Risk Score Groups Research Articles

FOXP3-based immune risk model for recurrence prediction in small-cell lung cancer at stages I–III

BackgroundImmunotherapies may prolong the survival of patients with small-cell lung cancer (SCLC) to some extent. The role of forkhead box protein P3 (FOXP3) in tumor microenvironment (TME) remains controversial. We...

Genomic Analysis of Glioblastoma Multiforme Reveals a Key Transcription Factor Signature Relevant to Prognosis and the Immune Processes.

IntroductionGlioblastoma multiforme (GBM) develops through the accumulation of both genetic and expression alterations. Although many gene signatures have been developed as prognostic and predictive biomarkers, their robustness and functional aspects are less well characterized. The expression of most genes is regulated by transcription factors (TFs); therefore, we aimed to investigate a TF signature relevant to GBM prognosis.MethodsWe used bioinformatic methods and data from public databases to establish four clusters of key TF genes, among which cluster 1, comprising 24 TFs, showed significant prognostic value. Further in silico functional analyses were applied to investigate the utility of the TF signature.ResultsDifferent mutation and copy number variation patterns were observed between different risk score groups (based on the TF signature). In silico analyses suggested that the cases with relative high risk scores were involved in immune and inflammatory processes or pathways.ConclusionThe TF signature has significant prognostic value in different cohorts or subgroups of patients with GBM and could lead to the development immunotherapy for GBM.

Performance of a cardiac lipid panel compared to four prognostic scores in chronic heart failure

The cardiac lipid panel (CLP) is a novel panel of metabolomic biomarkers that has previously shown to improve the diagnostic and prognostic value for CHF patients. Several prognostic scores have been developed for cardiovascular disease risk, but their use is limited to specific populations and precision is still inadequate. We compared a risk score using the CLP plus NT-proBNP to four commonly used risk scores: The Seattle Heart Failure Model (SHFM), Framingham risk score (FRS), Barcelona bio-HF (BCN Bio-HF) and Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) score. We included 280 elderly CHF patients from the Cardiac Insufficiency Bisoprolol Study in Elderly trial. Cox Regression and hierarchical cluster analysis was performed. Integrated area under the curves (IAUC) was used as criterium for comparison. The mean (SD) follow-up period was 81 (33) months, and 95 (34%) subjects met the primary endpoint. The IAUC for FRS was 0.53, SHFM 0.61, BCN Bio-HF 0.72, MAGGIC 0.68, and CLP 0.78. Subjects were partitioned into three risk clusters: low, moderate, high with the CLP score showing the best ability to group patients into their respective risk cluster. A risk score composed of a novel panel of metabolite biomarkers plus NT-proBNP outperformed other common prognostic scores in predicting 10-year cardiovascular death in elderly ambulatory CHF patients. This approach could improve the clinical risk assessment of CHF patients.

Correlation of Likert scores III–V with increasingly worse pathology in radical prostatectomy specimens significant only for men aged <60 or PSAD >0.15, with age <60 as good as PSAD <0.15 at discriminating lower risk in Likert III

Objectives: This study aimed to compare Likert scores with radical prostatectomy specimens. Methods: This study examined 443 men with validated pre-biopsy magnetic resonance imaging results and used cross-tabulation and chi-square significance testing with National Comprehensive Cancer Network risk categories. Results: The mean prostate-specific antigen (PSA) was 10, and the mean age was 64 years. Comparing Likert III to Likert V and Likert IV to Likert V, both (each p=0.02) were significantly associated with higher prostate cancer risk groups, but Likert III versus Likert IV was not ( p=0.1). Within the subgroup PSA density (PSAD) <0.15 ( n=140), the correlation of Likert score and final pathological risk group was lost ( p=0.5), but it was not lost within the subgroup PSAD >0.15 ( n=281; p=0.045 III vs. IV only and p=0.055 overall). Within the subgroup age <60 ( n=104), the correlation of Likert score and final pathological risk group was significant ( p=0.006 for III vs. IV and p=0.04 overall), whereas within the subgroup age >60 ( n=339) this significant difference was lost ( p=0.34). Further subgroup analysis within Likert III ( n=86) found that men <60 ( n=22) had neither high-grade (G3 or G4 or G5) nor very high-risk disease. There were only two high-risk cases, both of which were G2T3a (2/22; 10%). In men with Likert III and PSAD <0.15 ( n=31), there were seven high-risk and two very high-risk cases (9/31; 25%). This difference was not significant ( p=0.31) Conclusion: With these two findings, we recommend that men <60 with Likert III can be counselled like men with Likert III and PSAD <0.15, that they are unlikely to have unfavourable or high-risk disease and that they may wish to avoid biopsy or treatment. Level of evidence: Level 1b.

