European Journal of Cancer

Background: Cases requiring 13 or more tissue sections in Mohs micrographic surgery (MMS) demand extended operative time, additional resources, and often specialised closure techniques. Pre-operative identification of such cases would improve surgical scheduling, resource allocation, and patient counselling. We aimed to develop and validate a machine learning prediction tool using pre-operative clinical features to identify cases likely to require13 sections. Objectives: To develop and validate machine learning models for predicting which Mohs procedures will require 13 sections, using pre-operative clinical features, and to identify key predictive factors. Methods: We analysed 408 consecutive Mohs procedures with 16 pre-operative clinical variables. Thirty machine learning algorithms were evaluated, including ensemble methods (Stacking, Voting), gradient boosting (XGBoost, LightGBM, CatBoost), neural networks (3-7 layers), support vector machines, and traditional classifiers. Model performance was assessed using 5-fold stratified cross-validation and independent test set evaluation. Feature importance was determined using SHAP (SHapley Additive exPlanations) analysis. Results: The stacking ensemble achieved the highest cross-validation AUC of 0.891 (95% CI: 0.849-0.934) and test AUC of 0.884. Tumour area (cm2), calculated using the ellipse formula to approximate clinical tumour morphology, emerged as the strongest predictor (SHAP importance: 0.141), followed by tumour size dimensions (0.086 and 0.068), aggressive histopathology (0.046), and recurrence status (0.035). Wide neural network architectures (5-layer) outperformed deeper configurations (7-layer). The model demonstrated 70.7% high-confidence predictions with uncertainty <15%. Conclusions: Machine learning models using pre-operative clinical features can accurately predict which Mohs procedures will require 13 or more sections. The stacking ensemble approach provides robust predictions suitable for clinical decision support. External validation in multi-centre cohorts with diverse patient populations and practice patterns is warranted to assess model generalisability.

Background The clinical significance of clonal hematopoiesis of indeterminate potential (CHIP) in melanoma remains incompletely defined, particularly with respect to CHIP genotype, clone size, and somatic mutations (e.g BRAF mutations). We integrated human cohort data and a syngeneic melanoma mouse model to evaluate whether CHIP is associated with melanoma risk, tumor growth, and differential clinical outcomes. Methods We analyzed CHIP prevalence and survival in a large treatment-unselected melanoma cohort (n=2,480), evaluated tumor growth in a syngeneic BRAF-mutant (BRAFmut) melanoma murine model of TET2-CHIP and DNMT3A-CHIP, and assessed survival outcomes in an immune checkpoint inhibitor (ICI)-treated advanced melanoma cohort (n=361). Associations with progression-free survival (PFS) and overall survival (OS) were evaluated using Kaplan-Meier analyses and multivariable Cox proportional hazards models. Results CHIP was enriched among patients with treatment-unselected melanoma compared with age/sex-matched healthy controls, and larger CHIP clone size showed an age-adjusted association with inferior OS. In a syngeneic BRAFmut melanoma murine model, TET2-CHIP, but not DNMT3A-CHIP, was associated with significantly increased primary melanoma tumor growth. Among patients with ICI-treated advanced melanoma, CHIP was associated with worse OS compared with patients without CHIP. TET2-CHIP had the strongest adverse association with survival, whereas DNMT3A-CHIP was not significantly associated with PFS or OS. Conclusions CHIP is enriched in melanoma and exploratory analyses demonstrate genotype-specific differences in melanoma tumor growth and clinical outcomes. These findings support further investigation of genotype-specific CHIP profiling as a potential biomarker for melanoma risk stratification and immunotherapy outcomes.

Population-based mammography screening improves breast cancer outcomes, but its impact on real-world treatment pathways and quality indicators (QIs) remains incompletely described. We conducted a retrospective nationwide cohort study using linked data from the Czech National Cancer Registry and the National Registry of Reimbursed Health Services. Women aged [&ge;]18 years with a first breast cancer diagnosis between 2017 and 2024 were classified as screen-detected (SCR) or diagnostically-detected (DIG) according to the imaging modality preceding histological verification. Outcomes included stage distribution, untreated cases, first-line treatment, main treatment modality, time to treatment, multidisciplinary team discussion (MDT), centralization to Comprehensive Cancer Centres (COCs), and survival patterns. The verified cohort included 47,648 women: 26,817 SCR cases (56.3 %) and 20,831 DIG cases (43.7 %). In this nationwide analysis, SCR breast cancer was associated with earlier stage at diagnosis and better survival patterns, but also with longer time to treatment and longer time to MDT discussion than DIG-detected disease. Although treatment rates were high and centralization improved over time, substantial regional variation persisted in care pathways, MDT use, and access to COCs. These findings support continued strengthening of screening participation, monitoring of care intervals, and quality assurance of MDT reporting and regional oncology care delivery.

