Immune checkpoint inhibitor (ICI)-related cardiovascular toxicity is associated with high mortality, and prediction models may facilitate its prevention and management. However, the predictive performance, quality, risk of bias, and applicability of existing models remain unclear.

To systematically review prediction models for ICI-related cardiovascular toxicity.

Nine databases were searched for studies on prediction models for ICI-related cardiovascular toxicity from inception to July 12, 2026. Data were extracted in accordance with the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies. The included models were assessed using the Quality, Risk of Bias, and Applicability Assessment Tool for Prediction Models Using Regression or Artificial Intelligence Methods. This systematic review was registered on PROSPERO (CRD420261296378).

A total of 34, 541 articles were identified, and 23 articles met the inclusion criteria. These 23 articles described 82 prognostic models (71 for predicting the occurrence risk of ICI-related cardiovascular toxicity and 11 for predicting the prognosis of this toxicity) and two diagnostic models. Modeling methods comprised logistic or Cox regression and machine learning algorithms. Common predictors included demographic characteristics, medical history, treatment-related characteristics, and laboratory and imaging parameters. The area under the receiver operating characteristic curves or C statistic ranged from 0.699 to 0.967 for apparent performance, 0.595 to 0.942 for internal performance, and 0.549 to 0.949 for external performance. Calibration and clinical utility were assessed in 20 and 15 models using calibration curves/Hosmer-Lemeshow test and decision curve/clinical impact curve analysis, respectively, in apparent, internal, or external performance validation. Models were presented using techniques such as nomograms, scoring systems, and regression equations. All models were graded as low quality, high risk of bias, and only seven models were graded as high applicability.

Existing prediction models have concerns regarding quality, risk of bias, and applicability, limiting their clinical practice. Currently, baseline and dynamic risk screening using relevant risk biomarkers is suggested to better manage ICI-related cardiovascular toxicity. Future research is warranted to validate and improve existing models or develop new prediction models with rigorous methods.

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420261296378.

Pembrolizumab, an immune checkpoint inhibitor (ICI) targeting programmed cell death protein 1 (PD-1), has demonstrated significant clinical value in the treatment of human epidermal growth factor receptor 2 (HER2)-negative advanced gastric cancer (GC) and gastroesophageal junction cancer (GEJC). However, due to the relatively short duration of existing studies, inconsistent survival benefits among patients, and the lack of a standardized risk assessment system, its efficacy and safety still remain controversial.

By systematically querying the following English-language databases, including PubMed, Embase, Web of Science, Scopus, Ovid, Cochrane Library, and CINAHL, along with the clinical trial registry ClinicalTrials.gov, studies reporting clinical efficacy and safety outcomes of pembrolizumab in patients with HER2-negative advanced GC or GEJC were identified. A meta analysis was subsequently conducted to pool objective response rate (ORR), duration of response (DoR), overall survival (OS), progression free survival (PFS), 12/24-month overall survival rate (OS-12/24), 12/24-month progression-free survival rate (PFS-12/24), as well as treatment related adverse events (TRAEs) and immune related adverse events (irAEs). Comprehensive subgroup analyses were further performed based on PD-L1 combined positive score (CPS), age, region, chemo backbone, and median follow-up.

Nine studies encompassing 3406 patients with HER2-negative advanced GC or GEJC were included. In randomized controlled trials (RCTs), pembrolizumab plus chemotherapy significantly improved ORR (OR 1.57, 95%CI:1.35-1.81) and OS (HR 0.82, 95%CI:0.75-0.89) compared with chemotherapy alone. Pooled median PFS from RCTs in the pembrolizumab arm was 6.77 months (95%CI:6.19-7.36) and from single-arm studies was 6.53 months (95%CI:4.59-9.31). Combination chemotherapy regimens showed numerically longer median OS (RCT combination subgroup median OS (mOS) 12.74 months vs monotherapy subgroup 10.60 months; single-arm combination cohort mOS 16.96 months). The most common TRAEs was decreased neutrophil count with an incidence of 24.9%, which was also the most common grade 3 or higher event. The most common irAEs was hypothyroidism (pooled incidence 21.4% in RCTs). Overall toxicity was manageable and safety outcomes were consistent across studies.

