Safety, Tolerability, and Preliminary Efficacy of Serplulimab, a Novel Anti-PD-1 Antibody, in Patients with Metastatic or Recurrent Solid Tumors: A Phase I Study.

BACKGROUND: Serplulimab is a novel, recombinant, humanized, monoclonal, anti-programmed death 1 antibody with a similar or better affinity and pre-clinical antitumor activity than pembrolizumab and nivolumab. OBJECTIVE: This phase I, open-label, dose-escalation study evaluated serplulimab in patients with advanced solid tumors. The second interim analysis of the dose-finding phase is reported here. METHODS: Adult patients with histologically confirmed metastatic/recurrent solid tumors who had progressed on, or were intolerant to/clinically unsuitable for standard treatment, were enrolled. Four intravenous serplulimab dose levels were evaluated: 0.3, 1.0, 3.0, and 10.0 mg/kg every 2 weeks in 28-day cycles for up to 2 years. Primary endpoints were the incidence of treatment-emergent adverse events and the maximum tolerated dose. RESULTS: By 27 July, 2020 (data cut-off), 29 patients with stage IV disease (34.5% with lung cancer) received one or more doses of serplulimab. One (3.4%) patient had completed treatment and 26 (89.7%) had discontinued from the study. The maximum tolerated dose was not reached. Twenty-two (75.9%) patients experienced treatment-emergent adverse events related to serplulimab, most frequently nausea (24.1%), with no notable differences in incidence between dose cohorts; of these, grade ≥ 3 events occurred in four (13.8%) patients. Pharmacokinetic data demonstrated minimal accumulation of serplulimab after repeated administration. Functional programmed death 1 blockade was observed across dose levels. Objective response and disease control rates were 8.0 and 60.0%, respectively. CONCLUSIONS: Serplulimab was well tolerated and demonstrated antitumor activity. These data support further study of serplulimab in larger patient populations. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov NCT03468751 (19 March, 2018).

Maintenance therapy for chronic lymphocytic leukaemia.