The Clinical Utility of DCISionRT\xae on Radiation Therapy Decision Making in Patients with Ductal Carcinoma In Situ Following Breast-Conserving Surgery

BackgroundThe role of radiation therapy (RT) following breast-conserving surgery (BCS) in ductal carcinoma in situ (DCIS) remains controversial. Trials have not identified a low-risk cohort, based on clinicopathologic features, who do not benefit from RT. A biosignature (DCISionRT®) that evaluates recurrence risk has been developed and validated. We evaluated the impact of DCISionRT on clinicians’ recommendations for adjuvant RT.MethodsThe PREDICT study is a prospective, multi-institutional, observational registry in which patients underwent DCISionRT testing. The primary endpoint was to identify the percentage of patients where testing led to a change in RT recommendations.ResultsOverall, 539 women were included in this study. Pre DCISionRT testing, RT was recommended to 69% of patients; however, post-testing, a change in the RT recommendation was made for 42% of patients compared with the pre-testing recommendation; the percentage of women who were recommended RT decreased by 20%. For women initially recommended not to receive an RT pre-test, 35% had their recommendation changed to add RT following testing, while post-test, 46% of patients had their recommendation changed to omit RT after an initial recommendation for RT. When considered in conjunction with other clinicopathologic factors, the elevated DCISionRT score risk group (DS > 3) had the strongest association with an RT recommendation (odds ratio 43.4) compared with age, grade, size, margin status, and other factors.ConclusionsDCISionRT provided information that significantly changed the recommendations to add or omit RT. Compared with traditional clinicopathologic features used to determine recommendations for or against RT, the factor most strongly associated with RT recommendations was the DCISionRT result, with other factors of importance being patient preference, tumor size, and grade.

Background Parenchymal Enhancement on Breast MRI as a Prognostic Surrogate: Correlation With Breast Cancer Oncotype Dx Score.

PurposeBreast MRI background parenchymal enhancement (BPE) can potentially serve as a prognostic marker, by possible correlation with molecular subtype. Oncotype Dx, a gene assay, is a prognostic and predictive surrogate for tumor aggressiveness and treatment response. The purpose of this study was to investigate the association between contralateral non-tumor breast magnetic resonance imaging (MRI) background parenchymal enhancement and tumor oncotype score.MethodsIn this retrospective study, patients with ER+ and HER2− early stage invasive ductal carcinoma who underwent preoperative breast MRI, oncotype risk scoring, and breast conservation surgery from 2008–2010 were identified. After registration, BPE from the pre and three post-contrast phases was automatically extracted using a k-means clustering algorithm. Four metrics were calculated: initial enhancement (IE) relative to the pre-contrast signal, late enhancement, overall enhancement (OE), and area under the enhancement curve (AUC). Histogram analysis was performed to determine first order metrics which were compared to oncotype risk score groups using Mann–Whitney tests and Spearman rank correlation analysis.ResultsThis study included 80 women (mean age = 51.1 ± 10.3 years); 46 women were categorized as low risk (≤17) and 34 women were categorized as intermediate/high risk (≥18) according to Oncotype Dx. For the mean of the top 10% pixels, significant differences were noted for IE (p = 0.032), OE (p = 0.049), and AUC (p = 0.044). Using the risk score as a continuous variable, correlation analysis revealed a weak but significant correlation with the mean of the top 10% pixels for IE (r = 0.26, p = 0.02), OE (r = 0.25, p = 0.02), and AUC (r = 0.27, p = 0.02).ConclusionBPE metrics of enhancement in the non-tumor breast are associated with tumor Oncotype Dx recurrence score, suggesting that the breast microenvironment may relate to likelihood of recurrence and magnitude of chemotherapy benefit.