Pembrolizumab in conjunction with chemotherapy confers substantial clinical advantage in the management of HER2-negative advanced GC or GEJC, as evidenced by improvements in ORR, OS, and PFS. In contrast, the therapeutic efficacy of pembrolizumab monotherapy appears constrained. Vigilant surveillance for heightened hematologic and gastrointestinal toxicities is warranted within routine clinical practice.

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420261298020.

To investigate the predictive value of the cancer antigen-125 elimination rate constant K (KELIM) for treatment response and prognosis in patients with advanced high-grade serous ovarian cancer (HGSOC) undergoing neoadjuvant chemotherapy followed by interval debulking surgery (NACT-IDS), and to analyze the combined prognostic significance of KELIM and the mutation status of breast cancer susceptibility gene (BRCA).

A total of 106 patients with advanced HGSOC who had undergone NACT-IDS were retrospectively enrolled. The KELIM values during neoadjuvant chemotherapy were calculated, and patients were divided into high- and low-KELIM groups using a cutoff value of 1.0. Clinicopathological characteristics, R0 resection rates, and platinum sensitivity rates were compared between the two groups. Logistic regression analysis was performed to identify predictive factors for R0 resection, while Kaplan-Meier survival analysis and Cox proportional hazards regression were performed to evaluate factors associated with progression-free survival (PFS). Furthermore, the patients were stratified according to both KELIM and BRCA status to assess the risk of platinum-resistant recurrence in each subgroup.

The R0 resection rate was higher in the KELIM ≥ 1 group than in the KELIM < 1 group (77.1% vs 55.2%), and the difference was statistically significant (P = 0.024). Multivariate logistic regression analysis showed that KELIM was an independent predictor of R0 resection (odds ratio [OR] = 2.922, 95% CI: 1.112-7.678). Survival analysis demonstrated longer PFS in the KELIM ≥1 group compared with that in the KELIM <1 group (33.0 months vs 18.0 months), and the difference was statistically significant (P < 0.001). Multivariate Cox regression analysis showed that KELIM ≥ 1 was associated with a reduced risk of disease progression (hazard ratio [HR] = 0.481, 95% CI: 0.280-0.826). Combined stratification analysis revealed that no platinum-resistant recurrence was observed in the subgroup with both KELIM ≥1 and a BRCA-positive status (0/21). Compared with patients with KELIM <1 and a BRCA-negative status, this subgroup exhibited a lower risk of platinum-resistant recurrence (OR = 0.053, 95% CI: 0.003-0.932, P = 0.006).

KELIM is an effective dynamic biomarker for predicting surgical outcomes and PFS in patients undergoing NACT-IDS. Combined stratification by KELIM and BRCA status allows more precise identification of the patient population with both KELIM ≥1 and BRCA-positive status, who have an extremely low risk of platinum-resistant recurrence, thereby providing an important basis for individualized treatment and risk stratification management in patients with advanced HGSOC.

Predicting occult lymph node metastasis in early-stage tongue squamous cell carcinoma remains a clinical challenge because traditional markers, such as depth of invasion, exhibit limited accuracy. This study aimed to identify spatial immunological biomarkers to improve risk stratification and clinical decision-making.

Olink proteomic profiling was conducted to screen for metastasis-associated biomarkers. Subsequently, multiplex immunofluorescence coupled with artificial intelligence-powered spatial analysis was utilized to evaluate the microenvironment in primary lesions and paired cervical lymph nodes. A novel "Spatial Availability Index" was applied to map cellular distribution, and diagnostic performance was evaluated using receiver operating characteristic curve analysis.

Arginase-1 (ARG1) was identified as a top candidate biomarker, exhibiting a unique "tissue-low, serum-high" expression pattern in cases with occult metastasis. Spatial analysis revealed a significant depletion of ARG1⁺ polymorphonuclear myeloid-derived suppressor cells (PMN-MDSCs) in both primary tumors and paired lymph nodes during metastatic progression. Specifically, the reduction of these intact cells was most pronounced within a 35-μm proximal segment from the tumor boundary. This localized cellular loss inversely correlated with an accumulation of neutrophil extracellular traps (NETs) at the peritumoral interface, indicating that ARG1⁺ PMN-MDSC-associated spatial alterations coincide with NET-associated remodeling at the peritumoral interface. Integrating the intrastromal density of ARG1⁺ PMN-MDSCs with depth of invasion significantly enhanced the diagnostic accuracy for occult metastasis (Area Under the Curve = 0.8318) compared to using depth of invasion alone.

