1. Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer

2. A clinical trial is an evaluation of a new treatment procedure. Clinical trials When physicians conduct a trial, they recruit patients with matching health problems and medical histories.

3. Selection of patients The selection of trial participants is a manual procedure, and physicians may miss eligible patients. Gotay [1991] demonstrated that physicians choose only 39% of the eligible patients Fallowfield et al. [1997] showed that they choose less than 50% of the eligible patients

4. Expert system We have developed a system that automatically selects prospective trial participants.

5. Outline Knowledge base Selection results Cost reduction

6. Knowledge base Tests and questions Eligibility criteria

7. Tests and questions Example Mammogram, $150 What is the cancer stage? Does the patient have invasive cancer? Biopsy, $400 How many lymph nodes have tumor cells? What is the greatest tumor diameter? The knowledge base includes a list of medical tests. A test description includes a dollar cost and related questions about a patient’s health.

8. Eligibility criteria The knowledge base also includes logical expressions that represent eligibility for the available trials. AND cancer-stage  {II, III} OR invasive-cancer = NO lymph-nodes  3 tumor-diameter  2.5 Example

9. Selection process The system collects data until it can determine whether the eligibility expressions are TRUE or FALSE. If patient records do not provide enough data, the system identifies the required medical tests.

10. Outline Knowledge base Selection results Cost reduction

11. Experiments We have used fifteen breast-cancer trials at the Moffitt Cancer Center. Past data from 187 patients Current data from 169 patients

12. Finding eligible patients Past data for 187 patients Clinical Trial Parti- cipants Other Eligible 10822 10840 11072 11378 11992 12100 12101 10. 0. 48. 4. 5. 8. 20. 5. 19. 26. 19. 6. 20. 30.

13. Finding eligible patients Current data for 169 patients Clinical Trial Parti- cipants Other Eligible 11132 11931 11971 12100 12101 12385 12601 12643 12757 12775 4. 2. 4. 0. 11. 0. 0. 16. 1. 23. 1. 26. 0. 5. 52. 19. 1. 36. 3. 17.

14. Participation in other trials Current data for 169 patients Clinical Trial Incom- patible Compa- tilbe No Other Trial 11132 11931 11971 12100 12101 12385 12601 12643 12757 12775 0. 0. 13. 8. 0. 3. 1. 11. 0. 1. 6. 2. 0. 10. 1. 3. 0. 15. 0. 4. 33. 9. 1. 26. 2. 11.

15. Summary The results suggest that the system can increase the number of trial participants by a factor of three.

16. Outline Knowledge base Selection results Cost reduction

17. Medical tests The selection of trial participants may require medical tests. The total cost of tests may depend on their ordering Finding the right ordering is often a complex problem

18. Ordering of tests The system chooses the ordering of tests that reduces their expected total cost. The ordering is based on the test costs, number of trials that require each test, and structure of eligibility expressions. After getting the results of the first test, it revises the ordering of the remaining tests.

19. Cost reduction Past data for 187 patients Clinical Trial Mean Cost W/O Test Reordering With Test Reordering 10822 11072 11378 $70. $209. $35. $11. $60. $19.

20. Cost reduction Past data for 187 patients $0 $250 $200 $150 $100 $50 10822 1137811072 W/O Reordering With Reordering

21. Cost reduction Current data for 169 patients Clinical Trial Mean Cost W/O Test Reordering With Test Reordering 11971 12601 12757 $192. $36. $107. $192. $3. $107.

22. Cost reduction Current data for 169 patients $0 $250 $200 $150 $100 $50 11971 1275712601 W/O Reordering With Reordering

23. Conclusions We have developed a system that selects prospective trial participants. Helps physicians to identify eligible patients Can increase the number of trial participants Can reduce the cost of the selection process

24. Future work Deploy the system at the Moffitt Cancer Center Evaluate the satisfaction of physicians and nurses Add probabilistic reasoning