Keratinocyte carcinomas, area-level socioeconomic status and geographic remoteness in Tasmania: cross-sectional associations and temporal trends.

OBJECTIVE: This article aims to examine cross-sectional associations and assess temporal trends in keratinocyte carcinoma (KC) incidence by area-level socioeconomic status (SES) and geographic remoteness in Tasmania, Australia. METHODS: KCs - basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (SCC) - registered by the Tasmanian Cancer Registry were assigned to area-level SES and remoteness area. Incidence rate ratios (2014-2018) were estimated using Poisson regression. Average annual percentage changes (2001-2018) were estimated using the Joinpoint Regression Program. RESULTS: BCC incidence increased with increasing area-level advantage (p-value for trend <0.001), but no trend was found for SCC. SCC incidence was higher in rural than urban areas (p-value <0.001), and BCC incidence was slightly higher in rural than urban areas for females (p-value = 0.009), but not for males (p-value = 0.373). BCC and SCC incidence increased between 2001 and the mid-2010s, when it peaked across most areas. CONCLUSIONS: Associations were found between BCC and higher area-level SES, and between SCC and geographic remoteness. The findings suggest differences in sun exposure behaviours, skin cancer awareness and access to services, or ascertainment bias. IMPLICATIONS FOR PUBLIC HEALTH: Efforts to control and deliver KC services in Tasmania should consider targeting populations with specific area-level characteristics.

Individual and area level factors associated with the breast cancer diagnostic-treatment interval in Queensland, Australia.

BACKGROUND: Delays to breast cancer treatment can lead to more aggressive and extensive treatments, increased expenses, increased psychological distress, and poorer survival. We explored the individual and area level factors associated with the interval between diagnosis and first treatment in a population-based cohort in Queensland, Australia. METHODS: Data from 3216 Queensland women aged 20 to 79, diagnosed with invasive breast cancer (ICD-O-3 C50) between March 2010 and June 2013 were analysed. Diagnostic dates were sourced from the Queensland Cancer Registry and treatment dates were collected via self-report. Diagnostics-treatment intervals were modelled using flexible parametric survival methods. RESULTS: The median interval between breast cancer diagnosis and first treatment was 15 days, with an interquartile range of 9-26 days. Longer diagnostic-treatment intervals were associated with a lack of private health coverage, lower pre-diagnostic income, first treatments other than breast conserving surgery, and residence outside a major city. The model explained a modest 13.7% of the variance in the diagnostic-treatment interval [Formula: see text]. Sauerbrei's D was 0.82, demonstrating low to moderate discrimination performance. CONCLUSION: Whilst this study identified several individual- and area-level factors associated with the time between breast cancer diagnosis and first treatment, much of the variation remained unexplained. Increased socioeconomic disadvantage appears to predict longer diagnostic-treatment intervals. Though some of the differences are small, many of the same factors have also been linked to screening and diagnostic delay. Given the potential for accumulation of delay at multiple stages along the diagnostic and treatment pathway, identifying and applying effective strategies address barriers to timely health care faced by socioeconomically disadvantaged women remains a priority.

Mapping the prevalence of cancer risk factors at the small area level in Australia.

BACKGROUND: Cancer is a significant health issue globally and it is well known that cancer risk varies geographically. However in many countries there are no small area-level data on cancer risk factors with high resolution and complete reach, which hinders the development of targeted prevention strategies. METHODS: Using Australia as a case study, the 2017-2018 National Health Survey was used to generate prevalence estimates for 2221 small areas across Australia for eight cancer risk factor measures covering smoking, alcohol, physical activity, diet and weight. Utilising a recently developed Bayesian two-stage small area estimation methodology, the model incorporated survey-only covariates, spatial smoothing and hierarchical modelling techniques, along with a vast array of small area-level auxiliary data, including census, remoteness, and socioeconomic data. The models borrowed strength from previously published cancer risk estimates provided by the Social Health Atlases of Australia. Estimates were internally and externally validated. RESULTS: We illustrated that in 2017-2018 health behaviours across Australia exhibited more spatial disparities than previously realised by improving the reach and resolution of formerly published cancer risk factors. The derived estimates revealed higher prevalence of unhealthy behaviours in more remote areas, and areas of lower socioeconomic status; a trend that aligned well with previous work. CONCLUSIONS: Our study addresses the gaps in small area level cancer risk factor estimates in Australia. The new estimates provide improved spatial resolution and reach and will enable more targeted cancer prevention strategies at the small area level. Furthermore, by including the results in the next release of the Australian Cancer Atlas, which currently provides small area level estimates of cancer incidence and relative survival, this work will help to provide a more comprehensive picture of cancer in Australia by supporting policy makers, researchers, and the general public in understanding the spatial distribution of cancer risk factors. The methodology applied in this work is generalisable to other small area estimation applications and has been shown to perform well when the survey data are sparse.

