This study evaluated the effect of structured grief counseling on grief responses in family caregivers of advanced cancer patients from the terminal phase through early bereavement, and may inform bereavement care in oncology and hospice settings.

We conducted a randomized controlled trial from October 2024 to November 2025 among family caregivers of patients with advanced cancer. Participants were assigned to structured grief counseling (intervention group, n = 55) or only psychological materials (control group, n = 56). Counseling began before the death and continued for 3 months after the death. Outcomes were assessed at enrollment, at the end of the intervention, and at 1 and 3 months after the death. Measures included grief, guilt, anxiety, depression, post-traumatic growth, and health-related quality of life. Linear mixed-effects models estimated group differences over time.

Compared with control, the intervention produced lower Anticipatory Grief Scale scores over time (estimates = -9.31, P < 0.001). The intervention also yielded higher Post-traumatic Growth Inventory scores and Short-Form 36 Health Survey scores (estimates = 6.02 and 5.97, respectively; P < 0.001). Between-group differences for Bereavement Guilt Scale scores, Self-Rating Anxiety Scale scores, and Self-Rating Depression Scale scores were not significant.

Structured grief counseling provided to family caregivers from the patient's terminal phase through the early bereavement period effectively improves grief status, post-traumatic growth, and health-related quality of life. These findings support the integration of standardized, family-centered bereavement support systems into oncology and hospice care services.

Primary brain tumor (PBT) patients commonly experience cognitive dysfunction. This study aims to describe the prevalence and factors associated with perceived cognitive function (PCF) in PBT patients enrolled in a natural history study (NCT02851706: Principal Investigator T. S. Armstrong).

The Neuro-QoL Cognition Function was used to measure PCF with T-scores < 40 categorized as cognitively impaired. Clinical and demographic characteristics, patient-reported outcomes (PROs: symptom burden, depression, anxiety), and KPS were collected and characterized using descriptive statistics. Univariate tests on PCF with p-value < 0.10 were performed and included in a subsequent multivariate logistic regression with backward selection. Clinical variables and PROs were evaluated separately, then combined for a final multivariate model with p-value < 0.05.

The cohort included 327 patients (median age: 47 years [range: 18-85], primarily white [78%] males [55%] with high-grade tumors [73%]). Perceived cognitive impairment occurred in 29% of patients. Patients presenting with cognitive dysfunction at diagnosis, or who had undergone multiple surgeries, were more likely to have poor PCF, as were those currently on corticosteroids and reporting cognitive symptoms and symptom interference. Evaluated together, a multivariate model found that only higher scores on symptom interference and the cognitive symptom factor increased the likelihood of cognitive impairment (symptom interference odds ratio [OR] = 1.25, 95% confidence interval [CI] [1.09, 1.44], p < 0.001; cognitive symptom factor OR = 1.81, 95% CI [1.50, 2.19], p < 0.001) with an 84% classification rate.

Self-reported cognitive symptoms and interference were the strongest patient-reported correlates of PCF and should be interpreted as concurrent associations among related constructs. Further psychometric and longitudinal work is needed to clarify the incremental clinical value of the Neuro-QoL Cognition Function Short Form in PBT care and research.

During radiation therapy, liver tumor motion can reduce dose delivery accuracy and increase irradiation of adjacent healthy tissues. Because liver tumors are difficult to visualize directly on kilovoltage (kV) X-ray images, fiducial markers are commonly implanted as surrogates for tumor position during treatment. Conventional marker-segmentation approaches such as template matching can lose accuracy when markers are obscured by bone, surgical clips, or stents. Although Convolutional Neural Network (CNN)-based approaches have shown strong performance for image analysis, their application has been constrained to more static organs such as the prostate or has used single-center and vendor-specific datasets, limiting assessment of model transportability across different institutions and anatomic sites.

The aim of this study was to develop, integrate, and evaluate a CNN-based method for fiducial marker detection in kV X-ray images to support real-time image-guided radiation therapy (IGRT) during liver radiotherapy using a multi-institutional, multi-platform dataset spanning both large and fast free-breathing motion and slow and small breath-hold motion.

