Related Experiment Video
Updated: Sep 12, 2026

The Helsinki Rat Microsurgical Sidewall Aneurysm Model
Published on: October 12, 2014
Variation in cancer survival between hospital districts and within them in Finland
Karri Seppä1, Nea Malila1, Janne Pitkäniemi1,2,3
1Finnish Cancer Registry, Institute for Statistical and Epidemiological Cancer Research, Helsinki, Finland.
Background:
Monitoring regional variation in population-based cancer survival is useful for assessing equity in national health-care system. This study quantifies variation in survival between municipalities and hospital districts responsible for primary care and for specialised care, respectively, in Finland.
Material And Methods:
Five-year relative survival of 11 cancers and close to 700,000 patients was estimated by municipality in Finland over 1962-2016 using hierarchical Bayesian modelling. Variation (i) between hospital districts, (ii) between municipalities within hospital districts, and (iii) between all municipalities (total variation) were quantified by the standard deviation of 5-year relative survival standardised by the average survival level.
Results:
In 2007-2016, the largest variation in 5-year relative survival between all municipalities was in stomach, prostate, kidney and liver cancer and skin melanoma. In male skin melanoma, prostate, and kidney cancer and in male and female pancreatic cancer, there was substantial and statistically significant variation between hospital districts, too. Variation within hospital districts was on average 67% (95% posterior interval [58%,76%]) out of the total variation and had decreased by 18% [2%, 33%] from 1997-2006.
Conclusion:
The decrease in variation within hospital districts suggests that equity in diagnostics and primary care has improved in Finland. However, the variation between hospital districts in skin melanoma, prostate and kidney cancer reflects differences in early diagnostics. In pancreatic cancer, substantial variation between hospital districts may relate to regional differences in the accessibility and the quality of cancer treatments.
Related Concept Videos
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Kaplan-Meier Approach
Comparing the Survival Analysis of Two or More Groups
Cancer Survival Analysis

