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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. [ABSTRACT FROM AUTHOR]

• Quality of life (QOL) is commonly considered in evaluations of health policies. • Evaluations of screening can be biased by overestimating pre-screening QOL. • Lung screening selects people with poorer QOL due to past smoking. • QOL does not differ between proposed lung cancer screening selection criteria. 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. 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 PLCO m2012 risk tool. 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 PLCO m2012 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). 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. [ABSTRACT FROM AUTHOR]

• Assumptions about quality-of-life (QOL) varied across evaluations of lung screening. • Assumptions about QOL impact lung screening evaluation results. • Lung cancer utilities should be appropriately sourced and calculated. • Utilities for screening participants should reflect people with heavy tobacco use. • Recovery from lung cancer treatment and ageing should be considered. Lung cancer screening with low-dose computed tomography (LDCT) in high-risk populations has been shown in randomised controlled trials to lead to early diagnosis and reduced lung cancer mortality. However, investment into screening will largely depend on the outcomes of cost-effectiveness analyses that demonstrate acceptable costs for every quality-adjusted life year (QALY) gained. The methods used to apply utility values to measure QALYs can significantly impact the outcomes of cost-effectiveness analyses and if applied inaccurately can lead to unreliable estimates. We reviewed the use of utility values in 26 cost-effectiveness analyses of lung screening with LDCT conducted between 2005 and 2021, and found considerable variation in methods. Specifically, authors made different assumptions made relating to (i) baseline quality-of-life among screening participants, (ii) potential harms from screening, (iii) utilities and disutilities applied to lung cancer health states, and (iv) quality-of-life for lung cancer survivors. We discuss how each of these assumptions can influence incremental cost-effectiveness ratios. Key recommendations for future evaluations are (i) that modelling studies should justify the choice of baseline utilities, especially if patients are assumed to recover fully after curative treatment; (ii) the impact of false positive scans on quality-of-life should be modelled, at least in sensitivity analyses; (iii) modellers should justify assumptions relating to post-operative recovery, preferably based on knowledge of local practices; (iv) utilities applied to a lung cancer diagnosis should be appropriately sourced and calculated; and (v) adjustment for age-related declines in quality-of-life should be considered, especially for models that examine lifetime horizons. [ABSTRACT FROM AUTHOR]

• Using the PLCOm2012 risk model saves costs and improves outcomes compared with age-smoking history categorical methods. • The risk model mitigated gender-based and socioeconomic disparities in access to lung screening. • The PLCOm2012 risk model was most cost-effective for females and at a 1.5 %/6 year threshold for both sexes. • Our findings call for deeper inquiry into screening eligibility processes through a sex and gender plus-based lens. 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). 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). 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). The PLCOm2012 model saved costs, increased QALYs and mitigated socioeconomic and sex-based disparities in access to screening. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer is the third most diagnosed cancer globally and the second leading cause of cancer death. We examined colon and rectal cancer treatment patterns in Australia. Methods: From cancer registry records, we identified 1,236 and 542 people with incident colon and rectal cancer, respectively, diagnosed during 2006-2013 in the 45 and Up Study cohort (267,357 participants). Cancer treatment and deaths were determined via linkage to routinely collected data, including hospital and medical services records. For colon cancer, we examined treatment categories of "surgery only", "surgery plus chemotherapy", "other treatment" (i.e. other combinations of surgery/chemotherapy/radiotherapy), "no record of cancer-related treatment, died"; and, for rectal cancer, "surgery only", "surgery plus chemotherapy and/or radiotherapy", "other treatment", and "no record of cancer-related treatment, died". We analysed survival, time to first treatment, and characteristics associated with treatment receipt using competing risks regression. Results: 86.4% and 86.5% of people with colon and rectal cancer, respectively, had a record of receiving any treatment ≤2 years post-diagnosis. Of those treated, 93.2% and 90.8% started treatment ≤2 months post-diagnosis, respectively. Characteristics significantly associated with treatment receipt were similar for colon and rectal cancer, with strongest associations for spread of disease and age at diagnosis (p<0.003). For colon cancer, the rate of "no record of cancer-related treatment, died" was higher for people with distant spread of disease (versus localised, subdistribution hazard ratio (SHR)=13.6, 95% confidence interval (CI):5.5-33.9), age ≥75 years (versus age 45-74, SHR=3.6, 95%CI:1.8-7.1), and visiting an emergency department ≤1 month pre-diagnosis (SHR=2.9, 95%CI:1.6-5.2). For rectal cancer, the rate of "surgery plus chemotherapy and/or radiotherapy" was higher for people with regional spread of disease (versus localised, SHR=5.2, 95%CI:3.6-7.7) and lower for people with poorer physical functioning (SHR=0.5, 95%CI:0.3-0.8) or no private health insurance (SHR=0.7, 95%CI:0.5-0.9). Conclusion: Before the COVID-19 pandemic, most people with colon or rectal cancer received treatment ≤2 months post-diagnosis, however, treatment patterns varied by spread of disease and age. This work can be used to inform future healthcare requirements, to estimate the impact of cancer control interventions to improve prevention and early diagnosis, and serve as a benchmark to assess treatment delays/disruptions during the pandemic. Future work should examine associations with clinical factors (e.g. performance status at diagnosis) and interdependencies between characteristics such as age, comorbidities, and emergency department visits. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]