BACKGROUND

The survival advantage of HER2-positive breast cancer from targeted treatment is commonly undermined by catastrophic health expenditure (CHE), particularly in resource-limited areas. Recognizing that financial catastrophe leads to non-adherence to treatment and dissaving practices, we examined the out-of-pocket (OOP) expenses of patients with HER2-positive breast cancer.

The study aimed to estimate the median total per-cycle out-of-pocket expenditure of HER2-positive breast cancer treatment from the patient perspective, in public and private clinics, evaluate the association of catastrophic health expenditure with non-adherence to treatment, and describe dissaving practices.

This was a cross-sectional micro-costing analysis of the treatment of HER2-positive breast cancer from the patient perspective from a tertiary cancer center and select private clinics in the Philippines. Random sampling of patients with HER2-positive breast cancer was done. Using a validated questionnaire, a guided interview was administered. Catastrophic health expenditure was estimated as having OOP of >20% of the household income. OOP costs were assessed retrospectively from the time of confirmed HER2 diagnosis up to the date of survey, while household income referred to the corresponding period. The proportion of patients experiencing catastrophic health expenditure was computed. Fisher's exact was used to assess for any association between CHE and non-adherence to treatment. Descriptive statistics were used to report dissaving practices. All statistical analyses were performed using Stata analytical software version 12.

A total of 101 patients participated in the study. The mean age of participants from the tertiary cancer center and private clinics were 52 and 58 years old respectively. Patients from the private clinics had a median total OOP expenditure of PhP 54,737.06 (IQR = PhP 102,670.00), compared with patients from tertiary cancer center who had a median total OOP expenditure of PhP 13,920.66 (IQR = PhP 20,830.00). The overall prevalence of CHE (90.9%, 95% CI 0.81, 0.95) and nonadherence to treatment with trastuzumab (79%, 95% CI 0.70, 0.87) were high, and similar in both groups. A number of dissaving practices such as resignation from work, borrowing money from friends, selling assets were observed.

The high rate of CHE and treatment delay among patients with HER2-positive breast cancer were not addressed by the existing cancer programs. Most OOP expenditure was for trastuzumab. Current cancer support programs have potential to address the financial impact of their treatment.

Adenoid cystic carcinoma (ACC) is a rare subtype of invasive breast cancer, occurring in <0.1% of all malignant breast tumors. Though majority are triple-negative, ACC of the breast has good prognosis with a low incidence of regional and distant metastases.

A 45-year-old premenopausal female presented with a 5-month history of a gradually enlarging mass on her left breast. After core needle biopsy and subsequent metastatic work-up, she underwent total mastectomy with sentinel lymph node biopsy. Final histopathology showed adenoid cystic carcinoma, 2.1 cm in size and no lymph nodes positive for tumor. She has completed adjuvant radiotherapy of 50 Gy to the chestwall, and is currently well after 6 years of follow-up.

Surgery with either lumpectomy or mastectomy has been established as the mainstay of treatment of adenoid cystic carcinoma of the breast, but the use of adjuvant radiotherapy (RT) and chemotherapy has not been established. While adjuvant RT has been shown to improve cause-specific and overall survival following breast-conserving surgery, its indications after a mastectomy are not as well-defined. The decision to administer adjuvant RT was based on the current evidence indicating the advantages of adjuvant treatment for breast carcinomas, lack of survival difference between invasive ductal carcinomas and adenoid cystic carcinomas, indications for post-mastectomy RT in a retrospective Rare Cancer Network study, and reported incidences of local recurrences following mastectomy alone: 21.4% and 22.2%.

Our patient with adenoid cystic carcinoma of the breast, treated with surgery and adjuvant radiation therapy, showed favorable outcomes after 6 years.

BACKGROUND

Breast cancer remains a leading malignancy among women globally. In addition to established factors like histopathology, hormone receptor status, and lymph node involvement, tools such as immunohistochemistry and molecular tests have been developed to assess tumor behavior and recurrence risk.

This study investigates the concordance between the Ki-67 proliferation index measured by immunohistochemistry and the recurrence risk scores obtained from molecular genomic testing in patients with invasive breast cancer.

This cross-sectional study included patients with invasive breast carcinoma at St. Luke’s Medical Center from 2019 to 2024, who underwent biopsy or mastectomy, with hormone status and Ki-67 index assessed by immunohistochemistry. All patients also had molecular genomic testing using either MammaPrint or OncotypeDX. Concordance between Ki-67 and the genomic recurrence risk score was evaluated using Kappa statistics, and results were further analyzed according to clinical risk and hormone receptor status.