Mitotic Activity in Gastrointestinal Stromal Tumors: Can we use Phosphohistone H3 Immunohistochemistry Instead of Hematoxylin and Eosin for Mitotic Count?

ObjectivesIn gastrointestinal stromal tumors (GIST), malignancy potential is determined by the prognostic disease risk stratification based on mitosis, tumor size, and location. Phosphohistone H3 (PHH3) is an immunohistochemical marker showing mitotic activity in cells. In this study, we aimed to evaluate mitosis in GIST with PHH3, compare the results with hematoxylin and eosin (HE) stained slides, and examine its relationship with other prognostic data.MethodsClinicopathological findings and survival were determined in GIST cases diagnosed between 2006 and 2017. The prognostic risk score was calculated according HE- and PHH3-based mitosis. The cases were classified as Group I: HE + and PHH3 + and Group II: HE + and PHH3–. They were also grouped as those diagnosed before and after 2012 and the staining results of HE and PHH3 were re-analyzed.ResultsNinety-eight cases were included in the study. Mitosis was detected with both HE and PHH3 in 63.3% of the cases (62/98 cases) (Group I) while in 36.7% of cases, it was detected with HE but not with PHH3 (Group II). In only two cases, the risk score changed with PHH3 (very low → intermedier grade). The ratio of HE + and PHH3 + cases in 2012 and after was significantly higher than HE + and PHH3 – cases. A statistically significant relation was found between HE- and PHH3-based risk scores (p<0.05). There was a significant difference between HE-based risk score groups in terms of survival (p<0.05), while no difference was observed between the PHH3-based risk score groups (p>0.05).ConclusionIn GIST cases, PHH3 can be used to determine mitosis in more recent blocks, taking into account the technical conditions of the laboratory, but it does not seem to be superior to mitosis detected by HE. Research should continue on new survival determinants for GIST.

A novel long non-coding RNA-based prognostic signature for renal cell carcinoma patients with stage IV and histological grade G4

ABSTRACT This study aimed to establish a lncRNA-based signature for predicting the prognosis of patients with high stage and grade renal cell carcinoma (RCC). According to the Surveillance, Epidemiology, and End Results (SEER) database, sex, age, grade, stage, surgery, chemotherapy, radiation, tumor size, and marital status were the independent prognostic factors for RCC and also had significant correlations with the overall survival through Cox univariate and multivariate analyses. Noticeably, among these influencing factors, the histological classification of undifferentiated group and pathological stage IV had the greatest prognostic risks for RCC patients. Furthermore, based on the samples at stage IV and histological grade G4 from The Cancer Genome Atlas (TCGA) portal, 9 key lncRNAs, including KIAA2012, CCNT2-AS1, ITPKB-AS1, TBX2-AS1, NUTM2A-AS1, LINC02522, LINC02384, LINC01559, and LINC00865 were identified and a prognostic signature was constructed by Lasso analysis and Cox regression model. The Kaplan-Meier analysis suggested that patients at stage IV and histological grade of G4 in high risk score group had a worse overall survival than that in low risk score group. The following receiver operating characteristic curve (ROC) curves also showed that this signature possesses a better predictive power performance. Pathway enrichment analysis discovered that 9 lncRNAs held potential roles in cell division, cell cycle, DNA damage and cytokines levels in RCC. This work indicates that the established 9-lncRNA signature has a good capacity in predicting the prognosis of RCC patients with stage IV and histological grade of G4, and may be helpful for guiding the treatment strategies for RCC patients.

R29 Hospital Resource Use and Costs of Isolated Aortic Valve Replacement Procedures in Patients with aortic stenosis, by STS risk scores in New South Wales, Australia

To estimate Australian health-system costs for TAVI compared with isolated SAVR, by Society of Thoracic Surgery (STS) risk score groups.

