Cervical Cancer Clinical Trial
Official title:
A Pilot Study of a Low-Cost Optical Imaging Tool for Cervical Cancer Screening in Brazil
Verified date | October 2021 |
Source | M.D. Anderson Cancer Center |
Contact | n/a |
Is FDA regulated | No |
Health authority | |
Study type | Interventional |
Objectives: Primary Objective: To perform a pilot clinical study to test multi-modal optical imaging for detection of cervical neoplasia in Brazil. Secondary Objective: Analyze clinical data to establish the imaging modes which demonstrate the highest degree of correlation with disease state.
Status | Completed |
Enrollment | 300 |
Est. completion date | October 7, 2021 |
Est. primary completion date | October 7, 2021 |
Accepts healthy volunteers | Accepts Healthy Volunteers |
Gender | Female |
Age group | 18 Years and older |
Eligibility | Inclusion Criteria: 1. Patients undergoing colposcopy 2. 18 years of age or older 3. Negative pregnancy test 4. Subjects must be willing and able to provide informed consent Exclusion Criteria: 1. Patients under 18 years of age 2. Positive pregnancy test 3. Subjects unwilling and unable to provide informed consent |
Country | Name | City | State |
---|---|---|---|
Brazil | Barretos Cancer Hospital | Barretos |
Lead Sponsor | Collaborator |
---|---|
M.D. Anderson Cancer Center |
Brazil,
Type | Measure | Description | Time frame | Safety issue |
---|---|---|---|---|
Primary | Area Under the Receiver Operating Characteristic (ROC) Curve for Classifying Cervical Tissue into One of 2 Diagnostic Categories | Data used to develop an algorithm to maximize the area under the receiver operating characteristic (ROC) curve for classifying tissue into one of 2 diagnostic categories (high grade squamous intraepithelial lesions; normal or low grade squamous intraepithelial lesions). Descriptive statistics used to summarize the demographic and clinical characteristics of patients by diagnostic category. Descriptive statistics and boxplots used to summarize nuclear size and N/C by diagnostic category. Logistic regression methods used with the training set to model the logit of the probability of being classified as a high grade squamous intraepithelial lesion and to identify the parameters and threshold values which maximize the area under the ROC curve. | 1 day |
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