Background: Cervical cancer screening uptake in Romania remains below 20%, with invasive sampling cited as a major participation barrier. Urinary HPV testing is a non-invasive alternative, but data from Eastern European populations are scarce and reporting stratified by histological grade is inconsistent. Objectives: To evaluate the agreement between paired urinary and clinician-collected cervico-vaginal HPV testing, and to assess the diagnostic performance of urinary HPV testing for biopsy-confirmed cervical intraepithelial neoplasia grade 2 or worse (CIN2+). Methods: Prospective cross-sectional study in three outpatient obstetrics and gynecology clinics (May 2025-May 2026). A total of 230 women aged 25-70 years provided paired cervico-vaginal (PreservCyt^®) and first-void urine (Colli-Pee^®) specimens. To capture the full spectrum of disease probability, participants were recruited across three clinical scenarios: primary screening, cytology triage and HPV-positive triage. A multiplex RT-PCR assay targeted a total of 14 high-risk HPV genotypes, providing separate identification for HPV16 and HPV18, alongside a pooled detection for the remaining 12 high-risk strains. Colposcopy-guided cervical biopsy served as the reference standard. Results: Paired hrHPV testing achieved substantial agreement (κ = 0.696, 95% CI 0.604-0.788), with higher genotype-specific concordance for HPV16 (κ = 0.755) and HPV18 (κ = 0.789). Discordance was directionally asymmetric (30 cervical-positive/urine-negative versus 4 urine-positive/cervical-negative; McNemar p < 0.001). For biopsy-confirmed CIN2+ (59 of 230; 25.7%), urinary hrHPV showed a sensitivity of 86.4% (95% CI 75.5-93.0), specificity 56.7%, positive predictive value 40.8% and negative predictive value 92.4%, compared with 91.5%, 43.3%, 35.8% and 93.7% for cervico-vaginal testing. Urinary HPV positivity increased monotonically with histological severity (25.0% no-lesion, 69.0% CIN1, 86.4% CIN2+; linear-by-linear p < 0.001). Conclusions: Urinary HPV testing demonstrates substantial agreement with clinician-collected sampling, near-equivalent negative predictive value, and a robust dose-response with histological severity. It is a clinically credible non-invasive entry point for a triage cascade in settings such as Romania, where low participation rather than analytical performance is the principal screening barrier.

Immune checkpoint inhibitors (ICIs) have significantly improved outcomes in metastatic non-small cell lung cancer (NSCLC), yet only a subset of patients derives durable benefit, suggesting that host and tumor-related factors may modify treatment efficacy. The renin-angiotensin system has been implicated in regulation of the tumor microenvironment, and angiotensin-converting enzyme inhibitors (ACEIs) have therefore been proposed as potential modulators of immunotherapy response.

We conducted a retrospective observational cohort study including patients with advanced metastatic NSCLC treated in the first-line setting with treatment-based immunotherapy, with or without chemotherapy, between January 2017 and September 2025. Chronic ACEI exposure was defined as continuous use for at least two years prior to initiation of immunotherapy. Progression-free survival (PFS) and overall survival (OS) were analyzed using Kaplan-Meier estimates and compared using the log-rank test, and multivariable Cox proportional hazards models were adjusted.

Among 446 eligible patients, 71 (16%) received ACEIs and 375 (84%) did not. The median age of the cohort was 67.5 years, and 70% were male. Adenocarcinoma was the predominant histology (67.7%), and most patients received chemo-immunotherapy (81.6%), while 18.4% received immunotherapy alone. PD-L1 expression ≥ 1% was present in 59.2% of patients. In the overall cohort, median PFS and OS were 12 and 15 months, respectively. Median OS was 17 months in the ACEI group compared with 14 months in the non-ACEI group (log-rank p < 0.047), while median PFS was 14 months versus 11 months, respectively (p = 0.066). The survival advantage was more pronounced for OS than for PFS and remained consistent after adjustment for clinical characteristics including age, sex, ECOG performance status, smoking status, histology, treatment regimen, and PD-L1 expression.

