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Breast Neoplasms

Breast Neoplasms: explore 12 source-linked works published from 2026 to 2026, with original documents and citations.

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Sources: pubmed. Collection updated 2026-09-15. Counts describe this index, not the complete source archives.

PubMed2026

PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.

BACKGROUND: The biology of the estrogen receptor-positive (ER+) and human epidermal growth factor receptor 2-negative (HER2-) breast cancers is heterogeneous even when they are categorized by their risk via genomics. Transcriptomic PGR expression reflects endocrine pathway activity and may provide complementary biological information within established GENE70-derived genomic-risk categories. Whether this molecular marker improves the biological interpretation of genomic-risk stratification beyond conventional clinicopathological assessment remains uncertain. OBJECTIVES: The aim of this study was to determine whether transcriptomic PGR expression provides complementary biological and prognostic information within reconstructed GENE70-derived genomic-risk categories and refines the characterization of endocrine-related tumour biology in ER-positive/HER2-negative breast cancer. METHODS: This study analysed publicly available transcriptomic and clinical data from three cohorts: METABRIC (discovery cohort), GSE96058/SCAN-B cohort (validation cohort) and TCGA-BRCA cohort (molecular validation cohort). The GENE70-derived genomic-risk score was reconstructed for each cohort using matched genes. Cox regression, Kaplan-Meier analysis and subgroup comparisons were used to assess relationships between PGR expression, clinicopathologic variables, molecular features and survival outcomes. RESULTS: Across the three independent cohorts, low transcriptomic PGR expression was consistently associated with higher GENE70-derived genomic risk, increased MKI67 expression, reduced ESR1 expression and enrichment of the Luminal B subtype. Survival findings differed between cohorts. In the discovery METABRIC cohort, transcriptomic PGR expression showed heterogeneous associations with survival, particularly within GENE70-derived high-risk subgroups, whereas the external GSE96058/SCAN-B validation cohort demonstrated consistent associations between low PGR expression and poorer overall survival in both the overall ER-positive/HER2-negative population and GENE70-derived high-risk subgroups. CONCLUSION: These findings suggest that transcriptomic PGR provides complementary biological and prognostic information within GENE70-derived genomic-risk categories. However, because treatment response was not evaluated in the present study, the findings should not be interpreted as evidence of predictive or pharmacogenomic utility and prospective studies incorporating treatment-response analyses are required before such applications can be established.

Humans↗

PubMed2026

Safety and efficacy of Meridian sinew tuina (MST) for post-surgical upper limb lymphedema: a systematic review and meta-analysis.

BACKGROUND: Complex Decongestive Therapy (CDT) is the non-operative standard for breast cancer-related lymphedema (BCRL), but many patients experience persistent subcutaneous stiffness, pain, and restricted mobility. This study systematically reviews the safety and clinical efficacy of Meridian Sinew Tuina (MST) protocols for BCRL. METHODS: Global and regional databases (PubMed, Cochrane Library, Embase, Web of Science, CNKI, Wanfang, VIP) were searched from inception to January 15, 2026, with alerts monitored through April 30, 2026. Randomised controlled trials (RCTs) evaluating MST (deep tissue mobilisation along the six-hand meridian sinew [Jingjin] lines via plucking, kneading, and pressing) were included. Two reviewers independently extracted data, evaluated risk of bias using Cochrane RoB 2, and assessed evidence certainty via GRADE using a random-effects model. RESULTS: Fifteen RCTs were included. For the primary anthropometric outcome, MST significantly reduced upper limb circumference compared to controls (SMD = 1.59; 95% CI: 1.44 to 1.74; Z = 20.81; p < 0.0001; I2=0.0%; N = 924; GRADE: Moderate certainty). The Clinical Response Efficacy Rate (≥ 30% swelling reduction and symptom relief) favoured MST (RR = 1.69; 95% CI: 1.54 to 1.87; Z = 10.62; p < 0.0001; I2=0.0%; N = 1,114; GRADE: Moderate certainty). Trial Sequential Analysis confirmed sample size sufficiency. For secondary outcomes (N = 924; GRADE: Low to Very Low certainty due to performance bias and clinical heterogeneity), MST showed favourable 3-month improvements in DASH functional scores (SMD = -1.81; 95% CI: -2.11 to -1.51; I2=45.1%), pain intensity (SMD = -2.44; 95% CI: -2.93 to -1.95; I2=50.4%), and quality of life (SMD = 1.04; 95% CI: 0.79 to 1.29; I2=0.0%). No serious adverse events occurred. CONCLUSIONS: MST protocols are associated with favourable short- and mid-term reductions in upper limb swelling. However, confidence is tempered by unblinded performance bias and control group variations. MST cannot be unconditionally recommended for standalone implementation but represents a promising, optional supportive adjunctive intervention within oncological rehabilitation.

