Contrast-enhanced mammography for surveillance in women with a personal history of breast cancer.

PURPOSE: Women with a personal history of breast cancer have an increased risk of subsequent breast malignancy and may benefit from more sensitive surveillance than conventional mammography (MG). We previously reported outcomes for first surveillance episode using contrast-enhanced mammography (CEM), demonstrating higher sensitivity and comparable specificity to MG. We now report CEM performance for subsequent surveillance. METHODS: A retrospective study of 1,190 women in an Australian hospital setting undergoing annual surveillance following initial surveillance CEM between June 2016 and December 2022. Outcome measures were recall rate, cancer detection rate, contribution of contrast to recalls, false positive rate, interval cancer rate and characteristics of surveillance detected and interval cancers. RESULTS: 2,592 incident surveillance episodes were analysed, of which 93% involved contrast-based imaging. Of 116 (4.5%) recall episodes, 40/116 (34%) recalls were malignant (27 invasive; 13 ductal carcinoma in situ), totalling 15.4 cancers per 1000 surveillance episodes. 55/116 (47%) recalls were contrast-directed including 17/40 (43%) true positive recalls. Tumour features were similar for contrast-directed recalls and other diagnoses. 8/9 (89%) of contrast-directed invasive recalls were Grade 2-3, and 5/9 (56%) were triple negative breast cancers. There were two symptomatic interval cancers (0.8 per 1000 surveillance episodes, program sensitivity 96%). CONCLUSION: Routine use of CEM in surveillance of women with PHBC led to an increase in the detection of clinically significant malignant lesions, with a low interval cancer rate compared to previous published series. Compared to mammographic surveillance, contrast-enhanced mammography increases the sensitivity of surveillance programs for women with PHBC.

Contrast enhanced mammography in breast cancer surveillance.

PURPOSE: Mammography (MG) is the standard imaging in surveillance of women with a personal history of breast cancer or DCIS (PHBC), supplemented with ultrasound. Contrast Enhanced Mammography (CEM) has higher sensitivity than MG and US. We report the performance of CEM compared with MG ± US. METHODS: A retrospective study of patients undergoing their first surveillance CEM in an Australian hospital setting between June 2006 and October 2020. Cases where a patient was recalled for assessment were identified, recording radiology, pathology and treatment details. Blinded re-reading of recalled cases was performed to determine the contribution of contrast. Use of surveillance US across the board was assessed for the period. RESULTS: 73/1191 (6.1%) patients were recalled. 35 (48%) were true positives (TP), with 26 invasive cancers and 9 cases of DCIS, while 38 (52%) were false positive (FP) with a positive predictive value (PPV) 47.9%. 32/73 were recalled due to MG findings, while 41/73 were only recalled due to Contrast. 14/73 had 'minimal signs' with a lesion identifiable on MG with knowledge of the contrast finding, while 27/73 were visible only with contrast. 41% (17/41) recalled due to contrast were TP. Contrast-only TPs were found with low and high mammographic density (MD). Screening breast US reduced by 55% in the year after CEM was implemented. CONCLUSION: Compared to MG, CEM as a single surveillance modality for those with PHBC has higher sensitivity and comparable specificity, identifying additional malignant lesions that are clinically significant. Investigation of interval cancer and subsequent round outcomes is warranted.

Breast cancer screening and overdiagnosis.

Overdiagnosis is a harmful consequence of screening which is particularly challenging to estimate. An unbiased setting to measure overdiagnosis in breast cancer screening requires comparative data from a screened and an unscreened cohort for at least 30 years. Such randomised data will not become available, leaving us with observational data over shorter time periods and outcomes of modelling. This collaborative effort of the International Cancer Screening Network quantified the variation in estimated breast cancer overdiagnosis in organised programmes with evaluation of both observed and simulated data, and presented examples of how modelling can provide additional insights. Reliable observational data, analysed with study design accounting for methodological pitfalls, and modelling studies with different approaches, indicate that overdiagnosis accounts for less than 10% of invasive breast cancer cases in a screening target population of women aged 50 to 69. Estimates above this level are likely to derive from inaccuracies in study design. The widely discrepant estimates of overdiagnosis reported from observational data could substantially be reduced by use of a cohort study design with at least 10 years of follow-up after screening stops. In contexts where concomitant opportunistic screening or gradual implementation of screening occurs, and data on valid comparison groups are not readily available, modelling of screening intervention becomes an advantageous option to obtain reliable estimates of breast cancer overdiagnosis.

