Prostate cancer survival in South West Victoria.

OBJECTIVE: To explore reasons for survival disparities for patients with prostate cancer in the Barwon South West area of Victoria. DESIGN, SETTING AND PARTICIPANTS: We have described incidence, diagnostics, treatment pathways, and survival for four regions of the Barwon South Western Victoria. Analysis included all newly diagnosed prostate cancer patients from 2009 to 2015 in the Evaluation of Cancer Outcomes Barwon South West Registry. Regions included 1: Queenscliffe 2: Geelong, Colac Otway and Corangamite 3: Moyne, Warrnambool and Southern Grampians and 4: Glenelg. Across the four regions, variables were compared using a chi square statistic or analysis of variance and survival data was assessed with the Kaplan-Meier curves. MAIN OUTCOME MEASURES: Incidence, treatment pathways and survival for prostate cancer patients. RESULTS: A total of 1776 patients were diagnosed with prostate cancer from 2009 to 2015 in the Barwon South West area. In regions 1-4, there were 298 (1.04%), 1085 (0.92%), 273 (0.97%) and 120 (1.2%) cases, respectively. There was no significant difference in Gleason score and treatment. The 5-year survival rate was 85%, 76%, 71% and 80%, respectively, as compared with the national average of 95%. PSA scores >20 ng/ml at diagnosis, as a surrogate for high-risk disease, occurred in 23%, 29%, 22% and 21%, respectively (p < 0.01). The proportions presenting with stage IV disease were 17%, 26%, 21% and 6%, respectively (p = 0.10). CONCLUSION: Men diagnosed with prostate cancer in South West Victoria have a considerably lower 5-year survival compared with the national average with later disease at presentation in some areas.

Population-based analysis of radiotherapy and chemotherapy treatment in the last month of life within regional Australia.

BACKGROUND: Cancer treatment near end of life is not likely to add meaningful benefit and minimising intervention rates has been promoted as an indicator of quality of care. Population-based analysis of treatment allows comparative analysis of treatment rates and provides insight into patterns of care. AIMS: To report a population-based analysis of both radiotherapy and active systemic therapy (AST) delivery rates along with patterns of treatment within the last 14 and 30 days of life. METHODS: The Evaluation of Cancer Outcomes Registry records clinical information on all newly diagnosed cancer patients for the Barwon South West Region of Victoria, Australia. Diagnosis details, tumour type and stage as well as core treatment details and date of death were extracted for all patients diagnosed from 2009 to 2015 inclusive. RESULTS: A total of 12 760 cases cancers were recorded. The median age of all cases was 68.8, and 53% were male. AST was received by 3699 (29%) of patients and radiotherapy by 3811 (30%). Patient deaths within 14 and 30 days of treatment for AST were 4.3 and 8.7%, respectively, and deaths within 14 and 30 days of treatment for radiotherapy 3.8 and 8.0% respectively. Factors associated with death within 30 days of AST and/or radiotherapy were male gender, age greater than 70 years and higher disease stage (all P < 0.01). Treatment rates within 30 days of death were highest for lung cancer (23% of cases) and lowest for breast cancer (2% of cases). CONCLUSIONS: This population-based analysis of AST and radiotherapy treatment within the last 30 days of life within a region of Australia has shown overall treatment rates below 10%. Treatment rates appear influenced by both patient and tumour characteristics. Future focus on subgroups with high rates of late intervention may help minimise treatment unlikely to add benefit.

Use of clinical quality indicators to improve lung cancer care in a regional/rural network of health services.

PROBLEM: Optimal lung cancer care requires multidisciplinary team input, with access to specialised diagnostic and therapeutic services that may be limited in rural or regional areas and impact clinical outcomes. Clinical quality indicators can be used to measure the quality of care delivered to patients with lung cancer in a region and identify areas for improvement. We describe the implementation of internationally recognised clinical quality indicators for lung cancer care in the Barwon South Western region. DESIGN: The consensus of an expert panel was used for the selection of clinical quality indicators. The data were retrospectively collected from the Evaluation of Cancer Outcomes Barwon South West Registry, which systematically records detailed information on all new patients with cancer in the region. SETTING: Region-based health service. KEY MEASURES FOR IMPROVEMENT: Adherence to clinical quality indicator targets. STRATEGIES FOR CHANGE: Clinical quality indicators, which fall short of the expected targets, highlight areas for improvement in the service provided to patients with lung cancer. These results have prompted changes in the service offered to these patients, such as the introduction of a multidisciplinary lung cancer clinic. EFFECTS OF CHANGE: The multidisciplinary lung cancer clinic has streamlined the access to lung cancer services, including specialist consultations, diagnostics and therapeutic services, in a regional setting. Ongoing data collection is required to determine the effect of such changes on adherence to clinical quality indicator targets. LESSONS LEARNT: The regular monitoring of clinical quality indicators serves as a useful method of quality assurance in the care of patients with lung cancer. We expect these clinical quality indicators to also be used by other health services to analyse and improve services provided to patients with lung cancer.