Humans↗

PubMed2026

Effects of erector spinae plane block on postoperative pain in patients undergoing implant-based breast reconstruction for breast cancer: a randomized controlled trial.

BACKGROUND: Implant-based breast reconstruction after mastectomy causes acute pain. OBJECTIVE: To determine whether a single-shot T5 erector spinae plane block (ESPB) reduces postoperative pain. DESIGN: Single-center, RCT with allocation concealment; blinded assessors and statisticians. SETTING: Tertiary cancer center in China. PATIENTS: 100 adults scheduled for radical mastectomy with implant reconstruction were randomized (1:1); follow-up complete. INTERVENTION: Before induction, ESPB was given under ultrasound guidance at T5 with 30 mL of 0.375% ropivacaine plus dexmedetomidine 1 μg/kg; controls received no block. Standardized general anesthesia and postoperative PCA for both groups. MAIN OUTCOME MEASURES: Resting NRS at 6 h (MCID=1). Secondary outcomes were opioid consumption, quality of recovery, and PONV. RESULTS: ESPB did not significantly reduce resting pain at 6 h at the median (τ =0.50; adjusted difference -0.9; p = 0.08). At the upper tail, pain intensity was lower (τ = 0.75; -1.8; p <0.01). Repeated measures provided additional time-point information, improving estimation precision and test sensitivity. ESPB get lower pain scores at 6, 12, and 24 hours (all p <0.01). But, the 95% CI includes the MCID, the clinical benefit remains uncertain. Opioid use decreased at 24 h (-13.5 mg; p <0.01) and 48 h (-6.6 mg; p <0.01). Quality of recovery improved at 24 h (difference 5 points; p <0.01), but not later. No differences were observed in intraoperative hemodynamics or PONV. CONCLUSIONS: Single-shot T5 ESPB with perineural dexmedetomidine may reduce postoperative pain and opioid requirements and improve early recovery. Further large trials are warranted. Clinical relevance remains to be confirmed. TRIAL REGISTRATION: ClinicalTrials.gov NCT06143020.

Humans↗

PubMed2026

Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.

