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Incidence and risk factors for malignancy in patients with incidental solitary pulmonary nodules: a systematic review and meta-analysis.

BACKGROUND: The increasing use of chest imaging has led to a higher detection rate of incidental solitary pulmonary nodules (SPNs), often causing patient anxiety. Determining the malignancy rate and associated risk factors is crucial for developing appropriate follow-up strategies to prevent overdiagnosis, overtreatment, or missed diagnoses. This meta-analysis aims to investigate the malignancy rate and risk factors in patients with incidental SPNs. METHODS: A systematic search of PubMed, Embase, Web of Science, and the Cochrane Library was conducted up to June 30, 2025. Data on malignancy rates and potential risk factors were extracted from eligible studies. All pooled analyses were performed using a random-effects model. RESULTS: Fifty-four studies involving 19,985 patients were included. The pooled malignancy rate for incidental SPNs was 56.7% (95% CI: 51.5-62.0), with significant between-study heterogeneity (I2 = 98.5%, p&#x2009;<&#x2009;0.001). The pooled effect size showed a minimal change after adjustment for potential publication bias using the non-parametric Trim-and-Fill method (54.7%; 95%CI: 50.9-58.8). Risk factor analysis identified that older age, history of cancer, cigarette smoker, larger nodule diameter, spiculation, upper lobe location, lobulation, pleural indentation, vascular convergence, solid nodules, family history of cancer, and irregular or ill-defined margins were significantly associated with an increased risk of malignancy. Conversely, male sex, presence of calcification, and clear borders were significantly associated with a reduced risk of malignancy. CONCLUSION: This meta-analysis provides a comprehensive assessment of malignancy rates and risk factors in incidental SPNs. The high pooled malignancy rate should be interpreted considering the significant heterogeneity and the inclusion of a high proportion of retrospective studies and populations from high-risk regions. Nonetheless, these findings offer essential evidence for clinical risk stratification, supporting optimized follow-up and informed decision-making.

Humans↗

Vaccine preferences and their role for vaccine confidence and uptake: a meta-ethnography.

Vaccine confidence and uptake are influenced by individuals' preferences regarding vaccine composition, quality, or administration pathways. However, literature synthesizing available qualitative insights into individuals' vaccine preferences remains limited. We therefore conducted a meta-ethnographic systematic review of the qualitative literature on vaccine preferences to identify opportunities for enhancing vaccine confidence and uptake. We implemented a comprehensive search strategy and screened 5,528 studies across seven research databases published between 2001 and 2023. We identified and synthesized 97 qualitative articles to delineate factors influencing consumers' vaccine preferences. Our findings revealed four primary domains shaping individuals' vaccine preferences: Product, Place, Price, and Promotion. First, individuals' preferences for vaccines often hinge on perceived quality and safety of the product itself, which can, for example, be associated with vaccine brand or origin, especially in the case of novel vaccines. Second, people prioritize convenience in terms of vaccination sites and delivery methods (wanting vaccinations offered at their doorstep or in local peripheral clinics); evidence regarding preferred groups to administer the vaccines was mixed. Third, the price of vaccines and the secondary costs associated with vaccination played a role in uptake considerations. Finally, both the sources of information (such as healthcare workers, community volunteers, and religious authorities) and the methods of promoting vaccine information (including face-to-face consultations during clinic visits and the distribution of leaflets or banners), emerged as crucial factors shaping decision-making processes. Overall findings highlight the importance of addressing multifaceted preferences to enhance vaccine confidence and uptake. By understanding individuals' vaccine preferences, strategic recommendations can be developed to optimize vaccination programs and ensure acceptability and utilization.

Humans↗

Advancing nursing education through social and emotional learning: A systematic review guided by the Collaborative for Academic, Social, and Emotional Learning framework.

