Among hematological malignancies, lymphoma is associated with an increased incidence of venous thromboembolism (VTE) ranging between 4 and 12%. Although Khorana score was validated for stratifying VTE risk in cancer, its discrimination reliability in lymphoma is reduced by the lack of specific predictors. The aim of this systematic review was to summarize the evidence regarding predictors and available risk assessment models (RAMs) for VTE in patients with lymphoma. A systematic search was conducted on PubMed, Embase and Scopus in order to identify papers published until February 2026, which evaluated predictors and RAMs for VTE in patients diagnosed with lymphoma. Out of 592 evaluated papers, 44 met the inclusion criteria. The widely used Khorana score failed to appropriately identify patients with lymphoma at high risk for VTE, while the Thrombosis Lymphoma predictive score (ThroLy) showed modest improvement. Strong predictors for VTE were a poor performance status, older age, previous history of VTE, the use of central venous catheters, and bulky disease. However, the lack of external validation, the small sample size and bias due to confounding factors limit the generalizability of the results. Therefore, larger studies with external validation cohorts are needed to design lymphoma-specific RAMs and to identify predictors with high discrimination power.

Background: Psychological distress, particularly anxiety and depression, is highly prevalent among cancer patients, and is associated with impaired quality of life, reduced treatment adherence, and increased mortality risk. Standardized screening instruments, such as the Hospital Anxiety and Depression Scale (HADS), are effective, but face implementation barriers in busy oncology outpatient settings. This cross-sectional study investigated whether BERT-based Natural Language Processing (NLP) analysis of brief patient-generated free texts would correlate with HADS scores in a consecutive cohort of cancer outpatients. Material and Methods: A total of 165 consecutive adult cancer outpatients were enrolled at a tertiary oncology center in Turkey. All participants completed the HADS questionnaire and were asked to write freely about their current emotional state in Turkish. Patient-generated texts were analyzed using a pre-trained Turkish BERT model to derive a continuous BERT Sentiment Score (BSS) and a categorical BERT Sentiment Cluster (BSC) via unsupervised hierarchical clustering. Univariate and multivariate linear regression analyses were performed to examine associations between clinical, demographic, and NLP-derived variables and the logarithmically transformed HADS score. Results: The mean total HADS score was 10.46 (range, 0-33), consistent with a moderate level of psychological distress. In multivariate analysis, two variables were independently associated with HADS scores: female sex (β = 0.20, t = 2.14, p = 0.034), associated with higher HADS scores, and BERT Sentiment Score (BSS) (β = -0.18, t = -2.43, p = 0.016), with higher values corresponding to lower HADS scores. Hierarchical clustering identified two distinct thematic groups: 'Coping and Fighting Spirit' (74%), and 'Hope and Negative Feelings' (26%); however, cluster membership (BSC) was not independently associated with HADS scores (β = -0.02, p = 0.789). Clinical variables, including cancer stage, diagnosis type, treatment status, and time since diagnosis, also were not independently associated with HADS scores. Conclusions: BERT-based sentiment analysis of brief patient-generated free texts yielded a continuous measure that independently correlated with HADS scores in cancer outpatients, alongside female sex. These findings provide proof-of-concept evidence that NLP-derived sentiment scoring may offer a practical, scalable, and complementary approach to standardized psychological screening in routine oncology care.

The BRCA1 protein serves an essential function in maintaining genomic integrity, to the extent that up to 80% of women carrying a pathogenic BRCA1 variant develop breast cancer (BC). Most of these carriers would benefit from prophylactic care, but genetic screens that uncover variants of uncertain significance (VUSs) do not provide insight on disease risk or clinical decision-making. In accordance with guidelines established by The American College of Molecular Genetics (ACMG) and Association for Molecular Pathology (AMP), this study produced computational and functional evidence to inform the reclassification of BRCA1 VUSs as pathogenic or benign, with a specific focus on the abundant subset of missense variants within the RING domain. A six-feature linear support vector machine (LSVM) specifically trained on BRCA1 RING variants performed well (84% accurate in predicting in vitro binding loss) and provided supporting classification evidence for 322 VUS. A mammalian cell co-immunoprecipitation (co-IP) assay that quantified the binding between variant BRCA RING constructs and endogenous BARD1 provided corroborating strong evidence for nine VUSs and correlated with a homology-directed repair (HDR) assay by Starita et al. (p = 0.04). The combined evidence warrants the reclassification of three VUSs as likely benign (N16S, A17D, and E100D) and one as likely pathogenic (H41P), and underscores the promise of domain-specific approaches for missense VUS reclassification.

