Selection of Clinical Trials: Knowledge Representation and Acquisition Committee: Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Savvas Nikiforou

Automated Matching of Patients to Clinical Trials Faculty: Lawrence O. Hall Dmitry B. Goldgof Eugene Fink Part of the project: Students: Lynn Fletcher Princeton Kokku Savvas Nikiforou Bhavesh Goswami Tim Ivanovskiy Rebecca Smith

Expert System The system analyzes a patient’s data and determines whether the patient is eligible for Moffitt clinical trials.

Expert System Guides a clinician through related questions Identifies appropriate medical tests Selects matching clinical trials Minimizes pain and cost of selection process

Outline Previous work Eligibility decisions Knowledge base Knowledge entry Experiments

Previous Work Medical expert systems Knowledge acquisition Medical systems at USF

Medical Expert Systems If-then rules: –Mycin (1972), Puff (1977), Centaur (1977) Qualitative reasoning: –Oncocin (1981), Eon (1995), OncoDoc (1998) Bayesian networks: –Hepar (1990), AIDS 2 (1990)

Knowledge Acquisition Teiresias (1974): Knowledge for Mycin Salt (1985): Elevator-design rules Opal (1987): Knowledge for Oncocin Protégé (1987, 2000): General-purpose tools for developing knowledge acquisition interfaces

Medical Systems at USF Selection of clinical trials for cancer patients Bayesian networks (Theocharous) Qualitative reasoning (Fletcher and Hall) No knowledge acquisition tools

Outline Previous work Eligibility decisions Knowledge base Knowledge entry Experiments

Example: Eligibility Criteria Female, older than 30 No prior surgery Breast cancer, stage II or III

Example: Questions Sex: Age: Female Male 25

Example: Conclusion Patient is not eligible

Example: Questions Sex: Age: 35 Female Male

Example: Questions Cancer stage: Prior surgery? Yes No Unknown I II III IV

Example: Conclusion Patient is eligible

Full Functionality Orders and groups the questions Considers multiple clinical trials

Old System A programmer has to code the questions

New System A programmer has to code the questions A nurse enters the questions through a friendly interface Problem: Build the interface

Outline Previous work Eligibility decisions Knowledge base Knowledge entry Experiments

Main Objects Questions Medical tests Eligibility criteria

Types of Questions Yes / No / Unknown Multiple choice Numeric

Examples of Questions Prior surgery? Yes No Unknown Cancer stage: I II III IV Age:

Tests A medical test answers several questions. It involves certain pain and cost.

Example Test: Name and Cost Test name: Cost:50.00 Pain:1 Mammogram

Example Test: Questions Yes / No Question: Breast cancer?

Example Test: Questions Multiple choice Question: Cancer stage I II III IV Options:

Example Test: Questions Numeric Question: Tumor size MinMaxPrec

Eligibility Criteria A logical expression that determines eligibility for a specific clinical trial

Example: Criteria AND Age > 30 Prior-surgery = NO OR Cancer-stage = II Cancer-stage = III

Outline Previous work Eligibility decisions Knowledge base Knowledge entry Experiments

Tests and Questions Adding tests Modifying a test Adding yes/no questions Adding multiple choice questions Adding numeric questions Deleting questions

Adding Tests Test name: Cost: Pain:1 Mammography test Yes/NoM-ChoiceNumericDeleting Adding Modifying

Mammography test Modifying a Test Test name: Cost: Pain:1 Mammogram Yes/NoM-ChoiceNumericDeleting Adding Modifying

Adding Yes/No Questions Breast cancer? Text Yes/NoM-ChoiceNumeric Adding Modifying Deleting

Cancer stage Adding Multiple Choice Questions TextOptions Yes/NoM-ChoiceNumeric Adding Modifying I II III IV Deleting

Adding Numeric Questions Tumor size TextMinMaxPrec 2500 Yes/NoM-ChoiceNumeric Adding Modifying Deleting

Deleting Questions Patient’s age Cancer stage Breast cancer? Tumor size Yes/NoM-ChoiceNumericDeleting Adding Modifying

Cancer stage Tumor size Yes/NoM-ChoiceNumericDelete Adding Modifying Deleting Questions

Demo

Eligibility Criteria Adding eligibility criteria Selecting tests Deleting expressions Editing questions Defining an expression Selecting questions

Example: Eligibility Criteria Female, older than 30 Breast cancer, stage II Post-menopausal or surgically sterilized

Adding Eligibility Criteria Adding criteria Selecting tests 001Clinical trial A Trial numberTrial name Deleting expressions Editing questions Defining an expression Selecting questions

Selecting Tests General questions Blood test Mammogram Biopsy Urine test Adding criteria Selecting tests Deleting expressions Editing questions Defining an expression Selecting questions

Selecting Questions I II III IV Cancer stage: Age:From:To: Post-menopausal? UnknownNoYes Surgically sterilized? UnknownNoYes Adding criteria Selecting tests Deleting expressions Editing questions Defining an expression Selecting questions Prior surgery? UnknownNoYes

Defining an Expression Cancer-stage = II Surgically-sterilized = YES Post-menopausal = YES Age > 30 Adding criteria Selecting tests Deleting expressions Editing questions Defining an expression Selecting questions

Defining an Expression AND Adding criteria Selecting tests Deleting expressions Editing questions Defining an expression Selecting questions Cancer-stage = II Surgically-sterilized = YES Post-menopausal = YES Age > 30

Defining an Expression Adding criteria Selecting tests Deleting expressions Editing questions Defining an expression Selecting questions Surgically-sterilized = YES Post-menopausal = YES AND Age > 30 Cancer-stage = II

Defining an Expression Adding criteria Selecting tests Deleting expressions Editing questions Defining an expression Selecting questions Surgically-sterilized = YES AND Age > 30 OR Post-menopausal = YES Cancer-stage = II

Defining an Expression Adding criteria Selecting tests Deleting expressions Editing questions Defining an expression Selecting questions AND Age > 30 OR Post-menopausal = YES Cancer-stage = II Surgically-sterilized = YES

Demo

Outline Previous work Eligibility decisions Knowledge base Knowledge entry Experiments

Performance of seven novice users Entering tests and questions Entering eligibility criteria

Entering Tests and Questions Learning curve

Entering Eligibility Criteria Learning curve

Entering Eligibility Criteria

Summary Learning time: 1 hour Adding a test: 2 to 10 minutes Building a knowledge base for Moffitt breast-cancer trials: 8 to 10 hours Adding eligibility criteria: 30 to 60 minutes

Main Results Formal model of selection criteria Representation of related knowledge Friendly interface for knowledge entry

Future Work Probabilities of different answers Logical connections among questions Detection of identical and related questions