BACKGROUND: With Generation Z entering the nursing workforce in growing numbers, strengthening social and emotional learning is critical for academic success, professional adaptation, and safe practice. However, the existing evidence remains fragmented because of varied interventions and inconsistent approaches. OBJECTIVES: This systematic review examined (1) the social and emotional learning essential for nursing students and nurses within the Collaborative for Academic, Social, and Emotional Learning framework, (2) their impact on educational and clinical outcomes, and (3) implications for advancing nursing education and practice. METHODS: Following Joanna Briggs Institute methodology and Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, five international (PubMed, EMBASE, CINAHL, PsycINFO, Cochrane) and three Korean (RISS, KoreaMed, KMBASE) databases were searched up to June 2025. Eighteen studies involving 2,952 participants met the inclusion criteria, including quasi-experimental quantitative studies, descriptive quantitative studies, qualitative studies, and mixed-methods studies. The methodological quality of the included studies was appraised using the Mixed Methods Appraisal Tool. RESULTS: Within the Collaborative for Academic, Social, and Emotional Learning framework, relationship skills and self-management were the most frequently studied competencies, emphasizing teamwork, communication, and stress regulation. Self-awareness and social awareness were underexplored, despite their importance in empathy, resilience, and reflective practice. Responsible decision-making was the least studied competency, despite its importance in ethical reasoning. Social and emotional learning was consistently associated with enhanced adaptation, communication, leadership, relationships, and clinical performance. Effective strategies included blended learning, simulation, reflective activities, and mentorship, which are aligned with Generation Z's learning preferences. CONCLUSION: Although social and emotional learning integration is associated with improvements in educational and clinical outcomes in nursing, current research has largely centered on relational and stress-related competencies while underrepresenting responsible decision-making. To cultivate reflective, empathetic, and ethically grounded nurses, curricula should integrate social and emotional learning through a balanced and structured approach. REGISTRATION: This study was registered on PROSPERO (ID: CRD420251005683).

Humans↗

Aligning awareness, systems and policy to increase equitable access to genomically driven cancer care.

Genomic testing has the potential to transform cancer care across the patient pathway. However, its benefits remain unevenly realised across populations and health systems. Precision oncology is characterised by a strong promissory discourse, with expectations of improved outcomes and cost-effectiveness, yet real-world implementation remains variable and context dependent. This review examines how patient and public awareness interacts with, and is constrained by, structural, organisational and political-economic factors that shape equitable access to genomically driven cancer care across five themes: (1) the power of patient and public advocacy; (2) learning from the patient perspective; (3) culturally responsive communication; (4) structural and personal barriers and facilitators and (5) political economy of health. Examples are mapped across global regions to highlight how health system, structural and societal factors continue to limit the universal realisation of genomic medicine's benefits. We present four recommendations to strengthen the translation of awareness into equitable access and clinical impact: (1) expand and adequately power genomic studies in underserved populations; (2) improve risk communication and decision-making across the cancer pathway; (3) equitable validation and interpretation of emerging genomic technologies and (4) generate real-world evidence on access, uptake and outcomes of genome-matched therapies. Embedding awareness, trust, access and equity in future initiatives is imperative to realise the promise of precision medicine for all patients.

Biomarkers↗

Identification of molecular subtypes in clear cell renal cell carcinoma based on chromatin regulators and tumor immune microenvironment profiling.

In the histological classification of renal cell carcinoma, clear cell renal cell carcinoma (ccRCC) accounts for the highest proportion and is the most common subtype. Despite advances in management, it continues to be associated with considerable incidence and mortality. Although surgery and systemic therapies are available, their efficacy is constrained by pronounced intratumoral heterogeneity and treatment resistance. Identifying robust biomarkers and clarifying the underlying biological mechanisms are therefore essential to improving diagnosis, risk stratification and therapeutic decision-making. In this work, we identified two ccRCC molecular subtypes displaying divergent chromatin regulator (CR) profiles and different clinical prognoses. Using the genes differentially expressed between these subgroups, we constructed a CR-related score (CRS) that effectively stratified patients according to survival. More analysis concluded that the low expression of CR was more linked with the immune-activated tumors, which encompassed the immune pathway enrichment, as well as the elevation of numerous immune cell subtypes. Moreover, elevated CRS was associated with improved immunotherapy responsiveness. Drug-sensitivity analyses nominated several candidate agents, and SMARCD3 knockdown in 786-O cells inhibited proliferation and migration and reduced sensitivity to masitinib. Collectively, these findings support the prognostic and therapeutic relevance of CR-related states in ccRCC and provide a framework for future experimental validation of chromatin-regulated tumor-immune interactions.