Discovery of tumor immune infiltration-related snoRNAs for predicting tumor immune microenvironment status and prognosis in lung adenocarcinoma

Lung adenocarcinoma (LUAD) has a high mortality rate and is difficult to diagnose and treat in its early stage. Previous studies have demonstrated that small nucleolar RNAs (snoRNAs) play a critical role in tumor immune infiltration and the development of a variety of solid tumors. However, there have been no studies on the correlation between tumor-infiltrating immune-related snoRNAs (TIISRs) and LUAD.In this study, we filtered six immune-related snoRNAs based on the tissue specificity index (TSI) and expression profile of all snoRNAs between all LUAD cell lines from the Cancer Cell Line Encyclopedia and 21 types of immune cells from the Gene Expression Omnibus database. Further, we performed real-time quantitative polymerase chain reaction (RT-qPCR) to validate the expression status of these snoRNAs on peripheral blood mononuclear cells (PBMCs) and lung cancer cell lines. Next, we developed a TIISR signature based on the expression profiles of snoRNAs from 479 LUAD patients filtered by the random survival forest algorithm. We then analyzed the value of this TIISR signature (TIISR risk score) for assessing tumor immune infiltration, immune checkpoint inhibitor (ICI) treatment response, and the prognosis of LUAD between groups with high and low TIISR risk score. Further, we found that the TIISR risk score groups showed significant differences in biological characteristics and that the risk score could be used to assess the level of tumor immune cell infiltration, thereby predicting prognosis and responsiveness to immunotherapy in LUAD patients.

A bioinformatics analysis to evaluate the prognostic value of stemness-related genes in gastric cancer.

BackgroundThis study aimed to identify potential stemness-related targets in gastric cancer (GC) in order to support the development of new treatment strategies and improve patient survival.MethodsUsing the edgeR package, we identified stemness-related differentially expressed genes (DEGs) using GSE112631 and the stemness-related signaling pathways in the Gene Set Enrichment Analysis (GSEA) database. Lasso-penalized Cox regression analysis and multivariate Cox regression analysis tested by Akaike Information Criterion (AIC) were used to screen out survival genes in order to construct a prognostic model. We verified the accuracy of our prognostic model using a nomogram and receiver operating characteristic (ROC) curve analysis. Patients were divided into two groups based on the median risk score, and functional enrichment analysis was used to explore the differences between the two groups.ResultsEight genes were selected to establish a prognostic model of The Cancer Genome Atlas (TCGA) and a validation model of the GSE84437 dataset from the Genome Expression Omnibus (GEO). In both models, we found that the low risk score group had better overall survival (OS) than the high-risk score group. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways between the two risk groups were totally different.ConclusionsWe used eight stemness-related genes to build a prognostic model. The high-risk score group had a worse prognosis compared to the low-risk score group.

Six Immune Associated Genes Construct Prognostic Model Evaluate Low-Grade Glioma.

BackgroundThe immunotherapy of Glioma has always been a research hotspot. Although tumor associated microglia/macrophages (TAMs) proves to be important in glioma progression and drug resistance, our knowledge about how TAMs influence glioma remains unclear. The relationship between glioma and TAMs still needs further study.MethodsWe collected the data of TAMs in glioma from NCBI Gene Expression Omnibus (GEO) that included 20 glioma samples and 15 control samples from four datasets. Six genes were screened from the Differential Expression Gene through Gene ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, protein–protein interaction (PPI) network and single-cell sequencing analysis. A risk score was then constructed based on the six genes and patients’ overall survival rates of 669 patients from The Cancer Genome Atlas (TCGA). The efficacy of the risk score in prognosis and prediction was verified in Chinese Glioma Genome Atlas (CGGA).ResultsSix genes, including CD163, FPR3, LPAR5, P2ry12, PLAUR, SIGLEC1, that participate in signal transduction and plasma membrane were selected. Half of them, like CD163, FPR3, SIGLEC1, were mainly expression in M2 macrophages. FPR3 and SIGLEC1 were high expression genes in glioma associated with grades and IDH status. The overall survival rates of the high risk score group was significantly lower than that of the low risk score group, especially in LGG.ConclusionJoint usage of the 6 candidate genes may be an effective method to diagnose and evaluate the prognosis of glioma, especially in Low-grade glioma (LGG).

An Eight-CircRNA Assessment Model for Predicting Biochemical Recurrence in Prostate Cancer.

