Bisphenol A (BPA), nonylphenol (NP), and octylphenol (OP) are common environmental phenolic endocrine disruptors and widely used industrial chemicals that have garnered significant attention due to their potential to disrupt endocrine functions. These compounds are known to interfere with hormonal activities, particularly those related to estrogen, and are linked to the onset and progression of breast cancer. This study aims to systematically investigate the potential relationship between BPA, NP, and OP and breast cancer risk, along with their underlying molecular mechanisms, by synthesizing data from multiple databases. We initially acquired the chemical structures and SMILES representations of BPA, NP, and OP from the PubChem database. Subsequently, we utilized multiple databases, including the Comparative Toxicogenomics Database (CTD), SEA, and Swiss Target Prediction, t0 estimate their probable biological targets. The predicted targets were standardized and consolidated to form a comprehensive target database. Breast cancer-related targets were subsequently identified from the GeneCards and DisGeNET databases, and their overlap with the targets of BPA, NP, and OP was analyzed to pinpoint potential breast cancer risk targets. To elucidate the functional pathways involved, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses using the DAVID database. This analysis offered insights into the molecular pathways influenced by BPA, NP, and OP in the context of breast cancer. Additionally, we utilized machine learning algorithms, specifically Least Absolute Shrinkage and Selection Operator (LASSO) regression and Support Vector Machine (SVM), to identify nuclear targets linked to BPA, NP, and OP-induced breast cancer. These nuclear targets were further validated through differential expression analysis and Receiver Operating Characteristic (ROC) curve analysis using the GEO dataset GSE42568. We also performed a Single Gene Gene Set Enrichment Analysis (GSEA) to investigate the potential regulatory mechanisms of these nuclear genes in breast cancer. The infiltration of immune cells in breast cancer tissues was analyzed using single-sample gene set enrichment analysis (ssGSEA), and the correlation between nuclear targets and immune cell infiltration was examined. Finally, molecular docking and molecular dynamics simulations were conducted to assess the binding affinity and stability of BPA, NP, and OP with their nuclear targets. In this study, we integrated network toxicology, machine learning and multi-omics validation, and identified for the first time that BPA, NP and OP may induce breast cancer through 156 common targets; among them, MAOA, MGLL, ADRA2A, RPN2, GF1R and CTSD were identified as the key causative genes, with a diagnostic efficacy of 0.80–0.94 AUC. Mechanistically, these genes are concentrated in the GPCR/MAPK/JNK, sphingolipid, and prolactin signaling pathways, which regulate the Wnt/TGF-β/chemokine network and dramatically modify the immunological infiltration of nine classes of M0-M2 macrophages and CD4⁺ T cells. Molecular docking and kinetic simulations suggested the strong affinity of BPA for MGLL, and the complex was stabilized with ≥ 3 hydrogen bonds. In conclusion, phenolic endocrine disruptors may cause breast cancer through the “multi-target-immune microenvironment-metabolic reprogramming” axis, and MAOA, MGLL, ADRA2A, and RPN2 may serve as new targets for early detection and management.

BACKGROUND:Rare occurrence, immune checkpoint inhibitors (ICI)-related myocarditis are poorly documented in the literature. RESEARCH DESIGN AND METHODS:We conducted a retrospective review of patients who had ICI until June 2023. Patient follow-up was extended until death or on May 2024. The primary outcome was the incidence of suspected ICI-related myocarditis. Logistic regression was used to investigate the associations between clinical characteristics and suspected ICI-related myocarditis. RESULTS:Among the included 8199 patients, 1638 (19.98%) patients developed suspected ICI-related myocarditis. Logistic regression revealed that thymomas and thymic carcinomas (OR 2.242; [95% CI, 1.132-4.440], p = 0.021), lung cancer (OR 1.259; [95% CI, 1.119-1.416], p < 0.001), older patients (OR 1.021; [95% CI, 1.016-1.026], p < 0.001), male (OR 1.213; [95% CI, 1.061-1.388], p = 0.005), block two or more immune checkpoints (OR = 1.391 [95% CI 1.058-1.828], p = 0.018), combined with hypertension (OR = 1.326 [95% CI 1.162-1.513], p < 0.001), or hyperlipidemia (OR = 1.656 [95% CI 1.302-2.107], p < 0.001) were associated with higher risk of suspected ICI-related myocarditis. CONCLUSIONS:This large, real-world cohort demonstrates that the incidence of suspected ICI-related myocarditis may be underestimated in previous literature. Routine cardiac surveillance is needed in high-risk patients receiving ICI therapy. TRIAL REGISTRATION:Registered at https://www.chictr.org.cn (identifier: ChiCTR2300075974).

