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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

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↗

PubMed2026

In silico identification of DNMT1 inhibitors from the PlantCyc database through computational approach to assess the anti-cancer potential of nutraceutical compounds in breast cancer.

Breast cancer accounts for a disproportionate share of global cancer-related deaths, with 670,000 fatalities and 2.3 million new diagnoses recorded in women during 2022 alone. Existing treatment modalities carry considerable toxicity burdens, and resistance to available agents remains an unresolved clinical problem. DNA methyltransferase 1 (DNMT1), the enzyme chiefly responsible for maintaining genome-wide methylation patterns during DNA replication, has been mapped out as a high-value target in breast cancer because its dysregulation silences tumour suppressor genes through promoter hypermethylation. The present work involves hierarchical in silico workflow to screen 4549 plant-derived compounds from the PlantCyc database (v16.0.3) against the human DNMT1 catalytic domain (PDB ID: 4WXX). Ten top-scoring compounds were taken forward for molecular docking via AutoDock Vina; Quercetin and Kaempferol both recorded the highest binding affinities at -9.5 kcal/mol, Wogonin (-9.3 kcal/mol) and Xanthohumol (-8.1 kcal/mol) also emerged as strong binders. Pharmacokinetic evaluation using ADMET-AI confirmed that all 10 compounds met Lipinski's rule of five, with human intestinal absorption values at or above 0.98. Wogonin and Xanthohumol were selected for a 100 ns all-atom molecular dynamics (MD) simulation in GROMACS due to their well-rounded ADMET profiles and limited existing data on their specific interactions with DNMT1 in breast cancer. Across all measured trajectory metrics, backbone RMSD, residue fluctuation, radius of gyration, solvent-accessible surface area, and intermolecular hydrogen bond count, Wogonin formed a more stable, compact complex. These findings suggest that Wogonin and Xanthohumol are non-toxic nutraceutical candidates suitable for DNMT1 targeted epigenetic therapy, with computational foundation strong enough to facilitate future in vitro and in vivo validation work.

Humans↗

PubMed2026

Efficacy of Mindfulness-Based Interventions on Anxiety and Sleep Quality in Patients with Breast Cancer: A Systematic Review and Meta-Analysis.

INTRODUCTION: Patients with breast cancer commonly experience anxiety and sleep disturbance during and after treatment, and these symptoms are closely interrelated, negatively affecting the quality of life. Mindfulness-based interventions (MBIs) have been increasingly used as a nonpharmacological supportive approach. This systematic review and meta-analysis aimed to evaluate the effects of MBIs on anxiety and sleep quality in patients with breast cancer. METHODS: A systematic search of PubMed, Web of Science, Cochrane Library, CINAHL, and Embase was conducted up to May 15, 2025. Random-effects meta-analysis was used to estimate standardized mean differences (SMDs) with 95% confidence intervals (CIs). Risk of bias was assessed using the Cochrane RoB 2.0, and the certainty of evidence was evaluated with Grading of Recommendations, Assessment, Development, and Evaluation. RESULTS: Twenty-four randomized controlled trials (RCTs) including 3,212 participants were analyzed. MBIs significantly reduced anxiety compared with control groups receiving usual care, no intervention, or wait-list conditions (SMD: -0.47, 95% CI: -0.62 to -0.32), whereas no significant effect was observed for sleep quality. Subgroup analysis indicated that intervention duration accounted for 55.5% of the heterogeneity in anxiety outcomes. All studies were rated as having some concerns regarding risk of bias, primarily due to self-reported outcomes and lack of blinding. Certainty of evidence was moderate for anxiety and low for sleep quality. DISCUSSION: MBIs appear to be effective in reducing anxiety among patients with breast cancer; however, no significant effect was observed for sleep quality. All included studies were rated as having some concerns regarding risk of bias, and the limited reporting of adverse events represents a limitation of the evidence. In addition, substantial heterogeneity in sleep quality outcomes and the limited number of included RCTs restrict exploration of heterogeneity sources and limit generalizability. Further high-quality well-designed RCTs are needed to strengthen and confirm the evidence.