Purpose: There are no clinically validated biomarkers to assess recurrence risk and guide treatment de-escalation in Basal-like and HER2-enriched breast cancer. Taxane-based chemotherapy remains a cornerstone of treatment despite significant toxicity. We evaluated the prognostic and predictive utility of the MHCII Immune Activation Score (IA Score) in these subtypes. Experimental Design: We retrospectively analyzed Basal-like and HER2-enriched breast cancers from the NCIC CTG MA.21 trial, which randomized patients with node-positive or high-risk node-negative disease to adjuvant chemotherapy with or without taxanes. MA.21 predated immune checkpoint inhibitors and routine HER2-targeted therapy. Subtype was previously assigned by PAM50. The 36-gene MHCII-IA assay used RNA from formalin-fixed, paraffin-embedded tissue. Multivariable Cox and Kaplan-Meier analyses evaluated associations between IA Score, clinicopathologic variables, tumor-infiltrating lymphocytes (TILs), relapse-free survival (RFS), and taxane benefit. Results: Among Basal-like (N=317) and HER2-enriched (N=155) tumors, higher IA Score was associated with improved RFS independent of lymph node status and provided stronger prognostic discrimination than TILs. Node-negative patients with high IA Score had excellent outcomes (8-year RFS >90%) versus those with low IA Score (8-year RFS <76%). In node-positive disease, high IA Score increased 8-year RFS by >10% relative to low IA Score. IA Score stratified taxane benefit: node-positive IA-low patients benefited, whereas IA-high tumors had favorable outcomes regardless of regimen. Conclusions: MHCII Immune Activation Score is a prognostic and predictive biomarker in Basal-like and HER2-enriched breast cancer. High IA Score identified patients with excellent outcomes before pembrolizumab, trastuzumab, and taxane-based treatment escalation, providing a rationale for prospective risk-adapted de-escalation strategies.

Sentinel lymph node biopsy (SLNB) is increasingly omitted in early-stage breast cancer, often prompting whole-breast irradiation (WBI). We evaluated partial-breast irradiation (PBI) without axillary surgery among 78 clinically node-negative patients (median age 75) treated from 2014 to 2022. After 53-month median follow-up, no ipsilateral, regional, or distant recurrences occurred. These results demonstrate excellent outcomes and suggest PBI is a feasible, safe alternative to WBI when SLNB is omitted.

Early detection of suspicious moles remains the most effective means of reducing mortality from skin cancer, yet systematic screening is constrained by the time and expertise required for manual mole assessment. This paper presents an end-to-end computational pipeline that utilizes wide-angle skin photographs (including consumer-grade smartphone images) and produces quantitative ABCD (Asymmetry, Border irregularity, Color variegation, Diameter) feature scores for every detected mole. The pipeline operates in four stages: mole detection via adaptive thresholding and blob analysis, super-resolution enhancement using EDSR, false-positive filtering using a brightness-based statistical criterion, and lesion segmentation using the Boundary Attention Mapper (BAM). BAM generates high-resolution segmentation masks by fusing early-layer activations with GradCAM heatmaps from a trained EfficientNet-B7 classifier, achieving 90.45% accuracy on the ISIC2017 dataset, outperforming both conventional GradCAM (87.78%) and dedicated segmentation architectures, including DeepLabv3 and SAM v2 by more than 5 percentage points in Dice score. The EfficientNet-B7 backbone achieves a micro-average AUC of 0.97 across eight lesion classes, with a melanoma AUC of 0.99. Color quantification uses K-means clustering with a threshold calibrated on the PH2 dataset (MSE = 1.425). Applied to 87 wide-angle images, the mole detection module achieved an F1 score of 86%. The system outputs a structured CSV of per-lesion ABCD scores suitable for clinical triage and longitudinal tracking. A clinical validation study with dermatologists and surgeons is underway to assess concordance between automated and expert assessments.