Cancer diagnosed in the Emergency Department of a Regional Health Service.

OBJECTIVE: Patients diagnosed with cancer in the Emergency Department (ED) have more advanced disease at diagnosis and poorer outcomes. High rates of initial presentation to ED suggest potential problems with access to care. The aim of this project was to interpret findings in regional/rural Victoria and explore implications for practice. DESIGN: Cross-sectional study linking two independent data sets. SETTING: Regional city of Geelong and surrounding rural areas in south-west Victoria. PARTICIPANTS: All newly diagnosed cancer patients in 2009. MAIN OUTCOME MEASURES: Number of cancer patients diagnosed in the ED. RESULTS: One in five newly diagnosed cancer patients present to ED 6 months prior to cancer diagnosis. One in 10 is diagnosed as a result of their ED visit. Patients presenting to ED were older, more often men and from disadvantaged areas. Symptoms on presentation included chest complaints, bowel obstruction, abdominal pain, anaemia and generalised weakness. Cancer diagnosed in the ED is associated with advanced stage and shorter survival. CONCLUSION: Reasons for presentation to ED would be multifactorial and include complex cases with coexisting symptoms making diagnosis difficult. The general public appear to have a low level of awareness of alternative primary care services or difficulty accessing such information. Some of the changes towards reducing the number of patients presenting to ED will include patient education.

Retrospective analysis of cancer survival across South-Western Victoria in Australia.

OBJECTIVE: This paper aims to describe cancer survival and examine association between survival and socio-demographic characteristics across Barwon South-Western region (BSWR) in Victoria, Australia. DESIGN: This study is based on the retrospective cohort database of patients accessing oncology services across BSWR. SETTING: Six rural and three urban hospital settings across the BSWR. PARTICIPANTS: The participants were patients who were diagnosed with cancer in 2009. MAIN OUTCOME MEASURES: Overall survival (OS) of participants was the main outcome measure. RESULTS: Total of 1778 eligible patients had four-year OS for all cancers combined of 59.7% (95% CI, 57.4-62.0). Improved OS was observed for patients in the upper socio-economic tertile (64.2%; 95% CI, 60.9-67.5) compared to the middle (59.3%; 95% CI, 55.5-63.1) and lowest tertiles (49.6%; 95% CI, 44.2-54.9) (P < 0.01). On multivariate analyses, higher socio-economic status remained a significant predictor of OS adjusting for gender, remoteness and age (HR [hazard ratio] 0.81; 95% CI 0.74-0.89; P < 0.01). Remoteness was significantly associated with improved OS after adjusting for age, gender and socio-economic status (HR 0.86; 95% CI, 0.77-0.97; P = 0.01). Older age ≥70 years compared to <70 years conferred inferior OS (HR 3.08; 95% CI, 2.64-3.59; P < 0.01). CONCLUSIONS: Our study confirmed improved survival outcomes for patients of higher socio-economic status and younger age. Future research to explain the unexpected survival benefit in patients who lived in more remote areas should examine factors including the correlation between geographical residence and eventual treatment facility as well as compare the BSWR care model to other regions' approaches.

Characteristics of cancer diagnoses and staging in South Western Victoria: a rural perspective.

