Out-of-pocket health care expenses for people with and without cancer, New South Wales, 2020: a cross-sectional study.

OBJECTIVES: To investigate self-reported out-of-pocket health care expenses, both overall and by cost type, for a large population-based sample of Australians, by cancer status and socio-demographic and medical characteristics. STUDY DESIGN: Cross-sectional study. SETTING, PARTICIPANTS: New South Wales residents participating in the 45 and Up Study (recruited aged 45 years or older during 2005-2009) who completed the 2020 follow-up questionnaire; survey responses linked with New South Wales Cancer Registry data. MAIN OUTCOME MEASURES: Proportions of respondents who reported that out-of-pocket health care expenses during the preceding twelve months exceeded $1000 or $10 000; adjusted odds ratios (aORs) for associations with socio-demographic and medical characteristics. RESULTS: Of the 267 357 recruited 45 and Up Study participants, 45 061 completed the 2020 survey (response rate, 53%); 42.7% (95% confidence interval [CI], 42.2-43.1%) reported that overall out-of-pocket health care expenses during the previous year exceeded $1000, including 55.4% (52.1-58.7%) of participants diagnosed in the preceding two years and 44.9% (43.7-46.1%) of participants diagnosed with cancer more than two years ago. After adjustment for socio-demographic factors, out-of-pocket expenses greater than $1000 were more likely to be reported by participants with cancer than by those without cancer (diagnosis in past two years: aOR, 2.06 [95% CI, 1.77-2.40]; diagnosis more than two years ago: aOR, 1.22 [95% CI, 1.15-1.29]). The odds of out-of-pocket expenses exceeding $1000 increased with area-based socio-economic advantage and household income, and were higher for people with private health insurance (v people with Medicare coverage only: aOR, 1.64; 95% CI, 1.53-1.75). Out-of-pocket expenses exceeding $10 000 were also more likely for participants diagnosed with cancer during the past two years (v no cancer: aOR, 3.30; 95% CI, 2.56-4.26). CONCLUSIONS: People diagnosed with cancer during the past two years were much more likely than people without cancer to report twelve-month out-of-pocket health care expenses that exceeded $1000. Out-of-pocket expenses for people with cancer can exacerbate financial strain at a time of vulnerability, and affect health care equity because some people cannot pay for all available treatments.

Multiple myeloma incidence, mortality, and prevalence estimates and projections, Australia, 1982-2043: a statistical modelling study.

OBJECTIVES: To examine changes in multiple myeloma incidence and mortality rates during 1982-2018, and to estimate its incidence, mortality, and prevalence for 2019-2043. STUDY DESIGN: Population-based statistical modelling study; analysis of and projections based on Australian Institute of Health and Welfare multiple myeloma incidence, mortality, and survival data. SETTING: Australia, 1982-2018 (historical data) and projections to 2043. MAIN OUTCOME MEASURES: Changes in multiple myeloma incidence and mortality rates, 1982-2018, determined by joinpoint regression analysis (age-standardised to 2021 Australian population); projection of rates to 2043 based on age-period-cohort models; estimated 5- and 30-year prevalence of multiple myeloma (modified counting method). RESULTS: The incidence of multiple myeloma increased during 1982-2018 (eg, annual percentage change [APC], 2006-2018, 1.9%; 95% confidence interval [CI], 1.7-2.2%), but the mortality rate declined during 1990-2018 (APC, -0.4%; 95% CI, -0.5% to -0.2%). The age-standardised incidence rate was projected to increase by 14.9% during 2018-2043, from 8.7 in 2018 to 10.0 (95% CI, 9.4-10.7) new cases per 100 000 population in 2043; the mortality rate was projected to decline by 27.5%, from 4.0 to 2.9 (95% CI, 2.6-3.3) deaths per 100 000 population. The annual number of people newly diagnosed with multiple myeloma was estimated to increase by 89.2%, from 2120 in 2018 to 4012 in 2043; the number of deaths from multiple myeloma was projected to increase by 31.7%, from 979 to 1289. The number of people living with multiple myeloma up to 30 years after initial diagnosis was projected to increase by 163%, from 10 288 in 2018 to 27 093 in 2043, including 13 019 people (48.1%) diagnosed during the preceding five years. CONCLUSION: Although the decline in the mortality rate was projected to continue, the projected increases in the incidence and prevalence of multiple myeloma in Australia over the next 25 years indicate that investment in prevention and early detection research, and planning for prolonged treatment and care, are needed.

Female reproductive and hormonal factors and lung cancer mortality among never-smokers: A prospective cohort study of 287 408 Chinese women.