The impact of the Covid-19 pandemic on breast cancer early detection and screening.

The COVID-19 pandemic affects mortality and morbidity, with disruptions expected to continue for some time, with access to timely cancer-related services a concern. For breast cancer, early detection and treatment is key to improved survival and longer-term quality of life. Health services generally have been strained and in many settings with population breast mammography screening, efforts to diagnose and treat breast cancers earlier have been paused or have had reduced capacity. The resulting delays to diagnosis and treatment may lead to more intensive treatment requirements and, potentially, increased mortality. Modelled evaluations can support responses to the pandemic by estimating short- and long-term outcomes for various scenarios. Multiple calibrated and validated models exist for breast cancer screening, and some have been applied in 2020 to estimate the impact of breast screening disruptions and compare options for recovery, in a range of international settings. On behalf of the Covid and Cancer Modelling Consortium (CCGMC) Working Group 2 (Breast Cancer), we summarize and provide examples of such in a range of settings internationally, and propose priorities for future modelling exercises. International expert collaborations from the CCGMC Working Group 2 (Breast Cancer) will conduct analyses and modelling studies needed to inform key stakeholders recovery efforts in order to mitigate the impact of the pandemic on early diagnosis and treatment of breast cancer.

Molecular comparison of interval and screen-detected breast cancers.

Breast cancer (BC) diagnosed after a negative mammogram but prior to the next screening episode is termed an 'interval BC' (IBC). Understanding the molecular differences between IBC and screen-detected BCs (SDBC) could improve mammographic screening and management options. Therefore, we assessed both germline and somatic genomic aberrations in a prospective cohort. Utilising the Lifepool cohort of >54 000 women attending mammographic screening programs, 930 BC cases with screening status were identified (726 SDBC and 204 IBC). Clinico-pathological and family history information were recorded. Germline and tumour DNA were collected where available and sequenced for BC predisposition and driver gene mutations. Compared to SDBC, IBCs were significantly associated with a younger age at diagnosis and tumour characteristics associated with worse prognosis. Germline DNA assessment of BC cases that developed post-enrolment (276 SDBCs and 77 IBCs) for pathogenic mutations in 12 hereditary BC predisposition genes identified 8 carriers (2.27%). The germline mutation frequency was higher in IBC versus SDBC, although not statistically significant (3.90% versus 1.81%, p = 0.174). Comparing somatic genetic features of IBC and SDBC matched for grade, histological subtype and hormone receptor revealed no significant differences, with the exception of higher homologous recombination deficiency scores in IBC, and copy number changes on chromosome Xq in triple negative SDBCs. Our data demonstrates that while IBCs are clinically more aggressive than SDBC, when matched for confounding clinico-pathological features they do not represent a unique molecular class of invasive BC, but could be a consequence of timing of tumour initiation and mammographic screening. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Prospective validation of the NCI Breast Cancer Risk Assessment Tool (Gail Model) on 40,000 Australian women.