Female↗

PubMed2026

Flavoromics-based profiling reveals taste and aroma differences between infant formula and breast milk.

Flavor differences between infant formula (IF) and breast milk (BM) are considered a potential factor affecting infants' acceptance of IF. This experiment employs flavoromics combined with multivariate statistical analysis to systematically compare the flavor profiles of IF and BM. Electronic tongue analysis and amino acid correlation revealed that IF was characterised by pronounced saltiness and umami richness, whereas BM exhibited greater bitterness and astringency. Volatile compound profiling identified five key flavor constituents in IF, predominantly aldehydes such as hexanal and pentanal. In contrast, BM contained a broader array of compounds-including acids, aldehydes, and esters-resulting in a more complex flavor profile. Kyoto Encyclopedia of Genes and Genomes (KEGG)-based metabolic pathway annotation, together with fatty acid profiling, suggested that some volatiles may be associated with lipid oxidation, Maillard reaction and sulfur-containing amino acid degradation pathways, offering a theoretical basis for the targeted optimisation of IF flavor.

Humans↗

PubMed2026

Screening of Estrogenic and Antiestrogenic Effects of Estradiol, Bisphenol A, and Fulvestrant Using 2D and 3D Breast Cancer Cell Systems With a Luciferase Reporter Gene Assay.

Endocrine-disrupting chemicals (EDCs) like bisphenol A (BPA) pose health risks by interfering with hormones. This study develops and utilizes in vitro 2D and 3D cell models to evaluate the estrogenic and antiestrogenic properties of compounds. Human breast cancer cell lines T47D and MCF7, stably transfected with a luciferase reporter gene (ERE-LUC), were first compared in 2D. Due to the significantly higher sensitivity and responsiveness observed in the T47D line during preliminary 2D screenings, this cell line was exclusively selected for the development of the 3D spheroid model. Cells were treated with 17β-estradiol (E2), BPA, and Fulvestrant (FUL) to assess cell viability and luciferase activity. In 2D models, T47D ERE-LUC cells showed higher responsiveness than MCF7 ERE-LUC, which failed to show significant luciferase induction with E2. In the 3D T47D model, cells exhibited significant and robust changes in luciferase activity in response to E2 and BPA, highlighting the enhanced fidelity of 3D cultures in replicating tissue conditions compared to their 2D counterparts. The study highlights the effectiveness of 3D models over 2D in evaluating estrogenic activity. Specifically, the 3D T47D ERE-LUC system serves as a superior, sensitive, and reliable platform for screening EDCs, offering benefits in cost, data speed, and reduced in vivo reliance.

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

Use of indocyanine green fluorescence versus patent blue V dye for sentinel lymph node biopsy in early breast cancer, a randomized controlled trial.

BACKGROUND: Sentinel lymph node biopsy (SLNB) is standard for axillary staging in early breast cancer. While the combination of radioisotope and blue dye (e.g., patent blue V, PBV) remains the standard, it has limitations including logistics, variable identification rate (IR), and allergic potential. Indocyanine green (ICG) fluorescence is a promising alternative, but high-quality comparative evidence is needed. METHODS: This was a single-center, prospective, randomized controlled trial. Forty patients with early-stage, node-negative breast cancer were allocated to SLNB using either ICG (n = 20) or PBV (n = 20). All patients subsequently underwent completion level I-II axillary lymph node dissection (ALND) as the pathological reference standard for diagnostic performance assessment. Primary outcome was sentinel lymph node (SLN) IR. Secondary outcomes included detection time, number of SLNs retrieved, false-negative rate (FNR), and safety. RESULTS: Baseline characteristics were comparable between groups. The SLN IR was significantly higher with ICG (100% [20/20]) than with PBV (75% [15/20], p = 0.047). ICG was associated with a significantly shorter median detection time (14.5 vs. 24.0 min, p < 0.001) and retrieved more SLNs (mean: 3.6 vs. 2.4, p = 0.002). Most critically, ICG demonstrated 100% sensitivity, specificity, negative predictive value (NPV), and overall diagnostic accuracy, with a 0% FNR. In contrast, PBV achieved a sensitivity of 75%, an overall diagnostic accuracy of 90%, and an FNR of 25%. No ICG-related adverse events occurred. PBV caused skin discoloration in 75% of patients and one (5%) allergic reaction. CONCLUSION: ICG fluorescence achieved a higher SLN IR, shorter detection time, higher sensitivity, lower FNR, and fewer tracer-related adverse events than PBV as a single tracer for SLNB in patients with early-stage breast cancer. These findings suggest that ICG is a promising standalone tracer when radioisotope mapping is unavailable. Larger multicenter studies are required before widespread adoption can be recommended.

