To evaluate the effectiveness of a staged health education pathway in the perioperative care of patients with esophageal cancer.

A total of 110 patients who underwent radical surgery for esophageal cancer and were discharged from our department between January and November 2022 were enrolled in the study. Patients were divided into a control group and an experimental group (55 patients each) based on the order of admission. The control group received routine health education, in which the responsible nurses provided subjective and random health guidance based on patients' daily treatment and condition. The experimental group received education based on a standardized staged health education pathway checklist. The two groups were compared in terms of discharge readiness scores and health education effectiveness, assessed using the Health Education Evaluation Criteria for Thoracic Surgery Patients.

The discharge readiness scores in the experimental group were significantly higher than those in the control group (P < 0.01). In addition, the experimental group outperformed the control group in overall health education scores and in the dimensions of health knowledge, health beliefs, and health behaviors, with statistically significant differences (P < 0.01).

The application of a standardized staged health education pathway checklist in the perioperative period of esophageal cancer patients allows nurses to provide more systematic and timely health guidance. This approach helps patients and their families gain a more comprehensive understanding of the disease and better meets their health information needs.

Bladder cancer has high morbidity and mortality rates when it is diagnosed at an advanced stage. The aim of our study is to determine the effect of the DR-70 protein in the diagnosis of bladder cancer and to evaluate its relationship with the grade of the disease.

Serum samples from 60 patients with bladder cancer and 24 control patients with macroscopic hematuria of benign etiology were included in the study. DR-70 levels were compared between the bladder cancer group and the control group. Additionally, a comparison was made between patients with non-muscle invasive bladder cancer and those with muscle invasive disease.

The median DR-70 level in the bladder cancer group was 1.08 U/mL (0.48-8.5), whereas it was 0.89 U/mL (0.29-1.76) in the control group. The DR-70 level was significantly greater in the bladder cancer group than in the control group (p = 0.012). DR-70 had a sensitivity of 73.3% and a specificity of 66.7% in detecting bladder cancer. On the other hand, the median DR-70 level was 1.06 U/mL (0.48-4.09) in patients with non-muscle-invasive bladder cancer (Ta, T1) and 2.66 U/mL (0.57-8.5) in patients with invasive bladder cancer (T2). DR-70 levels were significantly greater in patients with invasive bladder cancer than in those with non-muscle invasive bladder cancer (p = 0.021). Additionally, DR-70 had 72.7% sensitivity and 63.3% specificity in detecting muscle invasive bladder cancer.

Compared with that in the control group, the protein level of DR-70 significantly increased in patients with bladder cancer and was greater in the group with muscle invasion.

This study evaluated the efficacy and safety of the triple combination of transcatheter arterial chemoembolization (TACE), lenvatinib, and tislelizumab in patients with advanced unresectable hepatocellular carcinoma.  METHODS: Patients with confirmed HCC in Barcelona Clinic Liver Cancer stage C were included. Patients were initially treated with TACE, followed by intravenous tislelizumab (200 mg, IV) every 21 days and lenvatinib (8 or 12 mg/day) once daily. The primary endpoint was objective response rate based on the modified Response Evaluation Criteria in Solid Tumors (mRECIST). The secondary endpoints included disease control rate based on mRECIST, objective response rate and disease control rate based on the Response Evaluation Criteria in Solid Tumors (version 1.1), overall survival (OS), progression-free survival (PFS), time to progression (TTP), duration of response (DOR), and safety. An exploratory endpoint was systemic immune-inflammation index (SII).

Thirty-one patients with advanced unresectable HCC were enrolled. The objective response rate was 74.2% and disease control rate was 87.1% based on mRECIST. The median OS was 12.6 months and median PFS was 6.5 months. The median TTP was 8.2 months, and median DOR was 7.3 months. Treatment-related adverse events occurred in 64.5% of patients, and most events were grade1-2. The rate of grade ≥3 events was 19.4%. Overall survival and progression-free survival after triple therapy were better in patients with lower SII at baseline.

The combination of TACE, lenvatinib, and tislelizumab can be effective against advanced unresectable HCC, leading to a relatively high objective response rate and tolerable safety profile. SII may be useful for predicting response to this triple therapy.

ClinicalTrials.gov identifier: NCT05131698, registered 4 November 2021.

Patients with hematologic malignancies may experience prolonged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This study aimed to evaluate risk factors for persistent SARS-CoV-2 infection in patients with hematologic malignancies based on nucleic acid amplification test (NAAT) results. Patients with SARS-CoV-2 NAAT positivity lasting ≥ 8 weeks (persistent NAAT-positive group) were compared with those who became NAAT-negative within 8 weeks (non-persistent NAAT-positive group).

We examined patients with COVID-19 and hematologic malignancies between April 2021 and January 2023 at Tenri Hospital in Japan, examining hematologic malignancy type, chemotherapy regimens, and laboratory data.

