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Results for “shared decision-making”

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PubMed1976

An exploratory multi-level attempt to investigate intrapersonal and interpersonal patterns of 20 Athenian families.

The present study is an attempt to explore patterns of family relationships in the context of milieu specific value and role assumptions and to capture the trends in relation to social change. Information collected includes intrapsychic as well as interpersonal material elicited by a combination of tools administered individually and conjointly. The revealed patterns -- extreme emphasis on the future achievement of the child as a shared family goal, the mother's central role which was shown to inhibit constructive processes, the distant marital relationship, and scapegoating of the child because of denied marital difficulties -- are shown to create conflict and tension in all members and render cooperation and decision-making difficult. It is attempted to interpret the above-mentioned patterns in the light of traditional value and role assumptions. The analysis seems to indicate that the adherence to the dysfunctional patterns appears to serve the function of preserving stability of the family in a period of transition.

Achievement↗

PubMed2026

Leveraging traveller genomics for LMIC diarrhoeal disease management.

Diarrhoeal pathogens impose a substantial global health burden, disproportionately affecting low- and middle-income countries (LMICs). However, in these settings, health-seeking behaviours, suboptimal microbiological capacity, and challenges in establishing genomics capacity constrain effective surveillance, including surveillance of antimicrobial resistance (AMR). In contrast, high-income countries routinely generate and share large volumes of diarrhoeal pathogen genomes through established systems, with a significant proportion originating from travellers returning from LMICs. These data reveal strong geographical structuring of lineages and clinically relevant AMR patterns, demonstrating untapped potential to support improvements in geographically granulated surveillance to support antimicrobial treatment recommendations. In this opinion article, we outline the potential to integrate traveller-derived microbial genomic data into LMIC public health decision-making and highlight the scientific, ethical, practical, and governance considerations for implementation.

antimicrobial resistance↗

PubMed2026

NSCLC in Vulnerable and Special Populations: Toward Personalized Care.

NSCLC encompasses a heterogeneous patient population whose clinical needs, biological features, and treatment outcomes differ substantially from those represented in pivotal studies. Adolescents and young adults, women, pregnant patients, individuals with actionable genomic alterations or constitutional pathogenic variants, immunocompromised patients, including those with chronic viral infections, older adults, patients with brain metastases, and survivors with second primary lung cancers remain consistently underrepresented in research programs. This limits the generalizability of current evidence and challenges the delivery of equitable precision oncology. Across these populations, distinct disease biology, differential genomic landscapes, sex- and age-related variations in pharmacology, and complex psychosocial or ethical considerations shape clinical decision-making. Advances in molecular testing and targeted therapies have improved outcomes for some subgroups; however, persistent disparities in diagnostic access, trial eligibility, and supportive care remain major barriers. In parallel, modern systemic agents including brain-penetrant targeted therapies, immunotherapy combinations, and antibody-drug conjugates have broadened therapeutic options, although their safety, effectiveness, and long-term consequences require dedicated evaluation in underrepresented populations. This review synthesizes contemporary evidence from these special NSCLC populations, highlighting shared challenges and unique considerations. We discuss implications for clinical practice, supportive care, survivorship, and research design and outline opportunities to strengthen inclusivity in precision oncology. Addressing longstanding gaps in representation, trial methodology, and structural inequities is essential to ensure that recent therapeutic advances translate into improved outcomes for the full spectrum of patients living with NSCLC.

Humans↗

PubMed2026

Age- and sex-adjusted genomic differences between Korean and Beat AML cohorts.

Genomic profiling plays a central role in risk stratification and therapeutic decision-making in acute myeloid leukemia (AML), yet the clinical implications of population-specific genomic architectures remain incompletely defined. We conducted a prospective, multicenter study of 603 adults with newly diagnosed AML in Korea, integrating targeted sequencing of 83 recurrently mutated genes with comprehensive clinical annotation across treatment intensities, including allogeneic hematopoietic stem cell transplantation (allo-HSCT). For contextual comparison, genomic profiles were evaluated against the Beat AML cohort. The overall genomic landscape was broadly conserved, supporting shared core disease biology across populations. However, RUNX1::RUNX1T1, CEBPA, GATA2, KIT, and DDX41 mutations were more frequent in the Korean cohort, whereas FLT3 and NPM1 mutations were less common. These differences translated into a distinct distribution of European LeukemiaNet (ELN) 2022 risk categories, with implications for therapeutic stratification. Notably, most DDX41 alterations were germline (3.2%), highlighting the need for systematic germline evaluation with implications for genetic counseling and donor selection. Although unadjusted overall survival appeared longer in the Korean cohort, this difference was not significant after adjustment for key clinical variables. These findings indicate that population-specific genomic distributions reshape the clinical application of risk stratification and support population-aware precision medicine strategies in AML.

