Impact of weighting on the association between sociodemographic characteristics, health behaviours and cancer, cardiovascular and all-cause mortality in the Australian 45 and Up Study.

BACKGROUND: Weighting can improve study estimate representativeness. We examined the impact of weighting on associations between participants' characteristics and cancer, cardiovascular and all-cause mortality in the Australian 45 and Up Study cohort. METHODS: Raking weighted cohort data to the 2006 Australian population for seven sociodemographic characteristics. Deaths were ascertained via linkage to routinely collected data. Cox's proportional hazards regression quantified associations between 11 sociodemographic and health characteristics and cancer, cardiovascular and all-cause mortality. The ratios of hazard ratios (RHRs) compared unweighted and weighted estimates. RESULTS: Among 195,052 included participants (median follow-up 11.4 years), there were 7200 cancer, 5912 cardiovascular and 21,840 all-cause deaths. Overall, 102/111 (91.9%) weighted HRs did not differ significantly from unweighted HRs (100%, 86.5% and 89.2% of 37 HRs for cancer, cardiovascular and all-cause mortality, respectively). Significant differences included a somewhat stronger association between single/widowed/divorced (versus married/de-facto) and cardiovascular mortality (unweighted HR=1.25 (95%CI:1.18-1.32), weighted HR=1.33 (95%CI:1.24-1.42), RHR=1.06 (95%CI:1.02-1.11)); and between no school certificate/qualification (versus university degree) and all-cause mortality (unweighted HR=1.21 (95%CI:1.15-1.27), weighted HR=1.28 (95%CI:1.19-1.38), RHR=1.06 (95%CI:1.03-1.10)). CONCLUSION: Our results support the generalisability of most estimates of associations in the 45 and Up Study, particularly in relation to cancer mortality. Slight distortion of a few associations with cardiovascular or all-cause mortality were observed.

Development and Validation of txSim: A Model of Advanced Lung Cancer Treatment in Australia.

BACKGROUND AND OBJECTIVE: Since 2016, new therapies have transformed the standard of care for lung cancer, creating a need for up-to-date evidence for health economic modelling. We developed a discrete event simulation of advanced lung cancer treatment to provide estimates of survival outcomes and healthcare costs in the Australian setting that can be updated as new therapies are introduced. METHODS: Treatment for advanced lung cancer was modelled under a clinician-specified treatment algorithm for Australia in 2022. Prevalence of lung cancer subpopulations was extracted from cBioPortal and the Sax Institute's 45 and Up Study, a large prospective cohort linked to cancer registrations. All costs were from the health system perspective for the year 2020. Pharmaceutical and molecular diagnostic costs were obtained from public reimbursement fees, while other healthcare costs were obtained from health system costs in the 45 and Up Study. Treatment efficacy was obtained from clinical trials and observational study data. Costs and survival were modelled over a 10-year horizon. Uncertainty intervals were generated with probabilistic sensitivity analyses. Overall survival predictions were validated against real-world studies. RESULTS: Under the 2022 treatment algorithm, estimated mean survival and costs for advanced lung cancer 10 years post-diagnosis were 16.4 months (95% uncertainty interval [UI]: 14.7-18.1) and AU$116,069 (95% UI: $107,378-$124,933). Survival and costs were higher assuming optimal treatment utilisation rates (20.5 months, 95% UI: 19.1-22.5; $154,299, 95% UI: $146,499-$161,591). The model performed well in validation, with good agreement between predicted and observed survival in real-world studies. CONCLUSIONS: Survival improvements for advanced lung cancer have been accompanied by growing treatment costs. The estimates reported here can be used for budget planning and economic evaluations of interventions across the spectrum of cancer control.

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.

Economic impact of using risk models for eligibility selection to the International lung screening Trial.

