Introduction

Population-based mammography endeavours to reduce mortality via early detection and prompt treatment [1–3]. Despite growing evidence of high heterogeneity of breast cancer risk within populations, breast cancer screening programmes commonly recommend starting mammography screening at age 40 or 50 [4]. Furthermore, mammographic screening itself has many limitations–over-diagnosis and overtreatment being prime among them [5]. While substantially increasing the number of cases of early-stage breast cancer detected, it only marginally reduces the rate at which women present with advanced cancer, as illustrated in the Cochrane reviews [6], Canadian National Breast Screening Study [7] and other studies [8,9]. This has generated international interest in a more risk-stratified approach to the current “one-size-fits all” population screening programmes [10–15].

BreastScreen Singapore, a nation-wide mammography screening programme in Singapore established in 2002 by the Health Promotion Board, invites women aged 50 to 69 to participate in the early detection of breast cancer. However, only 66% of the target group have reported to ever had a mammogram, and half of them do not adhere to the recommended biennial screening guideline (<30% of the target group were reported to attend mammogram every 2 years) [16]. Lukewarm responses to these initiatives have been attributed to a low perception of risk and misperceptions of risk factors and knowledge of breast cancer by women [16–21]. A number of studies have since proposed that risk-based screening may improve timeliness of screening. Furthermore, under the current age-based screening paradigm, approximately 30% of diagnosed breast cancer cases in Singapore are women of a younger age than the recommended screening age by the national guidelines [22]. The striking difference of ~10 years in the peak age for breast cancer in between Asian (40 to 50 years) and Western (60 to 70 years) prompts the need to reconsider screening approaches adapted from Western studies in Asia [23]. The design and adoption of risk-stratified approach to screening is needful for timely identification and treatment of these high-risk individuals.

Personalised screening enhances an age-based screening paradigm by tailoring screening recommendations to the individual’s risk profile [24]. This reduces the rate of false positive results and over-diagnosis in lower risk individuals, thereby providing a more effective method to identify high risk individuals for intervention [25]. Currently, to identify high risk individuals, most screening programmes rely primarily on the evaluation of age, family history, clinical and lifestyle factors, and the testing of pathogenic variants in breast cancer predisposition genes [14,26].

Breast cancer is a multifactorial disease with both genetic and non-genetic risk factors. The Gail model (also known as the Breast Cancer Risk Assessment Tool) was first developed in 1989 for prediction using non-genetic risk factors in Whites, and has since been calibrated and validated for other ethnicities [27]. Furthermore, information from the first screen (i.e. mammographic density and false positive status) are indicators of elevated risk [28]. The validated Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) model is able to predict carriership of mutations in known breast cancer genes such as BRCA1 and BRCA2 [2,29–32].

Known pathogenic variants are rare. Due to cost issues, they are usually tested in only high risk individuals [33,34]. Common variants (i.e. single nucleotide polymorphism (SNP)) associated with breast cancer risk have been discovered through genome-wide association studies [35]. Individually, these SNPs have minimal effect on risk. However, Mavaddat et al. built a polygenic Risk Scores (PRS)–a tally of 313 SNPs–that emerged as a robust means to estimate an individual’s risk of breast cancer [36,37]. The PRS (313 SNPs) is able to reliably predict breast cancer risk, with those in the top centile having a lifetime absolute risk of 32.6% [38]. This PRS has been validated in women of Asian descent [38]. Despite a growing body of evidence illustrating the utility of PRS in population screening programmes, policy implementation has been low [3]. While the Gail model [27], mammographic density [39] and breast cancer predisposition genes [40] have been incorporated into prior risk stratification studies, implementation of PRS is less common [3].

BREATHE is a landmark study aiming to contextualise a personalised, risk-based screening approach to the Asian population (specific aims are listed in Table 1). The present study endeavours to explore the acceptability and potential impact on changes in screening behaviour of the BREATHE risk-stratified screening programme as the first step towards policy implementation. With the cost-effectiveness of similar approaches validated [41], it is hoped that BREATHE will greatly enhance resource allocation and patient outcomes in the era of precision medicine.