Peripheral whole-blood gene expression profiling offers a minimally invasive route to lung cancer detection, but high-dimensional transcriptomic data are prone to optimistic bias when preprocessing and model selection are not properly separated from performance evaluation. We applied L1-penalised (LASSO) logistic regression to 303 peripheral whole-blood microarray profiles (123 lung cancer cases and 180 healthy controls; Gene Expression Omnibus accession GSE252168; Illumina HumanHT-12 v4) within a leakage-free nested cross-validation framework (5 outer and 3 inner folds), in which all data-dependent steps (imputation, univariate feature screening by ANOVA F-test with k = 500, and standardisation) were confined strictly to training partitions. Statistical significance was assessed by permutation testing (B = 100), and feature selection stability was quantified across outer folds. LASSO was compared with ridge logistic regression, linear support vector machines, and random forest under the same framework. The LASSO model identified a sparse 29-probe signature with a pooled out-of-fold area under the ROC curve (AUC) of 0.990 (nested estimate 0.989 +/- 0.015), accuracy 97.4%, sensitivity 94.3%, and specificity 99.4% at a 0.50 threshold; permutation testing confirmed significance (p = 0.0099). Six probes, including CDC42, U2AF1, and RPS15A, were selected in all five outer folds, forming a stable core, and all classifiers exceeded AUC 0.987, indicating a strong, algorithm-independent signal. A leakage-free nested cross-validation framework enables unbiased performance estimation and reproducible feature selection in blood-based lung cancer classification. The 29-probe panel is an internally validated candidate requiring prospective, multicentre external validation before clinical use.

Background The NEO-EXCEL trial hypothesised that aromatase inhibitor (AI)-activity as neoadjuvant endocrine therapy for early-stage breast cancer in postmenopausal women may be enhanced in combination with cyclooxygenase-2 (COX-2) inhibition. Methods NEO-EXCEL was a phase III, placebo-controlled, randomised trial in postmenopausal women with oestrogen receptor (ER)-positive resectable breast cancer with tumours [&ge;]2cm. Women were randomised (1:1:1:1): exemestane (25mg od) plus celecoxib (400mg bid), exemestane (25mg od) plus placebo (bid), letrozole (2.5mg od) plus celecoxib (400mg bid), or letrozole (2.5mg od) plus placebo (bid). Primary endpoint was clinical response (complete/partial) measured by callipers at 16 weeks; a standard assessment method at the time of trial inception. Sixteen-week ultrasound-determined response was the main secondary outcome to verify the calliper-based primary. Analysis was intention-to-treat. Results Due to slow accrual the trial design was redesigned from a definitive 2x2, 1000 patient trial to one randomising 269 patients between 20-Nov-2007 and 29-Apr-2014; 34.9% were human epithelial growth factor receptor 2-positive. AI+celecoxib produced a significantly greater objective clinical response than AI+placebo (72.9% vs 55.6%, P=0.003), which remained after adjustment for AI type and stratification factors (odds ratio = 2.3; 95% CI 1.3-3.8, P=0.003). Ultrasound-determined response was however not significantly enhanced (48.7% [AI+celecoxib] vs 41.2% [AI+placebo], P=0.34). Progression free survival and overall survival remained similar (median follow-up = 5.1 years [range 0.1-7.1]). Conclusions NEO-EXCEL is the first completed, phase III double-blind, placebo-controlled trial testing the addition of celecoxib to AI as neoadjuvant endocrine therapy in early breast cancer. Clinical response showed significant improvement but there was no significant ultrasound-determined response improvement nor any surgical or long-term outcome evidence of AI+COX-2 inhibition improving treatment outcomes for ER+ early resectable postmenopausal breast cancers. Use of short-term celecoxib at 400mg bd for 16 weeks was safe with no excess cardiotoxicity observed.

