Breast Cancer in Women Over 65 years- a Review of Screening and Treatment Options

Construction and evaluation of a multifactorial clinical model for discriminating benign and malignant breast tumors using LASSO algorithm based on retrospective cohort study

Breast cancer is one of the malignant tumors that seriously threaten women's health, and early diagnosis and detection of breast cancer are crucial for effective treatment. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is an important diagnostic tool that allows for the dynamic observation of blood flow characteristics of breast tumors, including small lesions within the affected tissue. Currently, it is widely used in clinical practice and has been shown promising prospects. This study included a total of 1,987 patients who underwent breast surgery at Huangpu Branch, Shanghai Ninth People's Hospital, Shanghai Jiaotong University School of Medicine from January 1, 2019 to December 31, 2019. Comprehensive patient information was collected, including ultrasound, mammography findings, physical examination details, age, family history, and pathological diagnoses. The least absolute shrinkage and selection operator (LASSO) algorithm was employed to assign values to the x variables, facilitating the construction and validation of the LASSO model group. Receiver operating characteristic curves were generated using support vector machines to determine the area under the curve (AUC), as well as to assess sensitivity and specificity. There were no statistically significant differences (P>0.05) in average age, body mass index, tumor location, or tumor benignity/malignancy between the training and test sets. The AUC, sensitivity, and specificity of mammography for predicting the benignity or malignancy of breast tumors were 0.83, 86.96%, and 76%, respectively. In comparison, the AUC, sensitivity, and specificity of DCE-MRI for the same predictions were 0.91, 91.3%, and 88%, respectively. The predictive performance of DCE-MRI was significantly higher than that of mammography (P<0.05). In conclusion, both mammography and DCE-MRI demonstrated high AUC, sensitivity, and specificity in predicting the benignity or malignancy of breast tumors. However, DCE-MRI showed superior predictive performance, making it a valuable tool for the early detection of clinical breast cancer with potential for broader clinical application.

Construction of a nomogram risk prediction model for depressive symptoms in elderly breast cancer patients

The primary objective of this study was to identify the factors associated with the development of depressive symptoms in elderly breast cancer (BC) patients and to construct a nomogram model for predicting these symptoms. We recruited 409 patients undergoing BC treatment in the breast departments of two tertiary-level hospitals in Jiangsu Province from November 2023 to April 2024 as our study cohort. Participants were categorized into depressed and non-depressed groups based on their clinical outcomes. Univariate and multivariate logistic regression analyses were employed to identify independent risk factors for depression among BC patients. Multivariate analysis revealed that monthly income, pain score, family support score, and physical activity score significantly influenced the onset of depression in older BC patients (P < 0.05).The risk prediction model, constructed using these identified factors, demonstrated excellent discriminatory power, as evidenced by an area under the ROC curve (AUC) of 0.824. The maximum Youden index was 0.627, with a sensitivity of 90.60%, specificity of 72.10%, and a diagnostic threshold value of 1.501. The results of the Hosmer-Lemeshow goodness-of-fit test (χ² = 3.181, P = 0.923) indicated that the model fit the data well. The calibration curve for the model closely followed the ideal curve, suggesting a strong fit and high predictive accuracy. Our nomogram model exhibited superior predictive performance, enabling healthcare professionals to identify high-risk patients early and implement preventative measures to mitigate the development of depressive symptoms. This study is a cross-sectional study that lacks longitudinal data and has a small sample size. Future research could involve larger samples, multicenter studies, and prospective designs to build better clinical predictive models.

Reducing Barriers and Strategies to Improve Appropriate Screening Mammogram Attendance in Women 75 Years and Older

Although breast cancer death rates have persistently declined over the last 3 decades, older women have not experienced the same degree in mortality reduction as younger women despite having more favorable breast cancer phenotypes. This occurrence can be partially attributed to less robust mammographic screening in older women, the propensity to undertreat with advancing age, and the presence of underlying comorbidities. With recent revisions to breast cancer screening guidelines, there has been a constructive shift toward more agreement in the need for routine mammographic screening to commence at age 40. Unfortunately, this shift in agreement has not occurred for cutoff guidelines, wherein the recommendations are blurred and open to interpretation. With increasing life expectancy and an aging population who is healthier now than any other time in history, it is important to revisit mammographic screening with advanced age and understand why older women who should undergo screening are not being screened as well as offer suggestions on how to improve screening mammogram attendance in this population.