Humans↗

Intraoperative indocyanine green near-infrared fluorescence imaging for assessing testicular viability in pediatric testicular torsion: A retrospective study.

OBJECTIVE: To evaluate the clinical efficacy of indocyanine green near-infrared fluorescence (ICG-NIRF) imaging versus conventional surgery for assessing testicular viability and guiding decision-making in pediatric testicular torsion (TT). METHODS: A retrospective analysis was performed on 225 pediatric patients undergoing emergency scrotal exploration for TT between January 2019 and January 2025. Patients were categorized into a conventional surgery group (n = 118) relying on visual grading and an ICG-NIRF imaging group (n = 107). Primary outcomes included intraoperative testicular preservation rates and postoperative success rates. Multivariate Cox regression was utilized to identify factors influencing testicular preservation. RESULTS: Baseline characteristics were comparable between groups. The ICG-NIRF group demonstrated a significantly higher intraoperative preservation rate (74.77% vs. 61.02%, p = 0.028) and postoperative success rate (88.75% vs. 69.44%, p = 0.003) compared to the conventional group. Additionally, the ICG-NIRF group exhibited significantly lower rates of secondary orchiectomy (1.25% vs. 9.72%, p = 0.027) and 6-month testicular atrophy (7.59% vs. 23.08%, p = 0.02). Multivariate analysis confirmed ICG-NIRF application as an independent protective factor for testicular preservation (HR = 0.556, p < 0.001). CONCLUSION: ICG-NIRF imaging provides an objective, real-time assessment of testicular perfusion, significantly improving testicular preservation rates and postoperative outcomes. This technique overcomes the subjectivity of conventional visual methods, offering substantial clinical value for fertility preservation in pediatric TT.

Humans↗

AI-Driven Precision Medicine in Alzheimer's Disease: Drug Repurposing, Digital Therapeutics and Clinical Decision Support.

Alzheimer's Disease (AD) is a neurodegenerative disease that causes significant clinical, social, and economic burden worldwide. Despite improvements in understanding its multifaceted pathogenesis, current treatments are mostly symptomatic and ineffective across varied patient populations. To overcome these constraints, AI-driven precision medicine allows tailored risk assessment, treatment selection, and disease monitoring. This review covers AI's role in AD precision medicine, focusing on drug repurposing, digital therapies and clinical decision support systems. Machine and deep learning models are used to predict medication response, integrate heterogeneous data sources such as genomics, transcriptomics, neuroimaging and electronic health records, and uncover pharmacogenomic treatment success factors. The paper covers AIenabled precision pharmacology, including tailored dosing algorithms, adaptive therapeutic monitoring, and adverse drug reaction prediction. Bioinformatics-based target identification, network pharmacology, graphbased AI models, virtual screening, and real-world and clinical data validation are emphasized in AI-driven medication repurposing. AI-powered digital treatments like personalized cognitive training platforms, wearable- derived digital biomarkers, virtual and mixed reality interventions, adherence monitoring, and digital twins for therapy optimization have been discussed. AI-based clinical decision support systems are also thoroughly assessed for clinical value, accuracy, and explainability in disease subtyping, trajectory prediction, and risk stratification in preclinical and prodromal AD. Despite these promises, data heterogeneity, algorithmic bias, legal barriers, and privacy concerns exist. Federated learning enables safe multi-center collaboration and hybrid AI-human approaches, and it represents the future. AI's ability to alter AD care opens the door to precision medicine paradigms that use repurposed medications, digital tools and intelligent decision-making to improve patient outcomes.

