ORCID Profile
0000-0001-9041-9531
Current Organisations
Institute of Nuclear Physics, Polish Academy of Sciences
,
Queensland University of Technology
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Applied Statistics | Biostatistics | Statistical Theory | Statistics |
Publisher: Springer Science and Business Media LLC
Date: 04-10-2014
Publisher: Elsevier BV
Date: 02-2021
Publisher: Elsevier BV
Date: 08-2016
DOI: 10.1016/J.CANEP.2016.05.002
Abstract: 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.
Publisher: Elsevier BV
Date: 11-2017
DOI: 10.1016/J.SSTE.2017.09.002
Abstract: Interpreting changes over time in small-area variation in cancer survival, in light of changes in cancer incidence, aids understanding progress in cancer control, yet few space-time analyses have considered both measures. Bayesian space-time hierarchical models were applied to Queensland Cancer Registry data to examine geographical changes in cancer incidence and relative survival over time for the five most common cancers (colorectal, melanoma, lung, breast, prostate) diagnosed during 1997-2004 and 2005-2012 across 516 Queensland residential small-areas. Large variation in both cancer incidence and survival was observed. Survival improvements were fairly consistent across the state, although small for lung cancer. Incidence changes varied by location and cancer type, ranging from lung and colorectal cancers remaining relatively constant over time, to prostate cancer dramatically increasing across the entire state. Reducing disparities in cancer-related outcomes remains a health priority, and space-time modelling of different measures provides an important mechanism by which to monitor progress.
Publisher: Springer Science and Business Media LLC
Date: 13-12-2022
Publisher: Elsevier BV
Date: 06-2020
Publisher: Elsevier BV
Date: 10-2016
Publisher: The Open Journal
Date: 05-04-2023
DOI: 10.21105/JOSS.05328
Publisher: Elsevier BV
Date: 05-2022
DOI: 10.1016/J.LUNGCAN.2022.03.017
Abstract: To understand the geographic distribution of and area-level factors associated with malignant mesothelioma incidence and survival in Australia. 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. 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. 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.
Publisher: Elsevier BV
Date: 11-2016
DOI: 10.1016/J.SSTE.2016.08.002
Abstract: Despite improvements in cancer survival across many developed countries, it is unclear how survival is changing over time in small areas. This study investigated changes in breast and colorectal cancer survival across 478 areas over 11 years (2001-2011), and the influence of early diagnosis on changes. Queensland Cancer Registry data were analysed using an introduced Bayesian spatio-temporal flexible parametric relative survival model. All areas showed survival improvements between 2001-2003 and 2008-2011. The median absolute 5-year survival improvement for localised breast cancer was small (1.8%), compared to advanced (4.8%) and unknown (7.9%) breast cancer, as well as localised (2.6%), advanced (5.0%) and unknown (4.8%) colorectal cancers. Improvements in non-diagnostic factors, such as patient treatment and management, appear to be the main influence on recent survival increases for breast and colorectal cancers. Important inequalities in cancer survival between small areas remain.
Publisher: Elsevier BV
Date: 11-2012
DOI: 10.1016/J.HEALTHPLACE.2012.07.006
Abstract: 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.
Publisher: Elsevier BV
Date: 06-2015
DOI: 10.1016/J.CANEP.2015.03.001
Abstract: 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 Queensland average ranged from 0.48 to 2.00) and females (median RR range across SLAs 0.53-1.80), with high risks observed in many remote areas. Strong temporal trends were also observed. Males showed a decrease in the underlying risk across time, while females showed an increase followed by a decrease in the final 2 years. These patterns were largely consistent across each SLA. The high underlying risk estimates observed among disadvantaged, remote and indigenous areas decreased after adjustment, particularly among females. The modelled underlying risks appeared to reflect previous smoking prevalence, with a lag period of around 30 years, consistent with the time taken to develop lung cancer. The consistent temporal trends in lung cancer risk factors across small areas support the hypothesis that past interventions have been equally effective across the state. However, this also means that spatial inequalities have remained unaddressed, highlighting the potential for future interventions, particularly among remote areas.
Publisher: Elsevier BV
Date: 03-2022
DOI: 10.1016/J.DIABRES.2022.109239
Abstract: To investigate factors independently associated with time-to-(being)-ulcer-free, time-varying effects and predict adjusted ulcer-free probabilities, in a large prospective cohort with diabetes-related foot ulcers (DFU) followed-up for 24 months. Patients presenting with DFU(s) to 65 Diabetic Foot Services across Queensland, Australia, between July-2011 and December-2017 were included. Demographic, comorbidity, limb, ulcer, and treatment factors were captured at presentation. Patients were followed-up until ulcer-free (all DFU(s) healed), utation, death or two years. Factors associated with time-to-ulcer-free were investigated using both Cox proportional hazards and flexible parametric survival models to explore time-varying effects and plot predicted adjusted ulcer-free probability graphs. Of 4,709 included patients (median age 63 years, 69.5% male), median time-to-ulcer-free was 112 days (IQR:40->730), with 68.4% ulcer-free within two years. Factors independently associated with longer time-to-ulcer-free were each year of age younger than 60 years, living in a regional or remote area, smoking, neuropathy, peripheral artery disease (PAD), ulcer size >1 cm Multiple factors predicted longer and shorter time-to-ulcer-free in people presenting with DFUs. Considering these factors, their time-varying effects and adjusted ulcer-free probability graphs, should aid the prediction of the likely time-to-(being)-ulcer-free for DFU patients.
Publisher: The Royal Society
Date: 02-2021
DOI: 10.1098/RSOS.210085
Publisher: Elsevier BV
Date: 12-2013
DOI: 10.1016/J.CANEP.2013.09.014
Abstract: This paper reviews international patterns in sinonasal cancer incidence and mortality in light of changes in exposure to known risk factors. Sinonasal tumours are relatively rare, but they have the second highest occupational attributable fraction of all types of cancer, with a well-established link for workers exposed to wood dust. Data for a variety of countries, mainly in Europe, North America and the Asia-Pacific region, were obtained from publicly accessible sources and supplemented with information requested from selected cancer registries. Rates were directly age-standardised to the World Health Organization Standard Population. The average annual incidence of sinonasal cancer was typically between 5 and 10 per million in males and between 2 and 5 per million in females between 2004 and 2008. Denmark reported the highest rates, with incidence continuing to increase, in contrast to trends in other countries which either remained relatively stable, or were decreasing slightly. There were significant recent decreases in sinonasal cancer mortality rates within two-thirds of the included countries. Our observations are generally consistent with efforts to limit exposure to wood dust and other potentially causal substances in the workplace, as well as a reduction in the prevalence of smoking in many developed countries. Of concern is that occupational and behavioural risks related to sinonasal cancer are likely to increase among people in less developed countries into the future. However the incentive to intervene in these countries is limited by the lack of accurate and reliable cancer data.