MR-guided adaptive radiotherapy (ART) enables daily plan optimization for prostate cancer but is resource-intensive. This study evaluated dosimetric and clinical outcomes following transition from radiation oncologist (RO)-led to radiation therapist (RTT)-led MR-guided ART. All prostate cancer patients treated with MR-guided ART on a 1.5T MR-linac were retrospectively reviewed. Consecutive RO-led (September 2019-November 2021) and RTT-led (April 2022-October 2023) cohorts were compared, excluding the actual transition period. Toxicities (CTCAE v5.0), dose-volume metrics from daily adapted plans, target volume variation, and biochemical recurrence-free survival (BRFS) were analyzed. A total of 166 patients were included (78 RO-led, 88 RTT-led; median follow-up 40 and 35 months). Dosimetric differences between the cohorts were statistically small (<1%). Rates of G2+ GI adverse events were similar across all timepoints. An increase in on-treatment GU events was observed in the RTT-led cohort (G2+ 27% vs. 9%, G3 incidence n = 2 vs. n = 0), likely reflecting higher baseline urinary dysfunction; no post-treatment differences persisted. Early biochemical outcomes were comparable, with 36-month BRFS of 93.5% (RO-led) and 95.0% (RTT-led). RTT-led MR-guided ART achieved comparable dosimetric quality and early biochemical outcomes to RO-led workflows with adverse advents that resolved in the long term. With structured training and a mature practice setting, RTT-led ART represents a scalable model to support future adaptive radiotherapy practice.

Multiple myeloma (MM) has experienced rapid therapeutic innovation over the past two decades, leading to a substantial increase in clinical trial activity. However, the geographic distribution of these trials and the representation of different economic regions remain poorly characterized. We evaluated the global distribution, growth patterns, and phase-specific trends of MM clinical trials and trial sites across different economic settings.

We conducted a retrospective registry-based analysis interventional MM clinical trials registered on ClinicalTrials.gov between January 2006 and January 2026. Trials were categorized based on the economic classification of participating countries using World Bank income groups and Economic Co-operation and Development (OECD) status. Trial characteristics including phase, geographic distribution, number of participating sites, and site-years were analyzed. Population-adjusted trial density and compound annual growth rates (CAGR) were calculated to assess temporal trends and geographic representation.

A total of 845 interventional MM clinical trials were identified during the study period. Trial activity was highest in the United States (337 trials, 39.9%), followed by international trials (271, 32.1%), high-income-OECD countries (129, 15.3%), and upper-middle-income countries (103, 12.2%), while high-income non-OECD countries contributed only a small fraction of trials. Trial activity increased substantially over time across all regions with the highest growth observed in upper-middle-income countries (CAGR 18.5%). The US demonstrated the highest population-adjusted trial density (0.99 per million population) and accounted for the largest number of trial sites and site-years. Phase-specific analyses revealed distinct geographic patterns. Phase 1 trials were predominantly conducted in the US and in international collaborative trials. Phase 3 trials were largely international, although the majority of participating sites remained located in the US and High-income countries that are members of the OECD (HIC-OECD).

Over the past two decades, MM clinical trial activity has expanded globally but remains highly concentrated in the United States and high income-OECD countries, particularly with respect to trial sites and population-adjusted trial density. Although upper-middle-income countries have shown the fastest growth in trial activity expanding clinical trial infrastructure and strengthening international collaboration will be essential to promote a more equitable global distribution of MM research.

The Canadian cancer care landscape faces rising cancer incidence, persistent inequities, and increasing system pressures. Led by the Canadian Association of Provincial Cancer Agencies (CAPCA), this scoping review applied an implementation science lens to evaluate the scalability of innovative cancer care models across Canada. Using a mixed-methods design, innovations were identified through a scoping review (n = 42), grey literature analysis (>50), a pan-Canadian survey (n = 72), and key informant interviews (n = 24). Guided by the Consolidated Framework for Implementation Research (CFIR), this review assessed feasibility, barriers, and facilitators influencing adoption and scale-up of identified innovations. Results revealed widespread adoption across various domains including virtual oncology, artificial intelligence (AI)-driven tools, and expansion of team-based care. At-home models, including home infusion, palliative care, and pharmacist-led chronic disease clinics, demonstrated improved access, patient satisfaction, and reduced hospital burden. CFIR mapping revealed cross-cutting facilitators including strong stakeholder engagement, structured training, and demonstrated patient benefits. However, persistent barriers include regulatory variability, funding instability, digital infrastructure gaps, and workforce capacity constraints. This paper highlights implemented innovations in cancer care and identifies strategic scaling opportunities needed to ensure all people living in Canada benefit from high-quality, person-centred equitable cancer care.