Alzheimer&#x2019;s disease↗

The musculoskeletal pain literacy questionnaire (MSK-PLq) - Part 1: Development of a preliminary version through a systematic review and Delphi consensus.

OBJECTIVE: Chronic musculoskeletal (MSK) pain is a leading cause of disability worldwide, and self-management is a first-line approach recommended by international clinical guidelines. Access to evidence-based information that enhances health literacy may support patients' engagement in their self-management and treatment decision-making, potentially reducing disease burden and pain. However, no tool currently exists to assess health literacy specifically in MSK pain. This study aimed to develop and describe the preliminary version of a knowledge-based questionnaire to evaluate MSK pain literacy, the Musculoskeletal Pain-Literacy questionnaire (MSK-PLq). METHODS: A systematic literature review identified existing health literacy instruments and generated a preliminary list of domains. A two-round Delphi study with 22 panellists (19 experts and three people living with chronic MSK pain), followed by consensus meetings, was used to refine domains and items (&#x2265;70% agreement). Readability was assessed using the Flesch Reading Ease (FRE) score and three stakeholders were consulted to review the questionnaire for comprehensibility, clarity, and face validity. RESULTS: Six domains were retained (Understand, Access, Appraise, Apply, Digital, Beliefs), comprising 20 items in the preliminary version of MSK-PLq. Readability was acceptable (mean FRE 74, indicating fairly easy reading), and subject feedback supported the questionnaire's clarity and face validity. CONCLUSIONS: The preliminary version of the MSK-PLq is proposed as the first knowledge-based tool to assess functional, interactive, and critical aspects of MSK pain literacy. It may have applications in clinical practice, research, education, and digital health, by informing tailored patient education and supporting self-management strategies, although further psychometric validation is required.

Humans↗

How AI-supported intelligent systems support infection prevention and control training in healthcare: A systematic review of educational functions and outcomes.

AIMS: Artificial intelligence (AI)-supported intelligent systems have been increasingly incorporated into infection prevention and control (IPC) education and training, primarily to support the monitoring of observable behaviors and the provision of feedback. However, existing evidence has focused largely on short-term compliance outcomes, with limited synthesis of the educational role of AI-supported intelligent systems in supporting sustained IPC competence. This systematic review examined how AI-supported intelligent systems have been designed and used to support IPC education and training, with a focus on system characteristics, educational functions, and reported outcomes. DESIGN: A systematic literature search was conducted across the PubMed/MEDLINE, Embase, Cochrane, and CINAHL databases. DATA SOURCES: A total of 18 studies met the inclusion criteria. Findings were qualitatively synthesized according to system design characteristics, educational functions, and outcome domains. REVIEW METHODS: Methodological quality was appraised using the Mixed Methods Appraisal Tool. RESULTS: Most AI-supported intelligent systems focused on hand hygiene and relied on fully automated monitoring systems to capture behaviors and provide performance feedback. Educational functions were predominantly limited to performance assessment, automated feedback, and reminders. Outcomes were mainly measured using compliance or performance metrics, whereas sustained behavioral change and decision quality were rarely assessed. CONCLUSIONS: AI-supported intelligent systems have been used primarily to reinforce short-term IPC performance and compliance. However, their current applications for supporting sustained competence over time remain limited. The findings of this review suggest that AI-supported intelligent systems may serve as maintenance-oriented educational support by extending learning beyond initial instruction through repeated practice and feedback. Future research should prioritize outcome measures that capture the durability of performance and decision-making processes to better align AI-supported intelligent systems used in IPC education and training with the educational demands of clinical practice.

Humans↗

Criteria for Safe Hospital Discharge in Bronchiolitis: A Systematic Review.

