Inform Treatment Decisions Research Articles

Practice Patterns and Trends in the Surgical Management of Mismatch Repair Deficient Colon Cancer

IntroductionDefects in the DNA mismatch repair (MMR) pathway can predispose individuals to colorectal cancer (CRC), with germline mutations in this pathway leading to Lynch syndrome. Consequently, universal MMR testing is recommended for all newly diagnosed CRC patients to detect mismatch repair deficient (MMR-D) tumors, enabling informed treatment decisions. Given the increased potential for metachronous disease in patients with Lynch syndrome, the current guidelines for surgical management of Lynch-associated colon cancer recommend extended resection in patients under age 60. MethodsA retrospective analysis of nonmetastatic CRC was performed from the National Cancer Database to evaluate the current trends and practice patterns in the surgical management of MMR-D colon cancer, as well as assess the factors influencing choice of surgical procedure. ResultsFrom 2018 to 2020, 98,112 nonmetastatic CRC patients were identified, with 19.93% being MMR-D. MMR-D colon cancer patients were more likely to undergo extended resection than those with mismatch repair proficient tumors (9.4% versus 4.2%, P < 0.001). When accounting for approximately one-fourth of MMR-D colon cancers being attributable to Lynch syndrome, the frequency of extended resection was less than expected (9.4% versus 25%, P < 0.001). MMR-D patients under age 60 were more likely to undergo extended resection than those over age 60 (9% versus 3%) (odds ratio [OR] 3.57, 95% confidence interval [CI] 3.06-4.15). Several factors were associated with decreased rate of extended resection: uninsured (OR 0.42, 95% CI 0.21-0.84), Black race (OR 0.54, 95% CI 0.35-0.82), treatment at nonacademic centers (OR 0.74, 95% CI 0.56-0.97), and crowfly distance >25 miles (OR 1.98, 95% CI 1.14-3.45). ConclusionsThese findings provide valuable insight into the current surgical practice patterns in the management of MMR-D colon cancers and possibly colon cancers associated with Lynch syndrome.

Bone marrow aspirate concentrate for the treatment of fifth metatarsal head stress fracture: a case report.

Metatarsal head stress fractures pose treatment challenges with no established consensus. In this article, we introduce a percutaneous treatment involving autologous bone marrow aspirate concentrate (BMAC) injection without surgical fixation in a 21-year-old basketball player with a stress fracture of the right fifth metatarsal head. He underwent this procedure following unsuccessful 8months of conservative treatment. Twelve weeks after the procedure, a CT scan confirmed complete healing, facilitating his return to sports. This innovative method offers a promising alternative, avoiding the associated morbidity of surgical intervention. Further research, comparing refracture rates with surgical options, is warranted to inform treatment decisions for this uncommon injury and validate the efficacy of percutaneous BMAC injection.

Current approaches to the management of neuroendocrine breast carcinoma (NEBC): a review

Neuroendocrine breast carcinoma (NEBC), an infrequent malignancy, accounts for 2–5% of all invasive breast cancer cases. The minimal occurrence of these tumours has resulted in knowledge primarily acquired from unique case reports or short retrospective studies. NEBC is diagnosed by identifying morphological characteristics related to gastrointestinal tracts and lung neuroendocrine tumors and neuroendocrine biomarkers. Recent investigations have revealed that NEBCs, despite being hormone receptor-positive and HER2-negative, may have adverse outcomes in comparison to invasive breast cancer lacking neuroendocrine differentiation. The primary approach for early NEBC is surgical intervention, which is identical to invasive non-special histological carcinoma treatment. Anthracycline-and-taxane protocols are commonly used for neoadjuvant, adjuvant, and metastatic diseases, whereas platinum substances and etoposide are widely utilized for small-cell histology and high-proliferation tumors. At present, NEBC is categorized as an unspecified form of invasive breast carcinoma, lacking a more precise classification, as there is insufficient evidence to inform treatment decisions due to its low incidence and absence of randomized data. This review outlines the WHO classification, pathology, immunohistochemistry, diagnosis, treatment, and prognosis of NEBC. Furthermore, it encapsulates the most recent research on the molecular characteristics of NEBC, intending to offer innovative therapeutic insights into the disease.

Otolaryngologists Demonstrate Low Agreement on Pediatric Airway Inflammation Assessment.

