- SEER 9 Delay Model
- SEER 13 Delay Model
- Cancer Sites and Variables
- Veterans Affairs Backlog Adjustment
Cancer Incidence Rates Adjusted for Reporting Delay
Timely and accurate calculation of cancer incidence rates is hampered by reporting delay, the time elapsed before a diagnosed cancer case is reported to the NCI. Currently, the NCI allows a standard delay of 22 months between the end of the diagnosis year and the time the cancers are first reported to the NCI in November, almost 2 years later. The data are released to the public in the spring of the following year. For example:
- Cases diagnosed in 2010 were first reported to the NCI in November 2012 and released to the public in April 2013.
- In each subsequent release of the SEER data, all prior diagnosis years (e.g., diagnosis years 2009 and earlier in the 2012 submission to the NCI) are updated as either new cases are found or new information is received about previously submitted cases.
- The submissions for the most recent diagnosis year are, in general, about two percent below the number of cancers that will be submitted for that year in the future, although this varies by cancer site and other factors.
- Starting with the April 2009 release of the Cancer Statistics Review, for the first time we are producing delay-adjusted incidence rates based on SEER 13. This differs from previous years when delay-adjustment was available only for SEER 9.
- Starting with the November 2009 SEER data submission, a Veterans Affairs (VA) backlog adjustment was included in the delay model. This was developed to take into account a VA policy on data sharing that resulted in underreporting on VA hospital cases for submission years 2006-2008, and then a partial upsurge in VA cases in some registries in the 2009 submission, as prior cases started to be reported.
The idea behind modeling reporting delay is to adjust the current case count to account for anticipated future corrections (both additions and deletions) to the data. These adjusted counts and the associated delay model are valuable in more precisely determining current cancer trends, as well as in monitoring the timeliness of data collection — an important aspect of quality control (Clegg et al., 2002; Midthune et al., 2005). Reporting delay models have been previously used in the reporting of AIDS cases (Brookmeyer & Damiano, 1989; Pagano et al., 1994; Harris, 1990).