An interventional study of Logistic regression risk model in Colorectal Cancer, Colorectal Polyp and Colorectal Adenoma, sponsored by Kaiser Permanente. Withdrawn at 1 site in United States. Open to participants aged 18 Years to 85 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2023-02-28.
Sponsored by Kaiser Permanente · Not applicable, Interventional, and Health services research
This originated as an observational study of Kaiser Permanente Northern California (KPNC) patients with a history of adenoma diagnosed by colonoscopy who received a subsequent surveillance colonoscopy between 2014 and 2019. The original goal of the study was to develop a risk prediction model that would help identify patients at highest risk for a diagnosis of advanced neoplasia (colorectal cancer and/or advanced adenoma) at or within 6 months following their surveillance colonoscopy. Candidate predictors of interest included patient demographics, medical history, and details related to the index colonoscopy. The investigators are now at the implementation stage and applying the risk prediction model to patients awaiting surveillance colonoscopy at select KPNC service areas to help identify those at highest risk for colorectal cancer based on their risk scores.
In the implementation stage, the risk prediction model is being applied to patients who are awaiting surveillance colonoscopy at select KPNC service areas to help identify those at highest risk for colorectal cancer based on their risk scores. The prediction model is being used in 2-3 service area to identify about 60-80 patients per month who are at highest risk for colorectal cancer based on their risk scores. Risk scores represent one of a number of factors being considered for prioritizing patients for colonoscopy.
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Inclusion Criteria:
Patients are on the current colonoscopy pending list; excluding those who were fecal immunochemical test-positive, screening colonoscopies, had a colonoscopy in last 12 months or on a voluntary "pause" list
The prediction model is being used to identify patients who are at highest risk for colorectal cancer based on their risk scores.
Device: Logistic regression risk model
Logistic regression model to assign risk score, plus time overdue and PROMPT risk category
Rates of colorectal neoplasia per number of colonoscopies performed
The investigators anticipate observing changed rates of colorectal neoplasia per number of colonoscopies performed on account of prioritizing higher risk patients.
Time frame: 1 year
This study is withdrawn, as verified in Feb 2023. You cannot join it, but the record below documents what was studied.
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