Microlaryngoscopy and bronchoscopy (MLB) are essential tools for evaluating airway inflammation, but the reliability of endoscopic assessments for this purpose remains unclear. The aim of this study was to assess surgeons' interrater reliability during endoscopic assessment of airway inflammation. The endoscopic factors used to determine overall airway inflammation were also assessed. We conducted a cross-sectional study involving 24 pediatric patients who underwent MLB and arytenoid biopsy. Surgeons rated airway inflammation based on endoscopic images, and interrater reliability was assessed using Fleiss' Kappa. Fleiss's Kappa demonstrated poor interrater reliability among all surgeons (0.111) and experienced surgeons (0.117). Surgeons varied in prioritizing visual features for assessing inflammation. Current subjective assessments of airway inflammation during MLB exhibit poor interrater reliability, necessitating further research for improved diagnostic accuracy and informed treatment decisions in pediatric airway interventions. Level 3 Laryngoscope, 2024.

Enhancing advanced cervical cell categorization with cluster-based intelligent systems by a novel integrated CNN approach with skip mechanisms and GAN-based augmentation

Cervical cancer is one of the biggest challenges in global health, thus it forms a critical need for early detection technologies that could improve patient prognosis and inform treatment decisions. This development in the form of an early detection mechanism increases the chances of successful treatment and survival, as early diagnosis promptly offers interventions that can dramatically reduce the rate of deaths attributed to this disease. Here, a customized Convolutional Neural Network (CNN) model is proposed for cervical cancerous cell detection. It includes three convolutional layers with increasing filter sizes and max-pooling layers, followed by dropout and dense layers for improved feature extraction and robust learning. By using ResNet models as inspiration, the model further innovates by incorporating skip connections into the CNN design. By enabling direct feature transmission from earlier to later layers, skip links enhance gradient flow and help preserve important spatial information. By boosting feature propagation, this integration increases the model’s ability to recognize minute patterns in cervical cell images, hence increasing classification accuracy. In our methodology, the SIPaKMeD dataset has been employed which contains 4049 cervical cell images that are arranged into five different categories. To address class imbalance, Generative Adversarial Networks (GANs) have been applied for data augmentation; that is, synthetic images have been created, that improve the diversity of the dataset and further enhance the robustness of the same. The present model is astonishingly accurate in classifying five cervical cell types: koilocytes, superficial-intermediate, parabasal, dyskeratotic, and metaplastic, thus significantly enhancing early detection and diagnosis of cervical cancer. The model gives an excellent performance because it has a validation accuracy of 99.11% and a training accuracy of 99.82%. It is a reliable model in the diagnosis of cervical cancerous cells because it ensures advancement in the computer-assisted cervical cancer detection system.

Advancing precision in CT-guided bone biopsies: exploring the potential of dual-energy CT imaging.

This study aimed to investigate the integration of dual-energy CT (DECT) into CT-guided bone biopsy procedures, comparing it with conventional CT techniques. The focus was on technical aspects, accuracy and radiation dose exposure. A total of 51 bone biopsies were conducted, with 36 using conventional CT and 15 utilizing DECT. Patient data, lesion characteristics and biopsy techniques were analyzed. Statistical analyses, including Fisher's exact test and independent samples t-test, were performed to compare accuracy and radiation doses between the two methods. DECT-guided biopsies demonstrated a significantly higher accuracy (93.33%) compared to conventional CT biopsies (86.11%). The radiation dose exposure for DECT was comparable to conventional CT. DECT's ability to differentiate tissues, especially in bone marrow edema detection, led to higher precision. Integrating DECT into CT-guided bone biopsies enhances tissue differentiation and accuracy without significantly increasing radiation exposure. This advancement holds promise for improving musculoskeletal interventional radiology, leading to more precise diagnoses, informed treatment decisions and improved patient outcomes.

Diagnostic test accuracy of cellular analysis of bronchoalveolar lavage fluid in distinguishing pulmonary infectious and non-infectious diseases in patients with pulmonary shadow.