Background: Breast cancer survivors often experience psychological distress that may increase suicide risk. Marital status, a proxy for social support, may influence this risk, but its role within a competing-risk framework is unclear. This study examined the association between marital status and suicide mortality and assessed modification by socioeconomic and geographic factors. Methods: This is a population-based cohort study using SEER data, including adults diagnosed with primary breast cancer from 2000 to 2022. Marital status was classified as married/partnered or unmarried/non-partnered. Baseline characteristics were balanced using subdistribution inverse probability of treatment weighting (sIPTW). Suicide mortality was analyzed using sIPTW-weighted Fine-Gray competing-risk models, treating non-suicide deaths as competing events. Landmark, subgroup, interaction, and sensitivity analyses were performed. Results: Among 825,047 patients, 40.7% were unmarried. Covariates were well balanced after weighting (SMD <0.01). During follow-up, 529 suicide deaths occurred. Unmarried status was associated with higher suicide mortality (sHR = 1.34, 95% CI: 1.12-1.60). Male sex and estrogen receptor-negative tumors increased risk, while older age and non-White race were protective. Findings were consistent in Cox models (HR = 1.45) and sensitivity analyses (sHR = 1.42). Landmark analyses showed persistent associations at 1, 3, and 5 years. The association was attenuated in the highest income quartile but not modified by rural-urban status. Conclusions: Unmarried breast cancer patients had higher suicide mortality. These findings support integrating psychosocial assessment and targeted suicide prevention into survivorship care, especially for socially vulnerable groups.

Background: Interleukin-6 (IL-6) signalling drives chronic inflammation and is therapeutically targeted by tocilizumab, an approved IL-6 receptor inhibitor. Whether genetically proxied lifelong IL-6 inhibition causally influences the risk of hepatocellular carcinoma (HCC) or colorectal cancer (CRC) remains unanswered. Prior single-variant estimates from pooled observational data are methodologically limited and may reflect confounding. Methods: A two-sample drug-target Mendelian randomization (MR) study was conducted. Four independent cis-acting protein quantitative trait loci (pQTL) variants within the IL6 and IL6R gene loci (rs2228145, rs4129267, rs7529229, rs1800795) were selected as genetic instruments , with F-statistics ranging from 32.3 to 120.5, confirming instrument strength. Outcome data were obtained from four independent genome-wide association studies: HCC from BioBank Japan (BBJ; 1,866 cases, 195,745 controls), HCC from FinnGen Release 10 (674 cases, 218,118 controls), CRC from a European meta-analysis (19,948 cases, 12,124 controls), and CRC from BBJ (7,062 cases, 195,745 controls). Causal estimates were derived using inverse variance weighted (IVW) regression as the primary method, with MR-Egger and weighted median analyses as sensitivity methods. Cochran Q statistics assessed heterogeneity and MR-Egger intercept testing assessed directional pleiotropy. Results: Genetically proxied IL-6 inhibition showed no significant causal effect on HCC risk in East Asian populations (IVW odds ratio [OR] 0.997, 95% confidence interval [CI] 0.903 to 1.101, p=0.953) or European populations (IVW OR 0.984, 95% CI 0.802 to 1.208, p=0.880). Similarly, no causal effect was observed on CRC risk in European populations (IVW OR 1.015, 95% CI 0.957 to 1.075, p=0.623) or East Asian populations (IVW OR 0.999, 95% CI 0.948 to 1.052, p=0.971). Sensitivity analyses confirmed the absence of directional pleiotropy and heterogeneity across all four analyses. Leave-one-out analyses demonstrated that no single instrument drove the null findings. Conclusions: Genetically proxied IL-6 receptor inhibition, modelling the therapeutic effect of tocilizumab, showed no causal effect on HCC or CRC risk across four independent cohorts and two ancestries. These findings do not support a role for IL-6 pathway inhibition in the prevention of these cancers and provide reassuring genetic safety evidence regarding cancer risk in patients receiving tocilizumab. Larger HCC-specific GWAS are needed to definitively evaluate modest effects in this cancer type.