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Table 1. Specific aims of BREAst screening Tailored for HEr (BREATHE).

https://doi.org/10.1371/journal.pone.0265965.t001

Materials and methods

Study design and setting

BREATHE is a prospective multi-centre cohort to study a new modality of breast cancer screening in healthy Singaporean women aged between 35 and 59. Recruitment started in Oct 2021 and plans to recruit ~3,500 participants from two hospitals (Ng Teng Fong General Hospital and National University Hospital) and two polyclinics (Bukit Batok Polyclinic and Choa Chu Kang Polyclinic) over a period of two years. To achieve coverage of all age groups of interest, recruitment targets were allocated as such: 20% aged 35 to 39 years; 40% aged 40 to 49 years; and 40% aged 50 to 59 years. The proportion selected was based on the background population in the 2019 population report published on Singapore Department of Statistics. Participants will be on active follow-up for two years. In brief, enrolled participants will be asked (1) to provide a buccal swap for genotyping at study entry and (2) to answer various questionnaires and surveys at study entry and at the two follow-ups (at ~3 months and ~2 years after study entry) (Fig 1). All surveys are translated to the three major languages used in Singapore: Mandarin, Malay and Tamil.

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Fig 1. Summary of the recruitment and follow-up process.

This study was approved by the National Healthcare Group Domain Specific Review. Board (reference no: 2020/01327). Written informed consent will be obtained from each participant.

https://doi.org/10.1371/journal.pone.0265965.g001

Risk stratification process and personal breast cancer risk report

Participants will be classified as above average, average or below average risk, based on (1) the Gail model; (2) information from the most recent mammography screening (mammography density and positive recall status); (3) BOADICEA; and (4) the PRS. Participants will first be considered average risk and reclassified as above average or below average based on the criteria in Table 2. A risk report will be produced and presented to the participant during the first follow-up session. All participants are recommended to follow current national guidelines (Table 3). In the BREATHE programme, women identified to be above average in breast cancer risk are referred to breast specialists at designated study sites, in addition to prevailing guidelines.

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Table 2. Breast cancer risk reclassification criteria.

https://doi.org/10.1371/journal.pone.0265965.t002

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Table 3. National guidelines for breast cancer screening in Singapore.

https://doi.org/10.1371/journal.pone.0265965.t003

Gail model (non-genetic risk factors).

The Gail Model requires the following breast cancer risk factors from the questionnaire from the first visit: age, age at menarche, age at first live birth, number of previous benign breast biopsies, presence of atypical hyperplasia on biopsy, family history of breast cancer (mother, sisters or daughters), and ethnicity [44,45]. Weights (logistic regression coefficients derived from the Gail model) and attributable risks of Asian-Americans will be used in the calculation of five-year absolute risk based on the Gail model (“Asian.AABCS”, BCRA package in R) [45].

Information from most recent mammography screening.

Mammographic density will be ascertained according to the breast composition categories of the Breast Imaging-Reporting and Data System (5th edition): almost entirely fatty, scattered areas of fibroglandular density, heterogeneously dense or extremely dense. A participant is considered recalled (i.e positive recall status) when she is asked to return for additional confirmatory examination or additional mammography views due to abnormal findings from initial screening.

Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) predictions for breast cancer predisposition genes.

Carrier probabilities for breast cancer predisposition genes such as BRCA1 and BRCA2 will be predicted using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA, web application v3, https://ccge.medschl.cam.ac.uk/boadicea/boadicea-web-application/, accessed Dec 28, 2021) [40]. Briefly, as described by Antoniou et al [40], the probability that an individual carries a mutation in BRCA1/BRCA2 or other breast cancer genes based on family history can be computed using Bayes theorem.

Breast cancer polygenic risk score.