BACKGROUND: Predictive modelling for cancer risk, treatment-related complications, and survival is central to precision oncology. Conventional logistic regression (LR) and Cox proportional hazards (CoxPH) regression remain widely used but are limited when modelling nonlinear interactions, high-dimensional imaging features, and multimodal clinical-metabolic predictors. Artificial intelligence (AI) and machine learning (ML) methods offer expanded capability through automated feature extraction, ensemble learning, and flexible survival modelling, but the evidence on when AI/ML adds value over conventional models across cancer sites and predictive tasks remains fragmented. OBJECTIVE: To systematically evaluate the methodological performance, validation strategies, and translational limitations of AI/ML models compared with conventional statistical models in published predictive-modelling studies for breast, colorectal, or pancreatic cancer. METHODS: PubMed, Scopus, and Web of Science were searched for studies published between January 2019 and March 2025. Two reviewers independently conducted title-and-abstract screening, full-text eligibility assessment, and PROBAST risk-of-bias assessment. Sixty-five studies (n = 907,567 participants) were narratively synthesised by cancer site, predictive task, model family, comparator, validation strategy, predictor modality, and calibration or explainability reporting. RESULTS: The 65 studies comprised breast cancer (n = 35), colorectal cancer (n = 21), and pancreatic cancer (n = 9). AI/ML superiority over LR and CoxPH was task- and data-dependent. CNN- and U-Net-based models predominated in imaging and body-composition tasks, tree-based ensembles consistently outperformed LR for tabular perioperative complication prediction, and CoxPH remained competitive, and in the largest pancreatic risk study, superior to XGBoost (C-index 0.802 vs 0.723) in well-structured datasets. PROBAST analysis-domain risk was moderate in 54 of 65 studies (83%), driven by limited external validation, sparse calibration reporting (11/65), and few decision-curve analyses (7/65). CONCLUSION: AI/ML adds the most methodological value in imaging-derived feature extraction and nonlinear perioperative prediction, while conventional regression remains preferable in large, structured datasets with linear predictors. Clinical translation requires standardised body-composition definitions, external validation, calibration assessment, decision-curve analysis, and explainability, in line with TRIPOD+AI and CLAIM standards.

Humans↗

PubMed2026

Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.

BACKGROUND: Most European population mammography screening programs rely on double reading with arbitration, a model that delivers mortality benefit but is increasingly challenged by radiologist workload, variable specificity, and interval cancers. Artificial intelligence (AI) is being evaluated to support or optimize these established European screening pathways. PURPOSE: To synthesize prospective or program-embedded evaluations of AI conducted within European-style population screening programs and to estimate exploratory program-level absolute risk differences (RDs) per 1000 examinations for cancer detection rate (CDR) and recall. MATERIALS AND METHODS: We performed a prespecified, focused evidence synthesis of three large studies embedded within routine population screening programs operating under European-relevant workflows: MASAI (randomized AI-supported risk triage within a national program), ScreenTrustCAD (prospective paired-reader evaluation with AI as an independent reader in a double-reading framework), and PRAIM (nationwide decision-referral implementation). Outcomes were harmonized as AI-control RDs per 1000 examinations. Random-effects pooling used Hartung-Knapp-Sidik-Jonkman models. For the paired-reader design, sensitivity analyses applied a Kish effective sample-size approach across plausible within-examination correlations (ρ = 0.3-0.8). Positive predictive value (PPV) and workflow/time outcomes were summarized descriptively. RESULTS: Across 597,419 examinations, the pooled CDR RD was +0.9 per 1000 (95% CI -0.0 to +1.8; I2 ≈ 12%), consistent with a modest directional increase with borderline statistical uncertainty. The pooled recall RD was -0.6 per 1000 (95% CI -3.1 to +2.1; I2 ≈ 41-43%), indicating no consistent recall increase across screening programs. Where reported, PPV was higher with AI-supported screening. Efficiency signals included 44.3% fewer total readings in MASAI and shorter reading times for AI-normal examinations in PRAIM; in PRAIM, a program-level safety-net mechanism recovered 204 cancers that would otherwise have been missed. CONCLUSION: In European population screening programs characterized by double reading and arbitration, prospective program-embedded evidence suggests that AI integration may yield a small absolute increase in cancer detection (≈1/1000) without a consistent increase in recall, alongside improved PPV and efficiency signals. These findings suggestAI primarily as a complementary reader within European screening workflows, with implementation requiring explicit quality assurance and monitoring of interval cancers and stage distribution.

Humans↗

PubMed2026

Fatty acids and breast cancer: Epidemiology, subtype-specific metabolism, immune regulation, and clinical translation.