This study aims to assess the diagnostic accuracy of cellular analysis of bronchoalveolar lavage fluid (BALF) in distinguishing between pulmonary infectious and non-infectious diseases in patients with pulmonary shadows. Additionally, it will develop and validate a novel scoring system based on a nomogram for the purpose of differential diagnosis. A retrospective analysis was conducted involving data from 222 patients with pulmonary shadows, whose etiological factors were determined at our institution. The cohort was randomly allocated into a training set comprising 155 patients and a validation set of 67 patients, (ratio of 7:3), the least absolute shrinkage and selection operator (LASSO) regression model was applied to optimize feature selection for the model. Multivariable logistic regression analysis was applied to construct a predictive model. The receiver operating characteristic curve (ROC) and calibration curve were utilized to assess the prediction accuracy of the model. Decision curve analysis (DCA) and clinical impact curve (CIC) were employed to evaluate the clinical applicability of the model. Moreover, model comparison was set to evaluate the discrimination and clinical usefulness between the nomogram and the risk factors. Among the relevant predictors, the percentage of neutrophils in BALF (BALF NP) exhibited the most substantial differentiation, as evidenced by the largest area under the ROC curve (AUC = 0.783, 95% CI: 0.713-0.854). A BALF NP threshold of ≥16% yielded a sensitivity of 72%, specificity of 70%, a positive likelihood ratio of 2.07, and a negative likelihood ratio of 0.38. LASSO and multivariate regression analyses indicated that BALF NP (p < 0.001, OR = 1.04, 95% CI: 1.02-1.06) and procalcitonin (p < 0.021, OR = 52.60, 95% CI: 1.83-1510.06) serve as independent predictors of pulmonary infection. The AUCs for the training and validation sets were determined to be 0.853 (95% CI: 0.806-0.918) and 0.801 (95% CI: 0.697-0.904), respectively, with calibration curves demonstrating strong concordance. The DCA and CIC analyses indicated that the nomogram model possesses commendable clinical applicability. In models comparison, ROC analyses revealed that the nomogram exhibited superior discriminatory accuracy compared to alternative models, with DCA further identifying the nomogram as offering the highest net benefits across a broad spectrum of threshold probabilities. BALF NP ≥16% serves as an effective discriminator between pulmonary infectious and non-infectious diseases in patients with pulmonary shadows. We have developed a nomogram model incorporating BALF NP and procalcitonin (PCT), which has proven to be a valuable tool for predicting the risk of pulmonary infections. This model holds significant potential to assist clinicians in making informed treatment decisions.

A review of Neurosurgical RCTs in the Cochrane Database of Systematic Reviews: Key findings and implications for future research

Evidence available to clinicians and patients to inform treatment decisions is ideally produced by randomised controlled trials (RCT). The objective of this study was to assess the extent to which Neurosurgical practice is supported by RCT-level evidence. A search of the Cochrane Library was conducted to find reviews of the effectiveness of Neurosurgical operative interventions. Data were extracted on the intervention, patient population and outcome measures as well as the strength of evidence, as rated by the Cochrane authors. The extracted data were analysed to identify the gaps and areas of (in)consistency across the RCTs included within the Cochrane Reviews. A total of 52 Cochrane reviews met the inclusion criteria, which covered 8 Neurosurgical subspecialties. However, only 28 were published after 2015. There was limited coverage of multiple commonly performed Neurosurgical interventions and 9 reviews found no RCTs related to their selected topic. In 28 reviews, results were synthesized from 5 or fewer trials. Primary outcomes also varied among trials examining similar interventions. The overall quality rating of the evidence for the different subspecialties varied, with the majority of reviews rating the evidence as being from very low to low. The RCT level evidence supporting Neurosurgical practice is varied and the outcomes tested remain predominantly heterogenous. There remain important Neurosurgical conditions where treatment strategies are not underpinned by high quality evidence. Pragmatic RCTs, well-designed observational studies as well as robust audit and registry processes may provide the real-world evidence for treatment decisions in Neurosurgical care.

Cerebral cortical encephalitis in adults with myelin oligodendrocyte glycoprotein antibody-associated disease: A national case series.

