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Intratumor heterogeneity (ITH) is a biomarker of tumor progression, metastasis, and immune evasion. Previous studies evaluated ITH mostly based on DNA alterations. Here, we developed a new algorithm (DEPTH) for quantifying ITH based on mRNA alterations in the tumor. DEPTH scores displayed significant correlations with ITH-associated features (genomic instability, tumor advancement, unfavorable prognosis, immunosuppression, and drug response). Compared to DNA-based ITH scores (EXPANDS, PhyloWGS, MATH, and ABSOLUTE), DEPTH scores had stronger correlations with antitumor immune signatures, cell proliferation, stemness, tumor advancement, survival prognosis, and drug response. Compared to two other mRNA-based ITH scores (tITH and sITH), DEPTH scores showed stronger and more consistent associations with genomic instability, unfavorable tumor phenotypes and clinical features, and drug response. We further validated the reliability and robustness of DEPTH in 50 other datasets. In conclusion, DEPTH may provide new insights into tumor biology and potential clinical implications for cancer prognosis and treatment.

Malignant mesothelioma (MM) is an aggressive cancer primarily diagnosed on the basis of histological criteria 1 . The 2015 World Health Organization classification subdivides mesothelioma tumors into three histological types: epithelioid, biphasic and sarcomatoid MM. MM is a highly complex and heterogeneous disease, rendering its diagnosis and histological typing difficult and leading to suboptimal patient care and decisions regarding treatment modalities 2 . Here we have developed a new approach-based on deep convolutional neural networks-called MesoNet to accurately predict the overall survival of mesothelioma patients from whole-slide digitized images, without any pathologist-provided locally annotated regions. We validated MesoNet on both an internal validation cohort from the French MESOBANK and an independent cohort from The Cancer Genome Atlas (TCGA). We also demonstrated that the model was more accurate in predicting patient survival than using current pathology practices. Furthermore, unlike classical black-box deep learning methods, MesoNet identified regions contributing to patient outcome prediction. Strikingly, we found that these regions are mainly located in the stroma and are histological features associated with inflammation, cellular diversity and vacuolization. These findings suggest that deep learning models can identify new features predictive of patient survival and potentially lead to new biomarker discoveries.

Background: According to long-term follow-up data of malignant tumor patients, assessing treatment effects requires careful consideration of competing risks. The commonly used cause-specific hazard ratio (CHR) and sub-distribution hazard ratio (SHR) are relative indicators and may present challenges in terms of proportional hazards assumption and clinical interpretation. Recently, the restricted mean time lost (RMTL) has been recommended as a supplementary measure for better clinical interpretation. Moreover, for observational study data in epidemiological and clinical settings, due to the influence of confounding factors, covariate adjustment is crucial for determining the causal effect of treatment. Methods: We construct an RMTL estimator after adjusting for covariates based on the inverse probability weighting method, and derive the variance to construct interval estimates based on the large sample properties. We use simulation studies to study the statistical performance of this estimator in various scenarios. In addition, we further consider the changes in treatment effects over time, constructing a dynamic RMTL difference curve and corresponding confidence bands for the curve. Results: The simulation results demonstrate that the adjusted RMTL estimator exhibits smaller biases compared with unadjusted RMTL and provides robust interval estimates in all scenarios. This method was applied to a real-world cervical cancer patient data, revealing improvements in the prognosis of patients with small cell carcinoma of the cervix. The results showed that the protective effect of surgery was significant only in the first 20 months, but the long-term effect was not obvious. Radiotherapy significantly improved patient outcomes during the follow-up period from 17 to 57 months, while radiotherapy combined with chemotherapy significantly improved patient outcomes throughout the entire period. Conclusions: We propose the approach that is easy to interpret and implement for assessing treatment effects in observational competing risk data. [ABSTRACT FROM AUTHOR]

G0 arrest (G0A) is widely recognized as a crucial factor contributing to tumor relapse. The role of genes related to G0A in lung adenocarcinoma (LUAD) was unclear. This study aimed to develop a gene signature based on for LUAD patients and investigate its relationship with prognosis, tumor immune microenvironment, and therapeutic response in LUAD. We use the TCGA-LUAD database as the discovery cohort, focusing specifically on genes associated with the G0A pathway. We used various statistical methods, including Cox and lasso regression, to develop the model. We validated the model using bulk transcriptome and single-cell transcriptome datasets (GSE50081, GSE72094, GSE127465, GSE131907 and EMTAB6149). We used GSEA enrichment and the CIBERSORT algorithm to gain insight into the annotation of the signaling pathway and the characterization of the tumor microenvironment. We evaluated the response to immunotherapy, chemotherapy, and targeted therapy in these patients. The expression of six genes was validated in cell lines by quantitative real-time PCR (qRT-PCR). Our study successfully established a six-gene signature (CHCHD4, DUT, LARP1, PTTG1IP, RBM14, and WBP11) that demonstrated significant predictive power for overall survival in patients with LUAD. It demonstrated independent prognostic value in LUAD. To enhance clinical applicability, we developed a nomogram based on this gene signature, which showed high reliability in predicting patient outcomes. Furthermore, we observed a significant association between G0A-related risk and tumor microenvironment as well as drug susceptibility, highlighting the potential of the gene signature to guide personalized treatment strategies. The expression of six genes were significantly upregulated in the LUAD cell lines. This signature holds the potential to contribute to improved prognostic prediction and new personalized therapies specifically for LUAD patients. [ABSTRACT FROM AUTHOR]

Objective: Colon cancer is associated with multiple levels of molecular heterogeneity. RNA processing converts primary transcriptional RNA to mature RNA, which drives tumourigenesis and its maintenance. The characterisation of RNA processing genes in colon cancer urgently needs to be elucidated. Methods: In this study, we obtained 1033 relevant samples from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases to explore the heterogeneity of RNA processing phenotypes in colon cancer. Firstly, Unsupervised hierarchical cluster analysis detected 4 subtypes with specific clinical outcomes and biological features via analysis of 485 RNA processing genes. Next, we adopted the least absolute shrinkage and selection operator (LASSO) as well as Cox regression model with penalty to characterise RNA processing-related prognostic features. Results: An RNA processing-related prognostic risk model based on 10 genes including FXR1, MFAP1, RBM17, SAGE1, SNRPA1, SRRM4, ADAD1, DDX52, ERI1, and EXOSC7 was identified finally. A composite prognostic nomogram was constructed by combining this feature with the remaining clinical variables including TNM, age, sex, and stage. Genetic variation, pathway activation, and immune heterogeneity with risk signatures were also analysed via bioinformatics methods. The outcomes indicated that the high-risk subgroup was associated with higher genomic instability, increased proliferative and cycle characteristics, decreased tumour killer CD8+ T cells and poorer clinical prognosis than the low-risk group. Conclusion: This prognostic classifier based on RNA-edited genes facilitates stratification of colon cancer into specific subgroups according to TNM and clinical outcomes, genetic variation, pathway activation, and immune heterogeneity. It can be used for diagnosis, classification and targeted treatment strategies comparable to current standards in precision medicine. It provides a rationale for elucidation of the role of RNA editing genes and their clinical significance in colon cancer as prognostic markers. [ABSTRACT FROM AUTHOR]

Background: Anemia represents a well-established risk factor for patients diagnosed with gastric cancer, and is often associated with an unfavorable prognosis. In this context, the timely prediction of distant metastasis risk in patients with anemic gastric cancer assumes paramount importance. Methods: Information of gastric cancer patients complicated with preoperative anemia in the First Affiliated Hospital of Sun Yat-sen University was collected. The cohort from the First Affiliated Hospital of Guangxi Medical University was used as an external validation set. A Nomogram was established based on the risk factors screened by univariate and multivariate logistic regression analyses. Results: A total of 848 gastric cancer patients with preoperative anemia were enrolled. Pyloric obstruction, carcinoma antigen 125, T stage, N stage, tumor size, and preoperative weight loss were independent predictors of distant metastasis in gastric cancer patients with anemia (p < 0.05), based on which a nomogram was constructed. The accuracy, reliability and clinical value of the nomogram were evaluated by concordance index, receiver operating characteristic curve, decision curve analysis, calibration curve and showed good stability and clinical predictive value. Conclusions: Preoperative anemic gastric cancer patients, complicated with pyloric obstruction, elevated CA125, advanced T and N stage, larger tumor size, and preoperative weight loss, should be paid more attention to distant metastasis. [ABSTRACT FROM AUTHOR]

Background: The effect of whole-brain radiation therapy (WBRT) plus simultaneous integrated boost (SIB) in brain metastasis from breast cancers has not been demonstrated. Method: In this single-center retrospective study, we reviewed consecutive breast cancer patients who developed brain metastasis and were treated with hypofractionated radiation therapy plus WBRT using intensity-modulated radiation therapy (IMRT)-SIB approaches. We analyzed clinical outcomes, prognostic factors and patterns of treatment failure. Result: A total of 27 patients were eligible for analysis. Four (14.8%) patients achieved clinical complete response and 14 (51.9%) had partial response of brain lesions. The other nine patients were not evaluated for brain tumor response. The median brain progression-free survival was 8.60 (95% CI [6.43–13.33]) months and the median overall survival was 16.8 (95% CI [13.3–27.7]) months. Three patients had in-field failure, five had out-field failure and two had in-field and out-field failure. Conclusion: WBRT plus SIB led to improved tumor control and clinical outcome in breast cancer patients with brain metastasis. [ABSTRACT FROM AUTHOR]

