Skull base chordomas (SBCs) are rare and challenging tumors due to their midline location and invasive behavior, requiring a multidisciplinary approach that integrates advancements in surgical techniques, radiation therapy, and emerging therapies. This paper synthesizes clinical experience with 307 surgical resections performed on 197 patients to propose a cohesive treatment paradigm for SBCs. The endoscopic endonasal approach (EEA) is highlighted as a cornerstone of surgical management, with key considerations for postoperative radiation strategies and novel therapeutic options, such as immunotherapy, discussed. By emphasizing the importance of maximal safe resection, individualized treatment planning, and ongoing innovation, this paper aims to provide a framework for optimizing outcomes in patients with SBCs while highlighting areas for future research in this complex field.

Cardiac myxomas are the most common primary cardiac tumours. The overall prevalence is very low and up to 25% present asymptomatically. In Asia, the data on myxomas is limited. Therefore, we aimed to outline a multi-ethnic Asian population of cardiac myxoma patients. We included all index echocardiographic diagnoses of myxoma at a tertiary cardiovascular referral centre from May 2004 to April 2021. A retrospective review of all patients' medical records was conducted. Data including patient characteristics, clinical presentation, imaging, treatment, and outcomes were collected and analysed. A total of 64 patients (mean age 66.4 years old, male 61%) were diagnosed with cardiac myxoma. The incidence of major adverse cardiovascular events (MACE) was 10 (16.1%) and 10-year mortality was 11 (17.2%). The proportion of asymptomatic patients (30.2%) increased from 15.4% before 2012 to 35.3% after 2012. Pre-existing chronic kidney disease and ischaemic heart disease were independently associated with increased risk of mortality and MACE (p-values < 0.05). Most patients (75.0%) underwent surgical resection. This was associated with a decreased risk of mortality and MACE (p-values < 0.05). The increase in the diagnosis of asymptomatic patients over the years could be attributed to increased opportunistic screening and incidental pickups. Surgical resection was associated with better outcomes. However, the poor outcomes of non-operated patients may be due to the concurrent comorbidities that preclude surgery.

PCOS, a common disorder in reproductive aged women, characterized by hyperandrogenism. Hyperandrogenism can be attributed to the hyperactive androgen receptor (AR). Androgen receptor mediated signalling involves the association of multiple coregulators and any aberrant activity of these factors may disrupt the normal transcriptional activity of AR and hence may act as contributing factors in pathophysiology of hyperandrogenic disorders. LncRNAs PRNCR1 and PCGEM1 act as AR coactivators. The study was aimed at determining the association of these lncRNAs with PCOS. A total of 178 participants including 105 PCOS cases and 73 controls were recruited. The Anthropometric, Metabolic and hormonal characteristics of the participants were determined. Total RNA was isolated and reverse transcribed into cDNA. Quantitative real-time PCR was done to study the expression pattern of lncRNAs. The association between different parameters with the expression of PRNCR1 and PCGEM1 was determined by correlation analysis. The expression levels of PRNCR1 (PRNCR1, 5.28 (1.29-9.14) versus 1.07 (0.05-3.18); P < 0.001) (PCGEM1, 3.08 (0.29-8.79) versus 1.70 (0.116-3.73); P < 0.001) were significantly higher in Women with PCOS compared to controls. Furthermore, lncRNA PRNCR1 showed a positive correlation with testosterone (P < 0.001). ROC analysis showed a strong diagnostic performance of lncRNA PRNCR1 Optimal Cut off (Youden's Index) = 3.23, AUC = 0.988 (95% CI = 0.976-0.99) and Sensitivity = 0.91, Specificity = 1.00 and for PCGEM1 Optimal Cut off (Youden's Index) = 2.02, AUC = 0.86 (95% CI = 0.81-0.92) and Sensitivity = 0.82, Specificity: 0.90. Our results demonstrated that overexpression of AR coactivator lncRNAs PRNCR1 and PCGEM1 are associated with an increased risk of PCOS in Kashmiri women. These lncRNAs may act as important factors for the hyperactivation of AR and subsequent overexpression of AR regulated genes and thus may contribute towards the pathogenesis of PCOS and its clinical manifestations.

