Patient Care under Uncertainty

Name: Patient Care under Uncertainty
Brand: Princeton University Press
Price: 45.99 EUR
Availability: OnlineOnly

Charles F. Manski(Autor*in)

Princeton University Press

1. Auflage

Erschienen am 10. September 2019

184 Seiten

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Inhalt

Cover
Contents
Preface
Introduction
Surveillance or Aggressive Treatment
Evolution of the Book
Summary
1: Clinical Guidelines and Clinical Judgment
1.1. Adherence to Guidelines or Exercise of Judgment?
Variation in Guidelines
Case Study: Nodal Observation or Dissection in Treatment of Melanoma
1.2. Degrees of Personalized Medicine
Prediction of Cardiovascular Disease
The Breast Cancer Risk Assessment Tool
Predicting Unrealistically Precise Probabilities
1.3. Optimal Care Assuming Rational Expectations
Optimal Choice between Surveillance and Aggressive Treatment
1.4. Psychological Research Comparing Evidence-Based Prediction and Clinical Judgment
1.5. Second-Best Welfare Comparison of Adherence to Guidelines and Clinical Judgment
Surveillance or Aggressive Treatment of Women at Risk of Breast Cancer
2: Wishful Extrapolation from Research to Patient Care
2.1. From Study Populations to Patient Populations
Trials of Drug Treatments for Hypertension
Campbell and the Primacy of Internal Validity
2.2. From Experimental Treatments to Clinical Treatments
Intensity of Treatment
Blinding in Drug Trials
2.3. From Measured Outcomes to Patient Welfare
Interpreting Surrogate Outcomes
Assessing Multiple Outcomes
2.4. From Hypothesis Tests to Treatment Decisions
Using Hypothesis Tests to Compare Treatments
Using Hypothesis Tests to Choose When to Report Findings
2.5. Wishful Meta-Analysis of Disparate Studies
A Meta-Analysis of Outcomes of Bariatric Surgery
The Misleading Rhetoric of Meta-Analysis
The Algebraic Wisdom of Crowds
2.6. Sacrificing Relevance for Certitude
3: Credible Use of Evidence to Inform Patient Care
3.1. Identification of Treatment Response
Unobservability of Counterfactual Treatment Outcomes
Trial Data
Observational Data
Trials with Imperfect Compliance
Extrapolation Problems
Missing Data and Measurement Errors
3.2. Studying Identification
3.3. Identification with Missing Data on Patient Outcomes or Attributes
Missing Data in a Trial of Treatments for Hypertension
Missing Data on Family Size When Predicting Genetic Mutations
3.4. Partial Personalized Risk Assessment
Predicting Mean Remaining Life Span
3.5. Credible Inference with Observational Data
Bounds with No Knowledge of Counterfactual Outcomes
Sentencing and Recidivism
Assumptions Using Instrumental Variables
Case Study: Bounding the Mortality Effects of Swan-Ganz Catheterization
3.6. Identification of Response to Testing and Treatment
Optimal Testing and Treatment
Identification of Testing and Treatment Response with Observational Data
Measuring the Accuracy of Diagnostic Tests
3.7. Prediction Combining Multiple Studies
Combining Multiple Breast Cancer Risk Assessments
Combining Partial Predictions
4: Reasonable Care under Uncertainty
4.1. Qualitative Recognition of Uncertainty
4.2. Formalizing Uncertainty
States of Nature
4.3. Optimal and Reasonable Decisions
4.4. Reasonable Decision Criteria
Decisions with Rational Expectations
Maximization of Subjective Expected Utility
Decisions under Ambiguity: The Maximin and Minimax-Regret Criteria
4.5. Reasonable Choice between Surveillance and Aggressive Treatment
4.6. Uncertainty about Patient Welfare
5: Reasonable Care with Sample Data
5.1. Principles of Statistical Decision Theory
Some History, Post-Wald
5.2. Recent Work on Statistical Decision Theory for Treatment
Practical Appeal
Conceptual Appeal
5.3. Designing Trials to Enable Near-Optimal Treatment Choice
Using Power Calculations to Choose Sample Size
Sample Size Enabling Near-Optimal Treatment Choice
Choosing the Near-Optimality Threshold
Findings with Binary Outcomes, Two Treatments, and Balanced Designs
Implications for Practice
5.4. Reconsidering Sample Size in the MSLT-II Trial
6: A Population Health Perspective on Reasonable Care
6.1. Treatment Diversification
Treating X-Pox
6.2. Adaptive Diversification
Adaptive Treatment of a Life-Threatening Disease
6.3. The Practicality of Adaptive Diversification
Implementation in Centralized Health-Care Systems
Should Guidelines Encourage Treatment Variation under Uncertainty?
7: Managing Uncertainty in Drug Approval
7.1. The FDA Approval Process
7.2. Type I and II Errors in Drug Approval
7.3. Errors Due to Statistical Imprecision and Wishful Extrapolation
7.4. FDA Rejection of Formal Decision Analysis
7.5. Adaptive Partial Drug Approval
Adaptive Limited-Term Sales Licenses
Open Questions
Conclusion
Separating the Information and Recommendation Aspects of Guidelines
Educating Clinicians in Care under Uncertainty
Complement 1A. Overview of Research on Lymph Node Dissection
1A.1. Sentinel Lymph Node Biopsy
1A.2. Observation or SLN Biopsy
1A.3. Observation or Dissection after Positive SLN Biopsy
Complement 1B. Formalization of Optimal Choice between Surveillance and Aggressive Treatment
1B.1. Aggressive Treatment Prevents Disease
1B.2. Aggressive Treatment Reduces the Severity of Disease
Complement 2A. Odds Ratios and Health Risks
Complement 3A. The Ecological Inference Problem in Personalized Risk Assessment
Complement 3B. Bounds on Success Probabilities with No Knowledge of Counterfactual Outcomes
Complement 4A. Formalization of Reasonable Choice between Surveillance and Aggressive Treatment
Complement 5A. Treatment Choice as a Statistical Decision Problem
5A.1. Choice between a Status Quo Treatment and an Innovation When Outcomes Are Binary
Complement 6A. Minimax-Regret Allocation of Patients to Two Treatments
Complement 6B. Derivations for Criteria to Treat X-Pox
6B.1. Maximization of Subjective Expected Welfare
6B.2. Maximin
6B.3. Minimax Regret
References
Index

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