A compact Convolutional Neural Network (CNN) was trained on 314,625 kilovoltage (kV) X-ray images encompassing 28 patients from the multi-institutional TROG 17.03 LARK clinical trial (NCT02984566). The model was validated using a hold-out set of 31,463 images (10%) from the same cohort of 12 patients and 55 treatment fractions, spanning three centers and three respiratory motion-management techniques. The CNN was tested on 4184 images from 16 patients and 55 fractions across three centers and three motion-management techniques. The ground truth for testing was manually segmented marker positions from every 10 degrees of gantry rotation for each fraction of each test patient. Based on AAPM guidelines (TG147 and TGB135.B), feasibility for clinical implementation was predefined as > 95% of marker positions being within 2 mm of the ground truth position in each dimension, and processing time less than 150 ms per image using a simulated real-time Kilovoltage Intrafraction Monitoring (KIM) framework. Additional evaluation metrics included sensitivity, specificity, and the area under the precision-recall curve (AUC).

For the unseen test patient data, the marker position was segmented by the CNN within 2 mm in 95.4% of frames on the X axis and 97.6% of frames on the Y axis, meeting AAPM criteria. Sensitivity reached 97.76%, specificity was 99.94%, and the AUC was 0.9964. No statistically significant difference in localization error was observed between breath-hold and free-breathing treatments, although this comparison was limited by the small number of free-breathing patients. Localization error differed significantly between Varian and Elekta linacs due to imbalance within the dataset. The processing time for each image was 50-60 ms using a NVIDIA GeForce RTX 3070 GPU.

A CNN-based method for fiducial marker detection in the liver was developed and evaluated on multi-institutional kV X-ray images spanning free-breathing and breath-hold motion, as well as Varian and Elekta linac platforms. The method satisfied the predefined feasibility criteria for positional accuracy and computation time, supporting future translation toward clinical implementation.

Gastric cancer (GC) remains a major cause of cancer-related mortality worldwide, with prognosis and treatment costs strongly influenced by disease stage at diagnosis. Endoscopic GC screening has been proposed for intermediate-to-high-risk countries, although its economic feasibility remains uncertain. This study evaluated the costs associated with opportunistic GC screening integrated into a colorectal cancer screening programme and compared modeled early-stage management scenarios with the real-world costs of managing Stages II-IV disease.

A retrospective cost-comparison study was conducted from the perspective of the Portuguese National Health Service. Screening costs were derived from 377 fecal immunochemical testing-positive individuals undergoing one-time opportunistic esophagogastroduodenoscopy (EGD) during colonoscopy within the organized colorectal cancer screening programme, and treatment costs from a retrospective cohort of 222 patients with gastric adenocarcinoma. Direct medical costs were analyzed according to disease stage and compared with two modeled early-stage management scenarios.

Gastric precancerous conditions were identified in 46.9% of screened individuals, and gastric adenocarcinoma was detected in 0.8% (3/377). The estimated screening cost was €17,249 per cancer detected. Mean treatment and follow-up costs per patient were €32,140 for Stage II disease, €33,073 for Stage III disease, and €19,287 for Stage IV disease. The estimated cumulative cost of screening followed by ESD was €27,624, whereas screening followed by surgical treatment of Stage I disease was estimated at €44,493.

GC management is associated with substantial healthcare expenditure. The potential economic value of opportunistic GC screening is likely to depend on the detection of lesions amenable to endoscopic treatment.

NCT07522320.

Although chronic lymphocytic leukemia (CLL) typically follows an indolent course involving blood, lymph nodes, and bone marrow, extranodal organ involvement is rare and poorly characterized.

We retrospectively analyzed 19 patients with histologically confirmed extranodal CLL or small lymphocytic lymphoma (SLL), assessing organ involvement, clinical features, genetic risk factors, and response to therapy.

