Individuals with breast cancer (BC) experience significant psychological distress, yet their utilization of mental health services remains low. This study identified key factors influencing help-seeking behavior through integrated Theory of Planned Behavior (TPB) and Health Belief Model (HBM) frameworks. We conducted in-depth interviews (IDIs) with eight BC patients and nominal group technique (NGT) with six health professionals, followed by Fuzzy Delphi Method (FDM) to assess expert consensus. The IDIs revealed that the individuals with BC recognized the value of professional psychological support but were reluctant to engage with these services personally. The participants identified emotional thresholds for help-seeking, expressed preference for informal support networks, and demonstrated varied understanding of mental health professional roles. The FDM evaluation demonstrated strong expert consensus across all assessed elements, particularly those related to emotional support mechanisms. Three barrier categories emerged: individual factors (mental health literacy, autonomy preferences), social factors (family support, cultural stigma), and systemic factors (healthcare integration gaps). Expert consensus exceeded 80% agreement across all domains.This study identified a complex interplay between individual psychological barriers and systemic factors affecting mental health help-seeking among individuals with BC. Effective interventions must address psychological barriers and healthcare delivery factors while respecting individual autonomy in coping choices. A multi-level approach targeting individual education, family support systems, and healthcare integration is recommended to improve mental health service utilization among individuals with BC.

Advancements in deep learning technologies and an increase in medical data have enhanced the accuracy of disease diagnosis and treatment strategies. Notably, significant progress has been made in the use of deep learning-based time-series prediction models for short-term disease onset prediction and analysis of important features. However, research on explainable deep learning for long-term disease progression, such as cancer and chronic diseases, still faces challenges. The difficulty in estimating explainable gradual disease progression from observable patient test data is a key factor. To address this issue, we propose a new approach called the "deep state-space analysis framework." This framework utilizes sequentially obtained electronic health records (EHRs) to estimate and visualize temporal changes in the latent states of patients related to disease progression. It enables the clustering of latent patient states according to the severity of disease progression and identifies key factors leading to a poor prognosis with medication. To validate our framework, a detailed analysis of data from 12,695 patients with cancer was conducted. The estimated transitions of the latent states capture the clinical status of the patients and their continuous temporal changes. Furthermore, anemia was identified as a poor prognostic factor during state transitions in patients with cancer. Significant features were also confirmed, such as immune cell abnormalities, which are poor prognostic factors in patients treated with Nivolumab, Osimertinib, and Afatinib. This technological innovation deepens our understanding of disease progression and supports early treatment adjustments, prognostic evaluations, and the formulation of optimal long-term strategies. With the advancements in deep learning, its application in healthcare has even greater potential.

Patients with cancer who develop acute abdomen are at high risk of rapid clinical deterioration and often require emergency surgery and intensive care. This retrospective cohort study evaluated the impact of implementing a Rapid Response System (RRS) on survival among 274 patients admitted for emergency surgery at a tertiary cancer center in Korea (145 pre-RRS, 129 post-RRS). Although the post-RRS group had a higher burden of severe illness, including more metastatic disease and higher APACHE II scores, key time intervals from diagnosis to ICU admission, surgery, and antibiotic administration were significantly shorter following RRS implementation. The post-RRS group also demonstrated more favorable postoperative physiological trajectories, including lower postoperative day 7 SOFA scores and greater reductions in SOFA from baseline. Survival to discharge was higher after RRS implementation (85.27% vs. 74.48%, p = 0.039), and RRS activation remained independently associated with improved survival in multivariable analysis (adjusted odds ratio: 3.554, p = 0.021). Patients presenting outside RRS coverage hours had higher severity, longer delays to intervention, and lower survival; in an exploratory counterfactual model, predicted survival increased from 59.4% to 71.0% when RRS availability was hypothetically extended. These findings suggest that RRS implementation may attenuate progression of organ dysfunction and improve survival among high-risk cancer patients with acute abdomen. Expanding RRS operational hours, including continuous 24-hour coverage, may offer additional clinical benefit.