OBJECTIVES: Using risk models as eligibility criteria for lung screening can reduce race and sex-based disparities. We used data from the International Lung Screening Trial(ILST; NCT02871856) to compare the economic impact of using the PLCOm2012 risk model or the US Preventative Services' categorical age-smoking history-based criteria (USPSTF-2013). MATERIALS AND METHODS: The cost-effectiveness of using PLCOm2012 versus USPSTF-2013 was evaluated with a decision analytic model based on the ILST and other screening trials. The primary outcomes were costs in 2020 International Dollars ($), quality-adjusted life-years (QALY) and incremental net benefit (INB, in $ per QALY). Secondary outcomes were selection characteristics and cancer detection rates (CDR). RESULTS: Compared with the USPSTF-2013 criteria, the PLCOm2012 risk model resulted in $355 of cost savings per 0.2 QALYs gained (INB=$4294 at a willingness-to-pay threshold of $20 000/QALY (95 %CI: $4205-$4383). Using the risk model was more cost-effective in females at both a 1.5 % and 1.7 % 6-year risk threshold (INB=$6616 and $6112, respectively), compared with males ($5221 and $695). The PLCOm2012 model selected more females, more individuals with fewer years of formal education, and more people with other respiratory illnesses in the ILST. The CDR with the risk model was higher in females compared with the USPSTF-2013 criteria (Risk Ratio = 7.67, 95 % CI: 1.87-31.38). CONCLUSION: The PLCOm2012 model saved costs, increased QALYs and mitigated socioeconomic and sex-based disparities in access to screening.

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.

Health utilities for participants in a population-based sample who meet eligibility criteria for lung cancer screening.

INTRODUCTION: Trial-based, risk-targeted lung cancer screening with low-dose computed tomography has been shown to reduce lung cancer mortality but implementation may depend on favourable cost-effectiveness evaluations where quality-adjusted life-years are a key metric. Baseline health utility values for a screening population at high risk of lung cancer are not likely to match age-specific population norms, and utilities derived from screening trials may not be representative of real-world screening populations. We estimated utility values for screening-eligible individuals in a population-based cohort study in Australia. METHODS: Cancer-free participants aged 50-80 years in the New South Wales 45 and Up Study completed the 12-Item Short Form Survey (2010-2011). Mean SF-6D utility values were calculated for 19,991 participants and compared across screening criteria defined by the US Preventive Services Task Force (USPSTF-2021/2013), NELSON trial eligibility, and the PLCOm2012 risk tool. RESULTS: Mean SF-6D utility values were comparable across screening criteria: USPSTF-2021, 0.772 (95%CI, 0.768-0.776); USPSTF-2013, 0.764 (95%CI, 0.759-0.770); NELSON, 0.768 (95%CI, 0.763-0.774), and were each lower than among ineligible participants (0.810-0.814). While there was a decline in utilities with increasing risk of lung cancer as measured with the PLCOm2012 risk tool, mean utility values for those with ≥ 1.51% 6-year risk did not differ to other criteria (0.772, 95%CI, 0.767-0.776). CONCLUSION: Risk criteria are necessary for the efficiency of lung cancer screening programs, but they select populations with lower mean health utilities than population norms. We provide baseline values that can be used in cost-effectiveness evaluations of risk-targeted lung cancer screening.

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.

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.

Birth-cohort estimates of smoking initiation and prevalence in 20th century Australia: Synthesis of data from 33 surveys and 385,810 participants.

The aim of our study was to quantify sex-specific patterns of smoking prevalence and initiation in 10-year birth cohorts from 1910 to 1989 in Australia. We combined individual data of 385,810 participants from 33 cross-sectional surveys conducted between 1962 and 2018. We found that age-specific smoking prevalence varied considerably between men and women within birth cohorts born before 1960. The largest difference was observed in the earliest cohort (1910-1919), with up to 37.7% point greater proportion of current smokers in men than in women. In subsequent cohorts, the proportion decreased among men, but increased among women, until there was no more than 7.4% point difference in the 1960-69 birth cohort. In the 1970-79 and 1980-89 cohorts, smoking among men marginally increased, but the proportion was at most ~11.0% points higher than women. Our analysis of initiation indicated that many women born before the 1930s who smoked commenced smoking after age 25 years (e.g., ~27% born in 1910-19); compared to at most 8% of men in any birth cohort. The earliest birth cohort (1910-1919) had the greatest difference in age at initiation between sexes; 26.6 years in women versus 19.0 in men. In later cohorts, male and female smokers initiated increasingly earlier, converging in the 1960-69 cohort (17.6 and 17.8 years, respectively). While 22.9% of men and 8.4% of women initiated smoking aged < = 15 in the 1910-1919 cohort, in the latest cohort (1980-89) the reverse was true (21.4% and 28.8% for men and women, respectively). Marked differences in smoking prevalence and age at initiation existed between birth cohorts of Australian men and women born before 1960; after this, sex-specific trends in prevalence and initiation were similar. Understanding these patterns may inform the evaluation of tobacco control policies and the targeting of potential interventions for exposed populations such as lung cancer screening.

