The Impact of Rurality and Disadvantage on the Diagnostic Interval for Breast Cancer in a Large Population-Based Study of 3202 Women in Queensland, Australia.

Delays in diagnosing breast cancer (BC) can lead to poorer outcomes. We investigated factors related to the diagnostic interval in a population-based cohort of 3202 women diagnosed with BC in Queensland, Australia. Interviews ascertained method of detection and dates of medical/procedural appointments, and clinical information was obtained from medical records. Time intervals were calculated from self-recognition of symptoms (symptom-detected) or mammogram (screen-detected) to diagnosis (diagnostic interval (DI)). The cohort included 1560 women with symptom-detected and 1642 with screen-detected BC. Symptom-detected women had higher odds of DI of >60 days if they were Indigenous (OR = 3.12, 95% CI = 1.40, 6.98); lived in outer regional (OR = 1.50, 95% CI = 1.09, 2.06) or remote locations (OR = 2.46, 95% CI = 1.39, 4.38); or presented with a "non-lump" symptom (OR = 1.84, 95% CI = 1.43, 2.36). For screen-detected BC, women who were Indigenous (OR = 2.36, 95% CI = 1.03, 5.80); lived in remote locations (OR = 2.35, 95% CI = 1.24, 4.44); or disadvantaged areas (OR = 1.69, 95% CI = 1.17, 2.43) and attended a public screening facility (OR = 2.10, 95% CI = 1.40, 3.17) had higher odds of DI > 30 days. Our study indicates a disadvantage in terms of DI for rural, disadvantaged and Indigenous women. Difficulties in accessing primary care and diagnostic services are evident. There is a need to identify and implement an efficient and effective model of care to minimize avoidable longer diagnostic intervals

Psychosocial predictors of hope two years after diagnosis of colorectal cancer: Implications for nurse-led hope programmes

© 2019 John Wiley & Sons Ltd Objective: To prospectively explore predictors of hope in people with colorectal cancer at 24 months post-diagnosis. Methods: The present study is a secondary analysis of two waves within a longitudinal survey of patients newly diagnosed with colorectal cancer in Queensland, Australia. Baseline predictors (sociodemographic, disease, lifestyle characteristics, cancer threat appraisal and quality of life domains) were measured via mailed surveys and telephone interviews at 6 months post-diagnosis. Hope was measured via mailed surveys at 24 months post-diagnosis. Results: At 24 months post-diagnosis, 1,265 participants completed the hope measure. Hope was predicted by higher education, physical activity, cancer threat appraisal and each quality of life domain (i.e., physical, social, emotional and functional well-being; and colorectal cancer-specific concerns), which explained 23.63% of the total variance in hope, F(14, 1,081) = 23.89, p < 0.001. Conclusion: At 24 months post-diagnosis, hope was associated with greater functional, social and emotional well-being, and less threatened cancer appraisals. As hope programmes continue to be developed, designers should include activities that increase well-being and reduce cancer threat appraisal for people with colorectal cancer

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

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

The Supportive Care Needs of Regional and Remote Cancer Caregivers

Objective: As cancer survival rates continue to increase, so will the demand for care from family and friends, particularly in more isolated settings. This study aims to examine the needs of cancer caregivers in regional and remote Australia. Methods: A total of 239 informal (i.e., non-professional) cancer caregivers (e.g., family/friends) from regional and remote Queensland, Australia, completed the Comprehensive Needs Assessment Tool for Cancer Caregivers (CNAT-C). The frequencies of individuals reporting specific needs were calculated. Logistic regression analyses assessed the association between unmet needs and demographic characteristics and cancer type. Results: The most frequently endorsed needs were lodging near hospital (77%), information about the disease (74%), and tests and treatment (74%). The most frequent unmet needs were treatment near home (37%), help with economic burden (32%), and concerns about the person being cared for (32%). Younger and female caregivers were significantly more likely to report unmet needs overall (OR = 2.12; OR = 0.58), and unmet healthcare staff needs (OR = 0.35; OR = 1.99, respectively). Unmet family and social support needs were also significantly more likely among younger caregivers (OR = 0.35). Caregivers of breast cancer patients (OR = 0.43) and older caregivers (OR = 0.53) were significantly less likely to report unmet health and psychology needs. Proportions of participants reporting needs were largely similar across demographic groups and cancer type with some exceptions. Conclusions: Caregiver health, practical issues associated with travel, and emotional strain are all areas where regional and remote caregivers require more support. Caregivers’ age and gender, time since diagnosis and patient cancer type should be considered when determining the most appropriate supportive care

