The Philadelphia chromosome-negative myeloproliferative neoplasms (MPNs) are a group of haematological malignancies triggered by a driver mutation, most commonly the JAK2 V617F mutation, which is acquired in a haematopoietic stem cell. The diseases are characterised by an overproduction of myeloid cells and may result in severe complications such as thrombosis, myelofibrotic transition, and potentially progression to acute myeloid leukaemia. Treatment with interferon-α (IFN-α) can potentially deplete the disease-driving malignant stem cell population, thereby leading to long-term remission. We extend a mechanistic compartmental differential equation model of MPN progression to account for the effects of IFN-α treatment. In agreement with experimental mouse studies, we assume that IFN-α acts through effects on malignant stem cell differentiation and malignant progenitor and precursor cell apoptosis. We use a hierarchical Bayesian inference procedure to infer the drug response parameters of the model based on measurements of the JAK2 V617F variant allele frequency (VAF) for N=56 patients from the Danish DALIAH study, both on the individual and the population level, with 14 patients left out for subsequent testing. The model estimates are found to agree with data. The drug response parameters are found to act synergistically on the reduction of JAK2 VAF, with the model being able to capture qualitatively different types of treatment responses. Using the inferred information about the population distribution of drug response parameters is found to improve predictions compared to predictions without prior knowledge on a testing cohort. Such predictions may aid clinical decision-making regarding IFN-α treatment in patients with MPNs.

Gastric cancer (GC) is one of the most common malignant tumors worldwide, with Helicobacter pylori-associated intestinal-type gastric cancer (IGC) being the most prevalent subtype, accounting for approximately 85% of cases. Because most patients are diagnosed at intermediate or advanced stages, early screening and accurate stage stratification of IGC progression remain major clinical challenges.

This study aimed to develop an interpretable machine learning (ML) model that leverages routine laboratory indicators to perform stage-specific diagnosis for patients across different stages of IGC.

Data from 2180 patients with known H pylori infection status were collected at 2 centers and included healthy controls (HCs), nonatrophic gastritis, atrophic gastritis, intestinal metaplasia, and GC. After excluding cases with severe (>25%) missing data, 1784 patients were included for model development and validation. Data imputation and feature selection were performed, and synthetic minority oversampling technique (SMOTE) augmentation was applied to the internal training dataset to improve the diagnostic performance of the model. Six ML algorithms were developed. Model performance and clinical decision-making utility were evaluated using multiple metrics and approaches, while Shapley Additive Explanations (SHAP)-based interpretability was used to identify key indicators and provide threshold reference values for them. Finally, a web-based tool was developed based on the Streamlit platform.

Through feature selection, 27 features were ultimately retained for final model construction. Among the 6 algorithms, CatBoost (categorical boosting) demonstrated the best performance, achieving an internal validation accuracy of 80.91%, sensitivity of 78.57%, and specificity of 95.27%. In the Guangdong Provincial People's Hospital (GDPH) and Shengli Oilfield Central Hospital (SOCH) external validation cohorts, CatBoost maintained robust performance, with accuracies of 79.96% and 83.37%, sensitivities of 76.82% and 84.91%, specificities of 93.14% and 95.73%, and area under the curves (AUCs) of 0.94 and 0.97, respectively. Confusion matrix analysis showed that the model was particularly reliable in identifying extreme disease states, including HCs and GC, whereas misclassifications mainly occurred between adjacent intermediate pathological stages. Calibration curves and Brier scores indicated good agreement between predicted and observed outcomes. Decision curve analysis (DCA) further confirmed the clinical net benefit across relevant threshold ranges. SHAP-based interpretability analysis identified monocyte count (MONO%), albumin/globulin ratio (A/G), basophil percentage (BASO%), platelet distribution width (PDW), total bilirubin (DBIL), neutrophil count (NEUT#), age, lymphocyte count (LYMPH#), creatinine (CREA), and aspartate aminotransferase (AST) as important contributors, reflecting inflammatory, hematological, nutritional, and metabolic changes during IGC progression. Based on these features, a lightweight predictive model was developed and deployed as a web-based application to facilitate translational and practical applications.

This study developed an interpretable ML model based on routine laboratory data for stage-specific prediction of H pylori-associated IGC progression, with promising applicability as an auxiliary diagnostic tool.

Ground-glass nodules (GGNs) remain challenging to diagnose using endobronchial ultrasound-guided transbronchial biopsy (EBUS-TBB) due to limited visibility and low tissue yield. We evaluated a multimodal bronchoscopic approach and investigated a radiographic predictor of EBUS invisibility to guide the use of cone-beam computed tomography (CBCT).