BACKGROUND:Immune checkpoint inhibitor (ICI)-induced pancreatic adverse events (AEs) are rare occurrences that are poorly documented in the literature. RESEARCH DESIGN AND METHODS:We conducted a retrospective review of patients who had ICI up to June 2023. Patient follow-up was extended until death or to May 2024. The primary outcome was the incidence of severe ICI-related pancreatic AEs. Logistic regression was used to investigate the associations between clinical characteristics and severe ICI-related pancreatic AEs. RESULTS:The study included 7,840 participants who received ICI. The study population was predominantly male (74.50%), with a median age of 59.20 years [IQR 51.90-67.70 years]. Among them, 49 patients (0.63%) developed severe ICI-related pancreatic AEs. Logistic regression revealed that pancreatic cancer (OR 5.47; [95% CI, 1.12-26.82], p = 0.036), lung cancer (OR 2.62; [95% CI, 1.09-6.34], p = 0.032), younger patients (OR 0.97; [95% CI, 0.94-0.99], p = 0.015), and using PD-L1 inhibitor (OR 3.09, [95% CI 1.46 to 6.52], p = 0.003) were associated with a higher risk of severe ICI-related pancreatic AEs. CONCLUSIONS:This study demonstrated that most ICI-related pancreatic AEs were asymptomatic. Primary tumor type, age, and ICI type may be predictive factors for severe ICI-related pancreatic AEs. CLINICAL TRIAL REGISTRATION:https://www.chictr.org.cn identifier is ChiCTR2300075974.

BackgroundThis study aims to investigate the incidence of tuberculosis (TB) infection following administration of immune checkpoint inhibitors (ICI) and to explore the risk factors for developing TB in patients treated with ICIs.Research design and methodsWe conducted a retrospective review of patients who had ICI until June 2023. Patient follow-up was extended until death or on July 2025. The primary outcome was the incidence of TB infection in patients treated with ICIs. Logistic regression was used to investigate the associations between clinical characteristics and TB infection after ICI initiation.ResultsOf the 8,199 patients analyzed, 2.65% had a pre-existing TB diagnosis. The incidence of TB following ICI initiation was 1.96%, with pulmonary TB being the most frequent presentation. Logistic regression revealed that pre-existing TB (OR 3.277; [95% CI, 1.822–5.895]; p < 0.001) and male sex (OR 1.798; [95% CI, 1.173–2.756]; p = 0.007) were significantly associated with TB following ICI initiation.ConclusionIn this large, real-world cohort of cancer patients receiving ICI therapy, we observed a notable incidence of tuberculosis. These findings suggest that enhanced clinical vigilance may be warranted for these high-risk populations, and they highlight the need for prospective, controlled studies to definitively quantify the excess TB risk attributable to ICI therapy.Clinical Trial Registrationhttps://www.chictr.org.cn, identifier ChiCTR2300075974.