BACKGROUND: There is a growing interest in delivering more personalised, risk-based breast cancer screening protocols. This requires population-level validation of practical models that can stratify women into breast cancer risk groups. Few studies have evaluated the Gail model (NCI Breast Cancer Risk Assessment Tool) in a population screening setting; we validated this tool in a large, screened population. METHODS: We used data from 40,158 women aged 50-69 years (via the lifepool cohort) participating in Australia's BreastScreen programme. We investigated the association between Gail scores and future invasive breast cancer, comparing observed and expected outcomes by Gail score ranked groups. We also used machine learning to rank Gail model input variables by importance and then assessed the incremental benefit in risk prediction obtained by adding variables in order of diminishing importance. RESULTS: Over a median of 4.3 years, the Gail model predicted 612 invasive breast cancers compared with 564 observed cancers (expected/observed (E/O) = 1.09, 95% confidence interval (CI) 1.00-1.18). There was good agreement across decile groups of Gail scores (χ2 = 7.1, p = 0.6) although there was some overestimation of cancer risk in the top decile of our study group (E/O = 1.65, 95% CI 1.33-2.07). Women in the highest quintile (Q5) of Gail scores had a 2.28-fold increased risk of breast cancer (95% CI 1.73-3.02, p < 0.0001) compared with the lowest quintile (Q1). Compared with the median quintile, women in Q5 had a 34% increased risk (95% CI 1.06-1.70, p = 0.014) and those in Q1 had a 41% reduced risk (95% CI 0.44-0.79, p < 0.0001). Similar patterns were observed separately for women aged 50-59 and 60-69 years. The model's overall discrimination was modest (area under the curve (AUC) 0.59, 95% CI 0.56-0.61). A reduced Gail model excluding information on ethnicity and hyperplasia was comparable to the full Gail model in terms of correctly stratifying women into risk groups. CONCLUSIONS: This study confirms that the Gail model (or a reduced model excluding information on hyperplasia and ethnicity) can effectively stratify a screened population aged 50-69 years according to the risk of future invasive breast cancer. This information has the potential to enable more personalised, risk-based screening strategies that aim to improve the balance of the benefits and harms of screening.

Treatment Intensity Differences After Early-Stage Breast Cancer (ESBC) Diagnosis Depending on Participation in a Screening Program.

BACKGROUND: While population mammographic screening identifies early-stage breast cancers (ESBCs; ductal carcinoma in situ [DCIS] and invasive disease stages 1-3A), commentaries suggest that harms from overdiagnosis and overtreatment may outweigh the benefits. Apparent benefits to patients with screen-detected cancers may be due to selection bias from exclusion of interval cancers (ICs). Treatment intensity is rarely discussed, with an assumption that all ESBCs are treated similarly. We hypothesized that women diagnosed while in a screening program would receive less-intense treatment than those never or not recently screened (NRS). METHODS: This was a retrospective analysis of all women aged 50-69 years managed for ESBC (invasive or DCIS) during the period 2007-2013 within a single service, comparing treatment according to screening status. Data on demographics, detection, pathology, and treatment were derived from hospital, cancer registry, and screening service records. RESULTS: Overall, 622 patients were active screeners (AS) at diagnosis (569 screen-detected and 53 ICs) and 169 patients were NRS. AS cancers were smaller (17 mm vs. 26 mm, p < 0.0001), less likely to involve nodes (26% vs. 48%, p < 0.0001), and lower grade. For invasive cancer, NRS patients were more likely to be recommended for mastectomies [35% vs. 16%; risk ratio(RR) 2.2, p < 0.0001], axillary dissection (43% vs. 19%; RR 2.3, p < 0.0001), adjuvant chemotherapy (65% vs. 37%; RR 1.7, p < 0.0001), and postmastectomy radiotherapy (58% vs. 39%; RR 1.5, p = 0.04). CONCLUSION: Participants in population screening diagnosed with ESBC receive substantially less-intense treatment than non-participants. Differences persist when potential overdiagnosis is taken into account; these differences should be factored into debates around mammographic screening.

An Investigation into the Consistency in Mammographic Density Identification by Radiologists: Effect of Radiologist Expertise and Mammographic Appearance.

The aim of this work is to investigate how radiologist expertise and image appearance may have an impact on inter-reader variability of mammographic density (MD) identification. Seventeen radiologists, divided into three expertise groups, were asked to manually segment the areas they consider to be MD in 40 clinical images. The variation in identification of MD for each image was quantified by finding the range of segmentation areas. The impact of radiologist expertise and image appearance on this variation was explored. The range of areas chosen by participating radiologists varied from 7 to 73% across the 40 images, with a mean range of 35 ± 13%. Participants with high expertise were more likely to choose similar areas to one another, compared to participants with medium and low expertise levels (mean range were 19 ± 10%, 29 ± 13% and 25 ± 14 %, respectively, p < 0.0001). There was a significantly higher average grey level for the area segmented by all radiologists as MD compared to the area of variation, with mean grey level value for 8-bit images being 146 ± 19 vs. 99 ± 14, respectively. MD segmentation borders were consistent in areas where there was a sharp intensity change within a short distance. In conclusion, radiologists with high expertise tend to have a higher agreement when identifying MD. Tissues which have a lower contrast and a less visually sharp gradient change at the interface between high density tissue and adipose background lead to inter-reader variation in choosing mammographic density.