Myelin oligodendrocyte glycoprotein (MOG) antibody-associated disease (MOGAD) is a relatively recently described disease, most commonly presenting with optic neuritis and longitudinally extensive transverse myelitis. Cerebral cortical encephalitis is a rare manifestation of MOGAD. We identified patients presenting with cerebral cortical encephalitis with positive MOG antibodies in serum across a large specialized service. Demographic and clinical information were collected. We describe clinical and laboratory characteristics, treatment response, and subsequent relapse risk in adults presenting with this phenotype. We identified eight patients meeting clinical criteria for cerebral cortical encephalitis with MOG antibodies. All had seizures; four had focal onset seizures with or without secondary generalization. Two patients exhibited encephalopathy, and six demonstrated focal neurological deficits at presentation. All had fluid-attenuated inversion recovery hyperintensities. Five of eight displayed cerebral swelling, and two of eight displayed leptomeningeal enhancement. Where cerebrospinal fluid (CSF) results were available, five of seven had CSF pleocytosis, protein was raised in two of seven, and one patient had oligoclonal bands unique to CSF. Median time to seizure control was 1.25 months, and all clinical features and magnetic resonance imaging abnormalities resolved. Four of eight patients (50%) had a clinical relapse, with a median time to relapse of 6.4 months. Cerebral cortical encephalitis appears to share similar CSF findings, steroid responsiveness, and risk of relapse with other clinical manifestations of MOGAD. This informs treatment decisions and patient counselling.

Retinopathy of Prematurity: Incidence, Risk Factors, and Treatment Outcomes in a Tertiary Care Center.

Retinopathy of prematurity (ROP) remains a major cause of childhood blindness. Its pooled prevalence worldwide is 31.9%, and that of severe ROP is 7.5% among prematurely born babies. Investigating risk factors is essential for improving early detection and treatment outcomes. Purpose: To determine the frequency and stages of ROP cases and evaluate the treatment methods for premature infants at the Medical University of Vienna. Methods: In this retrospective study, 352 children who underwent ROP screening between 2018 and 2021 with a gestational age (GA) ≤ 32 weeks and/or a birth weight (BW) ≤ 1500 g were included. Results: ROP was found in 144 (40.9%) of the 352 screened premature infants, with 17 (4.8%) requiring treatment. Significant risk factors included GA and BW, while sex and pregnancy type were not significant. The mean GA was 27.7 ± 2.5 weeks, and the mean BW was 989.1 ± 359.7 g. Infants with ROP had a lower GA (25.9 ± 1.7 weeks) and BW (778.6 ± 262.4 g) than those without ROP (28.9 ± 2.2 weeks; 1134.9 ± 345.9 g). GA and BW were significantly lower in infants developing ROP (p < 0.001). Stage 2 ROP was the most common severity in 74 children (51.4%). Laser therapy was the most common first-line treatment, used in 11 infants (64.7%), followed by anti-VEGF therapy, used in 6 infants (35.3%). Children were treated within 1.0 ± 0.6 days on average. Of the 17 infants treated, 14 (82.4%) showed initial regression. Three infants (17.6%) required re-treatment: two with initial anti-VEGF therapy and one after laser therapy. Conclusions: The findings provide insights into ROP's prevalence and treatment preferences at a university tertiary care center. GA and BW were confirmed to be significant predictors, aiding in early detection and informing treatment decisions. These insights will enable comparisons with similar studies and contribute to improved patient care.

Abstract A014: Effects of senescence on the lung tumor microenvironment

Abstract Despite progress in screening and treatment, lung cancer remains the leading cause of cancer- related deaths worldwide. An overarching issue is the complexity and heterogeneous nature of the tumor microenvironment and eventual tumor spread. While aging is a key determinant, the relationship between aging and cancer is multi-faceted and extends beyond the accumulation of mutations. Therefore, a much-needed framework integrating the mechanistic principles that change with aging to drive neoplastic transformation beyond genetics will help us uncover predictive biomarkers that inform treatment decision-making and how we may use them to prevent, postpone, suppress tumor growth, and limit spread. Here, we investigate the role of age-related senescent cell accumulation in lung tumorigenesis and propose a potential strategy to delay tumor progression and spread by selectively targeting tumor-promoting senescent cells that arise with increasing age to sustain protective antitumor immunity. Citation Format: Luis Prieto. Effects of senescence on the lung tumor microenvironment [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor-body Interactions: The Roles of Micro- and Macroenvironment in Cancer; 2024 Nov 17-20; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(22_Suppl):Abstract nr A014.