BACKGROUND: Chronic lymphocytic leukaemia (CLL) is the most common lymphoproliferative disease in adults and currently remains incurable. As the progression-free period shortens after each successive treatment, strategies such as maintenance therapy are needed to improve the degree and duration of response to previous therapies. Monoclonal antibodies, immunomodulatory agents, and targeted therapies are among the available options for maintenance therapy. People with CLL who achieve remission after previous therapy may choose to undergo medical observation or maintenance therapy to deepen the response. Even though there is widespread use of therapeutic maintenance agents, the benefits and harms of these treatments are still uncertain. OBJECTIVES: To assess the effects and safety of maintenance therapy, including anti-CD20 monoclonal antibody, immunomodulatory drug therapy, anti-CD52 monoclonal antibody, Bruton tyrosine kinase inhibitor, and B-cell lymphoma-2 tyrosine kinase inhibitor, for individuals with CLL. SEARCH METHODS: We conducted a comprehensive literature search for randomised controlled trials (RCTs) with no language or publication status restrictions. We searched CENTRAL, MEDLINE, Embase, and three trials registers in January 2022 together with reference checking, citation searching, and contact with study authors to identify additional studies. SELECTION CRITERIA: We included RCTs with prospective identification of participants. We excluded cluster-randomised trials, cross-over trial designs, and non-randomised studies. We included studies comparing maintenance therapies with placebo/observation or head-to-head comparisons. DATA COLLECTION AND ANALYSIS: We used standard Cochrane methodological procedures. We assessed risk of bias in the included studies using Cochrane's RoB 1 tool for RCTs. We rated the certainty of evidence for the following outcomes using the GRADE approach: overall survival (OS), health-related quality of life (HRQoL), grade 3 and 4 adverse events (AEs), progression-free survival (PFS), treatment-related mortality (TRM), treatment discontinuation (TD), and all adverse events (AEs). MAIN RESULTS: We identified 11 RCTs (2393 participants) that met the inclusion criteria, including seven trials comparing anti-CD20 monoclonal antibodies (mAbs) (rituximab or ofatumumab) with observation in 1679 participants; three trials comparing immunomodulatory drug (lenalidomide) with placebo/observation in 693 participants; and one trial comparing anti-CD 52 mAbs (alemtuzumab) with observation in 21 participants. No comparisons of novel small molecular inhibitors were found. The median age of participants was 54.1 to 71.7 years; 59.5% were males. The type of previous induction treatment, severity of disease, and baseline stage varied among the studies. Five trials included early-stage symptomatic patients, and three trials included advanced-stage patients (Rai stage III/IV or Binet stage B/C). Six trials reported a frequent occurrence of cytogenic aberrations at baseline (69.7% to 80.1%). The median follow-up duration was 12.4 to 73 months. The risk of selection bias in the included studies was unclear. We assessed overall risk of performance bias and detection bias as low risk for objective outcomes and high risk for subjective outcomes. Overall risk of attrition bias, reporting bias, and other bias was low. Anti-CD20 monoclonal antibodies (mAbs): rituximab or ofatumumab maintenance versus observation Anti-CD20 mAbs maintenance likely results in little to no difference in OS (hazard ratio (HR) 0.94, 95% confidence interval (CI) 0.73 to 1.20; 1152 participants; 3 studies; moderate-certainty evidence) and likely increases PFS significantly (HR 0.61, 95% CI 0.50 to 0.73; 1255 participants; 5 studies; moderate-certainty evidence) compared to observation alone. Anti-CD20 mAbs may result in: an increase in grade 3/4 AEs (rate ratio 1.34, 95% CI 1.06 to 1.71; 1284 participants; 5 studies; low-certainty evidence); little to no difference in TRM (risk ratio 0.82, 95% CI 0.39 to 1.71; 1189 participants; 4 studies; low-certainty evidence); a slight reduction to no difference in TD (risk ratio 0.93, 95% CI 0.72 to 1.20; 1321 participants; 6 studies; low-certainty evidence); and an increase in all AEs (rate ratio 1.23, 95% CI 1.03 to 1.47; 1321 participants; 6 studies; low-certainty evidence) compared to the observation group. One RCT reported that there may be no difference in HRQoL between the anti-CD20 mAbs (ofatumumab) maintenance and the observation group (mean difference -1.70, 95% CI -8.59 to 5.19; 480 participants; 1 study; low-certainty evidence). Immunomodulatory drug (IMiD): lenalidomide maintenance versus placebo/observation IMiD maintenance therapy likely results in little to no difference in OS (HR 0.91, 95% CI 0.61 to 1.35; 461 participants; 3 studies; moderate-certainty evidence) and likely results in a large increase in PFS (HR 0.37, 95% CI 0.19 to 0.73; 461 participants; 3 studies; moderate-certainty evidence) compared to placebo/observation. Regarding harms, IMiD maintenance therapy may result in an increase in grade 3/4 AEs (rate ratio 1.82, 95% CI 1.38 to 2.38; 400 participants; 2 studies; low-certainty evidence) and may result in a slight increase in TRM (risk ratio 1.22, 95% CI 0.35 to 4.29; 458 participants; 3 studies; low-certainty evidence) compared to placebo/observation. The evidence for the effect on TD compared to placebo is very uncertain (risk ratio 0.71, 95% CI 0.47 to 1.05; 400 participants; 2 studies; very low-certainty evidence). IMiD maintenance therapy probably increases all AEs slightly (rate ratio 1.41, 95% CI 1.28 to 1.54; 458 participants; 3 studies; moderate-certainty evidence) compared to placebo/observation. No studies assessed HRQoL. Anti-CD52 monoclonal antibodies (mAbs): alemtuzumab maintenance versus observation Maintenance with alemtuzumab may have little to no effect on PFS, but the evidence is very uncertain (HR 0.55, 95% CI 0.32 to 0.95; 21 participants; 1 study; very low-certainty evidence). We did not identify any study reporting the outcomes OS, HRQoL, grade 3/4 AEs, TRM, TD, or all AEs. AUTHORS' CONCLUSIONS: There is currently moderate- to very low-certainty evidence available regarding the benefits and harms of maintenance therapy in people with CLL. Anti-CD20 mAbs maintenance improved PFS, but also increased grade 3/4 AEs and all AEs. IMiD maintenance had a large effect on PFS, but also increased grade 3/4 AEs. However, none of the above-mentioned maintenance interventions show differences in OS between the maintenance and control groups. The effects of alemtuzumab maintenance are uncertain, coupled with a warning for drug-related infectious toxicity. We found no studies evaluating other novel maintenance interventions, such as B-cell receptor inhibitors, B-cell leukaemia-2/lymphoma-2 inhibitors, or obinutuzumab.

Progression-Free Survival Efficacy in Refractory/Relapsed Multiple Myeloma among Elderly Patients: A Systematic Review.

BACKGROUND: Over the last decade, many studies have assessed the efficacy of treatments for refractory/relapsed multiple myeloma (R/R MM). While combination therapies show greater efficacy than traditional methods, limited research has targeted elderly patients who might be less resilient to treatments. Our study aimed to evaluate treatment efficacy for these elderly patients. METHODS: We carried out a comprehensive review of the literature using a systematic approach. Initially, 4966 citations were retrieved and subsequently narrowed down to 13 eligible randomized controlled trials (RCTs) through our systematic review process from databases like Embase, PubMed, and Cochrane Library from 1 January 2000 to 31 December 2022. Evidence was collated through a frequentist network meta-analysis, using the hazard ratio (HR) for evaluation. RESULTS: Combined therapy of daratumumab, lenalidomide, and dexamethasone (DaraLenDex) was the preferred treatment for R/R MM elderly patients. Its strengths included an HR for progression-free survival (0.15; 95% CI: 0.09-0.25) and a 96% P-score. CONCLUSIONS: Our analysis suggests that, pending more comprehensive RCTs, DaraLenDex is the treatment with the highest efficacy for R/R MM in elderly patients.