OBJECTIVE: Australian states and territories have legislation mandating reporting of cancer diagnoses; however, tumour stage at diagnosis, treatment plan and associated outcomes are not routinely recorded in cancer registries for all tumour types. This study describes the Evaluation of Cancer Outcomes study that collects detailed information for patients diagnosed with cancer in south-western Victoria. DESIGN: Retrospective data collection. SETTING: Population based. PARTICIPANTS: New cancer patients within the Barwon South Western region. MAIN OUTCOME MEASURES: Cancer incidence and staging data for a regional and rural area. RESULTS: In 2009, there were 1778 primary tumours. Prominent tumour streams included prostate, breast, colon, lung, lymphoma, melanoma and rectum. Stage at diagnosis was recorded for more than 50% of patients for the tumour streams of testis, breast, bowel, renal, lung, and head and neck. Patients reporting to health centres with an on-site oncologist as part of their team had a higher rate of staging recorded at diagnosis (48.0 versus 36.9%, P=0.01). More women (55.4%) than men (41.4%) had stage-recorded. CONCLUSION: The Evaluation of Cancer Outcomes study is an important initiative that collects information about newly diagnosed cases of cancer more detailed than is currently collected by the Cancer Council of Victoria. Future studies will build on this base dataset and provide valuable insight into the regional and rural experience of treatment pathways after diagnosis. More work is needed to bring more services to our rural patients, or more education is needed to encourage the recording of tumour staging.

Radiotherapy in the Barwon South Western Region: a rural perspective.

INTRODUCTION: Cancer-related mortality rates are higher in rural areas compared with urban regions. Whether there are corresponding geographical variations in radiotherapy utilisation rates (RURs) is the subject of this study. METHODS: RURs for the regional centre of Geelong and rural areas of the Barwon South Western Region were calculated using a population-based database (2009). RESULTS: Lower RURs were observed for rural patients compared with the Geelong region for prostate cancer (15.7% vs 25.8%, P = 0.02), rectal cancer (32.8% vs 44.7%, P = 0.11), lymphoma (9.4% vs 26.2%, P = 0.05), and all cancers overall (25.6% vs 28.9%, P = 0.06). This lower rate was significant in men (rural, 19.9%; Geelong, 28.3%; P = 0.00) but not in women (rural, 33.6%; Geelong, 29.7%; P = 0.88). Time from diagnosis to radiotherapy was not significantly different for patients from the two regions. Tumour staging within the rural and Geelong regions was not significantly different for the major tumour streams of rectal, prostate and lung cancer (P = 0.61, P = 0.79, P = 0.43, respectively). A higher proportion of tumours were unstaged or unstageable in the rural region for lung (44% vs 18%, P < 0.01) and prostate (73% vs 57%, P < 0.01) cancer. CONCLUSION: Lower RURs were observed in our rural region. Differences found within tumour streams and in men suggest a complexity of relationships that will require further study.

Machine-learning prediction of cancer survival: a retrospective study using electronic administrative records and a cancer registry.

OBJECTIVES: Using the prediction of cancer outcome as a model, we have tested the hypothesis that through analysing routinely collected digital data contained in an electronic administrative record (EAR), using machine-learning techniques, we could enhance conventional methods in predicting clinical outcomes. SETTING: A regional cancer centre in Australia. PARTICIPANTS: Disease-specific data from a purpose-built cancer registry (Evaluation of Cancer Outcomes (ECO)) from 869 patients were used to predict survival at 6, 12 and 24 months. The model was validated with data from a further 94 patients, and results compared to the assessment of five specialist oncologists. Machine-learning prediction using ECO data was compared with that using EAR and a model combining ECO and EAR data. PRIMARY AND SECONDARY OUTCOME MEASURES: Survival prediction accuracy in terms of the area under the receiver operating characteristic curve (AUC). RESULTS: The ECO model yielded AUCs of 0.87 (95% CI 0.848 to 0.890) at 6 months, 0.796 (95% CI 0.774 to 0.823) at 12 months and 0.764 (95% CI 0.737 to 0.789) at 24 months. Each was slightly better than the performance of the clinician panel. The model performed consistently across a range of cancers, including rare cancers. Combining ECO and EAR data yielded better prediction than the ECO-based model (AUCs ranging from 0.757 to 0.997 for 6 months, AUCs from 0.689 to 0.988 for 12 months and AUCs from 0.713 to 0.973 for 24 months). The best prediction was for genitourinary, head and neck, lung, skin, and upper gastrointestinal tumours. CONCLUSIONS: Machine learning applied to information from a disease-specific (cancer) database and the EAR can be used to predict clinical outcomes. Importantly, the approach described made use of digital data that is already routinely collected but underexploited by clinical health systems.