NAAT results at 8 weeks were available for 43 patients; eight (19%) remained positive for 8 weeks or more, while 35 (81%) became negative in < 8 weeks. Univariate analysis between the two groups showed significant differences in disease severity (p = 0.001), anti-CD20 monoclonal antibodies (mAb) use within the past 6 months (7/8 [88%] vs. 16/35 [46%], respectively; p = 0.05), obinutuzumab use within the past 6 months (3/8 [38%] vs. 2/35 [6%], respectively; p = 0.037), and anti-CD20 mAbs maintenance treatment (3/8 [38%] vs. 1/35 [3%], respectively; p = 0.016). COVID-19-related mortality was higher in the persistent group (3/8 [37.5%] vs. 0/35 [0%], p = 0.005). Seven of the eight patients in the persistent NAAT-positive group had malignant lymphomas, and five had follicular lymphoma.

The use of anti-CD20 mAbs, especially obinutuzumab and maintenance treatment, is associated with long-term SARS-CoV-2 infection in patients with hematologic malignancies.

Breast cancer remains a leading cause of mortality in women worldwide, with notable disparities in incidence and prognosis across regions. This systematic review explores the application of Deep Learning-based computer-aided diagnostic (CAD) systems for breast cancer detection, with a special focus on Asia to highlight underrepresented perspectives and challenges.

We conducted a systematic Literature review in accordance with PRISMA guidelines. A comprehensive search of Scopus and Web of Science databases was performed to identify relevant studies published between January 2018 and November 2023, with an additional hand search for recent studies from 2024 to 2025. After screening 1051 records, 287 articles were included based on predefined inclusion and exclusion criteria. Quality assessment focused on the relevance of deep learning-based approaches to mammographic breast cancer detection, emphasizing global research trends and focused analysis of studies involving Asian populations.

The review identified major research trends in deep learning-based mammographic analysis, with most studies focusing on lesion classification while comparatively fewer addressed detection, segmentation, and breast density assessment. Studies using Asian datasets revealed unique challenges, including higher breast density, limited annotations, and under-representation in public datasets. Analysis of methodologies highlighted varied use of image preprocessing and augmentation techniques. Focus maps were used to visualize contributions across tasks and populations, revealing gaps in multi-class BI-RADS classification and a global research bias toward Caucasian datasets (> 80%).

This review reveals that most deep learning models for breast cancer detection are trained predominantly on Caucasian datasets, creating significant limitations when applied to other populations due to demographic differences in breast density and imaging characteristics. To improve breast cancer screening globally, researchers must develop deep learning systems using diverse datasets that represent different populations, validate these models across various ethnic groups, and ensure clinical testing includes women from multiple demographic backgrounds.

PROSPERO CRD 42,023,478,896.

Microvascular invasion (MVI) is of great significance for the individualized treatment of hepatocellular carcinoma (HCC) and preoperative noninvasive prediction of MVI is still an urgent clinical problem. To explore the effects of different regions of interest (ROI) and image input dimensions on the performance of deep learning (DL) models, and to select the best result to develop and validate a DL model for preoperative prediction of MVI.

A total of 206 patients with pathologically confirmed HCC from three hospitals were retrospectively enrolled and divided into training, internal validation and external test set. Based on hepatobiliary phase images (HBP) of gadoxetic acid-enhanced MRI, 2D DL, 3D DL and 2.5D deep multi-instance learning (MIL) models were established. The receiver operating characteristic curve (ROC) was used to evaluate the predictive efficacy of the above models. Based on the optimal performance model, the T1WI-FS and T2WI-FS images were preprocessed correspondingly, and a multimodal prediction model including three sequences was constructed. The ROC, and decision curve were used to visualize the predictive ability of the model.

Compared with 2D DL and 3D DL models, the 2.5D DL model based on all axial images of ROI had the highest performance, with the AUC values of 0.802 (95% CI, 0.669-0.936) and 0.759 (95% CI, 0.643-0.875) in the validation and test sets. The AUCs of the multimodal MRI model were 0.954 (95% CI, 0.920-0.989) in the training set, 0.857 (95% CI, 0.736-0.978) in the validation set, and 0.788 (95% CI, 0.681-0.895) in the test set.

The DL model that selects all axial slices of intratumor and peritumor as input shows robust capability in predicting MVI, which is expected to help clinical decision-making of individualized treatment for HCC.

Awake craniotomy is the gold standard for resecting brain tumors in eloquent areas. This technique requires tailored anesthetic management to ensure patient safety and cooperation. We aimed to describe clinical characteristics, anesthetic management, and intraoperative outcomes in patients undergoing awake craniotomy at a high-complexity hospital in southwestern Colombia.

We conducted a retrospective case series. Sociodemographic, clinical, and intraoperative data were obtained from electronic medical records. Descriptive statistics were used to summarize the findings.

Fifteen patients underwent awake craniotomy with monitored anesthesia care using dexmedetomidine and remifentanil. All patients received a scalp block, non-opioid analgesics, and antiemetic prophylaxis. The most frequent adverse event was transient bradycardia without hemodynamic instability. No respiratory or neurological complications occurred. All procedures were successfully completed.