BackgroundDrug-induced agranulocytosis (DIA) is a rare but life-threatening hematologic disorder that demands increased clinical and research attention. This study aimed to provide the current overview of DIA for clinical guidance.MethodsUsing real-world data from FDA Adverse Event Reporting System (FAERS), we performed a disproportionality analysis to identify the drugs associated with agranulocytosis, employing the information component and reporting odds ratio algorithms. Logistic analysis was conducted to explore the confounding factors of DIA. Time-to-onset analysis was implemented to compare the adverse event onset time among different drugs. To comprehensively supplement and corroborate our disproportionality findings, we further conducted an umbrella review of systematic reviews (SRs). Five electronic databases were searched with SRs addressing DIA as an included adverse event. Two independent reviewers performed literature screening, data extraction, and quality assessment according to the preferred reporting items for systematic reviews and meta-analysis statement. The results of the included SRs were synthesized using qualitative analysis.ResultsThe disproportionality analysis revealed that most identified DIA signals were for anticancer drugs. The top-five drugs with DIA signals by case number were methotrexate (6,462 cases), lenalidomide (5,722 cases), rituximab (5,691 cases), doxorubicin (4,391 cases), and carboplatin (4,371 cases). High-risk drugs (e.g., deferiprone), old age, and abnormal weight were strongly associated with DIA based on multivariate logistic regression. Time-to-onset analysis showed that clozapine has the longest median of onset time (1,121.3 days), while azithromycin has the shortest time (8.1 days). The umbrella review included seven systematic reviews, with five focusing on anticancer therapy. Their findings on DIA-associated drugs, including protein kinase inhibitors and immune checkpoint inhibitors, were consistent with those from the disproportionality analysis. Antibiotics, antithyroid drugs, and psychotropic drugs were also identified as causative drugs of DIA.ConclusionThis study systematically reviewed the FAERS database and existing literature on DIA to identify a spectrum of associated drugs. Anticancer drugs were predominant, with targeted therapies comprising a large proportion, while non-chemotherapy drugs were also identified as suspect drugs. These findings underscored the need for heightened clinical vigilance toward suspected drugs and highlighted the importance of future efforts to validate high-risk mechanisms and explore DIA monitoring strategies.

INTRODUCTION:To compare the risks of serious infections, herpes zoster (HZ), and opportunistic infections associated with Janus kinase (JAK) inhibitors versus placebo, tumor necrosis factor-α inhibitors (TNFi), methotrexate (MTX), and among different JAK inhibitors. METHODS:We searched PubMed, Embase, Cochrane Library, and Web of Science databases from their inception until 23 January 2024. Network meta-analysis estimated odds ratios for infections using restricted maximum likelihood models. RESULTS:Eighty randomized controlled trials were included with 40,460 patients. Part of JAK inhibitors including tofacitinib (5 mg [2.01; 95%CI, 1.25-3.23], 10 mg [1.84; 95%CI, 1.06-3.17]), baricitinib (4 mg [1.57; 95%CI, 1.05-2.35]), and upadacitinib (15 mg [1.55; 95%CI, 1.06-2.27], 30 mg [1.94; 95%CI, 1.26-2.98]), exhibited a significantly different risk of serious infections compared to placebo. Similarly, tofacitinib (10 mg), baricitinib (4 mg), upadacitinib (15 mg, 30 mg), abrocitinib (200 mg), and peficitinib (100 mg) showed a significantly different risk of HZ infection compared to placebo. Most JAK inhibitors didn't raise opportunistic infections risks vs. TNFi and MTX, and risks among JAK inhibitors weren't statistically significant. CONCLUSION:Attention should be paid to JAK inhibitor's types, dosages, and it is important to be aware of the risk of serious infections and HZ infections. Future long-term studies should be conducted. PROSPERO:CRD42024523067.

Current guidelines lack definitive recommendations on the use of chemotherapy for early-stage breast cancer in patients aged over 70. Clinical decision-making on chemotherapy for elderly breast cancer remains challenging because of insufficient large-scale, long-term outcomes. We conducted a retrospective cohort study using the Surveillance, Epidemiology, and End Results database from 2010 to 2020 to investigate early-stage breast infiltrating ductal carcinoma in patients aged 70 to 79. Propensity score matching (PSM) with a ratio of 1:1 and caliper of 0.02 standard deviation of propensity score was employed to address covariate imbalance. Univariate and multivariate analyses were performed to assess the impact of chemotherapy on breast cancer-specific survival (BCSS) and overall survival (OS). We identified a total of 11,792 patients with complete information about breast cancer, who underwent surgical treatment and received systemic therapy after surgery. Among them, 3,490 patients received chemotherapy. After PSM, we obtained a matched cohort consisting of 3,156 patients where the characteristics between the two groups were balanced except for molecular subtypes. In the matched dataset, no significant differences were observed in BCSS (P = 0.118) and OS (P = 0.119) between the two groups based on Kaplan-Meier survival analysis. Similarly, multivariate COX analysis revealed that chemotherapy did not significantly reduce the risk of BCSS (HR: 1.212; 95% CI: [0.958-1.533], P = 0.109) and OS (HR: 0.888; 95% CI: [0.765-1.031], P = 0.12). Stratified analyses based on molecular subtypes revealed that chemotherapy did not confer a favorable prognosis in patients with hormone receptor (HR)-positive, human epidermal growth factor receptor 2(HER2)-negative breast cancer in stages I and IIa, as well as in patients with HR+HER2+ breast cancer in stages I. Chemotherapy may not confer a discernible benefit for all elderly patients with breast cancer. Nevertheless, de-escalating chemotherapy could be considered as a preferable alternative for older individuals diagnosed with HR+HER2- breast cancer in stages I and IIa or HR+HER2+ breast cancer in stages I.