Prostate cancer (PCa) is a high morbidity malignancy in males, and biochemical recurrence (BCR) may appear after the surgery. Our study is designed to build up a risk score model using circular RNA sequencing data for PCa. The dataset is from the GEO database, using a cohort of 144 patients in Canada. We removed the low abundance circRNAs (FPKM < 1) and obtained 546 circRNAs for the next step. BCR-related circRNAs were selected by Logistic regression using the “survival” and “survminer” R package. Least absolute shrinkage and selector operation (LASSO) regression with 10-fold cross-validation and penalty was used to construct a risk score model by “glmnet” R software package. In total, eight circRNAs (including circ_30029, circ_117300, circ_176436, circ_112897, circ_112897, circ_178252, circ_115617, circ_14736, and circ_17720) were involved in our risk score model. Further, we employed differentially expressed mRNAs between high and low risk score groups. The following Gene Ontology (GO) analysis were visualized by Omicshare Online tools. As per the GO analysis results, tumor immune microenvironment related pathways are significantly enriched. “CIBERSORT” and “ESTIMATE” R package were used to detect tumor-infiltrating immune cells and compare the level of microenvironment scores between high and low risk score groups. What’s more, we verified two of eight circRNA’s (circ_14736 and circ_17720) circular characteristics and tested their biological function with qPCR and CCK8 in vitro. circ_14736 and circ_17720 were detected in exosomes of PCa patients’ plasma. This is the first bioinformatics study to establish a prognosis model for prostate cancer using circRNA. These circRNAs were associated with CD8+ T cell activities and may serve as a circRNA-based liquid biopsy panel for disease prognosis.

Identification of an Immune-Related Gene Signature Based on Immunogenomic Landscape Analysis to Predict the Prognosis of Adult Acute Myeloid Leukemia Patients.

Acute myeloid leukemia (AML) is a hematopoietic malignancy characterized by highly heterogeneous molecular lesions and cytogenetic abnormalities. Immune disorders in AML and impaired immune cell function have been found to be associated with abnormal karyotypes in AML patients. Immunotherapy has become an alternative therapeutic method that can improve the outcomes of AML patients. For solid tumors, the expression patterns of genes associated with the immune microenvironment provide valuable prognostic information. However, the prognostic roles of immune genes in AML have not been studied as yet. In this study, we identified 136 immune-related genes associated with overall survival in AML patients through a univariate Cox regression analysis using data from TCGA-AML and GTEx datasets. Next, we selected 24 hub genes from among the 136 genes based on the PPI network analysis. The 24 immune-related hub genes further underwent multivariate Cox regression analysis and LASSO regression analysis. Finally, a 6 immune-related gene signature was constructed to predict the prognosis of AML patients. The function of the hub IRGs and the relationships between hub IRGs and transcriptional factors were investigated. We found that higher levels of expression of CSK, MMP7, PSMA7, PDCD1, IKBKG, and ISG15 were associated with an unfavorable prognosis of AML patients. Meanwhile, patients in the TCGA-AML datasets were divided into a high risk score group and a low risk score group, based on the median risk score value. Patients in the high risk group tended to show poorer prognosis [P = 0.00019, HR = 1.89 (1.26–2.83)]. The area under the curve (AUC) was 0.6643. Multivariate Cox Regression assay confirmed that the 6 IRG signature was an independent prognostic factor for AML. The prognostic role of the immune related-gene signature was further validated using an independent AML dataset, GSE37642. In addition, patients in the high risk score group in the TCGA dataset were found to be of an advanced age, IDH mutation, and M5 FAB category. These results suggested that the proposed immune related-gene signature may serve as a potential prognostic tool for AML patients.

A Novel RNA-Binding Protein-Based Nomogram for Predicting Survival of Patients with Gastric Cancer.

BackgroundWe attempted to develop a prognostic model and characterize molecular subtypes for gastric cancer on the basis of ribonucleic acid (RNA)-binding proteins (RBPs).Material/MethodsRNA sequence data of gastric cancer were obtained from The Cancer Genome Atlas. Univariate Cox regression analysis was used to screen survival-related RBPs, followed by least absolute shrinkage and selection operator Cox modeling. Overall and stratified survival analysis was carried out between high and low risk score groups, followed by receiver operator characteristic curve construction. Univariate and multivariate survival analysis was applied to assess its independent prognostic potential. A nomogram was constructed by combining age and the risk score, which was verified by calibration curves and decision curve analyses for 1-, 3-, and 5-year survival. Molecular subtypes were identified using nonnegative matrix factorization method. Clinical features of the identified subtypes were characterized on prognosis, drug sensitivity, and immune infiltration. An external Gene Expression Omnibus dataset was used to verify the above findings.ResultsOn the basis of 44 survival-related RBPs, a robust prognostic 15-RBP signature was constructed. Patients with high risk score had a poorer prognosis than those with low risk score. The risk score had good performance in predicting clinical outcomes for 1-, 3-, and 5-year survival. The signature was effectively independent of other clinical features. The nomogram model combining age and the 15-RBP prognostic model exhibited better practicality and reliability for prognosis. RBP expression data were utilized to define 2 distinct molecular subtypes obviously related to survival outcomes, chemotherapeutic drug sensitivity, and immune infiltration.ConclusionsOur study provides a nomogram model that consists of age and a 15-RBP signature and identifies 2 molecular subtypes for gastric cancer that possess potential value for preclinical, clinical, and translational research on gastric cancer.

