Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof...
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Transcript of Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof...
![Page 1: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/1.jpg)
Automated Selection of Patients for Clinical Trials
Eugene FinkLawrence O. Hall
Dmitry B. GoldgofBhavesh D. Goswami
Matthew BoonstraJeffrey P. Krischer
![Page 2: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/2.jpg)
A clinical trial is an evaluationof a new treatment procedure.
Clinical trials
When physicians conduct a trial, theyrecruit patients with matching healthproblems and medical histories.
![Page 3: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/3.jpg)
Selection of patients
The selection of trial participants isa manual procedure, and physiciansmay 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
![Page 4: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/4.jpg)
Expert system
We have developed a system thatautomatically selects prospectivetrial participants.
![Page 5: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/5.jpg)
Outline
• Knowledge base
• Selection results
• Cost reduction
![Page 6: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/6.jpg)
Knowledge base
• Tests and questions
• Eligibility criteria
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Tests and questions
ExampleMammogram, $150What is the cancer stage?Does the patient have invasive cancer?Biopsy, $400How many lymph nodes have tumor cells?What is the greatest tumor diameter?
The knowledge base includes a list of medical tests. A test descriptionincludes a dollar cost and relatedquestions about a patient’s health.
![Page 8: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/8.jpg)
Eligibility criteriaThe knowledge base also includeslogical expressions that representeligibility for the available trials.
AND
cancer-stage {II, III}
OR invasive-cancer = NO
lymph-nodes 3
tumor-diameter 2.5
Example
![Page 9: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/9.jpg)
Selection process
The system collects data until it candetermine whether the eligibilityexpressions are TRUE or FALSE.
If patient records do not provideenough data, the system identifiesthe required medical tests.
![Page 10: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/10.jpg)
Outline
• Knowledge base
• Selection results
• Cost reduction
![Page 11: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/11.jpg)
Experiments
We have used fifteen breast-cancertrials at the Moffitt Cancer Center.
• Past data from 187 patients
• Current data from 169 patients
![Page 12: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/12.jpg)
Finding eligible patients Past data for 187 patients
ClinicalTrial
Parti-cipants
OtherEligible
10822108401107211378119921210012101
10 .
0 .
48 .
4 .
5 .
8 .
20 .
5 .
19 .
26 .
19 .
6 .
20 .
30 .
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Finding eligible patients Current data for 169 patients
ClinicalTrial
Parti-cipants
OtherEligible
11132119311197112100121011238512601126431275712775
4 .
2 .
4 .
0 .
11 .
0 .
0 .
16 .
1 .
23 .
1 .
26 .
0 .
5 .
52 .
19 .
1 .
36 .
3 .
17 .
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Participation in other trials Current data for 169 patients
ClinicalTrial
Incom-patible
Compa-tilbe
No OtherTrial
11132119311197112100121011238512601126431275712775
0 .
0 .
0 .
0 .
13 .
8 .
0 .
0 .
0 .
3 .
1 .
11 .
0 .
1 .
6 .
2 .
0 .
10 .
1 .
3 .
0 .
15 .
0 .
4 .
33 .
9 .
1 .
26 .
2 .
11 .
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Summary
The results suggest that the systemcan increase the number of trialparticipants by a factor of three.
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Outline
• Knowledge base
• Selection results
• Cost reduction
![Page 17: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/17.jpg)
Medical tests
The selection of trial participantsmay require medical tests.
• The total cost of tests may depend on their ordering
• Finding the right ordering is often a complex problem
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Ordering of tests
The system chooses the ordering of teststhat 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, itrevises the ordering of the remaining tests.
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Cost reduction Past data for 187 patients
ClinicalTrial
Mean CostW/O Test
ReorderingWith Test
Reordering
10822
11072
11378
$70 .
$209 .
$35 .
$11 .
$60 .
$19 .
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Cost reduction Past data for 187 patients
$0
$250
$200
$150
$100
$50
10822 1137811072
W/O ReorderingWith Reordering
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Cost reduction Current data for 169 patients
ClinicalTrial
Mean CostW/O Test
ReorderingWith Test
Reordering
11971
12601
12757
$192 .
$36 .
$107 .
$192 .
$3 .
$107 .
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Cost reduction Current data for 169 patients
$0
$250
$200
$150
$100
$50
11971 1275712601
W/O ReorderingWith Reordering
![Page 23: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/23.jpg)
Conclusions
We have developed a system thatselects prospective trial participants.
• Helps physicians to identify eligible patients
• Can increase the number of trial participants
• Can reduce the cost of the selection process
![Page 24: Automated Selection of Patients for Clinical Trials Eugene Fink Lawrence O. Hall Dmitry B. Goldgof Bhavesh D. Goswami Matthew Boonstra Jeffrey P. Krischer.](https://reader036.fdocuments.us/reader036/viewer/2022062807/5697c01b1a28abf838ccf904/html5/thumbnails/24.jpg)
Future work
• Deploy the system at the Moffitt Cancer Center
• Evaluate the satisfaction of physicians and nurses
• Add probabilistic reasoning