Sarcoma awareness among healthcare practitioners in our institution was limited, prompting an evaluation of their ability to recognize early presentations and initiate appropriate work-up for soft tissue and bone sarcomas. A structured survey assessed familiarity with key clinical features, recommended investigations, and perceived contributors to diagnostic delay. Overall awareness was modest, but higher among healthcare practitioners with prior sarcoma exposure, oncology-focused training, longer experience, or heavier patient loads; female practitioners and oncology nurses also scored higher. Confidence in identifying red-flag symptoms was strongly linked to familiarity with guideline-based practice. Despite these strengths, notable gaps persisted across specialties and training levels, indicating that exposure alone is insufficient. Targeted education, improved recognition of early warning signs, and clearer referral pathways are needed to reduce diagnostic delays and support timely management of suspected sarcomas.

Facility-level availability of Japanese Society of Medical Oncology (JSMO) specialists may influence care processes, but national cancer genomic medicine data rarely capture patient-level specialist involvement. We conducted a nationwide retrospective analysis of pancreatic cancer cases in the Center for Cancer Genomics and Advanced Therapeutics (C-CAT). The primary exposure was facility-level registry-listed JSMO specialist count (0-1 vs. ≥2 specialists), with ≥2 interpreted as a proxy for minimum plural specialist-team availability. The primary endpoint was time from systemic therapy start to recorded first-line treatment end. The primary cohort included 14,568 patients at 261 facilities. Median recorded first-line treatment-process duration was 5.7 months in the 0-1 specialist group and 6.4 months in the ≥2 specialist group. In the clinical plus facility-adjusted Cox model, ≥2 specialist availability was associated with a lower hazard of recorded first-line treatment end (HR 0.895, 95% CI 0.810-0.988; p = 0.028). Supportive overall survival findings did not indicate a survival advantage, reinforcing the operational nature of the primary endpoint. These findings indicate a facility-level association with an operational treatment-process endpoint, not patient-level specialist involvement, treatment efficacy, survival benefit, facility ranking, or causality. Chemotherapy-specific national database elements are needed to evaluate specialist contribution directly.

After first-line therapy with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP), 20-30% of patients with diffuse large B-cell lymphoma (DLBCL) have relapsed or refractory disease. Semi-quantitative volume parameters on [18F]Fluorodeoxyglucose positron emission tomography/computed tomography ([18F]FDG PET/CT), performed at diagnosis, could represent variables with prognostic influence. We retrospectively analyzed 53 consecutive patients, treated between 2016 and 2022. Semi-quantitative metabolic parameters, assessed by the software LIFEx, included total metabolic tumor volume (TMTV), total lesion glycolysis (TLG), Dmax and DmaxVox. All cases received R-CHOP/CHOP-like regimens with curative intent. The International Metabolic Prognostic Index (IMPI) was low in 43/53 cases (81.1%). CR was achieved in 49/53 patients (92.4%); 7/53 (13.2%) relapsed after achieving a CR. For the entire cohort, 2-year PFS and OS were 84.9% and 90.6%, respectively, while 5-year PFS and OS were 65.5% and 77.6%, respectively. IPI score, B symptoms, TMTV, Dmax and DmaxVox were associated with reduced PFS in an exploratory univariate analysis. IPI score was the only variable for which we found a significant association with reduced OS. In this exploratory analysis in a small, event-limited population, we suggest the baseline, semi-quantitative metabolic parameters of PET/CT at diagnosis could contribute to defining tumor burden and to predict PFS for DLBCL patients.

This study aimed to investigate the prognostic value of peripheral blood inflammatory markers and nutritional indices for overall survival (OS) in young patients with advanced non-small cell lung cancer (NSCLC) at initial diagnosis. Additionally, we sought to develop a survival prediction model based on combined indicators.

We retrospectively analyzed the clinicopathological characteristics, inflammatory markers, and nutritional indices of young patients with advanced NSCLC initially diagnosed at the Fourth Hospital of Hebei Medical University between January 2013 and March 2025. Univariate and multivariate Cox regression analyses were performed to identify independent prognostic factors for OS. Three prognostic models were constructed: a clinical-inflammation model, a clinical-nutrition model, and a clinical-inflammation-nutrition model. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), concordance index (C-index), and decision curve analysis (DCA), with TNM staging as the reference.

A total of 514 patients were included, with a median follow-up of 56.6 months and a median survival time of 27.2 months. Multivariate analysis identified sex, liver metastasis, gene mutation, targeted therapy, white blood cell count, and serum albumin level as independent prognostic factors for OS. Among the three models, the clinical-inflammation-nutrition model showed the best predictive performance, with 1-, 3-, and 5-year AUCs of 0.788, 0.756, and 0.704, respectively, and a C-index of 0.711 (95% CI: 0.696-0.726). DCA further demonstrated its clinical net benefit.

Peripheral blood inflammatory markers and nutritional indices are closely associated with survival in young patients with advanced NSCLC. In this exploratory single-center study, a prognostic model integrating clinicopathological factors, inflammatory markers, and nutritional indices showed better apparent predictive performance than models based on single categories of variables or TNM staging, warranting further validation in independent cohorts.