In this single-center retrospective study, patients with GGNs (consolidation-to-tumor ratio <50%) who underwent EBUS-TBB followed by transbronchial cryobiopsy (TBC) using ultrathin bronchoscopy with intraprocedural CBCT between January 2022 and December 2024 were included. The primary endpoint was diagnostic accuracy.

Ninety patients were included. Diagnostic accuracy was 68.9% for EBUS-TBB with CBCT and 76.7% for TBC (p = 0.241). Combined biopsy improved accuracy  over TBB alone (85.6% vs. 68.9%, p = 0.008), with higher diagnostic accuracy across predefined subgroups. After Bonferroni correction, statistically significant remained only for lesions not visible on chest radiography. TBC yielded larger samples (16.8 vs. 3.7 mm², p < 0.001). Lower HU values were independently associated with EBUS invisibility (adjusted odds ratio per 10-HU decrease, 1.30; 95% CI, 1.08-1.57; p = 0.006). Receiver operating characteristic analysis demonstrated excellent discrimination (area under the curve, 0.94), with an optimal cutoff of -541.95 HU. No life-threatening bleeding, mortality, intensive care unit admission, or surgical intervention occurred.

A multimodal bronchoscopic approach provides favorable diagnostic yield for GGNs, and the combined use of forceps biopsy and TBC improves diagnostic performance and tissue acquisition. Lower HU values predict EBUS invisibility and may help guide the selective use of CBCT.

Systemic light chain amyloidosis (AL) is a life-threatening disease in which dexamethasone (Dex) is a core therapy but is limited by cumulative toxicity. The optimal duration of Dex, particularly in the era of daratumumab (Dara)-based regimens, is uncertain.

We retrospectively analyzed 216 newly diagnosed AL amyloidosis patients (2017-2023). Dex exposure was categorized as limited (≤3 months) or prolonged (>3 months) using restricted cubic spline-derived associations with hematologic response kinetics. Outcomes included hematologic and organ response, toxicity, and overall survival.

Median Dex duration was 5.5 months and was similar by Dara use. Overall response rates exceeded 90% at 6 months in both Dex groups. Limited Dex was associated with higher rates of early deep hematologic response (VGPR or better 77.5 vs 56.5%, p = 0.001; CR 42.2 vs 19.4%, p < 0.001), reflecting faster response kinetics, while overall response rates were similar. Among patients receiving limited Dex, Dara was associated with higher 6-month CR rates (66.7 vs 30.4%, p < 0.001) and increased likelihood of achieving CR in multivariable analysis (HR 4.38, 95% CI 2.44-7.85; p < 0.001). Organ responses were similar between groups. Dex-related toxicities increased after 6 months, and hospitalization was associated with worse survival.

Limiting Dex exposure was associated with preserved efficacy and reduced toxicity. Prolonged Dex was associated with increased toxicity without improving overall hematologic or organ outcomes, supporting limited Dex duration in frontline AL amyloidosis therapy.

Fatigue is a common debilitating symptom of breast cancer (BC), and its treatment may result in a significant symptom burden and affect adherence to treatment. Graded exercise therapy (GET) and cognitive behavioral therapy (CBT) have separately been shown in previous studies to be beneficial for the management of cancer-related fatigue.

This study's coprimary aims are to assess the feasibility and acceptability of combining GET and CBT for the treatment of fatigue in patients with BC in Singapore. The secondary aims are to generate preliminary efficacy estimates of the combination therapy.

In this randomized controlled pilot study, a total of 100 female patients with BC, with a self-reported rating of at least moderate fatigue (One-Item Fatigue Scale score ≥4), will be recruited and randomized in a 1:1 ratio to undergo a combination of GET and CBT vs GET alone (standard of care). This will include a primary cohort of 90 patients with stage I to III BC who have completed surgery and adjuvant chemotherapy (if indicated), and an exploratory cohort of 10 patients with stage IV BC undergoing systemic therapy. Acceptability will be measured using the Client Satisfaction Questionnaire, including items on cultural sensitivity. Feasibility will be measured by participant uptake, adherence to sessions, and willingness to pay for therapy sessions. Efficacy will be assessed based on quantitative measures of fatigue, treatment adherence, quality of life, and physical and functional outcomes.

Recruitment of participants commenced on July 14, 2025, and is projected to be completed by December 31, 2026. The primary completion date is expected to be April 30, 2027, and publication of the final results is expected by the end of 2027.