Fifty-eight (58) patients met the study criteria. Most had grade 2, hormone receptor-positive, HER2-negative, and node-negative tumors, with high clinical risk based on Adjuvant! Online criteria (adapted from the MINDACT trial). The agreement between categorical Ki-67 and molecular recurrence risk was only fair: 66.7% for MammaPrint (kappa=0.35) and 60% for OncotypeDX (kappa = 0.29) using a 30% Ki-67 cutoff.

There is a fair agreement between Ki-67 and the molecular genomic tests. These findings are consistent with prior studies reporting weak to moderate association. Despite the limited sample size, Ki-67 remains a practical and accessible risk stratification tool, particularly where genomic assays are unavailable. The study supports integrating Ki-67 with clinicopathologic and genomic data to guide therapy, reflecting current best-practice recommendations.

BACKGROUND AND OBJECTIVE

The burden of treatment delay in breast cancer is high, especially among developing countries. Despite adversely affecting morbidity and mortality, treatment delay remains unexplored in the Philippines. This study aimed to determine treatment delays among breast cancer patients in a tertiary hospital during surgery, neoadjuvant chemotherapy, and adjuvant chemotherapy, and to identify predictors of delay.

A cross-sectional study was conducted among breast cancer patients seen between January 1, 2012 to December 31, 2018. The following outcomes were investigated: ≥90 days from initial diagnosis to surgery, ≥8 weeks from diagnosis to initiation of neoadjuvant chemotherapy, and >120 days from diagnosis to initiation of adjuvant chemotherapy. Summary statistics were reported as percent for categorical data and as mean for continuous data. The individual correlations were performed using Chi-square for qualitative data and t-test for quantitative data while predictors were determined through logistic regression.

A total of 324 patients were included in this study. The majority of the patients were less than 65 years old living in urban areas. More than half of the patients were overweight or obese, hypertensive, and diabetic. The following delays were observed: 61.1% (n = 198) with any type of delay, 23.8% (n = 53) with delay in surgery, 53.8% (n = 120) with delay in adjuvant chemotherapy, and 74.3% (n = 75) with delay in neoadjuvant chemotherapy. The patients noted to have any type of delay were more likely to be hypertensive (p = 0.046) and residing in urban areas (p = 0.041). There were no differences in the distribution of age, body mass index, and presence of co-morbid conditions such as hypertension, diabetes mellitus, coronary artery disease, and heart failure among those with any form of delay compared with no delay.

The present study shows the presence of treatment delay among breast cancer patients and may be used to enact policy changes to optimize breast cancer care delivery. Further studies may be done to identify other factors affecting these delays and policy changes are recommended to address these gaps in surgery and chemotherapy administration among breast cancer patients.

The accurate segmentation of breast ultrasound images is an important precondition for the lesion determination. The existing segmentation approaches embrace massive parameters, sluggish inference speed, and huge memory consumption. To tackle this problem, we propose T ²KD Attention U-Net (dual-Teacher Knowledge Distillation Attention U-Net), a lightweight semantic segmentation method combined double-path joint distillation in breast ultrasound images. Primarily, we designed two teacher models to learn the fine-grained features from each class of images according to different feature representation and semantic information of benign and malignant breast lesions. Then we leveraged the joint distillation to train a lightweight student model. Finally, we constructed a novel weight balance loss to focus on the semantic feature of small objection, solving the unbalance problem of tumor and background. Specifically, the extensive experiments conducted on Dataset BUSI and Dataset B demonstrated that the T ²KD Attention U-Net outperformed various knowledge distillation counterparts. Concretely, the accuracy, recall, precision, Dice, and mIoU of proposed method were 95.26%, 86.23%, 85.09%, 83.59%and 77.78% on Dataset BUSI, respectively. And these performance indexes were 97.95%, 92.80%, 88.33%, 88.40% and 82.42% on Dataset B, respectively. Compared with other models, the performance of this model was significantly improved. Meanwhile, compared with the teacher model, the number, size, and complexity of student model were significantly reduced (2.2×10 ⁶ vs. 106.1×10 ⁶, 8.4 MB vs. 414 MB, 16.59 GFLOPs vs. 205.98 GFLOPs, respectively). Indeedy, the proposed model guarantees the performances while greatly decreasing the amount of computation, which provides a new method for the deployment of clinical medical scenarios.
Humans ; Breast Neoplasms/diagnostic imaging* ; Female ; Ultrasonography, Mammary/methods* ; Image Processing, Computer-Assisted/methods* ; Algorithms ; Neural Networks, Computer ; Breast/diagnostic imaging*