These findings suggest that chronic ACE inhibitor use may be associated with improved outcomes in metastatic NSCLC patients treated with immune checkpoint inhibitors.

Emerging evidence suggests exercise may improve radiotherapy efficacy by reducing treatment resistance caused by tumour hypoxia. However, recruitment to exercise oncology studies is low (median 38%), particularly for people with lung cancer. One strategy to address such engagement barriers is by collaborating through Patient and Public Involvement and Engagement (PPIE).

To co-design an acceptable pre‑radiotherapy exercise programme for people living with lung cancer, incorporating the perspectives and experiences of those affected by the disease.

A PhD researcher collaborated with people impacted by lung cancer and an expert advisory group in a series of meetings and workshops underpinned by the principles of experience-based co-design and Boyd's co-design approach. Workshops were recorded and transcribed verbatim and analysed using reflexive thematic analysis. Findings relating to programme design were deducted into Frequency, Intensity, Time and Type principles, whereas barriers and facilitators were deducted into the five domains of the Practical planning for Implementation and Scale-up guidelines.

Seven attendees accepted workshop invitation, of which three had received a lung cancer diagnosis, and four were family members. Considering design, daily exercise was regarded acceptable for short duration treatment plans, with an optimal duration of 20 min. Exercise intensity must also be personalised and autoregulated. Furthermore, 15 barriers and 40 facilitators were identified, the most pertinent relating to physical activity coach conduct and research design. For example, supervised exercise and developing professional working relationships were considered essential.

This project shows how PPIE can effectively inform early research to improve acceptability and presents the first co‑designed pre‑radiotherapy exercise programme for lung cancer.

PPIE was integral for this project. People diagnosed with lung cancer, along with family members, participated in two co‑design workshops, contributing their perspectives and experiences to shape the development of a pre‑radiotherapy exercise programme. Patient advocates within the advisory group reviewed and refined workshop materials to ensure they were accessible, meaningful, and patient‑friendly. Finally, one co‑design attendee and a patient advocate from the advisory group assisted drafting this manuscript to ensure published findings authentically represent the workshop discussions and the lived experiences shared throughout the project.

As society is increasingly depending on large language models (LLMs) for health-related questions, it is essential to objectively evaluate the quality and accessibility of the oral cancer information they provide. Although LLMs occupy a growing space in digital health communication, it remains unknown whether the information they generate is both reliable and easy to read.

The purpose of this study was to evaluate the reliability and readability, respectively, of the responses generated by four mainstream LLMs (ChatGPT, Gemini, Perplexity, and DeepSeek) to questions related to oral cancer. Specifically, the present authors aimed to evaluate the reliability of responses to common oral cancer questions and assess whether the readability of responses meets established expectations.

Twenty-two commonly asked, patient-orientated oral cancer-related questions were developed through two predefined phases: Google Trends analysis and expert consultation with specialists in oral oncology. Each question was entered as an independent single-turn prompt into four LLMs: ChatGPT-5, Gemini 2.5, Perplexity Pro, and DeepSeek v3.2. The primary outcome was information reliability and quality, assessed using four standardized instruments: the DISCERN questionnaire, the Ensuring Quality Information for Patients (EQIP) tool, the Journal of the American Medical Association (JAMA) benchmark criteria, and the Global Quality Scale (GQS). The secondary outcome was readability, assessed using six established indices: the Automated Readability Index, Flesch Reading Ease Score, Gunning Fog Index, Flesch-Kincaid Grade Level, Coleman-Liau Index, and Simple Measure of Gobbledygook.

Significant differences were observed among the four LLMs in DISCERN, EQIP, and JAMA scores (all P 0.001), whereas no significant difference was found in GQS scores (P = 0.440). Perplexity Pro achieved the highest mean DISCERN score (46.36 ± 4.70), EQIP score (85.00 ± 0.00), GQS score (4.05 ± 0.58), and JAMA score (1.00 ± 0.00). However, all models produced responses above the recommended sixth-grade readability level. The mean FKGL scores ranged from 12.65 ± 3.07 for ChatGPT-5 to 15.65 ± 3.36 for Perplexity Pro, and the mean FRES scores ranged from 37.50 ± 14.27 for Perplexity Pro to 52.59 ± 12.47 for Gemini 2.5.