Identification of immune-related genes as prognostic factors in bladder cancer

Bladder cancer is one of the most common cancers worldwide. The immune response and immune cell infiltration play crucial roles in tumour progression. Immunotherapy has delivered breakthrough achievements in the past decade in bladder cancer. Differentially expressed genes and immune-related genes (DEIRGs) were identified by using the edgeR package. Gene ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed for functional enrichment analysis of DEIRGs. Survival-associated IRGs were identified by univariate Cox regression analysis. A prognostic model was established by univariate COX regression analysis, and verified by a validation prognostic model based on the GEO database. Patients were divided into high-risk and low-risk groups based on the median risk score value for immune cell infiltration and clinicopathological analyses. A regulatory network of survival-associated IRGs and potential transcription factors was constructed to investigate the potential regulatory mechanisms of survival-associated IRGs. Nomogram and ROC curve to verify the accuracy of the model. Quantitative real-time PCR was performed to validate the expression of relevant key genes in the prognostic model. A total of 259 differentially expressed IRGs were identified in the present study. KEGG pathway analysis of IRGs showed that the “cytokine-cytokine receptor interaction” pathway was the most significantly enriched pathway. Thirteen survival-associated IRGs were selected to establish a prognostic index for bladder cancer. In both TCGA prognostic model and GEO validation model, patients with high riskscore had worse prognosis compared to low riskscore group. A high infiltration level of macrophages was observed in high-risk patients. OGN, ELN, ANXA6, ILK and TGFB3 were identified as hub survival-associated IRGs in the network. EBF1, WWTR1, GATA6, MYH11, and MEF2C were involved in the transcriptional regulation of these survival-associated hub IRGs. The present study identified several survival-associated IRGs of clinical significance and established a prognostic index for bladder cancer outcome evaluation for the first time.

Development and validation of a nomogram in survival prediction among advanced breast cancer patients

BackgroundThe overall survival (OS) among patients with advanced breast cancer (ABC) varies greatly. Although molecular subtype is known as the most important factor in OS differentiation, significant differences in OS among patients with the same molecular subtype still occur, leading to the need for a more accurate prognostic prediction model. This study aimed to develop a prediction model (nomogram) based on current diagnosis and treatment to predict the OS of newly diagnosed ABC patients in China.MethodsFrom the institution’s database, we collected data of 368 ABC patients from Sun Yat-sen Memorial Hospital (national hospital) as a training set to establish a nomogram with prognostic risk factors that calculated the predicted probability of survival. Nomograms were independently validated with 278 patients with ABC from two other institutions using the concordance index (C-index), calibration plots and risk group stratifications.ResultsThe initial primary tumor stage, molecular subtype, disease-free survival (DFS), presence of brain metastasis, and the tumor burden of metastasis disease (local recurrence, oligo-metastatic disease, or multiple-metastatic disease) were included in the prognostic nomogram. The nomogram had a C-index of 0.77 and 0.71 in the training and the validation sets, respectively. The nomogram was able to stratify patients into different risk groups, respectively (HR 6.81, 95% CI: 4.69 to 9.89, P<0.001). In the lower risk score group (risk score <11), there was no significant difference between the OS with chemotherapy and hormone therapy (HR 0.81, 95% CI: 0.44 to 1.47, P=0.48).ConclusionsWe have constructed a novel prediction nomogram that can guide the physicians to select personalized treatment options. Furthermore, our study is the first to add oligo-metastatic disease and primary endocrine/trastuzumab resistance into the prognostic models.