Comprehensive analysis of risk factors for postoperative wound infection following radical mastectomy in breast cancer patients

Surgical site infections (SSIs) following radical mastectomy in breast cancer patients can significantly affect patient recovery and healthcare resources. Identifying and understanding the risk factors for postoperative wound infections (PWIs) are crucial for improving surgical outcomes. This retrospective study was conducted from June 2020 to June 2023, including 23 breast cancer patients who developed PWIs post-radical mastectomy and a control group of 46 patients without such infections. Comprehensive patient data, including variables such as intraoperative blood loss, hospital stay duration, body mass index (BMI), operation time, anaemia, drainage time, diabetes mellitus, cancer stage, white blood cell (WBC) count, serum albumin levels and preoperative neoadjuvant chemotherapy, were meticulously gathered. Statistical analyses, including univariate and multivariate logistic regression, were performed using SPSS software (Version 27.0). The univariate analysis identified several factors significantly associated with an increased risk of PWIs, including preoperative neoadjuvant chemotherapy, low serum albumin levels, advanced cancer stage, diabetes mellitus and reduced WBC count. Multivariate logistic regression highlighted anaemia, prolonged drainage time, diabetes mellitus, advanced cancer stage, reduced WBC count, hypoalbuminemia and preoperative neoadjuvant chemotherapy as significant contributors to the increased risk of PWIs. Anaemia, extended drainage time, diabetes mellitus, advanced cancer stage, low WBC count, hypoalbuminemia and preoperative neoadjuvant chemotherapy are key risk factors for SSIs post-radical mastectomy. Early identification and proactive management of these factors are imperative to reduce the incidence of postoperative infections and enhance recovery outcomes in breast cancer patients.

Construction and Analysis of a Mitochondrial Metabolism-Related Prognostic Model for Breast Cancer to Evaluate Survival and Immunotherapy

As one of the most prevalent malignancies among women, breast cancer (BC) is tightly linked to metabolic dysfunction. However, the correlation between mitochondrial metabolism-related genes (MMRGs) and BC remains unclear. The training and validation datasets for BC were obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases, respectively. MMRG-related data were obtained from the Molecular Signatures Database. A risk score prognostic model incorporating MMRGs was established based on univariate, LASSO, and multivariate Cox regression analyses. Independent factors affecting BC prognosis were identified through regression analysis and presented in a nomogram. Single-sample gene set enrichment analysis was employed to assess the immune levels of high-risk (HR) and low-risk (LR) groups. The sensitivity of BC patients in the two groups to common anti-tumor drugs was evaluated by utilizing the Genomics of Drug Sensitivity in Cancer database. 12 MMRGs significantly associated with survival were selected from 1234 MMRGs. A 12-gene risk score prognostic model was built. In the multivariate regression analysis incorporating classical clinical factors, the MMRG-related risk score remained an independent prognostic factor. As revealed by tumor immune microenvironment analysis, the LR group with higher survival rates had elevated immune levels. The drug sensitivity results unmasked that the LR group demonstrated higher sensitivity to Irinotecan, Nilotinib, and Oxaliplatin, while the HR group demonstrated higher sensitivity to Lapatinib. The development of MMRG characteristics provides a comprehensive understanding of mitochondrial metabolism in BC, aiding in the prediction of prognosis and tumor microenvironment, and offering promising therapeutic choices for BC patients with different MMRG risk scores.

Adjuvant chemotherapy and survival outcomes in older women with HR+/HER2- breast cancer: a propensity score-matched retrospective cohort study using the SEER database

OBJECTIVES

This study aimed to investigate the impact of adjuvant chemotherapy (ACT) on survival outcomes in older women with hormone receptor-positive and human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer (BC).

DESIGN

A retrospective cohort study using data from the Surveillance, Epidemiology, and End Results database, which contains publicly available information from US cancer registries.

SETTING AND PARTICIPANTS

The study included 45 762 older patients with BC aged over 65 years diagnosed between 2010 and 2015.

METHODS

Patients were divided into two groups based on age: 65-79 years and ≥80 years. Propensity score matching (PSM) was employed to balance clinicopathological characteristics between patients who received ACT and those who did not. Data analysis used the χ2 test and Kaplan-Meier method, with a subgroup analysis conducted to identify potential beneficiaries of ACT.

OUTCOME MEASURES

Overall survival (OS) and cancer-specific survival (CSS).