Journal Article↗

PubMed2026

Integrating rare and common variation in epilepsy genetics: from genetic architecture to penetrance and clinical expressivity.

Epilepsy genetics has often been interpreted through a useful but simplified dichotomous framework in which severe epilepsies, particularly developmental and epileptic encephalopathies, are attributed mainly to rare, high-effect variants, whereas more common epilepsies are viewed as arising largely from the cumulative effects of common, small-effect variation. Although this framework has been instrumental for gene discovery, molecular diagnosis, and mechanism-based treatment, it does not fully explain incomplete penetrance, intrafamilial phenotypic heterogeneity, or marked differences in severity among individuals sharing the same molecular diagnosis. Evidence from exome sequencing, copy number variant (CNV) studies, and genome-wide association studies increasingly suggests that rare SNVs/indels, CNVs, and common variant should not be interpreted as entirely independent risk sources, but may partially converge on shared genes, pathways, cell types, and neurobiological processes relevant to neuronal excitability, network stability, and seizure susceptibility. Here, we review evidence across epilepsy subtypes, focusing on convergence and divergence across the allelic spectrum, and discuss how polygenic background and other modifiers may influence penetrance and clinical expressivity among carriers of rare pathogenic variants and CNVs. We also consider implications for variant interpretation, genetic counseling, risk stratification, and precision medicine, while emphasizing that most rare-common integrated models remain insufficiently validated for routine clinical decision-making.

common variants↗

PubMed2025

Future-proofing tuberculosis therapy: framework for concurrent drug and resistance testing development.

The rapid emergence of resistance to novel tuberculosis drugs, such as bedaquiline, is a key threat to the long-term effectiveness of novel regimens. Given that the introduction of these agents has enabled the introduction of an all-oral regimen for rifampicin-resistant and multidrug-resistant tuberculosis, the rise of resistance underscores the urgent need to safeguard their efficacy and responsible use. A major barrier is the delay in developing reliable tools to detect resistance to novel compounds, which limits clinical decision-making and surveillance efforts. Herein, we outline a framework for integrating the development of drug susceptibility testing alongside tuberculosis drug development, including early stage resistance profiling and defining appropriate epidemiological cutoff values. We highlight key gaps, including the need for structured partnerships between drug developers, diagnostic manufacturers, regulators, research institutions, funders, and policy makers. We propose a roadmap to accelerate drug susceptibility testing and development of new tuberculosis regimens, ensuring that resistance detection maintains pace with the introduction of novel drugs. Establishing collaborative platforms for data sharing, genomic analysis, and diagnostic innovation will help ensure that resistance detection evolves in step with drug development, thereby preserving novel treatments and improving global tuberculosis care.

Humans↗

PubMed2026

iMTSS: an integrated framework for biology- and patient-driven prognosis in myelofibrosis undergoing transplantation.

BACKGROUND: Allogeneic hematopoietic cell transplantation is the only curative treatment for myelofibrosis, but failure occurs by two mechanistically distinct routes: relapse of the neoplasm, which reflects its underlying genetics, and non-relapse mortality, which reflects whether the patient and graft tolerate the procedure. Established prognostic systems either lack molecular granularity or were derived in the non-transplant setting, and all collapse these two routes into a single survival estimate. None can indicate why an individual patient is at risk, or which class of intervention might reduce that risk. OBJECTIVE: To determine why an individual patient is at risk and to develop and validate an integrated framework that quantifies biology- and patient-driven prognosis. STUDY DESIGN: We analyzed 1,550 adults undergoing first allogeneic transplantation for primary or secondary myelofibrosis across international centers, the largest genomically annotated transplant cohort in this disease. The cohort was split into development (n=930) and validation (n=620) sets. Overall survival was modeled by Cox regression; relapse and non-relapse mortality were modeled as competing events by Fine-Gray subdistribution-hazard regression at 2 years. Discrimination was assessed by the concordance index with bootstrap confidence intervals. The molecular contribution was quantified by variance decomposition of, and robustness to the analytic choices was examined by resampling. RESULTS: A genetically defined disease-intrinsic axis, including TP53 allelic state, RAS pathway mutations, ASXL1 and driver genotype, blasts and blood counts, predicted 2 year relapse incidence (validation concordance 0.69, 95% CI 0.63 to 0.74), whereas a non-overlapping host and structural axis, including portal vein thrombosis, donor type, patients' performance status, and age predicted 2-year non-relapse mortality (0.63, 95% CI 0.59 to 0.68). The two scores shared only 3.4% of their variance, indicating that a patient's disease genetics carried almost no information about non-relapse mortality. Variance decomposition showed that TP53 allelic state alone accounted for 30% of the relapse score. Recombined, the framework discriminated overall survival (concordance 0.640, 95% CI 0.616 to 0.662) better than every established prognostic system. For proof of concept, 3 risk groups separated in the validation cohort, with 5 year survival of 72%, 58%, and 39% (P<0.001), and the models were well calibrated. CONCLUSIONS: Relapse and non-relapse mortality after transplantation for myelofibrosis are governed by distinct dimensions. Estimating both outcomes independently with genetic and clinical information, in addition to overall survival, establishes an individualized basis for transplant decision-making. The calculator is openly available (https://imtss-calculator.com).