There is growing, but inconsistent evidence suggesting oestrogen may play a key role in lung cancer development, especially among never-smoking women for whom lung cancer risk factors remain largely elusive. Using the China Kadoorie Biobank, a large-scale prospective cohort with 302 510 women aged 30 to 79 years recruited from 10 regions in China during 2004 to 2008, we assessed the risk of lung cancer death among self-reported never-smoking women who were cancer-free at baseline, in relation to age at menarche, age at menopause, time since menopause, prior use of oral contraceptives (OCP), number of livebirths, breastfeeding and age at first livebirth. Women were followed up to December 31, 2016 with linkage to mortality data. Hazard ratios (HR) and 95% confidence intervals (CI) were estimated using Cox regression, adjusting for key confounders including several socio-demographic, environmental and lifestyle factors. Among 287 408 never-smoking women, 814 died from lung cancer with a median follow-up of 10.3 years. Women who had used OCP within 15 years prior to baseline had a significantly higher hazard of lung cancer death compared with never-users: HR = 1.85 (95% CI: 1.14-3.00) and risk increased by 6% with each additional year of use: HR = 1.06 (1.01-1.10). Among parous women, the hazard of lung cancer death increased by 13% with each single livebirth: HR = 1.13 (1.05-1.23); and among post-menopausal women, the risk increased by 2% with each year since menopause: HR = 1.02 (1.01-1.04). These results suggest that reproductive factors which were proxies for lower endogenous oestrogen level, for example, longer duration of OCP use, could play a role in lung cancer development.

Updated cost-effectiveness analysis of lung cancer screening for Australia, capturing differences in the health economic impact of NELSON and NLST outcomes.

BACKGROUND: A national, lung cancer screening programme is under consideration in Australia, and we assessed cost-effectiveness using updated data and assumptions. METHODS: We estimated the cost-effectiveness of lung screening by applying screening parameters and outcomes from either the National Lung Screening Trial (NLST) or the NEderlands-Leuvens Longkanker Screenings ONderzoek (NELSON) to Australian data on lung cancer risk, mortality, health-system costs, and smoking trends using a deterministic, multi-cohort model. Incremental cost-effectiveness ratios (ICERs) were calculated for a lifetime horizon. RESULTS: The ICER for lung screening compared to usual care in the NELSON-based scenario was AU$39,250 (95% CI $18,150-108,300) per quality-adjusted life year (QALY); lower than the NLST-based estimate (ICER = $76,300, 95% CI $41,750-236,500). In probabilistic sensitivity analyses, lung screening was cost-effective in 15%/60% of NELSON-like simulations, assuming a willingness-to-pay threshold of $30,000/$50,000 per QALY, respectively, compared to 0.5%/6.7% for the NLST. ICERs were most sensitive to assumptions regarding the screening-related lung cancer mortality benefit and duration of benefit over time. The cost of screening had a larger impact on ICERs than the cost of treatment, even after quadrupling the 2006-2016 healthcare costs of stage IV lung cancer. DISCUSSION: Lung screening could be cost-effective in Australia, contingent on translating trial-like lung cancer mortality benefits to the clinic.

Pain and its interference with daily living in relation to cancer: a comparative population-based study of 16,053 cancer survivors and 106,345 people without cancer.

BACKGROUND: Pain is a common, debilitating, and feared symptom, including among cancer survivors. However, large-scale population-based evidence on pain and its impact in cancer survivors is limited. We quantified the prevalence of pain in community-dwelling people with and without cancer, and its relation to physical functioning, psychological distress, and quality of life (QoL). METHODS: Questionnaire data from participants in the 45 and Up Study (Wave 2, n = 122,398, 2012-2015, mean age = 60.8 years), an Australian population-based cohort study, were linked to cancer registration data to ascertain prior cancer diagnoses. Modified Poisson regression estimated age- and sex-adjusted prevalence ratios (PRs) for bodily pain and pain sufficient to interfere with daily activities (high-impact pain) in people with versus without cancer, for 13 cancer types, overall and according to clinical, personal, and health characteristics. The relation of high-impact pain to physical and mental health outcomes was quantified in people with and without cancer. RESULTS: Overall, 34.9% (5,436/15,570) of cancer survivors and 31.3% (32,471/103,604) of participants without cancer reported bodily pain (PR = 1.07 [95% CI = 1.05-1.10]), and 15.9% (2,468/15,550) versus 13.1% (13,573/103,623), respectively, reported high-impact pain (PR = 1.13 [1.09-1.18]). Pain was greater with more recent cancer diagnosis, more advanced disease, and recent cancer treatment. High-impact pain varied by cancer type; compared to cancer-free participants, PRs were: 2.23 (1.71-2.90) for multiple myeloma; 1.87 (1.53-2.29) for lung cancer; 1.06 (0.98-1.16) for breast cancer; 1.05 (0.94-1.17) for colorectal cancer; 1.04 (0.96-1.13) for prostate cancer; and 1.02 (0.92-1.12) for melanoma. Regardless of cancer diagnosis, high-impact pain was strongly related to impaired physical functioning, psychological distress, and reduced QoL. CONCLUSIONS: Pain is common, interfering with daily life in around one-in-eight older community-dwelling participants. Pain was elevated overall in cancer survivors, particularly for certain cancer types, around diagnosis and treatment, and with advanced disease. However, pain was comparable to population levels for many common cancers, including breast, prostate and colorectal cancer, and melanoma.