PRS is estimated as the weighted sum of effect alleles in 313 SNPs found to be associated with breast cancer; using PLINK (version 3) with the “scoresum” option [46]. where x_k is the risk allele (0, 1, 2) for SNP k, β_k is the corresponding weight. The weights of the 313 SNPs for overall breast cancer risk were obtained from are of the overall breast cancer risk published by Mavaddat et al [47].

Discussion

Many previous works have evaluated the validity and discriminatory power of breast cancer risk calculators, alone or in combination [27,28,48]. In spite of the advances in breast cancer risk prediction, screening recommendations in practice have remained largely unchanged for the past few decades [23]. Several large-scale studies conducted in populations of European ancestry, such as KARMA—KARolinska MAmmography Project for Risk Prediction of Breast Cancer [49], PROCAS—Predicting the Risk of Cancer at Screening [50], WISDOM—Women Informed to Screen Depending On Measures of risk [43], are already underway to evaluate the feasibility of implementing risk stratification in breast screening programmes. However, prediction tools should be validated and calibrated to the target population [51]. To our knowledge, BREATHE is the first initiative to incorporate risk stratification approaches to enhance the efficacy of existing breast screening protocols in Asia.

Our study leverages on the existing national breast cancer screening programme (BreastScreen Singapore) [21]. Hence mammography service is consistent across all participants. The setup is scalable to include additional hospitals and polyclinics in the future. Singapore is geographically small and convenient for participants to visit breast clinics for recommendations to manage their breast cancer risk. While potential participants can visit multiple hospitals or polyclinics throughout our recruitment period, each individual’s unique National Registration Identity Card number allows us to track them for follow-up. Loss to passive follow-up due to emigration is expected to be minimal for the duration of the study. The BREATHE risk classification is adapted from the established WISDOM Personalized Breast Cancer Screening Trial [43]. WISDOM uses a five-year absolute risk threshold of 6% (risk of an average BRCA carrier) for stratification [43]. However, it is known that the incidence of breast cancer among Asian women is lower [38,43]. Hence, the BREATHE study uses five-year absolute risk above 3% as a threshold (equivalent to women aged 50 years at the top risk percentile based on PRS in Singapore, S7 Appendix).

In this study, only one risk report is generated per participant based on information at recruitment. Over time, the participant’s risk will change. An updated risk report is recommended if the programme were to be implemented in a nation-wide screening programme. As our risk estimates reflect a five-year absolute risk by the Gail model and PRS, a review of breast cancer risk should be done at a minimum frequency of five years.

Personal risk of breast cancer is a difficult concept to grasp. Breast cancer risk prediction tools are mainly designed for providers, hence the participant may have a limited understanding of the results [52]. We deliberated over the readiness of the Singapore’s population to receive personalised disease risk results with various stakeholders (representatives of the hospitals and clinics, ethics representatives, public health experts, and researchers), and concluded that only the general risk classification (below-average, average and above-average risk) is to be conveyed to the participants as part of this research study.

Details on the risk classification categories are communicated and explained to the participants by healthcare professionals to ensure that the results are interpreted accurately and meaningfully. At recruitment, participants are briefed about the risk stratification tools used in this study. We understand that in this current information age, it is likely that there will be participants especially those in the above-average risk group will want details about their risk levels. Our main concern is in the participants’ understanding of genetic risk, in particular the genetic risk component. As we want to create an inclusive risk-based screening program, we are not performing clinical genetic testing as part of this screening design. Unlike the better known and more expensive clinical genetic testing, PRS is a new method of breast cancer risk assessment that is not familiar to our study population. To avoid the situation where participants reject screening due to any misconception about risk (i.e. the idea that if I am genetically above-average risk there is nothing I can do to avoid getting breast cancer), we will only indicate the general risk level in the risk report. Based on the risk assessment by our ethics board, it is prudent that the follow-up of the above-average risk group and conveying of the details of the risk classification is done based on current clinical practice by clinicians and not part of the research study. Participants who are predicted carriers of BRCA1/2 by BOADICEA will be recommended to see a breast specialist and referred to genetic counselling and subsequently genetic testing if appropriate.