Disease mapping: Geographic differences in population rates of interventional treatment for prostate cancer in Australia.

BACKGROUND: Treatment decisions for men diagnosed with prostate cancer depend on a range of clinical and patient characteristics such as disease stage, age, general health, risk of side effects and access. Associations between treatment patterns and area-level factors such as remoteness and socioeconomic disadvantage have been observed in many countries. OBJECTIVE: To model spatial differences in interventional treatment rates for prostate cancer at high spatial resolution to inform policy and decision-making. METHODS: Hospital separations data for interventional treatments for prostate cancer (radical prostatectomy, low dose rate and high dose rate brachytherapy) for men aged 40 years and over were modelled using spatial models, generalised linear mixed models, maximised excess events tests and k-means statistical clustering. RESULTS: Geographic differences in population rates of interventional treatments were found (p<0.001). Separation rates for radical prostatectomy were lower in remote areas (12.2 per 10 000 person-years compared with 15.0-15.9 in regional and major city areas). Rates for all treatments decreased with increasing socioeconomic disadvantage (radical prostatectomy 19.1 /10 000 person-years in the most advantaged areas compared with 12.9 in the most disadvantaged areas). Three groups of similar areas were identified: those with higher rates of radical prostatectomy, those with higher rates of low dose brachytherapy, and those with low interventional treatment rates but higher rates of excess deaths. The most disadvantaged areas and remote areas tended to be in the latter group. CONCLUSIONS: The geographic differences in treatment rates may partly reflect differences in patients' physical and financial access to treatments. Treatment rates also depend on diagnosis rates and thus reflect variation in investigation rates for prostate cancer and presentation of disease. Spatial variation in interventional treatments may aid identification of areas of under-treatment or over-treatment.

Treatment intervals and survival for women diagnosed with early breast cancer in Queensland: the Breast Cancer Outcomes Study, a population-based cohort study.

OBJECTIVES: To assess associations between breast cancer-specific survival and timeliness of treatment, based on 2020 Australian guidelines for the treatment of early breast cancer. DESIGN: Population-based cohort study; analysis of linked Queensland Cancer Register, patient medical record, and National Death Index data, supplemented by telephone interviews. SETTING, PARTICIPANTS: Women aged 20-79 years diagnosed with invasive breast cancer during 1 March 2010 - 30 June 2013, followed to 31 December 2020. MAIN OUTCOME MEASURES: Breast cancer-specific survival for women who received or did not receive treatment within the recommended timeframe, overall and for six treatment intervals; optimal cut-points for each treatment interval; characteristics of women for whom treatment was not provided within the recommended timeframe. RESULTS: Of 5426 eligible women, 4762 could be invited for interviews; complete data were available for 3044 women (56% of eligible women, 65% of invited women). Incomplete compliance with guideline interval recommendations was identified for 1375 women (45%); their risk of death from breast cancer during the follow-up period was greater than for those for whom guideline compliance was complete (adjusted hazard ratio [aHR], 1.43; 95% confidence interval [CI], 1.04-1.96). Risk of death was greater for women for whom the diagnosis to surgery interval exceeded 29 days (aHR, 1.76; 95% CI, 1.19-2.59), the surgery to chemotherapy interval exceeded 36 days (aHR, 1.63; 95% CI, 1.13-2.36), or the chemotherapy to radiotherapy interval exceeded 31 days (aHR, 1.83; 95% CI, 1.19-2.80). Treatment intervals longer than recommended were more frequent for women for whom breast cancer was detected by public facility screening (adjusted odds ratio [aOR], 1.58; 95% CI, 1.22-2.04) or by symptoms (aOR, 1.39; 95% CI, 1.09-1.79) than when cancer had been detected in private facilities, and for women without private health insurance (aOR, 1.96; 95% CI, 1.66-2.32) or living outside major cities (aOR, 1.38; 95% CI, 1.18-1.62). CONCLUSIONS: Breast cancer-specific survival was poorer for women for whom the diagnosis to surgery, surgery to chemotherapy, or chemotherapy to radiotherapy intervals exceeded guideline-recommended limits. Our findings support 2020 Australian guideline recommendations regarding timely care.