mortality↗

PubMed2026

RBM20 Truncating Variants and Human Cardiomyopathy.

IMPORTANCE: Genetic diagnosis has become increasingly important to guide clinical decision-making for patients with dilated cardiomyopathy (DCM). Pathogenic or likely pathogenic (P/LP) missense variants in the gene RBM20 cause a highly penetrant arrhythmogenic DCM, but the role of RBM20 truncating variants (RBM20tvs) is unclear. OBJECTIVE: To assess the contribution of RBM20 variants to arrhythmogenic DCM. DESIGN, SETTING, AND PARTICIPANTS: In this cohort study, participants in the genome-first UK Biobank (UKB) and All of Us populations were evaluated to assess the etiologic fraction, natural history and penetrance of RBM20 variants. Retrospective data were collected from an international cohort of patients with DCM and RBM20 variants identified at centers of excellence for genetic heart disease and compared based on time to event. Study dates are not disclosed because the institutional review board did not authorize the sharing of this information. EXPOSURES: RBM20 variants were compared to known P/LP variants and variants of uncertain significance in RBM20 as well as titin truncating variants (TTNtvs). MAIN OUTCOMES AND MEASURES: Major ventricular arrhythmias, end-stage heart failure, and heart failure hospitalization as measured by medical record review (retrospective cohort) and diagnostic codes (UKB). RESULTS: Two main cohorts were studied for this project. In UK Biobank, a cohort of participants with RBM20tvs, RBM20 synonymous variants, and TTNtvs was studied. Of these 4249 participants, 1869 (44%) were male. The mean (SD) age at enrollment was 56 (8.2) years. In the RBM20 registry, of 179 patients, 105 (58.6%) were male, and the mean (SD) age at enrollment was 43.8 (19.1) years. A validation cohort from the All of Us biobank was also used. This consisted of 7002 participants, 4342 of whom (62.0%) were male, and the mean (SD) age was 52.7 (16.7) years. The etiologic fraction of RBM20 variants in arrhythmogenic DCM was 0.53 (95% CI, 0.32-0.67; P < .001). In genome-first biobanks, lifetime incidence of cardiomyopathy, heart failure, or major ventricular arrhythmia diagnosis was lower in participants with RBM20 variants than in those with TTNtvs (hazard ratio, 0.55; 95% CI, 0.36-0.84; P < .001). Patients with RBM20tvs and DCM presented to referral centers later in life than those with P/LP RBM20 and DCM (mean [SD], 53 [10] vs 34 [18] years; P < .001) and were less likely to have a family history of sudden cardiac arrest (2 of 10 [20%] vs 11 of 17 [65%]; P = .046) or cardiomyopathy (2 of 10 [20%] vs 14 of 18 [78%]; P < .001). There was no significant difference in age- and sex-adjusted incident major heart failure or arrhythmia events between patients with RBM20tv and DCM or those with P/LP RBM20 and DCM, though sex-adjusted lifetime hazard was reduced in those with RBM20tv and DCM (hazard ratio, 0.13; 95% CI, 0.03-0.56; P = .01). CONCLUSIONS AND RELEVANCE: This study found that RBM20 variants contributed to arrhythmogenic DCM phenotypes but conferred reduced lifetime disease penetrance compared to TTNtvs and milder disease severity alone than P/LP RBM20 variants. Their potential for additive interactions with other damaging variants should be considered in patients with DCM and their families.

Humans↗

PubMed2026

Identifying General Practitioners, Nurses, and Pharmacists Training Needs in Precision Medicine: A Survey Study.