Breast cancer screening of women aged 70-74 years: results from a natural experiment across Australia.

There is a lack of evidence regarding the optimal age at which to cease mammographic screening for breast cancer. This ecological study compared Australian state and territory level screening participation rates and cancer outcomes from 1996 to 2005 to identify the extent to which screening women aged 70-74 results in smaller, earlier stage breast cancers. With each 10 % absolute increase in screening participation, there was no significant difference in cancer incidence, but the incidence of large cancers was 8 % lower (IRR = 0.92, 95 % CI 0.90-0.94, p < 0.001); there was some evidence of reduced nodal involvement at diagnosis (IRR 0.97, 95 % CI 0.95-0.99, p = 0.004) but this estimate was sensitive to assumptions regarding missing data. Increased mammographic screening of women aged 70-74 years reduces the incidence of large (>15 mm) cancers-and possibly cancers with nodal involvement-without a concomitant increase in overall cancer incidence.

Factors influencing the time to diagnosis and treatment of breast cancer among women in low- and middle-income countries: A systematic review.

PURPOSE: Shorter time from symptoms recognition to diagnosis and timely treatment would be expected to improve the survival of patients with breast cancer (BC). This review identifies and summarizes evidence on time to diagnosis and treatment, and associated factors to inform an improved BC care pathways in Low- and Middle-Income Countries (LMICs). METHODS: A systematic search was conducted in electronic databases including Medline, Embase, PsycINFO and Global Health, covering publications between January 1, 2010, and November 6, 2023. Inclusion criteria encompassed studies published in English from LMICs that reported on time from symptoms recognition to diagnosis and/or from diagnosis to treatment, as well as factors influencing these timelines. Study quality was assessed independently by two reviewers using a standard checklist. Pre-contact, post-contact and treatment intervals and delays in these intervals are presented. Barriers and facilitators for shorter time to diagnosis and treatment found by individual studies after adjusting with covariates are summarized. RESULTS: The review identified 21 studies across 14 countries and found that BC cases took a longer time to diagnosis than to treatment. However, time to treatment also exceeded the World Health Organization (WHO) recommended period for optimal survival. There was inconsistency in terminology and benchmarks for defining delays in time intervals. Low socioeconomic status and place of residence emerged as frequent barriers, while initial contact with a private health facility or specialist was commonly reported as a facilitator for shorter time to diagnosis and treatment. CONCLUSIONS: Guidelines or consensus recommendations are essential for defining the optimal time intervals to BC diagnosis and treatment. Our review supported WHO's Global Breast Cancer Initiative recommendations. Increasing public awareness, strengthening of healthcare professional's capacities, partial decentralization of diagnostic services and implementation of effective referral mechanisms are recommended to achieve a shorter time to diagnosis and treatment of BC in LMICs.

AutoDensity: an automated method to measure mammographic breast density that predicts breast cancer risk and screening outcomes.