Abstract 4135852: Safety and Post-operative Complications of Endovascular Versus Surgical Versus Follow-up and Medical Treatment for Patients with Vertebrobasilar Artery Stenosis: Propensity Score Weighting and a Machine Learning Driven Analysis

Background: Vertebrobasilar artery stenosis (VBAS) can cause posterior circulation strokes (PCS). Optimal management is controversial, with options including medical therapy (MT), endovascular stenting (ES), and surgical revascularization (SR). This study compares outcomes of these treatments and evaluates the correlation between clinical features and medical history with 30-day outcome. Methods: Patients with VBAS were identified from the 2017-2018 National Inpatient Sample (NIS). Propensity scores adjusted for baseline differences. Outcomes included mortality, neurological complications (NC), discharge destination (DD), length of stay (LOS), total charges (TC), and procedural complications (PC). Predictive ability of clinical variables was assessed using logistic regression (LR) and machine learning techniques (MLT). Results: Of 1,343 patients, 1,061 (79.0%) received NI, 234 (17.4%) underwent ES, and 24 (1.8%) had SR. Mean age was 69.45 years, with 64.1% male. Demographics: 69.8% White, 14.9% Black, 10.0% Hispanic, and 5.3% other races. Hypertension (HTN, 85.4%) and diabetes (DM, 18.9%) were prevalent. After propensity weighting, ES was associated with higher odds of mortality, surgical/medical complications (SMC), and device/graft complications (DGC) compared to NI. SR showed a non-significant trend toward higher non-home discharges (NHD). ES and SR groups had higher resource utilization with longer LOS and greater TC. Clinical variables alone were weak predictors, with AUC values ranging from 0.454 to 0.71 across different outcomes and models. Conclusion: ES of VBAS was associated with higher mortality and complication rates compared to MT alone, with inconsistent benefits for NC. SR also carried elevated risks without clear advantages over MT. These results support that current clinical independent variables from the NIS are weak predictors. This highlights the limitation of the database in relying solely on clinical and medical history, and suggests that future use of radiological and anatomical features can improve predictions of outcomes and determination of subgroups that can benefit from certain treatment. More studies should be conducted, including post hoc analyses based on radiological and anatomical features, to better inform treatment decisions and determine subgroups that can benefit from intervention or surgery. These findings suggest a need for judicious patient selection and reinforce the role of optimal MT.

Gene-eral survey to describe genomic education needs in hospital pharmacy departments in the West Midlands and Oxford

Abstract Introduction Genomic medicine is a rapidly developing field and a priority for the NHS to ensure it is embedded into Medicine Service Alliance is that the NHS staff have understanding and confidence to utilise genomics safely and effectively. Pharmacy professionals, as experts in medicines, will lead the implementation and delivery of pharmacogenomics and wider genomic medicine services across all healthcare sectors1. Aim To understand current levels of genomic education across NHS Trust Pharmacy Departments in the Central and South region, and preferences for types of future learning. Methods A MS Forms survey was distributed across the Pharmacy Departments of five NHS Trusts, emailed to all local pharmacy staff via the Education and Training lead pharmacists; all pharmacy staff were eligible to participate, and total numbers of staff were not available. The survey was based on a previously published national survey2, but reduced in content to allow completion within 5 minutes; content was agreed between the genomics specialist pharmacy team at C&amp;S. Ethics approval was not sought as this baseline evaluation formed part of a planned service improvement. Results One hundred and twenty-nine respondents participated in the survey, including pharmacists (62%), pharmacy technicians (29%) and assistant technical officers (5%). Seventy-one out of 127 respondents (56%) had more than 10 years of experience since qualified. Given a scale of ’very low-low-medium -high-very high’, the majority of the 127 respondents (63%) considered their knowledge about Genomic Medicine to be medium or high, and no responder considered themselves to have a very high level of knowledge about Genomic Medicine. Most participants saw the relevance of Genomic Medicine to their professions, particularly in areas like personalised medicine and 82% expressed an interest in learning more about Genomic Medicine and 15% answered ’Maybe’; the cohort had a preference for in-person meetings and seminars (32%), followed by on-line meetings (27%). Discussion / Conclusion Respondents saw the relevance of Genomic Medicine to their professions, and showed a mixture of enthusiasm, curiosity, and uncertainty about Genomic Medicine, with no respondent feeling they had a very high level of knowledge of Genomic Medicine. Most pharmacy staff in the 5 departments surveyed have an interest in furthering their knowledge of Genomic Medicine, with a marked preference for in-person meetings and seminars. Respondents recognised the potential benefits such as personalized medicine, improved treatment outcomes and reduced trial-and-error approaches in medication selection, with expectations that Genomic Medicine will improve patient care and outcomes, reducing adverse events and informing treatment decisions Limitations to this study include an inability to judge response rate due to lack of denominator data, however relatively similar numbers were obtained from each Department, with a good mix of respondent roles. An in-person training event with hybrid online options is being planned as a result of this work.