RESULTS

Due to clinicopathological characteristic imbalances between patients with BC aged 65-79 years and those aged ≥80 years, PSM was used to categorise the population into two groups for analysis: the 65-79 years age group (n=38 128) and the ≥80 years age group (n=7634). Among patients aged 65-79 years, Kaplan-Meier analysis post-PSM indicated that ACT was effective in improving OS (p<0.05, HR=0.80, 95% CI 0.73 to 0.88), particularly in those with advanced disease stages, but did not show a significant benefit in CSS (p=0.09, HR=1.13, 95% CI 0.98 to 1.31). Conversely, for patients aged ≥80 years, ACT did not demonstrate any improvement in OS (p=0.79, HR=1.04, 95% CI 0.79 to 1.36) or CSS (p=0.09, HR=1.46, 95% CI 0.69 to 2.26) after matching. Subgroup analysis also revealed no positive impact on OS and CSS.

CONCLUSIONS

Patients with HR+/HER2- BC ≥80 years of age may be considered exempt from ACT because no benefits were found in terms of OS and CSS.

Prevalence and associated factors of chemotherapy-related cognitive impairment in older breast cancer survivors

AIMS

To examine the prevalence and associated factors of chemotherapy-related cognitive impairment (CRCI) in older breast cancer survivors (BCS).

DESIGN

Systematic review.

DATA SOURCES

We searched EMBASE, PubMed, PsychInfo, CINAHL, Cochrance Library, Web of Science, CNKI and SinoMed, without language restrictions, for studies published from the establishment of the database to September 2022.

REVIEW METHODS

Two researchers independently examined the full texts, data extraction and quality assessment, and any discrepancies were resolved through discussion with a third reviewer. Quality of evidence was assessed using the Newcastle-Ottawa Scale and the Agency for Healthcare Research and Quality Scale.

RESULTS

The seven included studies showed that the estimated prevalence of CRCI in older BCS ranged from 18.6% to 27% on objective neuropsychological tests and from 7.6% to 49% on subjective cognitive assessments. The areas most affected were attention, memory, executive functioning and processing speed. CRCI was associated with 10 factors in six categories, including sociodemographic (e.g. age, education level), physiological (e.g. sleep disorders, fatigue and comorbidities), psychological (e.g. anxiety, depression), treatment modalities (e.g. chemotherapy cycles, chemotherapy regimens), genetic (e.g. APOE2, APOE4) and lifestyle factor (e.g. physical inactivity).

CONCLUSION

CRCI is multifactorial and has a relatively high prevalence. However, the results of subjective and objective cognitive examinations were inconsistent, possibly due to variations in tools used to evaluate different definitions of CRCI. Nevertheless, as there are few published studies of older BCS, this conclusion still require verification by well-designed studies in the future.

IMPACT

We found that the prevalence of CRCI in older adults is relatively high and multifactorial, providing evidence for further health care for this population.

NO PATIENT OR PUBLIC CONTRIBUTION

There was no patient or public involvement.

Clinical application of the 21-gene oncotype recurrence score in an older cohort: A single center experience

BACKGROUND

In early luminal breast cancer, the Oncotype DX® Recurrence Score (RS) prognostic and predictive value with regards to chemotherapy (CHT) application benefit has been broadly validated. In older patients its value has not been deeply addressed. This study aimed to evaluate the benefits of RS testing and to look at differences in treatment allocation for these patients when compared with younger ones.

METHODS

We included data from consecutive patients with early luminal HER2-negative breast cancer, treated between 2010 and 2022 at the University Hospital Basel and Cantonal Hospital Baselland, Switzerland. The older cohort included 63 (19%) patients aged ≥70, and the younger cohort 263 (81%) patients aged <70.

RESULTS

Older breast cancer patients had more co-morbidities (N = 36, 57% vs. N = 92, 35%, p = 0.002) and a higher clinical risk status (N = 49, 78% vs. N = 155, 59%; p = 0.01) when compared to younger patients. Histopathologic characteristics were significantly different between the two cohorts. Although older patients had a higher clinical risk status (78% vs. 59%) (p = 0.01), most of them (74%) received no CHT. Specifically, adjuvant CHT was administered less frequently in older than in younger patients (13% vs. 22%; p = 0.01). Moreover, older patients were less likely to complete CHT (>4 cycles: 78% vs. 97%).

