, epidemiology, statistics, drug regulatory and legal affairs, medicine and marketing. But also more experienced colleagues in departments engaged in clinical development as well as researchers and marketing experts in the pharmaceutical industry will find concise and up-to-date information. The book is completed by a list of a about 1000 abbreviations encountered in pharmaceutical medicine and a compilation of important addresses of national and international health authorities. |
| what is an intent to treat analysis: Good Research Practice in Non-Clinical Pharmacology and Biomedicine Anton Bespalov, Martin C. Michel, Thomas Steckler, 2020-01-01 This open access book, published under a CC BY 4.0 license in the Pubmed indexed book series Handbook of Experimental Pharmacology, provides up-to-date information on best practice to improve experimental design and quality of research in non-clinical pharmacology and biomedicine. |
| what is an intent to treat analysis: The Lady Tasting Tea David Salsburg, 2002-05-01 An insightful, revealing history of the magical mathematics that transformed our world. The Lady Tasting Tea is not a book of dry facts and figures, but the history of great individuals who dared to look at the world in a new way. At a summer tea party in Cambridge, England, a guest states that tea poured into milk tastes different from milk poured into tea. Her notion is shouted down by the scientific minds of the group. But one man, Ronald Fisher, proposes to scientifically test the hypothesis. There is no better person to conduct such an experiment, for Fisher is a pioneer in the field of statistics. The Lady Tasting Tea spotlights not only Fisher's theories but also the revolutionary ideas of dozens of men and women which affect our modern everyday lives. Writing with verve and wit, David Salsburg traces breakthroughs ranging from the rise and fall of Karl Pearson's theories to the methods of quality control that rebuilt postwar Japan's economy, including a pivotal early study on the capacity of a small beer cask at the Guinness brewing factory. Brimming with intriguing tidbits and colorful characters, The Lady Tasting Tea salutes the spirit of those who dared to look at the world in a new way. |
| what is an intent to treat analysis: Randomization in Clinical Trials William F. Rosenberger, John M. Lachin, 2015-11-23 Praise for the First Edition “All medical statisticians involved in clinical trials should read this book...” - Controlled Clinical Trials Featuring a unique combination of the applied aspects of randomization in clinical trials with a nonparametric approach to inference, Randomization in Clinical Trials: Theory and Practice, Second Edition is the go-to guide for biostatisticians and pharmaceutical industry statisticians. Randomization in Clinical Trials: Theory and Practice, Second Edition features: Discussions on current philosophies, controversies, and new developments in the increasingly important role of randomization techniques in clinical trials A new chapter on covariate-adaptive randomization, including minimization techniques and inference New developments in restricted randomization and an increased focus on computation of randomization tests as opposed to the asymptotic theory of randomization tests Plenty of problem sets, theoretical exercises, and short computer simulations using SAS® to facilitate classroom teaching, simplify the mathematics, and ease readers’ understanding Randomization in Clinical Trials: Theory and Practice, Second Edition is an excellent reference for researchers as well as applied statisticians and biostatisticians. The Second Edition is also an ideal textbook for upper-undergraduate and graduate-level courses in biostatistics and applied statistics. William F. Rosenberger, PhD, is University Professor and Chairman of the Department of Statistics at George Mason University. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics, and author of over 80 refereed journal articles, as well as The Theory of Response-Adaptive Randomization in Clinical Trials, also published by Wiley. John M. Lachin, ScD, is Research Professor in the Department of Epidemiology and Biostatistics as well as in the Department of Statistics at The George Washington University. A Fellow of the American Statistical Association and the Society for Clinical Trials, Dr. Lachin is actively involved in coordinating center activities for clinical trials of diabetes. He is the author of Biostatistical Methods: The Assessment of Relative Risks, Second Edition, also published by Wiley. |
| what is an intent to treat analysis: Causal Inference Miquel A. Hernan, James M. Robins, 2019-07-07 The application of causal inference methods is growing exponentially in fields that deal with observational data. Written by pioneers in the field, this practical book presents an authoritative yet accessible overview of the methods and applications of causal inference. With a wide range of detailed, worked examples using real epidemiologic data as well as software for replicating the analyses, the text provides a thorough introduction to the basics of the theory for non-time-varying treatments and the generalization to complex longitudinal data. |
