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.

Colon and rectal cancer treatment patterns and their associations with clinical, sociodemographic and lifestyle characteristics: analysis of the Australian 45 and Up Study cohort.

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.

Pathways to diagnosis of endometrial and ovarian cancer in the 45 and Up Study cohort.

PURPOSE: To determine pathways to endometrial or ovarian cancer diagnosis by comparing health service utilization between cancer cases and matched cancer-free controls, using linked health records. METHODS: From cancer registry records, we identified 238 incident endometrial and 167 ovarian cancer cases diagnosed during 2006-2013 in the Australian 45 and Up Study cohort (142,973 female participants). Each case was matched to four cancer-free controls on birthdate, sex, place of residence, smoking status, and body mass index. The use of relevant health services during the 13-18-, 7-12-, 0-6-, and 0-1-months pre-diagnosis for cases and the corresponding dates for their matched controls was determined through linkage with subsidized medical services and hospital records. RESULTS: Healthcare utilization diverged between women with cancer and controls in the 0-6-months, particularly 0-1 months, pre-diagnosis. In the 0-1 months, 74.8% of endometrial and 50.3% of ovarian cases visited a gynecologist/gynecological oncologist, 11.3% and 59.3% had a CA125 test, 5.5% and 48.5% an abdominal pelvic CT scan, and 34.5% and 30.5% a transvaginal pelvic ultrasound, respectively (versus ≤ 1% of matched controls). Moreover, 25.1% of ovarian cancer cases visited an emergency department in the 0-1-months pre-diagnosis (versus 1.3% of matched controls), and GP visits were significantly more common for cases than controls in this period. CONCLUSION: Most women with endometrial or ovarian cancer accessed recommended specialists and tests in the 0-1-months pre-diagnosis, but a high proportion of women with ovarian cancer visited an emergency department. This reinforces the importance of timely specialist referral.

Are patients with cancer at higher risk of COVID-19-related death? A systematic review and critical appraisal of the early evidence.

BACKGROUND: Early reports suggested that COVID-19 patients with cancer were at higher risk of COVID-19-related death. We conducted a systematic review with risk of bias assessment and synthesis of the early evidence on the risk of COVID-19-related death for COVID-19 patients with and without cancer. METHODS AND FINDINGS: We searched Medline/Embase/BioRxiv/MedRxiv/SSRN databases to 1 July 2020. We included cohort or case-control studies published in English that reported on the risk of dying after developing COVID-19 for people with a pre-existing diagnosis of any cancer, lung cancer, or haematological cancers. We assessed risk of bias using tools adapted from the Newcastle-Ottawa Scale. We used the generic inverse-variance random-effects method for meta-analysis. Pooled odds ratios (ORs) and hazard ratios (HRs) were calculated separately. Of 96 included studies, 54 had sufficient non-overlapping data to be included in meta-analyses (>500,000 people with COVID-19, >8000 with cancer; 52 studies of any cancer, three of lung and six of haematological cancers). All studies had high risk of bias. Accounting for at least age consistently led to lower estimated ORs and HRs for COVID-19-related death in cancer patients (e.g. any cancer versus no cancer; six studies, unadjusted OR=3.30,95%CI:2.59-4.20, adjusted OR=1.37,95%CI:1.16-1.61). Adjusted effect estimates were not reported for people with lung or haematological cancers. Of 18 studies that adjusted for at least age, 17 reported positive associations between pre-existing cancer diagnosis and COVID-19-related death (e.g. any cancer versus no cancer; nine studies, adjusted OR=1.66,95%CI:1.33-2.08; five studies, adjusted HR=1.19,95%CI:1.02-1.38). CONCLUSIONS: The initial evidence (published to 1 July 2020) on COVID-19-related death in people with cancer is characterised by multiple sources of bias and substantial overlap between data included in different studies. Pooled analyses of non-overlapping early data with adjustment for at least age indicated a significantly increased risk of COVID-19-related death for those with a pre-existing cancer diagnosis.

The risk of contracting SARS-CoV-2 or developing COVID-19 for people with cancer: A systematic review of the early evidence.

BACKGROUND: The early COVID-19 literature suggested that people with cancer may be more likely to be infected with SARS-CoV-2 or develop COVID-19 than people without cancer, due to increased health services contact and/or immunocompromise. While some studies were criticised due to small patient numbers and methodological limitations, they created or reinforced concerns of clinicians and people with cancer. These risks are also important in COVID-19 vaccine prioritisation decisions. We performed a systematic review to critically assess and summarise the early literature. METHODS AND FINDINGS: We conducted a systematic search of Medline/Embase/BioRxiv/MedRxiv/SSRN databases including peer-reviewed journal articles, letters/commentaries, and non-peer-reviewed pre-print articles for 1 January-1 July 2020. The primary endpoints were diagnosis of COVID-19 and positive SARS-CoV-2 test. We assessed risk of bias using a tool adapted from the Newcastle-Ottawa Scale. Twelve studies were included in the quantitative synthesis. All four studies of COVID-19 incidence (including 24,181,727 individuals, 125,649 with pre-existing cancer) reported that people with cancer had higher COVID-19 incidence rates. Eight studies reported SARS-CoV-2 test positivity for > 472,000 individuals, 48,370 with pre-existing cancer. Seven of these studies comparing people with any and without cancer, were pooled using random effects [pooled odds ratio 0.91, 95 %CI: 0.57-1.47; unadjusted for age, sex, or comorbidities]. Two studies suggested people with active or haematological cancer had lower risk of a positive test. All 12 studies had high risk of bias; none included universal or random COVID-19/SARS-CoV-2 testing. CONCLUSIONS: The early literature on susceptibility to SARS-CoV-2/COVID-19 for people with cancer is characterised by pervasive biases and limited data. To provide high-quality evidence to inform decision-making, studies of risk of SARS-CoV-2/COVID-19 for people with cancer should control for other potential modifiers of infection risk, including age, sex, comorbidities, exposure to the virus, protective measures taken, and vaccination, in addition to stratifying analyses by cancer type, stage at diagnosis, and treatment received.

