The WISDOM Personalized Breast Cancer Screening Trial: Simulation Study to Assess Potential Bias and Analytic Approaches

Precision public health in the era of genomics and big data

Precision public health (PPH) considers the interplay between genetics, lifestyle and the environment to improve disease prevention, diagnosis and treatment on a population level-thereby delivering the right interventions to the right populations at the right time. In this Review, we explore the concept of PPH as the next generation of public health. We discuss the historical context of using individual-level data in public health interventions and examine recent advancements in how data from human and pathogen genomics and social, behavioral and environmental research, as well as artificial intelligence, have transformed public health. Real-world examples of PPH are discussed, emphasizing how these approaches are becoming a mainstay in public health, as well as outstanding challenges in their development, implementation and sustainability. Data sciences, ethical, legal and social implications research, capacity building, equity research and implementation science will have a crucial role in realizing the potential for 'precision' to enhance traditional public health approaches.

Public Preferences for Genetic and Genomic Risk-Informed Chronic Disease Screening and Early Detection: A Systematic Review of Discrete Choice Experiments

PURPOSE

Genetic and genomic testing can provide valuable information on individuals' risk of chronic diseases, presenting an opportunity for risk-tailored disease screening to improve early detection and health outcomes. The acceptability, uptake and effectiveness of such programmes is dependent on public preferences for the programme features. This study aims to conduct a systematic review of discrete choice experiments assessing preferences for genetic/genomic risk-tailored chronic disease screening.

METHODS

PubMed, Embase, EconLit and Cochrane Library were searched in October 2023 for discrete choice experiment studies assessing preferences for genetic or genomic risk-tailored chronic disease screening. Eligible studies were double screened, extracted and synthesised through descriptive statistics and content analysis of themes. Bias was assessed using an existing quality checklist.

RESULTS

Twelve studies were included. Most studies focused on cancer screening (n = 10) and explored preferences for testing of rare, high-risk variants (n = 10), largely within a targeted population (e.g. subgroups with family history of disease). Two studies explored preferences for the use of polygenic risk scores (PRS) at a population level. Twenty-six programme attributes were identified, with most significantly impacting preferences. Survival, test accuracy and screening impact were most frequently reported as most important. Depending on the clinical context and programme attributes and levels, estimated uptake of hypothetical programmes varied from no participation to almost full participation (97%).

CONCLUSION

The uptake of potential programmes would strongly depend on specific programme features and the disease context. In particular, careful communication of potential survival benefits and likely genetic/genomic test accuracy might encourage uptake of genetic and genomic risk-tailored disease screening programmes. As the majority of the literature focused on high-risk variants and cancer screening, further research is required to understand preferences specific to PRS testing at a population level and targeted genomic testing for different disease contexts.

Clinicopathological profile of breast cancer from Chhattisgarh India: A single-center hospital-based study

Background

Global breast cancer incidence is increasing at an annual rate of 3·1%. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%). However, the data from different parts of India are still lacking and the study was conducted to assess the burden of disease at tertiary referral centers in central India.

Material and Methods

Retrospective record analysis (June 2013-June 2017) of data from outdoor clinics and pathology reports. The patients aged <15 yrs, nonresidence of Chhattisgarh, and diagnosed outside the study period were excluded. The triple assessment was used to diagnose all breast lumps (sensitivity 99%).

Results

Eighty patients were diagnosed having breast carcinoma. The mean age for breast cancer was 39 ± 3.028 years (ranged 31-50 years). Twenty patients had locally advanced breast carcinoma. The predominant religion was Hindu 55.00%. The referral pathway to seek medical care for breast cancer was via a gynecologist in 40% (32/80). Familial breast cancers were in 0.03% (3/80) of patients. None breast cancer patients have previous histology-proven benign breast disease. The mean size of the breast cancer lump was 3.56 cm (ranged 1.0-11.0 cm). Overlying skin ulceration (n = 2), skin infiltration/peau-d'- orange (n = 2), skin tethering (n = 4), and bloody nipple discharge were found in one patient. Breast cancer was diagnosed during lactation (postnatal period) in one patient. The maximum number of patients have tumor size >5 cm (72.6%). Immunohistochemistry and pathological analysis was done on core biopsy (n = 20) and surgical procedure (n = 60). Modified radical mastectomy was done in 52, breast conservative surgery with Sentinal Lymph node biopsy and axillary lymph node dissection in 6, and toilet mastectomy in two patients. The predominant tumors were solid (n = 79/80), with both solid and cystic types (1/80). The solid and cystic lesion on FNAC was of C3b type, and an excision biopsy revealed medullary carcinoma of the breast. Invasive ductal carcinoma-no special type (IDC-NST) was observed to be the most common histopathologic type (n = 70/80), followed by medullary carcinoma (n = 2), metaplastic carcinoma (n = 1), papillary carcinoma (n = 4), Paget disease with DCIS (n = 1), mucinous carcinoma (n = 1), invasive lobular carcinoma (n = 1). One male patient with breast cancer and two female patient having bilateral breast cancer also have IDC-NST.Scarff Bloom Richardson Grade was predominantly graded 2 in 46.25% (37/80) of breast cancer patients (Grade 1 = 9, Grade 2 = 37, Grade 3 = 34). Lymphovascular (LVI) and perineural invasion (PNI) were predominantly without LVI and PVI. (Lymphovascular present and perineural invasion present = 4, Lymphovascular present and perineural invasion absent = 32, Lymphovascular absent and perineural invasion absent = 42, Lymphovascular absent and perineural invasion present = 2). Histological examination of axillary lymph nodes showed the presence of malignant cells in all. Triple-negative breast carcinoma was 26.58% (21/79). Most breast cancer presented at stage II A = 37.5% (30/80) and II B = 28.7% (23/80) of the AJCC staging system.