Comparing five-year and ten-year predicted cardiovascular disease risk in Aotearoa New Zealand: national data linkage study of 1.7 million adults.

There is no consensus on the optimal time horizon for predicting cardiovascular disease (CVD) risk to inform treatment decisions. New Zealand and Australia recommend 5 years, whereas most countries recommend 10 years. We compared predicted risk and treatment-eligible groups using 5-year and 10-year equations. Individual-level linked administrative datasets identified 1,746,665 New Zealanders without CVD, aged 30-74 years in 2006, with follow-up to 2018. Participants were randomly allocated to derivation and validation cohorts. Sex-specific 5-year and 10-year risk prediction models were developed in the derivation cohort and applied in the validation cohort. 28,116 (3.2%) and 62,027 (7.1%) first CVD events occurred during 5-years and 10-years follow-up respectively (cumulative risk, derivation cohort). Median predicted 10-year CVD risk (3.8%) was approximately 2.5 times 5-year risk (1.6%) and 95% of individuals in the top quintile of 5-year risk were also in the top quintile of 10-year risk, across age/gender groups (validation cohort). Using common guideline-recommended treatment thresholds (5% 5-year, 10% 10-year risk), approximately 14% and 28% of women and men respectively were identified as treatment-eligible applying 5-year equations compared to 17% and 32% of women and men applying 10-year equations. Older age was the major contributor to treatment eligibility in both sexes. Predicted 10-year CVD risk was approximately 2.5 times 5-year risk. Both equations identified mostly the same individuals in the highest risk quintile. Conversely, commonly used treatment thresholds identified more treatment-eligible individuals using 10-year equations and both equations identified approximately twice as many treatment-eligible men as women. The treatment threshold, rather than the risk horizon, is the main determinant of treatment eligibility.

Neuroanatomy of the vertebrobasilar perforators: implications for aneurysm treatment.

The anatomy of vertebrobasilar perforators has been widely studied in human cadavers, with most reports found in the neurosurgical literature. These arterial perforators are extremely hard to visualize consistently with traditional two-dimensional digital subtraction angiography, but are reliably visible with cross sectional cone beam CT techniques. A clear understanding of this specific neurovascular anatomy and pathology is essential for informed treatment decisions. This review analyzes the anatomy of vertebrobasilar perforators with a focus on practical implications for aneurysm treatment, particularly flow diversion.

Conventional and Emerging Diagnostic Approaches for Differentiated Thyroid Carcinoma

Differentiated thyroid carcinoma (DTC) is among the most prevalent endocrine cancers. The diagnosis of DTC has witnessed tremendous progress in terms of technological advancement and clinical operational guidelines. DTC diagnostics have evolved significantly over centuries, from early clinical examinations to modern molecular testing and imaging modalities. The diagnosis and management of DTC are currently dependent on the international histological classification and identification of specific genetic abnormalities in tumor tissue, as well as the prognostic implications that can inform treatment decisions. This study goes down the memory lanes of various diagnostic methods for DTCs, highlighting recent advancements in molecular testing and point-of-care (POC) technology. Beginning with conventional methods like fine needle aspiration biopsy (FNAB), fine needle aspiration cytology (FNAC), and ultrasound (US) and moving to contemporary innovative approaches such as POC-thyroglobulin (POC-Tg) and liquid biopsy, this review showcases the current trends in DTC diagnostics. Although considerable progress has been achieved in early malignancy detection, patient stratification, prognosis, and personalized treatment, there is a need to refine the mainstay diagnostic procedures. Finally, future perspectives were provided, and emerging roles of artificial intelligence in DTC diagnostics were explored.