Chylothorax after chimeric antigen receptor T cell therapy for relapsed and refractory diffuse large B-cell lymphoma: A case report.

RATIONALE: Anti-CD19-targeted chimeric antigen receptor (CAR) T cell therapy is effective in treating relapsed/refractory diffuse large B-cell lymphoma (DLBCL). This therapy is associated with several side effects that can be life-threatening such as cytokine release syndrome (CRS). However, chylothorax associated with CRS after CAR-T therapy has not been reported. PATIENT CONCERNS: A 23-year-old male diagnosed with DLBCL relapsing after autologous peripheral blood stem cell transplantation was treated with anti-CD19-targeted CAR-T cell therapy. After CAR-T cell transfusion, he developed grade 3 CRS includes fever, dyspnea, tachycardia and hypotension. The symptoms of CRS persisted and chest plain film revealed bilateral pleural effusion. DIAGNOSIS: Chylothorax was confirmed by the pleural effusion analysis that triglyceride level was 1061 mg/dL. Bacterial and fungal culture of pleural fluid reported no pathogen was detected. Cytological examination of pleural effusion revealed no malignant cells. INTERVENTIONS: The chylothorax resolved after treatment with intravenous administration of tocilizumab. OUTCOMES: On 30-day follow-up, the patient was in stable clinical condition with complete remission of DLBCL on whole-body positron emission tomography scan. LESSONS: We reported a rare case of CAR-T associated chylothorax in a patient with relapsed and refractory DLBCL. Grade 3 CRS with high interleukin-6 level was presented in our patient. The symptoms of CRS were improved with tocilizumab treatment and the chylothorax resolved later on. It is suggested that high interleukin-6 releases might induce chyle leakage resulting from activations of endothelium and coagulation. Our finding highlights the occurrence of chylothorax during the course of CAR-T cell therapy and the importance of proper monitoring and prompt management of this life-threatening side effect.

Mortality risk prediction of the electrocardiogram as an informative indicator of cardiovascular diseases.

Background: The electrocardiogram (ECG) may be the most popular test in the management of cardiovascular disease (CVD). Although wide applications of artificial intelligence (AI)-enabled ECG have been developed, an integrating indicator for CVD risk stratification was not investigated. Since mortality may be the most important global outcome, this study aimed to develop a survival deep learning model (DLM) to establish a critical ECG value and explore the associations with various CVD events. Methods: We trained a DLM with 451,950 12-lead resting ECGs obtained from 210,552 patients, for whom 23,592 events occurred. The internal validation set included 27,808 patients with one ECG for each patient. The external validations were performed in a community hospital with 33,047 patients and two transnational data sets with 233,647 and 1631 ECGs. We distinguished the cause of mortality and additionally investigated CVD-related outcomes, including new-onset acute myocardial infarction (AMI), stroke (STK), and heart failure (HF). Results: The DLM achieved C-indices of 0.858/0.836 in internal/external validation sets by using ECG over a 10-year period. The high-mortality-risk group identified by the proposed DLM presented a hazard ratio (HR) of 14.16 (95% confidence interval (CI): 11.33-17.70) compared to the low-risk group in the internal validation and presented a higher risk of cardiovascular (CV) mortality (HR: 18.50, 95% CI: 9.82-34.84), non-CV mortality (HR: 13.68, 95% CI: 10.76-17.38), AMI (HR: 4.01, 95% CI: 2.24-7.17), STK (HR: 2.15, 95% CI: 1.70-2.72), and HF (HR: 6.66, 95% CI: 4.54-9.77), which was consistent in an independent community hospital. The transnational validation also revealed HRs of 4.91 (95% CI: 2.63-9.16) and 2.29 (95% CI: 2.15-2.44) for all-cause mortality in the SaMi-Trop and Clinical Outcomes in Digital Electrocardiography 15% (CODE15) cohorts. Conclusions: The mortality risk by AI-enabled ECG may be applied in passive electronic-health-record-based CVD risk screening, which may identify more asymptomatic and unaware high-risk patients.

Profiling of miRNAs and their interfering targets in peripheral blood mononuclear cells from patients with chronic myeloid leukaemia.