B-cell acute lymphoblastic leukemia (B-ALL) is the most common pediatric malignancy. Given racial/ethnic differences in incidence and outcomes, B-ALL genome-wide association studies among children of African ancestry are needed. Leveraging multi-institutional datasets with 840 African American children with B-ALL and 3360 controls, nine loci achieved genome-wide significance (P < 5 × 10^-8) after meta-analysis. Two loci were established trans-ancestral susceptibility regions (IKZF1, ARID5B), while the remaining novel loci were specific to African populations. Five-year overall survival among children carrying novel risk alleles was significantly worse (83% versus 96% in non-carriers, P = 4.8 × 10^-3). Novel risk variants were also associated with subtype-specific disease (P < 0.05), including higher susceptibility for a subtype overrepresented in African American children (TCF3-PBX1) and lower susceptibility for a subtype with excellent prognosis (ETV6-RUNX1). Functional experiments revealed novel B-ALL risk variants had allele-specific differences in transcriptional activity (P < 0.05) in B-cell and leukemia cell lines. These findings shed insights into ancestry-related differences in leukemogenesis and prognosis.

Although depression is prevalent and has significant consequences among individuals living with likely incurable cancer (ILLIC), optimal methods of identifying and treating depression in this population remain unknown.

To evaluate a paradigm of (1) proactive identification (ID) (i.e., remotely and asynchronously from clinical encounters) of depression among ILLIC and (2) digital mental health intervention (DMHI) for depression treatment.

In this decentralized randomized clinical trial, ILLIC with elevated depressive symptoms were proactively identified using electronic health record data and randomized 2:1 to a DMHI-based Behavioral Activation treatment or usual care (UC) depression treatment. Measures of feasibility (accrual, retention) and acceptability (engagement) were described; depression severity (change in PHQ-9 scores through 4 weeks post-randomization) was modeled with a generalized estimating equation.

Among 88 ILLIC who completed screening, 30 were eligible and randomized to the trial. No patients were lost to follow-up or withdrew; 80% of patients randomized to proactive ID + DMHI used the app through 4 weeks. Proactive ID + DMHI improved depression from baseline to 4 weeks relative to proactive ID + UC (mean difference in change from baseline to week 4 = -2.7; 90% CI: -4.9 to -0.4). At 4 weeks, the odds of a clinical response (PHQ-9 decrease of ≥ 5 points) was 9.0-fold higher for patients in proactive ID + DMHI relative to proactive ID + UC (OR 9.0; 90% CI: 1.1-74.2).

A proactive ID + DMHI approach to identifying and treating depression among ILLIC is feasible, acceptable, and potentially efficacious. These promising data support conducting a large efficacy trial evaluating this approach.

ClinicalTrials.gov identifier: NCT05932810.

Oesophageal cancer (EC) presents a substantial global health challenge, ranking eighth in incidence and sixth in cancer-related mortality. Oesophageal squamous cell carcinoma (ESCC) is the primary subtype and accounts for approximately 90% of cases in Asia. Despite treatment advances, the 5-year survival rate remains modest at 10%-30%. Immune checkpoint inhibitors, exemplified by KEYNOTE-590 and CheckMate 577 trials, have reshaped EC therapeutic landscapes. Our study addresses the critical gap in understanding the real-world impact of PD-1 (Programmed Death-1) inhibitors, conducting a multicentre, real-world, observational cohort analysis focused on ESCC. This research endeavours to provide practical insights into PD-1 treatment for EC, facilitating informed clinical decision-making and optimising patient outcomes in diverse healthcare settings.

This multicentre study includes patients diagnosed with histopathologically confirmed ESCC who have consented to treatment with PD-1 inhibitors. It is structured into two distinct segments: Part A, characterised by its retrospective nature, and Part B, representing the prospective arm. Within both parts, four stratified cohorts are delineated, comprising Cohort 1 (preoperative neoadjuvant/conversion therapy), Cohort 2 (postoperative adjuvant therapy), Cohort 3 (first-line therapy for advanced ESCC) and Cohort 4 (≥2 lines of therapy for advanced ESCC). The primary endpoint is the objective response rate in diverse treatment cohorts. Secondary endpoints include pathologic complete response rate, disease-free survival, progression-free survival, overall survival, adverse events, immune-related adverse events, quality of life and the intricacies of immunotherapy patterns and hyperprogression. Furthermore, exploratory endpoints scrutinise potentially predictive biomarkers, as well as the clinical and genomic characteristics inherent to ESCC patients if possible. The study endeavours to enrol 417 participants, subject to a comprehensive 5-year follow-up period.We will collect and analyse real-world data from Chinese ESCC patients treated with PD-1 inhibitors to observe and describe the efficacy and safety of PD-1 inhibitors in Chinese patients with ESCC at various treatment stages.

