ArticleBMC public health2020
Incorporating competing risk theory into evaluations of changes in cancer survival: making the most of cause of death and routinely linked sociodemographic data.
Article in BMC public health, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- External Validation of Prognostic Models for Nonmetastatic Clear Cell Renal Cell Carcinoma in a Japanese Cohort: Evaluation of Predictive Performance.International journal of urology : official journal of the Japanese Urological Association · 2026Article
- Surgery Reduces Cancer-specific Death in Elderly Right-Sided Colon Cancer: A SEER-Based Competing-Risk Analysis.Cancer control : journal of the Moffitt Cancer CenterArticle
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundRelative survival is the most common method used for measuring survival from population-based registries. However, the relative survival concept of 'survival as far as the cancer is concerned' can be biased due to differing non-cancer risk of death in the population with cancer (competing risks). Furthermore, while relative survival can be stratified or standardised, for example by sex or age, adjustment for a broad range of sociodemographic variables potentially influencing survival is not possible. In this paper we propose Fine and Gray competing risks multivariable regression as a method that can assess the probability of death from cancer, incorporating competing risks and adjusting for sociodemographic confounders.
methodsWe used whole of population, person-level routinely linked Western Australian cancer registry and mortality data for individuals diagnosed from 1983 to 2011 for major cancer types combined, female breast, colorectal, prostate, lung and pancreatic cancers, and grade IV glioma. The probability of death from the index cancer (cancer death) was evaluated using Fine and Gray competing risks regression, adjusting for age, sex, Indigenous status, socio-economic status, accessibility to services, time sub-period and (for all cancers combined) cancer type.
resultsWhen comparing diagnoses in 2008-2011 to 1983-1987, we observed substantial decreases in the rate of cancer death for major cancer types combined (N = 192,641, - 31%), female breast (- 37%), prostate (- 76%) and colorectal cancers (- 37%). In contrast, improvements in pancreatic (- 15%) and lung cancers (- 9%), and grade IV glioma (- 24%) were less and the cumulative probability of cancer death for these cancer types remained high.
conclusionConsidering the justifiable expectation for confounder adjustment in observational epidemiological studies, standard methods for tracking population-level changes in cancer survival are simplistic. This study demonstrates how competing risks and sociodemographic covariates can be incorporated using readily available software. While cancer has been focused on here, this technique has potential utility in survival analysis for other disease states.
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