Early metastatic risk is driven by localized alterations within the myeloid compartment, characterized by the transition of intact ARG1⁺ PMN-MDSCs to NETs within a 35-μm peritumoral hotspot. This spatial biomarker provides a high-resolution tool to optimize patient selection for elective neck dissection.

Colorectal cancer (CRC) with human epidermal growth factor receptor 2 (HER2) overexpression and RAS mutations is often associated with poor response to conventional treatments, presenting substantial therapeutic challenges. This report describes a remarkable response in a patient with HER2-amplified, KRAS-mutated metastatic rectal cancer, who was treated with a zanidatamab-based combination regimen.

A 54-year-old male was admitted to our hospital complaining of hematochezia and was diagnosed with rectal adenocarcinoma via biopsy. Baseline imaging revealed extensive, unresectable liver metastases. Next-generation sequencing identified a KRAS G12D mutation alongside HER2 amplification. Although the combination of chemotherapy and bevacizumab yielded promising efficacy, but tumor markers still remained high. When the anti-HER2 bispecific antibody zanidatamab was added, after three cycles of this triplet therapy, the liver metastases exhibited radiographic regression, and tumor markers showed substantial decline. The patient achieved sufficient downstaging and subsequently underwent successful hepatic resection. Pathological examination confirmed negative surgical margins.

This case underscores the potential of HER2 inhibition as an effective therapeutic strategy in KRAS-mutated CRC. It also highlights zanidatamab's promise as part of a conversion therapy approach in patients with historically refractory disease.

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related mortality worldwide. Although chemotherapy is an important treatment strategy for advanced NSCLC, its efficacy is limited by treatment resistance and adverse events. Traditional Chinese medicine injections (TCMIs) are widely used as adjunctive therapies; however, the comparative efficacy and safety of different TCMI-based regimens remain unclear. This study aimed to compare the efficacy and safety of various TCMIs combined with chemotherapy using Bayesian network meta-analysis.

RCTs on TCMIs combined with chemotherapy for NSCLC were retrieved from Chinese databases including CNKI, Wanfang, VIP, and Chinese Biomedical Literature Database, as well as English databases including PubMed, Web of Science, and Cochrane Library. The retrieval period was from January 1, 2021 to May 1, 2026. The Cochrane risk-of-bias tool was used to assess the methodological quality of the included studies, and the certainty of network evidence was evaluated using the Confidence in Network Meta-Analysis (CINeMA) framework. Stata and R software were used to perform network meta-analysis.

A total of 71 RCTs involving 6,386 patients were included. The results of the network meta-analysis showed that Kanglaite Injection combined with chemotherapy showed a relatively favorable ranking for objective response rate (ORR), CD8, and skin adverse reactions; Kang'ai Injection combined with chemotherapy for hemoglobin reduction-related adverse reactions; Shenqi Fuzheng Injection for natural killer cells (NK cells), immunoglobulin G (IgG), neuron-specific enolase (NSE), and carbohydrate antigen 19-9 (CA19-9); Aidi Injection for immunoglobulin A (IgA), immunoglobulin M (IgM), and bone marrow suppression-related adverse reactions; Fufang Kushen Injection for carcinoembryonic antigen (CEA), vascular endothelial growth factor (VEGF), and adverse reactions such as leukopenia, liver and kidney function damage, and gastrointestinal symptoms; Shenmai Injection combined with chemotherapy for carbohydrate antigen 125 (CA125); Yadanzi Youru injection combined with chemotherapy for squamous cell carcinoma antigen (SCC); Xiao'aiping Injection for cluster of differentiation 4 positive T lymphocyte (CD4⁺ T Cell)/cluster of differentiation 8 positive T lymphocyte (CD8⁺ T Cell); Renshen duotang injection for disease control rate (DCR), cluster of differentiation 3 positive T lymphocyte (CD3⁺ T Cell), cluster of differentiation 4 positive T lymphocyte (CD4⁺ T Cell), and cytokeratin 19 fragment (CYFRA21-1); Huangqi Duotang injection combined with chemotherapy for thrombocytopenia-related adverse reactions. Meta-regression analyses identified statistical associations between age and effect estimates of CYFRA21-1, SCC, VEGF, and IgM; however, these findings should be interpreted as exploratory associations rather than causal explanations. Subgroup analysis of CYFRA21-1 suggested potential differences across age-related subgroups, which require further validation.