Temporal changes in childhood cancer incidence and survival by stage at diagnosis in Australia, 2000-2017.

BACKGROUND: The Toronto Paediatric Cancer Stage Guidelines are a compendium of staging systems developed to facilitate collection of consistent and comparable data on stage at diagnosis for childhood cancers by cancer registries. MATERIAL AND METHODS: This retrospective, observational cohort study investigated changes in stage-specific incidence and survival for children diagnosed between 2000-2008 compared to 2009-2017 using the population-based Australian Childhood Cancer Registry. Information on mortality for each patient was available to 31st December 2020. Shifts in incidence by stage were evaluated using chi-square tests, and differences in stage-specific five-year observed survival for all causes of death over time were assessed using flexible parametric models. RESULTS: Stage was assigned according to the Toronto Guidelines for 96% (n = 7944) of the total study cohort (n = 8292). Changes in the distribution of incidence by stage between the two diagnosis periods were observed for retinoblastoma, with stage 0 increasing from 26% to 37% of cases (p = 0.02), and hepatoblastoma, with metastatic disease increasing from 22% to 39% of cases (p = 0.04). There were large gains in stage-specific survival over time for stage IV rhabdomyosarcoma (five-year adjusted mortality hazard ratio for 2009-2017 compared to 2000-2008 of 0.38, 95% CI 0.19-0.77; p = 0.01), stage M3 for medulloblastoma (HR = 0.41, 95% CI 0.21-0.79; p = 0.01) and metastatic neuroblastoma excluding stage MS (HR = 0.61, 95% CI 0.44-0.84; p < 0.01). CONCLUSION: These results indicate that improvements in childhood cancer survival in Australia are most likely due to refined management rather than changes in stage at diagnosis, particularly for metastatic solid tumours. Wide international uptake of the Toronto Guidelines will allow comprehensive evaluation of differences in survival between countries.

Geographical and spatial variations in bowel cancer screening participation, Australia, 2015-2020.

BACKGROUND: Participation in bowel cancer screening programs remains poor in many countries. Knowledge of geographical variation in participation rates may help design targeted interventions to improve uptake. This study describes small-area and broad geographical patterns in bowel screening participation in Australia between 2015-2020. METHODS: Publicly available population-level participation data for Australia's National Bowel Cancer Screening Program (NBCSP) were modelled using generalized linear models to quantify screening patterns by remoteness and area-level disadvantage. Bayesian spatial models were used to obtain smoothed estimates of participation across 2,247 small areas during 2019-2020 compared to the national average, and during 2015-2016 and 2017-2018 for comparison. Spatial heterogeneity was assessed using the maximized excess events test. RESULTS: Overall, screening participation rates was around 44% over the three time-periods. Participation was consistently lower in remote or disadvantaged areas, although heterogeneity was evident within these broad categories. There was strong evidence of spatial differences in participation over all three periods, with little change in patterns between time periods. If the spatial variation was reduced (so low participation areas were increased to the 80th centile), an extra 250,000 screens (4% of total) would have been conducted during 2019-2020. CONCLUSIONS: Despite having a well-structured evidence-based government funded national bowel cancer screening program, the substantial spatial variation in participation rates highlights the importance of accounting for the unique characteristics of specific geographical regions and their inhabitants. Identifying the reasons for geographical disparities could inform interventions to achieve more equitable access and a higher overall bowel screening uptake.

Keratinocyte carcinomas, area-level socioeconomic status and geographic remoteness in Tasmania: cross-sectional associations and temporal trends.