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C0), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug–drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.

BACKGROUND:Identifying the outcomes that matter in clinical research is important, especially those that matter to patients and their parents/guardians. Consistency in outcome reporting enables meaningful assessments of interventions and facilitates comparison of results across trials. The aim of this study was to develop core outcome sets for pediatric perioperative research. METHODS:The authors determined core outcome sets through extensive stakeholder engagement, following a stepwise process as recommended by the Core Outcome Measures in Effectiveness Trials (COMET) initiative. They surveyed patients, parents/guardians, and healthcare providers to elicit views on the importance of perioperative outcomes. These results informed a subsequent Delphi process of expert stakeholder representatives. Final core outcome sets were agreed to after virtual face-to-face meetings of the investigators. RESULTS:A total of 1,178 total subjects were included in the international stakeholder survey: 81 patients ages 8 to 12 yr, 99 patients ages 13 to 17 yr, 587 parents/guardians, and 411 healthcare providers (128 nurses, 147 anesthesiologists, and 136 surgeons). Subjects were recruited in Australia, Canada, China, Colombia, the Netherlands, New Zealand, South Africa, Switzerland, and the United States. Sixty-seven expert stakeholders completed a two-round Delphi, including 7 patient family representatives, 9 surgeons, 7 nurses, and 44 anesthesiologists. Proposed core outcome sets were voted on and unanimously agreed to after the virtual face-to-face meetings for the following populations: neonates, infants, children ages 1 to 12 yr, and adolescents ages 13 to 17 yr. Core outcomes for all populations included cardiovascular or respiratory adverse events, pain, assessment of pain relief, and unplanned medical attention. Quality of recovery was included in all but the neonate population, while return to normal function was also included in the adolescent population. CONCLUSIONS:The authors identified perioperative core outcome sets for four age-based pediatric populations. Researchers should include these outcomes in their studies whenever appropriate, in addition to the outcomes specific to their research question.

Background: The gut microbiome might be affected by proton-pump inhibitors (PPIs), increasing the risk of Clostridioides difficile infection (CDI); however, the association between PPIs and Clostridioides difficile infection (CDI) remains controversial. Aim: The aim of this study is to reevaluate the association between PPIs and CDI based on pharmacovigilance data, taking competition bias into account. Methods: PPI-related CDI adverse event reports, based on the Food and Drug Administration adverse event reporting system database from 2004 to 2023, were analyzed. Included PPI cases were stratified into CDI and non-CDI groups. Disproportionality analysis was performed using the reporting odds ratio (ROR) and information component (IC). The effect of competition bias on signal detection was quantitatively investigated. Age-stratified analyses were conducted to assess residual confounding. Results: A total of 238,470 PPI reports were included, with 1268 cases in the CDI group and 237,202 cases in the non-CDI group. Initial analysis revealed a significant PPI-CDI association (ROR = 2.36, 95% confidence interval (95%CI) 2.19 to 2.53; IC = 1.21, 95%CI 0.97 to 1.45), with CDI signals detected for five PPI agents, including pantoprazole, omeprazole, lansoprazole, rabeprazole, and dexlansoprazole. After excluding competition from antibacterial drugs, CDI signal strength decreased substantially (ROR = 1.47, 95%CI 1.34 to 1.62; IC = 0.55, 95%CI 0.23 to 0.87), retaining a significant CDI signal only for rabeprazole and pantoprazole. Upon further exclusion of antibacterial or immunosuppressive drug users and renal injury event cases, CDI signal strength decreased (ROR = 1.48, 95%CI 1.32 to 1.66; IC = 0.56, 95%CI 0.18 to 0.94), with pantoprazole as the sole CDI signal drug. Age-stratified analyses demonstrated complete signal loss after antibacterial drug adjustment across all age groups. Conclusions: The current large-scale pharmacovigilance study indicated that the observed PPI-CDI association may be mediated predominantly by antibacterial drug co-exposure rather than PPI direct causation.