Background: In recent years, the incidence of adenocarcinoma of the esophagogastric junction (AEG) has been rapidly increasing globally. Despite advances in the diagnosis and treatment of AEG, the overall prognosis for AEG patients remains concerning. Therefore, analyzing prognostic factors for AEG patients of Siewert type II and constructing a prognostic model for AEG patients is important. Methods: Data of primary Siewert type II AEG patients from the SEER database from 2004 to 2015 were obtained and randomly divided into training and internal validation cohort. Additionally, data of primary Siewert type II AEG patients from the China Medical University Dandong Central Hospital from 2012 to 2018 were collected for external validation. Each variable in the training set underwent univariate Cox analysis, and variables with statistical significance (p < 0.05) were added to the LASSO equation for feature selection. Multivariate Cox analysis was then conducted to determine the independent predictive factors. A nomogram for predicting overall survival (OS) was developed, and its performance was evaluated using ROC curves, calibration curves, and decision curves. NRI and IDI were calculated to assess the improvement of the new prediction model relative to TNM staging. Patients were stratified into high-risk and low-risk groups based on the risk scores from the nomogram. Results: Age, Differentiation grade, T stage, M stage, and LODDS (Log Odds of Positive Lymph Nodes)were independent prognostic factors for OS. The AUC values of the ROC curves for the nomogram in the training set, internal validation set, and external validation set were all greater than 0.7 and higher than those of TNM staging alone. Calibration curves indicated consistency between the predicted and actual outcomes. Decision curve analysis showed moderate net benefit. The NRI and IDI values of the nomogram were greater than 0 in the training, internal validation, and external validation sets. Risk stratification based on the nomogram’s risk score demonstrated significant differences in survival rates between the high-risk and low-risk groups. Conclusion: We developed and validated a nomogram for predicting overall survival (OS) in patients with Siewert type II AEG, which assists clinicians in accurately predicting mortality risk and recommending personalized treatment strategies. [ABSTRACT FROM AUTHOR]

Background: Several clinical prognostic models for diffuse large B‐cell lymphoma (DLBCL) have been proposed, including the most commonly used International Prognostic Index (IPI), the National Comprehensive Cancer Network IPI (NCCN‐IPI), and models incorporating beta‐2 microglobulin (β2M). However, the role of β2M in DLBCL patients is not fully understood. Methods: We identified 6075 patients with newly diagnosed DLBCL treated with immunochemotherapy registered in the Danish Lymphoma Registry. Results: A total of 3232 patients had data available to calculate risk scores from each of the nine considered risk models for DLBCL, including a model developed from our population. Three of four models with β2M and NCCN‐IPI performed better than the International Prognostic Indexes (IPI, age‐adjusted IPI, and revised IPI). Five‐year overall survival for high‐ and low‐risk patients were 43.6% and 86.4% for IPI and 34.9% and 96.2% for NCCN‐IPI. In univariate analysis, higher levels of β2M were associated with inferior survival, higher tumor burden (advanced clinical stage and bulky disease), previous malignancy and increased age, and creatinine levels. Furthermore, we developed a model (β2M‐NCCN‐IPI) by adding β2M to NCCN‐IPI (c‐index 0.708) with improved discriminatory ability compared to NCCN‐IPI (c‐index 0.698, p < 0.05) and 5‐year OS of 33.1%, 56.2%, 82.4%, and 96.4% in the high, high‐intermediate, low‐intermediate and low‐risk group, respectively. Conclusion: International Prognostic Indices, except for NCCN‐IPI, fail to accurately discriminate risk groups in the rituximab era. β2M, a readily available marker, could improve the discriminatory performance of NCCN‐IPI and should be re‐evaluated in the development setting of future models for DLBCL. [ABSTRACT FROM AUTHOR]

Background: Mucinous colorectal adenocarcinoma (MCA) is a distinct subtype of colorectal cancer (CRC) with the most aggressive pattern, but effective treatment of MCA remains a challenge due to its vague pathological characteristics. An in‐depth understanding of transcriptional dynamics at the cellular level is critical for developing specialised MCA treatment strategies. Methods: We integrated single‐cell RNA sequencing and spatial transcriptomics data to systematically profile the MCA tumor microenvironment (TME), particularly the interactome of stromal and immune cells. In addition, a three‐dimensional bioprinting technique, canonical ex vivo co‐culture system, and immunofluorescence staining were further applied to validate the cellular communication networks within the TME. Results: This study identified the crucial intercellular interactions that engaged in MCA pathogenesis. We found the increased infiltration of FGF7+/THBS1+ myofibroblasts in MCA tissues with decreased expression of genes associated with leukocyte‐mediated immunity and T cell activation, suggesting a crucial role of these cells in regulating the immunosuppressive TME. In addition, MS4A4A+ macrophages that exhibit M2‐phenotype were enriched in the tumoral niche and high expression of MS4A4A+ was associated with poor prognosis in the cohort data. The ligand‐receptor‐based intercellular communication analysis revealed the tight interaction of MUC1+ malignant cells and ZEB1+ endothelial cells, providing mechanistic information for MCA angiogenesis and molecular targets for subsequent translational applications. Conclusions: Our study provides novel insights into communications among tumour cells with stromal and immune cells that are significantly enriched in the TME during MCA progression, presenting potential prognostic biomarkers and therapeutic strategies for MCA. Key points: Tumour microenvironment profiling of MCA is developed.MUC1+ tumour cells interplay with FGF7+/THBS1+ myofibroblasts to promote MCA development.MS4A4A+ macrophages exhibit M2 phenotype in MCA.ZEB1+ endotheliocytes engage in EndMT process in MCA. [ABSTRACT FROM AUTHOR]

Background: T cell exhaustion in the tumor microenvironment has been demonstrated as a substantial contributor to tumor immunosuppression and progression. However, the correlation between T cell exhaustion and osteosarcoma (OS) remains unclear. Methods: In our present study, single-cell RNA-seq data for OS from the GEO database was analysed to identify CD8+ T cells and discern CD8+ T cell subsets objectively. Subgroup differentiation trajectory was then used to pinpoint genes altered in response to T cell exhaustion. Subsequently, six machine learning algorithms were applied to develop a prognostic model linked with T cell exhaustion. This model was subsequently validated in the TARGETs and Meta cohorts. Finally, we examined disparities in immune cell infiltration, immune checkpoints, immune-related pathways, and the efficacy of immunotherapy between high and low TEX score groups. Results: The findings unveiled differential exhaustion in CD8+ T cells within the OS microenvironment. Three genes related to T cell exhaustion (RAD23A, SAC3D1, PSIP1) were identified and employed to formulate a T cell exhaustion model. This model exhibited robust predictive capabilities for OS prognosis, with patients in the low TEX score group demonstrating a more favorable prognosis, increased immune cell infiltration, and heightened responsiveness to treatment compared to those in the high TEX score group. Conclusion: In summary, our research elucidates the role of T cell exhaustion in the immunotherapy and progression of OS, the prognostic model constructed based on T cell exhaustion-related genes holds promise as a potential method for prognostication in the management and treatment of OS patients. [ABSTRACT FROM AUTHOR]

The intricate crosstalk of various cell death forms was recently implicated in cancers, laying a foundation for exploring the association between cell death and cancers. Recent evidence has demonstrated that biological networks outperform snapshot gene expression profiles at discovering promising biomarkers or heterogenous molecular subtypes across different cancer types. In order to investigate the behavioral patterns of cell death-related interaction perturbation in colorectal cancer (CRC), this study constructed the interaction-perturbation network with 11 cell death pathways and delineated four cell death network (CDN) derived heterogeneous subtypes (CDN1-4) with distinct molecular characteristics and clinical outcomes. Specifically, we identified a subtype (CDN4) endowed with high autophagy activity and the worst prognosis. Furthermore, AOC3 was identified as a potential autophagy-related biomarker, which demonstrated exceptional predictive performance for CDN4 and significant prognostic value. Overall, this study sheds light on the complex interplay of various cell death forms and reveals an autophagy-related gene AOC3 as a critical prognostic marker in CRC. In colorectal cancer, four cell death subtypes (CDN1-4) are identified, each with distinct traits and prognoses. [ABSTRACT FROM AUTHOR]

Background/Aim: Sarcopenia accompanied by systemic inflammation is associated with poor prognosis in patients with cancer. This study evaluated the prognostic significance of sarcopenia (myopenia and myosteatosis) and systemic inflammatory markers in older patients (aged =80 years) with resected biliary tract cancer. Patients and Methods: Patients who underwent resection for biliary tract cancer between July 2010 and January 2023 at the NHO Fukuyama Medical Center were retrospectively reviewed. Preoperative computed tomography measured myopenia and myosteatosis, using the psoas muscle index and modified intramuscular adipose tissue content. Associations between clinicopathological characteristics, inflammation-based prognostic scores, and overall survival were analyzed using Cox proportional hazards models. Results: Univariate analysis revealed low C-reactive protein-to-albumin ratio (<0.125), low prognostic nutritional index (<42), low modified intramuscular adipose tissue content, higher T-stage (T3-4), lymph node metastasis, and postoperative complications associated with worse overall survival in older patients (aged = 80 years) with resected biliary tract cancer (n=48). Multivariate analysis identified low prognostic nutritional index (<42) (p=0.007), low modified intramuscular adipose tissue content (p=0.015), higher Tstage (T3-4) (p<0.001), lymph node metastasis (p=0.001), and postoperative complications (p=0.017) as independent predictors of overall survival. Conclusion: Preoperative myosteatosis and low prognostic nutritional index are independent prognostic factors for overall survival in older patients (aged =80 years) with resected biliary tract cancer. These factors may be useful for risk stratification and clinical decision-making. Early interventions, such as nutritional support and physical exercise, may improve outcomes after resection of biliary tract cancer. [ABSTRACT FROM AUTHOR]

Motivation Identification of genomic, molecular and clinical markers prognostic of patient survival is important for developing personalized disease prevention, diagnostic and treatment approaches. Modern omics technologies have made it possible to investigate the prognostic impact of markers at multiple molecular levels, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, and how these potential risk factors complement clinical characterization of patient outcomes for survival prognosis. However, the massive sizes of the omics datasets, along with their correlation structures, pose challenges for studying relationships between the molecular information and patients' survival outcomes. Results We present a general workflow for survival analysis that is applicable to high-dimensional omics data as inputs when identifying survival-associated features and validating survival models. In particular, we focus on the commonly used Cox-type penalized regressions and hierarchical Bayesian models for feature selection in survival analysis, which are especially useful for high-dimensional data, but the framework is applicable more generally. Availability and implementation A step-by-step R tutorial using The Cancer Genome Atlas survival and omics data for the execution and evaluation of survival models has been made available at https://ocbe-uio.github.io/survomics. [ABSTRACT FROM AUTHOR]

