Cancer survival for Aboriginal and Torres Strait Islander Australians: a national study of survival rates and excess mortality

BackgroundNational cancer survival statistics are available for the total Australian population but not Indigenous Australians, although their cancer mortality rates are known to be higher than those of other Australians. We aimed to validate analysis methods and report cancer survival rates for Indigenous Australians as the basis for regular national reporting.MethodsWe used national cancer registrations data to calculate all-cancer and site-specific relative survival for Indigenous Australians (compared with non-Indigenous Australians) diagnosed in 2001-2005. Because of limited availability of Indigenous life tables, we validated and used cause-specific survival (rather than relative survival) for proportional hazards regression to analyze time trends and regional variation in all-cancer survival between 1991 and 2005.ResultsSurvival was lower for Indigenous than non-Indigenous Australians for all cancers combined and for many cancer sites. The excess mortality of Indigenous people with cancer was restricted to the first three years after diagnosis, and greatest in the first year. Survival was lower for rural and remote than urban residents; this disparity was much greater for Indigenous people. Survival improved between 1991 and 2005 for non-Indigenous people (mortality decreased by 28%), but to a much lesser extent for Indigenous people (11%) and only for those in remote areas; cancer survival did not improve for urban Indigenous residents.ConclusionsCancer survival is lower for Indigenous than other Australians, for all cancers combined and many individual cancer sites, although more accurate recording of Indigenous status by cancer registers is required before the extent of this disadvantage can be known with certainty. Cancer care for Indigenous Australians needs to be considerably improved; cancer diagnosis, treatment, and support services need to be redesigned specifically to be accessible and acceptable to Indigenous people

The epidemiology of disparities in lung cancer in NSW: an exploration of intersecting populations

