Interval cancers following breast cancer screening in Singaporean women

Retrospective radiological review and classification of interval breast cancers within population-based breast screening programmes for the purposes of open disclosure: A systematic review

INTRODUCTION

Interval breast cancers occur following a negative breast screening mammogram and before the next scheduled appointment within screening programmes. Radiological review classifies them as cancers that develop between screens, cancers with no obvious malignant abnormalities on prior screens or cancers not detected at screening. This study aimed to systematically review published literature on the occurrence of open disclosure following interval cancer radiological reviews by breast screening programmes internationally in a retrospective setting and examine methodologies used for radiological reviews for the purposes of disclosure.

METHODS

A search for relevant articles published (January 2000 - May 2019) was conducted according to PICO and PRISMA guidelines. The databases Pubmed, Scopus, Google Scholar, Cinahl, Web of Science, Embase, Science Direct and Global Health were searched. Relevant studies were reviewed if they had completed a retrospective review and classification of interval breast cancers.

RESULTS

Of 46 relevant articles included, no study was identified that conducted a retrospective review purposely for open disclosure. Retrospective reviews were conducted for audit/quality assurance, and research including for radiologist education and learning. Variation in methodology was found across review type (non-blinded/semi-informed approach), number of reviewers and classification categories. The proportion of false negative cancers classified among the studies ranged from 4 to 40 %.

DISCUSSION

Variation among radiological review practices were observed, which likely impacts classification results. To ensure standardised classification of interval breast cancers are employed for the purposes of open disclosure in screening settings, reproducible and consistent methodology is required.

Deep-Learning-Based Computer-Aided Systems for Breast Cancer Imaging: A Critical Review

This paper provides a critical review of the literature on deep learning applications in breast tumor diagnosis using ultrasound and mammography images. It also summarizes recent advances in computer-aided diagnosis/detection (CAD) systems, which make use of new deep learning methods to automatically recognize breast images and improve the accuracy of diagnoses made by radiologists. This review is based upon published literature in the past decade (January 2010–January 2020), where we obtained around 250 research articles, and after an eligibility process, 59 articles were presented in more detail. The main findings in the classification process revealed that new DL-CAD methods are useful and effective screening tools for breast cancer, thus reducing the need for manual feature extraction. The breast tumor research community can utilize this survey as a basis for their current and future studies.

Long-term excess risk of breast cancer after a single breast density measurement

AIM

Breast density is a risk factor for breast cancer. As density changes across a woman's life span, we studied for how long a single density measurement taken in (post-)menopausal women remains informative.

METHODS

We used data from Singaporean women who underwent a single mammography screen at age 50-64 years. For each case with breast cancer diagnosed at screening or in the subsequent 10 years, whether screen detected or diagnosed following symptoms, two age-matched controls were selected. We studied the excess risk of breast cancer, calculated as an odds ratio (OR) with conditional logistic regression and adjusted for body mass index, associated with 26-50% and with 51-100% density compared with ≤25% density by time since screening.

RESULTS

In total, 490 women had breast cancer, of which 361 were diagnosed because of symptoms after screening. Women with 51-100% breast density had an excess risk of breast cancer that did not seem to attenuate with time. In 1-3 years after screening, the OR was 2.22 (95% confidence interval [CI]: 1.07-4.61); in 4-6 years after screening, the OR was 4.09 (95% CI: 2.21-7.58), and in 7-10 years after screening, the OR was 5.35 (95% CI: 2.57-11.15). Excess risk with a stable OR of about 2 was also observed for women with 26-50% breast density. These patterns were robust when the analyses were limited to post-menopausal women, non-users of hormonal replacement therapy and after stratification by age at density measurement.

CONCLUSION

A single breast density measurement identifies women with an excess risk of breast cancer during at least the subsequent 10 years.

The epidemiology, radiology and biological characteristics of interval breast cancers in population mammography screening

An interval breast cancer is a cancer that emerges following a negative mammographic screen. This overview describes the epidemiology, and the radiological and biological characteristics of interval breast cancers in population mammography screening. Notwithstanding possible differences in ascertainment of interval breast cancers, there was broad variability in reported interval breast cancer rates (range 7.0 to 49.3 per 10,000 screens) reflecting heterogeneity in underlying breast cancer rates, screening rounds (initial or repeat screens), and the length and phase of the inter-screening interval. The majority of studies (based on biennial screening) reported interval breast cancer rates in the range of 8.4 to 21.1 per 10,000 screens spanning the two-year interval with the larger proportion occurring in the second year. Despite methodological limitations inherent in radiological surveillance (retrospective mammographic review) of interval breast cancers, this form of surveillance consistently reveals that the majority of interval cancers represent either true interval or occult cancers that were not visible on the index mammographic screen; approximately 20–25% of interval breast cancers are classified as having been missed (false-negatives). The biological characteristics of interval breast cancers show that they have relatively worse tumour prognostic characteristics and biomarker profile, and also survival outcomes, than screen-detected breast cancers; however, they have similar characteristics and prognosis as breast cancers occurring in non-screened women. There was limited evidence on the effect on interval breast cancer frequency and outcomes following transition from film to digital mammography screening.