Fatty acids (FAs) are bioactive dietary and metabolic molecules that participate in membrane architecture, energy homeostasis, inflammatory signaling, gene regulation and immune function, all of which intersect with breast cancer (BC) risk, progression and treatment response. In this narrative review we integrate epidemiological, clinical, translational and mechanistic evidence on the role of FAs in BC. Saturated, monounsaturated, trans- and polyunsaturated FAs (PUFAs) are treated as distinct biological exposures rather than interchangeable measures of total fat intake. Similarly, evidence from dietary assessment, circulating biomarkers, erythrocyte membrane composition, adipose tissue stores and tumor lipid signatures is interpreted separately, because each captures exposure and biology at a different level. BC subtypes differ in FA synthesis, uptake, oxidation, storage and remodeling: luminal tumors are frequently linked to hormone-regulated lipogenesis, human epidermal growth factor receptor 2 (HER2)-positive tumors to growth-factor-driven lipid metabolism, and triple-negative tumors to exogenous FA uptake, inflammatory lipid mediators and ferroptosis-related vulnerabilities. FA-derived mediators also shape immune-cell polarization, cytokine signaling and the tumor microenvironment, and dietary FAs may reshape the gut microbiota; the fiber-derived short-chain FAs it produces, distinct from dietary FAs, likewise help regulate immune and inflammatory tone. Clinical data suggest possible roles for fat-quality modification and selected n-3 PUFA interventions, but findings are heterogeneous and not yet sufficient to support routine biomarker-guided precision onco-nutrition. Candidate biomarkers, such as erythrocyte n-6:n-3 composition, require prospective validation before clinical implementation. FA biology thus represents a modifiable but complex axis in BC prevention, tumor biology and supportive care.

Humans↗

PubMed2026

AI Health message intervention: The role of message customization and message source in breast cancer screening among women of color.

OBJECTIVES: To examine the effectiveness of breast cancer screening messages with varying levels of customization (generic, targeted, and tailored) and to compare AI-generated versus human-generated messages. METHODS: A between-subjects experimental design with a control condition was employed. Message content followed a standardized structure and varied by level of customization: generic, targeted (demographic-based), and tailored (perceived susceptibility- and barrier-based). Messages were developed by either the authors or GenAI (ChatGPT-4o). A total of 391 participants recruited via Prolific were randomly assigned to five groups (generic, targeted-human, targeted-AI, tailored-human, and tailored-AI). Self-efficacy, behavioral intentions, attitudes, and message believability were measured using different scales. RESULTS: Customized (tailoring and targeting) health messages performed comparably to generic messages in shaping positive health outcomes. GenAI-generated messages also produced outcomes comparable to those of human-generated messages under standardized conditions. Significant negative indirect effects through message believability for the human-tailored condition was found relative to the generic condition. CONCLUSIONS: GenAI may be a useful tool for developing and customizing scalable health messages. Its effectiveness depends not only on customization but also on maintaining message quality, including readability, clarity, coherence, naturalness, and credibility. PRACTICAL IMPLICATIONS: GenAI may support health practitioners in developing customized and scalable breast cancer messages. However, professional review remains necessary to ensure that the message is culturally appropriate, responsive to patient concerns, and suitable for use alongside patient-provider communication.

Humans↗

PubMed2026

Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.

