Postmenopausal overweight and breast cancer risk; results from the KARMA cohort

Mammographic features differ with body composition in women with breast cancer

OBJECTIVES

There are several breast cancer (BC) risk factors-many related to body composition, hormonal status, and fertility patterns. However, it is not known if risk factors in healthy women are associated with specific mammographic features at the time of BC diagnosis. Our aim was to assess the potential association between pre-diagnostic body composition and mammographic features in the diagnostic BC image.

MATERIALS AND METHODS

The prospective Malmö Diet and Cancer Study includes women with invasive BC from 1991 to 2014 (n = 1116). BC risk factors at baseline were registered (anthropometric measures, menopausal status, and parity) along with mammography data from BC diagnosis (breast density, mammographic tumor appearance, and mode of detection). We investigated associations between anthropometric measures and mammographic features via logistic regression analyses, yielding odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

There was an association between high body mass index (BMI) (≥ 30) at baseline and spiculated tumor appearance (OR 1.370 (95% CI: 0.941-2.010)), primarily in women with clinically detected cancers (OR 2.240 (95% CI: 1.280-3.940)), and in postmenopausal women (OR 1.580 (95% CI: 1.030-2.440)). Furthermore, an inverse association between high BMI (≥ 30) and high breast density (OR 0.270 (95% CI: 0.166-0.438)) was found.

CONCLUSION

This study demonstrated an association between obesity and a spiculated mass on mammography-especially in women with clinically detected cancers and in postmenopausal women. These findings offer insights on the relationship between risk factors in healthy women and related mammographic features in subsequent BC.

CLINICAL RELEVANCE STATEMENT

With increasing numbers of both BC incidence and women with obesity, it is important to highlight mammographic findings in women with an unhealthy weight.

KEY POINTS

Women with obesity and BC may present with certain mammographic features. Spiculated masses were more common in women with obesity, especially postmenopausal women, and those with clinically detected BCs. Insights on the relationship between obesity and related mammographic features will aid mammographic interpretation.

The unique risk factor profile of triple-negative breast cancer: a comprehensive meta-analysis

BACKGROUND

Triple-negative breast cancer (TNBC) has a poor prognosis compared with other breast cancer subtypes. This systematic review and meta-analysis examines whether known risk factors for breast cancer are also associated with TNBC in adult women.

METHODS

EMBASE, Medline, SCOPUS, and gray literature were queried with no limit on the date or language of publication. The exposures of interest included parity, breastfeeding, duration of breastfeeding, age at menarche, age at first live birth, oral contraceptive (OC) use, duration of OC use, use of menopausal hormone therapy (MHT), family history, body mass index (BMI), alcohol use, smoking, and breast density. The main outcome of interest was TNBC. Study quality was determined using the Newcastle-Ottawa scale for case control studies and cohort studies. We estimated weighted odds ratios from random effects models to study the exposure-outcome associations. Protocol was registered under the number: PROSPERO 2021 CRD42021254594.

RESULTS

Thirty-three studies were included. Family history, longer duration of OC use, and higher breast density were significantly associated with increased risk for TNBC, whereas later age at menarche, later age at first birth, and breastfeeding were protective against TNBC. Parity, MHT, alcohol, smoking, and BMI were not significantly associated with TNBC overall, but higher parity was associated with higher risk among Black women.

CONCLUSION

Our findings highlight that TNBC has a distinct risk factor profile compared with overall breast cancer. This can be the foundational work in identification of actionable TNBC risk factors to improve prevention and early detection of these poor prognosis breast tumors.

The 100 top-cited articles in menopausal syndrome: a bibliometric analysis

BACKGROUND

Significant scientific research has been conducted concerning menopausal syndrome(MPS), yet few bibliometric analyses have been performed. Our aim was to recognise the 100 most highly cited published articles on MPS and to analytically evaluate their key features.

METHODS

To identify the 100 most frequently cited articles, a search was conducted on Web of Science using the term 'menopausal syndrome'. Articles that matched the predetermined criteria were scrutinised to obtain the following data: citation ranking, year of publication, publishing journal, journal impact factor, country of origin, academic institution, authors, study type, and keywords.

RESULTS

The publication period is from January 1, 2000, to August 31, 2022. The maximum number of citations was 406 and in 2012. The median citations per year was 39.70. Most of the articles focused on treatment and complications. These articles were published in 36 different journals, with the Journal of MENOPAUSE having published the greatest number (14%). Forty-eight articles (48%) were from the United States, with the University of Pittsburgh being the leading institute (9%). Joann E. Manson was the most frequent first author (n = 6). Observational studies were the most frequently conducted research type (n = 53), followed by experimental studies (n = 33). Keyword analysis identified classic research topics, including genitourinary syndrome of menopause, bone mineral density (BMD), and anti-mullerian hormone (AMH) loci.