| what is an intent to treat analysis: Handbook of Neuroemergency Clinical Trials Brett E. Skolnick, Wayne M. Alves, 2017-11-13 Handbook of Neuroemergency Clinical Trials, Second Edition, focuses on the practice of clinical trials in acute neuroscience populations, or what have been called neuroemergencies. Neuroemergencies are complex, life-threatening diseases and disorders, often with devastating consequences, including death or disability. The overall costs are staggering in terms of annual incidence and costs associated with treatment and survival, yet despite their significance as public health issues, there are few drugs and devices available for definitive treatment. The book focuses on novel therapies and the unique challenges their intended targets pose for the design and analysis of clinical trials. This volume provides neurologists, neuroscientists, and drug developers with a more complete understanding of the scientific and medical issues of relevance in designing and initiating clinical development plans for novel drugs intended for acute neuroscience populations. The editors provide the best understanding of the pitfalls associated with acute CNS drug development and the best information on how to approach and solve issues that have plagued drug development. - Presents a comprehensive overview on clinical trials and drug development challenges in acute neuroscience populations - Provides neurologists, neuroscientists and drug developers with a complete understanding of scientific and medical issues related to designing clinical trials - Edited by leaders in the field who have designed and managed over 50 neuroemergency clinical trials |
| what is an intent to treat analysis: Essential Evidence-Based Medicine Dan Mayer, 2004-06-17 This is an ideal introductory text on Evidence Based Medicine (EBM) for medical students and all health-care professionals. |
| what is an intent to treat analysis: Handbook of Pharmacogenomics and Stratified Medicine Sandosh Padmanabhan, 2014-04-28 Handbook of Pharmacogenomics and Stratified Medicine is a comprehensive resource to understand this rapidly advancing field aiming to deliver the right drug at the right dose to the right patient at the right time. It is designed to provide a detailed, but accessible review of the entire field from basic principles to applications in various diseases. The chapters are written by international experts to allow readers from a wide variety of backgrounds, clinical and non-clinical (basic geneticists, pharmacologists, clinicians, trialists, industry personnel, ethicists) to understand the principles underpinning the progress in this area, the successes, failures and the challenges ahead. To be accessible to the widest range of readers, the clinical application section introduces the disease process, existing therapies, followed by pharmacogenomics and stratified medicine details.Medicine is the cornerstone of modern therapeutics prescribed on the basis that its benefit should outweigh its risk. It is well known that people respond differently to medications and in many cases the risk-benefit ratio for a particular drug may be a gray area. The last decade has seen a revolution in genomics both in terms of technological innovation and discovering genetic markers associated with disease. In parallel there has been steady progress in trying to make medicines safer and tailored to the individual. This has occurred across the whole spectrum of medicine, some more than others. In addition there is burgeoning interest from the pharmaceutical industry to leverage pharmacogenomics for more effective and efficient clinical drug development. - Provides clinical and non-clinical researchers with practical information normally beyond their usual areas of research or expertise - Includes an basic principles section explaining concepts of basic genetics, genetic epidemiology, bioinformatics, pharmacokinetics and pharmacodynamics - Covers newer technologies– next generation sequencing, proteomics, metabolomics - Provides information on animal models, lymphoblastoid cell lines, stem cells - Provides detailed chapters on a wide range of disease conditions, implementation and regulatory issues - Includes chapters on the global implications of pharmacogenomics |
| what is an intent to treat analysis: Essentials of Epidemiology in Public Health Ann Aschengrau, George R. Seage, 2013-06-03 Successfully tested in the authors' courses at Boston University and Harvard University, this text combines theory and practice in presenting traditional and new epidemiologic concepts. Broad in scope, the text opens with five chapters covering the basic epidemiologic concepts and data sources. A major emphasis is placed on study design, with separate chapters devoted to each of the three main analytic designs: experimental, cohort, and case-control studies. Full chapters on bias, confounding, and random error, including the role of statistics in epidemiology, ensure that students are well-equipped with the necessary information to interpret the results of epidemiologic studies. An entire chapter is also devoted to the concept of effect measure modification, an often-neglected topic in introductory textbooks. Up-to-date examples from the epidemiologic literature on diseases of public health importance are provided throughout the book. The Third Edition is a thorough update that offers: • New examples, the latest references, and public health statistics. • Nearly 50 new review questions. • Updated discussion of certain epidemiologic methods. • New figures depicting epidemiologic concepts. |
| what is an intent to treat analysis: Clinical Trials Stuart J. Pocock, 2013-07-17 This comprehensive, unified text on the principles and practice of clinical trials presents a detailed account of how to conduct the trials. It describes the design, analysis, and interpretation of clinical trials in a non-technical manner and provides a general perspective on their historical development, current status, and future strategy. Features examples derived from the author's personal experience. |
| what is an intent to treat analysis: A Mixed Model Approach for Intent-to-Treat Analysis in Longitudinal Clinical Trials with Missing Values Hrishikesh Chakraborty, Hong Gu, 2009 |