Publisher: Springer Science and Business Media LLC
Date: 15-04-2020
Publisher: Elsevier BV
Date: 04-2023
Publisher: Research Square Platform LLC
Date: 19-04-2023
DOI: 10.21203/RS.3.RS-2829471/V1
Abstract: Small area statistics on health outcomes like daily smoking prevalence are vital for measuring community progress towards healthy lifestyles. Due to sparse data and remoteness in Australia, the National Health Survey is insufficient to estimate at the disaggregated statistical areas (SA) in Australia, even sometimes at the sub-national level. This study estimates daily smoking prevalence for Australian adults at various sub-national levels comprising 8 States and Territories, 88 Statistical Areas Level 4 (SA4s), and 334 Statistical Areas Level 3 (SA3s) by extending widely used area-level models developed at the detailed SA3 level as a form of hierarchical Bayesian model and fitted by Markov Chain Monte Carlo simulation. Detailed level direct estimates with their smoothed standard errors from the 2017-18 National Health Survey are used as model inputs. Area-level models accounting for the detailed level structured (spatial) and unstructured (non-spatial) random effects provide slightly higher bias and lower coverage at the disaggregated SA4 level. An extension of area-level models by including intermediate (SA4) level non-spatial random effects is proposed to improve the unbiasedness and coverage of the model-based estimators at higher aggregation levels and is found to be suitable for the Australian smoking prevalence data through examination of model performance statistics.
Publisher: Springer Science and Business Media LLC
Date: 10-2019
DOI: 10.1186/S12942-019-0185-9
Abstract: It is well known that the burden caused by cancer can vary geographically, which may relate to differences in health, economics or lifestyle. However, to date, there was no comprehensive picture of how the cancer burden, measured by cancer incidence and survival, varied by small geographical area across Australia. The Atlas consists of 2148 Statistical Areas level 2 across Australia defined by the Australian Statistical Geography Standard which provide the best compromise between small population and small area. Cancer burden was estimated for males, females, and persons separately, with 50 unique sex-specific (males, females, all persons) cancer types analysed. Incidence and relative survival were modelled with Bayesian spatial models using the Leroux prior which was carefully selected to provide adequate spatial smoothing while reflecting genuine geographic variation. Markov Chain Monte Carlo estimation was used because it facilitates quantifying the uncertainty of the posterior estimates numerically and visually. The results of the statistical model and visualisation development were published through the release of the Australian Cancer Atlas ( atlas.cancer.org.au ) in September, 2018. The Australian Cancer Atlas provides the first freely available, digital, interactive picture of cancer incidence and survival at the small geographical level across Australia with a focus on incorporating uncertainty, while also providing the tools necessary for accurate estimation and appropriate interpretation and decision making. The success of the Atlas will be measured by how widely it is used by key stakeholders to guide research and inform decision making. It is hoped that the Atlas and the methodology behind it motivates new research opportunities that lead to improvements in our understanding of the geographical patterns of cancer burden, possible causes or risk factors, and the reasons for differences in variation between cancer types, both within Australia and globally. Future versions of the Atlas are planned to include new data sources to include indicators such as cancer screening and treatment, and extensions to the statistical methods to incorporate changes in geographical patterns over time.
Publisher: Springer Science and Business Media LLC
Date: 24-07-2011
Publisher: Elsevier BV
Date: 04-2020
Publisher: Wiley
Date: 06-2009
DOI: 10.1038/OBY.2008.660
Abstract: We examined the prospective association of childhood BMI z-score and BMI categories (normal or overweight) with young adult diabetes, controlling for early life, childhood, and adolescence factors. A subs le of 2,639 young adults from the Mater-University study of pregnancy (MUSP) and its outcomes, a prospective birth cohort who were born in Brisbane, Australia and for whom we had measured height and weight at 5 years and self-reported diabetes at age 21 years. The risk of developing diabetes by age 21 years was greater among young adults who had greater BMI z-score or were overweight at age 5 years than those who had normal BMI at age 5 years. Young adults who were overweight at age 5 years had an increased odds ratio of 2.60 (95% confidence interval (CI): 1.29, 5.22, in age- and sex-adjusted model) of experiencing diabetes by age 21 years. Adjustment for potential confounders and mediators including intrauterine environmental factors, childhood dietary patterns, television watching, participation in sports and exercise, and current weight, did not substantively alter these associations. Overweight and increasing BMI z-score at childhood is an independent predictor of young adult's type 1 and type 2 diabetes. Findings of this study suggest that childhood BMI may be central to the development and rising incidence of all diabetes.
Publisher: Springer Science and Business Media LLC
Date: 17-10-2020
DOI: 10.1186/S12942-020-00234-0
Abstract: Cancer atlases often provide estimates of cancer incidence, mortality or survival across small areas of a region or country. A recent ex le of a cancer atlas is the Australian cancer atlas (ACA), that provides interactive maps to visualise spatially smoothed estimates of cancer incidence and survival for 20 different cancer types over 2148 small areas across Australia. The present study proposes a multivariate Bayesian meta-analysis model, which can model multiple cancers jointly using summary measures without requiring access to the unit record data. This new approach is illustrated by modelling the publicly available spatially smoothed standardised incidence ratios for multiple cancers in the ACA ided into three groups: common, rare/less common and smoking-related. The multivariate Bayesian meta-analysis models are fitted to each group in order to explore any possible association between the cancers in three remoteness regions: major cities, regional and remote areas across Australia. The correlation between the pairs of cancers included in each multivariate model for a group was examined by computing the posterior correlation matrix for each cancer group in each region. The posterior correlation matrices in different remoteness regions were compared using Jennrich’s test of equality of correlation matrices (Jennrich in J Am Stat Assoc. 1970 (330):904–12. 10.1080/01621459.1970.10481133 ). Substantive correlation was observed among some cancer types. There was evidence that the magnitude of this correlation varied according to remoteness of a region. For ex le, there has been significant negative correlation between prostate and lung cancer in major cities, but zero correlation found in regional and remote areas for the same pair of cancer types. High risk areas for specific combinations of cancer types were identified and visualised from the proposed model. Publicly available spatially smoothed disease estimates can be used to explore additional research questions by modelling multiple cancer types jointly. These proposed multivariate meta-analysis models could be useful when unit record data are unavailable because of privacy and confidentiality requirements.