Ethical approval was provided by the Ethics Committee for Medical Research and New Medical Technology of Sichuan Cancer Hospital, China (Approval No. SCCHEC-02-2023-096). Each participating hospital has applied for research permission from the Institutional Review Board of its unit. We will disseminate the results through peer-reviewed journals and academic conferences.

ChiCTR2300078657.

Patients with cancer frequently experience psychological and social challenges, including depression, anxiety, and isolation, which are often intensified by treatment side effects and unmet psychosocial needs. Conventional support systems are often inaccessible, under-resourced, or poorly tailored to diverse patient populations. In this context, virtual communities have emerged as promising alternatives that enable peer interaction, emotional support, and information exchange. However, their implementation and sustainability are influenced by complex sociotechnical and organizational factors that remain underexplored.

This scoping review applies the Non-adoption, Abandonment, Scale-up, Spread, and Sustainability (NASSS) framework to examine how virtual communities have been implemented in cancer care. It aims to identify key barriers and facilitators, evaluate the alignment between platform features and user needs, and synthesize evidence to inform sustainable integration into care systems.

A systematic search was conducted across 6 databases (PubMed, Scopus, Embase, Web of Science, PsycINFO, and CINAHL), covering studies published between 2019 and 2024. Eligible studies were empirical and reported on the development, implementation, or evaluation of virtual communities for patients with cancer. Data were extracted using a structured Non-adoption, Abandonment, Scale-up, Spread, and Sustainability-based matrix and synthesized thematically across diverse research designs.

The search yielded 322 records, of which 175 full-text studies were assessed for eligibility, and 25 studies were included in the review. These studies covered a range of virtual community formats used by patients with cancer. All included studies reported psychosocial benefits, including reduced loneliness, improved emotional well-being, and greater opportunities for experience sharing. However, key challenges remained, such as low user retention, limited participation from underrepresented groups, and difficulties integrating these platforms into existing health care systems. Few studies reported longitudinal follow-up or detailed engagement metrics, limiting insights into long-term effectiveness.

Virtual communities show strong potential to address the psychosocial needs of patients with cancer, especially in underserved populations. However, to ensure long-term effectiveness, attention must be paid to inclusivity, user retention, ethical considerations, and system-level integration. Future research should incorporate standardized metrics, longitudinal designs, and equity-oriented approaches to optimize the development and implementation of virtual communities in cancer care.

Early diagnosis of hepatocellular carcinoma (HCC) in patients with chronic hepatitis B virus (HBV) is challenging. Models that combine novel biomarkers with clinical features may improve both early diagnosis and risk stratification, but few have been systematically validated.

This study aimed to develop and validate an extra spindle pole bodies-like 1 (ESPL1)-based model for diagnostic discrimination of HBV-related HCC and longitudinal risk stratification in patients with chronic HBV infection.

Patients with chronic HBV were consecutively recruited from the First Affiliated Hospital of Guangxi Medical University (a single-center, tertiary hospital) between January 2012 and November 2023. Patients were divided into a training set and an independent hold-out testing set. A LASSO logistic regression model was constructed to identify independent predictors and then used to develop a risk score discriminating patients with HBV-related HCC from those with chronic hepatitis B or cirrhosis. Model performance was evaluated using discrimination (C-index), calibration, and decision curve analysis. Internal validation was performed with bootstrap resampling, and independent hold-out validation was conducted with the independent hold-out testing set. Longitudinal follow-up of patients with chronic hepatitis B or cirrhosis was subsequently used to examine cumulative incidence across risk groups, thereby assessing the model's ability to stratify future HBV-related HCC risk. A web-based calculator was developed to facilitate clinical application.