BACKGROUND:Rheumatoid arthritis (RA) is a disease characterized by synovitis. The synovium of RA patients is rich in macrophages, which are differentiated mainly from monocytes. The susceptibility gene of RA, tumor necrosis factor-α inducible protein 3 (tnfaip3), is considered an anti-inflammatory factor. Our previous study revealed the abnormal protein expression of TNFAIP3 in monocytes from patients with RA. OBJECTIVE:In the present study, we aimed to explore the role of TNFAIP3 in monocytes in RA and its potential functions. METHODS:In vivo, we injected adenoviral vectors overexpressing tnfaip3 into mice with collagen-induced arthritis (CIA) (the TNFAIP3-oe group). Arthritis scores, as well as the expression of iNOS and CD206 in the synovium, were compared between the TNFAIP3-oe group and the CIA group. In vitro, we used lentivirus transfection to upregulate/downregulate the expression of tnfaip3 in THP-1 cells. The ability of these cells to migrate, secrete cytokines and differentiate into macrophages was compared. RESULTS:Compared with that in the CIA group, arthritis in the TNFAIP3-oe group was ameliorated (p = 0.030). Moreover, the joints of these mice presented more CD206+ cells and fewer iNOS+ cells (both p < 0.001), indicating the anti-inflammatory effect of TNFAIP3 and its regulation of macrophage polarization. In vitro, the tnfaip3-depleted cells (the TNFAIP3-i group) had greater migration and differentiated into M1 macrophages, and more cells overexpressing tnfaip3 (the TNFAIP3-oe group) differentiated into M2 macrophages. Furthermore, cells in the TNFAIP3-i group showed increased secretion of the proinflammatory cytokines IL-6 and MMPs. CONCLUSIONS:Taken together, these findings suggest that TNFAIP3 in monocytes can regulate inflammatory arthritis by modulating monocyte migration, differentiation, and cytokine secretion.

Introduction Drug-induced liver injury (DILI) is a significant adverse drug reaction, ranging from mild liver enzyme elevations to severe outcomes such as liver failure, transplantation, or death. This condition is especially concerning in older adults, who may exhibit increased susceptibility to adverse medication effects. This study aimed to develop and compare eight machine learning (ML) models using routine clinical, pharmacological, and laboratory data to predict DILI in older hospitalized patients.Methods We conducted a retrospective analysis of older patients hospitalized in 2022 who exhibited abnormal liver function tests. A total of 421 clinical, pharmacological, and laboratory variables were utilized for model development, with missing data addressed through multiple imputation techniques. The performance of 8 ML algorithms-XGBoost, LightGBM, Random Forest, AdaBoost, CatBoost, Gradient Boosting Decision Trees, Artificial Neural Network, and TabNet-was assessed. The dataset was randomly partitioned into a training set (80%, n = 2,880) and an independent testing set (20%, n = 720). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC).Results Out of the 3,600 older patients with abnormal liver function, 654 patients experienced DILI. The best-performing model, LightGBM combined with Random Forest imputation, achieved an AUC of 0.9829. SHapley Additive exPlanations (SHAP) analysis identified critical predictors for DILI, including the timing of DILI relative to surgery, undergoing surgery, and maximum rate of change (slope) in liver enzymes, albumin, lipoprotein cholesterol, total bilirubin, proBNP, and total bile acids. Additional significant factors included administration of liver-protective medications upon admission; use of diuretics, antibiotics, and narcotic analgesics; and pre-existing liver or gallbladder diseases or malignancies.Discussion The predictive model developed demonstrated excellent performance in identifying DILI in older adults. Leveraging machine learning techniques, this model holds significant potential for clinical implementation to effectively warn clinicians of DILI risk among older hospitalized patients.