Fifty-year forecasts of daily smoking prevalence: can Australia reach 5% by 2030?

OBJECTIVE: To compare 50-year forecasts of Australian tobacco smoking rates in relation to trends in smoking initiation and cessation and in relation to a national target of ≤5% adult daily prevalence by 2030. METHODS: A compartmental model of Australian population daily smoking, calibrated to the observed smoking status of 229 523 participants aged 20-99 years in 26 surveys (1962-2016) by age, sex and birth year (1910-1996), estimated smoking prevalence to 2066 using Australian Bureau of Statistics 50-year population predictions. Prevalence forecasts were compared across scenarios in which smoking initiation and cessation trends from 2017 were continued, kept constant or reversed. RESULTS: At the end of the observation period in 2016, model-estimated daily smoking prevalence was 13.7% (90% equal-tailed interval (EI) 13.4%-14.0%). When smoking initiation and cessation rates were held constant, daily smoking prevalence reached 5.2% (90% EI 4.9%-5.5%) after 50 years, in 2066. When initiation and cessation rates continued their trajectory downwards and upwards, respectively, daily smoking prevalence reached 5% by 2039 (90% EI 2037-2041). The greatest progress towards the 5% goal came from eliminating initiation among younger cohorts, with the target met by 2037 (90% EI 2036-2038) in the most optimistic scenario. Conversely, if initiation and cessation rates reversed to 2007 levels, estimated prevalence was 9.1% (90% EI 8.8%-9.4%) in 2066. CONCLUSION: A 5% adult daily smoking prevalence target cannot be achieved by the year 2030 based on current trends. Urgent investment in concerted strategies that prevent smoking initiation and facilitate cessation is necessary to achieve 5% prevalence by 2030.

Solid Fuel, Secondhand Smoke, and Lung Cancer Mortality: A Prospective Cohort of 323,794 Chinese Never-Smokers.

Rationale: Household air pollution and secondhand tobacco smoke are known carcinogens for lung cancer, but large-scale estimates of the relationship with lung cancer mortality are lacking. Objectives: Using the large-scale cohort China Kadoorie Biobank, we prospectively investigated associations between these two risk factors and lung cancer death among never-smokers. Methods: The Biobank recruited 512,715 adults aged 30-79 years from 10 regions in China during 2004-2008. Self-reported never-smoking participants were followed up to December 31, 2016, with linkage to mortality data. Total duration of exposure to household air pollution was calculated from self-reported domestic solid fuel use. Exposure to secondhand tobacco smoke was ascertained using exposure at home and/or other places. Hazard ratios and 95% confidence intervals for associations between these two exposures and lung cancer death were estimated using Cox regression, adjusting for key confounders. Measurements and Main Results: There were 979 lung cancer deaths among 323,794 never-smoking participants without a previous cancer diagnosis during 10.2 years of follow-up. There was a log-linear positive association between exposure to household air pollution and lung cancer death, with a 4% increased risk per 5-year increment of exposure (hazard ratio = 1.04; 95% confidence interval = 1.01-1.06; P trend = 0.0034), and participants with 40.1-50.0 years of exposure had the highest risk compared with the never-exposed (hazard ratio = 1.53; 95% confidence interval = 1.13-2.07). The association was largely consistent across various subgroups. No significant association was found between secondhand smoke and lung cancer death. Conclusions: This cohort study provides new prospective evidence suggesting that domestic solid fuel use is associated with lung cancer death among never-smokers.

Large-Scale Population-Based Surveys Linked to Administrative Health Databases as a Source of Data on Health Utilities in Australia.

