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

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

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

Many studies on asset pricing have highlighted the importance of downside risk, in line with the actual losses of investors. In addition, the capital asset pricing model (CAPM), although presented as a universal theory, may provide significantly different rates of return in bull and bear markets. Using the CAPM under different conditions could be regarded as an alternative measurement and valuation approach to downside risk. This paper investigates conventional and downside approaches to risk taking into account different measures of downside beta coefficients. A further contribution of this research is the development of an alternative approach to testing the CAPM relationship. For this purpose, conditional relationships of the CAPM are proposed in which risk premiums are set separately in bull and bear periods. Using equity data and portfolios from the United Kingdom, we obtained positive and statistically significant downside risk premiums. We observed a slight advantage of downside measures over conventional beta measures. Conditional models provide evidence of a positive risk premium in rising markets and a negative risk premium in falling markets. The robustness analysis in subperiods indicates that these findings are largely unchanged for downside beta coefficients, which is not fulfilled by the model in a variance approach.

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

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.

Studies show conflicting results on whether exercise interventions to improve outcomes for women with breast cancer are cost-effective. We modelled the long-term cost-effectiveness of the Exercise for Health intervention compared with usual care. A lifetime Markov cohort model for women with early breast cancer was constructed taking a societal perspective. Data were obtained from trial, epidemiological, quality of life, and healthcare cost reports. Outcomes were calculated from 5000 Monte Carlo simulations, and one-way and probabilistic sensitivity analyses. Over the cohort's remaining life, the incremental cost for the exercise versus usual care groups were $7409 and quality-adjusted life years (QALYs) gained were 0.35 resulting in an incremental cost per QALY ratio of AU$21,247 (95% Uncertainty Interval (UI): Dominant, AU$31,398). The likelihood that the exercise intervention was cost-effective at acceptable levels was 93.0%. The incremental cost per life year gained was AU$8894 (95% UI Dominant, AU$11,769) with a 99.4% probability of being cost effective. Findings were most sensitive to the probability of recurrence in the exercise and usual care groups, followed by the costs of out-of-pocket expenses and the model starting age. This exercise intervention for women after early-stage breast cancer is cost-effective and would be a sound investment of healthcare resources.

PURPOSE: Elevated mammographic density (MD) is an independent risk factor for breast cancer (BC) as well as a source of masking in X-ray mammography. High-frequency longitudinal monitoring of MD could also be beneficial in hormonal BC prevention, where early MD changes herald the treatment's success. We present a novel approach to quantification of MD in breast tissue using single-sided portable NMR. Its development was motivated by the low cost of portable-NMR instrumentation, the suitability for measurements in vivo, and the absence of ionizing radiation. METHODS: Five breast slices were obtained from three patients undergoing prophylactic mastectomy or breast reduction surgery. Carr-Purcell-Meiboom-Gill (CPMG) relaxation curves were measured from (1) regions of high and low MD (HMD and LMD, respectively) in the full breast slices; (2) the same regions excised from the full slices; and (3) excised samples after H2 O-D2 O replacement. T2 distributions were reconstructed from the CPMG decays using inverse Laplace transform. RESULTS: Two major peaks, identified as fat and water, were consistently observed in the T2 distributions of HMD regions. The LMD T2 distributions were dominated by the fat peak. The relative areas of the two peaks exhibited statistically significant (P < .005) differences between HMD and LMD regions, enabling their classification as HMD or LMD. The relative-area distributions exhibited no statistically significant differences between full slices and excised samples. CONCLUSION: T2 -based portable-NMR analysis is a novel approach to MD quantification. The ability to quantify tissue composition, combined with the low cost of instrumentation, make this approach promising for clinical applications.

In the original publication of the article, under the heading Discussion, 1st paragraph, the sentence that reads as, “Nonetheless, our observed improvements of over 50% for OS and over 30% for DFS (HRs: 0.45 and 0.66, respectively) are consistent with results from other available studies” should read as “Nonetheless, our observed improvements of over 50% for OS and DFS (HRs: 0.45 and 0.66, respectively) are consistent with results from other available studies.” Under the heading Discussion, 3rd paragraph, the sentence that reads as “We cannot discount the possibility …such as education, income and access to care [1, 7]” should read as “We cannot discount the possibility…such as education, income and access to care, which ultimately have on survival outcomes [1, 7].”.

Purpose A single‐sided NMR instrument was used to investigate the ability of the T1 relaxation constant to distinguish between regions of low and high mammographic density in human breast tissue. Methods Measurements were performed on 5 breast slices obtained from 3 women undergoing breast reduction surgery or prophylactic mastectomy. Results T1 values measured in regions of high mammographic density in both the full breast slices (T1 = 170 ± 30 ms) and excised regions (T1 = 160 ± 30 ms) were found to be significantly different (P < .001) from those measured in regions of low mammographic density, in which T1 = 120 ± 10 ms was observed both in full slices and excised regions. There was no statistically significant difference between the T1 values measured in the full breast slices and those measured in the excised regions. Conclusion The findings suggest that portable NMR may provide a low‐cost means of assessing mammographic density in vivo.

