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Aim: Systemic therapies for lung cancer are rapidly evolving. This study aimed to describe lung cancer treatment patterns in New South Wales, Australia, prior to the introduction of immunotherapy and latest‐generation targeted therapies. Methods: Systemic therapy utilization and treatment‐related factors were examined for participants in the New South Wales 45 and Up Study with incident lung cancer ascertained by record linkage to the New South Wales Cancer Registry (2006–2013). Systemic therapy receipt to June 2016 was determined using medical and pharmaceutical claims data from Services Australia, and in‐patient hospital records. Factors related to treatment were identified using competing risks regressions. Results: A total of 1,116 lung cancer cases were identified with a mean age at diagnosis of 72 years and median survival of 10.6 months. Systemic therapy was received by 45% of cases. Among 400 cases with metastatic non–small cell lung cancer, 51% and 28% received first‐ and second‐line systemic therapy, respectively. Among 112 diagnosed with small‐cell lung cancer, 79% and 29% received first‐ and second‐line systemic therapy. The incidence of systemic therapy was lower for participants with indicators of poor performance status, lower educational attainment, and those who lived in areas of socioeconomic disadvantage; and was higher for participants with small‐cell lung cancer histology or higher body mass index. Conclusion: This population‐based Australian study identified patterns of systemic therapy use for lung cancer, particularly small‐cell lung cancer. Despite a universal healthcare system, the analysis revealed socioeconomic disparities in health service utilization and relatively low utilization of systemic therapy overall. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Of all cancer types, healthcare for lung cancer is the third most costly in Australia, but there is little detailed information about these costs. Our aim was to provide detailed population-based estimates of health system costs for lung cancer care, as a benchmark prior to wider availability of targeted therapies/immunotherapy and to inform cost-effectiveness analyses of lung cancer screening and other interventions in Australia. Methods: Health system costs were estimated for incident lung cancers in the Australian 45 and Up Study cohort, diagnosed between recruitment (2006–2009) and 2013. Costs to June 2016 included services reimbursed via the Medicare Benefits Schedule, medicines reimbursed via the Pharmaceutical Benefits Scheme, inpatient hospitalisations, and emergency department presentations. Costs for cases and matched, cancer-free controls were compared to derive excess costs of care. Costs were disaggregated by patient and tumour characteristics. Data for more recent cases identified in hospital records provided preliminary information on targeted therapy/immunotherapy. Results: 994 eligible cases were diagnosed with lung cancer 2006–2013; 51% and 74% died within one and three years respectively. Excess costs from one-year pre-diagnosis to three years post-diagnosis averaged ~$51,900 per case. Observed costs were higher for cases diagnosed at age 45–59 ($67,700) or 60–69 ($63,500), and lower for cases aged ≥80 ($29,500) and those with unspecified histology ($31,700) or unknown stage ($36,500). Factors associated with lower costs generally related to shorter survival: older age (p<0.0001), smoking (p<0.0001) and unknown stage (p = 0.002). There was no evidence of differences by year of diagnosis or sex (both p>0.50). For 465 cases diagnosed 2014–2015, 29% had subsidised molecular testing for targeted therapy/immunotherapy and 4% had subsidised targeted therapies. Conclusions: Lung cancer healthcare costs are strongly associated with survival-related factors. Costs appeared stable over the period 2006–2013. This study provides a framework for evaluating the health/economic impact of introducing lung cancer screening and other interventions in Australia. [ABSTRACT FROM AUTHOR]