OBJECTIVES: Large-scale health surveys that contain quality-of-life instruments are a rich source of health utility data for health economic evaluations, especially when linked to routinely collected, administrative health databases. We derived health utility values for a wide range of health conditions using a large Australian cohort study linked to population-wide health databases. METHODS: Short-Form 6-Dimension utility values were calculated for 56 094 adults, aged 47+ years, in the New South Wales 45 and Up Study who completed the Social, Economic, and Environmental Factors survey (2010-2011). Mean utilities were summarized for major health conditions identified through self-report, hospital records, primary cancer notifications, and claims for government-subsidized prescription medicines and medical services. To identify unique associations between health conditions and utilities, beta regression was performed. Utility values were analyzed by time to death using linked death records. RESULTS: Mean Short-Form 6-Dimension utility was 0.810 (95% confidence interval [CI] 0.809-0.811), was age dependent, and was higher in men than women. Utilities for serious health conditions ranged from 0.685 (95% CI 0.652-0.718) for lung cancer to 0.800 (95% CI 0.787-0.812) for melanoma whereas disease-free respondents had a mean of 0.859 (95% CI 0.858-0.861). Most health conditions were independently associated with poorer quality of life. Utility values also declined by proximity to death where participants sampled 6 months before death had a mean score of 0.637 (95% CI 0.613-0.662). CONCLUSIONS: Our data offer a snapshot of the health status of an older Australian population and show that record linkage can enable comprehensive ascertainment of utility values for use in health economic modeling.

Raking of data from a large Australian cohort study improves generalisability of estimates of prevalence of health and behaviour characteristics and cancer incidence.

BACKGROUND: Health surveys are commonly somewhat non-representative of their target population, potentially limiting the generalisability of prevalence estimates for health/behaviour characteristics and disease to the population. To reduce bias, weighting methods have been developed, though few studies have validated weighted survey estimates against generally accepted high-quality independent population benchmark estimates. METHODS: We applied post-stratification and raking methods to the Australian 45 and Up Study using Census data and compared the resulting prevalence of characteristics to accepted population benchmark estimates and separately, the incidence rates of lung, colorectal, breast and prostate cancer to whole-of-population estimates using Standardised Incidence Ratios (SIRs). RESULTS: The differences between 45 and Up Study and population benchmark estimates narrowed following sufficiently-informed raking, e.g. 13.6% unweighted prevalence of self-reported fair/poor overall health, compared to 17.0% after raking and 17.9% from a population benchmark estimate. Raking also improved generalisability of cancer incidence estimates. For example, unweighted 45 and Up Study versus whole-of-population SIRs were 0.700 (95%CI:0.574-0.848) for male lung cancer and 1.098 (95%CI:1.002-1.204) for prostate cancer, while estimated SIRs after sufficiently-informed raking were 0.828 (95%CI:0.684-0.998) and 1.019 (95%CI:0.926-1.121), respectively. CONCLUSION: Raking may be a useful tool for improving the generalisability of exposure prevalence and disease incidence from surveys to the population.

Cancer incidence and cancer death in relation to tobacco smoking in a population-based Australian cohort study.

Tobacco smoke is a known carcinogen, but the magnitude of smoking-related cancer risk depends on country-specific, generational smoking patterns. We quantified cancer risk in relation to smoking in a population-based cohort, the 45 and Up Study (2006-2009) in New South Wales, Australia. Cox proportional hazards regressions estimated adjusted hazard ratios (HR) by self-reported smoking history at baseline (2006-2009) for incident, primary cancers via linkage to cancer registry data to 2013 and cancer death data to 2015. Among 229 028 participants aged ≥45 years, 18 475 cancers and 5382 cancer deaths occurred. Current-smokers had increased risks of all cancers combined (HR = 1.42, 95% confidence interval [CI], 1.34-1.51), cancers of the lung (HR = 17.66, 95%CI, 14.65-21.29), larynx (HR = 11.29, 95%CI, 5.49-23.20), head-and-neck (HR = 2.53, 95%CI, 1.87-3.41), oesophagus (HR = 3.84, 95%CI, 2.33-6.35), liver (HR = 4.07, 95%CI, 2.55-6.51), bladder (HR = 3.08, 95%CI, 2.00-4.73), pancreas (HR = 2.68, 95%CI, 1.93-3.71), colorectum (HR = 1.31, 95%CI, 1.09-1.57) and unknown primary site (HR = 3.26, 95%CI, 2.19-4.84) versus never-smokers. Hazards increased with increasing smoking intensity; compared to never-smokers, lung cancer HR = 9.22 (95%CI, 5.14-16.55) for 1-5 cigarettes/day and 38.61 (95%CI, 25.65-58.13) for >35 cigarettes/day. Lung cancer risk was lower with quitting at any age but remained higher than never-smokers for quitters aged >25y. By age 80y, an estimated 48.3% of current-smokers (41.1% never-smokers) will develop cancer, and 14% will develop lung cancer, including 7.7% currently smoking 1-5 cigarettes/day and 26.4% for >35 cigarettes/day (1.0% never-smokers). Cancer risk for Australian smokers is significant, even for 'light' smokers. These contemporary estimates underpin the need for continued investment in strategies to prevent smoking uptake and facilitate cessation, which remain key to reducing cancer morbidity and mortality worldwide.