We expect challenges in attaining our target recruitment of 3500 healthy women aged between 35 and 59. As this is a hospital led research study, publicity is limited to the hospitals and affiliated polyclinics. BREATHE may be extended to other sites (e.g. Alexandra Hospital and Jurong Medical Centre) to increase recruitment numbers. Participants are encouraged to refer family and friends to the program; they are given flyers with the sign-up link for enrolment. In addition, given the small geographic size of Singapore, redeployment of recruiters from sites with low numbers of potential participants to sites with higher numbers of potential participants is in our strategy to reach out to as many women as possible.

BREATHE has some limitations worth noting. Selection bias may arise due to systematic differences between baseline characteristics of responders and non-responders to BREATHE’s advertisements. BREATHE participants may be more health conscious or are already attending breast screening. Such a bias may affect sample representativeness and generalizability of findings. However, the BREATHE study collects information on the study participants (e.g. profession, socio-economic status, highest education attained) and how they found out about the study. This information will allow us to assess the implementation of a risk-based screening approach in this population first, before rolling out the initiative on a larger scale. The BREATHE risk report is based on information available from each participant. For example, if the participant does not participate in or is ineligible for mammography screening, information from first screen will not be in the risk report (participant is assumed to be of average risk). When information is incomplete, breast cancer risk will be underestimated. Barriers to active follow-up two years later are expected. However, the study coordinators will be actively contacting the participants to remind them about the follow-up visit. In addition, the questionnaire is designed such that the participant does not need to be present in-person (conducted electronically or over a phone call).

Conclusions

The aims of BREATHE are aligned with efforts to use personalized health for tailored interventions. For breast cancer screening, multiple studies have supported a risk-stratified approach over the current age-based paradigm due to potentially higher cost-effectiveness and reduced over-diagnosis [13,24,53,54]. If BREATHE is successful, women will gain a realistic understanding of their personal risk of breast cancer as well as strategies to reduce their risk, and fewer women will suffer from the anxiety of false positive mammograms and unnecessary biopsies. This work puts Singapore on the world map as a pioneer in integrating state-of-the-art breast cancer risk prediction tools, in particular, breast cancer PRS, in breast cancer screening. This study has real potential to transform breast cancer screening in Singapore.

BREATHE has assembled a multidisciplinary team to build on best practices and emerging data from other risk-based breast cancer screening studies elsewhere. Data-driven and patient-centric value-based care will benefit the healthcare system in many aspects. At the personal level: Women will gain a realistic understanding of their personal breast cancer risk and be empowered to make informed decisions together with their physicians on strategies to manage their risk. At the clinic: The comprehensive risk classification will aid physicians in the conversation on the need for further genetic testing as well as screening and risk reduction strategies. At the population-level: BREATHE generates real-world evidence on how to change the breast cancer screening paradigm to recognize the different needs of individuals. This includes assessment of the organizational readiness, effectiveness, efficiency, resources, costs and cost-effectiveness of implementing a risk-based breast cancer screening approach in Singapore. BREATHE puts Singapore on the world map as one of the pioneers in integrating state-of-the-art risk prediction tools in breast cancer screening, with a real potential to transform the health system to deliver better health and healthcare outcomes.

Supporting information

Acknowledgments

We want to thank our dedicated research and administrative staff—Ganga Devi D/O Chandrasegran, Hui Min Lau, Pooi Yee Wong, Hui Ling Tan, Kimiie Chia Wei Lin, Nabilah Binte Supiee, Nurfilya Binte Hamdil, Amanda Ong Tse Woon, Jing Jing Hong, Siew Li Tan, Evelyn Low Sok Peng, Marina Mohd, Noor Aisha Binte Mohamed Bahru Ali and Linus Chui for their contributions in the planning and preparation of BREATHE. We wish to acknowledge the contribution of Singapore Consortium of Cohort Studies-Multi-ethnic cohort (MEC) in providing information on women without breast cancer which is representative of the general population.