Introduction Little is known about population-wide emergency presentations and patterns of care for people diagnosed with non-small cell lung cancer (NSCLC) in Australia. We examined patients’ characteristics associated with presenting to an emergency department around the time of diagnosis (“emergency presenters”), and receiving anti-cancer treatment within 12 months of diagnosis. Materials and Methods Participants in the 45 and Up Study who were newly diagnosed with NSCLC during 2006–2010 were included. We used linked data from population-wide health databases including Medicare and pharmaceutical claims, inpatient hospitalisations and emergency department presentations to follow participants to June 2014. Patients’ characteristics associated with being an emergency presenter and receiving any anti-cancer treatment were examined. Results A total of 647 NSCLC cases were included (58.6% male, median age 73 years). Emergency presenters (34.5% of cases) were more likely to have a high Charlson comorbidity index score, be an ex-smoker who had quit in the past 15 years and to be diagnosed with distant metastases. Almost all patients had visited their general practitioner ≥3 times in the 6 months prior to diagnosis. Nearly one-third (29.5%) of patients did not receive any anti-cancer treatment, however, there were no differences between emergency and non-emergency presenters in the likelihood of receiving treatment. Those less likely to be treated were older, had no private health insurance, and had unknown stage disease recorded. Conclusion Our results indicate the difficulties in diagnosing lung cancer at an early stage and inequities in NSCLC treatment. Future research should address opportunities to diagnose lung cancer earlier and to optimise treatment pathways. [ABSTRACT FROM AUTHOR]

Background: Cancer care represents a substantial and rapidly rising healthcare cost in Australia. Our aim was to provide accurate population-based estimates of the health services cost of cancer care using large-scale linked patient-level data. Methods: We analysed data for incident cancers diagnosed 2006–2010 and followed to 2014 among 266,793 eligible participants in the 45 and Up Study. Health system costs included Medicare and pharmaceutical claims, inpatient hospital episodes and emergency department presentations. Costs for cancer cases and matched cancer-free controls were compared, to estimate monthly/annual excess costs of cancer care by cancer type, before and after diagnosis and by phase of care (initial, continuing, terminal). Total costs incurred in 2013 were also estimated for all people diagnosed in Australia 2009–2013. Results: 7624 participants diagnosed with cancer were matched with up to three controls. The mean excess cost of care per case was AUD$1,622 for the year before diagnosis, $33,944 for the first year post-diagnosis and $8,796 for the second year post-diagnosis, with considerable variation by cancer type. Mean annual cost after the initial treatment phase was $4,474/case and the mean cost for the last year of life was $49,733/case. In 2013 the cost for cancers among people in Australia diagnosed during 2009–2013 was ~$6.3billion (0.4% of Gross Domestic Product; $272 per capita), with the largest costs for colorectal cancer ($1.1billion), breast cancer ($0.8billion), lung cancer ($0.6billion) and prostate cancer ($0.5billion). Conclusions: The cost of cancer care is substantial and varies by cancer type and time since diagnosis. These findings emphasise the economic importance of effective primary and secondary cancer prevention strategies. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Prostate cancer (PC) is the most common non-cutaneous cancer in men worldwide. The relationships between PC and possible risk factors for PC cases ( n = 1,181) and male controls ( n = 875) from the New South Wales (NSW) Cancer, Lifestyle and Evaluation of Risk Study (CLEAR) were examined in this study. The associations between PC risk and paternal history of PC, body mass index (BMI), medical conditions, sexual behaviour, balding pattern and puberty, after adjusting for age, income, region of birth, place of residence, and PSA testing, were examined. Adjusted risk of PC was higher for men with a paternal history of PC (OR = 2.31; 95%CI: 1.70-3.14), personal history of prostatitis (OR = 2.30; 95%CI: 1.44-3.70), benign prostatic hyperplasia (OR = 2.29; 95%CI: 1.79-2.93), being overweight (vs. normal; OR = 1.24; 95%CI: 0.99-1.55) or obese (vs. normal; OR = 1.44; 95%CI: 1.09-1.89), having reported more than seven sexual partners in a lifetime (vs. < 3 partners; OR = 2.00; 95%CI: 1.49-2.68), and having reported more than 5 orgasms a month prior to PC diagnosis (vs. ≤3 orgasms; OR = 1.59; 95%CI: 1.18-2.15). PC risk was lower for men whose timing of puberty was later than their peers (vs. same as peers; OR = 0.75; 95%CI: 0.59-0.97), and a smaller risk reduction of was observed in men whose timing of puberty was earlier than their peers (vs. same as peers; OR = 0.85; 95%CI: 0.61-1.17). No associations were found between PC risk and vertex balding, erectile function, acne, circumcision, vasectomy, asthma or diabetes. These results support a role for adult body size, sexual activity, and adolescent sexual development in PC development. [ABSTRACT FROM AUTHOR]