| what is an intent to treat analysis: Sharing Clinical Research Data Institute of Medicine, Board on Health Care Services, Board on Health Sciences Policy, Roundtable on Translating Genomic-Based Research for Health, National Cancer Policy Forum, Forum on Neuroscience and Nervous System Disorders, Forum on Drug Discovery, Development, and Translation, 2013-06-07 Pharmaceutical companies, academic researchers, and government agencies such as the Food and Drug Administration and the National Institutes of Health all possess large quantities of clinical research data. If these data were shared more widely within and across sectors, the resulting research advances derived from data pooling and analysis could improve public health, enhance patient safety, and spur drug development. Data sharing can also increase public trust in clinical trials and conclusions derived from them by lending transparency to the clinical research process. Much of this information, however, is never shared. Retention of clinical research data by investigators and within organizations may represent lost opportunities in biomedical research. Despite the potential benefits that could be accrued from pooling and analysis of shared data, barriers to data sharing faced by researchers in industry include concerns about data mining, erroneous secondary analyses of data, and unwarranted litigation, as well as a desire to protect confidential commercial information. Academic partners face significant cultural barriers to sharing data and participating in longer term collaborative efforts that stem from a desire to protect intellectual autonomy and a career advancement system built on priority of publication and citation requirements. Some barriers, like the need to protect patient privacy, pre- sent challenges for both sectors. Looking ahead, there are also a number of technical challenges to be faced in analyzing potentially large and heterogeneous datasets. This public workshop focused on strategies to facilitate sharing of clinical research data in order to advance scientific knowledge and public health. While the workshop focused on sharing of data from preplanned interventional studies of human subjects, models and projects involving sharing of other clinical data types were considered to the extent that they provided lessons learned and best practices. The workshop objectives were to examine the benefits of sharing of clinical research data from all sectors and among these sectors, including, for example: benefits to the research and development enterprise and benefits to the analysis of safety and efficacy. Sharing Clinical Research Data: Workshop Summary identifies barriers and challenges to sharing clinical research data, explores strategies to address these barriers and challenges, including identifying priority actions and low-hanging fruit opportunities, and discusses strategies for using these potentially large datasets to facilitate scientific and public health advances. |
| what is an intent to treat analysis: Practical Biostatistics Mendel Suchmacher, Mauro Geller, 2012-07-26 Evidence-based medicine aims to apply the best available evidence gained from the scientific method to medical decision making. It is a practice that uses statistical analysis of scientific methods and outcomes to drive further experimentation and diagnosis. The profusion of evidence-based medicine in medical practice and clinical research has produced a need for life scientists and clinical researchers to assimilate biostatistics into their work to meet efficacy and practical standards. Practical Biostatistics provides researchers, medical professionals, and students with a friendly, practical guide to biostatistics. With a detailed outline of implementation steps complemented by a review of important topics, this book can be used as a quick reference or a hands-on guide to effectively incorporate biostatistics in clinical trials. - Customized presentation for biological investigators with examples taken from current clinical trials in multiple disciplines - Clear and concise definitions and examples provide a pragmatic guide to bring clarity to the applications of statistics in improving human health - Addresses the challenge of assimilation of mathematical concepts to better interpret literature, to build stronger studies, to present research effectively, and to improve communication with supporting biostatisticians |
| what is an intent to treat analysis: Patient Compliance in Medical Practice and Clinical Trials Joyce A. Cramer, Bert Spilker, 1991 Patient noncompliance with medical regimens is a major factor in therapeutic failure and is particularly detrimental to clinical trials. |
| what is an intent to treat analysis: Users' Guides to the Medical Literature Gordon Guyatt, Drummond Rennie, Maureen O. Meade, Deborah J. Cook, 2008-03-01 The “essential” companion to the landmark Users' Guides to the Medical Literature - completely revised and updated! 5 STAR DOODY'S REVIEW! This second edition is even better than the original. Information is easier to find and the additional resources that will be available at www.JAMAevidence.com will provide readers with a one-stop source for evidence-based medicine.--Doody's Review Service Evidence-based medicine involves the careful interpretation of medical studies and its clinical application. And no resource helps you do it better-and faster-than Users' Guides to the Medical Literature: Essentials of Evidence-Based Clinical Practice. This streamlined reference distills the most clinically-relevant coverage from the parent Users' Guide Manual into one highly-focused, portable resource. Praised for its clear explanations of detailed statistical and mathematical principles, The Essentials concisely covers all the basic concepts of evidence-based medicine--everything you need to deliver optimal patient care. It's a perfect at-a-glance source for busy clinicians and students, helping you distinguish between solid medical evidence and poor medical evidence, tailor evidence-based medicine for each patient, and much more. Now in its second edition, this carry-along quick reference is more clinically relevant--and more essential--than ever! FEATURES Completely revised and updated with all new coverage of the basic issues in evidence-based medicine in patient care Abundant real-world examples drawn from the medical literature are woven throughout, and include important related principles and pitfalls in using clinical research in patient care decisions Edited by over 60 internationally recognized editors and contributors from around the globe Also look for JAMAevidence.com, a new interactive database for the best practice of evidence based medicine. |