Bronchiolitis is the leading cause of hospital presentation and admission for infants in Australasia. We aimed to synthesise current evidence on the effect of discharge criteria for infants (aged <&#x2009;12&#x2009;months) who are presenting to or are admitted to hospital with bronchiolitis, to inform a binational guideline recommendation update. Systematic searches were conducted on MEDLINE, EMBASE, PubMed, Cochrane Library and CINAHL (last search 19 February 2025) for non-randomised studies evaluating hospital discharge criteria in bronchiolitis. The primary outcomes were length of stay (LOS) and readmission rates. The risk of bias (ROBINS-I) and certainty of the evidence (GRADE) were appraised, and findings were narratively synthesised. GRADE evidence-to-decision methodology, expert consensus voting and interest-holder consultation were used to finalise the recommendation update. Two retrospective observational studies were included (N&#x2009;=&#x2009;2697) (low to very low quality), reporting on unique discharge criteria. In both studies, use of the discharge criteria was associated with a significant reduction in LOS relative to alternative protocols. There was no significant difference in readmission rates observed in either study. There was low to very low certainty evidence across outcomes due to risk of bias, indirectness and imprecision. The review findings informed a recommendation update for safe discharge criteria in the 2025 Australasian Bronchiolitis Guideline update. Updated, prescriptive discharge criteria and flow chart were developed, covering clinical stability, oxygen saturation/support, feeding difficulties, caregiver confidence and education on deterioration, social factors and follow-up. The revised criteria provide clinicians with increased certainty in decision-making in bronchiolitis, albeit with further research needed.

Humans↗

The effect of monetary versus point-based rewards on effort-cost decision making in individuals at clinical high risk for psychosis.

OBJECTIVE: The dissemination of inexpensive computerized behavioral tasks indexing amotivation may enhance the assessment of clinical high risk (CHR) across settings. However, the impact of varying reward value in such tasks is unclear. If point-based rewards engage participants, this could improve the scalability of computerized assessments. We tested how point-based rewards versus money impacted effort-cost decision-making in CHR individuals. We further assessed how negative symptom severity and household income interacted with reward-type to impact behavior. METHODS: Participants completed the Effort Expenditure for Reward Task (EEfRT). Participants were randomly assigned to receive either money or points for their performance during the EEfRT. Data from a large sample of CHR (N&#xa0;=&#xa0;233) individuals and healthy controls (HC; N&#xa0;=&#xa0;157) were collected. RESULTS: Across diagnostic groups, we observed heightened effort expenditure when money was used as a reward (b&#xa0;=&#xa0;0.13, p&#xa0;=&#xa0;0.018). We did not find an interaction of CHR status (b&#xa0;=&#xa0;0.07, p&#xa0;=&#xa0;0.845) or negative symptoms (b&#xa0;=&#xa0;0.01, p&#xa0;=&#xa0;0.429) with reward-type. Within CHR individuals, heightened negative symptom severity was associated with reduced expended effort (b&#xa0;=&#xa0;-0.03, p&#xa0;=&#xa0;0.016), regardless of reward type. In an exploratory analysis, we found that individuals in the money condition with relatively high household income expended less effort during high reward, high probability trials (b&#xa0;=&#xa0;-0.24, p&#xa0;=&#xa0;0.046). CONCLUSIONS: Across CHR and HC individuals, individuals pursuing money expended greater effort. While we did not find a group by reward type interaction, CHR individuals with heightened negative symptom severity expended less effort across trials, replicating prior work. Present findings support further study of point-based rewards in tasks indexing amotivation.

Humans↗

The role of the external genitalia score (EGS) in evaluation of disorders of sex development.