The therapeutic landscape for hepatocellular carcinoma (HCC) is evolving rapidly, necessitating scalable approaches to synthesize the expanding scientific literature. We characterized thematic shifts in HCC treatment and prognosis research by conducting a retrospective bibliometric analysis of influential publications from 2023 and 2024. Using the OpenAlex database, we identified the 50 most highly cited papers from each year based on eighteen-month post-publication citation counts. Large language models were deployed to extract, normalize, and classify concepts from unstructured text into canonical topics and parent themes, enabling quantitative year-over-year frequency comparisons. Analysis of these 100 papers revealed a distinct maturation in research focus. Although broad categories like general immunotherapy remained prevalent, their relative frequency declined in favor of specific dual immune checkpoint regimens, notably CTLA-4 inhibition and the durvalumab plus tremelimumab combination. Concurrently, parent themes related to radiomics, imaging, and health systems exhibited significant growth in the 2024 cohort. These findings demonstrate a thematic transition in high-impact HCC research from foundational immuno-oncology toward optimized combination therapies and precision diagnostics. Furthermore, this study highlights the utility of artificial intelligence-driven bibliometrics for objectively tracking dynamic conceptual shifts in oncology. A web interface for exploring the data is available at https://pri.pepkio.com/.

Cutaneous squamous cell carcinoma (cSCC) is the second most common form of cancer worldwide. While most cSCCs are not life-threatening, 2-5% of patients develop metastases. To better understand what causes some cSCCs to progress to metastatic disease, we assembled a nationwide cohort of 19,120 patients with clinico-pathologically annotated tumors linked to metastatic outcome. RNA-sequencing was performed on 378 tumors, and whole-exome sequencing on 147, with balanced numbers of tumors that progressed to metastatic disease (cases) and did not (controls). UV radiation was the dominant mutational signature with additional contributions from aging, APOBEC activity, and, in immunosuppressed patients, azathioprine exposure. We identified 38 genes under selection across a core set of signaling pathways. Gene expression clusters were primarily associated with the differentiation state of tumor cells and secondarily with the composition of the tumor microenvironment. Several mutational and transcriptional programs were associated with metastasis, including a dedifferentiated gene expression signature, activating mutations in the RAS signaling pathway, loss-of-function alterations in the SWI/SNF chromatin remodeling complex, and specific arm-level copy number alterations. A 23-gene expression signature was built to predict metastasis from primary cSCC tissue. The signature was validated in two independent cohorts (N=102 and 52), where it predicted metastasis independently of staging systems. Together, these findings provide the most detailed molecular portrait of cSCC to date and establish an assay for risk stratification suitable for clinical implementation.

Background The value and optimal timing of circulating tumour DNA (ctDNA) analysis in locally advanced oesophageal adenocarcinoma (OAC) is uncertain. We hypothesised that perioperative detection would predict event-free (EFS) and overall (OS) survival, and that 3-6 months post-operative detection would predict recurrence. Methods In this prospective multi-centre cohort study, tumour-informed ctDNA assays were designed for 49 patients using whole-exome sequencing. Bloods were collected for ctDNA detection up to 8 days prior to surgery, and at 3-6 weeks and 3-6 months post-surgery, then correlated with clinicopathological characteristics, EFS and OS. Results Pre- and early post- surgery ctDNA positivity were associated with worse EFS (HRs 7.97 (95% confidence interval, CI 2.64-24.04), p<0.0001; 8.18 (95%CI 3.23-20.69), p<0.0001) and OS (HRs 7.82 (95%CI 2.22-27.54), p=0.00018; 13.69 (95%CI 4.52-41.49), p<0.0001). In pre-surgery positive patients, post-surgery ctDNA clearance associated with improved EFS and OS, and predicted better OS in those with a poor histopathological response to neoadjuvant treatment. 3-6 month ctDNA-positivity preceded standard-of-care recurrence detection by median 53.5 (interquartile range 39.3-200.0) days. Conclusions Perioperative ctDNA positivity associates with worse EFS and OS in OAC, identifying a subgroup with improved outcomes despite adverse pathological features. ctDNA testing at 3-6 months predicts recurrence earlier than standard-of-care surveillance.