Lung cancer is the most common cause of cancer death in Australia, resulting in considerable disease burden. Despite being a poor prognosis disease, there are marked disparities in the incidence, treatment, survival and mortality for sub-populations. The lung cancer burden in NSW is higher among people residing in lower socioeconomic areas, people who live regionally and remotely and Aboriginal people. This thesis uses theoretical and empirical approaches used in the fields of both social and cancer epidemiology to comprehensively examine lung cancer sub-population disparities in NSW. It is the first examination of intersecting disparities for people with lung cancer in NSW. Through the development of a conceptual framework for addressing lung cancer disparities in the Australian context, it explores how previous research has estimated disparities in lung cancer incidence, treatment, survival and mortality and assesses the utility of the mortality to incidence ratio using already available data as a proxy measure for survival. Using linked data and existing data from a patterns of care study, lung cancer disparities are explored by Aboriginal status, socioeconomic area and geographic remoteness with focus on the intersections of these sub-populations. It comprises of three sections which together include seven sequential chapters. The first section (chapters 1 to 3) provides the theoretical background and empirical evidence to support the basis of and approach to estimating lung cancer disparities in NSW. A conceptual framework was developed, underpinned by theoretical models, through available literature that provides potential explanations for lung cancer disparities. It aims to clarify mediating pathways and describe the broad range of determinants of lung cancer disparities and their relationships. A systematic review was also conducted examining the range of metrics used to estimate lung cancer disparities in the international setting. Recommendations for empirical approaches to measuring lung cancer disparities have been developed. Additionally, the variations in empirical vii evidence seen across the literature highlighted the need for the development of comprehensive national recommendations for estimating comparative cancer disparities. The second section (chapters 4 to 6) provides empirical investigations of lung cancer disparities in NSW with aims to elucidate complex patterns that exist when considering multiple sub-populations by investigating associations between Indigenous status, socioeconomic disadvantage, and geographic remoteness. A data linkage study included 20,846 residents of NSW with a primary diagnosis of lung cancer reported to the NSW Central Cancer Registry between January 01, 2001 and December 31, 2007. Records were linked (using the NSW Centre for Record Health Linkage) to the Admitted Patients Data Collection and deaths data collections. Methods of addressing intersectionality, examining how gender, ethnicity, disadvantage and other factors work together to create inequity, using population-level data were applied to incidence, utilisation of evidence-based surgery, survival and mortality rates to assess Indigenous, socioeconomic and geographic disparities. Indigenous people had a standardised incidence rate ratio (IRR) of 1.96 (p<0.001) when adjusting for socioeconomic disadvantage and remoteness. However, when stratified by geographic remoteness, Indigenous people were almost eight times (IRR 7.70, p<0.001) more likely to have a lung cancer diagnosis if they live in outer regional, remote and very remote areas when compared to non-Indigenous people in the same areas. Assessing the intersection of Indigenous status, geographic remoteness and socioeconomic disadvantage using health administration data identifies those sub-populations at greatest risk. Such analysis provides necessary empirical evidence to guide health service planning and health resource allocation. A secondary analysis of a retrospective lung cancer patterns of care study was undertaken to estimate the odds of receiving treatment in concordance with evidence-based guidelines (as specified by the 2004 National Health and Medical Research Councils clinical guidelines) by area-based measures of socioeconomic status and geographic remoteness. Survival analysis was viii also conducted to estimate the time to treatment for those people who received guideline concordant treatment. The dataset contained information on demographics, treatment and outcome for people lung cancer registered in the NSW Central Cancer Registry between November 01, 2001 and December 31, 2002. For 1,214 eligible patients, guideline concordant treatment ranged from 4% to 79%, depending upon the guideline. Geographic disparities were found in both evidence-based surgical treatment and time to evidence-based treatment. Socioeconomic disparities in evidence-based chemotherapy were experienced by advantaged people with late-stage NSCLC. The results suggest that geographic remoteness and socioeconomic status play independent roles in evidence-based treatment uptake. The last chapter in the second section assesses the utility of the mortality to incidence ratio complement (1-MIR) as a proxy measure for cause-specific survival. Linked data was used to obtain people diagnosed with lung cancer and who have died from lung cancer in NSW from 2001 to 2007. The validity of the 1-MIR was examined using publicly available data from NSW for 1999 to 2007, and from the NT for 2001 to 2010. Absolute differences between the 1-MIR and 3-year cause-specific survival; and absolute differences between 1-MIR and 5-year cause-specific survival for non-Indigenous and Indigenous people, males and females did not exceed 10% for NSW 2001-2007 linked data or the NSW 1999-2007. Differences between 1-MIR and 5-year relative survival estimates were overestimated by more than 10% in non-Indigenous persons and males and Indigenous and females for the NT 2001-2010. The 1-MIR was found to be a good approximation for 5-year cause-specific survival but it has some limitations in validly estimating health disparities in Indigenous sub-populations. The third section (chapter 7) provides concluding statements on the examination of lung cancer disparities for individuals, in terms of multiple dimensions or experiences of social status (e.g. Aboriginal people who live in regional areas). This thesis acknowledges the complex issues in ix identifying health disparities. It uses already available data to explore lung cancer disparities and provides empirical evidence for the use of intersectionality theory in describing the epidemiology of lung cancer in a state-wide population

Indigenous and Tribal Peoples Data Governance in Health Research: A Systematic Review

There is increasing potential to improve the research and reporting on the health and wellbeing of Indigenous and Tribal peoples through the collection and (re)use of population-level data. As the data economy grows and the value of data increases, the optimization of data pertaining to Indigenous peoples requires governance that defines who makes decisions on behalf of whom and how these data can and should be used. An international a priori PROSPERO (#CRD42020170033) systematic review was undertaken to examine the health research literature to (1) identify, describe, and synthesize definitions and principles; (2) identify and describe data governance frameworks; and (3) identify, describe, and synthesize processes, policies and practices used in Indigenous Data Governance (ID-GOV). Sixty-eight articles were included in the review that found five components that require consideration in the governance of health research data pertaining to Indigenous people. This included (1) Indigenous governance; (2) institutional ethics; (3) socio-political dynamics; (4) data management and data stewardship; and (5) overarching influences. This review provides the first systematic international review of ID-GOV that could potentially be used in a range of governance strategies moving forward in health research