Trial Outcomes & Findings for Expanded Development of a Medical Device Utilizing an EEG-Based Algorithm for the Objective Quantification of Pain (NCT NCT04585451)
NCT ID: NCT04585451
Last Updated: 2023-05-06
Results Overview
This measure is the performance of the classification of pain vs no pain compared to the patient self-report in the form of Numerical Rating Scale (NRS). The primary outcome measure is Area Under the Curve (AUC), derived from the Receiver Operating Characteristic (ROC) curve, a standard metric of performance for binary classifiers. AUC is a numeric quantity ranging from 0 to 1, where the value of 1 indicates perfect separation, while 0.5 represents zero separation. AUC represents a fundamental expression of classifier separation performance without the complexity of threshold selection. (NRS 0 vs 1-10)
COMPLETED
334 participants
Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.
2023-05-06
Participant Flow
Participant milestones
| Measure |
Chronic Pain Patients
ALGOS System: A Quantitative Electroencephalography (QEEG) based pain biomarker assessment that scales with patient reported Numeric Rating Scale (NRS)
|
Healthy Controls
ALGOS System: A Quantitative Electroencephalography (QEEG) based pain biomarker assessment that scales with patient reported Numeric Rating Scale (NRS)
|
|---|---|---|
|
Overall Study
STARTED
|
280
|
54
|
|
Overall Study
COMPLETED
|
254
|
54
|
|
Overall Study
NOT COMPLETED
|
26
|
0
|
Reasons for withdrawal
| Measure |
Chronic Pain Patients
ALGOS System: A Quantitative Electroencephalography (QEEG) based pain biomarker assessment that scales with patient reported Numeric Rating Scale (NRS)
|
Healthy Controls
ALGOS System: A Quantitative Electroencephalography (QEEG) based pain biomarker assessment that scales with patient reported Numeric Rating Scale (NRS)
|
|---|---|---|
|
Overall Study
Withdrawal by Subject
|
26
|
0
|
Baseline Characteristics
Expanded Development of a Medical Device Utilizing an EEG-Based Algorithm for the Objective Quantification of Pain
Baseline characteristics by cohort
| Measure |
Chronic Pain Patients
n=280 Participants
Chronic pain patients who meet the IASP definition of chronic pain for a musculoskeletal pain disorder.
|
Healthy Controls
n=54 Participants
Healthy control participants with no diagnosis of chronic pain nor other various neurological conditions
|
Total
n=334 Participants
Total of all reporting groups
|
|---|---|---|---|
|
Age, Categorical
<=18 years
|
0 Participants
n=5 Participants
|
0 Participants
n=7 Participants
|
0 Participants
n=5 Participants
|
|
Age, Categorical
Between 18 and 65 years
|
179 Participants
n=5 Participants
|
51 Participants
n=7 Participants
|
230 Participants
n=5 Participants
|
|
Age, Categorical
>=65 years
|
101 Participants
n=5 Participants
|
3 Participants
n=7 Participants
|
104 Participants
n=5 Participants
|
|
Sex: Female, Male
Female
|
145 Participants
n=5 Participants
|
34 Participants
n=7 Participants
|
179 Participants
n=5 Participants
|
|
Sex: Female, Male
Male
|
135 Participants
n=5 Participants
|
20 Participants
n=7 Participants
|
155 Participants
n=5 Participants
|
|
Race (NIH/OMB)
American Indian or Alaska Native
|
2 Participants
n=5 Participants
|
0 Participants
n=7 Participants
|
2 Participants
n=5 Participants
|
|
Race (NIH/OMB)
Asian
|
10 Participants
n=5 Participants
|
15 Participants
n=7 Participants
|
25 Participants
n=5 Participants
|
|
Race (NIH/OMB)
Native Hawaiian or Other Pacific Islander
|
0 Participants
n=5 Participants
|
0 Participants
n=7 Participants
|
0 Participants
n=5 Participants
|
|
Race (NIH/OMB)
Black or African American
|
80 Participants
n=5 Participants
|
11 Participants
n=7 Participants
|
91 Participants
n=5 Participants
|
|
Race (NIH/OMB)
White
|
123 Participants
n=5 Participants
|
26 Participants
n=7 Participants
|
149 Participants
n=5 Participants
|
|
Race (NIH/OMB)
More than one race
|
0 Participants
n=5 Participants
|
0 Participants
n=7 Participants
|
0 Participants
n=5 Participants
|
|
Race (NIH/OMB)
Unknown or Not Reported
|
65 Participants
n=5 Participants
|
2 Participants
n=7 Participants
|
67 Participants
n=5 Participants
|
|
Region of Enrollment
United States
|
280 participants
n=5 Participants
|
54 participants
n=7 Participants
|
334 participants
n=5 Participants
|
PRIMARY outcome
Timeframe: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.Population: Analysis was carried out using both arms combined: a control arm (negative class), and a pain arm (positive class). The reason for combining both arms is to assess the classifier's ability to differentiate the two classes and all outcome measures represent the performance of classification.