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

Targeting TP53 in triple-negative breast cancer: Molecular pathogenesis, therapeutic implications, and emerging pharmacological strategies.

Triple-negative breast cancer (TNBC) remains a highly aggressive and therapeutically challenging subtype, defined by the absence of oestrogen, progesterone, and HER2 expression. Tumour Protein 53 (TP53) mutations represent the most frequent genetic alteration, occurring in over 80% of cases and driving tumour initiation, progression, and therapeutic resistance. Mutant p53 proteins not only lose canonical tumour-suppressive functions but also often acquire gain-of-function (GOF) oncogenic properties that promote metastasis, genomic instability, and resistance to mechanisms like ferroptosis. This review examines the biological role of TP53 in TNBC pathogenesis and evaluates emerging pharmacological strategies aimed at targeting these vulnerabilities. Key approaches include the pharmacological reactivation of mutant p53 using small molecules such as APR-246, COTI-2, and the mutation-specific reactivator rezatapopt (PC14586), which has shown significant clinical tumour reduction in Y220C-mutant patients. Other strategies involve targeted protein degradation, the exploitation of synthetic lethal interactions (e.g., Chk1 or Aurora kinase B inhibition), and the use of natural products like cryptolepine or piperine derivatives. Recent clinical evidence further highlights the potential of combining epigenetic agents like decitabine with chemotherapy in TP53-mutant populations. Integrating TP53 mutation status into biomarker-driven treatment paradigms is a pivotal step toward achieving precision oncology and improving clinical outcomes for patients with TNBC.

Precision oncology↗

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

Effects of transcutaneous electrical acupoint stimulation versus acupressure on the trajectories of multidimensional adverse reactions to chemotherapy in breast cancer patients: a secondary analysis of a randomized controlled trial.

BACKGROUND: Chemotherapy for breast cancer often induces multidimensional adverse reactions such as nausea and vomiting, anxiety, depression, and sleep disturbances. These symptoms are interrelated and may evolve dynamically, impacting patients' treatment outcomes and quality of life. As non-pharmacological interventions, transcutaneous electrical acupoint stimulation (TEAS) and self-acupressure (SA) have shown potential in alleviating symptoms. However, their long-term effects on the joint developmental trajectories of these multidimensional symptoms (nausea and vomiting, anxiety, depression, and sleep disturbances) remain unclear. OBJECTIVE: This study aimed to identify potential trajectory class of multidimensional adverse reactions in breast cancer patients undergoing chemotherapy and to explore the differential effects of TEAS and SA on different trajectory subgroups. METHODS: This was a secondary analysis of a randomized controlled trial. A total of 189 breast cancer patients receiving chemotherapy were included. The Group-Based Multi-Trajectory Model (GBMTM) was employed to identify joint developmental trajectories of acute/delayed chemotherapy-induced nausea and vomiting (CINV), anxiety, depression, and sleep quality during chemotherapy. Subsequently, causal forest was used to analyze the average treatment effects (ATE) of TEAS (vs. control group) and SA (vs. control group) on patients' symptom trajectory. RESULTS: Multidimensional adverse reactions were classified into two heterogeneous trajectories: a "High Symptom Burden-Persistent (HSBP)" type (n = 101) and a "Low Symptom Burden-Relieving (LSBR)" type (n = 88). The persistent high incidence of acute CINV contrasted sharply with the comprehensive relief of other symptoms in the latter group. Causal forest suggested that both TEAS and SA significantly increased the probability of patients being classified into the "LSBR" trajectory. The ATE was 0.147 (95% CI: 0.143, 0.151) for TEAS, slightly lower (P < 0.05) than 0.176 (95% CI: 0.162, 0.190) for SA.  CONCLUSION: Multidimensional adverse reactions in breast cancer patients undergoing chemotherapy exhibit heterogeneity in their trajectories. Both TEAS and SA were associated with a higher probability of patients being classified into a more favorable symptom trajectory-LSBR. The multidimensional trajectory identification with treatment effect estimation may serve as a useful analytical strategy for future longitudinal research in cancer chemotherapy-induced adverse reactions symptom management. CLINICAL TRIAL REGISTRATION: ChiCTR2300077667 (Chinese Clinical Trial Registry, https://www.chictr.org.cn/ ), Registered 15 November 2023.