Importance: Combinations of VEGFR tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs), such as antibodies to programmed cell death-1 (PD-1), or to its ligand PD-L1, are now first-line standard of care for renal cell carcinoma (RCC), but the pivotal clinical trials excluded patients with common comorbidities, leaving their real-world effectiveness uncertain. Objective: To determine whether adding PD-1/PD-L1 inhibitors to VEGFR-TKIs therapy is associated with improved overall survival in a real-world RCC cohort. Design, Setting, and Participants: This retrospective cohort study used a target trial emulation framework and real-world electronic health records data from the University of Florida Health Integrated Data Repository (IDR). Data was analyzed from September 2009 through June 2023. Adult patients ([&ge;]18 years) with confirmed RCC and at least one VEGFR-TKIs prescription were eligible. The date of the first VEGFR-TKIs prescription was defined as the index date, and patients were followed for up to 24 months. Variable-ratio propensity score matching (up to 2:1) across 13 baseline covariates was used to emulate randomized treatment assignments. Of 107,783 patients screened, 387 met eligibility criteria, and 319 remained in the matched cohort. Exposures: VEGFR-TKIs monotherapy (control group) versus VEGFR-TKIs combined with PD-1/PD-L1 inhibitors (experimental group). Main Outcomes and Measures: Overall survival (OS), analyzed by weighted Kaplan-Meier estimation, cluster-robust Cox regression, and restricted mean survival time (RMST) at {tau} = 24 months, prespecified given anticipated non-proportional hazards. Results: Among 319 matched patients (mean [SD] age, 62 [12] years; 76% male), 107 deaths occurred (33.5%). Twelve-month OS was higher in the combination arm (81.8%; 95% CI, 74.7--89.6%) than VEGFR-TKIs monotherapy (68.1%; 95% CI, 61.1--76.0%), converging by 24 months (61.1% vs 56.7%). The Cox hazard ratio was 0.718 (95% CI, 0.484-- 1.064; P = 0.0986). RMST was 2.79 months greater with combination therapy (95% CI, 0.93-- 4.65; P = 0.0033). Conclusions: Adding PD-1/PD-L1 inhibitors to VEGFR-TKIs therapy was associated with a statistically significant and clinically meaningful gain in restricted mean survival, supporting the real-world generalizability of combination therapy and the importance of appropriate treatment effect measures under non-proportional hazards.

Background: Trastuzumab deruxtecan (T-DXd) is active in HER2-expressing solid tumours, but trials excluded HER2 immunohistochemistry (IHC) 1+ disease, and data in pretreated ovarian cancer are lacking. We evaluated real-world T-DXd activity and genomic correlates in pretreated ovarian cancer, predominantly high-grade serous (HGSOC). Methods: HER2 expression was assessed in an unselected ovarian cancer cohort (N=74). Fifteen patients receiving off-label T-DXd (14 HGSOC, 1 clear cell; IHC 1+ to 3+) had HER2 status centrally confirmed using gastric-type criteria. Activity was assessed by intra-patient growth modulation index (GMI; progression-free survival [PFS] on T-DXd divided by PFS on the prior line; [&ge;] 1.33 considered meaningful). Patients on treatment at data cut-off were censored. Objective response (RECIST 1.1) was assessed centrally where imaging was available (n=8). Results: Of the 40 HER2-expressing tumours, 15 received T-DXd, limited mainly by reimbursement. Among 14 evaluable patients (median 5 prior lines), 9 reached a GMI [&ge;] 1.33 (median 1.69); 8 remained on treatment at cut-off, making durability preliminary. Confirmed partial responses occurred across the HER2 spectrum. Benefit was independent of homologous-recombination (HR) status: one HR-proficient, CCNE1-wild-type patient achieved prolonged control and was rendered disease-free after radiotherapy to an oligoprogressive lesion. Exploratory analysis showed all four evaluable CCNE1-amplified tumours had reduced or non-durable benefit. Conclusions: T-DXd shows preliminary, clinically meaningful activity in HER2 IHC 1+ ovarian cancer independent of HR status. CCNE1 amplification may attenuate benefit, a candidate biomarker for WEE1-inhibitor combinations. Approval restricted to IHC 3+ disease would exclude most responders in this cohort. Prospective validation is required.