With the rising incidence of breast cancer among women, neoadjuvant chemotherapy (NAC) is becoming increasingly crucial as a preoperative treatment modality, enabling tumor downstaging and volume reduction. However, its efficacy varies significantly among patients, underscoring the importance of predicting pathological complete response (pCR) following NAC. Early research relied on statistical methods to integrate clinical data for predicting treatment outcomes. With the advent of artificial intelligence (AI), traditional machine learning approaches were subsequently employed for efficacy prediction. Deep learning emerged to dominate this field, and demonstrated the capability to automatically extract imaging features and integrate multimodal data for pCR prediction. This review comprehensively examined the applications and limitations of these three methodologies in predicting breast cancer pCR. Future efforts must prioritize the development of superior predictive models to achieve precise predictions, integrate them into clinical workflows, enhance patient care, and ultimately improve therapeutic outcomes and quality of life.
Humans ; Breast Neoplasms/pathology* ; Neoadjuvant Therapy ; Artificial Intelligence ; Female ; Machine Learning ; Deep Learning ; Chemotherapy, Adjuvant ; Treatment Outcome

OBJECTIVES

The aim of the study is to estimate the cost of breast cancer diagnosis, treatment, and management in the Philippines. Specifically, it aims to identify the resource requirements and interventions related to breast cancer diagnosis, treatment, and management, measure resource volumes (number of units), learn to value resource items (unit costs), and determine the total cost of treatment per disease stage.

The study covered nine tertiary hospitals, seven of which were government hospitals and two were private hospitals, with all tertiary hospitals providing breast cancer services and accredited by Philippine Health Insurance Corporation (PHIC or PhilHealth) for the Z-Benefit Package. Interventions and services related to breast cancer included radiographic procedures, laboratory and imaging tests, chemotherapy drugs and medications, medical and surgical supplies, surgical rates (for breast surgery), accommodation, staff time and salary/professional fees, and other procedure fees. The study conducted in 2022, examined cost prices of breast cancer interventions and services from stage 1–3B.

Purposive and convenience sampling were used based on PhilHealth accreditation and willingness of hospitals to participate in the study. The study conducted a focus group discussion with oncologists, radiologists, anesthesiologists, and other health care providers to validate the clinical guideline used and to solicit inputs to the costing design, analysis framework, and tools for data collection. Data collection of financial cost information (charge price) was conducted using a set of costing matrices filled out by the various departments of the hospitals. Costs and median rates were calculated across hospitals on diagnostics and imaging tests, surgery costs of both public and private facilities, medical treatment, and radiotherapy.

Breast MRI, Breast Panel, and Chest CT Scan are the top 3 most expensive diagnostic procedures ranging from PhP 8,102.00 to PhP 9,800.00 per procedure. Surgical procedures for breast cancer at private hospitals and public hospitals showed huge differences in costs. The cost of a cycle of chemotherapy ranges from PhP 596.70 to PhP 3,700.00 per session, while the cost of targeted therapy can cost up to PhP 46,394.21 per session. A year of hormone therapy ranges from PhP 3,276.00 with the use of Tamoxifen, and up to PhP 68,284.00 with Goserelin. Aromatase inhibitors such as Anastrozole and Letrozole cost from PhP 18,000 to PhP 36,000, respectively. Multiple cycles depending on the diagnosis are prescribed per patient and used in combination with other chemotherapy medications or other therapies such as targeted therapy and hormone therapy are usually taken daily up to 5 to 10 years. Conventional radiotherapy can cost up to PhP 88,150.00 covering 28 sessions, CT simulation, and CT planning.

This cost study provides relevant information and better perspective on benefit development for the PHIC, policy development for Department of Health on where and how to focus their support for the patient’s financial preparedness to address medical and f inancial catastrophes.

PhilHealth needs to guide the health care providers of their costing method and to develop their own integrated, interoperable, and comprehensive cost data library.

It recommends that the government allocate budget and cover for screening and assessment for earlier stage diagnosis of patients and lower health expenditure costs on cancer treatment.