Humans↗

PubMed2026

The Impact of Oncological Treatments on Return to Work, Work Ability, and Sickness Absence in Breast Cancer Survivors: A Systematic Review.

PURPOSE: Returning to work and maintaining an adequate ability to work serve as key indicators of quality of life, psychological well-being and psychosocial adjustment. Therefore, this study aims to analyze the impact of breast cancer treatments on return to work (RTW), work ability (WA), and sick leave (SL) among breast cancer survivors. METHODS: A systematic review was conducted according to the PRISMA guidelines. The sample consisted of 26 studies published between 2016 and 2025, including prospective multicenter cohorts and national registries from fifteen countries across four continents, with more than 25,000 participants. A methodological quality assessment and a narrative synthesis were performed to synthesize the results. RESULTS: Chemotherapy is the most consistent predictor of prolonged SL, delayed RTW, and significantly reduced WA. Radical surgery and axillary lymph node dissection (ALND) are associated with a significantly delayed RTW due to physical sequelae. While outcomes showed strong relationship with clinical factors, certain psychosocial variables such as depression, anxiety, and low self-efficacy seemed to act as important secondary factors that can further complicate the process. CONCLUSION: The findings suggest that more invasive or aggressive treatments (chemotherapy, ALND, and radical surgery) were associated with poorer outcomes on RTW, WA, and SL. Furthermore, the clinical recovery associated with treatment completion did not necessarily equate to a functional recovery in WA that facilitated a successful RTW. Thus, it is necessary to explore in depth the impact of cancer treatments on WA, alongside psychosocial variables, to design multidisciplinary interventions that enable sustainable occupational reintegration. REGISTRATION: PROSPERO 2026 (CRD420261322638).

Breast cancer survivors↗

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

Evidence-based insights into medial pedicle reduction mammaplasty: A systematic review and meta-analysis.

BACKGROUND: Breast reduction relieves the physical and psychosocial burden of macromastia. Medial pedicle reduction mammaplasty may enhance vascular reliability, preserve nipple-areola complex (NAC) sensation, and sustain upper pole fullness, even in large-volume reductions. The purpose of this study was to assess the outcomes of medial pedicle breast reduction. METHODS: A search across ScienceDirect, Cochrane, and PubMed was conducted. Included studies reported on perioperative outcomes and complications of medial pedicle breast reduction. Data on demographics, surgical variables, complications, sensory recovery, volumetric changes, and patient satisfaction were extracted. Proportion meta-analysis was performed, and odds ratios were calculated for comparison with inferior pedicle breast reduction. RESULTS: Twenty-five studies comprising 1033 patients met the inclusion criteria. Mean BMI ranged from 27 to 42 kg/m2, with mean resection weights between 412 and 3828 g. Mean surgical times ranged from 104 to 204 min. Pooled complication rates were low: infection 1%, seroma 1%, hematoma 1%, fat necrosis 2%, NAC necrosis 1%, dehiscence 8%, and reintervention 5%. Odds of complications did not differ significantly from inferior pedicle reductions. NAC sensation typically recovered by 6-12 months, with no long-term deficits. Volumetric analyses demonstrated stable breast shape after the first postoperative year, with superior upper pole tissue maintained. Patient satisfaction ranged 75-100%, with higher ratings for scar appearance and overall aesthetics in medial pedicle reductions. CONCLUSION: Medial pedicle breast reduction is a well-established and reproducible technique, preserving NAC sensation, achieving stable long-term shape, and enhancing upper pole fullness. It offers satisfactory aesthetic outcomes compared to other traditional methods, even in large-volume reductions.