TCMIs combined with chemotherapy maybe associated with improvements in clinical response, immune-related indicators, tumor-associated markers, and treatment tolerability in patients with advanced NSCLC. However,given the limited certainty of evidence, substantial heterogeneity, and methodological limitations of included studies, these findings should be interpreted cautiously and require confirmation through high-quality prospectivestudies.

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD420261392216.

The primary aim was to study the differences between pheochromocytomas (PCC) and sympathetic paragangliomas (PGL) in management and short- and long-term outcomes.

This was a retrospective study of 220 patients that had undergone surgery for PCC or PGL and had been managed during the period 2005-2025 at the Department of Endocrinology, Karolinska University Hospital. Patient data were collected from electronic medical journals.

Patients with PCC compared to PGL had a longer duration of preoperative treatment with alpha-adrenergic receptor antagonist (50.0 vs. 34.0 days, p = 0.014) and shorter hospital stay (4.0 vs. 7.0 days, p < 0.001). Patients with PCC presented more often with dysglycemia (42.2% vs. 17.6%, p = 0.012), and glucose improved to a greater extent as well after surgery (84.2% vs. 33.3%, p = 0.033). Patients with PGL were more affected by new related tumors (recurrence, metastases, or metachronous tumor) during the follow-up time (27.8% vs. 11.0%; p = 0.019).

There are many similarities between PCC and PGL; however, patients with PGL had a somewhat worse prognosis regarding short- and long-term outcomes, including longer length of stay at the hospital, risk for new associated tumors, and less positive effects on dysglycemia.

Thyroid cancer is one of the fastest-growing malignancies worldwide, with papillary thyroid carcinoma (PTC) accounting for approximately 85-90% of all cases. For patients with T1b-T2 PTC, the choice between thyroid lobectomy and total thyroidectomy remains controversial. Postoperative pathological examination reveals contralateral occult carcinoma in 20-40% of patients, while contralateral central lymph node metastasis (CLNM) represents a key prognostic factor. However, reliable and practical preoperative tools to support individualized surgical decision-making are currently lacking. This study aimed to develop and validate a preoperative prediction model for assessing the risk of contralateral occult carcinoma (OTC) and contralateral CLNM in patients with T1b-T2 PTC, thereby facilitating individualized surgical management.

This retrospective study enrolled 932 patients with T1b-T2 PTC who presented with unilateral nodules on preoperative ultrasound and underwent total thyroidectomy with bilateral central lymph node dissection. All 932 patients were included in the contralateral OTC prediction model, and 730 patients were included in the contralateral CLNM prediction model. Nine machine learning algorithms and logistic regression models were trained and compared using five-fold cross-validation. Key predictive features were selected through multivariate logistic regression and random forest. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), calibration curves, the Hosmer Lemeshow test, and decision curve analysis.

Feature selection identified four independent predictors of contralateral OTC: malignant isthmic nodule, sum of the longest diameter (SLD), number of malignant nodules, and capsular disruption. Five predictors were identified for contralateral CLNM: isthmus adjacent nodule, sex, SLD, age, and chronic lymphocytic thyroiditis (CLT), with CLT showing a negative association with CLNM.Logistic regression model demonstrated the best performance for OTC prediction (AUC = 82.00%). For contralateral CLNM, logistic regression achieved an AUC of 79.00%, comparable to that of the best-performing machine learning model (glmBoost, AUC = 79.10%), with no statistically significant difference observed between the two models. Model calibration was satisfactory, as demonstrated by calibration curves and the Hosmer-Lemeshow test (P = 0.5097). Decision curve analysis further indicated favorable clinical net benefit.