OBJECTIVE: To investigate the utility of the External Genitalia Score (EGS) in the diagnosis of disorders of sex development (DSD) and decision-making regarding gender assignment in affected patients. METHODS: A retrospective cohort study was conducted, enrolling 114 DSD patients aged <2 years (88 reared as males, 26 reared as females) treated at our hospital between April 2005 and June 2023, alongside 40 hypospadias patients aged <2 years who underwent surgery at our institution from January to July 2023. Demographic data (age) and EGS assessments of external genitalia were collected for all participants. Statistical analyses included independent samples t-tests, Mann-Whitney U tests and Receiver Operating Characteristic (ROC) curve analysis. Specifically, EGS scores were compared between the hypospadias group and the male-reared subgroup of the DSD cohort; additionally, EGS scores were contrasted between male-reared and female-reared DSD subgroups. RESULTS: The mean age was 20.3 months in the hypospadias group, 17.9 months in the male-reared DSD group, and 18.8 months in the female-reared DSD group. EGS ranged from 5.5 to 11.5 (median 10.5) in the hypospadias group and from 1 to 12 (median 4.75) in the DSD group. ROC curve analysis was performed to compare EGS scores between the hypospadias group and the male-reared DSD subgroup. The optimal diagnostic threshold was determined by maximizing the Youden index (sensitivity + specificity - 1), which balances sensitivity and specificity. A cut-off value of &#x2264;8.50 was identified as indicative of DSD; clinically, patients with an EGS score <9 should be prioritized for DSD screening. Further comparison between male-reared and female-reared DSD subgroups yielded a threshold of 4.00. Clinically, an EGS score &#x2264;4 may suggest a preference for female gender assignment. DISCUSSION: The EGS scale is a reliable, valid, and clinically feasible tool for characterizing external genitalia in DSD patients. An EGS score of 9 can serve as an indicator for initiating detailed sex development evaluation in hypospadias patients. While gender assignment in DSD is a complex, multifactorial process, EGS scores showed a significant association with the sex of rearing in our cohort. In settings where major determinants are balanced, EGS may serve as an adjunctive descriptive parameter rather than a standalone decision-making tool.

Humans↗

Nursing students' perspective of dignity: A systematic review.

AIM: This review synthesizes research on nursing students' perceptions of dignity shaped by education and clinical experiences. BACKGROUND: Respect for human dignity is central to nursing ethics. While dignity is well studied in patient care, less focus has been given to how nursing students perceive and experience dignity during their education. DESIGN: A systematic review of quantitative, qualitative, and mixed-methods studies. METHODS: A comprehensive search was conducted across the Medline, PubMed, ScienceDirect, Scopus, and Web of Science databases for English-language studies published from 2000 to 2025. Quality was assessed using the Joanna Briggs Institute Critical Appraisal Checklist and the Mixed Methods Appraisal. Tool. Data were synthesized thematically. Reporting followed PRISMA guidelines. RESULTS: A total of 24 articles were included. Students viewed patient dignity as linked to respect, privacy, and autonomy. Although students had solid theoretical knowledge, they encountered institutional and professional barriers in delivering dignified care. Supportive environments and participation in decision-making enhanced their sense of dignity. Finally, educational strategies such as role-playing, simulations, and empathy exercises enhanced emotional and psychosocial awareness. CONCLUSIONS: These findings indicate that dignity is crucial in shaping nursing students' professional identity and ethical awareness throughout their education. Reinforcing ethical values and dignity in nursing education is essential for high-quality care.

Humans↗

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

Germline variants and impact on lung cancer outcomes following chemotherapy: A systematic review.