This study will provide evidence on whether a combination of GET and CBT is feasible and acceptable for the treatment of fatigue in patients with BC in Singapore. It supports the refinement of evidence-based fatigue management guidelines and improvements in BC survivorship care.

Molecular classification has refined risk stratification in endometrial cancer and is now incorporated into the 2023 International Federation of Gynecology and Obstetrics (FIGO) staging system. However, prospective real-world data on its impact on multidisciplinary tumor board (MDT) decision making remain limited. We evaluated the impact of molecular information on adjuvant treatment recommendations in stage I to II endometrial cancer.

This prospective observational study included patients with surgically treated FIGO 2023 stage I to II endometrial carcinoma discussed at MDT between February 2024 and December 2025. Clinicopathologic risk stratification was performed using the ESGO-ESTRO-ESP 2016 criteria. Molecular classification was determined using POLE sequencing and immunohistochemistry for mismatch repair (MMR) and TP53. Estrogen receptor status was not assessed, as no specific molecular profile (NSMP) subclassification was part of the operative framework during the study period. MDT recommendations were recorded before and after the integration of molecular results.

A total of 122 patients were included. Molecular subtypes were NSMP in 55 (45.1%), MMR-deficient in 41 (33.6%), TP53-abnormal in 24 (19.7%), and POLE-mutated in two (1.6%). Integration of molecular classification changed MDT recommendations in 25 cases (20.5%), with escalation in 15 (12.3%) and de-escalation in 10 (8.2%). Therapy modification was most frequent in TP53-abnormal tumors (62.5%) compared with other subgroups (10.2%; odds ratio, 14.7 [95% CI, 5.1 to 42.1]; P < .001). No treatment changes were observed in NSMP or POLE-mutated tumors. The net incremental treatment cost was ₹11.8 lakh across the cohort; including molecular testing, the overall incremental cost was ₹34,672 per patient (∼$418 US dollars).

Integration of molecular classification modified adjuvant treatment in approximately one fifth of patients. Changes were biologically consistent, supporting the feasibility and clinical utility of molecularly integrated MDT decision making in early-stage endometrial cancer even in resource-constrained settings.

Breast cancer represents a major public health burden in Sudan, where most patients are diagnosed at advanced stages and access to comprehensive diagnostic and molecular services remains limited. Current treatment strategies are largely extrapolated from non-African populations, despite the substantial genetic diversity across African populations that may significantly influence drug response, efficacy, and toxicity. Pharmacogenomics offers a promising approach to optimize breast cancer therapy through genetically informed treatment decisions; however, its clinical application in Sudan and across Africa remains limited. This narrative review synthesizes published evidence on pharmacogenetic determinants influencing breast cancer treatment, with a particular focus on African and Sudanese populations. Relevant studies published between 2005 and 2026 were identified through searches of PubMed, Google Scholar, and PharmGKB. A qualitative synthesis was conducted to summarize key pharmacogenes, population-specific genetic variability, and their potential clinical and therapeutic implications. Considerable interethnic variability has been reported in pharmacogenes involved in drug metabolism and transport, including CYP2D6, CYP3A4, CYP2B6, DPYD, and ATP-binding cassette transporter genes. African populations exhibit distinct allele frequency patterns that may substantially affect drug disposition, therapeutic efficacy, and toxicity, particularly for endocrine therapies and commonly used chemotherapeutic agents. These differences limit the direct applicability of pharmacogenomic data derived from European and Asian populations and underscore the need for population-specific evidence. Integrating pharmacogenomics into breast cancer management has the potential to improve treatment effectiveness and safety in Sudan. Achieving this goal requires the generation of locally relevant pharmacogenomic data, strengthened diagnostic and laboratory infrastructure, and a stepwise, context-appropriate incorporation of pharmacogenomic principles into clinical practice. Such an approach is important to support equitable and effective precision oncology for Sudanese and African populations.

Clinical trial availability often varies between countries, independent of the local burden of disease. We aimed to evaluate the current global availability of prostate cancer clinical trials and the factors affecting it.

We searched for clinical trials involving prostate cancer between June 2019 and June 2024 through Clinicaltrials.gov. Noninterventional trials were excluded. Countries were classified according to the World Bank Ranking (WBR) as high-, upper-middle-, lower-middle-, and low-income countries (HICs, UMICs, LMICs, and LICs). Multivariable negative binomial regression was used to evaluate the association between the number of trials and country's characteristics. Multivariable logistic regression was used to evaluate the association between trial availability and country's characteristics. In addition, we collected data on sponsorship, funding, intervention, intervention intent, end point selection, trial phase, and cancer stage.