Introduction: MicroRNAs may be implicated in the acquisition of drug resistance in chronic myeloid leukemia as they regulate the expression of not only BCR-ABL1 but also genes associated with the activation of drug transfer proteins or essential signaling pathways. Methods: To understand the impact of specifically expressed miRNAs in chronic myeloid leukemia and their target genes, we collected peripheral blood mononuclear cells (PBMC) from patients diagnosed with chronic myeloid leukemia (CML) and healthy donors to determine whole miRNA expression by small RNA sequencing and screened out 31 differentially expressed microRNAs (DE-miRNAs) with high expression. With the utilization of miRNA set enrichment analysis tools, we present here a comprehensive analysis of the relevance of DE-miRNAs to disease and biological function. Furthermore, the literature-based miRNA-target gene database was used to analyze the overall target genes of the DE-miRNAs and to define their associated biological responses. We further integrated DE-miRNA target genes to identify CML miRNA targeted gene signature singscore (CMTGSS) and used gene-set enrichment analysis (GSEA) to analyze the correlation between CMTGSS and Hallmark gene-sets in PBMC samples from clinical CML patients. Finally, the association of CMTGSS stratification with multiple CML cell lineage gene sets was validated in PBMC samples from CML patients using GSEA. Results: Although individual miRNAs have been reported to have varying degrees of impact on CML, overall, our results show that abnormally upregulated miRNAs are associated with apoptosis and aberrantly downregulated miRNAs are associated with cell cycle. The clinical database shows that our defined DE-miRNAs are associated with the prognosis of CML patients. CMTGSS-based stratification analysis presented a tendency for miRNAs to affect cell differentiation in the blood microenvironment. Conclusion: Collectively, this study defined differentially expressed miRNAs by miRNA sequencing from clinical samples and comprehensively analyzed the biological functions of the differential miRNAs in association with the target genes. The analysis of the enrichment of specific myeloid differentiated cells and immune cells also suggests the magnitude and potential targets of differentially expressed miRNAs in the clinical setting. It helps us to make links between the different results obtained from the multi-faceted studies to provide more potential research directions.

Carbohydrate Antigen 19-9 Response to Initial Adjuvant Chemotherapy Predicts Survival and Failure Pattern of Resected Pancreatic Adenocarcinoma but Not Which Patients Are Suited for Additional Adjuvant Chemoradiation Therapy: From a Prospective Randomized Study.

PURPOSE: The predictive value of carbohydrate antigen 19-9 (CA19-9) for adjuvant chemo(radiation) therapy of resected pancreatic adenocarcinoma (PDAC) is undefined. METHODS AND MATERIALS: We analyzed CA19-9 levels in patients with resected PDAC in a prospective randomized trial of adjuvant chemotherapy with or without additional chemoradiation therapy (CRT). Patients with postoperative CA19-9 ≤92.5 U/mL and serum bilirubin ≤2 mg/dL were randomized to 2 arms: patients in 1 arm received 6 cycles of gemcitabine, whereas those in the other received 3 cycles of gemcitabine followed by CRT and another 3 cycles of gemcitabine. Serum CA19-9 was measured every 12 weeks. Those who had CA19-9 levels always <3 U/mL were excluded from the exploratory analysis. RESULTS: One hundred forty-seven patients were enrolled in this randomized trial. Twenty-two patients with CA19-9 levels always ≤3 U/mL were excluded from the analysis. For the 125 participants, median overall survival (OS) and recurrence-free survival were 23.1 and 12.1 months, respectively, with no significant differences between the study arms. Postresection CA19-9 levels and, to a lesser extent, CA19-9 change predicted OS (P = .040 and .077, respectively). For the 89 patients who completed the initial 3 cycles of adjuvant gemcitabine, the CA19-9 response was significantly correlated with initial failure over the distant site (P = .023) and OS (P = .0022). Despite a trend of less initial failure over the locoregional area (P = .031), neither postoperative CA19-9 level nor CA19-9 response helped to select patients who might have a survival benefit from additional adjuvant CRT. CONCLUSIONS: CA19-9 response to initial adjuvant gemcitabine predicts survival and distant failure of PDAC after resection; however, it cannot select patients suited for additional adjuvant CRT. Monitoring CA19-9 levels during adjuvant therapy for postoperative patients with PDAC may guide therapeutic decisions to prevent distant failure.

Cancer-Associated Thrombosis: A Taiwanese Perspective on Therapeutic Options with Focus on Non-Vitamin K Antagonist Oral Anticoagulants.

Cancer-associated thrombosis (CAT) is a common complication of malignancies. Patients with CAT are at risk of venous thromboembolism recurrence, but also at risk of bleeding while anticoagulated. Taiwanese patients are perceived to have a lower incidence of CAT, likely leading to false reassurance for Taiwanese patients with cancer. Because of this, oncologists and cardiologists from multiple medical institutions in Taiwan have set forth to provide clinical consensus guidelines on the management of CAT, based on local clinical practices and guided by predominant international clinical practice guidelines. This paper aims to describe the current disease burden of cancer-associated venous thromboembolism in Taiwanese cancer patients, and discusses the unmet needs and gaps in the management of this medical complication. It also outlines diagnostic and management strategies relevant to the different treatment options available, such as non-vitamin K antagonist oral anticoagulants.

Management of cancer-related fatigue in Taiwan: an evidence-based consensus for screening, assessment and treatment.