OBJECTIVE: This article aims to examine cross-sectional associations and assess temporal trends in keratinocyte carcinoma (KC) incidence by area-level socioeconomic status (SES) and geographic remoteness in Tasmania, Australia. METHODS: KCs-basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (SCC)-registered by the Tasmanian Cancer Registry were assigned to area-level SES and remoteness area. Incidence rate ratios (2014-2018) were estimated using Poisson regression. Average annual percentage changes (2001-2018) were estimated using the Joinpoint Regression Program. RESULTS: BCC incidence increased with increasing area-level advantage (p value for trend <0.001), but no trend was found for SCC. SCC incidence was higher in rural than urban areas (p value <0.001), and BCC incidence was slightly lower in rural than urban areas for males (p value = 0.026), but not for females (p value = 0.381). BCC and SCC incidence increased between 2001 and the mid-2010s, when it peaked across most areas. CONCLUSIONS: Associations were found between BCC and higher area-level SES, and between SCC and geographic remoteness. The findings suggest differences in sun exposure behaviours, skin cancer awareness and access to services, or ascertainment bias. IMPLICATIONS FOR PUBLIC HEALTH: Efforts to control and deliver KC services in Tasmania should consider targeting populations with specific area-level characteristics.

A Review of the Application of Spatial Survival Methods in Cancer Research: Trends, Modeling, and Visualization Techniques.

Spatial modeling of cancer survival is an important tool for identifying geographic disparities and providing an evidence base for resource allocation. Many different approaches have attempted to understand how survival varies geographically. This is the first scoping review to describe different methods and visualization techniques and to assess temporal trends in publications. The review was carried out using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline using PubMed and Web of Science databases. Two authors independently screened articles. Articles were eligible for review if they measured cancer survival outcomes in small geographical areas by using spatial regression and/or mapping. Thirty-two articles were included, and the number increased over time. Most articles have been conducted in high-income countries using cancer registry databases. Eight different methods of modeling spatial survival were identified, and there were seven different ways of visualizing the results. Increasing the use of spatial modeling through enhanced data availability and knowledge sharing could help inform and motivate efforts to improve cancer outcomes and reduce excess deaths due to geographical inequalities. Efforts to improve the coverage and completeness of population-based cancer registries should continue to be a priority, in addition to encouraging the open sharing of relevant statistical programming syntax and international collaborations.

Severity and risk factors of interval breast cancer in Queensland, Australia: a population-based study.

BACKGROUND: Interval breast cancers (BC) are those diagnosed within 24 months of a negative mammogram. This study estimates the odds of being diagnosed with high-severity BC among screen-detected, interval, and other symptom-detected BC (no screening history within 2 years); and explores factors associated with being diagnosed with interval BC. METHODS: Telephone interviews and self-administered questionnaires were conducted among women (n = 3,326) diagnosed with BC in 2010-2013 in Queensland. Respondents were categorised into screen-detected, interval, and other symptom-detected BCs. Data were analysed using logistic regressions with multiple imputation. RESULTS: Compared with screen-detected BC, interval BC had higher odds of late-stage (OR = 3.50, 2.9-4.3), high-grade (OR = 2.36, 1.9-2.9) and triple-negative cancers (OR = 2.55, 1.9-3.5). Compared with other symptom-detected BC, interval BC had lower odds of late stage (OR = 0.75, 0.6-0.9), but higher odds of triple-negative cancers (OR = 1.68, 1.2-2.3). Among women who had a negative mammogram (n = 2,145), 69.8% were diagnosed at their next mammogram, while 30.2% were diagnosed with an interval cancer. Those with an interval cancer were more likely to have healthy weight (OR = 1.37, 1.1-1.7), received hormone replacement therapy (2-10 years: OR = 1.33, 1.0-1.7; > 10 years: OR = 1.55, 1.1-2.2), conducted monthly breast self-examinations (BSE) (OR = 1.66, 1.2-2.3) and had previous mammogram in a public facility (OR = 1.52, 1.2-2.0). CONCLUSION: These results highlight the benefits of screening even among those with an interval cancer. Women-conducted BSE were more likely to have interval BC which may reflect their increased ability to notice symptoms between screening intervals.

Changes in prostate specific antigen (PSA) "screening" patterns by geographic region and socio-economic status in Australia: Analysis of medicare data in 50-69 year old men.