Publisher: American Diabetes Association
Date: 07-2021
DOI: 10.2337/DC20-3120
Publisher: Public Library of Science (PLoS)
Date: 26-10-2022
DOI: 10.1371/JOURNAL.PONE.0276761
Abstract: Diabetes is on the rise as the worldwide population ages. While physical activity can help protect against diabetes, ageing is commonly associated with reduced physical activity. This study aimed to examine if physical activity differs by diabetes status in mid-aged adults, how this association changes over time, and whether physical activity-related sociodemographic factors and health indicators differ in those with and without diabetes. Data came from four waves of the How Areas in Brisbane Influence HealTh and AcTivity (HABITAT), a longitudinal study of mid-age adults living in Brisbane, Australia. Random effects/Expectation-maximisation (RE-EM) regression trees were used to identify factors affecting physical activity among those with and without diabetes, both separately and combined. At study entry, those with diabetes had a higher median age of 58 years (95% CI: 57–60) and a lower median physical activity of 699 MET.min/week (95% CI: 599–799) than people without diabetes (53 years (95% CI: 53–53) and 849 MET.min/week (95% CI: 799–899)). However, the strongest factors influencing physical activity were BMI and gender, not diabetes status. It is vital to promote physical activity among adults, in particular among those with high BMI and women, as well as those with and at high risk of diseases like diabetes.
Publisher: Hindawi Limited
Date: 20-11-2019
DOI: 10.1155/2019/2680972
Abstract: Complex networks in reality may suffer from target attacks which can trigger the breakdown of the entire network. It is therefore pivotal to evaluate the extent to which a network could withstand perturbations. The research on network robustness has proven as a potent instrument towards that purpose. The last two decades have witnessed the enthusiasm on the studies of network robustness. However, existing studies on network robustness mainly focus on multilayer networks while little attention is paid to multipartite networks which are an indispensable part of complex networks. In this study, we investigate the robustness of multipartite networks under intentional node attacks. We develop two network models based on the largest connected component theory to depict the cascading failures on multipartite networks under target attacks. We then investigate the robustness of computer-generated multipartite networks with respect to eight node centrality metrics. We discover that the robustness of multipartite networks could display either discontinuous or continuous phase transitions. Interestingly, we discover that larger number of partite sets of a multipartite network could increase its robustness which is opposite to the phenomenon observed on multilayer networks. Our findings shed new lights on the robust structure design of complex systems. We finally present useful discussions on the applications of existing percolation theories that are well studied for network robustness analysis to multipartite networks. We show that existing percolation theories are not amenable to multipartite networks. Percolation on multipartite networks still deserves in-depth efforts.
Publisher: American Association for Cancer Research (AACR)
Date: 09-2020
DOI: 10.1158/1055-9965.EPI-20-0299
Abstract: This study quantifies the number of potentially “avoided”cancer deaths due to differences in 10-year relative survival between three time periods, reflecting temporal improvements in cancer diagnostic and/or treatment practices in Australia. National population-based cohort of 2,307,565 Australians ages 15 to 89 years, diagnosed with a primary invasive cancer from 1985 to 2014 with mortality follow-up to December 31, 2015. Excess mortality rates and crude probabilities of cancer deaths were estimated using flexible parametric relative survival models. Crude probabilities were then used to calculate “avoided cancer deaths” (reduced number of cancer deaths within 10 years of diagnosis due to survival changes since 1985–1994) for all cancers and 13 leading cancer types. For each cancer type, excess mortality (in the cancer cohort vs. the expected population mortality) was significantly lower for more recently diagnosed persons. For all cancers combined, the number of “avoided cancer deaths” (vs. 1985–1994) was 4,877 (1995–2004) and 11,385 (2005–2014) among males. Prostate (1995–2004: 2,144 2005–2014: 5,099) and female breast cancer (1,127 and 2,048) had the highest number of such deaths, whereas & were avoided for pancreatic or lung cancers across each period. Screening and early detection likely contributed to the high number of “avoided cancer deaths” for prostate and female breast cancer, whereas early detection remains difficult for lung and pancreatic cancers, highlighting the need for improved preventive and screening measures. Absolute measures such as “avoided cancer deaths” can provide a more tangible estimate of the improvements in cancer survival than standard net survival measures.
Publisher: Cambridge University Press (CUP)
Date: 29-10-2018
DOI: 10.1017/S0950268818002807
Abstract: Dengue fever (DF) is one of the world's most disabling mosquito-borne diseases, with a variety of approaches available to model its spatial and temporal dynamics. This paper aims to identify and compare the different spatial and spatio-temporal Bayesian modelling methods that have been applied to DF and examine influential covariates that have been reportedly associated with the risk of DF. A systematic search was performed in December 2017, using Web of Science, Scopus, ScienceDirect, PubMed, ProQuest and Medline (via Ebscohost) electronic databases. The search was restricted to refereed journal articles published in English from January 2000 to November 2017. Thirty-one articles met the inclusion criteria. Using a modified quality assessment tool, the median quality score across studies was 14/16. The most popular Bayesian statistical approach to dengue modelling was a generalised linear mixed model with spatial random effects described by a conditional autoregressive prior. A limited number of studies included spatio-temporal random effects. Temperature and precipitation were shown to often influence the risk of dengue. Developing spatio-temporal random-effect models, considering other priors, using a dataset that covers an extended time period, and investigating other covariates would help to better understand and control DF transmission.