BackgroundEmerging evidence indicates that immune checkpoint inhibitor-induced diabetes mellitus (ICI-DM) might be more common than initially reported, and more different clinical pictures associated with ICI-DM were described.ObjectiveThe aim of our study was to identify the clinical characteristics and possible predictive factors of ICI-DM.MethodsWe conducted a retrospective review of patients who received immune checkpoint inhibitors (ICI) at West China Hospital, Sichuan University until June 2023. Patients were reviewed at death or on 7 May 2024. We applied logistic regression to study the associations between clinical characteristics and ICI-DM.ResultsOur study included 8,199 participants who received ICI between October 2014 and June 2023. Among them, 1,077 patients (13.14%) developed ICI-DM according to diagnostic criteria based on guidelines. By excluding patients influenced by glucocorticoids or immunosuppressants, ICI-DM was observed in 713 of 8,199 (8.70%) patients. In all patients, hypertension, hyperlipidemia, using glucocorticoids or immunosuppressants, lung cancer, and using more than one pathway of ICI were associated with a higher risk of ICI-DM. However, the risk factors for ICI-DM in patients without the influence of glucocorticoids or immunosuppressants were only hypertension, hyperlipidemia, and pancreatic lesions. In all patients and those patients without the influence of glucocorticoids and immunosuppressants, hypertension and hyperlipidemia may increase the risk for ICI-DM.ConclusionsThis large, real-world cohort demonstrates that the incidence of ICI-DM may be underestimated in previous literature. Blood glucose monitoring is needed in patients receiving ICI therapy.Clinical trial registrationhttps://www.chictr.org.cn, identifier ChiCTR2300075974.

Processed electroencephalography (EEG) indices used to guide anesthetic dosing in adults are not validated in young infants. Raw EEG can be processed mathematically, yielding quantitative EEG parameters (qEEG). We hypothesized that machine learning combined with qEEG can accurately classify expired sevoflurane concentrations in young infants. Knowledge from this may contribute to development of future infant-specific EEG algorithms. Frontal EEG collected from infants ≤ 3 months were time-matched as one-minute epochs to expired sevoflurane (eSevo). Fifteen qEEG parameters were extracted from each epoch and eight machine learning models combined the qEEG to classify each epoch into one of four eSevo levels (

Objective This systematic review aimed to provide a comprehensive overview of the application of machine learning (ML) in predicting multiple adverse drug events (ADEs) using electronic health record (EHR) data. Methods Systematic searches were conducted using PubMed, Web of Science, Embase, and IEEE Xplore from database inception until 21 November 2023. Studies that developed ML models for predicting multiple ADEs based on EHR data were included. Results Ten studies met the inclusion criteria. Twenty ML methods were reported, most commonly random forest (RF, n = 9), followed by AdaBoost (n = 4), eXtreme Gradient Boosting (n = 3), and support vector machine (n = 3). The mean area under the summary receiver operator characteristics curve (AUC) was 0.76 (95% confidence interval [CI] = 0.26–0.95). RF combined with resampling-based approaches achieved high AUCs (0.9448–0.9457). The common risk factors of ADEs included the length of hospital stay, number of prescribed drugs, and admission type. The pooled estimated AUC was 0.72 (95% CI = 0.68–0.75). Conclusions Future studies should adhere to more rigorous reporting standards and consider new ML methods to facilitate the application of ML models in clinical practice.

AbstractCurrent brain tumor treatments are limited by the skull and BBB, leading to poor prognosis and short survival for glioma patients. We introduce a novel minimally-invasive brain tumor suppression (MIBTS) device combining personalized intracranial electric field therapy with in-situ chemotherapeutic coating. The core of our MIBTS technique is a wireless-ultrasound-powered, chip-sized, lightweight device with all functional circuits encapsulated in a small but efficient “Swiss-roll” structure, guaranteeing enhanced energy conversion while requiring tiny implantation windows ( ~ 3 × 5 mm), which favors broad consumers acceptance and easy-to-use of the device. Compared with existing technologies, competitive advantages in terms of tumor suppressive efficacy and therapeutic resolution were noticed, with maximum ~80% higher suppression effect than first-line chemotherapy and 50–70% higher than the most advanced tumor treating field technology. In addition, patient-personalized therapy strategies could be tuned from the MIBTS without increasing size or adding circuits on the integrated chip, ensuring the optimal therapeutic effect and avoid tumor resistance. These groundbreaking achievements of MIBTS offer new hope for controlling tumor recurrence and extending patient survival.