BACKGROUND: Cancer-related fatigue is one of the most common and persistent issues experienced by cancer patients. Cancer-related fatigue is a distinct form of fatigue that is subjective, long-lasting and unalleviated by rest or sleep. Studies have shown that almost all cancer patients experience severe fatigue that disrupts the quality of life and physical function, but cancer-related fatigue remains under-addressed in clinical care, and only about half of all patients receive treatment. METHODS: To increase the awareness of cancer-related fatigue and improve current management, the Taiwan Society of Cancer Palliative Medicine and the Taiwan Oncology Nursing Society convened a consensus committee to develop recommendations for the screening, assessment and treatment of cancer-related fatigue. RESULTS: Thirteen consensus recommendations were subsequently developed based on the best available evidence and the clinical experience of committee members. CONCLUSIONS: These recommendations are expected to facilitate the standardization of cancer-related fatigue management across Taiwan and may also serve as a reference for other clinicians.

Artificial intelligence-enabled electrocardiogram screens low left ventricular ejection fraction with a degree of confidence.

Background: Artificial intelligence-enabled electrocardiogram has become a substitute tool for echocardiography in left ventricular ejection fraction estimation. However, the direct use of artificial intelligence-enabled electrocardiogram may be not trustable due to the uncertainty of the prediction. Objective: The study aimed to establish an artificial intelligence-enabled electrocardiogram with a degree of confidence to identify left ventricular dysfunction. Methods: The study collected 76,081 and 11,771 electrocardiograms from an academic medical center and a community hospital to establish and validate the deep learning model, respectively. The proposed deep learning model provided the point estimation of the actual ejection fraction and its standard deviation derived from the maximum probability density function of a normal distribution. The primary analysis focused on the accuracy of identifying patients with left ventricular dysfunction (ejection fraction ≤ 40%). Since the standard deviation was an uncertainty indicator in a normal distribution, we used it as a degree of confidence in the artificial intelligence-enabled electrocardiogram. We further explored the clinical application of estimated standard deviation and followed up on the new-onset left ventricular dysfunction in patients with initially normal ejection fraction. Results: The area under receiver operating characteristic curves (AUC) of detecting left ventricular dysfunction were 0.9549 and 0.9365 in internal and external validation sets. After excluding the cases with a lower degree of confidence, the artificial intelligence-enabled electrocardiogram performed better in the remaining cases in internal (AUC = 0.9759) and external (AUC = 0.9653) validation sets. For the application of future left ventricular dysfunction risk stratification in patients with initially normal ejection fraction, a 4.57-fold risk of future left ventricular dysfunction when the artificial intelligence-enabled electrocardiogram is positive in the internal validation set. The hazard ratio was increased to 8.67 after excluding the cases with a lower degree of confidence. This trend was also validated in the external validation set. Conclusion: The deep learning model with a degree of confidence can provide advanced improvements in identifying left ventricular dysfunction and serve as a decision support and management-guided screening tool for prognosis.

Return to Work and Mortality in Breast Cancer Survivors: A 11-Year Longitudinal Study.

Breast cancer is the most commonly occurring cancer in women, and it is a major cause of cancer death around the world. With the development of diagnostic methods and improvements in treatment methods, the incidence rate of breast cancer and the number of breast cancer survivors continue to simultaneously increase. We used national registry database to analyze the features that affect employment and return to work among breast cancer survivors. A total of 23,220 employees, who were newly diagnosed with breast cancer were recruited based on the Labor Insurance Database (LID), the Taiwan Cancer Registry (TCR), and National Health Insurance Research Database (NHIRD) during the period 2004-2015. The correlations between return to work (RTW) and independent confounding factors were examined using Cox proportional hazards model. Survival probability was analyzed using the Kaplan-Meir method. After adjusting for confounding variables, cancer stage, chemotherapy and higher income were significantly negatively correlated with RTW. Among breast cancer survivors, RTW was found to be related to a lower risk of all-cause mortality in both the unadjusted and fully adjusted model. Patients who had RTW exhibited better survival in all stages. Work-, disease- and treatment-related factors influenced RTW among employees with breast cancer. RTW was associated with better breast cancer survival. Our study demonstrates the impact of RTW and the associated factors on breast cancer survivorship.

Large-scale transcriptomic analysis of coding and non-coding pathological biomarkers, associated with the tumor immune microenvironment of thyroid cancer and potential target therapy exploration.

