BackgroundCancer 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.MethodsWe 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.Results7624 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).ConclusionsThe 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.

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

In pest management programmes that incorporate the sterile insect technique (SIT), the ability of mass-reared insects to tolerate dry conditions may influence their survival after release in the field. In the present study, desiccation resistance of adult mass-reared Queensland fruit flies, Bactrocera tryoni (Frogatt) (Diptera: Tephritidae), that are routinely released in SIT programmes was compared with that of wild flies at 1, 10 and 20 days after adult eclosion. Under dry conditions without access to food or water, longevity of mass-reared B. tryoni was significantly less than that of their wild counterparts. Desiccation resistance of mass-reared flies declined monotonically with age, but this was not the case for wild flies. The sharp decline in desiccation resistance of mass-reared flies as they aged was likely explained by decreased dehydration tolerance. As in an earlier study, desiccation resistance of females was significantly lower than that of males but this was particularly pronounced in mass-reared females. Female susceptibility to dry conditions corresponded with declining dehydration tolerance with age and associated patterns of reproductive development, which suggests that water content of their oocyte load is not available for survival during periods of water stress.

Despite the significant advancements being made in the neurogenetics for mental health, the identification and validation of potential endophenotype markers of risk and resilience remain to be confirmed. The TWIN-E study (The Twin study in Wellbeing using Integrative Neuroscience of Emotion) aims to validate endophenotype markers of mental health across cognitive, brain, and autonomic measures by testing the heritability, clinical plausibility, and reliability of each of these measures in a large adult twin cohort. The specific gene and environmental mechanisms that moderate prospective links between endophenotypephenotype markers and the final outcome of wellbeing will also be identified. TWIN-E is a national prospective study with three phases: I) baseline testing on a battery of online questionnaires and cognitive tasks, and EEG, MRI, and autonomic testing; II) 12-month follow-up testing on the online assessments; and III) randomized controlled trial of brain training. Minimum target numbers include 1,500 male/female twins (18-65 years) for the online assessments (Phase I and II), 300 twins for the EEG testing component, and 244 twins for the MRI testing component. For Phase III, each twin out of the pair will be randomized to either the treatment or waitlist control group to test the effects of brain training on mental health over a 30-day period, and to confirm the gene-environment and endophenotype contributions to treatment response. Preliminary heritability results are provided for the first 50% of the MRI subgroup (n = 142) for the grey matter volume, thickness, and surface area measures, and white matter diffuse tensor imaging fractional anisotropy.