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.

Benefits, harms and cost-effectiveness of cancer screening in Australia: an overview of modelling estimates.

INTRODUCTION: There are three government-funded population-based screening programs in Australia - the national breast cancer screening program (BreastScreen Australia), the National Cervical Screening Program (NCSP), and the National Bowel Cancer Screening Program (NBCSP). Options for early detection of other cancers (e.g. hepatocellular carcinoma and melanoma) are under investigation. This study provides an overview of the health benefits, harms and cost-effectiveness of population-level breast, cervical and colorectal cancer screening, targeted-risk screening for lung cancer and Lynch syndrome, and prostate specific antigen (PSA) testing in Australia. METHODS: The study reviewed and, where possible, updated the estimated health benefits, harms and cost-effectiveness of screening approaches from modelling studies for four cancer types, PSA testing and Lynch syndrome testing in Australia. Costs are presented in 2018 Australian dollars. RESULTS: The renewed NCSP (for women not HPV-vaccinated) and the NBCSP were estimated to be cost-effective versus no screening; the cost-effectiveness ratio (CER) was $16 632 per life-year saved (LYS) for the NCSP, and $3380/LYS for the NBCSP. BreastScreen Australia was predicted to have a CER of $40 279/LYS-$65 065/LYS. In 2017, the NCSP transitioned to 5-yearly primary HPV testing with partial genotyping for HPV types 16 and 18 for women aged 25-74 years. Alongside vaccination, this change is predicted to prevent a further 587 cervical cancer deaths in 2018-2035, and have a favourable benefit-to-harm balance versus prior practice (biennial cytology testing for women aged 18-69 years). On average, the NBCSP (biennial screening using an immunochemical faecal occult blood test for people aged 50-74 years) is estimated to prevent 2519 colorectal cancer deaths and result in 350 colonoscopy-related adverse events annually. The inaccuracy of PSA testing as a screening tool impedes the capacity to conduct meaningful cost-effectiveness analyses at a population level, based on current evidence. Three annual low-dose computed tomography screens for lung cancer using the US National Lung Screening Trial selection criteria would not be cost-effective in Australia. A comprehensive cost-effectiveness evaluation of systematic proband testing, cascade testing and subsequent surveillance for Lynch syndrome in Australia is currently underway. CONCLUSIONS: Current evidence supports a favourable cost-effectiveness and benefit-to-harm balance for the NCSP and NBCSP. An updated cost-effectiveness and benefits-to-harms analysis for BreastScreen Australia is required. Carefully founded quantitative estimates of health benefits, harms and cost-effectiveness provide an important aid to policy decision making, and form the basis for developing decision aids to guide individual screening decisions. Opportunities exist for lung cancer screening, systematic Lynch syndrome testing and informed decision making about PSA testing. However, more evidence is required on risk assessment, targeting of screening tests, optimal referral pathways, managing potential harms and delivering services in a cost-effective framework.

Statistical projection methods for lung cancer incidence and mortality: a systematic review.

OBJECTIVES: To identify and summarise all studies using statistical methods to project lung cancer incidence or mortality rates more than 5 years into the future. STUDY TYPE: Systematic review. METHODS: We performed a systematic literature search in multiple electronic databases to identify studies published from 1 January 1988 to 14 August 2018, which used statistical methods to project lung cancer incidence and/or mortality rates. Reference lists of relevant articles were checked for additional potentially relevant articles. We developed an organisational framework to classify methods into groups according to the type of data and the statistical models used. Included studies were critically appraised using prespecified criteria. RESULTS: One hundred and one studies met the inclusion criteria; six studies used more than one statistical method. The number of studies reporting statistical projections for lung cancer increased substantially over time. Eighty-eight studies used projection methods, which did not incorporate data on smoking in the population, and 16 studies used a method which did incorporate data on smoking. Age-period-cohort models (44 studies) were the most commonly used methods, followed by other generalised linear models (35 studies). The majority of models were developed using observed rates for more than 10 years and used data that were considered to be good quality. A quarter of studies provided comparisons of fitted and observed rates. While validation by withholding the most recent observed data from the model and then comparing the projected and observed rates for the most recent period provides important information on the model's performance, only 12 studies reported doing this. CONCLUSION: This systematic review provides an up-to-date summary of the statistical methods used in published lung cancer incidence or mortality projections. The assessment of the strengths of existing methods will help researchers to better apply and develop statistical methods for projecting lung cancer rates. Some of the common methods described in this review can be applied to the projection of rates for other cancer types or other non-infectious diseases.