BACKGROUND: Psychological interventions for patients with breast cancer often overlook the critical role of maladaptive attributional style in shaping their adjustment. Therefore, the need for theory-driven, scalable interventions that target cognitive restructuring, particularly during the vulnerable post-diagnosis period, is clear. OBJECTIVE: To evaluate the effectiveness of a nurse-led attribution remodeling training intervention grounded in the Neuman systems model for improving resilience, adaptive coping, and attributional style among women newly diagnosed with breast cancer. DESIGN: A randomized controlled trial. SETTING: A tertiary general hospital. PARTICIPANTS: A total of 130 eligible women newly diagnosed with breast cancer were recruited between March and November 2024. METHODS: A two-arm parallel-group randomized controlled trial was conducted. Participants were randomly assigned to receive either attribution remodeling training plus routine nursing (n = 65) or routine nursing only (n = 65). The nurse-led attribution remodeling training intervention, delivered via a blended model of in-person sessions and continued support through the WeChat mobile platform, was designed to systematically reshape maladaptive attributions into more adaptive ones. Resilience (primary indicator), coping strategy (i.e., confrontation, avoidance, resignation), and attributional style (secondary indicators) were assessed at baseline and at 1, 3, and 6 months post-baseline. A linear mixed model was used to analyze the effects of group, time, and group-by-time interactions. Effect sizes (Cohen's D) were calculated based on the means and standard deviations. RESULTS: At the 6-month follow-up, the intervention group had better outcomes than the control group in terms of resilience (mean difference: 1.49, 95% confidence interval: 0.37, 2.61), confrontation coping (3.35 [2.33, 4.37]), and adaptive attributional style (4.16 [3.87, 4.45]). Avoidance coping showed a small increase (0.82 [0.22, 1.42]), whereas resignation coping decreased (-1.66 [-2.49, -0.83]). Group effects and group-by-time interactions were statistically significant for all outcomes. Effect sizes at 6 months ranged from small for resilience (D = 0.28) and avoidance coping (D = 0.26) to moderate for confrontation coping (D = 0.60) and resignation coping reduction (D = -0.51), and large for attributional style (D = 0.94). CONCLUSIONS: Attribution remodeling training is a promising and effective theory-based intervention that can enhance psychological adaptation in women newly diagnosed with breast cancer. By strengthening key defense mechanisms, as conceptualized by the Neuman systems model, the program is effective, scalable, and nurse-deliverable for psycho-oncology care, bridging a critical gap in supportive cancer care and empowering nurses as primary psychological support providers. REGISTRATION: ChiCTR2000031827, registered prospectively on April 11, 2020, www.Chictr.or.cn.

Humans↗

PubMed2026

Clinicopathological response and survival outcomes of HER2-low versus HER2-zero early breast Cancer: A systematic review and Meta-analysis.

BACKGROUND: Breast cancer is the most common malignant tumor in women. Human epidermal growth factor receptor 2 (HER2) is a key biomarker for classification and treatment. A subgroup with HER2-low expression has been identified, but existing evidence is heterogeneous. This systematic review and meta-analysis compared pathological response and survival outcomes between HER2-low and HER2-zero early-stage breast cancer to clarify prognostic features. METHODS: This study followed PRISMA guidelines and was registered in PROSPERO (CRD420251120506). PubMed, Embase, Web of Science, ClinicalTrials.gov, and major oncology conferences were searched through September 2025. Cohort studies of early-stage breast cancer comparing HER2-low (IHC 1+/2+ and ISH-negative) vs. HER2-zero with extractable pCR, DFS, or OS data were included. Studies involving HER2-positive patients or inconsistent definitions were excluded. Meta-analyses were performed using RevMan 5.3. RESULTS: Twenty-eight studies involving 115,182 patients were included. HER2-low patients showed significantly lower pCR rates (OR = 0.58, 95% CI: 0.52-0.65). DFS favored HER2-low (multivariate HR = 0.75, 95% CI: 0.69-0.83), especially in HR+ tumors, with a weaker effect in HR- cases. OS also favored HER2-low (HR = 0.80, 95% CI: 0.72-0.89), mainly driven by the HR- subgroup; no OS difference was seen in HR+ tumors. Sensitivity analyses and funnel plots indicated robust results with no apparent publication bias. Overall study quality was high (17 high-quality, 11 moderate-quality). CONCLUSION: HER2-low early breast cancer shows lower pCR after neoadjuvant therapy but better long-term survival. These findings support the clinical relevance of HER2-low as a biologically meaningful subgroup within HER2-negative disease, while its status as a stable and independent subtype still requires further validation through prospective studies, standardized testing, and multi-omics investigation.