DSTYK Inhibition Sensitizes NSCLC to Taxane-Based Chemotherapy

Chemotherapy continues to be the standard treatment for patients non-eligible for targeted or immune-based therapies; nevertheless, treatment resistance remains a major clinical challenge. We previously found that expression levels of DSTYK, a poorly explored dual serine/threonine, and tyrosine kinase frequently amplified in cancer, identify patients with lung cancer exhibiting poor response to immune checkpoint inhibitors and reported that its inhibition sensitizes to immunotherapy. Seeking to explore the potential of DSTYK targeting in additional indications, we investigated the functional relevance and actionability of DSTYK in lung cancer chemoresistance. We show that DSTYK depletion specifically sensitizes lung cancer cells to taxane-based chemotherapy, particularly in combination with carboplatin. Mechanistically, DSTYK ablation remodels the cytoskeleton and impairs distant invasion and metastatic outgrowth in vivo. DSTYK downregulation sensitizes both primary and metastatic lung tumors to chemoimmunotherapy treatment leading to tumor regression in mouse models. Consistently, clinical data of early and advanced patients with lung cancer (in the neoadjuvant and adjuvant settings) show a strong correlation between DSTYK amplification and taxane resistance, underscoring the clinical significance of our findings to inform treatment decision-making. Collectively, our data indicates that DSTYK amplification may be a predictor of resistance to taxane-based treatments and represents an actionable target for these patients.

Genomic Epidemiology of Antimicrobial Resistance: Tracking the Global Spread of Resistant Pathogens

The rapid development and spread of antimicrobial resistance have been one of the most prominent health crises globally, which significantly challenges treating infectious diseases. This paper will address the contribution that genomic epidemiology makes to track and understand the global spread of antimicrobial-resistant pathogens. Genomic epidemiology, an area combining pathogen genomics with epidemiological data, allows for an extremely powerful approach in the identification of resistance mechanisms and tracing transmission routes for guiding public health interventions. This review Emphasizes major bacterial pathogens, such as Escherichia coli, Staphylococcus aureus, and Klebsiella pneumoniae, which harbor major resistance genes: blaCTX-M, mecA, and blaKPC. These genes contribute to the worldwide dissemination of resistance, mainly through mechanisms involving horizontal gene transfer and selective antibiotic pressure. Thus, genomic surveillance, phylogenetic analysis, and bioinformatics approaches allow for the pinpointing of transmission hotspots, mapping of resistance gene distribution, and tracking of emerging resistant strains in real time. It also provides information on how genomic data are being used to improve antimicrobial stewardship programs and inform clinical treatment decisions. Public health responses can further be tailored by recognizing regional resistance patterns, hence enhancing interventions. However, several challenges persist—for example, the need for standardized sharing of data, interpretation of genomic data, and integration of these insights into public health systems, especially in low-resource settings. This abstract highlights the transformative impact of genomic epidemiology in the management of the AMR crisis while emphasizing the continued need for global cooperation, enhanced data infrastructures, and policy initiatives to ensure the effective use of genomic data in public health.

Assessment of medical doctors' knowledge of new psychoactive substances and their neurobehavioural effects

New Psychoacve Substances (NPS), also known as designer drugs, pose significant public health risks due to their potent psychoacve properes and potenal neurobehavioural effects. Medical doctors play a crucial role in idenfying and addressing the health risks associated with NPS use. This study assessed medical doctors' knowledge of NPS and their neurobehavioral effects. A cross-seconal online survey of licensed medical doctors was conducted, revealing varying levels of awareness and knowledge regarding NPS. While respondents showed familiarity with NPS terminology and street names, gaps existed, parcularly concerning specific NPS categories. This underscores the importance of enhancing medical professionals' understanding of NPS to ensure comprehensive paent care and informed treatment decisions.

Optimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach.

Decisions about when to change antidepressant treatment are complex and benefit from accurate prediction of treatment outcome. Prognostic accuracy can be enhanced by incorporating repeated assessments of symptom severity collected during treatment. Participants (n = 714) from the Genome-Based Therapeutic Drugs for Depression study received escitalopram or nortriptyline over 12 weeks. Remission was defined as scoring ≤ 7 on the Hamilton Rating Scale. Predictors included demographic, clinical, and genetic variables (at 0 weeks) and measures of symptom severity (at 0, 2, 4, and 6 weeks). Longitudinal descriptors extracted with growth curves and topological data analysis were used to inform prediction of remission. Repeated assessments produced gradual and drug-specific improvements in predictive performance. By Week 4, models' discrimination in all samples reached levels that might usefully inform treatment decisions (area under the receiver operating curve (AUC) = 0.777 for nortriptyline; AUC = 0.807 for escitalopram; AUC = 0.794 for combined sample). Decisions around switching or modifying treatments for depression can be informed by repeated symptom assessments collected during treatment, but not until 4 weeks after the start of treatment.