Risk of cancer associated with residential exposure to asbestos insulation: a whole-population cohort study.

BACKGROUND: The health risks associated with living in houses insulated with asbestos are unknown. Loose-fill asbestos was used to insulate some houses in the Australian Capital Territory (ACT). We compared the incidence of mesothelioma and other cancers in residents of the ACT who did and did not live in these houses. METHODS: Our cohort study included all ACT residents identified using Medicare enrolment data. These data were linked to addresses of affected residential properties in the ACT to ascertain exposure. We followed up residents by linking data to the Australian Cancer Database and National Death Index. Outcomes were diagnosis of mesothelioma and selected other cancers. Effects were estimated for males and females separately using standardised incidence ratios (SIRs), adjusting for age and calendar time of diagnosis. FINDINGS: Between Nov 1, 1983, and Dec 31, 2013, 1 035 578 ACT residents were identified from the Medicare database. Of these, 17 248 (2%) had lived in an affected property, including seven (2%) of 285 people diagnosed with mesothelioma. The adjusted incidence of mesothelioma in males who had lived at an affected property was 2·5 times that of unexposed males (SIR 2·54, 95% CI 1·02-5·24). No mesotheliomas were reported among females who had lived at an affected property. Among individuals who had lived at an affected property, there was an elevated incidence of colorectal cancer in women (SIR 1·73, 95% CI 1·29-2·26) and prostate cancer in men (1·29, 1·07-1·54); colorectal cancer was increased, although not significantly, in males (SIR 1·32, 95% CI 0·99-1·72), with no significant increase in the other cancers studied. INTERPRETATION: Residential asbestos insulation is likely to be unsafe. Our findings have important health, social, financial, and legal implications for governments and communities in which asbestos has been used to insulate houses. FUNDING: ACT Government.

Establishing a process for conducting cross-jurisdictional record linkage in Australia.

OBJECTIVE: To describe the realities of conducting a cross-jurisdictional data linkage project involving state and Australian Government-based data collections to inform future national data linkage programs of work. METHODS: We outline the processes involved in conducting a Proof of Concept data linkage project including the implementation of national data integration principles, data custodian and ethical approval requirements, and establishment of data flows. RESULTS: The approval process involved nine approval and regulatory bodies and took more than two years. Data will be linked across 12 datasets involving three data linkage centres. A framework was established to allow data to flow between these centres while maintaining the separation principle that serves to protect the privacy of the individual. CONCLUSIONS: This will be the first project to link child immunisation records from an Australian Government dataset to other administrative health datasets for a population cohort covering 2 million births in two Australian states. IMPLICATIONS: Although the project experienced some delays, positive outcomes were realised, primarily the development of strong collaborations across key stakeholder groups including community engagement. We have identified several recommendations and enhancements to this now established framework to further streamline the process for data linkage studies involving Australian Government data.

A Simple Sampling Method for Estimating the Accuracy of Large Scale Record Linkage Projects.

BACKGROUND: Record linkage techniques allow different data collections to be brought together to provide a wider picture of the health status of individuals. Ensuring high linkage quality is important to guarantee the quality and integrity of research. Current methods for measuring linkage quality typically focus on precision (the proportion of incorrect links), given the difficulty of measuring the proportion of false negatives. OBJECTIVES: The aim of this work is to introduce and evaluate a sampling based method to estimate both precision and recall following record linkage. METHODS: In the sampling based method, record-pairs from each threshold (including those below the identified cut-off for acceptance) are sampled and clerically reviewed. These results are then applied to the entire set of record-pairs, providing estimates of false positives and false negatives. This method was evaluated on a synthetically generated dataset, where the true match status (which records belonged to the same person) was known. RESULTS: The sampled estimates of linkage quality were relatively close to actual linkage quality metrics calculated for the whole synthetic dataset. The precision and recall measures for seven reviewers were very consistent with little variation in the clerical assessment results (overall agreement using the Fleiss Kappa statistics was 0.601). CONCLUSIONS: This method presents as a possible means of accurately estimating matching quality and refining linkages in population level linkage studies. The sampling approach is especially important for large project linkages where the number of record pairs produced may be very large often running into millions.

Mortality trends among people with type 1 and type 2 diabetes in Australia: 1997-2010.