Alcohol consumption, drinking patterns and cancer incidence in an Australian cohort of 226,162 participants aged 45 years and over.

BACKGROUND: Although overall alcohol consumption is known to increase the risk of a number of cancers internationally, evidence for Australia and evidence regarding the pattern of drinking and cancer risk is limited. METHODS: Adjusted hazard ratios (HR) and 95% confidence intervals (CI) for cancer risk in relation to overall alcohol consumption (drinks/week) and pattern of drinking were calculated using Cox proportional hazard regressions for 226,162 participants aged ≥45 years (2006-2009) in the 45 and Up Study, an Australian prospective cohort study. Incident primary cancer cases were ascertained by linkage to the New South Wales Cancer Registry to 2013 by the Centre for Health Record Linkage. RESULTS: Over a median of 5.4 years, 17,332 cancers were diagnosed. Increasing levels of alcohol intake were associated with increased risk of cancers of the upper aerodigestive tract (1.19; 1.10-1.29), mouth and pharynx (1.18; 1.08-1.29), oesophagus (1.22; 1.04-1.43), colorectum (1.09; 1.04-1.15), colon (1.13; 1.06-1.20), liver (1.22; 1.04-1.44) and breast (1.11; 1.02-1.21). Breast cancer risk was marginally associated with drinking pattern, with higher risk when intake was concentrated on 1-3 days/week compared to the same amount spread over 4-7 days (Pinteraction = 0.049). CONCLUSIONS: Alcohol consumption confers a significant risk of cancer, and drinking pattern may be independently related to breast cancer risk.

Patterns of care for men with prostate cancer: the 45 and Up Study.

OBJECTIVES: To describe patterns of care in New South Wales for men with prostate cancer, and to ascertain factors associated with receiving different types of treatment. DESIGN: Individual patient data record linkage study. SETTING, PARTICIPANTS: 4003 New South Wales men aged 45 years or more enrolled in the population-based 45 and Up Study in whom prostate cancer was first diagnosed during 2006-2013. MAIN OUTCOME MEASURES: Prostate cancer treatment type received; factors statistically associated with treatment received; proportions of patients who consulted radiation oncologists prior to treatment. RESULTS: In total, 1619 of 4003 patients underwent radical prostatectomy (40%), 893 external beam radiotherapy (EBRT) (22%), 183 brachytherapy (5%), 87 chemotherapy (2%), 373 androgen deprivation therapy alone (9%), and 848 no active treatment (21%). 205 of 1628 patients who had radical prostatectomies (13%) had radiation oncology consultations prior to surgery. Radical prostatectomy was more likely for patients aged 45-59 years, with regional stage disease, living 100 km or more from the nearest radiotherapy centre, having partners, or having private health insurance, while lower physical functioning, obesity, and living in areas of greater socio-economic disadvantage reduced the likelihood. EBRT was more likely for patients aged 70-79 years, with non-localised or unknown stage disease, living less than 100 km from the nearest radiotherapy centre, or not having private health insurance, while the likelihood was lower for patients aged 45-59 years or more than 80 years and for those who had several comorbid conditions. CONCLUSIONS: Men with prostate cancer were twice as likely to have radical prostatectomy as to receive EBRT, and fewer than one in seven had consulted radiation oncologists prior to prostatectomy. The treatment received was influenced by several socio-demographic factors. Given the treatment-specific side effects and costs, policies that affect access to different treatments for prostate cancer should be reviewed.

Lung cancer risk in never-smokers: An overview of environmental and genetic factors.

