Karri Seppä1, Timo Hakulinen2, Arun Pokhrel3. 1. Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Pieni Roobertinkatu 9, FI-00130 Helsinki, Finland; Department of Mathematical Sciences, University of Oulu, Oulu, Finland. 2. Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Pieni Roobertinkatu 9, FI-00130 Helsinki, Finland. 3. Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Pieni Roobertinkatu 9, FI-00130 Helsinki, Finland. Electronic address: arun.pokhrel@cancer.fi.
Abstract
BACKGROUND: A new net survival method has been introduced by Pohar Perme et al. (2012 [4]) and recommended to substitute the relative survival methods in current use for evaluating population-based cancer survival. METHODS: The new method is based on the use of continuous follow-up time, and is unbiased only under non-informative censoring of the observed survival. However, the population-based cancer survival is often evaluated based on annually or monthly tabulated follow-up intervals. An empirical investigation based on data from the Finnish Cancer Registry was made into the practical importance of the censoring and the level of data tabulation. A systematic comparison was made against the earlier recommended Ederer II method of relative survival using the two currently available computer programs (Pohar Perme (2013) [10] and Dickman et al. (2013) [11]). RESULTS: With exact or monthly tabulated data, the Pohar-Perme and the Ederer II methods give, on average, results that are at five years of follow-up less than 0.5% units and at 10 and 14 years 1-2% units apart from each other. The Pohar-Perme net survival estimator is prone to random variation and may result in biased estimates when exact follow-up times are not available or follow-up is incomplete. With annually tabulated follow-up times, estimates can deviate substantially from those based on more accurate observations, if the actuarial approach is not used. CONCLUSION: At 5 years, both the methods perform well. In longer follow-up, the Pohar-Perme estimates should be interpreted with caution using error margins. The actuarial approach should be preferred, if data are annually tabulated.
BACKGROUND: A new net survival method has been introduced by Pohar Perme et al. (2012 [4]) and recommended to substitute the relative survival methods in current use for evaluating population-based cancer survival. METHODS: The new method is based on the use of continuous follow-up time, and is unbiased only under non-informative censoring of the observed survival. However, the population-based cancer survival is often evaluated based on annually or monthly tabulated follow-up intervals. An empirical investigation based on data from the Finnish Cancer Registry was made into the practical importance of the censoring and the level of data tabulation. A systematic comparison was made against the earlier recommended Ederer II method of relative survival using the two currently available computer programs (Pohar Perme (2013) [10] and Dickman et al. (2013) [11]). RESULTS: With exact or monthly tabulated data, the Pohar-Perme and the Ederer II methods give, on average, results that are at five years of follow-up less than 0.5% units and at 10 and 14 years 1-2% units apart from each other. The Pohar-Perme net survival estimator is prone to random variation and may result in biased estimates when exact follow-up times are not available or follow-up is incomplete. With annually tabulated follow-up times, estimates can deviate substantially from those based on more accurate observations, if the actuarial approach is not used. CONCLUSION: At 5 years, both the methods perform well. In longer follow-up, the Pohar-Perme estimates should be interpreted with caution using error margins. The actuarial approach should be preferred, if data are annually tabulated.
Authors: Janis Campbell; Krupa Gandhi; Anne Pate; Amanda Janitz; Amber Anderson; Robin Kinnard; Kai Ding Journal: J Okla State Med Assoc Date: 2016 Jul-Aug