Ovarian cancer is the most lethal gynecologic neoplasm, and most patients experience recurrence and chemoresistance. Even the promising immunotherapy showed limited efficacy in ovarian cancer, probably due to the immunosuppressive microenvironment. However, the behind mechanisms of the immune exclusion or cold phenotype in ovarian cancer still remain to be explored. As a cancer dominated by copy number variations instead of mutations, ovarian cancer contains a high fraction of aneuploid, which might correlate with immune inhibition. Nevertheless, whether or how aneuploid affects ovarian cancer is still unclear. For exploring the role of aneuploid cancer cells and the potential ploidy-immune relationship, herein, the ploidy information was first comprehensively analyzed combining the karyotype data and copy number variation data obtained from Mitelman and cBioPortal databases, respectively. Ovarian cancer showed strong ploidy heterogeneity, with high fraction of aneuploid and recurrent arm-level and whole chromosome changes. Furthermore, clinical parameters were compared between the highly-aneuploid and the near-diploid ovarian cancers. Aneuploid indicated high grade, poor overall survival and poor disease-free survival in ovarian cancer. To understand the biofunction affected by aneuploid, the differentially expressed genes between the highly-aneuploid and the near-diploid groups were analyzed. Transcription data suggested that aneuploid cancer correlated with deregulated MHC expression, abnormal antigen presentation, and less infiltration of macrophages and activated T cells and higher level of T cell exclusion. Furthermore, the ploidy-MHC association was verified using the Human Protein Atlas database. All these data supported that aneuploid might be promising for cancer management and immune surveillance in ovarian cancer. [ABSTRACT FROM AUTHOR]

Background: The visually assessed time difference between the mitral valve and tricuspid valve opening (VMT) score was correlated with the increase of left ventricular filling pressure (LVFP). Hypothesis: We suspected that the VMT score might be a valuable prognostic biomarker for heart failure with mildly reduced ejection fraction (HFmrEF) patients. This study was to evaluate the predictive value of VMT score for 1‐year all‐cause and cardiovascular disease (CVD)‐cause mortality in HFmrEF patients. Methods: This cohort study enrolled 379 patients aged ≥18 years old with HFmrEF. Univariable and multivariable Cox regression analysis was employed to assess the association between VMT score and all‐cause or CVD‐cause mortality in HFmrEF patients. Hazards ratio (HR), and 95% confidence interval (CI) were effect sizes. Kaplan–Meier curves showed the survival probability of patients. The area under the curve (AUC) evaluated the prognostic value of the VMT score. Results: The risk of all‐cause mortality was increased in HFmrEF patients in the VMT score of 2 (HR = 2.80, 95%CI: 1.04–7.52) and 3 (HR = 4.29, 95%CI: 1.58–11.66). The VMT score of 3 was associated with an increased risk of 1‐year CVD‐cause mortality in patients with HFmrEF (HR = 7.63, 95%CI: 1.70–34.33). The AUC of VMT score for predicting 1‐year all‐cause mortality of HFmrEF patients was 0.724, and for predicting 1‐year CVD‐cause mortality of HFmrEF patients was 0.748. The survival probability of patients with the VMT score < 2 was higher than those with the VMT score of 2 and 3. Conclusion: The VMT score might be a reliable prognostic index for 1‐year all‐cause or CVD‐cause mortality of HFmrEF patients. [ABSTRACT FROM AUTHOR]

Background: There are sex differences in many risk factors associated with coronary artery disease (CAD). CT-derived fractional flow reserve (CT-FFR) and fat attenuation index (FAI) have been shown to independently predict cardiovascular events. We aimed to examine the impact of sex on the prognostic value of CT-FFR and FAI in suspected CAD patients, and to examine the incremental prognostic value of FAI over CT-FFR in both sex. Methods: A total of 1334 consecutive suspected CAD subjects who underwent coronary computed tomographic angiography (CCTA) were retrospectively collected. We divided the patients into males and females and calculated CT-FFR and FAI data from CCTA images. Kaplan-Meier analysis was used to assess the risk of major adverse cardiovascular events (MACE) stratified by CT-FFR and FAI in both sex. Cox regression models were used to assess the incremental prognostic value of FAI by adding the variable to a model that included CT-FFR and clinical variables. Results: During a median follow-up of 2.08 years, 212 patients had MACE. CT-FFR ≤ 0.80 was significantly associated with MACE in both sex. FAI value of left anterior descending artery (FAI[LAD]) and FAI value of left circumflex (FAI[LCX]) ≥ 70.1 were significantly associated with MACE in females. FAI[LCX] added incremental prognostic value over clinical and CT-FFR variables in females, with hazard ratio (HR) 3.230 (1.982–5.265, P = 0.000), Harrel's C 0.669 (P < 0.001), net reclassification improvement (NRI) 0.161 (0.073–0.260, P < 0.001), and integrated discrimination index (IDI) 0.036 (0.008–0.090, P = 0.010). FAI[LAD] did not enhance risk prediction in females (Harrel's C 0.643, P = 0.054; NRI 0.041, P = 0.189; IDI 0.005, P = 0.259). The decision curve analysis demonstrated that the model including FAI[LCX] resulted in the highest net benefit. Conclusions: In suspected CAD patients, the prognostic value of CT-FFR is not significantly biased by sex. The prognostic value of FAI[LAD] and FAI[LCX] were significantly associated with MACE in females, but not males. FAI[LCX], not FAI[LAD], added incremental prognostic value over CT-FFR and might enhance CT-FFR risk stratification in females. [ABSTRACT FROM AUTHOR]

Pancreatic cancer (PDAC) is one of the most aggressive solid tumors and is showing increasing incidence. The aim of our review is to provide practical help for all clinical oncologists and to summarize the current management of PDAC using a simple "ABC method" (A—anatomical resectability, B—biological resectability and C—clinical conditions). For anatomically resectable PDAC without any high-risk factors (biological or conditional), the actual standard of care is represented by surgery followed by adjuvant chemotherapy. The remaining PDAC patients should all be treated with initial systemic therapy, though the intent for each is different: for borderline resectable patients, the intent is neoadjuvant; for locally advanced patients, the intent is conversion; and for metastatic PDAC patients, the intent remains just palliative. The actual standard of care in first-line therapy is represented by two regimens: FOLFIRINOX and gemcitabine/nab-paclitaxel. Recently, NALIRIFOX showed positive results over gemcitabine/nab-paclitaxel. There are limited data for maintenance therapy after first-line treatment, though 5-FU or FOLFIRI after initial FOLFIRINOX, and gemcitabine, after initial gemcitabine/nab-paclitaxel, might be considered. We also dedicate space to special rare conditions, such as PDAC with germline BRCA mutations, pancreatic acinar cell carcinoma and adenosquamous carcinoma of the pancreas, with few clinically relevant remarks. [ABSTRACT FROM AUTHOR]

Background: Recently, there has been a growing focus on the prognostic significance of nutrition-related biomarkers. We attempted to explore the association between a novel albumin-related nutrition marker called "lymphocyte × albumin (LA)" and disease-free survival (DFS) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). Methods: In total, 711 non-metastatic breast cancer patients who underwent NAC at two medical centers were retrospectively analyzed. We performed least absolute shrinkage and selection operator (LASSO) Cox regression analysis as well as multivariate Cox regression analyses to identify the variables associated with DFS and to establish a predictive nomogram. Results: The nomogram incorporated four variables based on the multivariate analysis of DFS in the training cohort: LA, ypN stage, ypT stage, and hormone receptor status. In comparison with the traditional TNM staging system, the nomogram demonstrated superior discrimination, calibration ability, and clinical usefulness in both the training set and internal and external validation sets. Furthermore, patients stratified into different risk groups resulted in significant differences in DFS. Conclusions: LA is an independent prognostic biomarker, and LA-based prognostic nomogram offers a more precise assessment of DFS for breast cancer patients treated with NAC, potentially serving as a valuable tool for personalized prognostic predictions. [ABSTRACT FROM AUTHOR]

Background: lung adenocarcinoma (LUAD) remains one of the most common and lethal malignancies with poor prognosis. Programmed cell death (PCD) is an evolutionarily conserved cell suicide process that regulates tumorigenesis, progression, and metastasis of cancer cells. However, a comprehensive analysis of the role of PCD in LUAD is still unavailable. Methods: We analyzed multi-omic variations in PCD-related genes (PCDRGs) for LUAD. We used cross-validation of 10 machine learning algorithms (101 combinations) to synthetically develop and validate an optimal prognostic cell death score (CDS) model based on the PCDRGs expression profile. Patients were classified based on their median CDS values into the high and low-CDS groups. Next, we compared the differences in the genomics, biological functions, and tumor microenvironment of patients between both groups. In addition, we assessed the ability of CDS for predicting the response of patients from the immunotherapy cohort to immunotherapy. Finally, functional validation of key genes in CDS was performed. Results: We constructed CDS based on four PCDRGs, which could effectively and consistently stratify patients with LUAD (patients with high CDS had poor prognoses). The performance of our CDS was superior compared to 77 LUAD signatures that have been previously published. The results revealed significant genetic alterations like mutation count, TMB, and CNV were observed in patients with high CDS. Furthermore, we observed an association of CDS with immune cell infiltration, microsatellite instability, SNV neoantigens. The immune status of patients with low CDS was more active. In addition, CDS could be reliable to predict therapeutic response in multiple immunotherapy cohorts. In vitro experiments revealed that high DNA damage inducible transcript 4 (DDIT4) expression in LUAD cells mediated protumor effects. Conclusion: CDS was constructed based on PCDRGs using machine learning. This model could accurately predict patients' prognoses and their responses to therapy. These results provide new promising tools for clinical management and aid in designing personalized treatment strategies for patients with LUAD. [ABSTRACT FROM AUTHOR]

Background: Clinical prediction models are widely used in health and medical research. The area under the receiver operating characteristic curve (AUC) is a frequently used estimate to describe the discriminatory ability of a clinical prediction model. The AUC is often interpreted relative to thresholds, with "good" or "excellent" models defined at 0.7, 0.8 or 0.9. These thresholds may create targets that result in "hacking", where researchers are motivated to re-analyse their data until they achieve a "good" result. Methods: We extracted AUC values from PubMed abstracts to look for evidence of hacking. We used histograms of the AUC values in bins of size 0.01 and compared the observed distribution to a smooth distribution from a spline. Results: The distribution of 306,888 AUC values showed clear excesses above the thresholds of 0.7, 0.8 and 0.9 and shortfalls below the thresholds. Conclusions: The AUCs for some models are over-inflated, which risks exposing patients to sub-optimal clinical decision-making. Greater modelling transparency is needed, including published protocols, and data and code sharing. [ABSTRACT FROM AUTHOR]