Indicator models of sexual selection predict that females mating with the most ornamented males should produce offspring with enhanced expression of fitness-related traits, such as overall vigor and viability. Empirical support for this prediction, however, is limited. We quantified the effects of a heritable and condition-dependent secondary sexual trait on offspring performance traits in Drosophila bipectinata Duda (Diptera: Drosophilidae). Forty-eight genetic (isofemale) lines were extracted from a natural population, reared in a common environment, and characterized in terms of sex comb size. We measured pupal viability and adult mating success among the progeny of the 5 lines with the largest combs (high line category) and the 5 lines with the smallest combs (low line category). The high line category produced offspring that were significantly more viable than the low line category, and this advantage held across 2 developmental temperatures. In contrast, there was no effect of line category on male mating success, although at the individual-level, comb size was significantly positively correlated with mating success. Our results indicate that the relative size of the D. bipectinata sex comb taps genotypic properties that enhance offspring fitness in a trait-specific manner. Thus, distinct proximate mechanisms likely underlie relationships between secondary sexual trait expression and different performance traits in offspring, offering a possible explanation for inconsistent support for the existence of indirect benefits in sexual selection. [ABSTRACT FROM AUTHOR]

Animals that have a long pre-reproductive adult stage often employ mechanisms that minimize aging over this period in order to preserve reproductive lifespan. In a remarkable exception, one tephritid fruit fly exhibits substantial pre-reproductive aging but then mitigates this aging during a diet-dependent transition to the reproductive stage, after which life expectancy matches that of newly emerged flies. Here, we ascertain the role of nutrients, sexual maturation and mating in mitigation of previous aging in female Queensland fruit flies. Flies were provided one of three diets: ‘sugar’, ‘essential’, or ‘yeast-sugar’. Essential diet contained sugar and micronutrients found in yeast but lacked maturation-enabling protein. At days 20 and 30, a subset of flies on the sugar diet were switched to essential or yeast-sugar diet, and some yeast-sugar fed flies were mated 10 days later. Complete mitigation of actuarial aging was only observed in flies that were switched to a yeast-sugar diet and mated, indicating that mating is key. Identifying the physiological processes associated with mating promise novel insights into repair mechanisms for aging. [ABSTRACT FROM AUTHOR]

Feeding behaviour is an expression of an animal's underlying nutritional strategy. The study of feeding decisions can hence delineate nutritional strategies. Studies of Drosophila melanogaster feeding behaviour have yielded conflicting accounts, and little is known about how nutrients affect feeding patterns in this important model species. Here, we conducted two experiments to characterize nutrient prioritization and regulation. In a choice experiment, we allowed female flies to self-regulate their intake of yeast, sucrose and water by supplying Individual flies with three microcapillary tubes: one containing only yeast of varying concentrations, another with just sucrose of varying concentrations, and the last with just water. Flies tightly regulated yeast and sucrose to a constant ratio at the expense of excess water intake, indicating that flies prioritize macronutrient regulation over excess water consumption. To determine the relative importance of yeast and sucrose, in a no-choice experiment, we provided files with two microcapiliary tubes: the first with one of the 28 diets varying in yeast and sucrose content and the other with only water. Flies Increased total water intake in relation to yeast consumption but not sucrose consumption. Additionally, flies increased diet intake as diet concentration decreased and as the ratio of sugar to yeast equalized. Using a geometric scaling approach, we found that the patterns of diet intake can be explained by flies prioritizing protein and carbohydrates equally and by the lack of substitutability between the nutrients. We conclude by illustrating how our results harmonize conflicting results in the literature once viewed in a two-dimensional diet landscape. [ABSTRACT FROM AUTHOR]