INTRODUCTION: While Cumulus - a semi-automated method for measuring breast density - is utilised extensively in research, it is labour-intensive and unsuitable for screening programmes that require an efficient and valid measure on which to base screening recommendations. We develop an automated method to measure breast density (AutoDensity) and compare it to Cumulus in terms of association with breast cancer risk and breast cancer screening outcomes. METHODS: AutoDensity automatically identifies the breast area in the mammogram and classifies breast density in a similar way to Cumulus, through a fast, stand-alone Windows or Linux program. Our sample comprised 985 women with screen-detected cancers, 367 women with interval cancers and 4,975 controls (women who did not have cancer), sampled from first and subsequent screening rounds of a film mammography screening programme. To test the validity of AutoDensity, we compared the effect estimates using AutoDensity with those using Cumulus from logistic regression models that tested the association between breast density and breast cancer risk, risk of small and large screen-detected cancers and interval cancers, and screening programme sensitivity (the proportion of cancers that are screen-detected). As a secondary analysis, we report on correlation between AutoDensity and Cumulus measures. RESULTS: AutoDensity performed similarly to Cumulus in all associations tested. For example, using AutoDensity, the odds ratios for women in the highest decile of breast density compared to women in the lowest quintile for invasive breast cancer, interval cancers, large and small screen-detected cancers were 3.2 (95% CI 2.5 to 4.1), 4.7 (95% CI 3.0 to 7.4), 6.4 (95% CI 3.7 to 11.1) and 2.2 (95% CI 1.6 to 3.0) respectively. For Cumulus the corresponding odds ratios were: 2.4 (95% CI 1.9 to 3.1), 4.1 (95% CI 2.6 to 6.3), 6.6 (95% CI 3.7 to 11.7) and 1.3 (95% CI 0.9 to 1.8). Correlation between Cumulus and AutoDensity measures was 0.63 (P < 0.001). CONCLUSIONS: Based on the similarity of the effect estimates for AutoDensity and Cumulus inmodels of breast density and breast cancer risk and screening outcomes, we conclude that AutoDensity is a valid automated method for measuring breast density from digitised film mammograms.

Benefits and harms of breast cancer screening: Cohort study of breast cancer mortality and overdiagnosis.

BACKGROUND: Quantifying the benefits and harms of breast cancer screening accurately is important for planning and evaluating screening programs and for enabling women to make informed decisions about participation. However, few cohort studies have attempted to estimate benefit and harm simultaneously. AIMS: We aimed to quantify the impact of mammographic screening on breast cancer mortality and overdiagnosis using a cohort of women invited to attend Australia's national screening program, BreastScreen. METHODS: In a cohort of 41,330 women without prior breast cancer diagnosis, screening, or diagnostic procedures invited to attend BreastScreen Western Australia in 1994-1995, we estimated the cumulative risk of breast cancer mortality and breast cancer incidence (invasive and ductal carcinoma in situ) from age 50 to 85 years for attenders and non-attenders. Data were obtained by linking population-based state and national health registries. Breast cancer mortality risks were estimated from a survival analysis that accounted for competing risk of death from other causes. Breast cancer risk for unscreened women was estimated by survival analysis, while accounting for competing causes of death. For screened women, breast cancer risk was the sum of risk of being diagnosed at first screen, estimated using logistic regression, and risk of diagnosis following a negative first screen estimated from a survival analysis. RESULTS: For every 1,000 women 50 years old at first invitation to attend BreastScreen, there were 20 (95% CI 12-30) fewer breast cancer deaths and 25 (95% CI 15-35) more breast cancers diagnosed for women who attended than for non-attendees by age 85. Of the breast cancers diagnosed in screened women, 21% (95% CI 13%-27%) could be attributed to screening. DISCUSSION: The estimated ratio of benefit to harm was consistent with, but slightly less favourable to screening than most other estimates from cohort studies. CONCLUSION: Women who participate in organised screening for breast cancer in Australia have substantially lower breast cancer mortality, while some screen-detected cancers may be overdiagnosed.

Breast Cancer Risk Assessment Tools for Stratifying Women into Risk Groups: A Systematic Review.

BACKGROUND: The benefits and harms of breast screening may be better balanced through a risk-stratified approach. We conducted a systematic review assessing the accuracy of questionnaire-based risk assessment tools for this purpose. METHODS: Population: asymptomatic women aged ≥40 years; Intervention: questionnaire-based risk assessment tool (incorporating breast density and polygenic risk where available); Comparison: different tool applied to the same population; Primary outcome: breast cancer incidence; Scope: external validation studies identified from databases including Medline and Embase (period 1 January 2008-20 July 2021). We assessed calibration (goodness-of-fit) between expected and observed cancers and compared observed cancer rates by risk group. Risk of bias was assessed with PROBAST. RESULTS: Of 5124 records, 13 were included examining 11 tools across 15 cohorts. The Gail tool was most represented (n = 11), followed by Tyrer-Cuzick (n = 5), BRCAPRO and iCARE-Lit (n = 3). No tool was consistently well-calibrated across multiple studies and breast density or polygenic risk scores did not improve calibration. Most tools identified a risk group with higher rates of observed cancers, but few tools identified lower-risk groups across different settings. All tools demonstrated a high risk of bias. CONCLUSION: Some risk tools can identify groups of women at higher or lower breast cancer risk, but this is highly dependent on the setting and population.