A systematic review of geographical differences in management and outcomes for colorectal cancer in Australia.

BACKGROUND: Australia and New Zealand have the highest incidence of colorectal cancer (CRC) in the world, presenting considerable health, economic, and societal burden. Over a third of the Australian population live in regional areas and research has shown they experience a range of health disadvantages that result in a higher disease burden and lower life expectancy. The extent to which geographical disparities exist in CRC management and outcomes has not been systematically explored. The present review aims to identify the nature of geographical disparities in CRC survival, clinical management, and psychosocial outcomes. METHODS: The review followed PRISMA guidelines and searches were undertaken using seven databases covering articles between 1 January 1990 and 20 April 2016 in an Australian setting. Inclusion criteria stipulated studies had to be peer-reviewed, in English, reporting data from Australia on CRC patients and relevant to one of fourteen questions examining geographical variations in a) survival outcomes, b) patient and cancer characteristics, c) diagnostic and treatment characteristics and d) psychosocial and quality of life outcomes. RESULTS: Thirty-eight quantitative, two qualitative, and three mixed-methods studies met review criteria. Twenty-seven studies were of high quality, sixteen studies were of moderate quality, and no studies were found to be low quality. Individuals with CRC living in regional, rural, and remote areas of Australia showed poorer survival and experienced less optimal clinical management. However, this effect is likely moderated by a range of other factors (e.g., SES, age, gender) and did appear to vary linearly with increasing distance from metropolitan centres. No studies examined differences in use of stoma, or support with stomas, by geographic location. CONCLUSIONS: Overall, despite evidence of disparity in CRC survival and clinical management across geographic locations, the evidence was limited and at times inconsistent. Further, access to treatment and services may not be the main driver of disparities, with individual patient characteristics and type of region also playing an important role. A better understanding of factors driving ongoing and significant geographical disparities in cancer related outcomes is required to inform the development of effective interventions to improve the health and welfare of regional Australians

Geographic disparities in previously diagnosed health conditions in colorectal cancer patients are largely explained by age and area level disadvantage

© 2018 Goodwin, March, Ireland, Crawford-Williams, Ng, Baade, Chambers, Aitken and Dunn. Background: Geographical disparity in colorectal cancer (CRC) survival rates may be partly due to aging populations and disadvantage in more remote locations; factors that also impact the incidence and outcomes of other chronic health conditions. The current study investigates whether geographic disparity exists amongst previously diagnosed health conditions in CRC patients above and beyond age and area-level disadvantage and whether this disparity is linked to geographic disparity in CRC survival. Methods: Data regarding previously diagnosed health conditions were collected via computer-assisted telephone interviews with a cross-sectional sample of n = 1,966 Australian CRC patients between 2003 and 2004. Ten-year survival outcomes were acquired in December 2014 from cancer registry data. Multivariate logistic regressions were applied to test associations between previously diagnosed health conditions and survival rates in rural, regional, and metropolitan areas. Results: Results suggest that only few geographical disparities exist in previously diagnosed health conditions for CRC patients and these were largely explained by socio-economic status and age. Living in an inner regional area was associated with cardio-vascular conditions, one or more respiratory diseases, and multiple respiratory diagnoses. Higher occurrences of these conditions did not explain lower CRC-specific 10 years survival rates in inner regional Australia. Conclusion: It is unlikely that health disparities in terms of previously diagnosed conditions account for poorer CRC survival in regional and remote areas. Interventions to improve the health of regional CRC patients may need to target issues unique to socio-economic disadvantage and older age