ObjectiveThe association between proton pump inhibitor (PPI) and dementia was controversial. The aim of the current study was to perform an updated pharmacovigilance analysis of the association between dementia event and PPI treatment after minimizing competition bias.MethodsWe gathered cases reported with PPI treatment based on the United States Food and Drug Administration Adverse Event Reporting System database from 2004 to 2023. We employed disproportionality algorithms, including reporting odds ratio (ROR) and the information component (IC), to detect the association between dementia event and PPI. We investigated the affection of event competition bias on the current disproportionality signal detection.ResultsWe finally included a total of 776,191 PPI cases, and 1813 cases in the dementia group. Analyzing primary suspect PPIs, we detected a significant association between dementia and PPI (ROR = 1.38, 95%CI 1.22 to 1.56; IC = 0.46, 95%CI 0.04 to 0.86). After excluding the PPI case with renal injury events, the strength of the dementia signal increased. Omeprazole (589 cases), pantoprazole (514 cases), and esomeprazole (386 cases) were the top three PPI reported with dementia events.ConclusionThe current pharmacovigilance study identified a significant association between dementia and PPIs, except vonoprazan and tegoprazan, especially taking competition bias into account. Further high-quality prospective study still needed.

Background: Voriconazole plasma concentration exhibits significant variability and maintaining it within the therapeutic range is the key to enhancing its efficacy. We conducted a systematic review and meta-analysis to estimate the prevalence of patients achieving the therapeutic range of plasma voriconazole concentration and identify associated factors.Methods: Eligible studies were identified through the PubMed, Embase, Cochrane Library, and Web of Science databases from their inception until 18 November 2023. We conducted a meta-analysis using a random-effects model to determine the prevalence of patients who reached the therapeutic plasma voriconazole concentration range. Factors associated with plasma voriconazole concentration were summarized from the included studies.Results: Of the 60 eligible studies, 52 reported the prevalence of patients reaching the therapeutic range, while 20 performed multiple linear regression analyses. The pooled prevalence who achieved the therapeutic range was 56% (95% CI: 50%–63%) in studies without dose adjustment patients. The pooled prevalence of adult patients was 61% (95% CI: 56%–65%), and the pooled prevalence of children patients was 55% (95% CI: 50%–60%) The study identified, in the children population, several factors associated with plasma voriconazole concentration, including age (coefficient 0.08, 95% CI: 0.01 to 0.14), albumin (−0.05 95% CI: −0.09 to −0.01), in the adult population, some factors related to voriconazole plasma concentration, including omeprazole (1.37, 95% CI 0.82 to 1.92), pantoprazole (1.11, 95% CI: 0.17–2.04), methylprednisolone (−1.75, 95% CI: −2.21 to −1.30), and dexamethasone (−1.45, 95% CI: −2.07 to −0.83).Conclusion: The analysis revealed that only approximately half of the patients reached the plasma voriconazole concentration therapeutic range without dose adjustments and the pooled prevalence of adult patients reaching the therapeutic range is higher than that of children. Therapeutic drug monitoring is crucial in the administration of voriconazole, especially in the children population. Particular attention may be paid to age, albumin levels in children, and the use of omeprazole, pantoprazole, dexamethasone and methylprednisolone in adults.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023483728.

Older adults with dementia often face the risk of potentially inappropriate medication (PIM) use. The quality of PIM evaluation is hindered by researchers' unfamiliarity with evaluation criteria for inappropriate drug use. While traditional machine learning algorithms can enhance evaluation quality, they struggle with the multilabel nature of prescription data. This study aimed to combine six machine learning algorithms and three multilabel classification models to identify correlations in prescription information and develop an optimal model to identify PIMs in older adults with dementia. This study was conducted from January 1, 2020, to December 31, 2020. We used cluster sampling to obtain prescription data from patients 65 years and older with dementia. We assessed PIMs using the 2019 Beers criteria, the most authoritative and widely recognized standard for PIM detection. Our modeling process used three problem transformation methods (binary relevance, label powerset, and classifier chain) and six classification algorithms. We identified 18,338 older dementia patients and 36 PIMs types. The classifier chain + categorical boosting (CatBoost) model demonstrated superior performance, with the highest accuracy (97.93