Publisher: Springer International Publishing
Date: 2020
Publisher: Elsevier BV
Date: 10-2016
Publisher: Springer Science and Business Media LLC
Date: 20-10-2023
DOI: 10.1007/S10552-022-01643-1
Abstract: In Australia, Aboriginal and Torres Strait Islander peoples (First Nations population) often have low overall cancer survival, as do all residents of geographically remote areas. This study aimed to quantify the survival disparity between First Nations and other Queenslanders for 12 common cancer types by remoteness areas. For all Queensland residents aged 20–89 years diagnosed with a primary invasive cancer during 1997–2016, we ran flexible parametric survival models incorporating age, First Nations status, sex, diagnosis time period, area-level socioeconomic status, remoteness categories and where appropriate, broad cancer type. Three survival measures were predicted: cause-specific survival, survival differences and the comparative survival ratio, each standardised to First Nations peoples’ covariate distributions. The standardised five-year cause-specific cancer survival was 60% for urban First Nations and 65% for other Queenslanders, while remote residents were 54% (First Nations) and 58% (other). The absolute survival differential between First Nations and other Queenslanders was often similar, regardless of remoteness of residence. The greatest absolute difference in five-year standardised cancer survival was for head and neck cancers, followed by cervical cancer. The five-year comparative survival ratio (First Nations: other Queenslanders) for urban cancer patients was 0.91 (95% CI 0.90–0.93), similar to outer regional, inner regional and remote areas. The greatest comparative survival differential was for oesophageal cancer. First Nations’ survival inequalities are largely independent of geographical remoteness. It remains a priority to determine the contribution of other potential factors such as the availability of culturally acceptable diagnostic, management and/or support services.
Publisher: Wiley
Date: 12-2013
DOI: 10.1111/ANZS.12059
Publisher: American Physical Society (APS)
Date: 16-06-2021
Publisher: American Physical Society (APS)
Date: 16-06-2020
Publisher: American Physical Society (APS)
Date: 21-06-2021
Publisher: Elsevier BV
Date: 06-2013
DOI: 10.12954/PI.12014
Publisher: Public Library of Science (PLoS)
Date: 05-05-2016
Publisher: MDPI AG
Date: 30-01-2020
Abstract: Spatial models are becoming more popular in time-to-event data analysis. Commonly, the intrinsic conditional autoregressive prior is placed on an area level frailty term to allow for correlation between areas. We considered a range of Bayesian Weibull and Cox semiparametric spatial models to describe a dataset on hospitalisation of dengue. This paper aimed to extend these two models, to evaluate the suitability of these models for estimation and prediction of the length of stay, compare different spatial priors, and determine factors that significantly affect the duration of hospital stay for dengue fever patients in the case study location, namely Wahidin hospital in Makassar, Indonesia. We compared two different models with three different spatial priors with respect to goodness of fit and generalisability. For all models considered, the Leroux prior was preferred over the intrinsic conditional autoregressive and independent priors, but Cox and Weibull versions had similar predictive performance, model fit, and results. Age and platelet count were negatively associated with the length of stay, while red blood cell count was positively associated with the length of stay of dengue patients at this hospital. Using appropriate Bayesian spatial survival models enables identification of factors that substantively affect the length of stay.
Publisher: Springer International Publishing
Date: 2020
Publisher: Springer Science and Business Media LLC
Date: 10-2020
Abstract: The electron (anti-)neutrino component of the T2K neutrino beam constitutes the largest background in the measurement of electron (anti-)neutrino appearance at the far detector. The electron neutrino scattering is measured directly with the T2K off-axis near detector, ND280. The selection of the electron (anti-)neutrino events in the plastic scintillator target from both neutrino and anti-neutrino mode beams is discussed in this paper. The flux integrated single differential charged-current inclusive electron (anti-)neutrino cross-sections, dσ/dp and dσ/d cos( θ ), and the total cross-sections in a limited phase-space in momentum and scattering angle ( p 300 MeV/c and θ ≤ 45°) are measured using a binned maximum likelihood fit and compared to the neutrino Monte Carlo generator predictions, resulting in good agreement.
Publisher: American Physical Society (APS)
Date: 02-06-2020
Publisher: Springer Science and Business Media LLC
Date: 2011
Publisher: Oxford University Press (OUP)
Date: 06-09-2007
DOI: 10.1093/AJE/KWM224
Abstract: It has been suggested that sleeping problems are causally associated with obesity in early life, but most studies examining this association have been cross-sectional. The authors used a population-based birth cohort of 2,494 children who were born between 1981 and 1983 in Brisbane, Australia, to examine the prospective association between early-life sleeping problems (at ages 6 months and 2-4 years) and obesity at age 21 years. The authors compared mean body mass indices (BMIs weight (kg)/height (m)2) and persons in the categories of overweight (BMI 25.0-29.9) and obesity (BMI > or =30) among offspring at age 21 years according to maternally reported childhood sleeping problems. They found that young adult BMI and the prevalence of obesity were greater in offspring who had had sleeping problems at ages 2-4 years than in with those who had not had sleeping problems. These associations were robust to adjustment for a variety of potential confounders, including offspring sex, maternal mental health, and BMI, and several mediators, including adolescent dietary patterns and television-watching. These findings provide some evidence for a long-term impact of childhood sleeping problems on the later development of obesity.
Publisher: Elsevier BV
Date: 08-2017
Publisher: Springer Science and Business Media LLC
Date: 12-2015
Publisher: Springer Science and Business Media LLC
Date: 07-03-2016
Publisher: Elsevier BV
Date: 10-2019
DOI: 10.1016/J.CANEP.2019.101568
Abstract: While net probabilities of death in the relative survival framework ignore competing causes of death, crude probabilities allow estimation of the real risk of cancer deaths. This study quantifies temporal trends in net and crude probabilities of death. Australian population-based cohort of 2,015,903 people aged 15-89 years, diagnosed with a single primary invasive cancer from 1984 to 2013 with mortality follow-up to 31 December 2014. Survival was analyzed with the cohort method. Flexible parametric relative survival models were used to estimate both probability measures by diagnosis year for all cancers and selected leading sites. For each site, excess mortality rates reduced over time, especially for prostate cancer. While both the 10-year net and crude probability of cancer deaths decreased over time, specific patterns varied. For ex le, the crude probability of lung cancer deaths for males aged 50 years decreased from 0.90 (1984) to 0.79 (2013) whereas the corresponding probabilities for kidney cancer were 0.64 and 0.18 respectively. Patterns for crude probabilities of competing deaths were relatively constant. Although for younger patients, both net and crude measures were similar, crude probability of competing deaths increased with age, hence for older ages net and crude measures were different except for lung and pancreas cancers. The observed reductions in probabilities of death over three decades for Australian cancer patients are encouraging. However, this study also highlights the ongoing mortality burden following a cancer diagnosis, and the need for continuing efforts to improve cancer prevention, diagnosis and treatment.