The influence of disease risk on the optimal time interval between screens for the early detection of cancer: a mathematical approach

The intervals between screens for the early detection of diseases such as breast and colon cancer suggested by screening guidelines are typically based on the average population risk of disease. With the emergence of ever more biomarkers for cancer risk prediction and the development of personalized medicine, there is a need for risk-specific screening intervals. The interval between successive screens should be shorter with increasing cancer risk. A risk-dependent optimal interval is ideally derived from a cost-effectiveness analysis using a validated simulation model. However, this is time-consuming and costly. We propose a simplified mathematical approach for the exploratory analysis of the implications of risk level on optimal screening interval. We develop a mathematical model of the optimal screening interval for breast cancer screening. We verified the results by programming the simplified model in the MISCAN-Breast microsimulation model and comparing the results. We validated the results by comparing them with the results of a full, published MISCAN-Breast cost-effectiveness model for a number of different risk levels. The results of both the verification and validation were satisfactory. We conclude that the mathematical approach can indicate the impact of disease risk on the optimal screening interval.

Assessing risk of breast cancer in an ethnically South-East Asia population (results of a multiple ethnic groups study)

BACKGROUND

Gail and others developed a model (GAIL) using age-at-menarche, age-at-birth of first live child, number of previous benign breast biopsy examinations, and number of first-degree-relatives with breast cancer as well as baseline age-specific breast cancer risks for predicting the 5-year risk of invasive breast cancer for Caucasian women. However, the validity of the model for projecting risk in South-East Asian women is uncertain. We evaluated GAIL and attempted to improve its performance for Singapore women of Chinese, Malay and Indian origins.

METHODS

Data from the Singapore Breast Screening Programme (SBSP) are used. Motivated by lower breast cancer incidence in many Asian countries, we utilised race-specific invasive breast cancer and other cause mortality rates for Singapore women to produce GAIL-SBSP. By using risk factor information from a nested case-control study within SBSP, alternative models incorporating fewer then additional risk factors were determined. Their accuracy was assessed by comparing the expected cases (E) with the observed (O) by the ratio (E/O) and 95% confidence interval (CI) and the respective concordance statistics estimated.

RESULTS

From 28,883 women, GAIL-SBSP predicted 241.83 cases during the 5-year follow-up while 241 were reported (E/O=1.00, CI=0.88 to 1.14). Except for women who had two or more first-degree-relatives with breast cancer, satisfactory prediction was present in almost all risk categories. This agreement was reflected in Chinese and Malay, but not in Indian women. We also found that a simplified model (S-GAIL-SBSP) including only age-at-menarche, age-at-birth of first live child and number of first-degree-relatives performed similarly with associated concordance statistics of 0.5997. Taking account of body mass index and parity did not improve the calibration of S-GAIL-SBSP.

CONCLUSIONS

GAIL can be refined by using national race-specific invasive breast cancer rates and mortality rates for causes other than breast cancer. A revised model containing only three variables (S-GAIL-SBSP) provides a simpler approach for projecting absolute risk of invasive breast cancer in South-East Asia women. Nevertheless its role in counseling the individual women regarding their risk of breast cancer remains problematical and needs to be validated in independent data.

Cytology is useful in breast screening: results and long-term follow-up of the Singapore Breast Screening Pilot Project

OBJECTIVE

The Singapore Breast Screening Pilot Project (SBSPP) was embarked upon (1994-1997) to determine if mammography was useful in early breast cancer detection among Asian women.

PATIENTS AND MEASUREMENTS

Of 28 231 women screened, fine needle aspiration cytology (FNAC) was performed in 232 individuals as part of the triple assessment.

RESULTS

Absolute and complete sensitivities for the diagnosis of carcinoma were 46.7% and 82.2%, respectively, based on the results of FNAC. Specificity was 63.3%. The inadequate rate was 31%. Five women who were considered cancer-free on triple assessment and, in two cases open diagnostic biopsy during the SBSPP, subsequently developed breast cancer after a median follow-up of 6 years.

CONCLUSION

Although our FNAC results compared relatively well with international standards, they reflect a small cohort, and may face additional difficulties in a larger programme.