OBJECTIVE: With improvements in cardiovascular disease (CVD) rates among people with diabetes, mortality rates may also be changing. However, these trends may be influenced by coding practices of CVD-related deaths on death certificates. We analyzed trends of mortality over 13 years in people with diabetes and quantified the potential misclassification of CVD mortality according to current coding methods. RESEARCH DESIGN AND METHODS: A total of 1,136,617 Australians with diabetes registered on the National Diabetes Services Scheme between 1997 and 2010 were linked to the National Death Index. Excess mortality relative to the Australian population was reported as standardized mortality ratios (SMRs). Potential misclassification of CVD mortality was determined by coding CVD according to underlying cause of death (COD) and then after consideration of both the underlying and other causes listed in part I of the death certificate. RESULTS: For type 1 diabetes, the SMR decreased in males from 4.20 in 1997 to 3.08 in 2010 (Ptrend < 0.001) and from 3.92 to 3.46 in females (Ptrend < 0.01). For type 2 diabetes, the SMR decreased in males from 1.40 to 1.21 (Ptrend < 0.001) and from 1.56 to 1.22 in females (Ptrend < 0.001). CVD deaths decreased from 35.6 to 31.2% and from 31.5 to 27.2% in males and females with type 1 diabetes, respectively (Ptrend < 0.001 for both sexes). For type 2 diabetes, CVD decreased from 44.5 to 29.2% in males and from 45.5 to 31.6% in females (Ptrend < 0.001 for both sexes). Using traditional coding methods, ∼38 and 26% of CVD deaths are underestimated in type 1 diabetes and type 2 diabetes, respectively. CONCLUSIONS: All-cause and CVD mortality has decreased in diabetes. However, the total CVD mortality burden is underestimated when only underlying COD is considered. This has important ramifications for understanding mortality patterns in diabetes.

Cancer risk in 680,000 people exposed to computed tomography scans in childhood or adolescence: data linkage study of 11 million Australians.

OBJECTIVE: To assess the cancer risk in children and adolescents following exposure to low dose ionising radiation from diagnostic computed tomography (CT) scans. DESIGN: Population based, cohort, data linkage study in Australia. COHORT MEMBERS: 10.9 million people identified from Australian Medicare records, aged 0-19 years on 1 January 1985 or born between 1 January 1985 and 31 December 2005; all exposures to CT scans funded by Medicare during 1985-2005 were identified for this cohort. Cancers diagnosed in cohort members up to 31 December 2007 were obtained through linkage to national cancer records. MAIN OUTCOME: Cancer incidence rates in individuals exposed to a CT scan more than one year before any cancer diagnosis, compared with cancer incidence rates in unexposed individuals. RESULTS: 60,674 cancers were recorded, including 3150 in 680,211 people exposed to a CT scan at least one year before any cancer diagnosis. The mean duration of follow-up after exposure was 9.5 years. Overall cancer incidence was 24% greater for exposed than for unexposed people, after accounting for age, sex, and year of birth (incidence rate ratio (IRR) 1.24 (95% confidence interval 1.20 to 1.29); P<0.001). We saw a dose-response relation, and the IRR increased by 0.16 (0.13 to 0.19) for each additional CT scan. The IRR was greater after exposure at younger ages (P<0.001 for trend). At 1-4, 5-9, 10-14, and 15 or more years since first exposure, IRRs were 1.35 (1.25 to 1.45), 1.25 (1.17 to 1.34), 1.14 (1.06 to 1.22), and 1.24 (1.14 to 1.34), respectively. The IRR increased significantly for many types of solid cancer (digestive organs, melanoma, soft tissue, female genital, urinary tract, brain, and thyroid); leukaemia, myelodysplasia, and some other lymphoid cancers. There was an excess of 608 cancers in people exposed to CT scans (147 brain, 356 other solid, 48 leukaemia or myelodysplasia, and 57 other lymphoid). The absolute excess incidence rate for all cancers combined was 9.38 per 100,000 person years at risk, as of 31 December 2007. The average effective radiation dose per scan was estimated as 4.5 mSv. CONCLUSIONS: The increased incidence of cancer after CT scan exposure in this cohort was mostly due to irradiation. Because the cancer excess was still continuing at the end of follow-up, the eventual lifetime risk from CT scans cannot yet be determined. Radiation doses from contemporary CT scans are likely to be lower than those in 1985-2005, but some increase in cancer risk is still likely from current scans. Future CT scans should be limited to situations where there is a definite clinical indication, with every scan optimised to provide a diagnostic CT image at the lowest possible radiation dose.