Lung cancer is the leading cause of cancer-related mortality globally, accounting for 1.8 million deaths in 2020. While the vast majority are caused by tobacco smoking, 15%-25% of all lung cancer cases occur in lifelong never-smokers. The International Agency for Research on Cancer (IARC) has classified multiple agents with sufficient evidence for lung carcinogenesis in humans, which include tobacco smoking, as well as several environmental exposures such as radon, second-hand tobacco smoke, outdoor air pollution, household combustion of coal and several occupational hazards. However, the IARC evaluation had not been stratified based on smoking status, and notably lung cancer in never-smokers (LCINS) has different epidemiological, clinicopathologic and molecular characteristics from lung cancer in ever-smokers. Among several risk factors proposed for the development of LCINS, environmental factors have the most available evidence for their association with LCINS and their roles cannot be overemphasized. Additionally, while initial genetic studies largely focused on lung cancer as a whole, recent studies have also identified genetic risk factors for LCINS. This article presents an overview of several environmental factors associated with LCINS, and some of the emerging evidence for genetic factors associated with LCINS. An increased understanding of the risk factors associated with LCINS not only helps to evaluate a never-smoker's personal risk for lung cancer, but also has important public health implications for the prevention and early detection of the disease. Conclusive evidence on causal associations could inform longer-term policy reform in a range of areas including occupational health and safety, urban design, energy use and particle emissions, and the importance of considering the impacts of second-hand smoke in tobacco control policy.

A Prospective Study of Health Conditions Related to Alcohol Consumption Cessation Among 97,852 Drinkers Aged 45 and Over in Australia.

BACKGROUND: Evidence suggests that people who develop serious health conditions are likely to cease drinking alcohol (sometimes known as "sick-quitters"). We quantified the likelihood of quitting drinking in relation to the onset of a variety of health conditions. METHODS: Odds ratios (ORs) and 95% confidence intervals (CIs) of ceasing alcohol consumption after diagnosis of 28 health conditions and 4 general indicators of health were derived from logistic regression among 97,852 drinkers aged ≥ 45 years between baseline (2006 to 2009) and median 5.3 years of follow-up in the New South Wales 45 and Up Study. Incident health conditions at follow-up were self-reported. RESULTS: At follow-up, 9.6% (n = 9,438) of drinkers had ceased drinking. Drinking cessation was significantly associated with 24 of 32 health conditions examined: 15.4% of participants with newly diagnosed diabetes quit drinking (OR for quitting vs. continuing 1.77, 95% CI: 1.60 to 1.96), 16.4% with Parkinson's disease (1.71, 1.35 to 2.17), 17.8% with poor memory (1.68, 1.43 to 1.97), 19.2% with hip fracture (1.64, 1.30 to 2.06), 14.7% with stroke (1.45, 1.27 to 1.66), 12.5% with depression (1.40, 1.26 to 1.55), 15.0% with breast cancer (1.38, 1.18 to 1.61), 12.3% with heart disease (1.34, 1.25 to 1.44), and 13.3% with osteoarthritis (1.22, 1.12 to 1.33). Strong associations with quitting were observed in those with a decline in self-rated overall health (2.93, 2.53 to 3.40) and quality of life (2.68, 2.24 to 3.21). Some health conditions not significantly associated with quitting were prostate cancer, melanoma, nonmelanoma skin cancer, hay fever, and hearing loss. Findings were generally consistent for men and women, by age group and by smoking status. CONCLUSIONS: Diagnosis with a variety of health conditions appears to prompt drinking cessation in older adults.

Identifying high risk individuals for targeted lung cancer screening: Independent validation of the PLCOm2012 risk prediction tool.

Lung cancer screening with computerised tomography holds promise, but optimising the balance of benefits and harms via selection of a high risk population is critical. PLCOm2012 is a logistic regression model based on U.S. data, incorporating sociodemographic and health factors, which predicts 6-year lung cancer risk among ever-smokers, and thus may better predict those who might benefit from screening than criteria based solely on age and smoking history. We aimed to validate the performance of PLCOm2012 in predicting lung cancer outcomes in a cohort of Australian smokers. Predicted risk of lung cancer was calculated using PLCOm2012 applied to baseline data from 95,882 ever-smokers aged ≥45 years in the 45 and Up Study (2006-2009). Predictions were compared to lung cancer outcomes captured to June 2014 via linkage to population-wide health databases; a total of 1,035 subsequent lung cancer diagnoses were identified. PLCOm2012 had good discrimination (area under the receiver-operating-characteristic-curve; AUC 0.80, 95%CI 0.78-0.81) and excellent calibration (mean and 90th percentiles of absolute risk difference between observed and predicted outcomes: 0.006 and 0.016, respectively). Sensitivity (69.4%, 95%CI, 65.6-73.0%) of the PLCOm2012 criteria in the 55-74 year age group for predicting lung cancers was greater than that using criteria based on ≥30 pack-years smoking and ≤15 years quit (57.3%, 53.3-61.3%; p < 0.0001), but specificity was lower (72.0%, 71.7-72.4% versus 75.2%, 74.8-75.6%, respectively; p < 0.0001). Targeting high risk people for lung cancer screening using PLCOm2012 might improve the balance of benefits versus harms, and cost-effectiveness of lung cancer screening.