Aims To determine whether fully automated artificial intelligence-based global circumferential strain (GCS) assessed during vasodilator stress cardiovascular (CV) magnetic resonance (CMR) can provide incremental prognostic value. Methods and results Between 2016 and 2018, a longitudinal study included all consecutive patients with abnormal stress CMR defined by the presence of inducible ischaemia and/or late gadolinium enhancement. Control subjects with normal stress CMR were selected using a propensity score-matching. Stress-GCS was assessed using a fully automatic machine-learning algorithm based on featured-tracking imaging from short-axis cine images. The primary outcome was the occurrence of major adverse clinical events (MACE) defined as CV mortality or nonfatal myocardial infarction. Cox regressions evaluated the association between stress-GCS and the primary outcome after adjustment for traditional prognosticators. In 2152 patients [66 ± 12 years, 77% men, 1:1 matched patients (1076 with normal and 1076 with abnormal CMR)], stress-GCS was associated with MACE [median follow-up 5.2 (4.8–5.5) years] after adjustment for risk factors in the propensity-matched population [adjusted hazard ratio (HR), 1.12 (95% CI, 1.06–1.18)], and patients with normal CMR [adjusted HR, 1.35 (95% CI, 1.19–1.53), both P < 0.001], but not in patients with abnormal CMR (P = 0.058). In patients with normal CMR, an increased stress-GCS showed the best improvement in model discrimination and reclassification above traditional and stress CMR findings (C-statistic improvement: 0.14; NRI = 0.430; IDI = 0.089, all P < 0.001; LR-test P < 0.001). Conclusion Stress-GCS is not a predictor of MACE in patients with ischaemia, but has an incremental prognostic value in those with a normal CMR although the absolute event rate remains low. [ABSTRACT FROM AUTHOR]

Serologic biomarker to predict clinical outcome is needed for immune checkpoint inhibitors (ICIs). We evaluated soluble intercellular adhesion molecules‐1 (sICAM‐1) as a predictor of response to ICIs treatment. Ninety‐five patients with cancer treated with ICI were studied. The serum sICAM‐1 levels of baseline, post two cycle therapy and end of therapy (EOT) were measured by enzyme‐linked immunoassay. We randomly assigned the patients into the primary cohort (n = 47) and validation cohort (n = 48). Serum sICAM‐1 post two cycle (277.7 ± 181.6 ng/mL) and EOT (403.9 ± 218.9 ng/mL) were significantly elevated compared to baseline (244.8 ± 153.8 ng/mL, p = 0.008 and p = 0.004, respectively). Early changes of sICAM‐1 (ΔsICAM‐1), deemed as sICAM‐1 after two cycles minus baseline, were assessed. Following ICI treatments, responders had significantly lower ΔsICAM‐1 compared with nonresponders in the primary cohort (p = 0.040) and the validation cohort (p = 0.026). High ΔsICAM‐1 was strongly associated with inferior progression‐free survival (PFS; (primary cohort: p = 0.001 and validation cohort: p = 0.002) and overall survival (OS; (primary cohort: p < 0.001 and validation cohort: p = 0.007). The ΔsICAM‐1 remained independently associated with worse PFS and OS in the primary cohort and the validation cohort. Subgroup analysis indicated patients whose sICAM‐1 significantly elevated had shorter PFS and OS in both anti‐PD‐1 and anti‐PD‐L1 treatment groups. Early change of serum sICAM‐1 could be used to monitor and predict clinical benefit of ICI therapy in patients with solid cancer. [ABSTRACT FROM AUTHOR]

Simple Summary: The current study investigated the potential use of fluorometric cfDNA quantification as a prognostic biomarker in advanced non-small cell lung cancer (NSCLC) patients treated with an Immune Checkpoint Blockade (ICB). Results showed that a cfDNA cut-off of 0.55 ng/µL before the ICB determines the overall survival of patients with a log rank p-value of 3.3 × 10−4. High cfDNA concentrations identify patients with advanced NSCLC who do not benefit from ICB. The determination of cfDNA is a simple test that could select a group of patients in whom new therapeutic strategies are needed. The present study aimed to investigate the potential of basal cell-free fluorometric DNA (cfDNA) quantification as a prognostic biomarker in advanced non-small cell lung cancer (NSCLC) patients treated with an Immune Checkpoint Blockade (ICB). A discovery and validation cohort of 61 and 31 advanced lung cancer patients treated with ICB were included in this study. Quantification of cfDNA concentration was performed before the start of the treatment and patients were followed up for a median of 34 (30–40) months. The prognostic predicted value of cfDNA was evaluated based on ROC, and Cox regression was conducted via univariate and multivariate analyses to estimate the hazard ratio. We observed that a cfDNA cut-off of 0.55 ng/µL before the ICB determines the overall survival of patients with a log rank p-value of 3.3 × 10−4. That represents median survivals of 3.8 vs. 17.5 months. Similar results were obtained in the validation cohort being the log rank p-value 3.8 × 10−2 with median survivals of 5.9 vs. 24.3. The univariate and multivariate analysis revealed that the cut-off of 0.55 ng/µL before ICB treatment was an independent predictive factor and was significantly associated with a better survival outcome. High cfDNA concentrations identify patients with advanced NSCLC who do not benefit from the ICB. The determination of cfDNA is a simple test that could select a group of patients in whom new therapeutic strategies are needed. [ABSTRACT FROM AUTHOR]

Aims We investigated the prevalence and clinical value of assessing multi-organ congestion by ultrasound in heart failure (HF) outpatients. Methods and results Ultrasound congestion was defined as inferior vena cava of ≥21 mm, highest tertile of lung B-lines, or discontinuous renal venous flow. Associations with clinical characteristics and prognosis were explored. We enrolled 310 HF patients [median age: 77 years, median NT-proBNP: 1037 ng/L, 51% with a left ventricular ejection fraction (LVEF) <50%], and 101 patients without HF. There were no clinical signs of congestion in 224 (72%) patients with HF, of whom 95 (42%) had at least one sign of congestion by ultrasound (P < 0.0001). HF patients with ≥2 ultrasound signs were older, and had greater neurohormonal activation, lower urinary sodium concentration, and larger left atria despite similar LVEF. During a median follow-up of 13 (interquartile range: 6–15) months, 77 patients (19%) died or were hospitalized for HF. HF patients without ultrasound evidence of congestion had a similar outcome to patients without HF [reference; hazard ratio (HR) 1.02, 95% confidence interval (CI) 0.86–1.35], while those with ≥2 ultrasound signs had the worst outcome (HR 26.7, 95% CI 12.4–63.6), even after adjusting for multiple clinical variables and NT-proBNP. Adding multi-organ assessment of congestion by ultrasound to a clinical model, including NT-proBNP, provided a net reclassification improvement of 28% (P = 0.03). Conclusion Simultaneous assessment of pulmonary, venous, and kidney congestion by ultrasound is feasible, fast, and identifies a high prevalence of sub-clinical congestion associated with poor outcomes. [ABSTRACT FROM AUTHOR]

Episodes of worsening symptoms and signs characterize the clinical course of patients with chronic heart failure (HF). These events are associated with poorer quality of life, increased risks of hospitalization and death and are a major burden on healthcare resources. They usually require diuretic therapy, either administered intravenously or by escalation of oral doses or with combinations of different diuretic classes. Additional treatments may also have a major role, including initiation of guideline‐recommended medical therapy (GRMT). Hospital admission is often necessary but treatment in the emergency service or in outpatient clinics or by primary care physicians has become increasingly used. Prevention of first and recurring episodes of worsening HF is an essential component of HF treatment and this may be achieved through early and rapid administration of GRMT. The aim of the present clinical consensus statement by the Heart Failure Association of the European Society of Cardiology is to provide an update on the definition, clinical characteristics, management and prevention of worsening HF in clinical practice. [ABSTRACT FROM AUTHOR]

Hip fractures are common in patients of advanced age and are associated with excess mortality. Rapid and accurate prediction of the prognosis using information that can be easily obtained before surgery would be advantageous to clinical management. We performed a population‐based retrospective cohort study using an 8.5‐year Japanese claims database (April 2012–September 2020) to develop and validate a predictive model for long‐term mortality after hip fracture. The study included 43,529 patients (34,499 [79.3%] women) aged ≥65 years with first‐onset hip fracture. During the observation period, 43% of the patients died. Cox regression analysis identified the following prognostic predictors: sex, age, fracture site, nursing care certification, and several comorbidities (any malignancy, renal disease, congestive heart failure, chronic pulmonary disease, liver disease, metastatic solid tumor, and deficiency anemia). We then developed a scoring system called the Shizuoka Hip Fracture Prognostic Score (SHiPS); this system was established by scoring based on each hazard ratio and classifying the degree of mortality risk into four categories based on decision tree analysis. The area under the receiver operating characteristic (ROC) curve (AUC) (95% confidence interval [CI]) of 1‐year, 3‐year, and 5‐year mortality based on the SHiPS was 0.718 (95% CI, 0.706–0.729), 0.736 (95% CI, 0.728–0.745), and 0.758 (95% CI, 0.747–0.769), respectively, indicating good predictive performance of the SHiPS for as long as 5 years after fracture onset. Even when the SHiPS was individually applied to patients with or without surgery after fracture, the prediction performance by the AUC was >0.7. These results indicate that the SHiPS can predict long‐term mortality using preoperative information regardless of whether surgery is performed after hip fracture. [ABSTRACT FROM AUTHOR]

