Abstract

BackgroundNet survival is the most common measure of cancer prognosis and has been used to study differentials in cancer survival between ethnic or racial population subgroups. However, net survival ignores competing risks of deaths and so provides incomplete prognostic information for cancer patients, and when comparing survival between populations with different all-cause mortality. Another prognosis measure, “crude probability of death”, which takes competing risk of death into account, overcomes this limitation. Similar to net survival, it can be calculated using either life tables (using Cronin-Feuer method) or cause of death data (using Fine-Gray method). The aim of this study is two-fold: (1) to compare the multivariable results produced by different survival analysis methods; and (2) to compare the Cronin-Feuer with the Fine-Gray methods, in estimating the cancer and non-cancer death probability of both Indigenous and non-Indigenous cancer patients and the Indigenous cancer disparities.MethodsCancer survival was investigated for 9,595 people (18.5% Indigenous) diagnosed with cancer in the Northern Territory of Australia between 1991 and 2009. The Cox proportional hazard model along with Poisson and Fine-Gray regression were used in the multivariable analysis. The crude probabilities of cancer and non-cancer methods were estimated in two ways: first, using cause of death data with the Fine-Gray method, and second, using life tables with the Cronin-Feuer method.ResultsMultivariable regression using the relative survival, cause-specific survival, and competing risk analysis produced similar results. In the presence of competing risks, the Cronin-Feuer method produced similar results to Fine-Gray in the estimation of cancer death probability (higher Indigenous cancer death probabilities for all cancers) and non-cancer death probabilities (higher Indigenous non-cancer death probabilities for all cancers except lung cancer and head and neck cancers). Cronin-Feuer estimated much lower non-cancer death probabilities than Fine-Gray for non-Indigenous patients with head and neck cancers and lung cancers (both smoking-related cancers).ConclusionDespite the limitations of the Cronin-Feuer method, it is a reasonable alternative to the Fine-Gray method for assessing the Indigenous survival differential in the presence of competing risks when valid and reliable subgroup-specific life tables are available and cause of death data are unavailable or unreliable.

Highlights

  • Net survival is the most common measure of cancer prognosis and has been used to study differentials in cancer survival between ethnic or racial population subgroups

  • Despite the limitations of the Cronin-Feuer method, it is a reasonable alternative to the Fine-Gray method for assessing the Indigenous survival differential in the presence of competing risks when valid and reliable subgroupspecific life tables are available and cause of death data are unavailable or unreliable

  • Our study has shown that the Indigenous disparity in smoking-related cancer death probabilities estimated by Cronin-Feuer method is lower than that estimated by the Fine-Gray method, which suggests that survival analysis methods that use the life table such as relative survival might underestimate the Indigenous disparity in cancer survival for smoking-related cancers

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Summary

Introduction

Net survival is the most common measure of cancer prognosis and has been used to study differentials in cancer survival between ethnic or racial population subgroups. Net survival is the measure most commonly used to compare cancer prognosis in different populations (e.g., between nations, regions, or racial/ethnic groups) [1, 3,4,5,6,7,8,9] because net survival removes the effect of non-cancer deaths (which may vary between populations because of different all-cause mortality rates [10]) and measures the hypothetical scenario in which patients are only able to die of their cancer This is a disadvantage of net survival for patients and clinicians who, when considering the treatment options and weighing up the benefits, drawbacks, and toxicities of cancer therapy, want to know about actual prognosis: what is the chance of dying (from cancer or any cause) compared with the chance of surviving [5, 9, 10]? Life tables can be used to calculate net survival using the relative survival method or crude probabilities of cancer and non-cancer deaths using the Cronin-Feuer method

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