Humans↗

PubMed2026

Chemotherapy-Induced Nausea and Vomiting in Early Breast Cancer Patients Receiving Adjuvant Chemotherapy With Fluorouracil, Epirubicin, Cyclophosphamide Followed by Docetaxel Versus an Anthracycline-Free Regimen With Docetaxel, Cyclophosphamide-Results From a Randomized Clinical Trial.

Chemotherapy-induced nausea and vomiting (CINV) remains an important side effect despite new antiemetic drugs. This study tried to understand the occurrence of CINV in patients receiving two different chemotherapy regimens. As part of the randomized controlled clinical trial SUCCESS C (NCT00847444), 1582 of the 3463 patients completed CINV diaries. Patients were randomized to receive either chemotherapy with FEC (5-fluorouracil, epirubicin, cyclophosphamide followed by docetaxel) or TC (docetaxel, cyclophosphamide). CINV was evaluated hourly using a specially designed questionnaire. Endpoints of the study were complete response (no emesis) and total control (no nausea and no emesis) and were assessed with Kaplan-Meier curves and Cox regression analyses over three chemotherapy cycles. Eight hundred fourteen patients received FEC and 768 received TC; patients and tumor characteristics were similar in both groups. Patients receiving FEC had significantly more nausea and vomiting, with the main difference in the first 12 h. In the first cycle, the 0-12-h nausea/emesis-free rates were 70%/41% for FEC and 91/76% for TC. By 24 h after chemotherapy, the rates were 65%/33% (FEC) and 85%/60% (TC). The differences were similar in cycles 2 and 3. The detailed analysis of CINV in the study is unique and paves the way for modern CINV analysis of new therapeutics such as antibody-drug conjugates.

Adult↗

PubMed2026

Relationship between menopausal hormone therapy and incidence risk of breast cancer: systematic review and meta-analysis.

BACKGROUND: Menopausal hormone therapy (MHT) is widely prescribed for alleviating menopausal symptoms. Prior studies have mainly focused on individual hormone therapy formulations. This meta-analysis comprehensively synthesized evidence across various regimens to systematically evaluate the association between MHT and breast cancer risk. MATERIALS AND METHODS: We systematically searched CNKI, Wanfang, PubMed, and Web of Science from inception through August 2024. Eligible studies examining breast cancer risk following MHT were independently screened and assessed by two reviewers. The review and meta-analysis followed PRISMA guidelines. RESULTS: Thirty-four studies were included. The random-effects model showed a significant but heterogeneous overall association (OR = 1.15, 95% CI: 1.09-1.22; I² = 92.4%). Subgroup analysis identified hormone type, use status, and region as key determinants (P for interaction < 0.001). Stratification by hormone type resolved much of the heterogeneity, revealing risk confined to estrogen-progestin therapy (EPT; OR = 1.44, 95% CI: 1.26-1.64), while estrogen-only therapy (ET) showed no overall association (OR = 1.00, 95% CI: 0.91-1.10). Study type, region, and sample size were significant effect modifiers. For ET, randomized controlled trials demonstrated a protective effect (OR = 0.78, 95% CI: 0.70-0.87), contrasting with neutral findings from observational studies. CONCLUSIONS: MHT is associated with a modest but significant increase in breast cancer risk, primarily driven by EPT. This risk was not observed with ET in observational studies, though trials suggested a protective effect. Crucially, the association shows marked geographical heterogeneity, indicating risk is modified by regimen and regional factors.

Humans↗

PubMed2026

The gut microbiota-obesity axis in the pathogenesis and prognosis of breast cancer.