Introduction: Minimal residual disease (MRD) has been recognized as an important prognostic factor of survival in patients with hematological malignancies. However, the prognostic value of MRD in Waldenström macroglobulinemia (WM) remains unexplored. Methods: We analyzed 108 newly diagnosed WM patients receiving systematic therapy and assessed for MRD by multiparameter flow cytometry (MFC) using bone marrow samples. Results: Of the total patients, 34 (31.5%) achieved undetectable MRD (uMRD). A hemoglobin level of >115 g/L (P=0.03), a serum albumin level of >35 g/L (P=0.01), a β2-MG level of ≤3 mg/L (P=0.03), and a low-risk International Prognostic Scoring System for WM (IPSSWM) stage (P<0.01) were associated with a higher rate of uMRD. Improvements in monoclonal immunoglobulin (P<0.01) and hemoglobin (P=0.03) levels were more evident in uMRD patients compared with that in MRD-positive patients. The 3-year progression-free survival (PFS) was better in uMRD patients compared with that in MRD-positive patients (96.2% vs. 52.8%; P=0.0012). Landmark analysis also showed that uMRD patients had better PFS compared with MRD-positive patients after 6 and 12 months. Patients who achieved partial response (PR) and uMRD had a 3-year PFS of 100%, which was significantly higher than that of patients with MRD-positive PR (62.6%, P=0.029). Multivariate analysis showed that MRD positivity was an independent factor of PFS (HR: 2.55, P=0.03). Moreover, the combination of the 6th International Workshop on WM assessment (IWWM-6 Criteria) and MRD assessment had a higher 3-year AUC compared with the IWWM-6 criteria alone (0.71 vs. 0.67). Discussion: MRD status assessed by MFC is an independent prognostic factor for PFS in patients with WM, and its determination could improve the precision of response evaluation, especially in patients who achieved PR. [ABSTRACT FROM AUTHOR]

Background: Next-generation sequencing (NGS) is maturely applied for gene fusion detection. Although tumor fusion burden (TFB) has been identified as an immune marker for cancer, the relationship between these fusions and the immunogenicity and molecular characteristics of gastric cancer (GC) patients remains unclear. GCs have different clinical significance depending on their subtypes, and thus, this study aimed to investigate the characteristics and clinical relevance of TFB in non-Epstein–Barr-virus-positive (EBV+) GC with microsatellite stability (MSS). Methods: A total of 319 GC patients from The Cancer Genome Atlas stomach adenocarcinoma (TCGA-STAD) and a cohort of 45-case from ENA (PRJEB25780) were included. The cohort characteristics and distribution of TFB among the patients were analyzed. Additionally, the correlations of TFB with mutation characteristics, pathway differences, relative abundance of immune cells, and prognosis were examined in the TCGA-STAD cohort of MSS and non-EBV (+) patients. Results: We observed that in the MSS and non-EBV (+) cohort, the TFB-low group exhibited significantly lower gene mutation frequency, gene copy number, loss of heterozygosity score, and tumor mutation burden than in the TFB-high group. Additionally, the TFB-low group exhibited a higher abundance of immune cells. Furthermore, the immune gene signatures were significantly upregulated in the TFB-low group, 2-year disease-specific survival was markedly increased in the TFB-low group compared with to the TFB-high group. The rates of TFB-low cases were significantly higher TFB-than high cases in durable clinical benefit (DCB) and response groups with pembrolizumab treatment. Low TFB may serve as a predictor of GC prognosis, and the TFB-low group exhibits higher immunogenicity. Conclusion: In conclusion, this study reveals that the TFB-based classification of GC patient may be instructive for individualized immunotherapy regimens. [ABSTRACT FROM AUTHOR]

Background & Aims: In this retrospective study, we aimed to elucidate how the initial recurrence site influences the post-recurrence survival (PRS) after the curative resection of colorectal cancer. Patients and methods: We collected samples from patients with stage I-III colorectal adenocarcinoma who were admitted to Yunnan Cancer Hospital from January 2008 to December 2019. Four hundred and six patients who developed recurrence after radical resection were included. The cases were classified according to the original site of recurrence as follows: liver metastases (n = 98), lung metastases (n = 127), peritoneum (n = 32), other individual organ (n = 69), two or more organs or sites (n = 49), and local recurrence (n = 31). Kaplan–Meier survival curves were used to compare the PRS of patients with different initial sites of recurrence. The influence of the initial recurrence site on PRS was analyzed using the Cox proportional hazards model. Results: The 3-year PRS of simple liver metastasis was 54.04% (95% CI, 45.46%-64.24%), and the 3-year PRS of simple lung metastasis was 50.05% (95% CI, 42.50%-58.95%). No significant difference was observed between simple liver metastasis or simple lung metastasis and local recurrence with a 3-year PRS of 66.99% (95% CI, 53.23%-84.32%). The 3-year PRS for peritoneal metastases was 25.43% (95% CI, 14.76%-43.82%), and the 3-year PRS for two or more organ sites was 34.84% (95% CI, 24.16%-50.24%). The peritoneal (hazard ratio [HR], 1.75; 95% CI, 1.10–2.79; P = 0.0189) and metastasis to two or more organs or sites (HR, 1.59; 95% CI, 1.05–2.43; P = 0.0304) were PRS-independent adverse prognostic factors. Conclusion: The prognosis of patients with peritoneum and multiple organs or sites recurred was poor. This study suggests early monitoring of peritoneal and multiple organ or site recurrence after surgery. This part of patients should receive comprehensive treatment as early as possible to improve their prognosis. [ABSTRACT FROM AUTHOR]

Simple Summary: Severe clinical mastitis is an inflammation of the mammary gland with systemic clinical signs. It is a frequent and highly fatal disease of dairy cattle worldwide. Nomograms are practical tools that help predict a specific issue based on statistical models. Here, we developed nomograms for prediction of death or culling related with cases of severe clinical mastitis that were treated in dairy farm settings following a veterinary clinical examination. Such a tool will help veterinarians in prognosis prediction. A reliable prognosis is important to make euthanasia decisions in poor prognosis cases. Severe clinical mastitis is a frequent disease of dairy cattle. An effective mean of predicting survival despite treatment would be helpful for making euthanasia decisions in poor prognosis cases. The objective was to develop a nomogram for prediction of death or culling in the 60 days following a severe mastitis episode in dairy cows at first veterinary visit in farm settings. A total of 224 dairy cows presenting severe clinical mastitis and examined for the first time by a veterinarian were included in a prospective study. Clinical and laboratory (complete blood cell count, L-lactate, cardiac troponin I, milk culture) variables were recorded. Animals were followed for 60 days. A nomogram was built with an adaptive elastic-net Cox proportional hazards model. Performances and relevance were evaluated by area under the receiver operating characteristic curve (AUC), Harrell's concordance index (C-index), calibration curve, decision curve analysis (DCA) and misclassification cost term (MCT). The nomogram included: lactation number, recumbency, depression intensity, capillary refilling time, ruminal motility rate, dehydration level, lactates concentration, hematocrit, band neutrophils count, monocyte count, and milk bacteriology. The AUC and C-index showed a good calibration and ability to discriminate. The DCA suggested that the nomogram was clinically relevant. Euthanizing animals having less than 25% probability of survival is economically optimal. It could be used for early euthanasia decisions in animals that would not survive despite treatment. To facilitate the use of this nomogram by veterinarians, a web-based app was developed. [ABSTRACT FROM AUTHOR]

Patients with advanced cancer undergo comprehensive genomic profiling in Japan only after treatment options have been exhausted. Patients with a very poor prognosis were not able to undergo profiling tests, resulting in a selection bias called length bias, which makes accurate survival analysis impossible. The actual impact of length bias on the overall survival of patients who have undergone profiling tests is unclear, yet appropriate methods for adjusting for length bias have not been developed. To assess the length bias in overall survival, we established a simulation‐based model for length bias adjustment. This study utilized clinicogenomic data of 8813 patients with advanced cancer who underwent profiling tests at hospitals throughout Japan between June 2019 and April 2022. Length bias was estimated by the conditional Kendall τ statistics and was significantly positive for 13 of the 15 cancer subtypes, suggesting a worse prognosis for patients who underwent profiling tests in early timing. The median overall survival time in colorectal, breast, and pancreatic cancer from the initial survival‐prolonging chemotherapy with adjustment for length bias was 937 (886–991), 1225 (1152–1368), and 585 (553–617) days, respectively (median; 95% credible interval). Adjusting for length bias made it possible to analyze the prognostic relevance of oncogenic mutations and treatments. In total, 12 tumor‐specific oncogenic mutations correlating with poor survival were detected after adjustment. There was no difference in survival between FOLFIRINOX (leucovorin, fluorouracil, irinotecan, and oxaliplatin) or gemcitabine with nab‐paclitaxel‐treated groups as first‐line chemotherapy for pancreatic cancer. Adjusting for length bias is an essential part of utilizing real‐world clinicogenomic data. [ABSTRACT FROM AUTHOR]

Objectives: The B cell activating factor (BAFF) is a B cell survival factor involved in atherosclerosis and ischemia-reperfusion (IR) injury. This study sought to investigate whether BAFF is a potential predictor of poor outcomes in patients with ST-segment elevation myocardial infarction (STEMI). Methods: We prospectively enrolled 299 patients with STEMI, and serum levels of BAFF were measured. All subjects were followed for three years. The primary endpoint was major adverse cardiovascular events (MACEs), including cardiovascular death, nonfatal reinfarction, hospitalization for heart failure (HF), and stroke. Multivariable Cox proportional hazards models were constructed to analyze the predictive value of BAFF for MACEs. Results: In multivariate analysis, BAFF was independently associated with risk of MACEs (adjusted HR 1.525, 95% CI 1.085–2.145; p = 0.015) and cardiovascular death (adjusted hazard ratio [HR] 3.632, 95% confidence interval [CI] 1.132–11.650, p = 0.030) after adjustment for traditional risk factors. Kaplan-Meier survival curves demonstrated that patients with BAFF levels above the cut-off value (1.46 ng/mL) were more likely to have MACEs (log-rank p < 0.0001) and cardiovascular death (log-rank p < 0.0001). In subgroup analysis, the impact of high BAFF on MACEs development was stronger in patients without dyslipidemia. Furthermore, the C-statistic and Integrated Discrimination Improvement (IDI) values for MACEs were improved with BAFF as an independent risk factor or when combined with cardiac troponin I. Conclusions: This study suggests that higher BAFF levels in the acute phase are an independent predictor of the incidence of MACEs in patients with STEMI. [ABSTRACT FROM AUTHOR]