Background Tobacco smoke is a known carcinogen and the magnitude of smoking-related cancer risk varies according to time and population. Local, contemporary evidence can drive appropriate tobacco control. We provide comprehensive cancer risk estimates related to smoking in the population-based, New South Wales (NSW) 45 and Up Study. Methods We estimated smoking-related hazard ratios (HR) for cancer using Cox proportional hazards regression using linked questionnaire (2006-2009) and incident cancer data (n ≥ 50 cases per cancer type), from the NSW Cancer Registry (to December 2013) (via CHeReL). Results Of 18,475 cancers among 229,028 participants aged ≥45 years, current smokers had significantly increased risks of cancers of the lung, larynx, head and neck, oesophagus, liver, bladder, pancreas, stomach, colorectum, and cancers with unknown primary site, compared to never-smokers; lung cancer risk was markedly elevated, including for current-smokers of 1-5 cigarettes/day (HR = 9.25, 95%CI=5.2-16.6), increasing to 38.39 (26.2-56.2) for current-smokers of > 30 cigarettes/day. Quitting substantively decreased cancer risk compared to continued smoking, with lung cancer risk decreasing with decreasing age at quitting (p(trend)<0.05), however risks remained elevated for those quitting aged >25 compared to never-smokers (1.73, 1.1-2.6 for age 26-30 years). An estimated 20% of current-smokers in Australia will get lung cancer during their lifetime versus 1.6% of never-smokers. Conclusions Smoking-attributable cancer risks in Australia are significant, comparable to contemporary risks from other developed nations. Key messages Smokers – including "light" smokers – are at high cancer risk, with ∼one-fifth of Australian lifetime smokers developing lung cancer. Quitting is beneficial. Continued investment in tobacco control is essential. [ABSTRACT FROM AUTHOR]

Aim: Systemic therapies for lung cancer are rapidly evolving. This study aimed to describe lung cancer treatment patterns in New South Wales, Australia, prior to the introduction of immunotherapy and latest-generation targeted therapies., Methods: Systemic therapy utilization and treatment-related factors were examined for participants in the New South Wales 45 and Up Study with incident lung cancer ascertained by record linkage to the New South Wales Cancer Registry (2006-2013). Systemic therapy receipt to June 2016 was determined using medical and pharmaceutical claims data from Services Australia, and in-patient hospital records. Factors related to treatment were identified using competing risks regressions., Results: A total of 1,116 lung cancer cases were identified with a mean age at diagnosis of 72 years and median survival of 10.6 months. Systemic therapy was received by 45% of cases. Among 400 cases with metastatic non-small cell lung cancer, 51% and 28% received first- and second-line systemic therapy, respectively. Among 112 diagnosed with small-cell lung cancer, 79% and 29% received first- and second-line systemic therapy. The incidence of systemic therapy was lower for participants with indicators of poor performance status, lower educational attainment, and those who lived in areas of socioeconomic disadvantage; and was higher for participants with small-cell lung cancer histology or higher body mass index., Conclusion: This population-based Australian study identified patterns of systemic therapy use for lung cancer, particularly small-cell lung cancer. Despite a universal healthcare system, the analysis revealed socioeconomic disparities in health service utilization and relatively low utilization of systemic therapy overall., (© 2021 John Wiley & Sons Australia, Ltd.)

