TY - JOUR
T1 - The impact of excluding or including Death Certificate Initiated (DCI) cases on estimated cancer survival: A simulation study
AU - Andersson, Therese M-L
AU - Myklebust, Tor Åge
AU - Rutherford, Mark J
AU - Møller, Bjørn
AU - Soerjomataram, Isabelle
AU - Arnold, Melina
AU - Bray, Freddie
AU - Parkin, D Max
AU - Sasieni, Peter
AU - Bucher, Oliver
AU - De, Prithwish
AU - Engholm, Gerda
AU - Gavin, Anna
AU - Little, Alana
AU - Porter, Geoff
AU - Ramanakumar, Agnihotram V
AU - Saint-Jacques, Nathalie
AU - Walsh, Paul M
AU - Woods, Ryan R
AU - Lambert, Paul C
N1 - Copyright © 2020. Published by Elsevier Ltd.
PY - 2021/1/10
Y1 - 2021/1/10
N2 - BACKGROUND: Population-based cancer registries strive to cover all cancer cases diagnosed within the population, but some cases will always be missed and no register is 100 % complete. Many cancer registries use death certificates to identify additional cases not captured through other routine sources, to hopefully add a large proportion of the missed cases. Cases notified through this route, who would not have been captured without death certificate information, are referred to as Death Certificate Initiated (DCI) cases. Inclusion of DCI cases in cancer registries increases completeness and is important for estimating cancer incidence. However, inclusion of DCI cases will generally lead to biased estimates of cancer survival, but the same is often also true if excluding DCI cases. Missed cases are probably not a random sample of all cancer cases, but rather cases with poor prognosis. Further, DCI cases have poorer prognosis than missed cases in general, since they have all died with cancer mentioned on the death certificates.METHODS: We performed a simulation study to estimate the impact of including or excluding DCI cases on cancer survival estimates, under different scenarios.RESULTS: We demonstrated that including DCI cases underestimates survival. The exclusion of DCI cases gives unbiased survival estimates if missed cases are a random sample of all cancer cases, while survival is overestimated if these have poorer prognosis.CONCLUSION: In our most extreme scenarios, with 25 % of cases initially missed, the usual practice of including DCI cases underestimated 5-year survival by at most 3 percentage points.
AB - BACKGROUND: Population-based cancer registries strive to cover all cancer cases diagnosed within the population, but some cases will always be missed and no register is 100 % complete. Many cancer registries use death certificates to identify additional cases not captured through other routine sources, to hopefully add a large proportion of the missed cases. Cases notified through this route, who would not have been captured without death certificate information, are referred to as Death Certificate Initiated (DCI) cases. Inclusion of DCI cases in cancer registries increases completeness and is important for estimating cancer incidence. However, inclusion of DCI cases will generally lead to biased estimates of cancer survival, but the same is often also true if excluding DCI cases. Missed cases are probably not a random sample of all cancer cases, but rather cases with poor prognosis. Further, DCI cases have poorer prognosis than missed cases in general, since they have all died with cancer mentioned on the death certificates.METHODS: We performed a simulation study to estimate the impact of including or excluding DCI cases on cancer survival estimates, under different scenarios.RESULTS: We demonstrated that including DCI cases underestimates survival. The exclusion of DCI cases gives unbiased survival estimates if missed cases are a random sample of all cancer cases, while survival is overestimated if these have poorer prognosis.CONCLUSION: In our most extreme scenarios, with 25 % of cases initially missed, the usual practice of including DCI cases underestimated 5-year survival by at most 3 percentage points.
U2 - 10.1016/j.canep.2020.101881
DO - 10.1016/j.canep.2020.101881
M3 - Article
C2 - 33440295
SN - 1877-7821
VL - 71
SP - 101881
JO - Cancer Epidemiology
JF - Cancer Epidemiology
IS - Pt A
ER -