Background: It is imperative to explore potential biomarkers for predicting clinical outcome and developing targeted therapies for T‐cell acute lymphoblastic leukemia (T‐ALL). This study aimed to investigate the mutation patterns of tumor necrosis factor‐alpha‐inducing protein 3 (TNFAIP3, also known as A20) and its role in the prognosis of T‐ALL patients. Methods: Polymerase chain reaction (PCR) and Sanger sequencing data from T‐ALL (n = 49, JNU) and targeted sequencing data from T‐ALL (n = 54, NFH) in our clinical center and a publicly available dataset (n = 121, PRJCA002270), were used to detect TNFAIP3 mutation. Results: Three TNFAIP3 single nucleotide polymorphisms (SNPs; g.3033 C > T, g.3910 G > A, and g.3904 A > G) were detected in T‐ALL in the JNU dataset, and g.3033 C > T accounted for the highest proportion, reaching 60% (6/10). Interestingly, TNFAIP3 mutation mainly occurred in adults but not pediatric patients in all three datasets (JNU, NFH, and PRJCA002270). T‐ALL patients carrying a TNFAIP3 mutation were associated with a trend of poor overall survival (OS) (p = 0.092). Moreover, TNFAIP3 mutation was also an independent factor for OS for T‐ALL patients (p = 0.008). Further subgroup analysis suggested that TNFAIP3 mutation predicted poor OS for T‐ALL patients who underwent chemotherapy only (p < 0.001), and it was positively correlated with high risk and early T‐cell precursor ALL (ETP‐ALL) in two independent validation datasets (NFH and PRJCA002270). Conclusion: TNFAIP3 mutation mainly occurs in adult T‐ALL patients, and it was associated with adverse clinical outcomes for T‐ALL patients; thus, it might be a biomarker for prognostic stratification. [ABSTRACT FROM AUTHOR]

Despite the well-known importance of left atrial (LA) mechanics in diastolic function, data are scarce regarding the prognostic power of LA longitudinal strain and its potential added value in the risk stratification of an elderly population. Accordingly, our aim was to determine the long-term prognostic importance of 2D speckle-tracking echocardiography-derived peak atrial longitudinal strain (PALS) in a community-based screening sample. Three hundred and fourteen volunteers were retrospectively identified from a population-based screening program (mean age 62 ± 11 years; 58% female) with a median follow-up of 9.5 years. All subjects who participated in the screening program underwent 2D echocardiography to measure left ventricular (LV) ejection fraction (EF), global longitudinal strain (GLS), and PALS, as well as low-dose cardiac CT to determine the Agatston score. The primary endpoint was all-cause mortality. Thirty-nine subjects (12.4%) met the primary endpoint. Subjects with adverse outcomes had significantly lower LV GLS (dead vs. alive; − 19.2 ± 4.3 vs. − 20.6 ± 3.5%, p < 0.05) and PALS (32.3 ± 12.0 vs. 41.8 ± 14.2%, p < 0.001), whereas LV EF did not show a difference between the two groups (51.1 ± 7.0 vs. 52.1 ± 6.2, %, p = NS). By multivariable Cox regression analysis, PALS was found to be a significant predictor of adverse outcomes independent of LV GLS, and Agatston and Framingham scores. In subjects with PALS values below the standard cut-off of 39%, the risk of all-cause mortality was almost 2.5 times higher (hazard ratio: 2.499 [95% confidence interval: 1.334–4.682], p < 0.05). Beyond the assessment of LV EF and LV GLS, PALS offers incremental value in cardiovascular risk stratification in a community-based elderly cohort. PALS was found to be a significant and independent predictor of long-term mortality among other classical cardiovascular risk estimators. [ABSTRACT FROM AUTHOR]

Background In kidney transplant recipients (KTR), the end-stage kidney disease (ESKD) risk dependent on the risk factors acting in native chronic kidney disease (CKD) remains undefined. Methods We compared risk and determinants of ESKD between 757 adult KTR and 1940 patients with native CKD before and after propensity-score (PS) analysis matched for unmodifiable risk factors [(age, sex, diabetes, cardiovascular disease and estimated glomerular filtration rate (eGFR)]. Results In unmatched cohorts, eGFR was lower in CKD versus KTR (45.9 ± 11.3 versus 59.2 ± 13.4 mL/min/1.73 m2, P < 0.001). During a median follow-up of 5.4 years, the unadjusted cumulative incidence of ESKD was consistently lower in unmatched KTR versus CKD. Conversely, in PS-matched analysis, the risk of ESKD in KTR was 78% lower versus CKD at 1 year of follow-up while progressively increased over time resulting similar to that of native CKD patients after 5 years and 2.3-fold higher than that observed in CKD at 10 years. R2 analysis in unmatched patients showed that the proportion of the outcome variance explained by traditional ESKD determinants was smaller in KTR versus native CKD (31% versus 70%). After PS matching, the risk of ESKD [hazard ratio (HR), 95% confidence interval (95% CI)] was significantly associated with systolic blood pressure (1.02, 1.01–1.02), phosphorus (1.31, 1.05–1.64), 24-h proteinuria (1.11, 1.05–1.17) and haemoglobin (0.85, 0.78–0.93) irrespective of KTR status. Similar data were obtained after matching also for modifiable risk factors. Conclusions In KTR, when compared with matched native CKD patients, the risk of ESKD is lower in the first 5 years and higher later on. Traditional determinants of ESKD account for one-third of the variability of time-to-graft failure. [ABSTRACT FROM AUTHOR]

Simple Summary: The major histocompatibility complex (MHC) class I genes, encompassing the human leukocyte antigen (HLA) class I and the beta-2 microglobulin (B2M) genes, play a key role in neoantigens presentation to the immune system. We analyzed allelic imbalance (AI) of the respective chromosomal regions by multiplex PCRs using microsatellite markers in biopsies of 158 patients with gastric/gastroesophageal adenocarcinoma before neoadjuvant platinum/fluoropyrimidine chemotherapy (CTx) for an association with clinical outcome of the patients. AI with no marker was significantly associated with response or survival. However, subgroup analysis revealed interesting differences. Of note, AI at markers of the HLA region was associated with a decreased survival only in responding but not in non-responding patients. No associations were observed for B2M markers. Our results underline the importance of intact neoantigen presentation specifically for responding patients and may help explain an unexpectedly poor survival of a patient despite significant tumor regression after neoadjuvant CTx. We aimed to determine the clinical and prognostic relevance of allelic imbalance (AI) of the major histocompatibility complex (MHC) class I genes, encompassing the human leukocyte antigen (HLA) class I and beta-2 microglobulin (B2M) genes, in the context of neoadjuvant platinum/fluoropyrimidine chemotherapy (CTx). Biopsies before CTx were studied in 158 patients with adenocarcinoma of the stomach or gastroesophageal junction. The response was histopathologically evaluated. AI was detected by multiplex PCRs analysis of four or five microsatellite markers in HLA and B2M regions, respectively. AI with no marker was significantly associated with response or survival. However, subgroup analysis revealed differences. AI at marker D6S265, close to the HLA-A gene, was associated with an obvious increased risk in responding (HR, 3.62; 95% CI, 0.96–13.68, p = 0.058) but not in non-responding patients (HR, 0.92; 95% CI, 0.51–1.65, p = 0.773). Markers D6S273 and D6S2872 showed similar results. The interaction between AI at D6S265 and response to CTx was significant in a multivariable analysis (p = 0.010). No associations were observed for B2M markers. Our results underline the importance of intact neoantigen presentation specifically for responding patients and may help explain an unexpectedly poor survival of a patient despite significant tumor regression after neoadjuvant platinum/fluoropyrimidine CTx. [ABSTRACT FROM AUTHOR]

Background: The absence of breast cancer cells in surgical specimens, i.e., pathological complete response (pCR), is widely recognized as a favorable prognostic factor after neoadjuvant therapy. In contrast, the presence of disease at surgery characterizes a prognostically heterogeneous group of patients. Here, we challenged circulating microRNAs (miRNAs) at the end of neoadjuvant therapy as potential prognostic biomarkers in the NeoALTTO study. Methods: Patients treated within the trastuzumab arm (i.e., pre-operative weekly trastuzumab for 6 weeks followed by the addition of weekly paclitaxel for 12 weeks; post-operative FEC for 3 cycles followed by trastuzumab up to complete 1 year of treatment) were randomized into a training (n= 54) and testing (n= 72) set. RT-PCR-based high-throughput miRNA profile was performed on plasma samples collected at the end of neoadjuvant treatment of both sets. After normalization, circulating miRNAs associated with event free survival (EFS) were identified by univariate and multivariate Cox regression model. Results: Starting from 23 circulating miRNAs associated with EFS in the training set, we generated a 3-circulatingmiRNA prognostic signature consisting of miR-185-5p, miR-146a-5p, miR-22-3p, which was confirmed in the testing set. The 3-circulating miRNA signature showed a C-statistic of 0.62 (95% confidence interval [95%CI] 0.53-0.71) in the entire study cohort. By resorting to a multivariate Cox regression model we found a statistical significant interaction between the expression values of miR-194-5p and pCR status (p.interaction =0.005) with an estimate Hazard Ratio (HR) of 1.83 (95%CI 1.14-2.95) in patients with pCR, and 0.87 (95%CI 0.69-1.10) in those without pCR. Notably, the model including this interaction along with the abovementioned 3-circulatingmiRNA signature provided the highest discriminatory capability with a C-statistic of 0.67 (95%CI 0.58-0.76). Conclusions: Circulating miRNAs are informative to identify patients with different prognosis among those with heterogeneous response after trastuzumab-based neoadjuvant treatment, and may be an exploitable tool to select candidates for salvage adjuvant therapy. [ABSTRACT FROM AUTHOR]