BACKGROUND: Breast cancer (BC) remains a major global health concern, accounting for 11.7% of all cancer cases and ranking as the second leading cause of female cancer-related deaths worldwide. Increasing evidence highlights the interplay between gut microbiota (GM) dysbiosis and obesity-associated metabolic dysfunction in BC progression. This review aims to elucidate the role of GM in obese patients with BC. METHODS: A systematic literature search was conducted in PubMed and Web of Science databases for publications from July 2015 to January 2025. Search terms combined BC, GM, obesity, dysbiosis, immunity, and microbiome. Article selection prioritized studies investigating microbial alterations in BC patients, mechanistic links between obesity and cancer progression, and GM-targeted interventions. Both original studies and authoritative reviews were included, supplemented by manual reference screening. DISCUSSION: Obesity may trigger systemic inflammation, altered adipokine secretion, and disrupted steroid hormone metabolism via gut-derived β-glucuronidase activity, thereby exacerbating BC occurrence and recurrence. GM dysbiosis-driven metabolites such as branched-chain amino acids (BCAAs) and short-chain fatty acids (SCFAs) can activate oncogenic signaling pathways and immunosuppressive myeloid-derived suppressor cells (MDSCs), fostering tumor immune evasion. Conversely, dietary interventions, probiotics, and fecal microbiota transplantation (FMT) can alleviate dysbiosis, strengthen gut barriers, and restore anti-tumor immunity, improving chemotherapy response and reducing recurrence. However, challenges persist in deciphering BC subtype-related microbial signatures and optimizing microbiota-targeted therapies. CONCLUSION: Future longitudinal studies are needed to clarify causal relationships, validate microbial biomarkers, and translate preclinical findings into clinical applications. Addressing the gut-breast axis may offer transformative potential for precision oncology in obesity-driven BC.

Humans↗

Compare source metadata on this page

Work	Published	Source identifier	Source
PGR expression as a pharmacogenomic companion biomarker to GENE70-derived genomic risk in ER-positive/HER2-negative breast cancer.	2026-12-01	PMID 42708797	pubmed
Safety and efficacy of Meridian sinew tuina (MST) for post-surgical upper limb lymphedema: a systematic review and meta-analysis.	2026-09-07	PMID 42703097	pubmed
Effects of erector spinae plane block on postoperative pain in patients undergoing implant-based breast reconstruction for breast cancer: a randomized controlled trial.	2026-09-02	PMID 42686359	pubmed
Beyond predictive performance: A systematic review and critical methodological appraisal of AI/ML and conventional modelling strategies in breast, colorectal, and pancreatic Cancer.	2026-08-17	PMID 42641254	pubmed
Artificial intelligence-supported double reading in European population breast cancer screening: A systematic review and meta-analysis of prospective programs.	2026-08-11	PMID 42617468	pubmed
Fatty acids and breast cancer: Epidemiology, subtype-specific metabolism, immune regulation, and clinical translation.	2026-08-04	PMID 42551759	pubmed
AI Health message intervention: The role of message customization and message source in breast cancer screening among women of color.	2026-07-30	PMID 42537382	pubmed
Nurse-led attribution remodeling training based on the Neuman systems model to enhance resilience, adaptive coping, and attributional style in women newly diagnosed with breast cancer: A randomized controlled trial.	2026-07-14	PMID 42497495	pubmed
Clinicopathological response and survival outcomes of HER2-low versus HER2-zero early breast Cancer: A systematic review and Meta-analysis.	2026-06-04	PMID 42248318	pubmed
Chemotherapy-Induced Nausea and Vomiting in Early Breast Cancer Patients Receiving Adjuvant Chemotherapy With Fluorouracil, Epirubicin, Cyclophosphamide Followed by Docetaxel Versus an Anthracycline-Free Regimen With Docetaxel, Cyclophosphamide-Results From a Randomized Clinical Trial.	2026-04-29	PMID 42056728	pubmed
Relationship between menopausal hormone therapy and incidence risk of breast cancer: systematic review and meta-analysis.	2026-03-10	PMID 41808362	pubmed
The gut microbiota-obesity axis in the pathogenesis and prognosis of breast cancer.	2026-01-07	PMID 41503829	pubmed

These are bibliographic comparisons, not experimental rankings. Follow the original document for methods and conditions.