Papillary thyroid carcinoma (PTC) is the most prevalent endocrine malignancy with a steadily increasing global incidence in recent decades. The pathogenesis of PTC is poorly understood, and the present diagnostic protocols are deficient. Thus, identifying novel prognostic biomarkers to improve our understanding of the mechanisms of pathogenesis, diagnosis, and designing therapeutic strategies for PTC is crucial. In this study, we integrated 27 PTC transcriptomic datasets and identified overlapping differentially expressed genes (DEGs) and differentially expressed microRNAs, collectively known as thyroid tumor-enriched proteins (TTEPs), and TTEmiRs, respectively. Our integrated bioinformatics analysis revealed that TTEPs were associated with tumor stages, poor surgical outcomes, distant metastasis, and worse prognoses in PTC cohorts. In addition, TTEPs were found to be associated with tumor immune infiltrating cells and immunosuppressive phenotypes of PTC. Enrichment analysis suggested the association of TTEPs with epithelial-to-mesenchymal transition (EMT), cell-matrix remodeling, and transcriptional dysregulation, while the TTEmiRs (miR-146b-5p and miR-21-5p) were associated with the modulation of the immune response, EMT, migration, cellular proliferation, and stemness. Molecular docking simulations were performed to evaluate binding affinities between TTEPs and antrocinnamomin, antcin, and antrocin, the bioactive compounds from one of the most reputable Taiwan indigenous medicinal plants (Antrodia camphorata). Our results revealed that antcin exhibited higher binding efficacies toward FN1, ETV5, and NRCAM, whereas antrocin demonstrated the least. Among the targets, fibronectin (FN1) demonstrated high ligandability potential for the compounds whereas NRCAM demonstrated the least. Collectively, our results hinted at the potential of antcin for targeting TTEPs. In conclusion, this comprehensive bioinformatics analysis strongly suggested that TTEPs and TTEmiRs could be used as potential diagnostic biomarker signatures and be exploited as potential targets for therapeutics development.

Artificial Intelligence-Enabled Electrocardiography Detects Hypoalbuminemia and Identifies the Mechanism of Hepatorenal and Cardiovascular Events.

Background: Albumin, an important component of fluid balance, is associated with kidney, liver, nutritional, and cardiovascular diseases (CVD) and is measured by blood tests. Since fluid balance is associated with electrocardiography (ECG) changes, we established a deep learning model (DLM) to estimate albumin via ECG. Objective: This study aimed to develop a DLM to estimate albumin via ECG and explored its contribution to future complications. Materials and Methods: A DLM was trained for estimating ECG-based albumin (ECG-Alb) using 155,078 ECGs corresponding to albumin from 79,111 patients, and another independent 13,335 patients from an academic medical center and 11,370 patients from a community hospital were used for internal and external validation. The primary analysis focused on distinguishing patients with mild to severe hypoalbuminemia, and the secondary analysis aimed to provide additional prognostic value from ECG-Alb for future complications, which included mortality, new-onset hypoalbuminemia, chronic kidney disease (CKD), new onset hepatitis, CVD mortality, new-onset acute myocardial infarction (AMI), new-onset stroke (STK), new-onset coronary artery disease (CAD), new-onset heart failure (HF), and new-onset atrial fibrillation (Afib). Results: The AUC to identify hypoalbuminemia was 0.8771 with a sensitivity of 56.0% and a specificity of 90.7% in the internal validation set, and the Pearson correlation coefficient was 0.69 in the continuous analysis. The most important ECG features contributing to ECG-Alb were ordered in terms of heart rate, corrected QT interval, T wave axis, sinus rhythm, P wave axis, etc. The group with severely low ECG-Alb had a higher risk of all-cause mortality [hazard ratio (HR): 2.45, 95% CI: 1.81-3.33] and the other hepatorenal and cardiovascular events in the internal validation set. The external validation set yielded similar results. Conclusion: Hypoalbuminemia and its complications can be predicted using ECG-Alb as a novel biomarker, which may be a non-invasive tool to warn asymptomatic patients.

Modified-Dose Pembrolizumab and Prognostic Outcomes among Non-Small Cell Lung Cancer Patients: A Chart Review Study.

The modified dose (MD) regimen of pembrolizumab (2 mg/kg or 100 mg every 3 weeks) is an alternative option to reduce the financial burden resulting from the extremely high cost of the standard dose (SD) regimen (200 mg every 3 weeks). However, the clinical effectiveness and prognostic outcomes have not been fully elucidated in real-word clinical practice. Sixty-four consecutive patients in Taiwan receiving pembrolizumab for advanced NSCLC between 2018 and 2020 were recruited in this study. Comparisons of overall survival (OS) and progression-free survival (PFS) were performed using Kaplan−Meier survival curves. Additionally, 12 predictors, including pembrolizumab regimen, dose, neutrophil-to-lymphocyte ratio (NLR), age, sex, histopathology, smoking history, ECOG PS, EGFR mutation, PD-L1 expression, distant metastases and treatment line, were analyzed in multivariable Cox models for predicting OS and PFS. The results showed that the MD group and the SD group had similar OS and PFS, especially in patients beyond first-line treatment or with a pretreatment NLR < 5. The NLR was the only independent factor associated with both OS (adjusted HR = 0.052; p = 0.010) and PFS (adjusted HR = 0.259; p = 0.021). The results of this study assure the clinical effectiveness of MD pembrolizumab and suggest that the pretreatment NLR could highlight patients who may benefit from MD pembrolizumab.