Conclusion

The clinico-epidemio and histological profile of breast cancer in Chhattisgarh is similar to other parts of India. Scarff Bloom Richardson Grade was predominantly grade 2 in 46.25% (37/80) contrary to Grade III (70%) in other series from India.

Impact of a risk based breast screening decision aid on understanding, acceptance and decision making

Internationally, population breast cancer screening is moving towards a risk-stratified approach and requires engagement and acceptance from current and future screening clients. A decision aid ( www.defineau.org ) was developed based on women's views, values, and knowledge regarding risk-stratified breast cancer screening. This study aims to evaluate the impact of the decision aid on women's knowledge, risk perception, acceptance of risk assessment and change of screening frequency, and decision-making. Here we report the results of a pre and post-survey in which women who are clients of BreastScreen Victoria were invited to complete an online questionnaire before and after viewing the decision aid. 3200 potential participants were invited, 242 responded with 127 participants completing both surveys. After reviewing the decision aid there was a significant change in knowledge, acceptance of risk-stratified breast cancer screening and of decreased frequency screening for lower risk. High levels of acceptance of risk stratification, genetic testing and broad support for tailored screening persisted pre and post review. The DEFINE decision aid has a positive impact on acceptance of lower frequency screening, a major barrier to the success of a risk-stratified program and may contribute to facilitating change to the population breast screening program in Australia.

Polygenic risk scores and breast cancer risk prediction

Polygenic Risk Scores (PRS) are a major component of accurate breast cancer risk prediction and have the potential to improve screening and prevention strategies. PRS combine the risk from Single nucleotide polymorphisms (SNPs) associated with breast cancer in Genome Wide Association Studies (GWAS) and explain over 30% of breast cancer heritability. When incorporated into risk models, the more personalised risk assessment derived from PRS, help identify women at higher risk of breast cancer development and enables the implementation of stratified screening and prevention approaches. This review describes the role of PRS in breast cancer risk prediction including the development of PRS and their clinical application. We have also examined the role of PRS within more well-established risk prediction models which incorporate known classic risk factors and discuss the interaction of PRS with these factors and their capacity to predict breast cancer subtypes. Before PRS can be implemented on a population-wide scale, there are several challenges that must be addressed. Perhaps the most pressing of these is the use of PRS in women of non-White European origin, where PRS have been shown to have attenuated risk prediction both in discrimination and calibration. We discuss progress in developing and applying PRS in non-white European populations. PRS represent a significant advance in breast cancer risk prediction and their further development will undoubtedly enhance personalisation.

Breast cancer risk stratification for mammographic screening: A nation-wide screening cohort of 24,431 women in Singapore

Background

Breast cancer incidence is increasing in Asia. However, few women in Singapore attend routine mammography screening. We aim to identify women at high risk of breast cancer who will benefit most from regular screening using the Gail model and information from their first screen (recall status and mammographic density).

Methods

In 24,431 Asian women (50–69 years) who attended screening between 1994 and 1997, 117 developed breast cancer within 5 years of screening. Cox proportional hazard models were used to study the associations between risk classifiers (Gail model 5‐year absolute risk, recall status, mammographic density), and breast cancer occurrence. The efficacy of risk stratification was evaluated by considering sensitivity, specificity, and the proportion of cancers identified.