Amino acid metabolism plays a critical role in the progression and development of breast cancer. Cancer cells, including those in breast cancer, reprogram amino acid metabolism to meet the demands of rapid proliferation, survival, and immune evasion. This includes alterations in the uptake and utilization of amino acids, such as glutamine, serine, glycine, and arginine, which provide essential building blocks for biosynthesis, energy production, and redox homeostasis. Notably, the metabolic phenotypes of breast cancer cells vary across molecular subtypes and disease stages, emphasizing the need for patient stratification and personalized therapeutic strategies. Advances in multi-level diagnostics, including phenotyping and predictive tools, such as AI-based analysis and body fluid profiling, have highlighted the potential for tailoring treatments to individual metabolic profiles. Enzymes, such as glutaminase and serine hydroxymethyltransferase, often upregulated in breast cancer, represent promising therapeutic targets. Understanding the interplay between amino acid metabolism and breast cancer biology, alongside the integration of personalized medicine approaches, can uncover novel insights into tumor progression and guide the development of precision therapies. This review explores the metabolic pathways of amino acids in breast cancer, with a focus on their implications for personalized treatment strategies.
Humans ; Breast Neoplasms/therapy* ; Female ; Amino Acids/metabolism*

The inhibition of cyclin-dependent kinases (CDKs) is considered a promising strategy for cancer treatment due to their role in cell cycle regulation. However, CDK inhibitors with no selectivity among CDK families have not been approved. A CDK inhibitor with high selectivity for CDK4/6 exhibited significant treatment effects on breast cancer and has become a heavy bomb on the market. Subsequently, resistance gradually decreased the efficacy of selective CDK4/6 inhibitors in breast cancer treatment. In this review, we first introduce the development of selective CDK4/6 inhibitors and then explain the role of CDK2 activation in inducing resistance to CDK4/6 inhibitors. Moreover, we focused on the development of CDK2/4/6 inhibitors and selective CDK2 inhibitors, which will aid in the discovery of novel CDK inhibitors targeting the cell cycle in the future.
Humans ; Cell Cycle/drug effects* ; Protein Kinase Inhibitors/chemistry* ; Cyclin-Dependent Kinases/metabolism* ; Neoplasms/genetics* ; Antineoplastic Agents/pharmacology* ; Animals ; Breast Neoplasms/enzymology* ; Cyclin-Dependent Kinase 4/metabolism*

Triple-negative breast cancer (TNBC) represents an aggressive breast cancer subtype with poor prognosis and limited targeted treatment options. This investigation examined the anti-cancer potential of Caerulomycin A (Cae A), a natural compound derived from marine actinomycetes, against TNBC. Cae A demonstrated selective inhibition of viability and proliferation in TNBC cell lines, including 4T1, MDA-MB-231, and MDA-MB-468, through apoptosis induction. Mechanistic analyses revealed that the compound induced sustained endoplasmic reticulum (ER) stress and subsequent upregulation of C/EBP homologous protein (CHOP) expression, resulting in mitochondrial damage-mediated apoptosis. Inhibition of ER stress or CHOP expression knockdown reversed mitochondrial damage and apoptosis, highlighting the essential role of ER stress and CHOP in Cae A's anti-tumor mechanism. Both oxygen consumption rate (OCR) and extracellular acidification rate (ECAR) decreased in TNBC cells following Cae A treatment, indicating reduced mitochondrial respiratory and glycolytic capacities. This diminished energy metabolism potentially triggers ER stress and subsequent apoptosis. Furthermore, Cae A exhibited significant anti-tumor effects in the 4T1 tumor model in vivo without apparent toxicity. The compound also effectively inhibited human TNBC organoid growth. These results indicate that Cae A may serve as a potential therapeutic agent for TNBC, with its efficacy likely mediated through the disruption of glucose metabolism and the induction of ER stress-associated apoptosis.
Humans ; Endoplasmic Reticulum Stress/drug effects* ; Triple Negative Breast Neoplasms/genetics* ; Apoptosis/drug effects* ; Cell Line, Tumor ; Female ; Animals ; Glucose/metabolism* ; Mice ; Cell Proliferation/drug effects* ; Transcription Factor CHOP/genetics* ; Antineoplastic Agents/pharmacology* ; Mitochondria/metabolism* ; Mice, Inbred BALB C