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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 FletcherPrinceton KokkuSavvas NikiforouBhavesh GoswamiTim IvanovskiyRebecca 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
Medical Expert Systems
• If-then rules:
– Mycin (1972), Puff (1977), Centaur (1977)
• Qualitative reasoning:
– Oncocin (1981), Eon (1995), OncoDoc (1998)
• Bayesian networks:
– Hepar (1990), AIDS2 (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
Example: Eligibility Criteria
• Female, older than 30
• No prior surgery
• Breast cancer, stage II or III
New System
• A programmer has to code the questions
• A nurse enters the questions
through a friendly interface
• Problem: Build the interface
Eligibility Criteria
• A logical expression that determines eligibility for a specific clinical trial
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: 45.50
Pain: 1
Mammography test
Yes/No M-Choice Numeric Deleting
Adding Modifying
Mammography test
45.5050.00
Modifying a Test
Test name:
Cost:
Pain: 1
Mammogram
Yes/No M-Choice Numeric Deleting
Adding Modifying
Cancer stage
Adding Multiple Choice Questions
• Text Options
Yes/No M-Choice Numeric
Adding Modifying
IIIIIIIV
Deleting
Adding Numeric Questions
Tumor size
• Text Min Max Prec
250 0
Yes/No M-Choice Numeric
Adding Modifying
Deleting
Deleting Questions
Patient’s age
Cancer stage
Breast cancer?
Tumor size
Yes/No M-Choice Numeric Deleting
Adding Modifying
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
001 Clinical trial A
Trial number Trial 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 IVCancer stage:
Age: From: To:0 15030
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
Experiments
Performance of seven novice users
• Entering tests and questions
• Entering eligibility criteria
0
20
40
60
80
100
0 1 2 3 4
number of a test set
time
per
ques
tion
(sec
)Entering Tests and Questions
Learning curve
Entering Eligibility Criteria
Learning curve
0
20
40
60
80
100
0 1 2 3 4 5 6 7 8 9 10 11
number of a clinical trial
time
per
ques
tion
(sec
)
Entering Eligibility Criteria
0
200
400
600
800
1000
1200
1400
1600
0 5 10 15 20 25 30 35
number of questions
entr
y tim
e (s
ec)
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