Background. Duodenal adenocarcinoma (DA) is a rare gastrointestinal malignancy with limited DA-specific evidence on the prognostic role of perineural invasion (PNI) and the performance of AJCC 8th-edition staging. We described PNI, AJCC 8 discrimination, and adjuvant-chemotherapy subgroup associations in a single-center cohort. Methods. We retrospectively analyzed 51 patients with curatively resected, histologically invasive DA (2013-2025). Overall survival (OS) and disease-free survival (DFS) were estimated by Kaplan-Meier analysis; prognostic associations by Cox regression. Model discrimination was quantified by the C-index; adjuvant-chemotherapy associations were explored across pre-specified subgroups. Analyses were exploratory and hypothesis-generating. Results. Median follow-up was 34.9 months; 26 patients (51%) died and 32 (63%) recurred, with the highest recurrence frequency 6-12 months after surgery. AJCC 8 staging discriminated modestly (C-index 0.595); no adjacent stage pair differed significantly after Bonferroni correction (minimum raw pairwise P = 0.051). Among candidate factors, PNI had the largest effect estimate (univariable HR 2.08, 95% CI 0.88-4.90, P = 0.095) and the largest incremental discrimination when added to a stage + T + N base model (delta C-index +0.062; likelihood-ratio P = 0.145), exceeding the increments from tumor size (+0.046), differentiation (+0.034), and sex (+0.016). Adjuvant chemotherapy was associated with hazard-ratio reductions in PNI-positive (HR 0.19, 95% CI 0.02-1.59), stage III (HR 0.36, 95% CI 0.12-1.15), and node-positive (HR 0.36, 95% CI 0.12-1.15) subgroups; none reached statistical significance, consistent with limited power in subgroups of 8-22 patients. Conclusion. In this small single-center cohort, PNI showed the largest prognostic effect estimate among candidate variables and the largest incremental discrimination beyond AJCC 8 stage, although neither reached statistical significance and AJCC 8 discriminated only modestly. These hypothesis-generating findings - directionally concordant with larger published DA series - support formal evaluation of PNI as a stratification variable in multicenter cohorts and in individual-patient-data meta-analyses of duodenal adenocarcinoma, rather than a change in current practice.

Introduction: This study aimed to provide population level survival trends during the era in which new systemic therapies transformed treatment guidelines for metastatic cancer, as well as insights on the real world use of these treatments and associated survival. Methods: Adults diagnosed with synchronous metastatic solid cancer in 2008 until 2022 (22 cancer types) were identified from the Netherlands Cancer Registry. Median overall survival (OS) was assessed by five year diagnostic period. For 2018 until 2022, systemic therapy use in any treatment line was analyzed and survival percentiles within treatment and cancer types were estimated with Kaplan Meier survival analyses. Results: Median OS in the overall cohort (n=280,419 patients) improved from 6 to 8 months between the period 2008 until 2012 and 2018 until 2022. Among patients diagnosed in 2018 until 2022, 15% received immunotherapy, 15% targeted therapy, 29% chemotherapy and/or traditional hormone therapy only, and 39% no systemic therapy. In some cancer types, a relatively large proportion of treated patients had longterm survival (e.g., immunotherapy in melanoma: p50 = 67 months). Other cancer types had a smaller subset of treated patients (p10 and p25) with substantially better outcomes than the median (e.g., targeted therapy in NSCLC: p50 = 22 months, p10 = 96 months). Conclusion: Population level survival for patients with synchronous metastatic solid cancer has modestly improved over time. The marked survival heterogeneity within cancer and treatment types highlights both the potential and uncertainty associated with (novel) treatments. Improved prediction of treatment effects and clear communication regarding survival expectation remain critical. Presenting multiple survival scenarios over median survival alone can support decision making.

