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    Susanna Cramb

    This review presents the latest available international data for lung cancer incidence, mortality and survival, emphasizing the established causal relationship between smoking and lung cancer. In 2002, it was estimated that 1.35 million... more
    This review presents the latest available international data for lung cancer incidence, mortality and survival, emphasizing the established causal relationship between smoking and lung cancer. In 2002, it was estimated that 1.35 million people throughout the world were diagnosed with lung cancer, and 1.18 million died of lung cancer-more than for any other type of cancer. There are some key differences in the epidemiology of lung cancer between more developed and less developed countries. In more developed countries, incidence and mortality rates are generally declining among males and are starting to plateau for females, reflecting previous trends in smoking prevalence. In contrast, there are some populations in less developed countries where increasing lung cancer rates are predicted to continue, due to endemic use of tobacco. A higher proportion of lung cancer cases are attributable to nonsmoking causes within less developed countries, particularly among women. Worldwide, the majority of lung cancer patients are diagnosed after the disease has progressed to a more advanced stage. Despite advances in chemotherapy, prognosis for lung cancer patients remains poor, with 5-year relative survival less than 14% among males and less than 18% among females in most countries. Given the increasing incidence of lung cancer in less developed countries and the current lack of effective treatment for advanced lung cancers, these results highlight the need for ongoing global tobacco reform to reduce the international burden of lung cancer.
    We aim to update global lung cancer epidemiology and describe changing trends and disparities. We presented country-specific incidence and mortality from GLOBOCAN 2012, by region and socioeconomic factors via the Human Development Index... more
    We aim to update global lung cancer epidemiology and describe changing trends and disparities. We presented country-specific incidence and mortality from GLOBOCAN 2012, by region and socioeconomic factors via the Human Development Index (HDI). Between- and within-country incidence by histological type was analyzed from Cancer Incidence in Five Continents Volume X (IARC). Trend analyses including the IARC data, cancer registries, and the WHO Mortality database were conducted using Joinpoint regression. Survival was compared between and within countries, and by histology. In 2012, there were 1.82 and 1.59 million new cases and deaths of lung cancer worldwide, respectively. Incidence was highest in very high HDI countries and lowest in low HDI countries (42.2 vs. 7.9/100,000 for males and 21.8 vs. 3.1/100,000 for females, respectively). In most countries with a very high HDI, as male incidence decreased gradually (ranging from -0.3% in Spain to -2.5% in the USA each year), female incidence continued to increase (by 1.4% each year in Australia to 6.1% in recent years in Spain). While histology varied between countries, adenocarcinoma was more common than squamous cell carcinoma, particularly among females (e.g., in Chinese females, the adenocarcinoma-to-squamous cell carcinoma ratio=6.6). Five-year relative survival varied from 2% (Libya) to 30% (Japan), with substantial within-country differences. Lung cancer will continue to be a major health problem well through the first half of this century. Preventive strategies, particularly tobacco control, tailored to populations at highest risk are key to reduce the global burden of lung cancer.
    Disease maps are effective tools for explaining and predicting patterns of disease outcomes across geographical space, identifying areas of potentially elevated risk, and formulating and validating aetiological hypotheses for a disease.... more
    Disease maps are effective tools for explaining and predicting patterns of disease outcomes across geographical space, identifying areas of potentially elevated risk, and formulating and validating aetiological hypotheses for a disease. Bayesian models have become a standard approach to disease mapping in recent decades. This article aims to provide a basic understanding of the key concepts involved in Bayesian disease mapping methods for areal data. It is anticipated that this will help in interpretation of published maps, and provide a useful starting point for anyone interested in running disease mapping methods for areal data. The article provides detailed motivation and descriptions on disease mapping methods by explaining the concepts, defining the technical terms, and illustrating the utility of disease mapping for epidemiological research by demonstrating various ways of visualising model outputs using a case study. The target audience includes spatial scientists in health a...
