Related Experiment Video
Updated: Sep 13, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Modeling Reporting Delay in Cancer Incidence Counts in the Evolving US and Canadian Population-Based Cancer Registry
Huann-Sheng Chen1, Douglas Midthune2, Zhaohui Zou3
1Division of Cancer Control and Population Sciences, National Cancer Institute, NIH, Bethesda, Maryland.
Background:
Cancer incidence data collected by cancer registries in the United States and Canada are submitted to the North American Association of Central Cancer Registries, which publishes annual case counts for the two countries. To allow time to collect and report cases, counts for a given diagnosis year are initially published two years after the end of that year and updated annually. Initial counts typically underreport cases compared with updated counts due to reporting delays, potentially biasing estimated incidence trends.
Methods:
Existing methods for estimating "delay-adjusted" counts are modified for this heterogeneous group of registries exhibiting different patterns of reporting delay. The new method can be applied to individual registries and combined to produce delay-adjusted rates for the entire population, as well as for geographic or demographic subpopulations.
Results:
Steps involved in estimating delay-adjusted counts are illustrated for liver and intrahepatic bile duct cancer in White males, in which delay-adjusted rates exhibit a stabilized trend, in contrast to the rapid decline seen in observed (unadjusted) rates. Additionally, the new delay model reveals reporting delays varying across cancer sites, race, and ethnicity. Finally, an extended model provides validated delay-adjusted rates from preliminary data that reduces reporting time from 2 years to 1 year.
Conclusions:
Adjusting for reporting delay provides more accurate estimates of cancer incidence trends. The proposed method addresses practical issues of model implementation and continues the evolution of delay adjustment in cancer registries.
Impact:
The new model extends the use of delay adjustment to an important source of cancer surveillance statistics.
Related Concept Videos
Cancer Survival Analysis
Prevalence and Incidence
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Statistical Methods for Analyzing Epidemiological Data
Kaplan-Meier Approach
Bias in Epidemiological Studies