Chromothripsis is a catastrophic event involving numerous chromosomal rearrangements in confined genomic regions of one or a few chromosomes, causing complex effects on cells via the extensive structural variation. The development of whole-genome sequencing (WGS) has promoted great progress in exploring the mechanism and effect of chromothripsis. However, the gene expression characteristics of tumors undergone chromothripsis have not been well characterized. In this study, we found that the transcriptional profile of five tumor types experiencing chromothripsis is associated with an immune evasion phenotype. A gene set variation analysis (GSVA) was used to develop a CHP score, which is based on differentially expressed gene sets in the TCGA database, revealing that chromothripsis status in multiple cancers is consistent with an abnormal tumor immune microenvironment and immune cell cytotoxicity. Evaluation using four immunotherapy datasets uncovered the ability of the CHP score to predict immunotherapy response in diverse tumor types. In addition, the CHP score was found to be related to resistance against a variety of anti-tumor drugs, including anti-angiogenesis inhibitors and platinum genotoxins, while EGFR pathway inhibitors were found to possibly be sensitizers for high CHP score tumors. Univariate COX regression analysis indicated that the CHP score can be prognostic for several types of tumors. Our study has defined gene expression characteristics of tumors with chromothripsis, supporting the controversial link between chromothripsis and tumor immunity. We also describe the potential value of the CHP score in predicting the efficacy of immunotherapy and other treatments, elevating chromothripsis as a tool in clinical practice. [ABSTRACT FROM AUTHOR]

Background: It was previously reported that the production of exerkines is positively associated with the beneficial effects of exercise in lung adenocarcinoma (LUAD) patients. This study proposes a novel scoring system based on muscle failure-related genes, to assist in clinical decision making. Methods: A comprehensive analysis of bulk and single cell RNA sequencing (scRNA-seq) of early, advanced and brain metastatic LUAD tissues and normal lung tissues was performed to identify muscle failure-related genes in LUAD and to determine the distribution of muscle failure-related genes in different cell populations. A novel scoring system, named MFI (Muscle failure index), was developed and validated. The differences in biological functions, immune infiltration, genomic alterations, and clinical significance of different subtypes were also investigated. Results: First, we conducted single cell analysis on the dataset GSE131907 and identified eight cell subpopulations. We found that four muscle failure-related genes (BDNF, FNDC5, IL15, MSTN) were significantly increased in tumor cells. In addition, IL15 was widely distributed in the immune cell population. And we have validated it in our own clinical cohort. Then we created the MFI model based on 10 muscle failure-related genes using the LASSO algorithm, and MFI remained an independent prognostic factor of OS in both the training and validation cohorts. Moreover, we generated MFI in the single-cell dataset, in which cells with high MFI received and sent more signals compared to those with low MFI. Biological function analysis of both subtypes revealed stronger anti-tumor immune activity in the low MFI group, while tumor cells with high MFI had stronger metabolic and proliferative activity. Finally, we systematically assessed the immune cell activity and immunotherapy responses in LUAD patients, finding that the low MFI group was more sensitive to immunotherapy. Conclusion: Overall, our study can improve the understanding of the role of muscle failure-related genes in tumorigenesis and we constructed a reliable MFI model for predicting prognosis and guiding future clinical decision making. [ABSTRACT FROM AUTHOR]

Simple Summary: This work determines the predictive value of the consensus Immunoscore in 1885 patients with AJCC/UICC-TNM stage I-II Colon Cancer (CC) from North American, European, and Asian care centers. Herein, we demonstrate that the immunity of early-stage CC patients, more than cancer cell-associated parameters, predicts outcome for stage I/II patients. Similar results were found for high-risk patients defined based on parameters such as the grade of differentiation, T4 stage, venous emboli, lymphatic invasion or perineural invasion (VELIPI). Within these pathological risk subgroups, the consensus Immunoscore accurately identifies early-stage CC patients with different clinical outcome, without treatment bias. Thus, the Immunoscore reliably diagnoses low immune cell infiltrated patients at risk of relapse, that would benefit from a more frequent and detailed medical monitoring. The Immunoscore is a patient classification method that can guide treatment decisions, through the quantification of CD3+ and cytotoxic CD8+ T-lymphocytes densities within the tumor and its invasive margin. Background: The prognostic value of Immunoscore was evaluated in Stage II/III colon cancer (CC) patients, but it remains unclear in Stage I/II, and in early-stage subgroups at risk. An international Society for Immunotherapy of Cancer (SITC) study evaluated the pre-defined consensus Immunoscore in tumors from 1885 AJCC/UICC-TNM Stage I/II CC patients from Canada/USA (Cohort 1) and Europe/Asia (Cohort 2). METHODS: Digital-pathology is used to quantify the densities of CD3+ and CD8+ T-lymphocyte in the center of tumor (CT) and the invasive margin (IM). The time to recurrence (TTR) was the primary endpoint. Secondary endpoints were disease-free survival (DFS), overall survival (OS), prognosis in Stage I, Stage II, Stage II-high-risk, and microsatellite-stable (MSS) patients. RESULTS: High-Immunoscore presented with the lowest risk of recurrence in both cohorts. In Stage I/II, recurrence-free rates at 5 years were 78.4% (95%-CI, 74.4–82.6), 88.1% (95%-CI, 85.7–90.4), 93.4% (95%-CI, 91.1–95.8) in low, intermediate and high Immunoscore, respectively (HR (Hi vs. Lo) = 0.27 (95%-CI, 0.18–0.41); p < 0.0001). In Cox multivariable analysis, the association of Immunoscore to outcome was independent (TTR: HR (Hi vs. Lo) = 0.29, (95%-CI, 0.17–0.50); p < 0.0001) of the patient's gender, T-stage, sidedness, and microsatellite instability-status (MSI). A significant association of Immunoscore with survival was found for Stage II, high-risk Stage II, T4N0 and MSS patients. The Immunoscore also showed significant association with TTR in Stage-I (HR (Hi vs. Lo) = 0.07 (95%-CI, 0.01–0.61); P = 0.016). The Immunoscore had the strongest (69.5%) contribution χ2 for influencing survival. Patients with a high Immunoscore had prolonged TTR in T4N0 tumors even for patients not receiving chemotherapy, and the Immunoscore remained the only significant parameter in multivariable analysis. CONCLUSION: In early CC, low Immunoscore reliably identifies patients at risk of relapse for whom a more intensive surveillance program or adjuvant treatment should be considered. [ABSTRACT FROM AUTHOR]

Amplification of chromosome 9p24.1 targeting PD-L1, PD-L2, and JAK2 (PDJ amplicon) is present in subsets of triple negative breast cancers (TNBCs) and is associated with poor clinical outcomes. However, the prevalence of PDJ+ TNBCs varies extensively across studies applying different methods for interrogating samples of interest. To rigorously assess the prevalence of PDJ amplicons in TNBC, its prognostic value and whether it is enriched by chemotherapy, we interrogated 360 TNBC samples including 74 surgical resections from patients treated in the neoadjuvant setting, and tissue microarrays (TMAs) with 31 cases from African American women and 255 resected non-metastatic cases, with a 3 color fluorescence in situ hybridization (FISH) assay targeting the 9p24.1 PDJ amplicon, 9q24.3, and 9q34.1. Samples with mean PDJ signal of > 4.5 copies, and ratios of PDJ/9q24 ≥ 2 and/or PDJ/9q34.1 ≥ 2 were called amplified (PDJ+). Correlative analyses included the association of tumor infiltrating lymphocytes (TILs) with PDJ amplicons in TNBCs. In addition, we investigated intratumor copy number of PDJ amplicons in PDJ+ and PDJ− TNBCs. Matched pre- and post-neoadjuvant treatment biopsies were available from patients (n = 6) to evaluate the effects of therapy on PDJ status. Our study provides a rigorous analysis of the prevalence, distribution, and clinical correlatives of the PDJ amplicon in TNBC. [ABSTRACT FROM AUTHOR]

Background: Immune interactions play important roles in the regulation of T cells' cytotoxic function, further impacting the anti-tumor efficacy of immunotherapy. A comprehensive analysis of immune cell types in HCC and immune-cell-related signatures predicting prognosis and monitoring immunotherapy efficacy is still absent. Methods: More than 1,300 hepatocellular carcinomas (HCC) patients were collected from public databases and included in the present study. The ssGSEA algorithm was applied to calculate the infiltration level of 28 immunocyte subpopulations. A cell pair algorithm was applied to construct an immune-cell-related prognostic index (ICRPI). Survival analyses were performed to measure the survival difference across ICRPI risk groups. Spearman's correlation analyses were used for the relevance assessment. A Wilcoxon test was used to measure the expression level's differences. Results: In this study, 28 immune subpopulations were retrieved, and 374 immune cell pairs (ICPs) were established, 38 of which were picked out by the least absolute shrinkage and selection operator (LASSO) algorithm. By using the selected ICPs, the ICRPI was constructed and validated to play crucial roles in survival stratification and dynamic monitoring of immunotherapy effect. We also explored several candidate drugs targeting ICRPI. A composite ICRPI and clinical prognostic index (ICPI) was then constructed, which achieved a more accurate estimation of HCC's survival and is a better choice for prognosis predictions in HCC. Conclusions: In conclusion, we constructed and validated ICRPI based on the cell pair algorithm in this study, which might provide some novel insights for increasing the survival estimation and clinical response to immune therapy for individual HCC patients and contribute to the personalized precision immunotherapy strategy of HCC. [ABSTRACT FROM AUTHOR]

Simple Summary: Short, dysfunctional telomeres represent the genetic biomarkers of cancer. Studies in early-stage non-small-cell lung cancer (NSCLC) have shown that telomere length and telomerase levels are correlated with survival. In patients with advanced NSCLC, telomere status has not yet been investigated, and its clinical significance remains unknown. We studied telomere length and the expression of telomerase and shelterin genes in a cohort of 79 patients with advanced NSCLC, and evaluated these parameters as potential prognostic and predictive factors. Telomere shortening, high levels of telomerase and aberrant expression of shelterin genes TRF2, RAP1 and TIN2 were significantly correlated with shorter survival. Furthermore, a worse response to immunotherapy was observed in patients with shorter telomeres. The determination of telomere parameters in advanced NSCLC could be useful for individualized treatment decisions. Telomere length appears to correlate with survival in early non-small-cell lung cancer (NSCLC), but the prognostic impact of telomere status in advanced NSCLC remains undetermined. Our purpose was to evaluate telomere parameters as prognostic and predictive biomarkers in advanced NSCLC. In 79 biopsies obtained before treatment, we analyzed the telomere length and expression of TERT and shelterin complex genes (TRF1, TRF2, POT1, TPP1, RAP1, and TIN2), using quantitative PCR. Non-responders to first-line chemotherapy were characterized by shorter telomeres and low RAP1 expression (p = 0.0035 and p = 0.0069), and tended to show higher TERT levels (p = 0.058). In multivariate analysis, short telomeres were associated with reduced event-free (EFS, p = 0.0023) and overall survival (OS, p = 0.00041). TERT and TRF2 overexpression correlated with poor EFS (p = 0.0069 and p = 0.00041) and OS (p = 0.0051 and p = 0.007). Low RAP1 and TIN2 expression-levels were linked to reduced EFS (p = 0.00032 and p = 0.0069) and OS (p = 0.000051 and p = 0.02). Short telomeres were also associated with decreased survival after nivolumab therapy (p = 0.097). Evaluation of telomere status in advanced NSCLC emerges as a useful biomarker that allows for the selection of patient groups with different clinical evolutions, to establish personalized treatment. [ABSTRACT FROM AUTHOR]