Awake craniotomy under monitored anesthesia care with dexmedetomidine and remifentanil was feasible, safe, and well tolerated in this cohort. The absence of serious complications highlights the value of structured anesthetic protocols and trained multidisciplinary teams. This experience provides reference for the adoption of similar strategies in hospital settings across Latin America, where implementation of awake craniotomy remains limited.

Gastric cancer remains a major clinical challenge with poor prognosis. This study investigated survival outcomes based on treatment strategy, tumor stage, and histology in Danish gastric cancer patients.

From January 2013 to December 2021, 2,156 gastric cancers were registered in the Danish Esophagogastric Cancer Group database, covering 99% of national cases. Data were analyzed for patients with intestinal and diffuse-type cancers. Survival was assessed using Kaplan-Meier curves and Cox regression, adjusting for tumor stage, treatment, and demographics.

Median survival was significantly higher with surgery ± perioperative chemotherapy (SCT) than with palliative treatment. For the intestinal-type cancers, SCT resulted in a median survival of 45.2 months (95% CI [35.4-55.1]) versus 5.1 months (95% CI [4.6-5.7]) with palliative treatment. Patients with diffuse type, treated with SCT had a median survival exceeding 128 months, compared with 6.3 months (95% CI [5.2-7.5]) with palliative treatment. Patients receiving epirubicin based CT had a lower risk of death (HR 0.74, p = 0.04) compared with upfront surgery, while FLOT (5-fluorouracil, leucovorin, oxaliplatin, and docetaxel) similarly reduced the risk of death (HR 0.69, p = 0.04). No significant difference was observed between the two CT regimens. Palliative CT and radiotherapy improved survival over best supportive care (p < 0.001). Advanced tumor stage was associated with worse survival, while the histological subtype had no impact on overall survival outcomes.

This study emphasizes the survival benefit of multimodal treatment strategies, especially surgery combined with perioperative CT. Palliative interventions also improved outcomes in advanced disease.

This study investigated the evolution of Low Anterior Resection Syndrome (LARS) over 2 years following Total Mesorectal Excision (TME) for rectal cancer.

In this prospective cohort study, patients were recruited from three Belgian hospitals between January 2017 and January 2021. The primary outcome was the evolution of LARS, assessed with the LARS score at 1, 6, 12, and 24 months postoperatively or after stoma closure. The proportion of patients in each LARS category (no, minor, major) was analyzed, and transitions over time were examined using Bowker's test of symmetry. The secondary outcome was health-related quality of life, measured using the Short Form-12 (SF-12) at the same time points.

Of 180 patients who underwent TME for rectal cancer, 87 (48.3%) completed the LARS score at all time points. At 1 month postoperatively, 66 patients (75.9%) had major LARS, decreasing to 51 patients (58.6%) at 6 months (p = 0.028). No significant changes were observed thereafter (p = 0.43 and p = 0.45 for 6 to 12 months and 12-24 months, respectively). Among the 51 patients with major LARS at 6 months, 10 patients (20%) improved by 12 and 24 months. Between 1 month and later time points, approximately 60% remained in the same category, 30% improved, and 10% deteriorated. Mean SF-12 physical and mental scores were similar across LARS categories at all time points.

The majority of spontaneous improvement in LARS occurred within the first 6 months postoperatively, with little improvement thereafter. These findings highlight the need for early proactive management rather than expectant follow-up.

The rate of lung cancer patients with chronic obstructive pulmonary disease (COPD) is increasing. This study aimed to identify the risk factors associated with COPD mortality in lung cancer patients and to develop a practical tool to achieve an accurate prediction of COPD mortality in lung cancer patients. Patient-related data for this study were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Risk factors for COPD mortality were identified using Cox regression analysis. The Kaplan-Meier curves were depicted to further validate associated risk factors. Variables screened by multivariate Cox regression analysis were used to construct a predictive model for the risk of COPD mortality. The performance of the model was evaluated using receiver operating characteristic (ROC) curves, calibration curves, and its clinical applicability was evaluated using decision curve analysis (DCA). 28,194 patients were randomized in a 7:3 ratio into a training cohort (n = 19,736) and a validation cohort (n = 8458). Cox regression analysis showed age, race, sex, grade, histological type, T stage, N stage, surgery, chemotherapy, bone metastasis, and marital status as independent factors influencing COPD mortality. The area under the curve (AUC) values of the model in the training cohort were 0.886, 0.870, and 0.873, respectively. In the validation cohort, the AUC values were 0.901, 0.888, and 0.879, respectively. The calibration curves further demonstrate the reliability and stability of the model. DCA indicated that the model could achieve more net clinical benefit. A clinical model for predicting the risk of COPD mortality in lung cancer patients was further constructed, which could provide risk assessment and clinical decision-making for individualized treatment of patients.