# Optimizing long-term post-polypectomy surveillance for colorectal cancer prevention using a prediction rule developed from a large, community-based cohort

> **NIH NIH K07** · KAISER FOUNDATION RESEARCH INSTITUTE · 2020 · $171,720

## Abstract

PROJECT SUMMARY AND ABSTRACT
The purpose of this K07 proposal is to provide Jeffrey Lee, MD, MAS with the protected time and resources to
pursue the additional training needed to reach his long-term goal of becoming an independent clinical
investigator, focused on colorectal cancer (CRC) prevention. Screening has been shown to reduce the
incidence and mortality for CRC. However, screening has resulted in a growing cohort of patients with
adenomatous polyps (adenomas) and little is known about effectively managing their post-polypectomy
surveillance. With limited data available in the literature to determine the appropriate timing and frequency of
follow-up colonoscopy for patients after adenoma removal, recommendations for post-polypectomy
surveillance from our national guidelines have been imprecise at best. For example, the currently
recommended range of 5-10 years for a surveillance colonoscopy for patients with a single adenoma covers a
two-fold difference in exam frequency, with resultant two-fold impact on patient risk, cost, and colonoscopy
capacity. To help optimize the timing of colonoscopic surveillance and guide appropriate utilization of this
invasive and costly resource, stratification of CRC risk after colonoscopic polypectomy from a large
community-based cohort with long-term follow-up is needed. Building on his prior work in CRC screening, Dr.
Lee seeks to fill this knowledge gap by optimizing surveillance practices in post-polypectomy patients
according to patient-, polyp-, and colonoscopy exam-related factors. Specifically, he will determine the long-
term CRC risk in patients after colonoscopic polypectomy in a very large “real world” community-based
population (Aim 1). He will also identify patient-, polyp-, and exam-related risk factors associated with incident
CRC in these patients (Aim 2). Finally, he will develop a CRC risk prediction model that will identify post-
polypectomy patients at high and low risk for developing subsequent CRC (Aim 3). To achieve these goals, Dr.
Lee and his mentors have designed a career development plan for research and educational training to obtain:
1) knowledge and expertise in advanced epidemiologic methods for design and analysis of cohort studies; 2)
knowledge in medical informatics methods; and 3) predictive modeling skills. To achieve the proposed
research aims, Dr. Lee will leverage the rich electronic health records of Kaiser Permanente Northern
California, a large community-based healthcare system, in which data on patient, physician, colonoscopy,
pathology, and CRC status have been collected since 1994. In addition, Dr. Lee will use an established natural
language processing tool to efficiently collect data and evaluate potential confounding variables from more
than 600,000 colonoscopy reports in order to address one of the main practical challenges that have limited
the feasibility of large-scale population-based studies. Thus, completion of these aims has the potential to
improve p...

## Key facts

- **NIH application ID:** 9986702
- **Project number:** 5K07CA212057-06
- **Recipient organization:** KAISER FOUNDATION RESEARCH INSTITUTE
- **Principal Investigator:** Jeffrey Kuang Zou Lee
- **Activity code:** K07 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $171,720
- **Award type:** 5
- **Project period:** 2016-09-14 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9986702

## Citation

> US National Institutes of Health, RePORTER application 9986702, Optimizing long-term post-polypectomy surveillance for colorectal cancer prevention using a prediction rule developed from a large, community-based cohort (5K07CA212057-06). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9986702. Licensed CC0.

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