Lung cancer mortality in Australia in the twenty-first century: How many lives can be saved with effective tobacco control?

OBJECTIVES: To estimate the number of past and future lung cancer deaths that have already been averted by tobacco control initiatives in Australia, and to estimate the number of additional deaths averted under various smoking scenarios. METHODS: We predicted lung cancer mortality rates and case numbers to 2100 using a previously validated generalized linear model based on age, birth cohort and population cigarette smoking exposure. We estimated the impact of various tobacco control scenarios: 'actual tobacco control' (incorporating the aggregate effect of past and current taxation, plain packaging, mass media campaigns and other initiatives) and scenarios where 10%, 5% and 0% smoking prevalence was achieved by 2025, all of which were compared to a counterfactual scenario with the highest historical smoking consumption level continuing into the future as if no tobacco control initiatives had been implemented. RESULTS: Without tobacco control, there would have been an estimated 392,116 lung cancer deaths over the period 1956-2015; of these 20% (78,925 deaths; 75,839 males, 3086 females) have been averted due to tobacco control. However, if past and current measures continue to have the expected effect, an estimated 1.9 million deaths (1,579,515 males, 320,856 females; 67% of future lung cancer deaths) will be averted in 2016-2100. If smoking prevalence is reduced to 10%, 5% or 0% by 2025, an additional 97,432, 208,714 or 360,557 deaths could be averted from 2016 to 2100, respectively. CONCLUSION: Tobacco control in Australia has had a dramatic impact on the number of people dying from lung cancer. Several hundred thousand more lung cancer deaths could be averted over the course of the century if close-to-zero smoking prevalence could be achieved in the next decade.

Lung cancer mortality in Australia: Projected outcomes to 2040.

OBJECTIVES: The aim was to develop and validate a statistical model which uses past trends for lung cancer mortality and historical and current data on tobacco consumption to project lung cancer mortality rates into the future for Australia. METHODS: We used generalized linear models (GLMs) with Poisson distribution including either age, birth cohort or period, and/or various measures of population tobacco exposure (considering cross-sectional smoking prevalence, cigarettes smoked and tar exposure per capita). Sex-specific models were fitted to data for 1956-2015 and age-standardized lung cancer mortality rates were projected forward to 2040. Possible lags of 20-30 years between tobacco exposure and lung cancer mortality were examined. The best model was selected using analysis of deviance. To validate the selected model, we temporarily re-fitted it to data for 1956-1990 and compared the projected rates to 2015 with the observed rates for 1991-2015. RESULTS: The best fitting model used information on age, birth cohort and tar exposure per capita; close concordance with the observed data was achieved in the validation. The forward projections for lung cancer mortality using this model indicate that male and female age-standardized rates will decline over the period 2011-2015 to 2036-2040 from 27.2 to 15.1 per 100,000, and 15.8 to 11.8 per 100,000, respectively. However, due to population growth and ageing the number of deaths will increase by 7.9% for males and 57.9% for females; from 41,040 (24,831 males, 16,209 females) in 2011-2015 to 52,403 (26,805 males, 25,598 females) in 2036-2040. CONCLUSION: In the context of the mature tobacco epidemic with past peaks in tobacco consumption for both males and females, lung cancer mortality rates are expected to continually decline over the next 25 years. However, the number of lung cancer deaths will continue to be substantial, and to increase, in Australia's ageing population.

Estimating the Cost-Effectiveness of Lung Cancer Screening with Low-Dose Computed Tomography for High-Risk Smokers in Australia.