Results

Adjusting for information from first screen attenuated the hazard ratios (HR) associated with 5‐year absolute risk (continuous, unadjusted HR [95% confidence interval]: 2.3 [1.8–3.1], adjusted HR: 1.9 [1.4–2.6]), but improved the discriminatory ability of the model (unadjusted AUC: 0.615 [0.559–0.670], adjusted AUC: 0.703 [0.653–0.753]). The sensitivity and specificity of the adjusted model were 0.709 and 0.622, respectively. Thirty‐eight percent of all breast cancers were detected in 12% of the study population considered high risk (top five percentile of the Gail model 5‐year absolute risk [absolute risk ≥1.43%], were recalled, and/or mammographic density ≥50%).

Conclusion

The Gail model is able to stratify women based on their individual breast cancer risk in this population. Including information from the first screen can improve prediction in the 5 years after screening. Risk stratification has the potential to pick up more cancers.

Estimating the Breast Cancer Burden in Germany and Implications for Risk-based Screening

In Germany, it is currently recommended that women start mammographic breast cancer screening at age 50. However, recently updated guidelines state that for women younger than 50 and older than 70 years of age, screening decisions should be based on individual risk. International clinical guidelines recommend starting screening when a woman's 5-year risk of breast cancer exceeds 1.7%. We thus compared the performance of the current age-based screening practice with an alternative risk-adapted approach using data from a German population representative survey. We found that 10,498,000 German women ages 50-69 years are eligible for mammographic screening based on age alone. Applying the 5-year risk threshold of 1.7% to individual breast cancer risk estimated from a model that considers a woman's reproductive and personal characteristics, 39,000 German women ages 40-49 years would additionally be eligible. Among those women, the number needed to screen to detect one breast cancer case, NNS, was 282, which was close to the NNS = 292 among all 50- to 69-year-old women. In contrast, NNS = 703 for the 113,000 German women ages 50-69 years old with 5-year breast cancer risk <0.8%, the median 5-year breast cancer risk for German women ages 45-49 years, which we used as a low-risk threshold. For these low-risk women, longer screening intervals might be considered to avoid unnecessary diagnostic procedures. In conclusion, we show that risk-adapted mammographic screening could benefit German women ages 40-49 years who are at elevated breast cancer risk and reduce cost and burden among low-risk women ages 50-69 years. PREVENTION RELEVANCE: We show that a risk-based approach to mammography screening for German women can help detect breast cancer in women ages 40-49 years with increased risk and reduce screening costs and burdens for low-risk women ages 50-69 years. However, before recommending a particular implementation of a risk-based mammographic screening approach, further investigations of models and thresholds used are needed.

Comparison of breast density assessment between human eye and automated software on digital and synthetic mammography: Impact on breast cancer risk

PURPOSE

To evaluate the agreement between automatic assessment software of breast density based on artificial intelligence (AI) and visual assessment by a senior and a junior radiologist, as well as the impact on the assessment of breast cancer risk (BCR) at 5 years.

MATERIALS AND METHODS

We retrospectively included 311 consecutive women (mean age, 55.6±8.5 [SD]; range: 40-74 years) without a personal history of breast cancer who underwent routine mammography between January 1, 2019 and February 28, 2019. Mammographic breast density (MBD) was independently evaluated by a junior and a senior reader on digital mammography (DM) and synthetic mammography (SM) using BI-RADS (5th edition) and by an AI software. For each MBD, BCR at 5 years was estimated per woman by the AI software. Interobserver agreement for MBD between the two readers and the AI software were evaluated by quadratic κ coefficients. Reproducibility of BCR was assessed by intraclass correlation coefficient (ICC).

RESULTS

Agreement for MBD assessment on DM and SM was almost perfect between senior and junior radiologists (κ=0.88 [95% CI: 0.84-0.92] and κ=0.86 [95% CI: 0.82-0.90], respectively) and substantial between the senior radiologist and AI (κ=0.79; 95% CI: 0.73-0.84). There was substantial agreement between DM and SM for the senior radiologist (κ=0.79; 95% CI: 0.74-0.84). BCR evaluation at 5 years was highly reproducible between the two radiologists on DM and SM (ICC=0.98 [95% CI: 0.97-0.98] for both), between BCR evaluation based on DM and SM evaluated by the senior (ICC=0.96; 95% CI: 0.95-0.97) or junior radiologist (ICC=0.97; 95% CI: 0.96-0.98) and between the senior radiologist and AI (ICC=0.96; 95% CI: 0.95-0.97).

CONCLUSION

This preliminary study demonstrates a very good agreement for BCR evaluation based on the evaluation of MBD by a senior radiologist, junior radiologist and AI software.

