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.

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.

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.

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.

The TP53 mutation rate differs in breast cancers that arise in women with high or low mammographic density.

Mammographic density (MD) influences breast cancer risk, but how this is mediated is unknown. Molecular differences between breast cancers arising in the context of the lowest and highest quintiles of mammographic density may identify the mechanism through which MD drives breast cancer development. Women diagnosed with invasive or in situ breast cancer where MD measurement was also available (n = 842) were identified from the Lifepool cohort of >54,000 women participating in population-based mammographic screening. This group included 142 carcinomas in the lowest quintile of MD and 119 carcinomas in the highest quintile. Clinico-pathological and family history information were recorded. Tumor DNA was collected where available (n = 56) and sequenced for breast cancer predisposition and driver gene mutations, including copy number alterations. Compared to carcinomas from low-MD breasts, those from high-MD breasts were significantly associated with a younger age at diagnosis and features associated with poor prognosis. Low- and high-MD carcinomas matched for grade, histological subtype, and hormone receptor status were compared for somatic genetic features. Low-MD carcinomas had a significantly increased frequency of TP53 mutations, higher homologous recombination deficiency, higher fraction of the genome altered, and more copy number gains on chromosome 1q and losses on 17p. While high-MD carcinomas showed enrichment of tumor-infiltrating lymphocytes in the stroma. The data demonstrate that when tumors were matched for confounding clinico-pathological features, a proportion in the lowest quintile of MD appear biologically distinct, reflective of microenvironment differences between the lowest and highest quintiles of MD.

The financial impact of a breast cancer detected within and outside of screening: lessons from the Australian Lifepool cohort.

OBJECTIVE: To determine the government and out-of-pocket community costs (out-of-hospital medical services and prescription medicines) associated with screen-detected and community-detected cancers (i.e. cancers detected outside of Australia's organised screening program [BreastScreen]). METHODS: We analyse administrative data on government-subsidised medical services and prescription medicines for 568 Victorian women diagnosed with breast cancer or ductal carcinoma in situ (DCIS). Using multivariable regression analysis, we estimate the government and out-of-pocket community costs incurred in the three years after diagnosis for screen-detected cancers and community-detected cancers. Additionally, we estimate the government costs associated with diagnosis within and outside of BreastScreen. RESULTS: Average government costs for breast cancer diagnosis were similar within and outside of BreastScreen [$808 (lower limit 676; upper limit 940) vs $837 (95%CI 671; 1,003) respectively]; however, women with community-detected cancers incurred an additional $254 (95%CI 175; 332) out-of-pocket. Controlling for differences in known cancer characteristics, compared to screen-detected cancers, community-detected breast cancers were associated with an additional $2,622 (95%CI 644; 4,776) in government expenditure in the three years following diagnosis. Adverse cancer characteristics that were more prevalent in community-detected cancers (high grade, lymph node involvement, HER2 positive receptor status) were associated with increased government and out-of-pocket costs. CONCLUSIONS: Community-detected breast cancers were associated with increased government and out-of-pocket costs. Implications for public health: These costs should be considered when evaluating current and alternative breast cancer screening strategies.

Benefits, harms and cost-effectiveness of cancer screening in Australia: an overview of modelling estimates.

INTRODUCTION: There are three government-funded population-based screening programs in Australia - the national breast cancer screening program (BreastScreen Australia), the National Cervical Screening Program (NCSP), and the National Bowel Cancer Screening Program (NBCSP). Options for early detection of other cancers (e.g. hepatocellular carcinoma and melanoma) are under investigation. This study provides an overview of the health benefits, harms and cost-effectiveness of population-level breast, cervical and colorectal cancer screening, targeted-risk screening for lung cancer and Lynch syndrome, and prostate specific antigen (PSA) testing in Australia. METHODS: The study reviewed and, where possible, updated the estimated health benefits, harms and cost-effectiveness of screening approaches from modelling studies for four cancer types, PSA testing and Lynch syndrome testing in Australia. Costs are presented in 2018 Australian dollars. RESULTS: The renewed NCSP (for women not HPV-vaccinated) and the NBCSP were estimated to be cost-effective versus no screening; the cost-effectiveness ratio (CER) was $16 632 per life-year saved (LYS) for the NCSP, and $3380/LYS for the NBCSP. BreastScreen Australia was predicted to have a CER of $40 279/LYS-$65 065/LYS. In 2017, the NCSP transitioned to 5-yearly primary HPV testing with partial genotyping for HPV types 16 and 18 for women aged 25-74 years. Alongside vaccination, this change is predicted to prevent a further 587 cervical cancer deaths in 2018-2035, and have a favourable benefit-to-harm balance versus prior practice (biennial cytology testing for women aged 18-69 years). On average, the NBCSP (biennial screening using an immunochemical faecal occult blood test for people aged 50-74 years) is estimated to prevent 2519 colorectal cancer deaths and result in 350 colonoscopy-related adverse events annually. The inaccuracy of PSA testing as a screening tool impedes the capacity to conduct meaningful cost-effectiveness analyses at a population level, based on current evidence. Three annual low-dose computed tomography screens for lung cancer using the US National Lung Screening Trial selection criteria would not be cost-effective in Australia. A comprehensive cost-effectiveness evaluation of systematic proband testing, cascade testing and subsequent surveillance for Lynch syndrome in Australia is currently underway. CONCLUSIONS: Current evidence supports a favourable cost-effectiveness and benefit-to-harm balance for the NCSP and NBCSP. An updated cost-effectiveness and benefits-to-harms analysis for BreastScreen Australia is required. Carefully founded quantitative estimates of health benefits, harms and cost-effectiveness provide an important aid to policy decision making, and form the basis for developing decision aids to guide individual screening decisions. Opportunities exist for lung cancer screening, systematic Lynch syndrome testing and informed decision making about PSA testing. However, more evidence is required on risk assessment, targeting of screening tests, optimal referral pathways, managing potential harms and delivering services in a cost-effective framework.

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.

Measurement challenge: protocol for international case-control comparison of mammographic measures that predict breast cancer risk.

INTRODUCTION: For women of the same age and body mass index, increased mammographic density is one of the strongest predictors of breast cancer risk. There are multiple methods of measuring mammographic density and other features in a mammogram that could potentially be used in a screening setting to identify and target women at high risk of developing breast cancer. However, it is unclear which measurement method provides the strongest predictor of breast cancer risk. METHODS AND ANALYSIS: The measurement challenge has been established as an international resource to offer a common set of anonymised mammogram images for measurement and analysis. To date, full field digital mammogram images and core data from 1650 cases and 1929 controls from five countries have been collated. The measurement challenge is an ongoing collaboration and we are continuing to expand the resource to include additional image sets across different populations (from contributors) and to compare additional measurement methods (by challengers). The intended use of the measurement challenge resource is for refinement and validation of new and existing mammographic measurement methods. The measurement challenge resource provides a standardised dataset of mammographic images and core data that enables investigators to directly compare methods of measuring mammographic density or other mammographic features in case/control sets of both raw and processed images, for the purposes of the comparing their predictions of breast cancer risk. ETHICS AND DISSEMINATION: Challengers and contributors are required to enter a Research Collaboration Agreement with the University of Melbourne prior to participation in the measurement challenge. The Challenge database of collated data and images are stored in a secure data repository at the University of Melbourne. Ethics approval for the measurement challenge is held at University of Melbourne (HREC ID 0931343.3).

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.