CONCLUSION

Using bibliometrics, we conducted an analysis to identify the inadequacies, traditional focal points, and potential prospects in the study of MPS across current scientific areas. Treatment and complications are at the core of MPS research, whereas prediction and biomarkers have less literature of high quality. There is a necessity for innovative analytical metrics to measure the real effect of these papers with a high level of citation on clinical application.

Role of body mass index and weight change in the risk of cancer: A systematic review and meta-analysis of 66 cohort studies

Background

This study was designed to evaluate the effects of body mass index (BMI) and weight change on the risk of developing cancer overall and cancer at different sites.

Methods

We searched PubMed and other databases up to July 2023 using the keywords related to 'risk', 'cancer', 'weight', 'overweight', and 'obesity'. We identified eligible studies, and the inclusion criteria encompassed cohort studies in English that focused on cancer diagnosis and included BMI or weight change as an exposure factor. Multiple authors performed data extraction and quality assessment, and statistical analyses were carried out using RevMan and R software. We used random- or fixed-effects models to calculate the pooled relative risk (RR) or hazard ratio along with 95% confidence intervals (CIs). We used the Newcastle-Ottawa Scale to assess study quality.

Results

Analysis included 66 cohort studies. Compared to underweight or normal weight, overweight or obesity was associated with an increased risk of endometrial cancer, kidney cancer, and liver cancer but a decreased risk of prostate cancer and lung cancer. Being underweight was associated with an increased risk of gastric cancer and lung cancer but not that of postmenopausal breast cancer or female reproductive cancer. In addition, weight loss of more than five kg was protective against overall cancer risk.

Conclusions

Overweight and obesity increase the risk of most cancers, and weight loss of >5 kg reduces overall cancer risk. These findings provide insights for cancer prevention and help to elucidate the mechanisms underlying cancer development.

Registration

Reviewregistry1786.

Interaction between body mass index and family history of cancer on the risk of female breast cancer

Both body mass index (BMI) and family history of cancer are established risk factors for female breast cancer. However, few studies explored the potential interaction between both factors. We assessed the association of BMI and its interaction with family cancer history on the risk of female breast cancer in Shanghai, China. Based on a population-based prospective cohort study started from 2008 to 2012 with 15,055 Chinese female participants in Minhang district, Shanghai. Cox regression models were used to estimate the association of BMI and its interaction with a family history of cancer on breast cancer risk. The additive interaction was evaluated by the relative excess risk due to interaction (RERI) and the attributable proportion due to interaction (AP), and the multiplicative interaction was assessed by the product term (BMI* family history of cancer) in the Cox regression model. Compared with BMI of < 24 kg/m2 and no family history of cancer, women with BMI of ≥ 24 kg/m2 and a family history of cancer had a higher risk for breast cancer with HR 2.06 (95% CI 1.39, 3.06). There was an additive interaction between BMI and family history of cancer on breast cancer incidence, with the RERI being 0.29 (95% CI 0.08, 0.51) and the AP being 0.37 (95% CI 0.08, 0.66). The coexistence of obesity and cancer family history may exacerbate breast cancer incidence risk, highlighting the importance of weight management in women with a family history of cancer.

Trajectories of body mass index in adulthood and risk of subtypes of postmenopausal breast cancer

BACKGROUND

Body fatness is a dynamic exposure throughout life. To provide more insight into the association between body mass index (BMI) and postmenopausal breast cancer, we aimed to examine the age at onset, duration, intensity, and trajectories of body fatness in adulthood in relation to risk of breast cancer subtypes.

METHODS

Based on self-reported anthropometry in the prospective Norwegian Women and Cancer Study, we calculated the age at onset, duration, and intensity of overweight and obesity using linear mixed-effects models. BMI trajectories in adulthood were modeled using group-based trajectory modeling. We used Cox proportional hazards models to calculate hazard ratios (HRs) with 95% confidence intervals (CIs) for the associations between BMI exposures and breast cancer subtypes in 148,866 postmenopausal women.