A modelled evaluation of the impact of COVID-19 on breast, bowel, and cervical cancer screening programmes in Australia.

Australia introduced COVID-19 infection prevention and control measures in early 2020. To help prepare health services, the Australian Government Department of Health commissioned a modelled evaluation of the impact of disruptions to population breast, bowel, and cervical cancer screening programmes on cancer outcomes and cancer services. We used the Policy1 modelling platforms to predict outcomes for potential disruptions to cancer screening participation, covering periods of 3, 6, 9, and 12 mo. We estimated missed screens, clinical outcomes (cancer incidence, tumour staging), and various diagnostic service impacts. We found that a 12-mo screening disruption would reduce breast cancer diagnoses (9.3% population-level reduction over 2020-2021) and colorectal cancer (up to 12.1% reduction over 2020-21), and increase cervical cancer diagnoses (up to 3.6% over 2020-2022), with upstaging expected for these cancer types (2, 1.4, and 6.8% for breast, cervical, and colorectal cancers, respectively). Findings for 6-12-mo disruption scenarios illustrate that maintaining screening participation is critical to preventing an increase in the burden of cancer at a population level. We provide programme-specific insights into which outcomes are expected to change, when changes are likely to become apparent, and likely downstream impacts. This evaluation provided evidence to guide decision-making for screening programmes and emphasises the ongoing benefits of maintaining screening in the face of potential future disruptions.

A revision of sexual mixing matrices in models of sexually transmitted infection.

Two sexual mixing matrices previously used in models of sexually transmitted infections (STIs) are intended to calculate the probability of sexual interaction between age groups and sexual behaviour subgroups. When these matrices are used to specify multiple criteria for how people select sexual partners (such as age group and sexual behaviour class), their conditional probability structure means that they have in practice been prone to misuse. We constructed revised mixing matrices that incorporate a corrected conditional probability structure and then used one of them to examine the effect of this revision on population modelling of STIs. Using a dynamic model of human papillomavirus (HPV) transmission as an example, we examined changes to estimates of HPV prevalence and the relative reduction in age-standardised HPV incidence after the commencement of publicly funded HPV vaccination in Australia. When all other model specifications were left unchanged, the revised mixing matrix initially led to estimates of age-specific oncogenic HPV prevalence that were up to 11% higher than our previous models at certain ages. After re-calibrating the model by modifying unobservable parameters characterising HPV natural history, the revised mixing matrix yielded similar estimates to our previous models, predicting that vaccination would lead to relative HPV incidence reductions of 43% and 85% by 2010 and 2050, respectively, compared with 43% and 86% using the unrevised mixing matrix formulation. Our revised mixing matrix offers a rigorous alternative to commonly used mixing matrices, which can be used to reliably and explicitly accommodate conditional probabilities, with appropriate re-calibration of unobservable model parameters.

Expenditure and resource utilisation for cervical screening in Australia.