BACKGROUND: Lung cancer is the primary cause of cancer deaths in the UK and globally, and the main subtypes are non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC). Many treatment options are available, with platinum-based chemotherapy being a key component for many patients. However, variation in survival outcomes exists among individuals of European ancestry, which makes it important to identify germline genetic variants that help guide decision-making and optimise patient treatment and outcomes. METHOD: A systematic literature search was conducted in PubMed and Web of Science for lung cancer studies investigating the impact of germline genetic variants on systemic anti-cancer therapy (SACT) outcomes in populations of European ancestry. The review was conducted according to the Preferred Reporting Items of Systematic Review and Meta-Analysis (PRISMA) and Synthesis without Meta-Analysis (SWiM) guidelines. RESULTS: A total of 20 studies were included in the review out of 4469 on NSCLC and SCLC, encompassing 3639 patients. The most thoroughly investigated area was NSCLC treated with platinum-based chemotherapy. Genetic variants associated with overall survival and/or progression-free survival included XPD Lys751Gln, XPD Asp312Asn, ERCC1 C118T, and XRCC1 Arg399Gln. For non-platinum-treated NSCLC and SCLC, there was insufficient evidence to conduct a meaningful investigation. CONCLUSION: The XPD Lys751Gln, XPD Asp312Asn, ERCC1 C118T, and XRCC1 Arg399Gln variants showed potential associations with survival outcomes among patients of European ancestry with NSCLC after platinum-based chemotherapy. To support clinical implementation, large real-world pharmacogenomics studies stratified by ancestry are needed to overcome statistical power and heterogeneity limitations.

Humans↗

Health-Related quality of life (HRQoL) and health state utility values (HSUV) in patients with head and neck Cancer: A systematic review and Meta-Analysis.

BACKGROUND: Head and neck cancer (HNC) and its treatment can substantially impair speech, swallowing, eating, appearance, and social functioning, resulting in persistent reductions in health-related quality of life (HRQoL). Although the EuroQol 5-Dimensions questionnaire (EQ-5D) is widely used to assess generic HRQoL and derive health state utility values (HSUVs), EQ-5D-based evidence in HNC has not been comprehensively synthesized. This study aimed to summarize EQ-5D-based HRQoL and HSUVs in HNC, estimate pooled utility and EQ-VAS scores, explore subgroup differences, and identify predictors of poorer HRQoL. METHODS: A systematic review and meta-analysis was conducted according to PRISMA guidelines and registered in PROSPERO (CRD420261307907). PubMed, EMBASE, Web of Science, Cochrane Library, and Scopus were searched from inception to February 10, 2026. Studies reporting baseline EQ-5D utility values and/or EQ-VAS scores in patients with HNC were included. Random-effects meta-analyses using the DerSimonian-Laird (DL) estimator with the Hartung-Knapp-Sidik-Jonkman (HKSJ) adjustment were performed to pool mean scores. Between-study variance (&#x3c4;2) and 95&#xa0;% prediction intervals (PI) were calculated to capture parameter dispersion. Subgroup analyses were conducted across clinical and methodological vectors. RESULTS: Twenty studies involving 7,403 patients were included. The pooled mean EQ-5D utility score was 0.79 (95&#xa0;% CI: 0.75-0.83; &#x3c4;2&#xa0;=&#xa0;0.0011; 95&#xa0;% PI: 0.72-0.86). The pooled mean EQ-VAS score was 69.36 (95&#xa0;% CI: 65.71-73.01; &#x3c4;2&#xa0;=&#xa0;38.4586; 95&#xa0;% PI: 55.11-83.61). Extreme heterogeneity was observed (I2&#xa0;=&#xa0;96.4&#xa0;% and 97.1&#xa0;%, respectively). Utility values were significantly higher in studies utilizing the EQ-5D-5&#xa0;L than the EQ-5D-3&#xa0;L version (0.82 vs. 0.76). By tumor subsite, nasopharyngeal cancer showed the highest utility value (0.85, exploratory), whereas oral cancer demonstrated the lowest (0.73). Adjusted multivariable models revealed that advanced stage, high treatment intensity, severe pharyngolaryngeal pain, dysphagia, malnutrition, and older age were robust predictors of poorer HRQoL. CONCLUSIONS: Patients with HNC experience substantial and persistent HRQoL impairment, with meaningful variations driven by tumor subsites and instrument versions. In light of the extreme heterogeneity, these pooled findings establish a macro-level, broad reference estimate rather than a fixed target. These parameters directly inform localized survivorship care planning, health technology evaluations, and cost-utility decision-making modeling in head and neck oncology.

