Stuart Baker

Sc.D

National Cancer Institute

Mathematical Statistician

NLST (Learn more about this study)

NLST-1026

Mar 20, 2023

Quantifying cancer screening overdiagnosis using synthetic excess incidence

Introduction and objective An important concern in cancer screening is overdiagnosis, detecting preclinical cancer on screening that would not have developed into symptomatic cancer in the absence of screening. New liquid biopsy cancer screening technologies are being developed which require quantification of overdiagnosis. Because the technology is developing rapidly, this quantification should involve only short-term observational data. Unfortunately estimating the fraction overdiagnosed is “notoriously difficult,” even for approximations. Estimation based on previous modeling methods strongly relies on assumptions about the natural history of cancer. My objective was to develop a method for estimating the fraction overdiagnosed based on short-term observational data with less reliance on assumptions about the natural history of cancer.

Methods and Results. I framed the problem as computing synthetic excess incidence for periodic screening versus no screening based on data from at least two screens. This allowed me to apply previous methodology to estimate the age-specific incidence of cancer in the absence of screening. I also modeled cancer incidence after the oldest age screened which yielded estimated lower and upper bounds with a sensitivity analysis. Applying the methodology to short-term observational data from lung, breast, and colon cancer screening trials, I obtained estimates of the fraction overdiagnosed that were consistent with estimates from other methods.

Project Goal: Apply this methodology to NLST data

Part1. (Synthetic excess incidence method)
Separately for each arm of the study(x-ray and CT), I would like a table in the following form.
The rows are age (in years at the time of the screen).
The columns are (1) number who received first screen, (2) number positive on the first screen and positive for cancer on workup, (3) number who received a subsequent screen, (4) number positive on the subsequent screen and positive for cancer on work-up.
Note: A subsequent screen is a screen at T1 or T2 after a negative previous screen

Part 2 (alternative method of estimation for comparison)
I would like a table where the rows are year since randomization and the columns are (1) number of cancers cases in x-ray group diagnosed in that year (either screening or with symptoms), (2) number of cancers cases in CT group diagnosed in that year (either screening or with symptoms) (3) the number of cancer cases detected on screening in x-ray group (so zeros after the time of the last screen), and (4) the number of cancer cases detected on screening in the CT group