BACKGROUND: The National Cervical Screening Program in Australia currently recommends that women aged 18-69 years are screened with conventional cytology every 2 years. Publicly funded HPV vaccination was introduced in 2007, and partly as a consequence, a renewal of the screening program that includes a review of screening recommendations has recently been announced. This study aimed to provide a baseline for such a review by quantifying screening program resource utilisation and costs in 2010. METHODS: A detailed model of current cervical screening practice in Australia was constructed and we used data from the Victorian Cervical Cytology Registry to model age-specific compliance with screening and follow-up. We applied model-derived rate estimates to the 2010 Australian female population to calculate costs and numbers of colposcopies, biopsies, treatments for precancer and cervical cancers in that year, assuming that the numbers of these procedures were not yet substantially impacted by vaccination. RESULTS: The total cost of the screening program in 2010 (excluding administrative program overheads) was estimated to be A$194.8M. We estimated that a total of 1.7 million primary screening smears costing $96.7M were conducted, a further 188,900 smears costing $10.9M were conducted to follow-up low grade abnormalities, 70,900 colposcopy and 34,100 histological evaluations together costing $21.2M were conducted, and about 18,900 treatments for precancerous lesions were performed (including retreatments), associated with a cost of $45.5M for treatment and post-treatment follow-up. We also estimated that $20.5M was spent on work-up and treatment for approximately 761 women diagnosed with invasive cervical cancer. Overall, an estimated $23 was spent in 2010 for each adult woman in Australia on cervical screening program-related activities. CONCLUSIONS: Approximately half of the total cost of the screening program is spent on delivery of primary screening tests; but the introduction of HPV vaccination, new technologies, increasing the interval and changing the age range of screening is expected to have a substantial impact on this expenditure, as well as having some impact on follow-up and management costs. These estimates provide a benchmark for future assessment of the impact of changes to screening program recommendations to the costs of cervical screening in Australia.

BreastScreen Australia national data by factors of interest for risk-based screening: routinely reported data and opportunities for enhancement.

OBJECTIVE: There is growing interest in more risk-based approaches to breast cancer screening in Australia. This would require more detailed reporting of BreastScreen data for factors of interest in the assessment and monitoring of risk-based screening. This review assesses the current and potential availability and reporting of BreastScreen data for this purpose. METHODS: We systematically searched governmental BreastScreen reports and peer-reviewed literature to assess current and potential availability of outcomes for predetermined factors including breast cancer risk factors and factors important for implementing, monitoring or evaluating risk-based screening. Outcomes evaluated were BreastScreen Performance Indicators routinely included in BreastScreen Australia monitoring reports, and key tumour characteristics. RESULTS: All outcomes were reported annually by age group, except for tumour hormone receptor status, nodal involvement and grade. Screening participation was reported nationally for many factors important for risk-based screening; other reporting was ad hoc or unavailable. CONCLUSIONS: There is potential to build on BreastScreen's existing high-quality national data collection and reporting systems to inform and support risk-based breast screening. IMPLICATIONS FOR PUBLIC HEALTH: Enhanced BreastScreen data collection and reporting would improve the evidence base and support evaluation of risk-based screening and improve the detail available for benchmarking any future changes to the program.

Moving beyond the stage: how characteristics at diagnosis dictate treatment and treatment-related quality of life year losses for women with early stage invasive breast cancer.

Background:Although evaluations of breast cancer screening programs frequently estimate quality-adjusted life-year (QALY) losses by stage, other breast cancer characteristics influence treatment and vary by mode of detection - i.e. whether the cancer is detected through screening (screen-detected), between screening rounds (interval-detected) or outside screening (community-detected). Here, we estimate the association between early-stage invasive breast cancer (ESIBC) characteristics and treatment-related QALY losses.Methods:Using clinicopathological and treatment information from 675 women managed for ESIBC, we estimated the average five-year treatment-related QALY loss by detection group. We then used regression analysis to estimate the extent to which known cancer characteristics and the detection mode, are associated with treatment and treatment-related QALY losses.Results:Community-detected cancers had the largest QALY loss (0.76 QALYs [95% CI 0.73;0.80]), followed by interval-detected cancers (0.75 QALYs [95% CI 0.68;0.82]) and screen-detected cancers (0.69 QALYs [95%CI 0.67;0.71]). Adverse prognostic factors more common in community-detected and interval-detected breast cancers (large tumours, lymph node involvement, high grade) were largely associated with QALY losses from mastectomies and chemotherapy. Receptor-positive subtypes, more common in screen-detected cancers, were associated with QALY losses related to endocrine therapy.Conclusions:The associations between ESIBC characteristics and treatment-related QALY losses should be considered when evaluating breast cancer screening and treatment strategies.