Admission to hospital following head injury in England: Incidence and socio-economic associations

BACKGROUND: Head injury in England is common. Evidence suggests that socio-economic factors may cause variation in incidence, and this variation may affect planning for services to meet the needs of those who have sustained a head injury. METHODS: Socio-economic data were obtained from the UK Office for National Statistics and merged with Hospital Episodes Statistics obtained from the Department of Health. All patients admitted for head injury with ICD-10 codes S00.0–S09.9 during 2001–2 and 2002–3 were included and collated at the level of the extant Health Authorities (HA) for 2002, and Primary Care Trust (PCT) for 2003. Incidence was determined, and cluster analysis and multiple regression analysis were used to look at patterns and associations. Results: 112,718 patients were admitted during 2001–2 giving a hospitalised incidence rate for England of 229 per 100,000. This rate varied across the English HA's ranging from 91–419 per 100,000. The rate remained unchanged for 2002–3 with a similar magnitude of variation across PCT's. Three clusters of HA's were identified from the 2001–2 data; those typical of London, those of the Shire counties, and those of Other Urban authorities. Socio-economic factors were found to account for a high proportion of the variance in incidence for 2001–2. The same pattern emerged for 2002–3 at the PCT level. The use of public transport for travel to work is associated with a decreased incidence and lifestyle indicators, such as the numbers of young unemployed, increase the incidence. CONCLUSION: Head injury incidence in England varies by a factor of 4.6 across HA's and PCT's. Planning head injury related services at the local level thus needs to be based on local incidence figures rather than regional or national estimates. Socio-economic factors are shown to be associated with admission, including travel to work patterns and lifestyle indicators, which suggests that incidence is amenable to policy initiatives at the macro level as well as preventive programmes targeted at key groups

Measuring measurement

Measurement connects the world of quantum phenomena to the world of classical events. It plays both a passive role, observing quantum systems, and an active one, preparing quantum states and controlling them. Surprisingly - in the light of the central status of measurement in quantum mechanics - there is no general recipe for designing a detector that measures a given observable. Compounding this, the characterization of existing detectors is typically based on partial calibrations or elaborate models. Thus, experimental specification (i.e. tomography) of a detector is of fundamental and practical importance. Here, we present the realization of quantum detector tomography: we identify the optimal positive-operator-valued measure describing the detector, with no ancillary assumptions. This result completes the triad, state, process, and detector tomography, required to fully specify an experiment. We characterize an avalanche photodiode and a photon number resolving detector capable of detecting up to eight photons. This creates a new set of tools for accurately detecting and preparing non-classical light.Comment: 6 pages, 4 figures,see video abstract at http://www.quantiki.org/video_abstracts/0807244

Mouse Estrous Cycle Identification Tool and Images

The efficiency of producing timed pregnant or pseudopregnant mice can be increased by identifying those in proestrus or estrus. Visual observation of the vagina is the quickest method, requires no special equipment, and is best used when only proestrus or estrus stages need to be identified. Strain to strain differences, especially in coat color can make it difficult to determine the stage of the estrous cycle accurately by visual observation. Presented here are a series of images of the vaginal opening at each stage of the estrous cycle for 3 mouse strains of different coat colors: black (C57BL/6J), agouti (CByB6F1/J) and albino (BALB/cByJ). When all 4 stages (proestrus, estrus, metestrus, and diestrus) need to be identified, vaginal cytology is regarded as the most accurate method. An identification tool is presented to aid the user in determining the stage of estrous when using vaginal cytology. These images and descriptions are an excellent resource for learning how to determine the stage of the estrous cycle by visual observation or vaginal cytology