| what is an intent to treat analysis: Model Rules of Professional Conduct American Bar Association. House of Delegates, Center for Professional Responsibility (American Bar Association), 2007 The Model Rules of Professional Conduct provides an up-to-date resource for information on legal ethics. Federal, state and local courts in all jurisdictions look to the Rules for guidance in solving lawyer malpractice cases, disciplinary actions, disqualification issues, sanctions questions and much more. In this volume, black-letter Rules of Professional Conduct are followed by numbered Comments that explain each Rule's purpose and provide suggestions for its practical application. The Rules will help you identify proper conduct in a variety of given situations, review those instances where discretionary action is possible, and define the nature of the relationship between you and your clients, colleagues and the courts. |
| what is an intent to treat analysis: Statistical Issues in Drug Research and Development Karl E. Peace, 2017-09-19 This book is a compilation of topics addressed by the ASA Biopharmaceutical Section work groups, including the etiology and evolution of the work groups, the work group guidelines and structure, and the statistical issues associated with clinical trials in clinical drug development programs. |
| what is an intent to treat analysis: Knowing What Works in Health Care Institute of Medicine, Board on Health Care Services, Committee on Reviewing Evidence to Identify Highly Effective Clinical Services, 2008-05-29 There is currently heightened interest in optimizing health care through the generation of new knowledge on the effectiveness of health care services. The United States must substantially strengthen its capacity for assessing evidence on what is known and not known about what works in health care. Even the most sophisticated clinicians and consumers struggle to learn which care is appropriate and under what circumstances. Knowing What Works in Health Care looks at the three fundamental health care issues in the United States-setting priorities for evidence assessment, assessing evidence (systematic review), and developing evidence-based clinical practice guidelines-and how each of these contributes to the end goal of effective, practical health care systems. This book provides an overall vision and roadmap for improving how the nation uses scientific evidence to identify the most effective clinical services. Knowing What Works in Health Care gives private and public sector firms, consumers, health care professionals, benefit administrators, and others the authoritative, independent information required for making essential informed health care decisions. |
| what is an intent to treat analysis: Lakewood Megan Giddings, 2020-03-24 NPR Book of the Year 2020 Electric Literature: One of 55 Books by Women and Nonbinary Writers of Color to Read in 2020 | Lit Hub & The Millions: Most Anticipated Books of 2020 | Ms. Magazine: Anticipated 2020 Feminist Books | Refinery29: Books by Black Women We are Looking Forward To Reading | One of The Millions’ Most Anticipated Reads of 2020 | Amazon Book of the Month Pick | Audible Editor’s Pick | Essence’s Pick| Glamour’s Must Read | Ms. Magazine’s Anticipated Read of 2020 A startling debut about class and race, Lakewood evokes a terrifying world of medical experimentation—part The Handmaid’s Tale, part The Immortal Life of Henrietta Lacks. When Lena Johnson’s beloved grandmother dies, and the full extent of the family debt is revealed, the black millennial drops out of college to support her family and takes a job in the mysterious and remote town of Lakewood, Michigan. On paper, her new job is too good to be true. High paying. No out of pocket medical expenses. A free place to live. All Lena has to do is participate in a secret program—and lie to her friends and family about the research being done in Lakewood. An eye drop that makes brown eyes blue, a medication that could be a cure for dementia, golden pills promised to make all bad thoughts go away. The discoveries made in Lakewood, Lena is told, will change the world—but the consequences for the subjects involved could be devastating. As the truths of the program reveal themselves, Lena learns how much she’s willing to sacrifice for the sake of her family. Provocative and thrilling, Lakewood is a breathtaking novel that takes an unflinching look at the moral dilemmas many working-class families face, and the horror that has been forced on black bodies in the name of science. |
| what is an intent to treat analysis: The Oxford Handbook of Research Strategies for Clinical Psychology Jonathan S. Comer, Philip C. Kendall, 2013-05-09 The Oxford Handbook of Research Strategies for Clinical Psychology has recruited some of the field's foremost experts to explicate the essential research strategies currently used across the modern clinical psychology landscape that maximize both scientific rigor and clinical relevance. |
| what is an intent to treat analysis: Regression Modeling Strategies Frank E. Harrell, 2013-03-09 Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with too many variables to analyze and not enough observations, and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve safe data mining. |
