Human papillomavirus (HPV) is a major global health concern due to its link to cervical and other cancers. Although HPV vaccination is highly effective, acceptance and willingness to pay (WTP) differ widely across populations. This review summarizes global evidence from 2015-2025. A systematic search of PubMed, Scopus, CENTRAL, Web of Science, and Google Scholar was conducted in 2025 following PRISMA guidelines. Studies reporting data on knowledge, acceptance, attitudes, and WTP across any population were included. Quality assessment used ISPOR checklists, and data were synthesized in Excel 2019. Thirty-five studies met inclusion criteria, with China and Nigeria contributing most. WTP ranged from 52.68% in lower-middle-income countries to 65.38% in low-income countries. Mean WTP was highest in upper-middle-income settings. Knowledge, positive attitudes, socioeconomic status, and trust increased WTP, while cost remained the primary barrier. Improving affordability, awareness, and policy support is essential to enhance global HPV.

Grading meningioma guides treatment choices from follow-up to surgical resection with adjuvant radiation. Radiomics may offer a non-invasive alternative to biopsies. We assessed radiomic features (RFs) for distinguishing Grade 1 and Grade 2 meningiomas on preoperative multiparametric MRI.

Presurgical T1-weighted (T1), T2-weighted (T2), T2 gradient echo-weighted (T2GRE), fluid-attenuated inversion recovery (FLAIR), apparent diffusion coefficient (ADC), and T1-weighted contrast-enhanced (T1CE). MRI sequences of histopathologically diagnosed meningiomas were collected retrospectively. Each volume had 75 RFs extracted from semimanually segmented tumors using MintLesion Research (Version 3.10). The Lasso method selected variables from imputed data, and 10-fold cross-validation determined the optimal regularization parameter. For Lasso-retained variables, multivariate effects were estimated.

Out of 150 patients (67.3% women), 110 (73.3%) had Grade 1 meningiomas, and 40 (26.7%) Grade 2. The strongest metrics to distinguish meningiomas Grade 1 versus Grade 2 were intensity histogram coefficient of variation on T1CE (odds ratio [OR] 0.47, 95% confidence interval [CI] 0.23-0.88; p = 0.028), maximum histogram gradient on T1 (OR 2.11, 95% CI 1.18-4.82; p = 0.043), and intensity histogram quartile coefficient of dispersion on FLAIR (OR 0.53, 95% CI 0.31-0.89; p = 0.021). The combined RFs achieved an area under the curve of 0.814 (95% CI, 0.732-0.896) for grading differentiation. Texture features and metrics extracted from T2, T2GRE, and ADC sequences did not discriminate meningioma grading.

Histogram-based first-order RFs from T1, FLAIR, and T1CE may predict meningioma grades preoperatively. Larger, multicenter studies are needed to confirm these findings, providing insights for clinical decision-making and personalized treatment.

Ranking multiple interventions is a crucial task in network meta-analysis (NMA) to guide clinical and policy decisions. However, conventional ranking methods often oversimplify treatment distinctions, potentially yielding misleading conclusions due to inherent uncertainty in relative intervention effects. To address these limitations, we propose a novel Bayesian rank-clustering estimation approach, termed rank-clustering estimation (RaCE), specifically developed for NMA. Rather than identifying a single "best" intervention, RaCE enables the probabilistic clustering of interventions with similar effectiveness, offering a more nuanced and parsimonious interpretation. By decoupling the clustering procedure from the NMA modeling process, RaCE is a flexible and broadly applicable approach that can accommodate different types of outcomes (binary, continuous, and survival), modeling approaches (arm-based and contrast-based), and estimation frameworks (frequentist or Bayesian). Simulation studies demonstrate that RaCE effectively captures rank-clusters even under conditions of substantial uncertainty and overlapping intervention effects, providing more reasonable result interpretation than traditional single-ranking methods. We illustrate the practical utility of RaCE through an NMA application to frontline immunochemotherapies for follicular lymphoma, revealing clinically relevant clusters among treatments previously assumed to have distinct ranks. Overall, RaCE provides a valuable tool for researchers to enhance rank estimation and interpretability, facilitating evidence-based decision-making in complex intervention landscapes.