Social isolation is a growing public health concern, particularly among cancer survivors who face persistent challenges in maintaining social connections following treatment. While its impact on mental health is increasingly recognized, the underlying pathways and contextual differences across rural and urban settings remain underexplored. This study aimed to identify the psychosocial and personal factors that contribute to perceived social isolation among U.S. cancer survivors and to assess how isolation mediates the relationship between these factors and mental health. We also examined whether these associations differ between rural and urban populations. Data were drawn from the 2022 Health Information National Trends Survey (HINTS 6), with a subsample of cancer survivors (n = 926). A conceptual framework was developed using constructs from the Biopsychosocial Model, the Stress Process Model, the Transactional Model of Stress and Coping, and the Andersen Behavioral Model of Health Services Use. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used to evaluate the relationships among personal factors (age, BMI, time since diagnosis, inability of self-care), psychosocial perceptions (perceived care quality, cancer information comprehension, negative life perception), social isolation, and mental health (PHQ-4). Multigroup analysis compared rural and urban survivors. Social isolation was a strong predictor of mental health, with key antecedents including cancer information access, inability of self-care, time since diagnosis, negative life perception, and perception of care quality. Several pathways varied by geography; for instance, the effects of self-care difficulty and care perception on isolation and mental health were significant only in urban settings. This study highlights the central role of social isolation in shaping mental health outcomes among cancer survivors and underscores the importance of targeted, context-sensitive interventions to reduce isolation and promote psychosocial well-being, particularly in underserved rural communities.

Adults undergoing treatment for breast cancer (BC) are advised to participate in regular exercise. However, many struggle to exercise consistently due to the side effects of systemic treatments including nausea, fatigue, and pain. In adults with newly diagnosed BC, this trial will evaluate the effectiveness of a new exercise intervention, compared with usual care, on outcomes including health-related quality of life (HRQoL).

This randomised controlled trial is underway at an Australian tertiary hospital. The protocol was prospectively registered (Australian New Zealand Clinical Trials RegistryACTRN12623001168640p). Consenting adults with BC diagnosed within the prior six months, with planned chemotherapy and/or endocrine treatment will be randomised to an intervention or control group. Both groups receive usual physiotherapy and medical care. Those allocated to the intervention group are offered participation in the 'SMART' intervention (Self-determined, Monitored, Adaptable, Rehabilitation with Telehealth support). This involves 16-weeks of tailored, one-on-one physiotherapy-led exercise sessions including behaviour change techniques and the weekly goal of completing 150 minutes of aerobic exercise and two resistance training sessions. The primary outcome is HRQoL and secondary outcomes include physical assessments (muscle strength, exercise tolerance, body composition), healthcare utilisation, workplace absenteeism, mood, psychological determinants of behaviour change, chemotherapy completion rates and endocrine therapy completion. All outcomes are measured prior to randomisation and 16 weeks following randomisation. Additional assessments of all outcomes (excluding the physical assessment) occur at 8 weeks and 52 weeks following randomisation. Ongoing recruitment for two years from June 2024 is expected to achieve a sample size of 260. No results have been analysed.

If the SMART intervention produces favourable change, this will support its adoption in clinical practice. A greater understanding of factors including BC stage, treatment type or variables relating to the exercise program, that influence the magnitude of exercise-induced change on HRQoL will inform future exercise programs.

Sarcopenia is increasingly recognized as an important prognostic factor in oncology; however, its clinical relevance in liposarcoma remains insufficiently defined. This study aimed to evaluate longitudinal changes in CT-derived body composition parameters in liposarcoma patients, to assess the influence of tumor grade, recurrence, and treatment modalities on these parameters and to determine the association of baseline sarcopenia and progressive muscle loss with overall survival and functional status.

In a retrospective, single center study between 2010 and 2024, 64 patients were analyzed. All patients underwent surgical tumor resection of a histologically confirmed liposarcoma. Included were patients with two consecutive CT scans. The following morphometric parameters were measured on CT axial images at the height of lumbar vertebral 3: Skeletal muscle index (SMI), paraspinal muscle index (PSMI), psoas muscle index (PMI), skeletal muscle density (SMD), and visceral adipose tissue (VAT). Standardized Hounsfield unit thresholds were used for the assessment. Additionally, the influence of tumor grade, recurrence, and treatment modalities on body composition was assessed. A Kaplan Meier survival analysis was performed using data from the residents´ registration office. Survival was further analyzed by Cox regression using uni- and multivariate models. Metric data was compared using student´s t-test.