Artificial Intelligence-Enabled Electrocardiogram Predicted Left Ventricle Diameter as an Independent Risk Factor of Long-Term Cardiovascular Outcome in Patients With Normal Ejection Fraction.

Background: Heart failure (HF) is a global disease with increasing prevalence in an aging society. However, the survival rate is poor despite the patient receiving standard treatment. Early identification of patients with a high risk of HF is important but challenging. Left ventricular end-diastolic diameter (LV-D) increase was an independent risk factor of HF and adverse cardiovascular (CV) outcomes. In this study, we aimed to develop an artificial intelligence (AI) enabled electrocardiogram (ECG) system to detect LV-D increase early. Objective: We developed a deep learning model (DLM) to predict left ventricular end-diastolic and end-systolic diameter (LV-D and LV-S) with internal and external validations and investigated the relationship between ECG-LV-D and echocardiographic LV-D and explored the contributions of ECG-LV-D on future CV outcomes. Methods: Electrocardiograms and corresponding echocardiography data within 7 days were collected and paired for DLM training with 99,692 ECGs in the development set and 20,197 ECGs in the tuning set. The other 7,551 and 11,644 ECGs were collected from two different hospitals to validate the DLM performance in internal and external validation sets. We analyzed the association and prediction ability of ECG-LVD for CV outcomes, including left ventricular (LV) dysfunction, CV mortality, acute myocardial infarction (AMI), and coronary artery disease (CAD). Results: The mean absolute errors (MAE) of ECG-LV-D were 5.25/5.29, and the area under the receiver operating characteristic (ROC) curves (AUCs) were 0.8297/0.8072 and 0.9295/0.9148 for the detection of mild (56 ≦ LV-D < 65 mm) and severe (LV-D ≧ 65 mm) LV-D dilation in internal/external validation sets, respectively. Patients with normal ejection fraction (EF) who were identified as high ECHO-LV-D had the higher hazard ratios (HRs) of developing new onset LV dysfunction [HR: 2.34, 95% conference interval (CI): 1.78-3.08], CV mortality (HR 2.30, 95% CI 1.05-5.05), new-onset AMI (HR 2.12, 95% CI 1.36-3.29), and CAD (HR 1.59, 95% CI 1.26-2.00) in the internal validation set. In addition, the ECG-LV-D presents a 1.88-fold risk (95% CI 1.47-2.39) on new-onset LV dysfunction in the external validation set. Conclusion: The ECG-LV-D not only identifies high-risk patients with normal EF but also serves as an independent risk factor of long-term CV outcomes.

Phase I Targeted Combination Trial of Sorafenib and GW5074 in Patients with Advanced Refractory Solid Tumors.

BACKGROUND: Combination therapy with the administration of GW5074 and sorafenib significantly induced necrotic death in various cancer cells in vivo, as well as prolonging the survival of an animal disease model due to significant suppression of the primary and metastatic lesions. We sought to determine the safety, tolerability, pharmacokinetics, and anti-tumor activity of this co-administration therapy in patients with refractory advanced solid cancers. METHODS: Twelve patients were enrolled. Eligible subjects received different dosages of GW5074 in one of the three dose cohorts (Cohort 1: 750 mg daily, Cohort 2: 1500 mg daily, Cohort 3: 750 mg twice daily) plus 200 mg of sorafenib daily to determine the maximum tolerated dose (MTD) and dose limiting toxicities (DLT) at phase 1. Furthermore, the expression level of phosphorylated DAPKS308 in primary tumor, metastatic tumor, and circulating tumor cells (CTC) were evaluated to investigate the relationship between biomarker and the efficacy profile. RESULTS: Among the 12 enrolled patients in this phase 1 trial, most adverse effects (AE) were grade 1, with two being grade 3. The most frequent AE of all grades were weight loss and hypertension, occurring in 16.7% of participants. Eight patients (66.7%) had the disease controlled by receiving co-administration therapy of GW5074 and sorafenib. GW5074 was found to have poor absorption, as increasing the dosage did not result in a significant increase in the bioavailability of GW5074 in subjects. Furthermore, the expression level of phosphorylated DAPKS308 in tumor and CTCs were correlated with the disease control rate (DCR) and duration of response (DOR). CONCLUSIONS: Co-administration therapy of GW5074 and sorafenib demonstrated a favorable safety profile and showed anti-tumor activity in a variety of tumor types. However, the solubility of GW5074 is not satisfactory. A future phase 2a trial will be carried out using the new salted form that has been proven to be more effective.

Artificial Intelligence-Enabled Electrocardiogram Estimates Left Atrium Enlargement as a Predictor of Future Cardiovascular Disease.