INTRODUCTION: The clinical advances of precision medicine, elevating clinical decision-making through use of genetic and genomic data, lifestyle, and environment factors, is improving patient outcomes. Health care professionals report they are not competent or confident to deliver precision medicine to patients. To design continuing education for advanced practice nurses, general practitioners, and pharmacists, this research investigates perceived knowledge, importance, and self-efficacy in precision medicine. METHODS: Items were informed from results of a literature review and focus group study. A one-sample t test was used to compare differences for each item toward the theoretical neutral value (indifferent in our case, to number 3). To analyze differences between professions, parametric analyses of variance (ANOVA) was used. RESULTS: A lack of time, further complicated by a lack of knowledge about precision medicine services, and how to safely share patient data, with a perceived limited network of professionals in precision medicine were reported. Respondents demonstrated low confidence in precision medicine topics while indicating a willingness to pursue training aimed at improving their genetic and genomic competencies. Participants rated topics as only slightly important to their current professional roles. No significant differences were found across professional groups. DISCUSSION: Flexible formats for continuing education aligned to needs are required to target the knowledge and skills gap in precision medicine. Improved knowledge on topics including ethics, legal frameworks, and precision services is needed. Effective educational interventions aimed at enhancing the confidence and competence of health care professionals are essential to making precision care a reality for patients.

CPD↗

PubMed2026

A multi-scale fusion model based on multi-phase contrast-enhanced CT for predicting pancreatic cancer resectability.

Purpose.Develop a multi-scale fusion model (MSFM) based on multi-phase contrast-enhanced computed tomography (CECT) to predict pancreatic cancer (PC) resectability, thereby assisting expert decision-making.Methods.This retrospective study enrolled 280 patients with PC from four institutions, which were randomly divided into a training cohort (202 patients) and an independent test cohort (78 patients). Three-phase CECT images (arterial, venous, and delayed phases) were used for modeling. The MSFM comprises two sub-networks: (1) a multi-phase fusion network for extracting cross-phase shared fusion features, (2) a phase-specific branch network for capturing phase-specific features; and a post-fusion strategy to generate the final predictive score by integrating the shared fusion features and three groups of phase-specific features. Additionally, a human-machine fusion deep learning model (HMfDL) was constructed by fusing the predictive score of the MSFM with expert assessments.Results.In the independent test, the MSFM achieved an AUC (area under the receiver operating characteristic curve) of 0.8385 (95% CI: 0.7521-0.9249), accuracy of 84.62%, sensitivity of 72.00%, and specificity of 90.57%. This performance outperformed single-phase models (AUC range: 0.7638-0.7781), two-phase models (AUC range: 0.7826-0.7864), and ten states-of-the-art classifiers (AUC range: 0.7404-0.7796). The HMfDL further improved the performance, reaching an AUC of 0.8626 (95% CI: 0.7853-0.9400), accuracy of 91.03%, sensitivity of 80.00%, and specificity of 96.23%. Notably, the HMfDL corrected 58.82% of misdiagnosis made by experts.Conclusions. The MSFM effectively fuses multi-phase CECT to enable highly accurate predictions of PC resectability, and provides valuable support for expert decision-making through HMfDL.

Humans↗

PubMed2026

Large cell neuroendocrine carcinoma of the lung: Current standards, emerging targets, and translational foundations.

Pulmonary large cell neuroendocrine carcinoma (LCNEC) is one of the most complex and heterogenous clinical entities in thoracic oncology, sharing features with both non-small cell lung cancer (NSLC) and neuroendocrine lung cancers. LCNEC diagnosis and classification relies on evolving histopathological and molecular criteria that define its diagnostic boundaries. Recent advances have confirmed the dual nature of LCNEC, with distinct small cell-like and non-small cell-like molecular characteristics, which guide treatment decisions. In this review, we synthesize current evidence on the diagnosis, molecular characterization, and multimodality management of LCNEC to provide a comprehensive framework for clinical and translational decision-making. A comprehensive literature search was conducted using the PubMed database with no date restrictions, last updated on 12th of April 2026. Articles were selected based on relevance to the diagnosis, molecular characterization, and management of pulmonary LCNEC. Emphasis was placed on studies providing clinical, pathological, and molecular insights into the field. In this review, we summarize contemporary diagnostic approaches, including the expanding role of immunohistochemistry, next‑generation sequencing, and integrated morpho‑molecular assessment. This review represents a consolidated update on LCNEC genomic and transcriptional landscapes, and actionable molecular alterations that are anticipated to impact treatment decisions. Additionally, it provides a state-of-the-art overview of multimodality management, covering surgical approaches, radiotherapy, perioperative therapy, systemic treatment, and the emerging role of immunotherapy. Despite incremental progress, LCNEC remains constrained by limited prospective data and lack of consensus on optimal treatment pathways. By conducting literature review, we identified persistent gaps in LCNEC published data and hereby highlight key priorities for future research.

Humans↗