BACKGROUND: While it is known that national PSA testing rates have decreased in Australia since 2007, it is not known whether these trends are consistent by broad geographical areas, nor whether previously reported area-specific differences have remained in more recent time periods. METHODS: Population-based cohort study of Australian men (n = 2793,882) aged 50-69 who received at least one PSA test (Medicare Benefit Schedule item number 66655) during 2002-2018. Outcome measures included age-standardised participation rate, annual percentage change using JoinPoint regression and indirectly standardised participation rate ratio using multivariable Poisson regression. RESULTS: During 2005-09, two thirds (68%) of Australian men aged 50-69 had at least one PSA test, reducing to about half (48%) during 2014-18. In both periods, testing rates were highest among men living in major cities, men aged 50-59 years, and among men living in the most advantaged areas. Nationally, the Australian PSA testing rate increased by 9.2% per year between 2002 and 2007, but then decreased by 5.0% per year to 2018. This pattern was generally consistent across States and Territories, and socio-economic areas, however the magnitude of the trends was less pronounced in remote and very remote areas. CONCLUSIONS: The decreasing trends are consistent with a greater awareness of the current guidelines for clinical practice in Australia, which recommend a PSA test be done only with the informed consent of individual men who understand the potential benefits and risks. However, given there remain substantial geographical disparities in prostate cancer incidence and survival in Australia, along with the equivocal evidence for any benefit from PSA screening, there remains a need for more effective diagnostic strategies for prostate cancer to be implemented consistently regardless of where men live.

Childhood cancer survival and avoided deaths in Australia, 1983-2016.

BACKGROUND: Large improvements in childhood cancer survival have been reported over recent decades. Data from cancer registries have the advantage of providing a 'whole of population' approach to gauge the success of cancer control efforts. OBJECTIVES: The aim of this study was to investigate recent survival estimates for children diagnosed with cancer Australia and to examine the extent of changes in survival over the last 35 years. For the first time, we also estimated the number of deaths among Australian children that were potentially avoided due to improvements in survival. METHODS: A retrospective, population-based cohort study design was used. Case information was extracted from the Australian Childhood Cancer Registry for 1983-2016, with follow-up to 31 December 2017. Eligible children were aged 0-14 with a basis of diagnosis other than autopsy or death certificate only. Five-year relative survival was calculated using the semi-complete cohort method for three diagnosis periods (1983-1994, 1995-2006 and 2007-2016), and changes in survival over time were assessed via flexible parametric models. Avoided deaths within 5 years for those diagnosed between 1995 and 2016 were estimated under the assumption that survival rates remained the same as for 1983-1994. RESULTS: Overall 5-year survival within the study cohort (n = 20,871) increased from 72.8% between 1983 and1994 to 86.1% between 2007 and 2016, equating to an adjusted excess mortality hazard ratio of 1.82 (95% confidence interval 1.67, 1.97). Most cancers showed improvements in survival; other gliomas, hepatoblastoma and osteosarcoma were exceptions. Among children diagnosed between 1995 and 2016, 38.7% of expected deaths within 5 years of diagnosis (n = 1537 of 3970) were avoided due to temporal improvements in survival. CONCLUSIONS: Survival for childhood cancer has continued to improve over recent years, thanks mainly to ongoing progress in treatment development combined with improved supportive care. Providing innovative measures of survival, such as avoided deaths, may assist with understanding outcome data produced by cancer registries.

Long-term childhood cancer survival in Australia using period estimation.

Estimates of childhood cancer survival are usually reported at 5 years after diagnosis only. Using cases prevalent between 2014 and 2018 from the population-based Australian Childhood Cancer Registry, we used the period method to calculate relative survival up to 20 years post diagnosis by cancer type. Twenty-year relative survival for all childhood cancers combined (n = 14,353) was 83.8% (95% confidence interval [CI] = 82.6%-85.0%). Survival decreased only slightly after 10 years for most childhood cancers, except for some types of brain and liver tumours. These contemporary estimates of long-term survival provide valuable information to assist childhood cancer patients and their families in planning for the future.

Geographical and spatial disparities in the incidence and survival of rare cancers in Australia.