CONCLUSION

Breast cancer patients aged ≥70 have higher clinical risk status, more co-morbidities, higher clinical stage (driven by larger tumor size), and more often RS ≥26. However, they receive fewer adjuvant RT and CHT than those aged <70. RS maintains its independent prognostic value in older patients. However, assessing the predictive value of additional CHT benefit remains challenging due to significant differences in CHT administration. Although therapy decision-making in older patients with breast cancer still follows RS-based guidelines, clinical practice indicates an individualized treatment approach.

Toward a Value-Based Therapy Recommendation Model

Patient value is an important factor in clinical decision making, but conventionally, it is not incorporated in the decision processes. Clinical decision making has some clinical guidelines as a reference. There are very few value-based clinical guidelines, but knowledge about how values affect decision making is mentioned in some scattered studies in the literature. We use a literature review method to extract evidence and integrate it as part of the decision-making model. In this paper, a value-based therapy recommendation comprehensive model is proposed. A literature analysis is conducted to collect value-based evidence. The patients' values are defined and classified with fine granularity. Categorized values and candidate therapies are used in combination as filtering keywords to build this literature database. The literature analysis method generates a literature database used as a source of arguments for influencing decision making based on values. Then, a formalism model is put forward to integrate the value-based evidence with clinical evidence, and the literature databases and clinical guidelines are collected and analyzed to populate the evidence repository. During the decision-making processes, the evidence repository is utilized to match patients' clinical information and values. Decision-makers can dynamically adjust the relative importance of the two pieces of evidence to obtain a treatment plan that is more suitable for the patient. A prototype system was implemented using a case study for breast cancer and validated for feasibility and effectiveness through controlled experiments.

Breast cancer screening and diagnosis in older adults women in Brazil: why it is time to reconsider the recommendations

Introduction

Breast cancer screening in women of 70 years of age or older remains controversial due to a lack of studies that include women of this age.

Methods

This ecological study evaluated data from the Brazilian National Health Service (SUS) on breast cancer screening and staging in this age group compared to 50-69-year olds, for Brazil as a whole and for its geographical regions, between 2013 and 2019. A secondary database was obtained from the outpatient data system of the SUS's Informatics Department, the Brazil Oncology Panel, the Brazilian Institute of Geography and Statistics, the Supplementary Health Agency and the Online Mortality Atlas.

Results

There was a marked reduction in screening in women ≥70 years of age (annual percent change [APC] -3.5; p < 0.001) compared to those of 50-69 years of age (APC-2.2; p = 0.010). There was a trend towards an increase in clinical staging, with a greater occurrence of stages III and IV in the ≥70 group (44.3%) compared to the women of 50-69 years of age (40.8%; p < 0.001).

Conclusion

Considering the increasing age of the Brazilian population and the heterogeneity among older adults women, screening for the over-70s within the SUS merits greater debate insofar as the implementation of public policies is concerned.

Evaluation of the Dynamics of Breast Cancer Incidence in Kyrgyzstan: Component Analysis

BACKGROUND: In 2020, 19.2 million cases of all types of cancer were registered worldwide, of which 11.7%, that is, 2.3 million, related to breast cancer (BC). The global burden of cancer is increasing worldwide, with the majority of new cancer cases and related deaths occurring in low- and middle-income countries. OBJECTIVE: The study is to conduct a component analysis of the dynamics of the incidence of BC in Kyrgyzstan. METHODS: Primary data were for registered patients with BC (International Classification of Diseases – C50) in the whole country during the period of 2003–2017. Evaluation of changes in BC incidence in the population of Kyrgyzstan was performed using component analysis according to the methodological recommendations. RESULTS: The study period, 7850 new cases of BC were recorded. The incidence rate increased from 17.70°/0000 (2003) to 19.03°/0000 in 2017 and the overall growth was 1.34°/0000, including due to the age structure – ΣΔA=2.08°/0000, due to the risk of acquiring illness – ΣΔR=−0.55°/0000 and their combined effect – ΣΔRA=−0.19°/0000. The component analysis revealed that the increase in the number of patients with BC was mainly due to the growth of the population (ΔP=+71.8%), changes in its age structure (ΔA=+35.5%), and changes associated with the risk of acquiring illness (ΔR=+8.4%). The increase and, in some cases, the decrease in the number of patients in the regions of the republic is due to the influence of demographic factors and risk factors for getting sick. CONCLUSION: The component analysis assessed the role of the influence of demographic factors and the risk of acquiring the disease on the formation of the number of patients and the incidence of BC, while geographical variability was established. The implementation of the results of this study is recommended in the management of anticancer measures for BC.