This study developed a logistic regression-based preoperative predictive tool to assess the individualized risk of contralateral occult carcinoma and contralateral CLNM in patients with T1b-T2 PTC. To our knowledge, this is the first dual-outcome prediction model specifically designed for this patient population. The prediction results were visualized using two nomograms and two web-based applications, which may assist clinicians in making individualized surgical decisions before surgery. Specifically, low-risk patients may be considered for thyroid lobectomy to avoid overtreatment, whereas high risk-patients may undergo total thyroidectomy to reduce the risk of recurrence.

Extreme weather events are an increasing public health concern, particularly for adults living with chronic diseases. In this study, we examined whether illness perceptions were associated with preparedness for extreme weather events through a theoretically informed serial indirect association involving threat appraisal and weather-related worry, and whether these associations differed across respiratory disease, cancer, and cardiovascular disease groups.

A cross-sectional study was conducted among 450 Israeli adults aged 50 years or older with a physician-diagnosed respiratory disease, cancer, or cardiovascular disease. Participants completed self-report measures of illness perceptions, threat appraisal, weather-related worry, and preparedness for extreme weather events.

More negative illness perceptions showed a significant serial indirect association with greater preparedness for extreme weather events through higher threat appraisal and greater weather-related worry. This indirect association was significant for both "intuitive" and "planned" preparedness behaviors across all three disease groups. The pattern of indirect associations specified in the serial mediation model was similar across groups. Of the nine interaction terms tested, one was significant, where disease group moderated the association between illness perceptions and weather-related worry. This association was significant among participants with respiratory disease, but not among those with cancer or cardiovascular disease. This exploratory finding should be examined in future research.

This study found that illness perceptions, threat appraisal, weather-related worry, and preparedness for extreme weather events were interrelated among adults with chronic diseases, with a similar pattern of indirect associations across respiratory disease, cancer, and cardiovascular disease groups. Given the cross-sectional design, the proposed ordering of these variables should be interpreted as theoretically informed rather than as evidence of a temporal or causal pathway. These findings contribute to research at the intersection of illness self-regulation and climate-health adaptation and may inform future longitudinal research and preparedness interventions for medically vulnerable populations.

In South Korea, the companion-dog population is strongly skewed toward a small number of small-breed purebred dogs, and distinguishing breed-type differences in recorded diagnoses from confounding by age, neuter status, and healthcare utilization is challenging in primary-care data.

This retrospective study used electronic medical records (EMRs) from primary-care veterinary clinics in South Korea, covering January 2016-December 2024, to compare the adjusted odds of the 20 most frequently recorded diagnoses between purebred and mixed-breed dogs. Records were standardized using Veterinary Nomenclature (VENOM) coding. For each condition, a separate multivariable logistic regression model estimated the adjusted odds ratio (aOR) and 95% confidence interval (CI) for purebred status, adjusting for age, sex, neuter status, and visit frequency. Age was assigned as age at first recorded diagnosis for cases and last observed age for non-cases.

After adjustment, purebred dogs showed higher odds of recorded diagnosis for nine conditions, including meningoencephalitis (aOR 2.77; 95% CI 1.17-6.57), intervertebral disc disorder (aOR 1.85; 95% CI 1.49-2.29), myxomatous mitral valve degeneration (aOR 1.57; 95% CI 1.46-1.68), and patellar luxation (aOR 1.54; 95% CI 1.38-1.71). Mammary neoplasm showed higher crude prevalence in mixed-breed dogs, and this association remained statistically significant after adjustment for binary neuter status (aOR 0.80; 95% CI 0.68-0.95; Adj p = 0.0202), likely reflecting unmeasured confounding by the timing of neutering. Ten conditions, including chronic kidney disease and unspecified dermatitis, showed no statistically significant difference between groups. These findings indicate breed-type differences in the odds of recorded diagnoses in a Korean primary-care EMR dataset rather than true disease risk or causal effects. Because the cohort was dominated by small-breed dogs and the analyses could not fully account for body size, follow-up duration, detection bias, or diagnostic-coding heterogeneity, the observed associations may reflect breed composition, morphology, owner behavior, healthcare access, and recording practices in addition to underlying biological differences.