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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↗

PubMed2025

Impact of stromal maturity and proportion on prognosis and immune landscape in colorectal cancer.

BACKGROUND: Tumour microenvironment and cancer cells have constant interaction affecting cancer progression. Tumour-stroma ratio (TSR) in the tumour centre and desmoplastic reaction (DR) classification at the invasive margin are prognostic factors based on stroma evaluation on H&E slides. However, their combined value and immunological associations remain poorly defined. This study examines the prognostic and immunological value of TSR, DR, and their combination in two large colorectal cancer cohorts. METHODS: Two colorectal cancer cohorts (N = 1,876) were analyzed. We introduced a three-tiered Stromal Maturity and Proportion Score (SMAPS) based on the presence of high (>50%) TSR and myxoid stroma (immature DR classification). Alcian blue staining was used to further quantify myxoid stroma. Multiplex immunohistochemistry combined with digital image analyses, was utilized to study immune cell densities associated with SMAPS, TSR, DR, and Alcian blue intensity. RESULTS: In the study cohort (N = 1,100), SMAPS was a stronger predictor of cancer-specific mortality [HR for high (vs. low) SMAPS 2.01 (95% CI 1.47-2.75), p < 0.0001] compared to TSR [HR for stroma-high (vs. stroma-low) 1.49 (95% CI 1.15-1.93), p = 0.003] and DR classification [HR for immature (vs. mature) 1.84 (95% CI 1.39-2.45), p < 0.0001]. High SMAPS, stroma-high TSR, and immature DR correlated with lower densities of CD3+ T cells, B cells, M1-like macrophages, CD66B+ granulocytes, and mast cells. Alcian blue staining was associated with immature DR and corresponding immune cells. The validation cohort (N = 776) confirmed the association of SMAPS with survival and T cell densities. CONCLUSIONS: TSR and DR are independent prognostic factors for cancer-specific survival. SMAPS is a promising prognostic tool that integrates stromal maturity at the invasive margin and stromal proportion in the tumour centre. SMAPS has stronger prognostic value compared to TSR and DR classifications alone. A high stromal proportion and myxoid content are associated with an immunosuppressive microenvironment characterized by lower densities of antitumourigenic immune cells.

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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.

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PubMed2026

Artificial intelligence (AI) uses in stereotactic radiosurgery (SRS): diagnosis with brain metastasis (BM) - A systematic review.

BACKGROUND: Brain metastases (BM) are the most common intracranial tumors in adults, and stereotactic radiosurgery (SRS) has become a mainstay of management. However, several diagnostic challenges persist in the SRS pathway, particularly the differentiation of radiation necrosis (RN) from true tumor progression, which conventional MRI and even advanced imaging techniques often cannot reliably resolve. Recent advances in artificial intelligence (AI) offer the potential to address these diagnostic limitations. This systematic review synthesizes current literature on AI applications for MRI-based diagnostic decision support in BM patients undergoing SRS, with a focus on radiomics and deep learning tools for distinguishing RN from progression, classifying molecular and histologic subtypes, and predicting treatment response. METHODS: A systematic review was performed in accordance with PRISMA guidelines. PubMed, Web of Science, and Scopus were searched using a targeted query combining terms related to AI, brain metastasis, diagnosis or imaging, and SRS. After screening 483 records and applying strict inclusion and exclusion criteria, 18 studies published between 2015 and 2025 were included. Data were extracted on study design, cohort characteristics, imaging modality, AI methodology, validation strategy, and reported diagnostic performance. RESULTS: Among the 18 included studies, AI models demonstrated strong performance across diagnostic tasks in the BM-SRS pathway. The differentiation of RN from true tumor progression was the most extensively studied application, addressed by 14 of 18 studies, with reported AUCs ranging from 0.71 to 0.94. Support vector machines, random-forest ensembles, convolutional neural networks, and transformer-based multimodal architectures were widely used. The literature evolved from single-sequence radiomic classifiers in 2018 to multimodal deep learning frameworks fusing imaging with clinical and genomic data in 2025. Contrast-enhanced T1-weighted MRI was the dominant imaging input, and texture-based radiomic features (GLCM, GLSZM, GLDM, and wavelet-derived features) were the most consistently predictive. The highest-performing models reached AUCs of 0.85-0.91 through multimodal integration of imaging with clinical and genomic features, and consistently outperformed expert neuroradiologist read on matched cases. Remaining studies addressed longitudinal segmentation-based detection of local failure and adverse radiation effects, BRAF mutation status in melanoma BM, early Gamma Knife treatment response, and primary tumor histology classification, with more variable performance. CONCLUSION: AI models, particularly those integrating MRI-derived radiomic features with clinical and genomic data, show high accuracy in supporting diagnostic decisions for BM patients treated with SRS. The post-SRS differentiation of radiation necrosis from true tumor progression has reached the greatest level of maturity and is closest to clinical translation, with potential to reduce unnecessary biopsies, personalize surveillance intervals, and rationalize treatment-pathway decisions. Other diagnostic applications, including molecular subtyping and primary tumor histology classification, remain exploratory and require further multicenter validation. Integration of AI tools into multidisciplinary tumor-board workflows, combined with prospective validation and standardized reporting, will be essential to realize the full clinical benefits of AI in SRS for brain metastases.