Background: The tumor immune microenvironment (TIME) of adrenocortical carcinoma (ACC) is heterogeneous. However, a classification of ACC based on the TIME remains unexplored. Methods: We hierarchically clustered ACC based on the enrichment levels of twenty-three immune signatures to identify its immune-specific subtypes. Furthermore, we comprehensively compared the clinical and molecular profiles between the subtypes. Results: We identified two immune-specific subtypes of ACC: Immunity-H and Immunity-L, which had high and low immune signature scores, respectively. We demonstrated that this subtyping method was stable and reproducible by analyzing five different ACC cohorts. Compared with Immunity-H, Immunity-L had lower levels of immune cell infiltration, worse overall and disease-free survival prognosis, and higher tumor stemness, genomic instability, proliferation potential, and intratumor heterogeneity. Furthermore, the ACC driver gene CTNNB1 was more frequently mutated in Immunity-L than in Immunity-H. Several proteins, such as mTOR, ERCC1, Akt, ACC1, Cyclin_E1, β-catenin, FASN, and GAPDH, were more highly expressed in Immunity-L than in Immunity-H. In contrast, p53, Syk, Lck, PREX1, and MAPK were more highly expressed in Immunity-H. Pathway and gene ontology analysis showed that the immune, stromal, and apoptosis pathways were highly enriched in Immunity-H, while the cell cycle, steroid biosynthesis, and DNA damage repair pathways were highly enriched in Immunity-L. Conclusions: ACC can be classified into two stable immune-related subtypes, which have significantly different antitumor responses, molecular characteristics, and clinical outcomes. This subtyping may provide clinical implications for prognostic and immunotherapeutic stratification of ACC. [ABSTRACT FROM AUTHOR]

Maintenance in small hydroelectric plants (SHPs) is essential for securing the expansion of clean energy sources and supplying the energy estimated to be required for the coming years. Identifying failures in SHPs before they happen is crucial for allowing better management of asset maintenance, lowering operating costs, and enabling the expansion of renewable energy sources. Most fault prognosis models proposed thus far for hydroelectric generating units are based on signal decomposition and regression models. In the specific case of SHPs, there is a high occurrence of data being censored, since the operation is not consistently steady and can be repeatedly interrupted due to transmission problems or scarcity of water resources. To overcome this, we propose a two-step, data-driven framework for SHP prognosis based on time series feature engineering and survival modeling. We compared two different strategies for feature engineering: one using higher-order statistics and the other using the Tsfresh algorithm. We adjusted three machine learning survival models—CoxNet, survival random forests, and gradient boosting survival analysis—for estimating the concordance index of these approaches. The best model presented a significant concordance index of 77.44%. We further investigated and discussed the importance of the monitored sensors and the feature extraction aggregations. The kurtosis and variance were the most relevant aggregations in the higher-order statistics domain, while the fast Fourier transform and continuous wavelet transform were the most frequent transformations when using Tsfresh. The most important sensors were related to the temperature at several points, such as the bearing generator, oil hydraulic unit, and turbine radial bushing. [ABSTRACT FROM AUTHOR]

Background and objective: The prognostic value of age and other non-hematological factors in predicting outcomes in older patients with newly diagnosed acute myeloid leukemia (AML) undergoing antileukemic therapy is not well understood. We performed a systematic review to determine the association between these factors and mortality and health-related quality of life or fatigue among these patients. Methods: We searched Medline and Embase through October 2021 for studies in which researchers quantified the relationship between age, comorbidities, frailty, performance status, or functional status; and mortality and health-related quality of life or fatigue in older patients with AML receiving antileukemic therapy. We assessed the risk of bias of the included studies using the Quality in Prognostic Studies tool, conducted random-effects meta-analyses, and assessed the quality of the evidence using the Grading of Recommendations, Assessment, Development and Evaluation approach. Results: We included 90 studies. Meta-analysis showed that age (per 5-year increase, HR 1.16 95% CI 1.11–1.21, high-quality evidence), comorbidities (Hematopoietic Cell Transplantation-specific Comorbidity Index: 3+ VS less than 3, HR 1.60 95% CI 1.31–1.95, high-quality evidence), and performance status (Eastern Cooperative Oncology Group/ World Health Organization (ECOG/WHO): 2+ VS less than 2, HR 1.63 95% CI 1.43–1.86, high-quality evidence; ECOG/WHO: 3+ VS less than 3, HR 2.00 95% CI 1.52–2.63, moderate-quality evidence) were associated with long-term mortality. These studies provided inconsistent and non-informative results on short-term mortality (within 90 days) and quality of life. Conclusion: High-quality or moderate-quality evidence support that age, comorbidities, performance status predicts the long-term prognosis of older patients with AML undergoing antileukemic treatment. [ABSTRACT FROM AUTHOR]

Background: We evaluated three-dimensional speckle tracking echocardiography (3DSTE) strain and cardiac magnetic resonance (CMR) with delayed contrast enhancement (DCE) for the prediction of cardiac events in left ventricular (LV) dysfunction. Methods: CMR and 3DSTE in 75 patients with ischaemic and 38 with non-ischaemic LV dysfunction were analysed and temporally correlated to cardiac events during 41 ± 9 months of follow-up. Results: Cardiac events occurred in 44 patients, more in patients with ischaemic LV dysfunction. LV ejection fraction (LVEF), global circumferential and global area strain were reduced more in patients with more cardiac events, whereas 3DSTE LV end-systolic volumes and 3DSTE LV masses were larger. However, the area under the curve using receiver-operating characteristic analysis showed modest sensitivity and specificity for all evaluated parameters. Additionally, DCE did not differ significantly between the two groups. Univariate analysis showed ischaemic aetiology of LV dysfunction, LVEF and LV mass by CMR to be predictors of cardiac events with an increased relative risk of 2.4, 1.6 and 1.5, respectively. By multivariate analysis, only myocardial ischaemia and LVEF ≤ 39% were independent predictors of events (p = 0.004 and 0.005, respectively). Subgroup analysis in ischaemic and non-ischaemic patients showed only 3DSTE LV mass in ischaemic patients to have a significant association (p = 0.033) but without an increased relative risk. Conclusion: LVEF calculated by 3DSTE or CMR were both good predictors of cardiac events in patients with LV dysfunction. A reduced LVEF ≤ 39% was associated with a 1.6-fold higher probability of a cardiac event. 3DSTE strain measurements and DCE-CMR did not add to the prognostic value of LVEF. [ABSTRACT FROM AUTHOR]

Background: The expression of INMT (indolethylamine N-methyltransferase) has been reported to be downregulated in non-small-cell lung cancer (NSCLC). However, the role of INMT in NSCLC remains elusive. We aim to investigate the underlying mechanisms and clinical value of INMT in NSCLC, especially in lung adenocarcinoma (LUAD). Methods: Gene expression cohorts from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to assess the effect of INMT on NSCLC. Gene expression data from an immunotherapy cohort were used to investigate the association of INMT with immunotherapy in NSCLC. Results: INMT expression was significantly downregulated in NSCLC compared with adjacent normal tissues. Downregulated INMT was associated with poor overall survival in LUAD, but not in lung squamous carcinoma. Multivariate Cox regression analysis suggested that INMT was an independent prognostic marker in LUAD. INMT had a reference value in the diagnosis and prognostic estimation of LUAD. Gene set enrichment analysis showed that pathways of the cell cycle and DNA damage response were enriched in the INMT low-expression group. The top 10 hub genes upregulated in the INMT low-expression group mainly activated the cell cycle pathway. In addition, more frequently mutated TP53 genes, higher aneuploidy scores, a fraction of genomes altered, MANTIS scores, and tumor mutation burden were found in tumors with low expression of INMT. Furthermore, patients with low expression of INMT showed favorable clinical benefits to anti-PD-1 treatment with higher enrichment scores of immune-related signatures. Conclusion: The low expression of INMT was associated with poor prognosis but favorable immunotherapy response in LUAD. INMT may affect the progression of LUAD by regulating the cell cycle and may serve as a valuable independent prognostic biomarker in patients with LUAD. [ABSTRACT FROM AUTHOR]

Purpose: The relationship with endothelial activation and stress index (EASIX), which represents the degree of endothelial dysfunction, is unwell known in upper tract urothelial carcinoma (UTUC). The present study aims to assess the prognostic value of the EASIX for recurrence-free survival (RFS) and overall survival (OS) in patients with UTUC who underwent radical nephroureterectomy (RNU). Materials and Methods: We retrospectively reviewed the clinical data of 627 patients with UTUC who underwent RNU without neoadjuvant chemotherapy at three hospitals between 2002 and 2019. EASIX scores were calculated using the formula "serum lactate dehydrogenase (U/L)×creatinine (mg/dL)/platelet count (109/L)" and evaluated based on log2-transformed values. We divided the patients according to the EASIX score (>1.27 vs. ≤1.27). Results: Among 627 patients, 380 were finally analyzed. Using maximally selected log-rank statistics, the optimal EASIX cutoff value was 1.27 on the log2 scale. The baseline characteristics were similar between the two groups except for age. The high EASIX score group had worse RFS and OS than the low EASIX score group (log-rank p=0.001 and p=0.006, respectively). At 5 years, the mean RFS and OS difference between the low and high EASIX score groups was 11.1 and 7.35 months, respectively. High EASIX score remained a key prognosticator of RFS and OS after RNU in multivariable analysis. Conclusions: EASIX score may represent endothelial dysfunction in patients with UTUC and may serve as a readily available prognostic factor for oncologic outcomes. [ABSTRACT FROM AUTHOR]