Primary thromboprophylaxis in ambulatory cancer patients with a high Khorana score: a systematic review and meta-analysis

AbstractGuidelines suggest thromboprophylaxis for ambulatory cancer patients starting chemotherapy with an intermediate to high risk of venous thromboembolism (VTE) according to Khorana score. Data on thromboprophylaxis efficacy in different Khorana score risk groups remain ambiguous. We sought to evaluate thromboprophylaxis in patients with an intermediate- to high-risk (≥2 points) Khorana score and an intermediate-risk score (2 points) or high-risk score (≥3 points) separately. MEDLINE, Embase, and CENTRAL were searched for randomized controlled trials (RCTs) comparing thromboprophylaxis with placebo or standard care in ambulatory cancer patients. Outcomes were VTE, major bleeding, and all-cause mortality. Relative risks (RRs) were calculated in a profile-likelihood random-effects model. Six RCTs were identified, involving 4626 cancer patients. Thromboprophylaxis with direct oral anticoagulants (DOACs) or low molecular weight heparin (LMWH) significantly reduced VTE risk in intermediate- to high-risk (RR, 0.51; 95% confidence interval [CI], 0.34-0.67), intermediate-risk (RR, 0.58; 95% CI, 0.36-0.83), and high-risk patients (RR, 0.45; 95% CI, 0.28-0.67); the numbers needed to treat (NNTs) were 25 (intermediate to high risk), 34 (intermediate risk), and 17 (high risk), respectively. There was no significant difference in major bleeding (RR, 1.06; 95% CI, 0.69-1.67) or all-cause mortality (RR, 0.90; 95% CI, 0.82-1.01). The numbers needed to harm (NNHs) for major bleeding in intermediate- to high-risk, intermediate-risk, and high-risk patients were 1000, −500, and 334, respectively. The overall NNH was lower in DOAC studies (100) versus LMWH studies (−500). These findings indicate thromboprophylaxis effectively reduces the risk of VTE in patients with an intermediate- to high-risk Khorana score, although the NNT is twice as high for intermediate-risk patients compared with high-risk patients.

Protocol for Telehealth Evaluation and Follow-up of Patients With Chronic Heart Failure During the COVID-19 Pandemic

Because of the Coronavirus Disease 2019 (COVID-19) pandemic, we were forced to cancel scheduled visits for nearly 150 patients followed in our heart failure (HF) outpatient clinic. Therefore, we structured a telephone follow-up, developing a standardized 23-item questionnaire from which we obtained the Covid-19-HF score. The questionnaire was built to reproduce our usual clinical evaluation investigating a patient's social and functional condition, mood, adherence to pharmacological and nonpharmacological recommendations, clinical and hemodynamic status, pharmacological treatment, and need to contact emergency services. The score was used as a clinical tool to define patients' clinical stability and timing of the following telephone contact on the basis of the assignment to progressively increasing risk score groups: green (0–3), yellow (4–8), and red (≥9).Here we present our experience applying the score in the first 30 patients who completed the 4-week follow-up, describing baseline clinical characteristics and events that occurred in the period of observation.

Prognostic value of immune related genes in lung adenocarcinoma.

Lung cancer has the highest incidence and mortality rates of all cancers in China. Immune-related genes and immune infiltrating lymphocytes are involved in tumor growth, and in the past decade, immunotherapy has become increasingly important in the treatment of lung cancer. Using the edgeR package, differentially expressed genes and immune-related genes (DEIRGs) were identified in patients with lung adenocarcinoma (LUAD). Functional enrichment analysis of DEIRGs was performed using Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Survival-associated immune-related genes (IRGs) were selected using univariate Cox regression analysis and the prognostic model was assessed using multivariate Cox regression analysis. Overall, 273 DEIRGs were identified in LUAD, and KEGG pathway analysis of IRGs showed that ‘cytokine-cytokine receptor interaction’ was the most significantly enriched pathway. Furthermore, six survival associated IRGs were screened to establish a prognostic model; patients in the high risk score group had less favorable survival times, and the prognostic model was negatively associated with B cell infiltration. The present study established a prognostic model using analysis of survival-related immune-related genes, which were associated with B cell infiltration.