This measure is the performance of the classification of pain vs no pain compared to the patient self-report in the form of Numerical Rating Scale (NRS). The primary outcome measure is Area Under the Curve (AUC), derived from the Receiver Operating Characteristic (ROC) curve, a standard metric of performance for binary classifiers. AUC is a numeric quantity ranging from 0 to 1, where the value of 1 indicates perfect separation, while 0.5 represents zero separation. AUC represents a fundamental expression of classifier separation performance without the complexity of threshold selection. (NRS 0 vs 1-10)
Outcome measures
| Measure |
Study Participants
n=308 Participants
All participants in study, chronic pain patients and controls
|
|---|---|
|
Area Under the Curve of Classification Versus Patient Self Report of Pain vs no Pain State
|
.70 probability
|
PRIMARY outcome
Timeframe: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.Population: Analysis was carried out using both arms combined: a control arm (negative class), and a pain arm (positive class). The reason for combining both arms is to assess the classifier's ability to differentiate the two classes and all outcome measures represent the performance of classification.
Sensitivity, or true positive rate is the probability of a positive result in the true chronic pain patients. This measure is calculated by dividing true positives by the summation of true positives and false negatives. (NRS 0 vs 1-10)
Outcome measures
| Measure |
Study Participants
n=308 Participants
All participants in study, chronic pain patients and controls
|
|---|---|
|
Sensitivity of Classification Versus Patient Self Report of Pain vs no Pain State
|
.783 probability
|
PRIMARY outcome
Timeframe: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.Population: Analysis was carried out using both arms combined: a control arm (negative class), and a pain arm (positive class). The reason for combining both arms is to assess the classifier's ability to differentiate the two classes and all outcome measures represent the performance of classification.
Specificity, or true negative rate is the probability of a negative result in the true healthy control patients. This measure is calculated by dividing true negatives by the summation of true negatives and false positives. (NRS 0 vs 1-10)
Outcome measures
| Measure |
Study Participants
n=308 Participants
All participants in study, chronic pain patients and controls
|
|---|---|
|
Specificity of Classification Versus Patient Self Report of Pain vs no Pain State
|
.607 probability
|
SECONDARY outcome
Timeframe: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.Population: Analysis was carried out using both arms combined: No/Mild vs Moderate/Severe pain. The reason for combining both arms is to assess the classifier's ability to differentiate the two classes and all outcome measures represent the performance of classification.
This measure is the performance of the classification of No/Mild vs Moderate/Severe pain compared to the patient self-report in the form of Numerical Rating Scale (NRS). The outcome measure is Area Under the Curve (AUC), derived from the Receiver Operating Characteristic (ROC) curve, a standard metric of performance for binary classifiers. AUC is a numeric quantity ranging from 0 to 1, where the value of 1 indicates perfect separation (the classifier is correct on every subject), while 0.5 represents zero separation (no better than guessing). AUC represents a fundamental expression of classifier separation performance without the complexity of threshold selection. (NRS 0-3.5 vs 4-10)
Outcome measures
| Measure |
Study Participants
n=308 Participants
All participants in study, chronic pain patients and controls
|
|---|---|
|
Area Under the Curve of Classification Versus Patient Self Report of no/Mild Pain vs Moderate/Severe Pain State
|
.694 probability
|
SECONDARY outcome
Timeframe: Self-reported pain using average of NRS value at the start and end of EEG collection, and classification based on 15 minutes of EEG collection.Population: Analysis was carried out using both arms combined: No/Mild/Moderate vs Severe pain. The reason for combining both arms is to assess the classifier's ability to differentiate the two classes and all outcome measures represent the performance of classification.
This measure is the performance of the classification of No/Mild/Moderate vs Severe pain compared to the patient self-report in the form of Numerical Rating Scale (NRS). The outcome measure is Area Under the Curve (AUC), derived from the Receiver Operating Characteristic (ROC) curve, a standard metric of performance for binary classifiers. AUC is a numeric quantity ranging from 0 to 1, where the value of 1 indicates perfect separation (the classifier is correct on every subject), while 0.5 represents zero separation (no better than guessing). AUC represents a fundamental expression of classifier separation performance without the complexity of threshold selection. (NRS 0-6.5 vs 7-10)
Outcome measures
| Measure |
Study Participants
n=308 Participants
All participants in study, chronic pain patients and controls
|
|---|---|
|
Area Under the Curve of Classification Versus Patient Self Report of no, Mild, or Moderate Pain vs Severe Pain State
|
.669 probability
|
Adverse Events
Chronic Pain Patients
Healthy Controls
Serious adverse events
Adverse event data not reported
Other adverse events
Adverse event data not reported
Additional Information
Results disclosure agreements
- Principal investigator is a sponsor employee
- Publication restrictions are in place