BACKGROUND: Left atrium enlargement (LAE) can be used as a predictor of future cardiovascular diseases, including hypertension (HTN) and atrial fibrillation (Afib). Typical electrocardiogram (ECG) changes have been reported in patients with LAE. This study developed a deep learning model (DLM)-enabled ECG system to identify patients with LAE. METHOD: Patients who had ECG records with corresponding echocardiography (ECHO) were included. There were 101,077 ECGs, 20,510 ECGs, 7611 ECGs, and 11,753 ECGs in the development, tuning, internal validation, and external validation sets, respectively. We evaluated the performance of a DLM-enabled ECG for diagnosing LAE and explored the prognostic value of ECG-LAE for new-onset HTN, new-onset stroke (STK), new-onset mitral regurgitation (MR), and new-onset Afib. RESULTS: The DLM-enabled ECG achieved AUCs of 0.8127/0.8176 for diagnosing mild LAE, 0.8587/0.8688 for diagnosing moderate LAE, and 0.8899/0.8990 for diagnosing severe LAE in the internal/external validation sets. Notably, ECG-LAE had higher prognostic value compared to ECHO-LAE, which had C-indices of 0.711/0.714 compared to 0.695/0.692 for new-onset HTN, 0.676/0.688 compared to 0.663/0.677 for new-onset STK, 0.696/0.695 compared to 0.676/0.673 for new-onset MR, and 0.800/0.806 compared to 0.786/0.760 for new-onset Afib in internal/external validation sets, respectively. CONCLUSIONS: A DLM-enabled ECG could be considered as a LAE screening tool and provide better prognostic information for related cardiovascular diseases.

Identification of DPP4/CTNNB1/MET as a Theranostic Signature of Thyroid Cancer and Evaluation of the Therapeutic Potential of Sitagliptin.

In recent years, the incidence of thyroid cancer has been increasing globally, with papillary thyroid cancer (PTCa) being the most prevalent pathological type, accounting for approximately 80% of all cases. Although PTCa has been regarded to be slow growing and has a good prognosis, in some cases, PTCa can be aggressive and progress despite surgery and radioactive iodine treatment. In addition, most cancer treatment drugs have been shown to be cytotoxic and nonspecific to cancer cells, as they also affect normal cells and consequently cause harm to the body. Therefore, searching for new targets and therapies is required. Herein, we explored a bioinformatics analysis to identify important theranostic markers for THCA. Interestingly, we identified that the DPP4/CTNNB1/MET gene signature was overexpressed in PTCa, which, according to our analysis, is associated with immuno-invasive phenotypes, cancer progression, metastasis, resistance, and unfavorable clinical outcomes of thyroid cancer cohorts. Since most cancer drugs were shown to exhibit cytotoxicity and to be nonspecific, herein, we evaluated the anticancer effects of the antidiabetic drug sitagliptin, which was recently shown to possess anticancer activities, and is well tolerated and effective. Interestingly, our in silico molecular docking results exhibited putative binding affinities of sitagliptin with DPP4/CTNNB1/MET signatures, even higher than standard inhibitors of these genes. This suggests that sitagliptin is a potential THCA therapeutic, worthy of further investigation both in vitro and in vivo and in clinical settings.

The association between metabolic risk factors, nonalcoholic fatty liver disease, and the incidence of liver cancer: a nationwide population-based cohort study.

BACKGROUND AND AIMS: Liver cancer is a detrimental complication in patients with chronic viral hepatitis and alcoholic or nonalcoholic fatty liver disease (NAFLD). However, metabolic risk factors underlying NAFLD usually cause substantial differences in their clinical outcomes. Recently, several studies have used a novel definition of metabolic dysfunction-associated fatty liver disease (MAFLD) to reassess patients with NAFLD and pointed out the importance of metabolic risk factors. Since patients with NAFLD, MAFLD, or metabolic syndrome (MetS) have different burden of metabolic risk factors, it is crucial to decipher the risk of developing hepatic complications in these populations. METHODS: Through a longitudinal nationwide cohort study, the risk of liver cancer was investigated in patients with MetS alone, NAFLD alone, overlap NAFLD/MAFLD, and coexisting MetS and NAFLD. The general characteristics, comorbidities, and incidence of liver cancer were also compared. RESULTS: Intriguingly, patients diagnosed with MetS alone did not have a significant risk of developing HCC compared to control individuals, while patients with NAFLD alone, NAFLD/MAFLD, and coexisting NAFLD and MetS exhibited 6.08-, 5.81-, and 15.33-fold risks of developing HCC, respectively. Apart from metabolic risk factors, renal function status and liver cirrhosis were the independent risk factors for the development of HCC among these groups. CONCLUSION: Our data emphasize that metabolic dysfunction has a significant impact on hepatocarcinogenesis in patients with NAFLD. Moreover, coexisting multiple metabolic risk factors would dampen the risk of developing HCC in patients with NAFLD. Closely tracing HCC formation through laboratory examination or imaging is crucial in these patients.