Of the 1,531 trials identified, 1,413 met the eligibility criteria. Most trials were conducted exclusively in HICs (80.4%), included patients with metastatic disease (55.4%), and were sponsored by academia (68.8%). Pharma-funded trials had a higher number of participating countries (mean 2.7 v 1.0, P < .001) and were more likely to include metastatic disease (72.0% v 32.3%, P < .001) and to investigate systemic therapy (76.3% v 29.4%, P < .001). In the multivariable analysis, WBR, gross national income (GNI), and annual health expenditure were all associated with the presence of at least one trial (P < .001). Only GNI was independently associated with the number of trials within a country (P < .001).

Prostate cancer trials are disproportionately concentrated in HICs despite a lower burden of disease. Intentional efforts are needed to ensure global representation and long-term benefits for populations historically excluded from research.

Cancer care capacity in sub-Saharan Africa (SSA) is constrained by late diagnosis and limited treatment access. Few funding mechanisms support innovative, locally led programs to address these challenges. A collaborative initiative was developed to strengthen oncology care through quality improvement (QI) projects.

The program was developed by Global Bridges Oncology (GBO) at Mayo Clinic, Pfizer Global Medical Grants, and the African Organisation for Research and Training in Cancer. A committee composed primarily of African oncology experts guided the process. An RFP was disseminated across SSA in English, French, and Portuguese, inviting applications to improve diagnostic and therapeutic cancer care. Applications underwent a structured, two-stage review, with GBO providing technical support, expert guidance, and training resources.

The RFP generated 218 applications reflecting strong demand for oncology QI funding in SSA. After review, 17 projects representing 10 African countries were selected and awarded $1.1 million USD. Funded initiatives reflected four themes: oncology training and clinical practice improvements, early detection and accurate diagnostics, pediatric cancer care, and oncology nursing and palliative medicine. As of March 2026, 11 (65%) of 17 projects are complete, with 4,565 health care professionals engaged through direct training, conference dissemination, system adoption, and sensitization activities, and program-supported services were delivered to more than 47,300 patients.

This initiative demonstrates the feasibility of a competitive, regionally guided grant program to strengthen cancer care capacity. Early implementation outcomes, including measurable improvements in diagnostic delay, treatment adherence, and care network expansion, confirm that locally led QI initiatives can generate meaningful results across diverse institutional settings. By centering African leadership and supporting diverse QI projects, it advances equitable access to funding, capacity building, and sustainability planning.

Motivated by the rising incidence of cancers at younger ages, this study compares tumor genomic alterations between adolescents and young adults (AYAs; 18-39 years) and non-AYAs (40 years and older) and explores the relationship with continuous age in patients with relapsed/refractory ovarian, breast, and colorectal cancers accrued to the NCI-MATCH trial.

Tumor genomic profiles generated by a next-generation sequencing 143-gene panel (NCI-MATCH assay, v2) were analyzed for association with age (AYA/total: 21/455 ovarian, 27/576 breast, 43/759 colorectal cancers). For each gene, AYA and non-AYA DNA alteration proportions were compared (Fisher exact test) and alteration association with continuous age (logistic regression) was evaluated (false discovery rate‑adjusted P value <.1 statistically significant). For colorectal cancer, sex-stratified analysis was also performed.

No significant AYA versus non-AYA differences were observed in the prevalence of gene mutations (single nucleotide variant [SNV]/indel). A significant association of gene amplification with AYAs (odds ratio [OR], 95% CI) was CCND1 (0.2, 0.1-0.4), favoring AYAs in breast cancer. Examining age as a continuous variable, significant associations of gene mutations (SNV/indel) with older age, expressed as 5-year OR (OR [95% CI]), were observed: TP53 (1.3 [1.1 to 1.4]), ovarian cancer; CDH1 (1.4 [1.2 to 1.6]) and PIK3CA (1.1 [1.1 to 1.2]), breast cancer; and BRAF (1.4 [1.2 to 1.7]), female colorectal cancer. Associations with younger age included SMAD4 (0.8 [0.7 to 0.9]), male colorectal cancer. Significant associations of gene amplification with age (continuous) were as follows: CCNE1 (1.3 [1.1 to 1.6]), older ovarian cancer, and CCND1 (0.8 [0.8 to 0.9]), younger breast cancer.

Comparing AYAs with non-AYAs among patients having relapsed/refractory disease, no significant differences in SNV/indel prevalence were observed, but CCND1 amplifications were more prevalent in AYA breast cancer. For several genes, DNA alterations were associated with continuous age and may depend on sex in colorectal cancer.