Publisher: American Association for Cancer Research (AACR)
Date: 09-2019
DOI: 10.1158/1055-9965.EPI-19-0203
Abstract: China contributes to almost half of the esophageal cancer cases diagnosed globally each year. However, the prognosis information of this disease in this large population is scarce. Data on a population-based cohort consisting of residents of Shandong Province, China who were diagnosed with esophageal cancer during the period from 2005 to 2014 were analyzed. The cancer-specific survival rates were estimated using Kaplan–Meier analysis. Discrete-time multilevel mixed-effects survival models were used to investigate socioeconomic status (SES) disparities on esophageal cancer survival. The unadjusted 1-, 3-, and 5-year cause-specific survival rates were 59.6% [95% confidence interval (CI), 59.2%–59.9%], 31.9% (95% CI, 31.5%–32.3%), and 23.6% (95% CI, 23.1%–24.0%), respectively. Patients of blue-collar occupations had higher risk of esophageal cancer–related death than those of white-collar occupations in the first 2 years after diagnosis. Rural patients had higher risk of death than urban patients in the first 3 years after diagnosis. The risks of esophageal cancer–related death among patients living in low/middle/high SES index counties were not different in the first 2 years after diagnosis. However, patients living in high SES index counties had better long-term survival (3–5 years postdiagnosis) than those living in middle or low SES index counties. Socioeconomic inequalities in esophageal cancer survival exist in this Chinese population. Higher in idual- or area-level SES is associated with better short-term or long-term cancer survival. Elucidation of the relative roles of the SES factors on survival could guide interventions to reduce disparities in the prognosis of esophageal cancer.
Publisher: Oxford University Press (OUP)
Date: 09-2021
Abstract: Myeloproliferative neoplasms (MPNs) are a relatively new group of blood cancers arising from genetic mutations in haematopoietic stem cells. Diagnostic delay is associated with thromboses, strokes and heart attacks. We investigated geographic variation in diagnosis and survival for classic MPNs. Data for classic MPNs were obtained from the Australian Cancer Database. Leroux spatial models for incidence and survival were fitted using CARBayes, WinBUGS via R and tests for spatial clustering were conducted. The age-standardised incidence rate was 4.9 (95% CI: 4.8-5.0) per 100,000 person-years during 2007-2016 with relative survival of 78% (77%, 79%) at 5 years after diagnosis. Strong evidence of spatial variation in incidence was observed (p & 0.001), with incidence rates low in Tasmania (4.2 per 100,000 person-years, 95% CI: 3.5-5.0) and Western Australia (6.1, 5.6-6.6) and high in Victoria (9.5, 9.2-9.9) and Queensland (10.6, 10.2-11.1). Differences between states and territories could not be explained by population rates of genetic testing or the proportion of registered cases with histological evidence. Stark spatial differences in incidence rates of classic MPNs suggest that varying diagnosis and registration patterns between states results in under-recognition, and potentially undertreatment. It is imperative that reporting is consistent so that sound evidence is available for efforts to reduce disparities in diagnosis and management. Early identification of MPNs is crucial, however, strong spatial geographical variation in incidence rates suggest diagnostic and notification practices may not be consistent across the country.
Publisher: AMPCo
Date: 03-2012
DOI: 10.5694/MJA11.11194
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 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.
Publisher: Wiley
Date: 04-2009
DOI: 10.1038/OBY.2008.594
Abstract: We examined whether behavioral problems in childhood and adolescence are associated with young adults' BMI and obesity, and tested whether childhood behavioral problems have a greater impact on young adults' obesity than adolescent behavioral problems. The data were from the Mater-University of Queensland Study of Pregnancy (MUSP) and Its Outcomes, a population-based birth cohort study commenced in Brisbane, Australia, in 1981. A subs le of 2,278 children for whom we had prospective information on their behavioral problems at ages 5 and 14 and measured BMI, and its categories (normal, overweight, and obese) at age 21 was chosen. Young adults who experienced behavioral problems at ages 5 or 14 had a greater average BMI and were more likely to be obese compared to young adults without behavioral problems at both ages. The childhood onset group was at greater risk of becoming obese by age 21 compared to the adolescent onset group (P = 0.04). These associations remained consistent after adjusting for a variety of potential covariates including maternal characteristics (i.e., demographics and life style), child dietary patterns, family meals, television (TV) watching, and participation in sports and exercise at 14 years. Childhood as well as persistent behavioral problems during childhood and adolescence predicts young adults' BMI and obesity. Although further studies are needed to confirm this association, there is a need for close monitoring of children presenting with behavioral problems.
Publisher: Elsevier BV
Date: 06-2012
DOI: 10.1016/J.CANEP.2012.02.007
Abstract: 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.
Publisher: The Royal Society
Date: 08-2020
DOI: 10.1098/RSOS.192151
Abstract: Analysis of spatial patterns of disease is a significant field of research. However, access to unit-level disease data can be difficult for privacy and other reasons. As a consequence, estimates of interest are often published at the small area level as disease maps. This motivates the development of methods for analysis of these ecological estimates directly. Such analyses can widen the scope of research by drawing more insights from published disease maps or atlases. The present study proposes a hierarchical Bayesian meta-analysis model that analyses the point and interval estimates from an online atlas. The proposed model is illustrated by modelling the published cancer incidence estimates available as part of the online Australian Cancer Atlas (ACA). The proposed model aims to reveal patterns of cancer incidence for the 20 cancers included in ACA in major cities, regional and remote areas. The model results are validated using the observed areal data created from unit-level data on cancer incidence in each of 2148 small areas. It is found that the meta-analysis models can generate similar patterns of cancer incidence based on urban/rural status of small areas compared with those already known or revealed by the analysis of observed data. The proposed approach can be generalized to other online disease maps and atlases.