Significant reductions in SMI, PSMI, PMI, and VAT were observed over the disease course, particularly among patients with high-grade tumors, chemotherapy, or local tumor recurrence. Baseline sarcopenia and a progressive SMI loss were independently associated with reduced overall survival. In multivariate analysis, baseline sarcopenia (HR: 2.331, p = 0.007) and a ≥ 15% SMI decline (HR: 2.601, p = 0.006) remained significant predictors of mortality. Both markers did not correlate with changes in Eastern Cooperative Oncology Group (ECOG) performance status.

CT-morphometric parameters deteriorate substantially during the disease course of liposarcoma patients and serve as independent predictors of survival. These findings support the integration of CT-based body composition analysis into routine oncologic assessment and highlight its potential role in identifying high-risk patients for early supportive intervention.

to investigate the effect of tumor location on oncological outcomes in patients receiving robot-assisted radical nephroureterectomy (RANU) for upper urinary tract carcinoma (UTUC).

A retrospective single-center cohort study of 54 patients with UTUC who underwent RANU by a single surgeon between July 2019 and July 2025, without neoadjuvant chemotherapy or previous or simultaneous cystectomy, were included. Patients were divided into two groups based on tumor location: 18 patients (33%) with ureteral tumors (Group 1) and 36 patients (67%) with renal pelvis tumors (Group 2). Demographics, perioperative data, and pathological results were analyzed. The primary endpoints Cancer-specific survival (CSS) and overall survival (OS) were estimated using Kaplan-Meier and univariable log-rank test.

Console time, blood transfusion, complications, and readmission were comparable in both groups. Group 1 experienced longer hospital stays (8 days vs. 6.5 days, p = 0.03). 48% of patients had ≥ pT2 disease, with a similar T-stage distribution across groups. Of 26 candidates for adjuvant therapy, 10 received chemotherapy with gemcitabine/cisplatin, 2 received nivolumab, and one patient received enfortumab vedotin with pembrolizumab. During a median 26.5-month follow-up, six patients developed bladder recurrence, (median 9 months) after RANU (p = 0.10), and four developed distant metastases (median 4 months) (p = 0.72), resulting in a disease-free survival of 81% (p = 0.08)Cancer-specific survival was 94%, overall survival 89%, with no significant group differences (p = 0.24 and 0.49).

In our series, we observed that tumor location does not impact postoperative and oncological outcomes after RANU for UTUC, regardless of adjuvant therapy. However, further studies are needed to explore this proposed hypothesis.

IntroductionThis retrospective study aimed to investigate the correlation between TP53 identified via next-generation sequencing (NGS) and p53 expression in colorectal adenocarcinoma (CRC), as assessed by immunohistochemistry (IHC). Additionally, we characterized p53 IHC staining patterns and sought to determine the optimal threshold for p53 expression as a surrogate for TP53 mutation status.MethodsIn this retrospective cohort analysis, we included 294 archived surgically resected CRC specimens from patients who did not receive preoperative chemotherapy were analyzed. All data were collected from pathology database and electronic medical records. TP53 mutations were identified using NGS, and p53 expression was evaluated by IHC. The correlation between mutation status and IHC staining patterns was assessed, and sensitivity and specificity were calculated.ResultsThe TP53 mutation rate was 78.2%, comprising missense (68.4%), nonsense (12.4%), frameshift (11.0%), and splice-site (8.3%) mutations. Missense mutations were associated with nuclear p53 staining, while frameshift mutations mostly showed loss of expression. Nonsense and splice-site mutations exhibited diverse patterns, including loss of expression, nuclear staining with/without cytoplasmic staining, or cytoplasmic staining alone. Among cases with loss of p53 expression, the TP53 mutation rate was 88.9%. When the proportion of strong p53-positive cells exceeded 55%, the missense mutation-positivity rate increased significantly (P < 0.05). The sensitivity and specificity of p53 IHC in predicting TP53 mutations were 92.3% and 94.8%, respectively.ConclusionsCRC predominantly exhibited missense TP53 mutations. p53 IHC revealed diverse expression patterns, including overexpression, complete loss, cytoplasmic staining, and normal-type patterns. Strong p53 expression (>55%) correlated closely with TP53 missense mutations, supporting IHC as a reliable surrogate. However, cases showing loss of p53 expression should undergo gene sequencing to confirm mutation status.

