knowledge acquisition for clinical-trial selection savvas nikiforou eugene fink lawrence o. hall...

Knowledge Acquisition for Clinical-Trial Selection

Savvas Nikiforou

Eugene Fink

Lawrence O. Hall

Dmitry B. Goldgof

Jeffrey P. Krischer

Expert System

The system analyzes a patient’s data and

determines whether the patient is eligible

for clinical trials at the H. Lee Moffitt

Cancer Center.

Expert System

• Guides a clinician through related questions

• Identifies appropriate medical tests

• Selects matching clinical trials

• Minimizes pain and cost of selection process

Outline

• 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

I

II

III

IV

Example: Conclusion

Patient is eligible

Full Functionality

• Orders and groups the questions

• Considers multiple clinical trials

Outline

• Eligibility decisions

• Knowledge base

• Knowledge entry

• Experiments

Main Objects

• Questions

• Medical tests

• Eligibility criteria

Types of Questions

• Yes / No

• Multiple choice

• Numeric

Tests

A medical test answers several questions.

It involves certain pain and cost.

Eligibility Criteria

• A logical expression that determines eligibility for a specific clinical trial

Example: CriteriaAND

Age > 30

Prior-surgery = NO

OR

Cancer-stage = II

Cancer-stage = III

Outline

• 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:

Yes/No M-Choice Numeric Deleting

Adding Modifying

45.50

1

Mammogram

Adding Yes/No Questions

Breast cancer?

• Text

Yes/No M-Choice Numeric

Adding Modifying

Deleting

Adding Multiple Choice Questions

• Text Options

Yes/No M-Choice Numeric

Adding Modifying

Cancer stage IIIIIIIV

Deleting

Adding Numeric Questions

• Text Min Max

Tumor size 250

Yes/No M-Choice Numeric

Adding Modifying

Deleting

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? Yes

Surgically sterilized? Yes

Adding criteria

Selecting tests

Deleting expressions

Editing questions

Defining an expression

Selecting questions

Prior surgery?

No

No

NoYes

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

Outline

• Eligibility decisions

• Knowledge base

• Knowledge entry

• Experiments

Experiments

Performance of sixteen 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

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

Learning curve

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