Publisher: American Physical Society (APS)
Date: 21-07-2020
Publisher: Oxford University Press (OUP)
Date: 09-2021
Abstract: Diabetes-related foot disease is the leading cause of lower limb utations in Queensland. Amputations can be either minor (below the ankle joint) or major (above the ankle joint). Minor utations may be performed to prevent major utations prophylactically, but how these forms of utations interrelate, and where their interrelationships are weakest and strongest, is unknown. Knowledge of small-area variation in interrelations between minor and major utations is relevant to prevention and improved management of foot disease. Data on lower limb utations performed between 2014 and 2018 on patients aged 20+ years with diabetes were obtained from the Queensland Hospital Admitted Patient Data Collection. Rates were calculated using the number of people, rather than the number of utation procedures. A Bayesian hierarchical spatial multivariate model was used to examine patterns over 516 populated statistical areas 2 in Queensland. During 2014 to 2018, 3,548 Queenslanders had at least one minor utation, and 1,114 had at least one major utation. Modelled utation rates varied markedly across the State (standardised morbidity ratio (SMR) IQR: 0.67 to 1.22), with areas in far north Queensland having extremely high rates. There was consistently high area-level correlation between minor and major utation rates. The highest SMRs for both minor and major utations were in the Northern Peninsula. Elevated rates of minor and major utations in areas in Queensland, most noticeably the far north, indicate an urgent need for greater support for people with diabetes-related foot disease. Text: Large differences in minor and major utation rates across Queensland indicate that certain regions require greater assistance in managing diabetes-related foot disease.
Publisher: Oxford University Press (OUP)
Date: 02-03-2021
DOI: 10.1093/PTEP/PTAB014
Abstract: We report measurements of the flux-integrated ν̅μ and ν̅μ + νμ charged-current cross-sections on water and hydrocarbon targets using the T2K anti-neutrino beam with a mean beam energy of 0.86 GeV. The signal is defined as the (anti-)neutrino charged-current interaction with one induced $\\mu^\\pm$ and no detected charged pion or proton. These measurements are performed using a new WAGASCI module recently added to the T2K setup in combination with the INGRID Proton Module. The phase space of muons is restricted to the high-detection efficiency region, $p_{\\mu}& ~{\\rm MeV}/c$ and $\\theta_{\\mu}& ^{\\circ}$, in the laboratory frame. An absence of pions and protons in the detectable phase spaces of $p_{\\pi}& ~{\\rm MeV}/c$, $\\theta_{\\pi}& ^{\\circ}$ and $p_{\\rm p}& ~{\\rm MeV}/c$, $\\theta_{\\rm p}& ^{\\circ}$ is required. In this paper, both the $\\overline{\\nu}_\\mu$ cross-sections and $\\overline{\\nu}_\\mu+\\nu_\\mu$ cross-sections on water and hydrocarbon targets and their ratios are provided by using the D’Agostini unfolding method. The results of the integrated $\\overline{\\nu}_\\mu$ cross-section measurements over this phase space are $\\sigma_{\\rm H_{2}O}=(1.082\\pm0.068(\\rm stat.)^{+0.145}_{-0.128}(\\rm syst.)) \\times 10^{-39}\\,{\\rm cm^{2} / nucleon}$, $\\sigma_{\\rm CH}=(1.096\\pm0.054(\\rm stat.)^{+0.132}_{-0.117}(\\rm syst.)) \\times 10^{-39}\\,{\\rm cm^{2} / nucleon}$, and $\\sigma_{\\rm H_{2}O}/\\sigma_{\\rm CH} = 0.987\\pm0.078(\\rm stat.)^{+0.093}_{-0.090}(\\rm syst.)$. The $\\overline{\\nu}_\\mu+\\nu_\\mu$ cross-section is $\\sigma_{\\rm H_{2}O} = (1.155\\pm0.064(\\rm stat.)^{+0.148}_{-0.129}(\\rm syst.)) \\times 10^{-39}\\,{\\rm cm^{2} / nucleon}$, $\\sigma_{\\rm CH}=(1.159\\pm0.049(\\rm stat.)^{+0.129}_{-0.115}(\\rm syst.)) \\times 10^{-39}\\,{\\rm cm^{2} / nucleon}$, and $\\sigma_{\\rm H_{2}O}/\\sigma_{\\rm CH}=0.996\\pm0.069(\\rm stat.)^{+0.083}_{-0.078}(\\rm syst.)$.
Publisher: BMJ
Date: 2023
DOI: 10.1136/BMJOPEN-2022-065608
Abstract: In many jurisdictions, people experiencing an injury often pursue compensation to support their treatment and recovery expenses. Healthcare costs form a significant portion of payments made by compensation schemes. Compensation scheme regulators need accurate and comprehensive data on injury severity, treatment pathways and outcomes to enable scheme modelling, monitoring and forecasting. Regulators routinely rely on data provided by insurers which have limited healthcare information. Health data provide richer information and linking health data with compensation data enables the comparison of profiles, patterns, trends and outcomes of injured patients who claim and injured parties who are eligible but do not claim. This is a retrospective population-level epidemiological data linkage study of people who have sought ambulatory, emergency or hospital treatment and/or made a compensation claim in Queensland after suffering a transport or work-related injury, over the period 1 January 2011 to 31 December 2021. It will use person-linked data from nine statewide data sources: (1) Queensland Ambulance Service, (2) Emergency Department, (3) Queensland Hospital Admitted Patients, (4) Retrieval Services, (5) Hospital Costs, (6) Workers’ Compensation, (7) Compulsory Third Party Compensation, (8) National Injury Insurance Scheme and (9) Queensland Deaths Registry. Descriptive, parametric and non-parametric statistical methods and geospatial analysis techniques will be used to answer the core research questions regarding the patient’s health service use profile, costs, treatment pathways and outcomes within 2 years postincident as well as to examine the concordance and accuracy of information across health and compensation databases. Ethics approval was obtained from the Royal Brisbane and Women’s Hospital Human Research Ethics Committee, and governance approval was obtained via the Public Health Act 2005, Queensland. The findings of this study will be used to inform key stakeholders across the clinical, research and compensation regulation area, and results will be disseminated through peer-reviewed journals, conference presentations and reports/seminars with key stakeholders.
Publisher: Wiley
Date: 12-2007
DOI: 10.1038/OBY.2007.369
Publisher: Elsevier BV
Date: 08-2008
Publisher: Wiley
Date: 30-10-2012
Publisher: Wiley
Date: 21-12-2023
DOI: 10.1002/IJC.34395
Abstract: 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 in idual 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.