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PubMed2026

Public health, public protest: The role of health burdens and healthcare access in protest mobilisation.

Health and politics are intertwined, yet few studies have examined the association between health and protest. This study examined whether population health burdens were associated with protest incidence and whether healthcare access modified these associations. Analysis was based on an unbalanced 2004-2023 country-year panel, combining protest counts from ACLED with rates for 22 GBD causes. Mixed-effects negative-binomial models estimated incidence-rate ratios (IRRs) with interactions for healthcare access (±1 SD). Two-way fixed-effects Poisson models were estimated as a benchmark to distinguish cross-national associations from within-country dynamics. Health burdens were systematically, but heterogeneously, associated with protest. Rates for several non-communicable burdens were associated with protest, notably musculoskeletal disorders (IRR 1.72, 95% CI 1.37-2.15), neoplasms (1.24, 1.06-1.44), substance-use disorders (1.32, 1.12-1.56) and HIV/AIDS and other STIs (1.24, 1.12-1.38). Higher healthcare access generally attenuated health-protest associations. Fixed-effects models confirmed several associations (e.g. HIV/AIDS, neoplasms) but revealed that others (e.g. maternal/neonatal disorders, enteric infections) were driven primarily by cross-national differences. Population health burdens were associated with cross-national variation in protest mobilisation. Chronic, non-communicable burdens were associated with heightened protest, whereas poverty-linked and early-life burdens were associated with lower mobilisation. Healthcare access was associated with attenuation of these relationships.

Humans↗

PubMed2026

Long-term outcomes of non-operative compared to operative management of acute uncomplicated appendicitis - a systematic review and meta-analysis.

BACKGROUND: We evaluated long-term outcomes of non-operative management (NOM) versus surgical management of acute uncomplicated appendicitis. METHODS: Systematic review of studies comparing NOM versus surgery with ≥2 years follow-up. Primary outcome was long-term failure rate. RESULTS: 9/1635 studies were included (3 RCTs; 6 non-RCT studies), involving 3883 patients; 5 were in pediatric populations. Median follow-up was 33.6 (range 24-312) months. NOM pooled long-term failure rate was 38.9% (95% CI: 31.1%-46.7%), increasing to 44.4% (95% CI: 41.4%-47.4%) in RCTs. Pooled appendectomy rate after NOM was 36.3% (95% CI: 28.9%-43.7%). Incidence of appendiceal neoplasms was approximately 0.3%. Non-operative management had cost savings of €1535 (95% CI: -€1892 to -€1178) versus surgery. CONCLUSIONS: NOM of acute uncomplicated appendicitis was associated with high long-term failure rates and significant risk of subsequent appendectomy.

Humans↗

PubMed2026

Efficacy and safety of Ruxolitinib-based combination therapy in the patients with Myelofibrosis (MF): a systematic review and meta-analysis.

BACKGROUND: Myelofibrosis (MF) is a chronic myeloproliferative neoplasm. Although Ruxolitinib, a JAK1/2 inhibitor, remains the cornerstone of MF treatment, it does not reverse disease progression, and resistance frequently emerges. These limitations have prompted investigation into combination therapies targeting pathways beyond the JAK-STAT axis. This meta-analysis aims to evaluate the efficacy and safety of Ruxolitinib-based combination therapies in patients with MF. METHODS: We conducted a systematic search of databases for studies published through August 1, 2025. Thirteen distinct Ruxolitinib-based combination regimens were included. Primary efficacy endpoints were ≥35% spleen volume reduction at 24 weeks (SVR35) and ≥50% reduction in total symptom score (TSS50). Safety endpoints focused on the incidence of grade 3/4 thrombocytopenia and anemia. Subgroup analyses were performed based on prior JAK inhibitor exposure and therapeutic mechanism of action. RESULTS: A total of 19 studies comprising 1,088 patients were included in the meta-analysis. Among JAK inhibitor-naïve patients, the combination of Ruxolitinib with Selinexor demonstrated the highest efficacy (SVR35: 92%; TSS50: 78%), followed by Ruxolitinib plus BMS-986158 (SVR35: 90%). For patients with prior JAK inhibitor exposure, Ruxolitinib plus Siremadlin (SVR35: 45%) showed notable activity. CONCLUSION: For JAK inhibitor-naïve patients, Ruxolitinib-based combination regimens demonstrated satisfactory clinical responses and the potential for meaningful disease control. For patients with prior JAK inhibitor exposure, the addition of combination therapy drugs may further enhance the efficacy. Personalized treatment selection remains essential, as therapeutic efficacy is significantly influenced by prior JAK inhibitor exposure.

Humans↗