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.

BACKGROUND: While weight gain following breast cancer is considered common, results supporting these findings are dated. This work describes changes in body weight following breast cancer over 72 months, compares weight with normative data and explores whether weight changes over time are associated with personal, diagnostic, treatment or behavioral characteristics. METHODS: A population-based sample of 287 Australian women diagnosed with early-stage invasive breast cancer was assessed prospectively at six, 12, 18 and 72 months post-surgery. Weight was clinically measured and linear mixed models were used to explore associations between weight and participant characteristics (collected via self-administered questionnaire). Those with BMI changes of one or more units were considered to have experienced clinically significant changes in weight. RESULTS: More than half (57%) of participants were overweight or obese at 6 months post-surgery, and by 72 months post-surgery 68% of women were overweight or obese. Among those who gained more weight than age-matched norms, clinically significant weight gain between 6 and 18 months and 6 and 72 months post-surgery was observed in 24% and 39% of participants, respectively (median [range] weight gain: 3.9 kg [2.0-11.3 kg] and 5.2 kg [0.6-28.7], respectively). Clinically-significant weight losses were observed in up to 24% of the sample (median [range] weight loss between 6 and 72 months post-surgery: -6.4 kg [-1.9--24.6 kg]). More extensive lymph node removal, being treated on the non-dominant side, receiving radiation therapy and lower physical activity levels at 6 months was associated with higher body weights post-breast cancer (group differences >3 kg; all p < 0.05). CONCLUSIONS: While average weight gain among breast cancer survivors in the long-term is small, subgroups of women experience greater gains linked with adverse health and above that experienced by age-matched counterparts. Weight change post-breast cancer is a c

BACKGROUND: In Australia, breast cancer is the most common cancer affecting Australian women. Inequalities in clinical and psychosocial outcomes have existed for some time, affecting particularly women from rural areas and from areas of disadvantage. We have a limited understanding of how individual and area-level factors are related to each other, and their associations with survival and other clinical and psychosocial outcomes. METHODS/DESIGN: This study will examine associations between breast cancer recurrence, survival and psychosocial outcomes (e.g. distress, unmet supportive care needs, quality of life). The study will use an innovative multilevel approach using area-level factors simultaneously with detailed individual-level factors to assess the relative importance of remoteness, socioeconomic and demographic factors, diagnostic and treatment pathways and processes, and supportive care utilization to clinical and psychosocial outcomes. The study will use telephone and self-administered questionnaires to collect individual-level data from approximately 3, 300 women ascertained from the Queensland Cancer Registry diagnosed with invasive breast cancer residing in 478 Statistical Local Areas Queensland in 2011 and 2012. Area-level data will be sourced from the Australian Bureau of Statistics census data. Geo-coding and spatial technology will be used to calculate road travel distances from patients' residence to diagnostic and treatment centres. Data analysis will include a combination of standard empirical procedures and multilevel modelling. DISCUSSION: The study will address the critical question of: what are the individual- or area-level factors associated with inequalities in outcomes from breast cancer? The findings will provide health care providers and policy makers with targeted information to improve the management of women with breast cancer, and inform the development of strategies to improve psychosocial care for women with breast cancer.

Udgivelsesdato: 2005-Jan, AIMS: Recently, a novel human G protein-coupled receptor 40 (GPR40), which is predominantly expressed in pancreatic islets, was shown to mediate an amplifying effect of long-chain fatty acids on glucose-induced insulin secretion. The present aim was to examine the coding region of GPR40 for variation and to assess whether identified variants confer an increased risk of Type 2 diabetes or altered insulin release. METHODS: Mutation analysis was performed in 43 patients with Type 2 diabetes, 18 normal glucose-tolerant subjects, and 3 maturity-onset of diabetes in the young (MODY) X patients using direct sequencing. Genotyping was performed using polymerase chain reaction (PCR)-generated primer extension products analysis by high throughput chip-based mass spectrometry (MALDI-TOF). The potential impact of GPR40 mutations on [(3)H]-myo-inositol turnover was estimated in COS-7 cells after stimulation with various concentrations of 5,8,11-eicosatriynoic acid. RESULTS: Two nucleotide substitutions, an Arg211His polymorphism and a rare Asp175Asn mutation, were identified. Both variants showed EC(50) values similar to the wild type. However, the maximal efficacy of the rare Asp175Asn was 39% lower compared with the wild type (P = 0.01). The Arg211His polymorphism had a similar allele frequency among 1384 Type 2 diabetic patients [MAF%; 23.4 (95% CI: 21.8-25.0)] and 4424 middle-aged glucose-tolerant subjects [24.1% (23.2-25.0)]. A genotype-quantitative trait study of 5597 non-diabetic, middle-aged subjects from the Inter99 cohort showed no significant differences in oral glucose tolerance test (OGTT)-derived estimates of insulin release between carriers of various GPR40 genotypes. CONCLUSIONS: Variations in the coding region of GPR40 do not appear to be associated with Type 2 diabetes or insulin release alterations.