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There are currently no single disruptors to breast cancer screening akin to the impact of human papillomavirus testing and vaccination on cervical cancer screening. However, there is a groundswell of interest to review the BreastScreen Australia program to consider more risk-based screening protocols and to establish whether to routinely inform women about their breast density. We propose a framework for a considered, evidence-based review. Population-level effectiveness of breast cancer screening is ultimately measured through its impact on breast cancer mortality, and this has been realised in Australia. Effectiveness can also be measured through treatment intensity, estimated overdiagnosis, false-positive screens and health economics measures. Key levers to improve such population-level outcomes include screening participation, screening test sensitivity and specificity, risk assessment and screening protocols. We propose that the review of the program should fall under an evidence-based, consensus-guided framework comprising four complementary elements: improved evidence on current program performance for population risk subgroups; regularly updated evidence on key levers for change; clinical trials and population simulation modelling working in tandem; and consensus-based decision making about the degree of improvement required to justify change. Informing women about their breast density is feasible and would be valued by some BreastScreen clients to help understand the accuracy of their screening test. However, without agreed protocols for screening women with dense breasts, increases in supplemental screening as observed in other settings would, in Australia, shift screening costs to clients and Medicare. This would reduce equity of access to population screening, and maintaining BreastScreen's usual standard of monitoring and quality management (such as screen-detected and interval cancer diagnoses, and imaging and biopsy rates) would require data linkage between BreastScreen and other services. The proposed framework assesses screening effectiveness in the era of personalised medicine, allows review of multiple factors that may together warrant change, and gives full, evidence-based consideration of the benefits, harms and costs of various approaches to breast cancer screening. To be effective, the framework requires a coordinated approach to generating the evidence required for policy makers, with time to prepare appropriate health services., Competing Interests: CN receives salary funding via the project 'Optimising Early Detection of Breast Cancer in Australia', funded by the Australian Department of Health and led by Cancer Council Australia. She jointly leads the development of the AutoDensity automated breast density measurement tool, through a collaboration between the University of Melbourne and the CSIRO. PB is the Chief Executive Officer of the start-up DetectEd-X, which provides radiology training and research.

This study demonstrates that the clinical sensitivity, specificity, and reproducibility of the novel cobas human papillomavirus (HPV) test on the cobas 6800 system for high-risk HPV types fulfills the criteria for use in population-based cervical screening. The criteria were formulated by an international consortium, using the cobas 4800 HPV test as a validated reference assay. The cobas HPV test detected over 98% of histologically confirmed cervical intraepithelial neoplasia grade 2+ (CIN2+) lesions in women age 30 years or older, with a specificity of 98.9% compared with the reference cobas 4800 test. Both the intra- and interlaboratory agreement for the cobas HPV test were 98%. The clinical performance of the cobas HPV test is comparable to those of longitudinally validated HPV assays and fulfills the criteria for its use in primary cervical screening., (Copyright © 2019 Saville et al.)

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 (χ 2  = 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.

Primary HPV screening enables earlier diagnosis of cervical lesions compared to cytology, however, its effect on the risk of treatment and adverse obstetric outcomes has not been extensively investigated. We estimated the cumulative lifetime risk (CLR) of cervical cancer and excisional treatment, and change in adverse obstetric outcomes in HPV unvaccinated women and cohorts offered vaccination (>70% coverage in 12-13 years) for the Australian cervical screening program. Two-yearly cytology screening (ages 18-69 years) was compared to 5-yearly primary HPV screening with partial genotyping for HPV16/18 (ages 25-74 years). A dynamic model of HPV transmission, vaccination, cervical screening and treatment for precancerous lesions was coupled with an individual-based simulation of obstetric complications. For cytology screening, the CLR of cervical cancer diagnosis, death and treatment was estimated to be 0.649%, 0.198% and 13.4% without vaccination and 0.182%, 0.056% and 6.8%, in vaccinated women, respectively. For HPV screening, relative reductions of 33% and 22% in cancer risk for unvaccinated and vaccinated women are predicted, respectively, compared to cytology. Without the implementation of vaccination, a 4% increase in treatment risk for HPV versus cytology screening would have been expected, implying a possible increase in pre-term delivery (PTD) and low birth weight (LBW) events of 19 to 35 and 14 to 37, respectively, per 100,000 unvaccinated women. However, in vaccinated women, treatment risk will decrease by 13%, potentially leading to 4 to 41 fewer PTD events and from 2 more to 52 fewer LBW events per 100,000 vaccinated women. In unvaccinated women in cohorts offered vaccination as 12-13 year olds, no change to lifetime treatment risk is expected with HPV screening. In unvaccinated women in cohorts offered vaccination as 12-13 year olds, no change to lifetime treatment risk is expected with HPV screening. HPV screening starting at age 25 in populations with high vaccination coverage, is therefore expected to both improve the benefits (further decrease risk of cervical cancer) and reduce the harms (reduce treatments and possible obstetric complications) associated with cervical cancer screening., (© 2017 UICC.)

Simple Summary: Early detection of breast cancer in asymptomatic women through screening is an important strategy in reducing the burden of breast cancer. In current organized breast screening programs, age is the predominant risk factor. Breast cancer risk assessment tools are numerical models that can combine information on various risk factors to estimate the risk of being diagnosed with breast cancer within a certain time period. These tools could be used to offer risk-based screening. This systematic review assessed, using a variety of methods, how accurately breast cancer risk assessment tools can group women eligible for screening within a population, into risk groups, so that each group could potentially be offered a screening protocol with more benefits and less harms compared to current age-based screening. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]