Current LLMs may support oral cancer patient education, but their use remains limited by variable information quality, insufficient transparency, and poor readability. Although Perplexity Pro performed better on several reliability-related metrics, no model showed consistently high performance across all dimensions or met recommended readability standards. Future LLM-based patient education tools should prioritise verifiable sourcing, guideline-based accuracy, risk communication, and plain-language adaptation.

To evaluate the histological subtypes, surgical margin status, and high-risk features of periocular basal cell carcinomas (BCC) excised over a one-year period at a secondary referral centre in England.

This retrospective audit included 100 consecutive periocular BCC excisions performed at James Paget University Hospital between August 2024 and August 2025. Demographic, clinical, and histopathological data were extracted from operative records and histopathology reports. Surgical margins were classified as complete (≥0.4 mm), close (0.1-0.3 mm), or incomplete (tumour present at the inked margin or <0.1 mm). Fisher's exact test was used to evaluate the association between infiltrative histological subtype and the presence of perineural invasion.

Of the 100 patients included (58% male, 42% female; mean age 75.7 years), nodular BCC was the most common histological subtype (83%), followed by infiltrative (14%), superficial (2%), and basosquamous (1%) variants. Complete excision was achieved in 83% of cases, while close and incomplete margins were observed in 8% and 9% of excisions, respectively. Perineural invasion was identified in 2% of tumours, both of which demonstrated infiltrative histology. The infiltrative subtype showed a statistically significant association with perineural invasion (p=0.007). The majority of BCCs were located in the medial canthus (56%), an anatomically complex region associated with increased surgical difficulty and a higher risk of incomplete excision.

High rates of complete excision were achieved in this cohort of periocular BCCs. Infiltrative histological subtype was associated with an increased risk of perineural invasion and incomplete excision, particularly when located in the medial canthus. These findings support a risk-adapted surgical strategy as well as consideration of Mohs micrographic surgery for aggressive tumour subtypes and anatomically complex periocular locations.

Monoclonal antibodies (mAbs) have transformed the treatment of cancer and immune disorders, but their single-target nature limits efficacy against heterogeneous tumors and mutating pathogens. Recombinant polyclonal antibodies (RPABs)-defined as mixtures of typically 2-25 defined mAbs produced as a single drug substance from one mixed master cell bank-were proposed to combine the epitope breadth of polyclonal antibodies with the manufacturing consistency of mAbs. This review critically analyzes the four RPABs candidates that have entered clinical trials to date (Sym001, Sym004, Sym013, and Sym015), all developed by Symphogen using its proprietary Sympress™ platform. We identify seven interrelated barriers that collectively explain why no RPABs product has yet received regulatory approval: modest efficacy restricted to biomarker-selected subgroups, significant toxicity, pharmacokinetic mismatch among components, instability of mixed cell banks, lack of standardized quality control methods, regulatory uncertainty, and commercial deprioritization after acquisition. Critically, we distinguish between scientific failure (Sym013, discontinued after early termination of its Phase I trial due to tolerability concerns and pharmacokinetic mismatches) and strategic discontinuation (Sym001 and Sym015, which showed clinical signals but were deprioritized for commercial reasons). All clinical and manufacturing data analyzed in this review are derived exclusively from Symphogen's proprietary Sympress™ platform, as no other RPABs candidate from independent developers has entered clinical trials. We conclude that without independent validation of manufacturing consistency, pharmacokinetic-based component ratio design, and a dedicated regulatory pathway, RPABs face an uncertain future. Recommendations for future development are provided.

Decentralised clinical trials (DCTs) are increasingly promoted in UK research policy and practice; however, their benefits and implementation challenges in oncology remain unclear. We examined DCT use in oncology through a review of studies evaluating decentralised oncology trial delivery, UK regulatory and policy frameworks and a survey of UK academic Clinical Trials Units (CTUs).

Multimethod study including a structured literature review, policy review and cross-sectional survey of UK Clinical Research Collaboration (UKCRC)-registered CTUs.

