Data from Modeling Reporting Delay in Cancer Incidence Counts in the Evolving US and Canadian Population–Based Cancer Registry Environment

<div>AbstractBackground:<p>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.</p>Methods:<p>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.</p>Results:<p>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.</p>Conclusions:<p>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.</p>Impact:<p>The new model extends the use of delay adjustment to an important source of cancer surveillance statistics.</p></div>

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Publication Details

Published
2025-10-03
DOI
https://doi.org/10.1158/1055-9965.c.8069376
Primary Topic
Global Cancer Incidence and Screening
Type
article
Field-Weighted Citation Impact
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article

Data from Modeling Reporting Delay in Cancer Incidence Counts in the Evolving US and Canadian Population–Based Cancer Registry Environment

Huann‐Sheng Chen, Eric J. Feuer, Zhaohui Zou, Daniel G. Miller et al.
Global Cancer Incidence and Screening
article

Data from Modeling Reporting Delay in Cancer Incidence Counts in the Evolving US and Canadian Population–Based Cancer Registry Environment

Huann‐Sheng Chen, Eric J. Feuer, Zhaohui Zou, Daniel G. Miller, Douglas Midthune
article en

Abstract

<div>AbstractBackground:<p>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.</p>Methods:<p>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.</p>Results:<p>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.</p>Conclusions:<p>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.</p>Impact:<p>The new model extends the use of delay adjustment to an important source of cancer surveillance statistics.</p></div>

Openalex Percentile: Top 63%
Global Cancer Incidence and Screening
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Data from Modeling Reporting Delay in Cancer Incidence Counts in the Evolving US and Canadian Population–Based Cancer Registry Environment — Huann‐Sheng Chen, Eric J. Feuer, et al. · (2025) | TGRS Research Map | TGRS