Background: While many high-income countries including Australia have successfully implemented a range of tobacco control policies, smoking remains the leading preventable cause of cancer death in Australia. We have projected Australian mortality rates for cancer types, which have been shown to have an established relationship with cigarette smoking and estimated numbers of cancer deaths attributable to smoking to 2044., Methods: Cancer types were grouped according to the proportion of cases currently caused by smoking: 8%-30% and >30%. For each group, an age-period- cohort model or generalised linear model with cigarette smoking exposure as a covariate was selected based on the model fit statistics and validation using observed data. The smoking-attributable fraction (SAF) was calculated for each smoking-related cancer using Australian smoking prevalence data and published relative risks., Results: Despite the decreasing mortality rates projected for the period 2015-2019 to 2040-2044 for both men and women, the overall number of smoking-related cancer deaths is estimated to increase by 28.7% for men and 35.8% for women: from 138 707 (77 839 men and 60 868 women) in 2015-2019 to 182 819 (100 153 men and 82 666 women) in 2040-2044. Over the period 2020-2044, there will be 254 583 cancer deaths (173 943 men and 80 640 women) directly attributable to smoking, with lung, larynx, oesophagus and oral (comprising lip, oral cavity and pharynx) cancers having the largest SAFs., Interpretation: Cigarette smoking will cause over 250 000 cancer deaths in Australia from 2020 to 2044. Continued efforts in tobacco control remain a public health priority, even in countries where smoking prevalence has substantially declined., Competing Interests: Competing interests: KC is co-principal investigator of an investigator-initiated trial of cervical screening, Compass, run by the Australian Centre for Prevention of Cervical Cancer (ACPCC), which is a government-funded not-for-profit charity; the ACPCC has received equipment and a funding contribution from Roche Molecular Diagnostics, and operational support from the Australian Government. KC is also co-principal investigator on a major investigator-initiated implementation programme Elimination of Cervical Cancer in the Western Pacific (ECCWP) which will receive support from the Minderoo Foundation, the Frazer Family Foundation, and equipment donations from Cepheid. Neither KC nor her institution on her behalf receives direct funding from industry for any project. MC is an investigator on an investigator-initiated trial of cytology and primary human papillomavirus screening in Australia (Compass; ACTRN12613001207707 and NCT02328872), which is conducted and funded by the Australian Centre for the Prevention of Cervical Cancer, a government-funded health promotion charity. The Australian Centre for the Prevention of Cervical Cancer has received equipment and a funding contribution for the Compass trial from Roche Molecular Systems and operational support from the Australian Government. However, neither MC nor his institution on his behalf (the Daffodil Centre, a joint venture between Cancer Council NSW and The University of Sydney) receive direct funding from industry for Compass Australia or any other project. All other authors declare no competing interests., (© Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Introduction: Socioeconomic disparities in cancer survival have been reported in many developed countries, including Australia. Although some international studies have investigated the determinants of these socioeconomic disparities, most previous Australian studies have been descriptive, as only limited relevant data are generally available. Here, we describe a protocol for a study to use data from a large-scale Australian cohort linked with several other health-related databases to investigate several groups of factors associated with socioeconomic disparities in cancer survival in New South Wales (NSW), Australia, and quantify their contributions to the survival disparities., Methods and Analysis: The Sax Institute's 45 and Up Study participants completed a baseline questionnaire during 2006-2009. Those who were subsequently diagnosed with cancer of the colon, rectum, lung or female breast will be included. This study sample will be identified by linkage with NSW Cancer Registry data for 2006-2013, and their vital status will be determined by linking with cause of death records up to 31 December 2015. The study cohort will be divided into four groups based on each of the individual education level and an area-based socioeconomic measure. The treatment received will be obtained through linking with hospital records and Medicare and pharmaceutical claims data. Cox proportional hazards models will be fitted sequentially to estimate the percentage contributions to overall socioeconomic survival disparities of patient factors, tumour and diagnosis factors, and treatment variables., Ethics and Dissemination: This research is covered by ethical approval from the NSW Population and Health Services Research Ethics Committee. Results of the study will be disseminated to different interest groups and organisations through scientific conferences, social media and peer-reviewed articles., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2019. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

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. PLCO m2012 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 PLCO m2012 in predicting lung cancer outcomes in a cohort of Australian smokers. Predicted risk of lung cancer was calculated using PLCO m2012 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. PLCO m2012 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 PLCO m2012 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 PLCO m2012 might improve the balance of benefits versus harms, and cost-effectiveness of lung cancer screening., (© 2017 UICC.)