Publisher: American Association for Cancer Research (AACR)
Date: 03-2020
DOI: 10.1158/1055-9965.EPI-19-0693
Abstract: With the improvements in cancer diagnosis and treatment, more patients with cancer are surviving for longer periods than before. This study aims to quantify the proportion cured and median survival time for those who are not cured for major cancers in Australia. Australian population-based cohort of 2,164,172 cases, ages 15 to 89 years, whose first cancer diagnosis between 1982 and 2014 was one of 22 leading cancers, were followed up to December 2014. Flexible parametric cure models were used to estimate the proportion cured and median survival time for those uncured by age, sex, and spread of disease, and temporal trends in these measures. Cure estimates could be generated for 19 of the 22 cancer types. The unadjusted proportion cured ranged from 5.0% for pancreatic cancer to 90.0% for melanoma. Median survival time for those uncured ranged from 0.35 years for pancreatic cancer to 6.05 years for prostate cancer. Cancers were ided into four groups according to their proportion cured in the 1980s and the degree of improvement over 28 years. Esophageal, stomach, pancreatic, liver, gallbladder, lung, and brain cancer had lower proportion cured and smaller improvements over time. For cancers with poor survival in which little has changed over time either in prolonging life or achieving statistical cure, efforts should be focused on reducing the prevalence of known risk factors and earlier detection, thereby enabling more effective treatment. Cure models provide unique insights into whether survival improvements are due to prolonging life or through curing the disease.
Publisher: Wiley
Date: 30-09-2022
DOI: 10.1111/DME.14961
Abstract: The provision of guideline‐based care for patients with diabetes‐related foot ulcers (DFU) in clinical practice is suboptimal. We estimated the cost‐effectiveness of higher rates of guideline‐based care, compared with current practice. The costs and quality‐adjusted life‐years (QALYs) associated with current practice (30% of patients receiving guideline‐based care) were compared with seven hypothetical scenarios with increasing proportion of guideline‐based care (40%, 50%, 60%, 70%, 80%, 90% and 100%). Comparisons were made using discrete event simulations reflecting the natural history of DFU over a 3‐year time horizon from the Australian healthcare perspective. Incremental cost‐effectiveness ratios were calculated for each scenario and compared to a willingness‐to‐pay of AUD 28,000 per QALY. Probabilistic sensitivity analyses were conducted to incorporate joint parameter uncertainty. All seven scenarios with higher rates of guideline‐based care were likely cheaper and more effective than current practice. Increased proportions compared with current practice resulted in between AUD 0.28 and 1.84 million in cost savings and 11–56 additional QALYs per 1000 patients. Probabilistic sensitivity analyses indicated that the finding is robust to parameter uncertainty. Higher proportions of patients receiving guideline‐based care are less costly and improve patient outcomes. Strategies to increase the proportion of patients receiving guideline‐based care are warranted.
Publisher: Wiley
Date: 08-08-2016
DOI: 10.1002/SIM.7071
Abstract: Most of the few published models used to obtain small-area estimates of relative survival are based on a generalized linear model with piecewise constant hazards under a Bayesian formulation. Limitations of these models include the need to artificially split the time scale, restricted ability to include continuous covariates, and limited predictive capacity. Here, an alternative Bayesian approach is proposed: a spatial flexible parametric relative survival model. This overcomes previous limitations by combining the benefits of flexible parametric models: the smooth, well-fitting baseline hazard functions and predictive ability, with the Bayesian benefits of robust and reliable small-area estimates. Both spatially structured and unstructured frailty components are included. Spatial smoothing is conducted using the intrinsic conditional autoregressive prior. The model was applied to breast, colorectal, and lung cancer data from the Queensland Cancer Registry across 478 geographical areas. Advantages of this approach include the ease of including more realistic complexity, the feasibility of using in idual-level input data, and the capacity to conduct overall, cause-specific, and relative survival analysis within the same framework. Spatial flexible parametric survival models have great potential for exploring small-area survival inequalities, and we hope to stimulate further use of these models within wider contexts. Copyright © 2016 John Wiley & Sons, Ltd.
Publisher: Springer Science and Business Media LLC
Date: 25-09-2020
DOI: 10.1186/S12942-020-00233-1
Abstract: There is an expanding literature on different representations of spatial random effects for different types of spatial correlation structure within the conditional autoregressive class of priors for Bayesian spatial models. However, little is known about the impact of these different priors when the number of areas is small. This paper aimed to investigate this problem both in the context of a case study of spatial analysis of dengue fever and more generally through a simulation study. Both the simulation study and the case study considered count data aggregated to a small area level in a region. Five different conditional autoregressive priors for a simple Bayesian Poisson model were considered: independent, Besag-York-Mollié, Leroux, and two variants of a localised clustering model. Data were simulated with eight different sizes of areal grids, ranging from 4 to 2500 areas, and two different levels of both spatial autocorrelation and disease counts. Model goodness-of-fit measures and model estimates were compared. A case study involving dengue fever cases in 14 local areas in Makassar, Indonesia, was also considered. The simulation study showed that model performance varied under different scenarios. When areas had low autocorrelation and high counts, and the number of areas was at most 25, the BYM, Leroux and localised $$G = 2$$ G = 2 models performed similarly and better than the independent and localised $$G = 3$$ G = 3 models. However, when the number of areas were at least 100, all models performed differently, and the Leroux model performed the best. Overall, the Leroux model performed the best for every scenario especially when there were at least 16 areas. Based on the case study, the comparative performance of spatial models may also vary for a small number of areas, especially when the data have a relatively large mean and variance over areas. In this case, the localised model with G = 3 was a better choice. Detecting spatial patterns can be difficult when there are very few areas. Understanding the characteristics of the data and the relative influence of alternative conditional autoregressive priors is essential in selecting an appropriate Bayesian spatial model.
Publisher: Springer Science and Business Media LLC
Date: 23-04-2019
DOI: 10.1038/S41598-019-42774-X
Abstract: Esophageal cancer (EC) is a leading cause of cancer death in China. Within Shandong Province, a geographic cluster with high EC mortality has been identified, however little is known about how area-level socioeconomic status (SES) is associated with EC mortality in this province. Multilevel models were applied to EC mortality data in 2011–13 among Shandong residents aged 40+ years. Area-level SES factors consisted of residential type (urban/rural) of the sub-county-level units (n = 262) and SES index (range: 0–10) of the county-level units (n = 142). After adjustment for age and sex, residents living in rural areas had a 22% (95% CI: 13–32%) higher risk of dying from EC than those in urban areas. With each unit increase in the SES index, the average risk of dying from EC reduced by 10% (95% CI: 3–18%). The adjustment of area-level SES variables had little impact on the risk ratio of EC mortality between the high-mortality cluster and the rest of Shandong. In conclusion, rural residence and lower SES index are strongly associated with elevated risks of EC death. However, these factors are independent of the high mortality in the cluster area of Shandong. The underlying causes for this geographic disparity need to be further investigated.