Different organs were affected, most frequently the kidneys (7/19). Median age at initial CLL diagnosis was 54 years, median time from CLL diagnosis to extranodal manifestation was 3 years. Genetic risk factors were comparable to typical CLL cohorts. Per treatment episode, exploratory overall response rate (ORR) for Bruton tyrosine kinase inhibitors (BTKi) was 88.9% (8/9); median progression-free survival (PFS) from treatment initiation was 29 months. For venetoclax-based regimens, ORR was 83.3% (5/6) and median PFS 52 months.

These data suggest meaningful activity of BTK and BCL-2 inhibitors in CLL/SLL with extranodal organ involvement.

Neoadjuvant chemotherapy (NAC) for colorectal cancer liver metastasis (CRLM) remains a major clinical challenge, with outcomes varying widely among patients, yet the mechanisms that drive therapeutic resistance remain incompletely understood. In this study, we integrated single‑cell RNA‑sequencing and spatial transcriptomics of patient tumor specimens to dissect the interplay between the hepatic tumor microenvironment and chemotherapy resistance. We identified a specific macrophage subpopulation marked by elevated expression of Secreted Phosphoprotein 1 (SPP1) that is significantly enriched in insufficient responders to NAC. Mechanistically, these SPP1 + macrophages exhibit a pro‑tumoral transcriptomic profile and directly suppress CD8 + T cell cytotoxic function through the SPP1‑CD44 signaling axis, as demonstrated by in vitro co‑culture assays, a large‑scale tissue microarray, and multiple syngeneic mouse models. Spatially, they are scattered throughout the tumour and form dense barriers that sequester CD8 + T cells and drive their exhaustion. Strikingly, this spatial configuration inversely correlates with cytotoxic activity and adaptive immune signatures and thereby reinforces a local immunosuppressive niche that sustains chemoresistance. These data provide the missing link: effective chemotherapy requires an immune‑active hepatic microenvironment, and SPP1 + macrophage infiltration actively disrupts this state, which in turn promotes clinical resistance. In a preclinical CRLM model, SPP1 blockade synergised with anti‑PD‑1, inducing significant tumour regression and restoring T‑cell function. Collectively, our findings position SPP1 + macrophages as central drivers of NAC resistance in CRLM and highlight the spatial immune barrier they create as a promising therapeutic target for overcoming chemoresistance and improving immunotherapy responses.

Left ventricular ejection fraction (EF) and global longitudinal strain (GLS) are widely used for cardiac surveillance in patients receiving potentially cardiotoxic cancer therapy. While GLS is more sensitive for detecting early myocardial dysfunction, the relationship between EF and GLS in routine clinical practice remains incompletely characterized, and discordance between these parameters may complicate clinical interpretation.

This retrospective observational study included 117 oncology patients undergoing serial echocardiographic assessment at baseline, early follow-up (6-12 weeks), and short-term follow-up (3-6 months). EF was measured by biplane Simpson's method, and GLS by speckle-tracking echocardiography as absolute values. EF deterioration was defined as a ≥ 10% absolute reduction or EF < 53%, while GLS deterioration was defined as a ≥ 15% relative reduction in absolute GLS magnitude. Concordance between EF and GLS deterioration was assessed, using Cohen's kappa and McNemar's test.

Mean EF and GLS values remained stable (EF p = 0.124; GLS p = 0.803). EF deterioration occurred in 32 patients (27.4%), and GLS deterioration in 25 patients (21.4%). Discordance was common, with isolated GLS deterioration in 17 patients (14.5%), and EF deterioration without GLS decline in 24 patients (20.5%), representing discordance in 41% of patients. Agreement was poor (κ = 0.05), and McNemar's test was not significant (p = 0.27). ΔGLS showed a weak association with ΔEF (r = 0.19, p = 0.036).

Although systolic function remained stable overall, clinically relevant deterioration occurred in a subset. Frequent EF-GLS discordance highlights their complementary but non-interchangeable roles in cardio-oncology surveillance.

To develop a scientifically sound and feasible death education program tailored to the needs of family caregivers of patients with advanced cancer, aimed at guiding clinical practice and enhancing the effectiveness of death education.