Rare cancers collectively account for around a quarter of cancer diagnoses and deaths. However, epidemiological studies are sparse. We describe spatial and geographical patterns in incidence and survival of rare cancers across Australia using a population-based cancer registry cohort of rare cancer cases diagnosed among Australians aged at least 15 years, 2007 to 2016. Rare cancers were defined using site- and histology-based categories from the European RARECARE study, as individual cancer types having crude annual incidence rates of less than 6/100 000. Incidence and survival patterns were modelled with generalised linear and Bayesian spatial Leroux models. Spatial heterogeneity was tested using the maximised excess events test. Rare cancers (n = 268 070) collectively comprised 22% of all invasive cancer diagnoses and accounted for 27% of all cancer-related deaths in Australia, 2007 to 2016 with an overall 5-year relative survival of around 53%. Males and those living in more remote or more disadvantaged areas had higher incidence but lower survival. There was substantial evidence for spatial variation in both incidence and survival for rare cancers between small geographical areas across Australia, with similar patterns so that those areas with higher incidence tended to have lower survival. Rare cancers are a substantial health burden in Australia. Our study has highlighted the need to better understand the higher burden of these cancers in rural and disadvantaged regions where the logistical challenges in their diagnosis, treatment and support are magnified.

Factors associated with cancer survival disparities among Aboriginal and Torres Strait Islander peoples compared with other Australians: A systematic review.

Background: While cancer survival among Aboriginal and Torres Strait Islander peoples has improved over time, they continue to experience poorer cancer survival than other Australians. Key drivers of these disparities are not well understood. This systematic review aimed to summarise existing evidence on Aboriginal and Torres Strait Islander cancer survival disparities and identify influential factors and potential solutions. Methods: In accordance with PRISMA guidelines, multiple databases were systematically searched for English language peer-reviewed articles on cancer survival by Aboriginal and Torres Strait Islander status published from 1/1/2008 to 4/05/2022. Observational studies presenting adjusted survival measures in relation to potential causal factors for disparities were included. Articles were screened independently by two authors. Included studies were critically assessed using Joanna Briggs Institute tools. Results: Thirty population-based and predominantly state-level studies were included. A consistent pattern of poorer unadjusted cancer survival for Aboriginal and Torres Strait Islander peoples was evident. Studies varied widely in the covariates adjusted for including a combination of socio-demographics, cancer stage, comorbidities, and treatment. Potential contributions of these factors varied by cancer type. For lung and female breast cancer, adjusting for treatment and comorbidities reduced the survival disparity, which, while still elevated was no longer statistically significant. This pattern was also evident for cervical cancer after adjustment for stage and treatment. However, most studies for all cancers combined, or colorectal cancer, reported that unexplained survival disparities remained after adjusting for various combinations of covariates. Conclusions: While some of the poorer survival faced by Aboriginal and Torres Strait Islander cancer patients can be explained, substantial disparities likely to be related to Aboriginal determinants, remain. It is imperative that future research consider innovative study designs and strength-based approaches to better understand cancer survival for Aboriginal and Torres Strait Islander peoples and to inform evidence-based action.

Quantifying the number of deaths among Aboriginal and Torres Strait Islander cancer patients that could be avoided by removing survival inequalities, Australia 2005-2016.

BACKGROUND: While Aboriginal and Torres Strait Islander peoples have poorer cancer survival than other Australians, absolute measures of survival disparities are lacking. This study quantified crude probabilities of deaths from cancer and other causes and estimated the number of avoidable deaths for Aboriginal and Torres Strait Islanders if these survival disparities were removed. METHODS: Flexible parametric relative survival models were used to estimate reported measures for a population-based cohort of 709,239 Australians (12,830 Aboriginal and Torres Strait Islander peoples), 2005-2016. RESULTS: Among Aboriginal and Torres Strait Islander peoples, the 5-year crude probability of cancer death was 0.44, while it was 0.07 for other causes of death. These probabilities were 0.07 and 0.03 higher than among other Australians, respectively. Magnitude of these disparities varied by cancer type and ranged for cancer deaths from <0.05 for pancreatic, prostate and uterine cancers to 0.20 for cervical and head and neck cancers. Values for disparity in other causes of death were generally lower. Among an average cohort of Aboriginal and Torres Strait Islander peoples diagnosed per year over the most recent five-year diagnosis period (2012-2016, n = 1,269), approximately 133 deaths within 5 years of diagnosis were potentially avoidable if they had the same overall survival as other Australians, with 94 of these deaths due to cancer. The total number of avoided deaths over the entire study period (2005-2016) was 1,348, with 947 of these deaths due to cancer. CONCLUSIONS: Study findings suggest the need to reduce the prevalence of risk factors prevalence, increase screening participation, and improve early detection, diagnosis and treatment rates to achieve more equitable outcomes for a range of cancer types. Reported measures provide unique insights into the impact of a cancer diagnosis among Aboriginal and Torres Strait Islander peoples from a different perspective to standard relative survival measures.

