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Innos K, Lang K, Pärna K, et al. Age-specific cancer survival in Estonia: recent trends and data quality. Clin Epidemiol. 2015;7:355-62doi: 10.2147/CLEP.S87699.
Innos, K., Lang, K., Pärna, K., & Aareleid, T. (2015). Age-specific cancer survival in Estonia: recent trends and data quality. Clinical epidemiology, 7355-62. https://doi.org/10.2147/CLEP.S87699
Innos, Kaire, et al. "Age-specific cancer survival in Estonia: recent trends and data quality." Clinical epidemiology vol. 7 (2015): 355-62. doi: https://doi.org/10.2147/CLEP.S87699
Innos K, Lang K, Pärna K, Aareleid T. Age-specific cancer survival in Estonia: recent trends and data quality. Clin Epidemiol. 2015 Jul 29;7:355-62. doi: 10.2147/CLEP.S87699. eCollection 2015. PMID: 26251630; PMCID: PMC4524267.
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Clin Epidemiol. 2015 Jul 29;7:355-62. doi: 10.2147/CLEP.S87699. eCollection 2015.

Age-specific cancer survival in Estonia: recent trends and data quality.

Clinical epidemiology

Kaire Innos, Katrin Lang, Kersti Pärna, Tiiu Aareleid

Affiliations

  1. Department of Epidemiology and Biostatistics, National Institute for Health Development, Tallinn, Estonia.
  2. Department of Public Health, University of Tartu, Tartu, Estonia.

PMID: 26251630 PMCID: PMC4524267 DOI: 10.2147/CLEP.S87699

Abstract

BACKGROUND: A number of population-based studies have demonstrated lower cancer survival in elderly patients than among middle-aged or younger patients. Also, data quality in cancer registries has been shown to be associated with age. The objective of this study was to examine the recent age-specific cancer survival trends and age-specific quality of cancer data in Estonia.

METHODS: Using Estonian Cancer Registry data, we calculated relative survival ratios (RSRs) for eight common cancers in Estonia in 1995-1999 (cohort method) and 2005-2009 (period method) for four major age groups (15-54, 55-64, 65-74, and 75-84 years at diagnosis). The main data quality indicators were calculated, and the age-specific effect of missing death certificate initiated (DCI) cases on survival was estimated comparing 5-year RSRs computed from the complete data set with those from data set without DCI cases.

RESULTS: We observed overall rise in 5-year RSR for all eight cancers over the study period, with a considerable variation by age, with the lowest survival among the oldest patients. The widest age gradient in 5-year RSR was seen for bladder cancer (20% units in 2005-2009), followed by cancers of lung (16% units), kidney (15% units), breast and prostate (13% units), stomach and rectum (11% units), and colon (5% units). All data quality indicators, including proportion of cases with unknown stage showed a similar age-related pattern with the lowest quality in the oldest age group. The effect of missing DCI cases on survival estimates increased by age and was around 3% units for prostate and kidney cancers among the oldest patients.

CONCLUSION: Young or middle-aged patients in Estonia experienced larger survival gain since the late 1990s than elderly patients. Decreasing quality of cancer registry data along with increasing patient age suggests less thorough clinical investigations in older age groups.

Keywords: age differences; cancer registry; data quality; population-based; relative survival

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