Projections of smoking-related cancer mortality in Australia to 2044.

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.

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.

Accurate categorisation of menopausal status for research studies: a step-by-step guide and detailed algorithm considering age, self-reported menopause and factors potentially masking the occurrence of menopause.

OBJECTIVE: Menopausal status impacts risk for many health outcomes. However, factors including hysterectomy without oophorectomy and Menopausal Hormone Therapy (MHT) can mask menopause, affecting reliability of self-reported menopausal status in surveys. We describe a step-by-step algorithm for classifying menopausal status using: directly self-reported menopausal status; MHT use; hysterectomy; oophorectomy; intervention timing; and attained age. We illustrate this approach using the Australian 45 and Up Study cohort (142,973 women aged ≥ 45 years). RESULTS: We derived a detailed seven-category menopausal status, able to be further consolidated into four categories ("pre-menopause"/"peri-menopause"/"post-menopause"/"unknown") accounting for participants' ages. 48.3% of women had potentially menopause-masking interventions. Overall, 93,107 (65.1%), 9076 (6.4%), 17,930 (12.5%) and 22,860 (16.0%) women had a directly self-reported "post-menopause", "peri-menopause", "pre-menopause" and "not sure"/missing status, respectively. 61,464 women with directly self-reported "post-menopause" status were assigned a "natural menopause" detailed derived status (menopause without MHT use/hysterectomy/oophorectomy). By accounting for participants' ages, 105,817 (74.0%) women were assigned a "post-menopause" consolidated derived status, including 15,009 of 22,860 women with "not sure"/missing directly self-reported status. Conversely, 3178 of women with directly self-reported "post-menopause" status were assigned "unknown" consolidated derived status. This algorithm is likely to improve the accuracy and reliability of studies examining outcomes impacted by menopausal status.

Lung cancer treatment patterns and factors relating to systemic therapy use in Australia.

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.

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.

Large-scale systematic analysis of exposure to multiple cancer risk factors and the associations between exposure patterns and cancer incidence.

Exposures to cancer risk factors such as smoking and alcohol are not mutually independent. We aimed to identify risk factor exposure patterns and their associations with sociodemographic characteristics and cancer incidence. We considered 120,771 female and, separately, 100,891 male participants of the Australian prospective cohort 45 and Up Study. Factor analysis grouped 36 self-reported variables into 8 combined factors each for females (largely representing 'smoking', 'alcohol', 'vigorous exercise', 'age at childbirth', 'Menopausal Hormone Therapy', 'parity and breastfeeding', 'standing/sitting', 'fruit and vegetables') and males (largely representing 'smoking', 'alcohol', 'vigorous exercise', 'urology and health', 'moderate exercise', 'standing/sitting', 'fruit and vegetables', 'meat and BMI'). Associations with cancer incidence were investigated using multivariable logistic regression (4-8 years follow-up: 6193 females, 8749 males diagnosed with cancer). After multiple-testing correction, we identified 10 associations between combined factors and cancer incidence for females and 6 for males, of which 14 represent well-known relationships (e.g. bowel cancer: females 'smoking' factor Odds Ratio (OR) 1.16 (95% Confidence Interval (CI) 1.08-1.25), males 'smoking' factor OR 1.15 (95% CI 1.07-1.23)), providing evidence for the validity of this approach. The catalogue of associations between exposure patterns, sociodemographic characteristics, and cancer incidence can help inform design of future studies and targeted prevention programmes.

Health services costs for lung cancer care in Australia: Estimates from the 45 and Up Study.

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.

Contributions of prognostic factors to socioeconomic disparities in cancer survival: protocol for analysis of a cohort with linked data.

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.

Health services costs for cancer care in Australia: Estimates from the 45 and Up Study.

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.

Patterns of care and emergency presentations for people with non-small cell lung cancer in New South Wales, Australia: A population-based study.

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.

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.

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.

Adult body size, sexual history and adolescent sexual development, may predict risk of developing prostate cancer: Results from the New South Wales Lifestyle and Evaluation of Risk Study (CLEAR).

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.

Mating Reverses Actuarial Aging in Female Queensland Fruit Flies.

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.