Publisher: American Physical Society (APS)
Date: 26-01-2021
Publisher: Oxford University Press (OUP)
Date: 09-2021
Abstract: Diabetes-related foot ulcers (DFU) take months to heal, reduce patient’s quality-of-life, and induce large healthcare expenditure. Various factors have been identified to influence DFU healing at fixed periods, however, data on factors associated with time-to-healing is scarce. Patients presenting with DFU to Diabetic Foot Services across Queensland, Australia between July 2011 and December 2017 were included and had their demographics, disease history and treatments examined at baseline. Outcome of interest was healing of all ulcers within two-year follow-up time. Time-to-healing and associated factors were examined using flexible parametric survival models, which easily enabled including time-varying coefficients and predicting proportions healed. Of 4,709 included patients (median age 63 years, 69.5% male, 10.5% Indigenous), median time-to-healing was 112 days, and 68% healed within two years. Younger age (& years), geographical remoteness, smoking, neuropathy, deep ulcers, infection, not receiving offloading, and no recent podiatry treatment were independently associated with longer time-to-healing. Time-varying effects of peripheral artery disease and ulcer size were identified for the first time: both had a negative influence on healing with effects diminishing after six months. The predicted proportions healed, for ex le, within six months is 65.0% (63.3-66.7) for people residing in a major city, 54.6% (52.6-56.8) in regional area, and 40.3% (34.6-47.1) in remote area. This study identified novel and confirmatory factors influencing time-to-healing over 24 months in a large real-world cohort of people with diabetes-related foot ulcers. Visualizing the adjusted predicted proportion healed revealed the influence each factor had on healing rates over time. Flexible parametric survival model provided flexibility in investigating time-varying effects and outcome prediction in those with diabetes-related foot ulcer healing.
Publisher: eLife Sciences Publications, Ltd
Date: 04-04-2022
DOI: 10.7554/ELIFE.76123
Abstract: When researchers’ careers are disrupted by life events – such as illness or childbirth – they often need to take extended time off. This creates a gap in their research output that can reduce their chances of winning funding. In Australia, applicants can disclose their career disruptions and peer reviewers are instructed to make appropriate adjustments. However, it is not clear if and how applicants use career disruption sections or how reviewers adjust and if they do it consistently. To examine career disruption, we used surveys of the Australian health and medical research community. We used both a random s le of Australian authors on PubMed and a non-random convenience s le. Respondents expressed concerns that sharing information on career disruption would harm their chances of being funded, with 13% saying they have medical or social circumstances but would not include it in their application, with concerns about appearing ‘weak’. Women were more reluctant to include disruption. There was inconsistency in how disruption was adjusted for, with less time given for those with depression compared with caring responsibilities, and less time given for those who did not provide medical details of their disruption. The current system is likely not adequately adjusting for career disruption and this may help explain the ongoing funding gap for senior women in Australia. National Health and Medical Research Council Senior Research Fellowship (Barnett).
Publisher: Wiley
Date: 06-05-2021
DOI: 10.1002/CAM4.3844
Abstract: To estimate trends in the crude probability of death for cancer patients by sex, age and spread of disease over the past 30 years in New South Wales, Australia. Population‐based cohort of 716,501 people aged 15–89 years diagnosed with a first primary cancer during 1985–2014 were followed up to 31 December 2015. Flexible parametric relative survival models were used to estimate the age‐specific crude probability of dying from cancer and other causes by calendar year, sex and spread of disease for all solid tumours combined and cancers of the colorectum, lung, female breast, prostate and melanoma. Estimated 10‐year sex, age and spread‐specific crude probabilities of cancer death generally decreased over time for most cancer types, although the magnitude of the decrease varied. For ex le, out of 100 fifty‐year old men with localized prostate cancer, 12 would have died from their cancer if diagnosed in 1985 and 3 in 2014. Greater degree of spread was consistently associated with higher probability of dying from cancer, although outcomes for lung cancer were consistently poor. For both males and females, the probability of non‐cancer deaths was higher among older patients, those diagnosed with localized cancers and where cancer survival was higher. Crude probabilities presented here may be useful in helping clinicians and their patients better understand prognoses and make informed decisions about treatment. They also provide novel insights into the relative contributions that early detection and improved treatments have on the observed temporal patterns in cancer survival.
Publisher: BMJ
Date: 09-2021
DOI: 10.1136/BMJOPEN-2021-051047
Abstract: Falls remain one of the most prevalent adverse events in hospitals and are associated with substantial negative health impacts and costs. Approaches to assess patients’ fall risk have been implemented in hospitals internationally, ranging from brief screening questions to multifactorial risk assessments and complex prediction models, despite a lack of clear evidence of effect in reducing falls in acute hospital environments. The increasing digitisation of hospital systems provides new opportunities to understand and predict falls using routinely recorded data, with potential to integrate fall prediction models into real-time or near-real-time computerised decision support for clinical teams seeking to mitigate fall risk. However, the use of non-traditional approaches to fall risk prediction, including machine learning using integrated electronic medical records, has not yet been reviewed relative to more traditional fall prediction models. This scoping review will summarise methodologies used to develop existing hospital fall prediction models, including reporting quality assessment. This scoping review will follow the Arksey and O’Malley framework and its recent advances, and will be reported using Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews recommendations. Four electronic databases (CINAHL via EBSCOhost, PubMed, IEEE Xplore and Embase) will be initially searched for studies up to 12 November 2020, and searches may be updated prior to final reporting. Additional studies will be identified by reference list review and citation analysis of included studies. No restriction will be placed on the date or language of identified studies. Screening of search results and extraction of data will be performed by two independent reviewers. Reporting quality will be assessed by the adherence to the Transparent Reporting of a multivariable prediction model for In idual Prognosis Or Diagnosis. Ethical approval is not required for this study. Findings will be disseminated through peer-reviewed publication and scientific conferences.
Publisher: Wiley
Date: 24-05-2018
Location: Poland
Start Date: 08-2021
End Date: 07-2024
Amount: $588,955.00
Funder: Australian Research Council
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