Identifying incident colorectal and lung cancer cases in health service utilisation databases in Australia: a validation study.

BACKGROUND: Data from centralised, population-based statutory cancer registries are generally considered the 'gold standard' for confirming incident cases of cancer. When these are not available, or more current information is needed, hospital or other routinely collected population-level data may be feasible alternative sources. We aimed to determine the validity of various methods using routinely collected administrative health data for ascertaining incident cases of colorectal or lung cancer in participants from the 45 and Up Study in New South Wales (NSW), Australia. METHODS: For 266,844 participants in the 45 and Up Study (recruited 2006-2009) ascertainment of incident colorectal or lung cancers was assessed using diagnosis and treatment records in linked administrative health datasets (hospital, emergency department, Medicare and pharmaceutical claims, death records). This was compared with ascertainment via the NSW Cancer Registry (NSWCR, the 'gold standard') for a period for which both data sources were available for participants. RESULTS: A total of 2253 colorectal and 1019 lung cancers were recorded for study participants in the NSWCR over the period 2006-2010. A diagnosis of primary cancer recorded in the statewide Admitted Patient Data Collection identified the majority of NSWCR colorectal and lung cancers, with sensitivities and positive predictive values (PPV) of 95% and 91% for colorectal cancer and 81% and 85% for lung cancer, respectively. Using additional information on lung cancer deaths from death records increased sensitivity to 84% (PPV 83%) for lung cancer, but did not improve ascertainment of colorectal cancers. Hospital procedure codes for colorectal cancer surgery identified cases with sensitivity 81% and PPV 54%. No other individual indicator had sensitivity >50% or PPV >65% for either cancer type and no combination of indicators increased both the sensitivity and PPV above that achieved using the hospital cancer diagnosis data. All specificities were close to 100%; 95% confidence intervals for sensitivity and PPV were generally +/-2%. CONCLUSIONS: In NSW, identifying new cases of colorectal and lung cancer from administrative health datasets, such as hospital records, is a feasible alternative when cancer registry data are not available. However, the strengths and limitations of the different data sources should be borne in mind.

Widening socioeconomic disparity in lung cancer incidence among men in New South Wales, Australia, 1987-2011.

OBJECTIVE: We assessed the trends in lung cancer incidence over a 25-year period by socioeconomic groups for men in New South Wales (NSW), Australia. METHODS: Men diagnosed with lung cancer between 1987 and 2011 were divided into five quintiles according to an Index of Education and Occupation (IEO). We assessed relative socioeconomic differences over time by calculating age-standardized incidence ratios (SIRs) by 5-year period of diagnosis, and estimated absolute differences by comparing the observed and expected numbers of cases using the highest IEO quintile as the reference. RESULTS: Lung cancer incidence for men decreased from 1987 to 2011 for all IEO quintiles, with a greater rate of decline for men living in the highest IEO areas. Thus, the relative disparity increased significantly over the 25-year period (P=0.0006). For example, the SIR for the lowest IEO quintile increased from 1.28 during 1987-1991 to 1.74 during 2007-2011. Absolute differences also increased with the proportion of " potentially preventable" cases doubling from 14.5% in 1987-1991 to 30.2% in 2007-2011. CONCLUSIONS: Despite the overall decline in lung cancer incidence among men in NSW over the past 25 years, there was a significant increase in disparity across socioeconomic areas in both relative and absolute terms.

Tobacco smoking and all-cause mortality in a large Australian cohort study: findings from a mature epidemic with current low smoking prevalence.

BACKGROUND: The smoking epidemic in Australia is characterised by historic levels of prolonged smoking, heavy smoking, very high levels of long-term cessation, and low current smoking prevalence, with 13% of adults reporting that they smoked daily in 2013. Large-scale quantitative evidence on the relationship of tobacco smoking to mortality in Australia is not available despite the potential to provide independent international evidence about the contemporary risks of smoking. METHODS: This is a prospective study of 204,953 individuals aged ≥45 years sampled from the general population of New South Wales, Australia, who joined the 45 and Up Study from 2006-2009, with linked questionnaire, hospitalisation, and mortality data to mid-2012 and with no history of cancer (other than melanoma and non-melanoma skin cancer), heart disease, stroke, or thrombosis. Hazard ratios (described here as relative risks, RRs) for all-cause mortality among current and past smokers compared to never-smokers were estimated, adjusting for age, education, income, region of residence, alcohol, and body mass index. RESULTS: Overall, 5,593 deaths accrued during follow-up (874,120 person-years; mean: 4.26 years); 7.7% of participants were current smokers and 34.1% past smokers at baseline. Compared to never-smokers, the adjusted RR (95% CI) of mortality was 2.96 (2.69-3.25) in current smokers and was similar in men (2.82 (2.49-3.19)) and women (3.08 (2.63-3.60)) and according to birth cohort. Mortality RRs increased with increasing smoking intensity, with around two- and four-fold increases in mortality in current smokers of ≤14 (mean 10/day) and ≥25 cigarettes/day, respectively, compared to never-smokers. Among past smokers, mortality diminished gradually with increasing time since cessation and did not differ significantly from never-smokers in those quitting prior to age 45. Current smokers are estimated to die an average of 10 years earlier than non-smokers. CONCLUSIONS: In Australia, up to two-thirds of deaths in current smokers can be attributed to smoking. Cessation reduces mortality compared with continuing to smoke, with cessation earlier in life resulting in greater reductions.