Human papillomavirus-positive (HPV+) oropharyngeal squamous cell carcinoma (OPSCC) is a peculiar entity, with distinct patient, tumor, and biological characteristics, and a different prognosis compared to HPV-negative (HPV-) OPSCC. Due to the rising incidence, there is a need to develop novel therapeutic approaches, especially considering the long-term morbidities of traditional treatments such as surgery and chemoradiotherapy. In this regard, therapeutic vaccines targeting HPV epitopes have been put at the forefront of the immunotherapeutic strategies for HPV+ OPSCC. Multiple clinical trials are investigating their efficacy and safety in the advanced setting, more frequently as a combination therapy. As for the early setting, HPV therapeutic vaccines could represent a strategy to further deepen responses and to facilitate de-escalation of standard treatment. This review aims to provide the clinician with useful and up-to-date information on the current advances in this field. To that end, we will provide the results of the main ongoing/completed clinical trials including patients with OPSCC, focusing on immunogenicity and clinical benefit, in both early and advanced setting. We will also map the challenges and limitations in this area to guide future research.

Melanoma, a highly malignant skin tumor with high metastatic propensity and poor survival in advanced stages, poses a major global public health challenge, as conventional treatments have notable limitations. Tumor immunotherapy, particularly cancer vaccines, has emerged as a promising approach by activating/regulating immune mechanisms to target cancer cells.

This study systematically searched the Trialtrove database for interventional clinical trials of melanoma and cancer vaccines up to August 5, 2025. After screening via inclusion/exclusion criteria, 442 trials were analyzed, adhering to PRISMA guidelines with independent dual review for data reliability.

Trials were geographically concentrated in developed regions (69% in the US), with minimal participation from Asia, Africa, and Latin America. A "translational funnel effect" was observed: Phase I/I-II trials accounted for 63.6%, while Phase III trials only 6.1%, with a 22.9% termination rate. Peptide/recombinant protein vaccines (186 trials) and cellular vaccines (151 trials) were mainstream, with nucleic acid vaccines (58 trials) as a promising emerging platform. Combination therapy (227 trials, >50%), especially with immune checkpoint inhibitors (ICIs), dominated; adjuvants (e.g., IL-2, GM-CSF agonists) enhanced efficacy. Most trials focused on Stage III/IV patients (91.1%): key trials showed mRNA-4157 + pembrolizumab reduced recurrence/death risk by 49% in resected melanoma, and herpes simplex virus RP1 + nivolumab achieved 58.3% objective response rate (ORR) in ICI-resistant patients. Primary endpoints favored safety/immunogenicity (215/142 trials), with overall survival (OS, 33 trials) rarely used; academic institutions led funding (52.3%).

Melanoma vaccines, especially in combination with ICIs and via personalized platforms, have significant potential. However, challenges include tumor heterogeneity, immunosuppressive tumor microenvironment (TME), inefficient delivery, geographical R&D imbalance, and low Phase III conversion. Interdisciplinary collaboration, international multicenter trials, optimized clinical design (e.g., early-stage patient enrollment), and policy support are needed to advance their clinical translation.

Accurate prediction of mortality after allogeneic hematopoietic stem cell transplantation (alloHCT) is essential for individualized treatment decisions, yet existing clinical risk scores capture only a limited number of variables and show modest predictive performance. In our single-center retrospective analysis, we included data from 909 adult patients with hematologic malignancies undergoing alloHCT. We used 31 features to build machine-learning models to predict death within the first year after alloHCT. These features included established clinical risk factors together with pre-transplant lymphocyte subsets and inflammatory markers. Among four models, a random forest algorithm showed the best performance (AUC = 0.773) and retained good generalizability in an independent test set (AUC = 0.748). SHapley Additive exPlanations (SHAP)-based interpretation of the machine-learning models showed that age together with five easily measurable pre-transplant immunological and inflammatory parameters influenced the outcome: pre-transplant CD4⁺, CD8⁺, and B-lymphocyte counts, albumin, and C-reactive protein (CRP) levels. Based on these features, our random forest approach outperformed established clinical risk scores (HCT-CI, EASIX, rDRI, mGPS) in predicting one-year mortality after alloHCT and more effectively distinguished patients at low and high risk of an adverse outcome. Our study shows that machine-learning-based models can not only predict patient outcomes after alloHCT but also serve as powerful tools for data exploration, confirming the prognostic relevance of pre-transplant inflammation while uncovering the critical role of lymphocyte subsets as previously unknown risk factors. External validation in independent multicenter cohorts will be required to confirm generalizability.