RESULTS

A total of 7223 incident invasive postmenopausal breast cancer cases occurred during follow-up. Increased overweight duration and age at the onset of overweight or obesity were associated with luminal A-like breast cancer. Significant heterogeneity was observed in the association between age at overweight and overweight duration and the intrinsic-like subtypes (pheterogeneity 0.03). Compared with women who remained at normal weight throughout adulthood, women with a descending BMI trajectory had a reduced risk of luminal A-like breast cancer (HR 0.54, 95% CI 0.33-0.90), whereas women with ascending BMI trajectories were at increased risk (HR 1.09; 95% CI 1.01-1.17 for "Normal-overweight"; HR 1.20; 95% CI 1.07-1.33 for "Normal-obesity"). Overweight duration and weighted cumulative years of overweight and obesity were inversely associated with luminal B-like breast cancer.

CONCLUSIONS

In this exploratory analysis, decreasing body fatness from obesity in adulthood was inversely associated with overall, hormone receptor-positive and luminal A-like breast cancer in postmenopausal women. This study highlights the potential health benefits of reducing weight in adulthood and the health risks associated with increasing weight throughout adult life. Moreover, our data provide evidence of intrinsic-like tumor heterogeneity with regard to age at onset and duration of overweight.

Application of SHAP for Explainable Machine Learning on Age-Based Subgrouping Mammography Questionnaire Data for Positive Mammography Prediction and Risk Factor Identification

Mammography is considered the gold standard for breast cancer screening. Multiple risk factors that affect breast cancer development have been identified; however, there is an ongoing debate regarding the significance of these factors. Machine learning (ML) models and Shapley Additive Explanation (SHAP) methodology can rank risk factors and provide explanatory model results. This study used ML algorithms with SHAP to analyze the risk factors between two different age groups and evaluate the impact of each factor in predicting positive mammography. The ML model was built using data from the risk factor questionnaires of women participating in a breast cancer screening program from 2017 to 2021. Three ML models, least absolute shrinkage and selection operator (lasso) logistic regression, extreme gradient boosting (XGBoost), and random forest (RF), were applied. RF generated the best performance. The SHAP values were then applied to the RF model for further analysis. The model identified age at menarche, education level, parity, breast self-examination, and BMI as the top five significant risk factors affecting mammography outcomes. The differences between age groups ranked by reproductive lifespan and BMI were higher in the younger and older age groups, respectively. The use of SHAP frameworks allows us to understand the relationships between risk factors and generate individualized risk factor rankings. This study provides avenues for further research and individualized medicine.

Oncoplastic and reconstructive breast surgery

This article provides an overview of the principles and techniques of oncoplastic and reconstructive breast surgery for patients with early-stage breast cancer. Oncoplastic breast surgery (OPBS) with partial breast reconstruction is a natural evolution in the application of breast conserving surgery and permits wide surgical resection of tumours that might otherwise mandate mastectomy and whole breast reconstruction. These reconstructive techniques must be optimally selected and integrated with ablative breast surgery together with non-surgical treatments such as radiotherapy and chemotherapy that may be variably sequenced with each other. A multidisciplinary approach with shared decision-making is essential to ensure optimal clinical and patient-reported outcomes that address oncological, aesthetic, functional and psychosocial domains. Future practice of OPBS must incorporate routine audit and comprehensive evaluation of outcomes.

Impact of body mass index in therapeutic response for HER2 positive breast cancer treated with neoadjuvant targeted therapy: a multi-center study and meta-analysis

While overweight/obesity has become a major public health issue worldwide, any association between body mass index (BMI) and therapeutic response in neoadjuvant targeted therapy treated HER2 positive breast cancer patients remain unclear. The information from a total of four-hundred and ninety-one neoadjuvant targeted therapy treated HER2 positive breast cancer patients from four institutions were retrospectively collected. Univariate and multivariate logistic analysis was developed to determine the association between BMI and therapeutic response. A meta-analysis of published literature was then conducted to confirm the effect of overweight/obesity on pCR for patients treated with neoadjuvant targeted therapy. Restricted cubic spline (RCS) adjusted for confounding factors demonstrated a decrease pCR with increasing BMI (OR = 0.937, P = 0.045). Patients were then categorized into under/normal weight (n = 299) and overweight/obesity (n = 192). Overweight/obese patients were independently associated with a poor therapeutic response. In the subgroup analysis, a significant negative impact of overweight/obesity on pCR can be observed both in single-targeted (OR = 0.556; P = 0.02) and dual-targeted (OR = 0.392; P = 0.021) populations. Six eligible studies involving 984 neoadjuvant targeted therapy treated HER2 positive breast cancer patients were included in the meta-analysis. The meta-analysis also demonstrated that overweight/obesity was significantly associated with a poor response to neoadjuvant anti-HER2 therapy (OR = 0.68; P = 0.007). Our result show that overweight and obese HER2 positive breast cancer patients are less likely to achieve pCR after neoadjuvant targeted therapy.