European polygenic risk score for prediction of breast cancer shows similar performance in Asian women

Polygenic risk scores (PRS) have been shown to predict breast cancer risk in European women, but their utility in Asian women is unclear. Here we evaluate the best performing PRSs for European-ancestry women using data from 17,262 breast cancer cases and 17,695 controls of Asian ancestry from 13 case-control studies, and 10,255 Chinese women from a prospective cohort (413 incident breast cancers). Compared to women in the middle quintile of the risk distribution, women in the highest 1% of PRS distribution have a ~2.7-fold risk and women in the lowest 1% of PRS distribution has ~0.4-fold risk of developing breast cancer. There is no evidence of heterogeneity in PRS performance in Chinese, Malay and Indian women. A PRS developed for European-ancestry women is also predictive of breast cancer risk in Asian women and can help in developing risk-stratified screening programmes in Asia.

Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations

Background

The clinical utility of machine-learning (ML) algorithms for breast cancer risk prediction and screening practices is unknown. We compared classification of lifetime breast cancer risk based on ML and the BOADICEA model. We explored the differences in risk classification and their clinical impact on screening practices.

Methods

We used three different ML algorithms and the BOADICEA model to estimate lifetime breast cancer risk in a sample of 112,587 individuals from 2481 families from the Oncogenetic Unit, Geneva University Hospitals. Performance of algorithms was evaluated using the area under the receiver operating characteristic (AU-ROC) curve. Risk reclassification was compared for 36,146 breast cancer-free women of ages 20–80. The impact on recommendations for mammography surveillance was based on the Swiss Surveillance Protocol.

Results

The predictive accuracy of ML-based algorithms (0.843 ≤ AU-ROC ≤ 0.889) was superior to BOADICEA (AU-ROC = 0.639) and reclassified 35.3% of women in different risk categories. The largest reclassification (20.8%) was observed in women characterised as ‘near population’ risk by BOADICEA. Reclassification had the largest impact on screening practices of women younger than 50.

Conclusion

ML-based reclassification of lifetime breast cancer risk occurred in approximately one in three women. Reclassification is important for younger women because it impacts clinical decision- making for the initiation of screening.

Effect of a Mammography Screening Decision Aid for Women 75 Years and Older: A Cluster Randomized Clinical Trial

IMPORTANCE

Guidelines recommend that women 75 years and older be informed of the benefits and harms of mammography before screening.

OBJECTIVE

To test the effects of receipt of a paper-based mammography screening decision aid (DA) for women 75 years and older on their screening decisions.

DESIGN, SETTING, AND PARTICIPANTS

A cluster randomized clinical trial with clinician as the unit of randomization. All analyses were completed on an intent-to-treat basis. The setting was 11 primary care practices in Massachusetts or North Carolina. Of 1247 eligible women reached, 546 aged 75 to 89 years without breast cancer or dementia who had a mammogram within 24 months but not within 6 months and saw 1 of 137 clinicians (herein referred to as PCPs) from November 3, 2014, to January 26, 2017, participated. A research assistant (RA) administered a previsit questionnaire on each participant's health, breast cancer risk factors, sociodemographic characteristics, and screening intentions. After the visit, the RA administered a postvisit questionnaire on screening intentions and knowledge.

INTERVENTIONS

Receipt of the DA (DA arm) or a home safety (HS) pamphlet (control arm) before a PCP visit.

MAIN OUTCOMES AND MEASURES

Participants were followed up for 18 months for receipt of mammography screening (primary outcome). To examine the effects of the DA, marginal logistic regression models were fit using generalized estimating equations to allow for clustering by PCP. Adjusted probabilities and risk differences were estimated to account for clustering by PCP.

RESULTS

Of 546 women in the study, 283 (51.8%) received the DA. Patients in each arm were well matched; their mean (SD) age was 79.8 (3.7) years, 428 (78.4%) were non-Hispanic white, 321 (of 543 [59.1%]) had completed college, and 192 (35.2%) had less than a 10-year life expectancy. After 18 months, 9.1% (95% CI, 1.2%-16.9%) fewer women in the DA arm than in the control arm had undergone mammography screening (51.3% vs 60.4%; adjusted risk ratio, 0.84; 95% CI, 0.75-0.95; P = .006). Women in the DA arm were more likely than those in the control arm to rate their screening intentions lower from previsit to postvisit (69 of 283 [adjusted %, 24.5%] vs 47 of 263 [adjusted %, 15.3%]), to be more knowledgeable about the benefits and harms of screening (86 [adjusted %, 25.5%] vs 32 [adjusted %, 11.7%]), and to have a documented discussion about mammography with their PCP (146 [adjusted %, 47.4%] vs 111 [adjusted %, 38.9%]). Almost all women in the DA arm (94.9%) would recommend the DA.

CONCLUSIONS AND RELEVANCE

Providing women 75 years and older with a mammography screening DA before a PCP visit helps them make more informed screening decisions and leads to fewer women choosing to be screened, suggesting that the DA may help reduce overscreening.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT02198690.