International literature, UK-based regulatory and policy documents and survey data from UKCRC-registered CTUs.

None.

Literature review: decentralised components evaluated and reported outcomes.Policy review: opportunities, barriers and gaps in UK regulatory and policy guidance relevant to DCTs.Survey: CTU awareness, uptake, perceived benefits and challenges related to decentralised trial delivery, comparing oncology and non-oncology settings.

Of 68 studies meeting broader eligibility criteria, only 8 formally evaluated decentralised elements within oncology trials and were included in the primary synthesis. Conducted across five countries, these studies primarily assessed feasibility, recruitment, usability and data completeness. Only one UK oncology study formally evaluated DCT methods, assessing use of remote electronic consent to support recruitment during the COVID-19 pandemic, highlighting limited published UK evaluation. Non-UK studies showed mixed findings, including improvements in trial processes or participant satisfaction in some contexts alongside operational challenges in others.The UK-based policy review identified strategic support for decentralisation but fragmented regulatory guidance and ambiguity around key decentralisation concepts. Temporary COVID-19-induced flexibilities demonstrated feasibility but have not been fully incorporated into permanent guidance.Survey responses were received from 27 CTUs (54% response rate). Awareness of decentralised approaches was high; however, use of these was lower in oncology than in non-oncology trials. Decentralisation was most commonly applied to patient follow-up. CTUs reported reduced participant burden and increased flexibility, but also challenges relating to governance, contracting, infrastructure, staffing and data management.

Decentralised approaches in UK oncology trials are gaining momentum but remain unevenly adopted, alongside a limited oncology-specific evidence base, regulatory ambiguity and operational challenges. Oncology presents distinct challenges that may limit decentralisation of trials compared with other disease areas, including complex interventions, intensive safety monitoring requirements and protocol-specific assessments. Evidence on patient/public involvement and acceptability of decentralised approaches among people with cancer remains limited. Clearer guidance and more robust evaluation, incorporating patient perspectives, are needed to support wider implementation in the UK and may also be relevant internationally.

Thyroid nodules are highly prevalent, with increasing detection rates driven by advanced imaging and expanded screening. Ultrasound serves as the first-line tool for screening, diagnosis and follow-up, owing to its non-invasiveness, real-time capability, cost-effectiveness and absence of ionizing radiation. However, conventional ultrasound diagnosis is highly operator-dependent, resulting in substantial inter-observer variability and diagnostic errors, particularly for subtle or indeterminate lesions. Artificial intelligence (AI), particularly deep learning and radiomics, has emerged as a promising approach to address these limitations by enabling automated feature extraction, quantitative analysis and standardized interpretation, which has the potential to improve diagnostic efficiency and risk stratification. This review summarizes AI applications in thyroid ultrasound, including image preprocessing, nodule segmentation, quantitative feature analysis, benign-malignant differentiation, TIRADS optimization and automated reporting. We highlight AI's potential in enhancing diagnostic consistency and accuracy, while critically assessing the methodological quality, bias risks and external validation of existing studies. Most AI tools are still in early translational phases, lacking large-scale validation in real clinical settings and standardized reporting protocols. We further discuss key challenges, including data bias, limited generalizability due to small or single-center datasets, poor interpretability and significant translational barriers. Future directions involving multi-modal fusion, explainable AI, real-time clinical systems and rigorous, multi-center standardized validation are proposed to facilitate clinical translation and improve patient care.

Since February 2022, Ukraine has been facing the challenges of active armed conflict, undermining its healthcare system. Despite the ongoing war, the national cervical cancer screening program was launched in 2025. However, little is known about whether laboratory diagnostic quality can be maintained under these conditions. This study aimed to assess the resilience of cervical cancer screening services in Ukraine during wartime by evaluating the temporal dynamics of PAP smears, HPV testing, and their quality indicators.