Family caregivers serve as crucial social support for patients with advanced cancer. Beyond bearing heavy caregiving responsibilities, they must also manage negative emotions arising from the patients' advanced illness or death. Family caregivers' levels of death anxiety may even exceed those of the advanced cancer patients themselves. Death education can transform individuals' attitudes toward death, alleviate death anxiety, reduce fear of death, and promote awareness and understanding of life. Currently, death education for family caregivers of patients advanced cancer receives limited attention, and comprehensive death education programs tailored to this group are lacking.

An initial draft of a death education program, specifically tailored to address the needs of family caregivers providing care for patients with advanced cancer, was systematically developed through a quantitative survey, semi-structured interviews and literature review. The program was then refined through two rounds of Delphi expert consultation and pilot testing.

The two rounds of Delphi expert surveys distributed 18 and 15 questionnaires, respectively. The valid response rates were 83% and 100%, with expert authority coefficients of 0.858 and 0.870, and Kendall's coefficient of concordance of 0.234 and 0.272 (P < 0.001). After Delphi expert consultation and pilot testing, the final program comprised 5 primary items, 17 secondary items, and 54 tertiary items. In the pilot test, the recruitment rate was 83% and the completion rate was 70%, providing preliminary evidence of the program's acceptability and feasibility.

By systematically integrating quantitative survey findings, qualitative interview findings, literature review evidence, Delphi expert consultation, and pilot testing, this study developed a death education program specifically designed to meet the needs of family caregivers of patients with advanced cancer. The program development process was scientifically sound and reliable, and the program content was comprehensive and targeted. The pilot test provided preliminary evidence of acceptability and feasibility; however, further validation in larger samples and real-world clinical settings is needed.

This study presents EffAtt-LungNet, an attention-guided deep learning framework for three-class lung histopathology classification. The model combines an EfficientNetB3 backbone with the Convolutional Block Attention Module (CBAM) to refine features and improve discrimination among benign lung tissue, lung adenocarcinoma, and lung squamous cell carcinoma. Experiments used the publicly released LC25000 lung subset, which contains 15,000 images across three classes and was itself produced by augmenting a smaller collection of underlying histopathology images. We generated 10,500 additional fixed variants, creating a balanced working corpus of 25,500 images with training, validation, and test partitions of 15,300, 2,550, and 7,650 images. EffAtt-LungNet reached 99.86% accuracy, 99.86% precision, 99.86% recall, 99.86% F1 score, and 0.9997 AUC on the image-level test partition. Performance was stable across five random seeds (mean accuracy 99.86±0.02%), and paired errors differed from those of the EfficientNetB3 backbone (McNemar's test, χ2=47.27, p < 0.001). Because pre-augmentation source identifiers for the released LC25000 images were unavailable, independence at the earliest source-image level could not be confirmed. The results therefore represent internal tile-level benchmark performance and require validation on independent, non-augmented, multi-centre datasets before any translational or clinical claim can be made.

Genomic or transcriptomic sequencing guides the precision of cervical cancer (CC) diagnosis; however, the molecular profile of Asian patients remains poorly understood. We established a comprehensive multi-omics cohort comprising 112 tumor-normal adjacent tissue pairs from Chinese CC patients. Our integrated analysis revealed a mutational burden comparable to other populations, with three major mutational signatures primarily attributed to APOBEC-associated, age-associated, and DNA repair-associated biological categories. Multi-omics profiling elucidated the functional consequences of somatic mutations and copy number variations, identifying PIK3CA, EP300, and MPRIP as key driver events. We further uncovered both concordant and discordant activation patterns across cancer-related signaling pathways. Transcriptomic and proteomic analyses nominated cell cycle regulation, epithelial-mesenchymal transition, and LAMC2 as promising diagnostic and therapeutic targets. Comprehensive immune characterization enabled stratification of patients into three major immune phenotypes with varying microenvironmental profiles. This study provides valuable resources and novel insights into the molecular architecture of cervical cancer in the Chinese population, identifying potential biomarkers to guide precision detection and immunotherapy strategies.