ObjectiveTo compare long-term survival in early-stage breast cancer patients treated with different radiation therapy modalities.MethodsData was retrospectively derived from SEER database. We compared overall survival (OS), breast cancer specific survival (BCSS) and second primary malignancies (SPM) in early-stage breast cancer patients treated with postoperative radiotherapy (PORT) versus those treated neoadjuvant radiotherapy (NART) and intraoperative radiotherapy (IORT) after propensity score matching by 1:1.ResultsA total of 457,166 patients were included in this study. After matching, the 20-year OS of 1441 patients in NART cohort was lower than that in PORT cohort (p < 0.01), particularly in hormone receptor positive patients (p < 0.01). NART were dependent prognostic factors for 20-year OS [Hazard Ratio (HR):1.21, 95%CI: 1.06-1.38, p < 0.01). No significant difference in BCSS was observed between NART and PORT treatments. Additionally, patients undergoing NART had a lower risk of all SPM (p = 0.01) and second solid cancers (p = 0.02) but a comparable risk of second hematological malignancies (p = 0.55) than patients administered PORT. HR-positive was a risk factor for SPM. No OS, BCSS or SPM risk difference were significantly observed in the 2096 pairs of IORT and PORT groups.ConclusionCompared to PORT, NART and IORT don't offer survival advantages for early-stage breast cancer patients. Altering the sequence of radiotherapy requires careful evaluation.

While life expectancy in the US has increased among both sexes, a significant sex gap in mortality has been consistently observed during the past 2 decades.

To examine differences in mortality rates between males and females for overall mortality and the leading 9 causes of mortality (coded by the National Death Index as diseases of the heart, malignant neoplasms, chronic lower respiratory diseases, unintentional injuries, cerebrovascular diseases, Alzheimer disease, diabetes, influenza and pneumonia, and nephritis, nephrotic syndrome, and nephrosis).

This prospective cohort study included adults 20 years or older participating in the National Health and Nutrition Examination Survey (NHANES) cycles between 1999 and 2016. Data were linked to the National Death Index from the date of survey participation through December 31, 2019. Data were analyzed from July 16, 2024, to August 14, 2025.

Participation in the 1999-2016 NHANES cycles.

Cox proportional hazards regression was used to estimate male-to-female hazard ratios (MF HR) for overall and cause-specific mortality, adjusting for sociodemographic characteristics (eg, age, race and ethnicity), behavioral factors (eg, smoking, alcohol use), and chronic conditions (eg, diabetes, hypertension). The adjusted MF HRs were stratified by self-rated health, race and ethnicity, income, and educational level.

Among 47 056 participants (52.0% female and 48.0% male [weighted]), 12.9% (12.2% females and 13.6% males) were deceased at the end of follow-up. Males had a 63% higher risk of all-cause mortality compared with females, with the largest difference in mortality among individuals who died from heart disease (MF HR, 1.96; 95% CI, 1.72-2.24). The MF HR differed significantly across race and ethnicity for heart disease (range, 0.92 [95% CI, 0.36-2.35] for individuals of other race or ethnicity to 2.11 [95% CI, 1.80-2.48] for White individuals; P = .02 for interaction) and across income quartiles for mortality due to cerebrovascular diseases (range, 0.59 [95% CI, 0.25-1.38] for highest to 2.25 [95% CI, 1.31-3.86] for lowest income; P = .03 for interaction) and accidents (range, 0.57 [95% CI, 0.16-1.99] for highest income to 2.40 [95% CI, 1.03-5.58] for third highest income; P = .02 for interaction). No difference in the MF HR was found across self-rated health categories or education attainment levels. Information on covariates was largely collected by self-report, resulting in underreporting or overreporting due to social desirability bias. How these factors may have changed leading up to the time of mortality could not be accounted for.

In this cohort study of adult NHANES participants, after accounting for a wide range of risk factors, the sex gap in mortality remained for most causes of mortality, suggesting there may be intrinsic biological factors (eg, sex hormones, chromosomes, immune response) associated with sex differences in mortality. Further research should investigate the effects of sex-linked biological factors on mortality.