Coding of Selection Criteria for Cancer Treatment Plans

Savvas Nikiforou

Automated Matching of Patients to Clinical Trials

Part of the project:

Research Group

• Faculty– Lawrence Hall

– Dmitry Goldgof

– Eugene Fink

• Students– Lynn Fletcher

– Princeton Kokku

– Savvas Nikiforou

– Rochelle Harris

Motivation

• Selecting among treatment plans

• Minimizing pain and cost of the selection process

• Reducing the physician’s effort

Expert System

• Guides the nurse through related questions

• Identifies the appropriate medical tests

Outline of the Talk

• Eligibility decisions

• Knowledge base

• Input of the knowledge

• Demonstration

Related Work

• Initial expert systemFletcher, Hall and Goldgof, 1999

• Minimizing pain and costKokku, Hall and Goldgof, 2001

Example: Selection Criteria

• Female, not older than 50

• Breast cancer, stage II

• No prior surgery

Example: Questions

Sex:

Age:

Female

Male

35

Example: Conclusion

Patient is not eligible

Example: Questions

Sex:

Age:

Female

Male

35

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 treatment plans

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 of the Talk

• Eligibility decisions

• Knowledge base

• Input of the knowledge

• Demonstration

Main Objects

• Questions

• Tests

• Eligibility criteria

Types of Questions

• Yes / No / Unknown

• Multiple choice

• Numeric

Examples of Questions

Prior surgery? Yes No Unknown

Examples of Questions

Prior surgery? Yes No Unknown

Cancer stage: I

II

III

IV

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: 42.23

Pain: 1

Blood test

Example Test: Questions

• Yes / No

Question:

Histologically proven breast cancer?

Example Test: Questions

• Multiple choice

Question: Options:

Patient’s clinical state T-1T-2T-3

Example Test: Questions

• Numeric

Question: White cell blood count 0 500000 0

Min Max Prec

Eligibility Criteria

• A logical expression that determines eligibility for a specific treatment

Example: CriteriaAND

White Blood Count >100,000

No Heart Related Problems

OR

Cancer Stage I

Cancer Stage II

Outline of the Talk

• Eligibility decisions

• Knowledge base

• Input of the knowledge

• Demonstration

Input

• Questions

• Tests

• Eligibility criteria

Input: Test

• Name:

• Cost:

• Pain:

Type test name here

$$$$.$$

0-5

Input: Question Format

• Text

• Type

Yes / No Multiple Choice Numeric

Input: Yes / No Question

Yes / No

Is patient’s age less than 64?

• Text

• Type

Input: Multiple Choice Question

Multiple Choice

Patient’s age

• Text

• Type

Options

< 20

20 to 40

41 to 60

> 60

Input: Numeric Question

Numeric

Patient’s age

• Text

• Type

Min Max Prec.

1200 0

Yes No

Input: Eligibility

• Logical structure AND

OR

• Questions

SexFemaleMale

Age

Tumors?

Lesions?

Yes No• Eligibility answers

40 65From To

Outline of the Talk

• Eligibility decisions

• Knowledge base

• Input of the knowledge

• Demonstration

Current System

Online Demo

Main results

• Formal model of selection criteria and related optimization problems

• Friendly input interface

• Visual representation of these criteria

Coming soon

• Completion of the interface

• Converting the input knowledge into internal logical structures