    The survival inequality faced by Indigenous Australians after a cancer diagnosis is well documented; what is less understood is whether this inequality has changed over time and what this means in terms of the impact a cancer diagnosis... more
    The survival inequality faced by Indigenous Australians after a cancer diagnosis is well documented; what is less understood is whether this inequality has changed over time and what this means in terms of the impact a cancer diagnosis has on Indigenous people. Survival information for all patients identified as either Indigenous (n=3168) or non-Indigenous (n=211,615) and diagnosed in Queensland between 1997 and 2012 were obtained from the Queensland Cancer Registry, with mortality followed up to 31st December, 2013. Flexible parametric survival models were used to quantify changes in the cause-specific survival inequalities and the number of lives that might be saved if these inequalities were removed. Among Indigenous cancer patients, the 5-year cause-specific survival (adjusted by age, sex and broad cancer type) increased from 52.9% in 1997-2006 to 58.6% in 2007-2012, while it improved from 61.0% to 64.9% among non-Indigenous patients. This meant that the adjusted 5-year comparative survival ratio (Indigenous: non-Indigenous) increased from 0.87 [0.83-0.88] to 0.89 [0.87-0.93], with similar improvements in the 1-year comparative survival. Using a simulated cohort corresponding to the number and age-distribution of Indigenous people diagnosed with cancer in Queensland each year (n=300), based on the 1997-2006 cohort mortality rates, 35 of the 170 deaths due to cancer (21%) expected within five years of diagnosis were due to the Indigenous: non-Indigenous survival inequality. This percentage was similar when applying 2007-2012 cohort mortality rates (19%; 27 out of 140 deaths). Indigenous people diagnosed with cancer still face a poorer survival outlook than their non-Indigenous counterparts, particularly in the first year after diagnosis. The improving survival outcomes among both Indigenous and non-Indigenous cancer patients, and the decreasing absolute impact of the Indigenous survival disadvantage, should provide increased motivation to continue and enhance current strategies to further reduce the impact of the survival inequalities faced by Indigenous people diagnosed with cancer.
    An increasing number of studies have identified spatial differences in breast cancer survival. However little is known about whether the structure and dynamics of this spatial inequality are consistent across a region. This study aims to... more
    An increasing number of studies have identified spatial differences in breast cancer survival. However little is known about whether the structure and dynamics of this spatial inequality are consistent across a region. This study aims to evaluate the spatially varying nature of predictors of spatial inequality in relative survival for women diagnosed with breast cancer across Queensland, Australia. All Queensland women aged less than 90 years diagnosed with invasive breast cancer from 1997 to 2007 and followed up to the end of 2008 were extracted from linked Queensland Cancer Registry and BreastScreen Queensland data. Bayesian relative survival models were fitted using various model structures (a spatial regression model, a varying coefficient model and a finite mixture of regressions model) to evaluate the relative excess risk of breast cancer, with the use of Markov chain Monte Carlo computation. The spatially varying coefficient models revealed that some covariate effects may not be constant across the geographic regions of the study. The overall spatial patterns showed lower survival among women living in more remote areas, and higher survival among the urbanised south-east corner. Notwithstanding this, the spatial survival pattern for younger women contrasted with that for older women as well as single women. This complex spatial interplay may be indicative of different factors impacting on survival patterns for these women.
    ABSTRACT
    Although early diagnosis and improved treatment can reduce breast cancer mortality, there still appears to be a geographic differential in patient outcomes. This study aims to determine and quantify spatial inequalities in intended... more
    Although early diagnosis and improved treatment can reduce breast cancer mortality, there still appears to be a geographic differential in patient outcomes. This study aims to determine and quantify spatial inequalities in intended adjuvant (radio-, chemo- and hormonal) therapy usage among women with screen-detected breast cancer in Queensland, Australia. Linked population-based datasets from BreastScreen Queensland and the Queensland Cancer Registry during 1997-2008 for women aged 40-89 years were used. We adopted a Bayesian shared spatial component model to evaluate the relative intended use of each adjuvant therapy across 478 areas as well as common spatial patterns between treatments. Women living closer to a cancer treatment facility were more likely to intend to use adjuvant therapy. This was particularly marked for radiotherapy when travel time to the closest radiation facility was 4 + h (OR =0.41, 95 % CrI: [0.23, 0.74]) compared to <1 h. The shared spatial effect increas...
    Preventing risk factor exposure is vital to reduce the high burden from lung cancer. The leading risk factor for developing lung cancer is tobacco smoking. In Australia, despite apparent success in reducing smoking prevalence, there is... more
    Preventing risk factor exposure is vital to reduce the high burden from lung cancer. The leading risk factor for developing lung cancer is tobacco smoking. In Australia, despite apparent success in reducing smoking prevalence, there is limited information on small area patterns and small area temporal trends. We sought to estimate spatio-temporal patterns for lung cancer risk factors using routinely collected population-based cancer data. The analysis used a Bayesian shared component spatio-temporal model, with male and female lung cancer included separately. The shared component reflected lung cancer risk factors, and was modelled over 477 statistical local areas (SLAs) and 15 years in Queensland, Australia. Analyses were also run adjusting for area-level socioeconomic disadvantage, Indigenous population composition, or remoteness. Strong spatial patterns were observed in the underlying risk factor estimates for both males (median Relative Risk (RR) across SLAs compared to the Quee...
    Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly... more
    Multilevel and spatial models are being increasingly used to obtain substantive information on area-level inequalities in cancer survival. Multilevel models assume independent geographical areas, whereas spatial models explicitly incorporate geographical correlation, often via a conditional autoregressive prior. However the relative merits of these methods for large population-based studies have not been explored. Using a case-study approach, we report on the implications of using multilevel and spatial survival models to study geographical inequalities in all-cause survival. Multilevel discrete-time and Bayesian spatial survival models were used to study geographical inequalities in all-cause survival for a population-based colorectal cancer cohort of 22,727 cases aged 20-84 years diagnosed during 1997-2007 from Queensland, Australia. Both approaches were viable on this large dataset, and produced similar estimates of the fixed effects. After adding area-level covariates, the betwe...
    This study examines the influence of cancer stage, distance to treatment facilities and area disadvantage on breast and colorectal cancer spatial survival inequalities. We also estimate the number of premature deaths after adjusting for... more
    This study examines the influence of cancer stage, distance to treatment facilities and area disadvantage on breast and colorectal cancer spatial survival inequalities. We also estimate the number of premature deaths after adjusting for cancer stage to quantify the impact of spatial survival inequalities. Population-based descriptive study of residents aged <90 years in Queensland, Australia diagnosed with primary invasive breast (25,202 females) or colorectal (14,690 males, 11,700 females) cancers during 1996-2007. Bayesian hierarchical models explored relative survival inequalities across 478 regions. Cancer stage and disadvantage explained the spatial inequalities in breast cancer survival, however spatial inequalities in colorectal cancer survival persisted after adjustment. Of the 6,019 colorectal cancer deaths within 5 years of diagnosis, 470 (8%) were associated with spatial inequalities in non-diagnostic factors, i.e. factors beyond cancer stage at diagnosis. For breast cancers, of 2,412 deaths, 170 (7%) were related to spatial inequalities in non-diagnostic factors. Quantifying premature deaths can increase incentive for action to reduce these spatial inequalities.
    This paper presents the latest international descriptive epidemiological data for invasive breast cancer amongst women, including incidence, survival and mortality, as well as information on mammographic screening programmes. Almost 1.4... more
    This paper presents the latest international descriptive epidemiological data for invasive breast cancer amongst women, including incidence, survival and mortality, as well as information on mammographic screening programmes. Almost 1.4 million women were diagnosed with breast cancer worldwide in 2008 and approximately 459,000 deaths were recorded. Incidence rates were much higher in more developed countries compared to less developed countries (71.7/100,000 and 29.3/100,000 respectively, adjusted to the World 2000 Standard Population) whereas the corresponding mortality rates were 17.1/100,000 and 11.8/100,000. Five-year relative survival estimates range from 12% in parts of Africa to almost 90% in the United States, Australia and Canada, with the differential linked to a combination of early detection, access to treatment services and cultural barriers. Observed improvements in breast cancer survival in more developed parts of the world over recent decades have been attributed to the introduction of population-based screening using mammography and the systemic use of adjuvant therapies. The future worldwide breast cancer burden will be strongly influenced by large predicted rises in incidence throughout parts of Asia due to an increasingly "westernised" lifestyle. Efforts are underway to reduce the global disparities in survival for women with breast cancer using cost-effective interventions.
    ABSTRACT
    To examine the differential in cancer survival between Indigenous and non-Indigenous people in Queensland in relation to time after diagnosis, remoteness and area-socioeconomic disadvantage. Descriptive study of population-based data on... more
    To examine the differential in cancer survival between Indigenous and non-Indigenous people in Queensland in relation to time after diagnosis, remoteness and area-socioeconomic disadvantage. Descriptive study of population-based data on all 150,059 Queensland residents of known Indigenous status aged 15 years and over who were diagnosed with a primary invasive cancer during 1997-2006. Hazard ratios for the categories of area-socioeconomic disadvantage, remoteness and Indigenous status, as well as conditional 5-year survival estimates. Five-year survival was lower for Indigenous people diagnosed with cancer (50.3%; 95% CI, 47.8%-52.8%) compared with non-Indigenous people (61.9%; 95% CI, 61.7%-62.2%). There was no evidence that this differential varied by remoteness (P = 0.780) or area-socioeconomic disadvantage (P = 0.845). However, it did vary by time after diagnosis. In a time-varying survival model stratified by age, sex and cancer type, the 50% excess mortality in the first year (adjusted HR, 1.50; 95% CI, 1.38-1.63) reduced to near unity at 2 years after diagnosis (HR, 1.03; 95% CI, 0.78-1.35). After a wide disparity in cancer survival in the first 2 years after diagnosis, Indigenous patients with cancer who survive these 2 years have a similar outlook to non-Indigenous patients. Access to services and socioeconomic factors are unlikely to be the main causes of the early lower Indigenous survival, as patterns were similar across remoteness and area-socioeconomic disadvantage. There is an urgent need to identify the factors leading to poor outcomes early after diagnosis among Indigenous people with cancer.