This single-center, repeated cross-sectional study included laboratory data collected on PAP smears from 946,451 cases and 114,974 HPV tests retrieved from the database of the Medical Laboratory CSD in 2021-2025. The Annual Bethesda System 2014 (BS 2014) category proportions and quality metrics (including the ASC/SIL ratio and non-diagnostic rate) were assessed and compared with the benchmarks from BS 2014 and the College of American Pathologists (CAP). HPV testing data included overall positivity rates and HPV 16/18 genotype distribution.

The volume of PAP tests decreased by 21.5% in 2022; however, there was a significant recovery in 2023, with an increase of 85.3% in 2025 compared to the pre-war baseline (2021). Each Bethesda category proportion for every year aligned within international benchmark ranges. The five-year CSD medians were as follows: NILM-91.27% (89.24-91.61%); ASC-US-4.45% (3.94-5.38%); LSIL-2.83% (2.49-3.57%); HSIL-0.38% (0.31-0.62%), non-diagnostic-0.80% (0.54-1.03%); SCC-0.024% (0.016-0.051%); and AGC-0.25% (0.22-0.26%). Quality metrics were consistent with global reference values, with a total abnormal sample rate of 7.81% (7.7-9.67%), ASC/SIL ratio of 1.36 (1.18-1.66), and ASC-US/LSIL ratio of 1.47 (1.28-1.79). HPV testing expanded at a disproportionately higher rate than Pap test utilization, surging 27.8-fold over the wartime period. HPV positivity declined significantly from 21.07% in 2021 to 17.16% in 2025 (p = 0.011). While HPV16 prevalence remained relatively stable, the relative contribution of HPV18 nearly doubled, rising from 5.6 to 10.4% among HPV-positive individuals (p = 0.008).

Cytopathological reporting patterns remained within benchmark ranges under 4 years of armed conflict in Ukraine, with diagnostic performance of CSD LAB corresponding to international benchmarks. The rapid HPV testing expansion associated with an increased rate of testing among younger women, a decline in HPV positivity among the 30-65 cohort, and a rise in the HPV 18 proportional rate have direct implications for national vaccination and screening policies.

The PD-1/PD-L1 axis plays a critical role in suppressing T-cell activation and facilitating immune evasion in lung adenocarcinoma (LUAD). This study focused on PD-1-related genes to develop a robust prognostic prediction model for LUAD.

Immune scores were calculated using the ESTIMATE algorithm, and immune-related gene modules were identified through WGCNA. Differentially expressed genes (DEGs) were identified between normal and tumor tissues, and between high and low PD-1 expression groups, using the limma package. Univariate and multivariate Cox regression analyses were performed to construct a prognostic risk model, which was subsequently evaluated using time-dependent ROC curve analysis with the timeROC package. Biomarker expression and function were validated in LUAD cells via western blot (WB), CCK-8, wound healing, and Transwell assays. Functional enrichment analysis was conducted using the clusterProfiler package. The tumor microenvironment (TME) was characterized by integrating MCPcounter, ESTIMATE, and ssGSEA. Drug sensitivity was predicted using the pRRophetic R package.

WGCNA showed that genes in the brown module were significantly positively correlated with the immune score, and these genes were predominantly enriched in biological processes such as neutrophil activation and cytokine activity. By intersecting the brown module genes, DEGs, and PD-1-related genes, we constructed a risk prognosis model comprising nine key genes (ADA2, CD53, HLA-DMA, ITGAX, MYO1F, NCKAP1L, PTPRC, RENBP, and TNFAIP8L2). The model demonstrated robust predictive performance, with high AUC values in time-dependent ROC analysis. Patients within the high-risk group exhibited a worse prognosis. Additionally, RiskScore for patients in the high-risk group was closely associated with immune infiltration, immune checkpoint expression, and drug sensitivity. The low-risk group exhibited higher levels of immune cell infiltration, including T cells, CD8⁺ T cells, and B lineage cells. Furthermore, in vitro experiments have demonstrated that silencing the representative gene MYO1F significantly inhibited the migration and invasion of LUAD cells, whereas PTPRC knockdown promoted these capacities. Drug sensitivity analysis identified distinct candidate therapeutic agents for the high- and low-risk groups.

In conclusion, this study developed a robust prognostic prediction model for LUAD, contributing to personalized therapeutic strategies.