Humans↗

Machine learning vs. traditional methods for predicting postoperative cardiac complications after non-cardiac surgery: a systematic review and Bayesian network meta-analysis.

INTRODUCTION: Accurate prediction of peri-operative cardiac complications is critical to optimise pre-operative decision-making. Traditional risk prediction scores, such as the Revised Cardiac Risk Index, show only modest discrimination. Machine learning can model complex, non-linear relationships but their predictive performance compared with traditional scores remains unclear. METHODS: We performed a systematic review and Bayesian network meta-analysis. The primary outcome was postoperative adverse cardiac events following non-cardiac surgery. Prediction models were assessed relative to the Revised Cardiac Risk Index. As many studies evaluated multiple versions of each model type, the highest performing ('best version') and lowest performing ('worst version') results were analysed. Models were ranked using the surface under the cumulative ranking curve (SUCRA). RESULTS: Thirteen studies evaluating 54 models and 927,113 patients were included. Machine learning approaches generally outperformed traditional risk scores. Automated machine learning ranked highest (SUCRA 96.6) showed the greatest improvement in the best version analysis (mean difference (MD) 0.28 (95%CrI 0.16-0.40)) and remained superior in the sensitivity analysis (MD 0.30 (95%CrI 0.14-0.45)). Gradient boosting models showed superior performance over the Revised Cardiac Risk Index across analysis (best version: MD 0.20 (95%CrI 0.14-0.26), worst version: MD 0.18 (95%CrI 0.12-0.25), SUCRA 82.4). The Gupta Perioperative Risk for Myocardial Infarction or Cardiac Arrest score outperformed the Revised Cardiac Risk Index in the best version analysis (MD 0.16 (95%CrI 0.01-0.32)). Between-study heterogeneity was low. None of the included studies externally validated their machine learning models and only six were judged to be at low risk of bias. DISCUSSION: Most machine learning models showed better discrimination than traditional risk scores, with automated machine learning and gradient boosting models ranking highest. However, study quality, calibration reporting and absence of external validation limit immediate clinical adoption. Prospective, multicentre evaluation is required before integration of these models into peri-operative practice.

Humans↗

Perspectives of participating neurologists and study nurses - Mixed-methods process evaluation of a web-based program for relapse management in multiple sclerosis (POWER@M2).

BACKGROUND: Relapsing-remitting multiple sclerosis is a chronic inflammatory disease of the central nervous system and the leading cause of disability in young adults. In Germany, 90% of relapses are treated with high-dose intravenous glucocorticoids, despite limited evidence for long-term benefit and international preference for oral administration. Time constraints often hinder informed decision-making. The multicentre Randomized Controlled Trial (RCT) POWER@MS2 (N&#x202f;=&#x202f;160, 2020-2023), conducted at 18 German MS-centres, aimed to promote self-determined relapse management through a complex intervention (dialogue-based decision aid, nurse-led webinar, online-chat). OBJECTIVE: While RCTs demonstrate effectiveness, process evaluations are essential to understand implementation, mechanisms of impact and contextual factors. This study explored healthcare professionals' experiences and attitudes toward implementing relapse self-management and self-medication in clinical practice. METHODS: A mixed-methods process evaluation followed the UK Medical Research Council- framework. Quantitative data were collected via validated questionnaires at up to three time points and analysed descriptively. Interview guides were developed based on these results. Qualitative data from neurologist and study nurse interviews were thematically analysed. Results were triangulated using a joint display. RESULTS: Data were collected from 55 neurologists and 17 study nurses (quantitative) and from 7 neurologists and 4 nurses (qualitative) (2020-2024). Most neurologists opposed routine steroid use, reserving it for severe relapses. Some voiced concerns about self-management, but informed patients were generally viewed as capable of safe self-medication. Study nurses gave mixed feedback on the intervention, citing overload and improved guidance. CONCLUSION: Clinicians showed openness toward implementing the intervention. Enhancing accessibility and addressing specific concerns may support broader adoption.

Humans↗