INTRODUCTION: Health economic evaluations of lung cancer screening with low-dose computed tomography (LDCT) that are underpinned by clinical outcomes are relatively few. METHODS: We assessed the cost-effectiveness of LDCT lung screening in Australia by applying Australian cost and survival data to the outcomes observed in the U.S. National Lung Screening Trial (NLST), in which a 20% lung cancer mortality benefit was demonstrated for three rounds of annual screening among high-risk smokers age 55 to 74 years. Screening-related costs were estimated from Medicare Benefits Schedule reimbursement rates (2015), lung cancer diagnosis and treatment costs from a 2012 Australian hospital-based study, lung cancer survival rates from the New South Wales Cancer Registry (2005-2009), and other-cause mortality from Australian life tables weighted by smoking status. The health utility outcomes, screening participation rates, and lung cancer rates were those observed in the NLST. Incremental cost effectiveness ratios (ICER) were calculated for a 10-year time horizon. RESULTS: The cost-effectiveness of LDCT lung screening was estimated at AU$138,000 (80% confidence interval: AU$84,700-AU$353,000)/life-year gained and AU$233,000 (80% confidence interval: AU$128,000-AU$1,110,000)/quality-adjusted life year (QALY) gained. The ICER was more favorable when LDCT screening impact on all-cause mortality was considered, even when the costs of incidental findings were also estimated in sensitivity analyses: AU$157,000/QALY gained. This can be compared to an indicative willingness-to-pay threshold in Australia of AU$30,000 to AU$50,000/QALY. CONCLUSIONS: LDCT lung screening using NLST selection and implementation criteria is unlikely to be cost-effective in Australia. Future economic evaluations should consider alternative screening eligibility criteria, intervals, nodule management, the impact and cost of new therapies, investigations of incidental findings, and incorporation of smoking cessation interventions.

The extracellular matrix, p53 and estrogen compete to regulate cell-surface Fas/Apo-1 suicide receptor expression in proliferating embryonic cerebral cortical precursors, and reciprocally, Fas-ligand modifies estrogen control of cell-cycle proteins.

BACKGROUND: Apoptosis is important for normal cerebral cortical development. We previously showed that the Fas suicide receptor was expressed within the developing cerebral cortex, and that in vitro Fas activation resulted in caspase-dependent death. Alterations in cell-surface Fas expression may significantly influence cortical development. Therefore, in the following studies, we sought to identify developmentally relevant cell biological processes that regulate cell-surface Fas expression and reciprocal consequences of Fas receptor activation. RESULTS: Flow-cytometric analyses identified two distinct neural sub-populations that expressed Fas on their cell surface at high (FasHi) or moderate (FasMod) levels. The anti-apoptotic protein FLIP further delineated a subset of Fas-expressing cells with potential apoptosis-resistance. FasMod precursors were mainly in G0, while FasHi precursors were largely apoptotic. However, birth-date analysis indicated that neuroblasts express the highest levels of cell-surface Fas at the end of S-phase, or after their final round of mitosis, suggesting that Fas expression is induced at cell cycle checkpoints or during interkinetic nuclear movements. FasHi expression was associated with loss of cell-matrix adhesion and anoikis. Activation of the transcription factor p53 was associated with induction of Fas expression, while the gonadal hormone estrogen antagonistically suppressed cell-surface Fas expression. Estrogen also induced entry into S-phase and decreased the number of Fas-expressing neuroblasts that were apoptotic. Concurrent exposure to estrogen and to soluble Fas-ligand (sFasL) suppressed p21/waf-1 and PCNA. In contrast, estrogen and sFasL, individually and together, induced cyclin-A expression, suggesting activation of compensatory survival mechanisms. CONCLUSIONS: Embryonic cortical neuronal precursors are intrinsically heterogeneous with respect to Fas suicide-sensitivity. Competing intrinsic (p53, cell cycle, FLIP expression), proximal (extra-cellular matrix) and extrinsic factors (gonadal hormones) collectively regulate Fas suicide-sensitivity either during neurogenesis, or possibly during neuronal migration, and may ultimately determine which neuroblasts successfully contribute neurons to the differentiating cortical plate.