Please use this identifier to cite or link to this item: http://docs.prosentient.com.au/prosentientjspui/handle/1/10258
Title: Different survival analysis methods for measuring long-term outcomes of Indigenous and non-Indigenous Australian cancer patients in the presence and absence of competing risks.
Authors: He, Vincent Y F
Condon, John R
Baade, Peter D
Zhang, Xiaohua
Zhao, Yuejen
Affiliation: Menzies School of Health Research, Charles Darwin University, PO Box 41096, Casuarina, NT, 0811, Australia. vincent.he@menzies.edu.au..
Menzies School of Health Research, Charles Darwin University, PO Box 41096, Casuarina, NT, 0811, Australia..
Menzies School of Health Research, Charles Darwin University, PO Box 41096, Casuarina, NT, 0811, Australia.. Cancer Council Queensland, PO Box 201, Spring Hill, QLD, 4004, Australia..
Northern Territory Government Department of Health, Health Gains Planning Branch, PO Box 40596, Casuarina, NT, 0811, Australia..
Northern Territory Government Department of Health, Health Gains Planning Branch, PO Box 40596, Casuarina, NT, 0811, Australia..
Issue Date: 2017
Citation: Population health metrics 2017; 15(1): 1
Abstract: 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. 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. Cancer 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. Multivariable 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). 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 subgroup-specific life tables are available and cause of death data are unavailable or unreliable.
URI: http://docs.prosentient.com.au/prosentientjspui/handle/1/10258
DOI: 10.1186/s12963-016-0118-9
Type: Comparative Study
Journal Article
Research Support, Non-U.S. Gov't
Subjects: Cancer prognosis
Cause of death data
Competing risks
Crude probability of death
Fine-Gray model
Indigenous Australians
Life tables
Net survival
Smoking
Survival analysis
Adolescent
Adult
Aged
Aged, 80 and over
Child
Child, Preschool
Female
Humans
Infant
Infant, Newborn
Male
Middle Aged
Neoplasms
Northern Territory
Outcome Assessment (Health Care)
Probability
Proportional Hazards Models
Risk Factors
Young Adult
Cause of Death
Health Status Disparities
Life Tables
Oceanic Ancestry Group
Survival Analysis
Appears in Collections:NT Health digital library

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