Humans↗

PubMed2025

Mindfulness and Sex Education for Sexual Dysfunction in Breast Cancer Survivors: Mediators and Moderators of Treatment Outcome.

Mindfulness-based cognitive therapy (MBCT) and supportive-expressive sex education therapy (STEP) are effective group treatments for sexual dysfunction after breast cancer (BrCa). We explored mediators and moderators of outcomes following the 8-week groups. BrCa survivors (n = 116, mean age = 49.9 ± 9.5) were randomized to group and completed measures before, immediately after, and 6 months after treatment. Mediators assessed were changes in depression, chronic pain acceptance, pain catastrophizing, and trait mindfulness. Potential moderators included age, treatment expectations, baseline mental health, cancer treatment duration, use of chemotherapy, and adjuvant endocrine therapy. Longitudinal mediation and moderation were assessed using linear mixed models. Increases in pain acceptance mediated improvements in sexual desire and reductions in both sexual distress and vaginal pain. Decreases in pain catastrophizing mediated improvements in sexual distress. Higher expectations for treatment led to greater reductions in sexual distress. Those with low baseline anxiety showed greater improvements in desire and distress. Low baseline depression predicted greater improvements in desire, but only in the STEP arm. Older STEP participants improved significantly more than younger STEP participants. Cancer-related treatment variables, and the impact of adjuvant endocrine therapy, had differential effects on outcomes based on the treatment arm of the study. In conclusion, treatments aimed at improving pain acceptance and pain catastrophizing are likely to promote improvements in sexual health among BrCa survivors, and factoring in patients' expectations about treatment improvements, depression and anxiety, age, duration of cancer treatment, chemotherapy, and adjuvant hormonal therapy may help to guide treatment recommendations for sexual dysfunction.

Humans↗

PubMed2026

Impact of kangaroo care on circadian rhythm, growth, physiological stability in premature infants, and cortisol and melatonin levels in maternal breast milk: A randomized controlled trial.

PURPOSE: This study aimed to examine the effects of regular kangaroo care (KC) on sleep-wake cycles, growth, physiological stability, and maternal breast milk cortisol and melatonin levels in premature infants. DESIGN: This study was a parallel group, single-blind, pre-test-post-test, randomised controlled trial (RCT). METHODS: This randomized controlled study was conducted in a neonatal intensive care unit (NICU) in Türkiye between September 2024 and September 2025 Thirty-six premature infants were randomized to intervention (n = 28) or control (n = 28). Infants in the intervention group received KC for three consecutive days, twice daily (10:00 a.m. and 10:00 p.m.) for 60 min per session. Data were collected using the Infant Information Form, Physiological Parameters Monitoring Chart, and Premature Infant Sleep-Wake Cycles Tracking Chart. Sleep-wake cycles were monitored using a Bispectral Index device. Breast milk cortisol and melatonin levels were measured at baseline and on day three using the competitive ELISA method. The study was registered at ClinicalTrials.gov (NCT06589349). RESULTS: Regular KC had a statistically significant effect on BIS values, heart rate, respiratory rate, oxygen saturation, and body temperature (p < 0.05). No statistically significant effects were observed on infant body weight or on maternal breast milk cortisol and melatonin levels (p > 0.05). CONCLUSION: The findings indicate that regular KC is associated with improved regulation of the sleep-wake cycle and enhanced physiological stability in premature infants. No significant changes were observed in maternal breast milk cortisol or melatonin levels following KC.

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↗