Co-occurrence of chronic disease lifestyle risk factors in middle-aged and older immigrants: A cross-sectional analysis of 264,102 Australians.

BACKGROUND: The way in which lifestyle risk factors for chronic disease co-occur among people with different cultural backgrounds is largely unknown. METHODS: This study investigated chronic disease risk among immigrants aged ≥45 years in Australia by combining common lifestyle risk factors into a weighted chronic disease risk index (CDRI). Among 64,194 immigrants and 199,908 Australian-born participants in the 45 and Up Study (2006-2009), Poisson regression was used to derive relative risks (RR) and 95% confidence intervals (CI) for five risk factors (smoking, alcohol use, overweight/obesity, physical activity, diet) by place of birth adjusting for socio-demographic characteristics. Multiple linear regression was used to determine adjusted mean differences (AMDs) in CDRI score by place of birth and years lived in Australia. RESULTS: Immigrants had higher RRs of smoking than Australian-born participants, lower RRs of excessive alcohol consumption and overweight/obesity, and no difference in RR for physical inactivity and insufficient fruit/vegetable intake. Participants born in the Middle East/North Africa (AMD 3.5, 95% CI 2.7, 4.3), Eastern/Central Europe (1.3, 0.8, 1.9), and Western Europe (0.5, 0.1, 0.8) had higher mean CDRI scores than Australian-born participants, while participants born in East Asia (-7.2, -7.8, -6.6), Southeast Asia (-6.6, -7.2, -6.1), Central/South Asia (-3.1, -4.0, -2.1), Sub-Saharan Africa (-1.9, -2.6, -1.2) and the United Kingdom/Ireland (-0.2, -0.5, 0.0) had lower scores. CDRI score among immigrants generally approximated that of Australian-born participants with greater years lived in Australia. CONCLUSIONS: This study reveals differences in potential risk of chronic disease among different immigrant groups in Australia.

Colorectal cancer screening and subsequent incidence of colorectal cancer: results from the 45 and Up Study.

OBJECTIVE: To investigate the association of colorectal cancer (CRC) screening history and subsequent incidence of CRC in New South Wales, Australia. DESIGN, SETTING AND PARTICIPANTS: A total of 196,464 people from NSW recruited to the 45 and Up Study, a large Australian population-based prospective study, by completing a baseline questionnaire distributed from January 2006 to December 2008. Individuals without pre-existing cancer were followed for a mean of 3.78 years (SD, 0.92 years) through linkage to population health datasets. MAIN OUTCOME MEASURES: Incidence of CRC; hazard ratio (HR) according to screening history, adjusted for age, sex, body mass index, income, education, remoteness, family history, aspirin use, smoking, diabetes, alcohol use, physical activity and dietary factors. RESULTS: Overall, 1096 cases of incident CRC accrued (454 proximal colon, 240 distal colon, 349 rectal and 53 unspecified cancers). Ever having undergone CRC screening before baseline was associated with a 44% reduced risk of developing CRC during follow-up (HR, 0.56; 95% CI, 0.49-0.63) compared with never having undergone screening. This effect was more pronounced for those reporting endoscopy (HR, 0.50; 95% CI, 0.43-0.58) than those reporting faecal occult blood testing (FOBT) (HR, 0.61; 95% CI, 0.52-0.72). Associations for all screening exposures were strongest for rectal cancer (HR, 0.35; 95% CI, 0.27-0.45) followed by distal colon cancer (HR, 0.60; 95% CI, 0.46-0.78), while relationships were weaker for cancers of the proximal colon (HR, 0.76; 95% CI, 0.62-0.92). CONCLUSION: CRC incidence is lower among individuals with a history of CRC screening, through either FOBT or endoscopy, compared with individuals who have never had CRC screening, lasting for at least 4 years after screening.