Three audiences -- the family of a newly diagnosed Ewing sarcoma patient, the long-term survivor, and the cooperative-group trial statistician -- receive cohort-mean answers to patient-level questions because the patient-level data machine learning requires do not exist for rare cancers. We present a framework producing patient-level predictions from published aggregate trial data. A six-stage discrete-event Monte Carlo simulation integrates genetic risk factors, serial biomarker dynamics with genotype-conditional weighting, post-surgical ctDNA-based minimal residual disease (ctDNA-MRD) assessment, and treatment-related mortality as a separable competing risk. Adverse-effects modules project 30-year incidence across five organ systems from chemotherapy and radiation exposures. Its four structural ingredients are instantiated in Ewing sarcoma and validated against trial data from more than 3,400 patients. The framework achieves 3.2% mean absolute error across 23 efficacy endpoints (none exceeding 6%) and falls within published confidence intervals for all 20 toxicity endpoints. ctDNA-MRD stratification separates candidate populations -- 5.5% recurrence (de-escalation) versus 87.8% (intensification) -- and multi-timepoint integration produces 16-fold five-year EFS resolution spanning 5-96%, exceeding the 3- to 5-fold ranges of single-timepoint approaches. The 16.1-fold recurrence risk ratio emerges from simulation, not as a supplied parameter. Genotype-conditional weighting improves discrimination over equal-weight scoring in every subgroup (Pearson r +0.060 to +0.129), with largest gains where biological rationale is strongest. A Monte Carlo framework calibrated to published aggregate data turns cohort-mean answers into patient-level predictions as exemplified in the rare cancer Ewing sarcoma, where the conventional patient-level machine-learning pathway is structurally unavailable; transfer to other rare cancers remains a hypothesis for future validation. Survivorship-surveillance refinement is the most concrete current use; trial-design and prognostic counseling are next-decade pathways.

Background: Cardiotoxicity remains a key concern of HER2-directed therapies, with no proven prevention strategies. The success of cardioprotective interventions will depend not only on efficacy, but on patient acceptability, an underexplored determinant of trial participation and clinical implementation. Objectives: To evaluate willingness to take cardioprotective medication and identify factors influencing decision-making among individuals with HER2-positive breast cancer. Methods: We conducted a cross-sectional online survey of adults with HER2-positive breast cancer in Australia and the United States. The survey assessed willingness, beliefs regarding benefits and risks, and treatment preferences. Multivariable logistic regression examined associations between clinical and demographic characteristics and willingness. Results: Among 74 respondents (Australia n=24; United States n=50), 74.3% reported being likely or very likely to take cardioprotective medication. Physician recommendation emerged as a dominant driver (79.1%). While most participants valued long-term cardiovascular health (72.9%), uncertainty regarding benefit was common (60.4%). Cancer-related outcomes were prioritized over cardiovascular outcomes. Participants demonstrated flexibility regarding treatment burden, including willingness to take multiple medications and continue therapy long term. No demographic or clinical predictors of willingness were identified. Perceived acceptability, appropriateness, and feasibility were consistently high. Conclusions: Willingness to adopt cardioprotective strategies is high but conditional, shaped by cancer priorities, clinician endorsement, and uncertainty regarding benefit. These findings highlight patient acceptability as a critical, and often overlooked, determinant of successful trial participation and downstream clinical implementation in cardio-oncology.

Abstract Introduction: The optimal examined lymph node (ELN) count after resection for pancreatic body/tail ductal adenocarcinoma (PDAC) remains uncertain. Guidelines recommend 12-15 nodes, but the value of higher thresholds is unclear. Method: SEER patients with pancreatic body/tail PDAC undergoing resection from 2000 to 2020 were analysed. Survival-anchored ELN thresholds were assessed using log-rank cut-point search, segmented Cox analysis, adjusted restricted cubic splines, and overlap-weighted restricted mean survival time (OW-RMST). A structured synthesis of 17 studies compared threshold attainment after conventional distal pancreatectomy (DP), radical antegrade modular pancreatosplenectomy (RAMPS), and posterior/artery-first approaches. Results: Among 5107 patients, 3630 deaths occurred (71.1%). Log-rank analysis identified ELN = 12 as the optimal binary cut-point; segmented Cox analysis identified ELN = 21 as a change point (bootstrap 95% CI 6.0-35.0). Adjusted splines showed a nonlinear inverse association between ELN and mortality, with attenuation beyond approximately 21 nodes. Each 5-node increase in ELN was associated with lower mortality (HR 0.964, 95% CI 0.949-0.980; P < 0.001). At 60 months, OW-RMST gains for ELN >= 12, >= 14, and >= 21 were 2.59, 2.31, and 2.60 months. Estimated probabilities of achieving ELN >= 21 were 16.5% after conventional DP, 40.0% after RAMPS, and 82.7% after posterior/artery-first approaches, with lowest certainty for the latter. Conclusion: ELN >= 12 is a minimum quality benchmark after resection for pancreatic body/tail PDAC, whereas approximately 21 nodes may be a higher-yield target. RAMPS may improve target attainment, but survival superiority remains unproven.