Immunotherapies such as checkpoint blockade, adoptive cell transfer and vaccines can induce durable responses, yet most solid tumors remain refractory because the tumor immune microenvironment (TIME) is both immunosuppressive and physically difficult to access. In parallel, extracellular vesicles (EVs) and synthetic nanomaterials have emerged as complementary immune messengers and programmable carriers. Exo-nanomaterials, hybrids that fuse EV membranes with synthetic cores, aim to unite EV biocompatibility and trafficking with the loading capacity, modularity and stimulus-responsiveness of engineered nanomaterials. Here, we summarize how exosomes shape the TIME by distributing checkpoint ligands, reprogramming myeloid cells and modulating antigen presentation, and how nanomaterials are engineered to improve tumor-localized delivery of innate agonists and vaccine cargos. We then outline major construction routes (coating, loading and mimetic fabrication) and design modules that enable cold-to-hot conversion, sensitization to checkpoint blockade, and delivery of neoantigen and nucleic-acid vaccines. Finally, we discuss key translational challenges, including standardization, mechanism deconvolution, scalable manufacturing and safety, and propose immune-by-design principles to guide reproducible, mechanism-grounded development toward durable immunotherapy in solid tumors.

Pigmented villonodular synovitis is a rare disease that occurs on synovial tissue within and outside a joint. It can be localized or diffuse. Localized pigmented villonodular synovitis (LPVNS) can occur in any compartment of the knee joint. The aim of this study was to retrospectively analyze our consecutive series of LPVNS of the knee. From January 1999 to December 2018, 10 consecutive patients with LPVNS of the knee underwent surgical treatment at our department. All patients were arthroscopically treated by the senior author by removal of the localized mass and partial synovial resection of the area surrounding the bottom of the lesion. The series included four female and six male patients, mean age 29.5 (range, 17-60) years. Their symptoms prior to the operation lasted from 3 months to 3 years (mean, 11.8 months). At the mean follow-up of 110.9 (range, 11-239) months, none of the patients had recurrence of the disease. Our study confirms the consensus in the literature that LPVNS of the knee should be treated arthroscopically by excision of the localized mass and partial synovectomy of the area surrounding the base of the lesion.

To investigate medical expenses and factors influencing surgical choices among lung cancer patients in a tertiary hospital in Xiamen, China, and to identify key cost differences between surgical and non-surgical approaches.

In this retrospective cross-sectional study, we analyzed 3,806 lung cancer patients treated in 2023. Data analysis was performed using SPSS 27.0, with independent-sample t-tests for cost comparisons and binary logistic regression to identify factors influencing surgical intervention.

The study analyzed 3,806 lung cancer patients (60.7% male, 51.1% aged 61-80 years), revealing significant demographic and clinical predictors of surgical intervention. Multivariate analysis identified female gender (adjusted OR = 1.989, 95%CI:1.624-2.436, p < 0.001), younger age (61-80 years: adjusted OR = 0.454, 95% CI:0.305-0.676, p = 0.001; >80 years: adjusted OR = 0.353, 95%CI: 0.161-0.774, p = 0.009), and prolonged hospitalization (adjusted OR = 106.729, 95%CI: 79.485-143.312, p < 0.001) as key determinants, while insurance type showed no association. Surgical patients incurred 8.5-fold higher median costs (¥48,610 vs. ¥5,676), with medical consumables exhibiting the most pronounced disparity (>2,000-fold difference). The predictive model demonstrated excellent discrimination (AUC = 0.904), calibration (Hosmer-Lemeshow p = 0.402), and specificity (81.6%) at a 46.75% probability threshold, with length of stay being the strongest individual predictor (univariate AIC = 2,874 vs. full model AIC = 2,802). Insurance type showed no significant association with surgical treatment in either univariate or multivariate analyses.

Gender, age, and hospital stay length were major factors associated with surgical decisions in lung cancer patients, with surgery significantly increasing total medical costs. Policy improvements in the management of high-value medical consumables and insurance reimbursement are needed to reduce financial burdens and enhance surgical accessibility.

Leukemia cutis is an uncommon but clinically significant manifestation of hematologic malignancies caused by infiltration of the skin by malignant leukocytes. Its presentation is highly variable and may closely resemble benign inflammatory dermatoses, frequently leading to diagnostic delay. We report the case of a 76-year-old man with JAK2-positive essential thrombocythemia (ET) who developed persistent, intensely pruritic maculopapular skin lesions initially diagnosed as dermatitis. Despite symptomatic treatment, the lesions progressed and were followed by systemic symptoms. Further investigation revealed acute myeloid leukemia (AML) arising from blastic transformation of ET, with probable cutaneous involvement consistent with leukemia cutis. This case highlights the importance of maintaining a high index of suspicion when evaluating new or treatment-refractory skin lesions in patients with myeloproliferative neoplasms (MPNs), as early recognition may allow timely diagnosis of leukemic transformation and prompt initiation of appropriate therapy.