A prognostic survival model for women diagnosed with invasive breast cancer in Queensland, Australia.

PURPOSE: Prognostic models can help inform patients on the future course of their cancer and assist the decision making of clinicians and patients in respect to management and treatment of the cancer. In contrast to previous studies considering survival following treatment, this study aimed to develop a prognostic model to quantify breast cancer-specific survival at the time of diagnosis. METHODS: A large (n = 3323), population-based prospective cohort of women were diagnosed with invasive breast cancer in Queensland, Australia between 2010 and 2013, and followed up to December 2018. Data were collected through a validated semi-structured telephone interview and a self-administered questionnaire, along with data linkage to the Queensland Cancer Register and additional extraction from medical records. Flexible parametric survival models, with multiple imputation to deal with missing data, were used. RESULTS: Key factors identified as being predictive of poorer survival included more advanced stage at diagnosis, higher tumour grade, "triple negative" breast cancers, and being symptom-detected rather than screen detected. The Harrell's C-statistic for the final predictive model was 0.84 (95% CI 0.82, 0.87), while the area under the ROC curve for 5-year mortality was 0.87. The final model explained about 36% of the variation in survival, with stage at diagnosis alone explaining 26% of the variation. CONCLUSIONS: In addition to confirming the prognostic importance of stage, grade and clinical subtype, these results highlighted the independent survival benefit of breast cancers diagnosed through screening, although lead and length time bias should be considered. Understanding what additional factors contribute to the substantial unexplained variation in survival outcomes remains an important objective.

Supportive care needs and psychosocial outcomes of rural versus urban women with breast cancer.

OBJECTIVE: To identify whether supportive care needs vary according to remoteness and area-level socio-economic status and to identify the combinations of socio-demographic, area-level and health factors that are associated with poorer quality of life, psychological distress and severity of unmet supportive care needs. METHODS: Cross sectional data was collected from women with a breast cancer diagnosis (n = 2635) in Queensland, Australia, through a telephone survey including socio-demographic, health, psychosocial and supportive care needs measures. Hierarchical regression and cluster analyses were applied to assess the predictors of unmet need and psychosocial outcomes and to identify socio-demographic and health status profiles of women, comparing their level of unmet needs and psychosocial outcomes. RESULTS: Women living in outer regional areas reported the highest severity of unmet need in the patient care domain. Greater unmet need for health systems and information and patient care was also evident for those in moderately and most disadvantaged areas. Three clusters were identified reflecting (1) older women with poorer health and lower education (19%); (2) younger educated women with better health and private insurance (61%); and (3) physically active women with localised cancer who had completed treatment (20%). Poorer outcomes were evident in the first two of these clusters. CONCLUSIONS: This better understanding of the combinations of characteristics associated with poorer psychosocial outcomes and higher unmet need can be used to identify women with higher supportive care needs early and to target interventions.

Geographic distribution of malignant mesothelioma incidence and survival in Australia.

OBJECTIVES: To understand the geographic distribution of and area-level factors associated with malignant mesothelioma incidence and survival in Australia. MATERIALS AND METHODS: Generalised linear models and Bayesian spatial models were fitted using population registry data. Area-level covariates were socioeconomic quintile, remoteness category and state or territory. The maximised excess events test was used to test for spatial heterogeneity. RESULTS: There was strong evidence of spatial differences in standardised incidence rates for malignant mesothelioma but survival was uniformly poor. Incidence rates varied by state or territory and were lower in remote areas. Patterns in the geographic distribution of modelled incidence counts for malignant mesothelioma differed substantially from patterns of standardised incidence rates. CONCLUSIONS: Geographic variation in the modelled incidence counts of malignant mesothelioma demonstrates varying demand for diagnostic and management services. The long latency period for this cancer coupled with migration complicates any associations with patterns of exposure, however some of the geographic distribution of diagnoses can be explained by the location of historical mines and asbestos-related industries.