The study involved a cohort of 621 patients diagnosed with chronic HBV infection, divided into a training set of 373 (60.1%) patients and an independent hold-out testing set of 248 (39.9%) patients. Age (odds ratio [OR] 1.08, 95% CI 1.05-1.12), ESPL1 expression (OR 1.01, 95% CI 1.00-1.01), and log (alpha-fetoprotein) levels (OR 2.55, 95% CI 1.95-3.33) were identified as independent predictors of HBV-related HCC. The model demonstrated excellent diagnostic discrimination, with a C-index of 0.922 in the training set and 0.958 in the independent hold-out testing set, coupled with strong calibration. Decision curve analysis revealed that the model consistently provided a higher net benefit across clinically relevant threshold probabilities. Subgroup analyses further validated the model's high discriminative power, with C-index values ranging from 0.86 to 0.98, and no significant interactions were detected (all interaction P values > .10). Furthermore, the model demonstrated superior discriminatory power relative to 5 established HBV-related HCC risk scores, including REACH-B, GAG-HCC, CU-HCC, PAGE-B, mPAGE-B, and alpha-fetoprotein alone, with all pairwise comparisons yielding statistical significance (P<.001). For prognostic stratification, patients categorized as low risk, medium risk, and high risk had distinct 5-year cumulative HCC incidences of 5.1%, 21.1%, and 31.3%, respectively (P<.001).

The ESPL1-based model may serve as both a diagnostic tool for differentiating patients with HCC from those with non-HCC and as a preliminary approach for risk stratification during follow-up. This dual role has the potential to support earlier detection and personalized monitoring. The web-based calculator improves accessibility and may facilitate future clinical integration.

Ontario's primary care reforms have introduced three blended physician payment models: (i) blended fee-for-service (BFFS), (ii) blended capitation without interprofessional teams, and (iii) blended capitation with teams. Each model includes the same pay-for-performance incentives, yet their impact on cancer screening, including that during the COVID-19 pandemic, remains unclear.

We used linked administrative data (2018-23) to examine the associations between these models and colorectal, cervical, and breast cancer screening rates. Fractional probit regression models, adjusting for physician and patient characteristics, estimated the effects of each payment model relative to the BFFS. Stratified analyses explored heterogeneity by physician sex, age, practice size, rurality, and socioeconomic deprivation.

Compared with the BFFS model, the blended capitation models were associated with higher screening rates, although initial differences were modest. By 2022, nonteam and team capitation models had colorectal screening rates 3.0% and 3.6% higher, respectively, than those of the BFFS. Similar but smaller increases were observed for cervical and breast cancer screening. These advantages persisted through COVID-19 disruptions and were most pronounced among physicians serving rural or socioeconomically disadvantaged populations. Stratified analyses indicated that female, younger, and higher-volume physicians performed better in capitation-based models.

Blended capitation arrangements, especially those integrating interprofessional teams, appear more effective than the BFFS in delivering preventive cancer screening. Strengthening team-based primary care and targeted incentives could bolster preventable cancer screening rates in the population, even under pandemic-related challenges. These findings can inform policy decisions aimed at improving population health through optimized primary care provisions.

Over the past decade, Fast Healthcare Interoperability Resources (FHIR) have become increasingly relevant in health care data standardization. However, the complex structure of FHIR makes cohort analytics with many-to-many relations extremely time-consuming, and, impossible in many cases. To support exploratory cohort building and data visualization in oncology, especially for nontechnical users, we developed the DermaDashboard, an interactive dashboard built on top of a relational FHIR-compliant PostgreSQL database. Relevant oncology data was preaggregated with a materialized view, and the subsequent visualization layer was implemented using an open-source visualization tool, enabling clinicians to filter and analyze data without requiring familiarity with FHIR or SQL. The database encompassed data from 3949 patients with melanoma and included 82,783 health records. Core FHIR resources were Patient, DiagnosticReport, and QuestionnaireResponse, with 54 mapped attributes spanning demographics, stagings, mutations, and treatments. The resulting dashboard allowed filtering across 29 variables to construct subcohorts and generate aggregation analyses. This implementation shows how open interoperability data standards, such as FHIR, can be used in the development of modular, user-friendly clinical dashboards for cohort analysis, and the architecture demonstrates a feasible path toward democratizing access to structured health care data.