FOREWORD XVII
PREFACE XVIII
ABOUT THE COMPANION WEBSITE XX

1 Introduction: Medical Decisions 1
1.1 Introduction 1
1.2 Example of a Medical Decision 2
1.3 Uncertainty in Medical Decisions 9
1.4 Quantifying What the Possible Outcomes Mean to the Patient 13
1.5 Temporal Aspects of Decision Outcomes 22
1.6 Who Is the Decision-Maker? 25
1.7 Epilogue 30

2 Probabilistic Analysis: Quantifying Uncertainty 36
2.1 Introduction 36
2.2 Basic Principles – Probability as a Measure of Certainty 38
2.3 Bayes' Formula – An Example of How Probability Is Analyzed 44
2.4 Generalizing Probabilistic Analysis 64
2.5 Expected Value – Summarizing Random Variables 72
2.6 Epilogue 74

3 Decision Trees: Structuring Decision Problems 82
3.1 Introduction 82
3.2 Decision Tree Basics 82
3.3 Decision Tree Analysis 95
3.4 Leukemia Treatment Decision – A Complete, Detailed Medical Example 101
3.5 Epilogue 112

4 Sensitivity Analysis: Analyzing the Analysis 115
4.1 Introduction 115
4.2 Medical Example – Maintenance Therapy for Acute Myeloid Leukemia 115
4.3 Traditional Sensitivity Analysis 116
4.4 Stochastic Sensitivity Analysis 123
4.5 Epilogue 137

5 Determining Probabilities: Empirical and Subjective Methods 147
5.1 Introduction 147
5.2 Empirical Probabilities Based on Predictive Models 147
5.3 Subjective Methods 168
5.4 Epilogue 186

6 Survival Models: Representing the Uncertainty About the Length of Life 191
6.1 Introduction 191
6.2 Survival Model Basics 192
6.3 Constant Hazard Rate Survival Models 200
6.4 Actuarial Survival Models 204
6.5 Fitting Parametric Models to Observations 214
6.6 Epilogue 222

7 Utility Fundamentals: Risk Attitudes and Quantifying Preferences 225
7.1 Introduction 225
7.2 What Are Risk Attitudes? 226
7.3 Demonstration of Risk Attitudes in a Medical Context 227
7.4 Mathematical Foundations 237
7.5 General Observations About Outcome Utilities 243
7.6 More Mathematics 248
7.7 Determining Outcome Utilities – Underlying Concepts 254
7.8 Epilogue 260

8 Parametric Utility Models: Simplifying the Representation of Risk Attitudes 266
8.1 Introduction 266
8.2 First Example of a Parametric Model for Outcome Utilities 267
8.3 Other Parametric Utility Models 292
8.4 Incorporating Risk Attitudes into Clinical Policies 306
8.5 Epilogue 315

9 Multidimensional Utility Models: Adjusting for the Quality of Life 321
9.1 Introduction 321
9.2 Example – Why Does the Quality-of-Life Matters? 322
9.3 Quality-Lifetime Tradeoff Models 326
9.4 Quality-Survival Tradeoff Models 336
9.5 Utility Independence 343
9.6 What Does It All Mean? – Utility Assessment and an Extended Example 355
9.7 Epilogue 362

10 Markov Models: Representing the Dynamics of Uncertainty 366
10.1 Introduction 366
10.2 Markov Model Basics 367
10.3 Analysis of Markov Models – Direct Approach 377
10.4 Nonstationary Markov Models 393
10.5 Epilogue 402

11 Utility for Time-Varying Outcomes: Preferences for When Things Happen 411
11.1 Introduction 411
11.2 Motivating Example and Notation 411
11.3 Willingness-To-Pay Models 416
11.4 The Markovian Utility Model 419
11.5 Example 433
11.6 Generalizations 440
11.7 Epilogue 447

12 Decision Thresholds: Deciding When to Act 453
12.1 Introduction 453
12.2 Threshold Probability for Treatment 454
12.3 Test Threshold Probabilities for Binary Tests 467
12.4 Test Threshold Probabilities for More Complex Tests 480
12.5 Epilogue 483

13 Receiver Operating Characteristic Curves: Graphical Analysis of Diagnostic Performance 489
13.1 Introduction 489
13.2 Receiver Operating Characteristic Curve Analysis 491
13.3 Parameterized Cutoff Analysis 505
13.4 Decision Curve Analysis 510
13.5 Accounting for Nondiagnostic Effects 512
13.6 Epilogue 519

14 Influence Diagrams: Scalable Alternative to Decision Trees 526
14.1 Introduction 526
14.2 Influence Diagram Structure 527
14.3 Encoding Uncertainty in an Influence Diagram 530
14.4 Analyzing an Influence Diagram 532
14.5 Extending Influence Diagrams 537
14.6 Epilogue 543

15 Analyzing Screening Protocols: Predicting How Periodic Testing Affects Patient Outcomes 545
15.1 Introduction 545
15.2 Cervical Cancer 546
15.3 Representing the Natural History of Cervical Cancer 551
15.4 Screening Protocol Analysis 561
15.5 Epilogue 584

16 Monetary Costs: The Elephant in the Exam Room 589
16.1 Introduction 589
16.2 Cost-Effectiveness and Cost–Benefit Analysis 590
16.3 Shared Resource Analysis 606
16.4 Epilogue 631
Exercises 634

17 Prospect Theory: A Possible Paradigm Shift for Decision Analysis 636
17.1 Introduction 636
17.2 Examples of How Decisions Are Made 636
17.3 Prospect Theory 646
17.4 Framing Decision Problems 654
17.5 Cumulative Prospect Theory 657
17.6 Assessment of Weighting Functions in a Medical Context 666
17.7 Epilogue 669

INDEX 671