Predicted Survival Probabilities Research Articles

Construction and Validation of a Novel Ferroptosis-Related Prognostic Model for Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is a clonal malignant proliferative blood disorder with a poor prognosis. Ferroptosis, a novel form of programmed cell death, holds great promise for oncology treatment, and has been demonstrated to interfere with the development of various diseases. A range of genes are involved in regulating ferroptosis and can serve as markers of it. Nevertheless, the prognostic significance of these genes in AML remains poorly understood. Transcriptomic and clinical data for AML patients were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Univariate Cox analysis was performed to identify ferroptosis-related genes with prognostic value, and the least absolute shrinkage and selection operator (LASSO) algorithm and stepwise multivariate Cox regression analysis were utilized to optimize gene selection from the TCGA cohort (132 samples) for model construction. Tumor samples from the GEO database (136 samples and 104 samples) were used as validation groups to estimate the predictive performance of the risk model. Finally, an eight-gene prognostic signature (including CHAC1, CISD1, DPP4, GPX4, AIFM2, SQLE, PGD, and ACSF2) was identified for the prediction of survival probability and was used to stratify AML patients into high- and low-risk groups. Survival analysis illustrated significantly prolonged overall survival and lower mortality in the low-risk group. The area under the receiver operating characteristic curve demonstrated good results for the training set (1-year: 0.846, 2-years: 0.826, and 3-years: 0.837), which verified the accuracy of the model for predicting patient survival. Independent prognostic analysis indicated that the model could be used as a prognostic factor (p ≤ 0.001). Functional enrichment analyses revealed underlying mechanisms and notable differences in the immune status of the two risk groups. In brief, we conducted and validated a novel ferroptosis-related prognostic model for outcome prediction and risk stratification in AML, with great potential to guide individualized treatment strategies in the future.

Clinical effects of durability of immunosuppression in virologically suppressed ART-initiating persons with HIV in Latin America. A retrospective cohort study

SummaryBackgroundClinical outcomes are rarely studied in virologically suppressed people living with HIV (PWH) and incomplete CD4 recovery. To explore whether time living with severe immunosuppression predict clinical outcomes better than baseline or time updated CD4, we estimated the association between cumulative percentage of time with CD4 <200 cells/μL during viral suppression (VS) (%tCD4<200), and mortality and comorbidities during 2000–2019.MethodsIn a retrospective cohort analysis, we followed PWH initiating ART in Latin America from first VS (HIV-RNA<200 copies/μL) to death, virological failure or loss to follow-up. We fit Cox models to estimate risk of death and/or AIDS-defining and serious non-AIDS-defining events (ADE and SNADE -cancer, cardiovascular, liver, and renal diseases) by %tCD4<200 (continuous variable). We predicted survival probabilities for each event and calculated risks of hypothetical cases of different %tCD4<200.FindingsIn 8,369 patients with 34·9 months of follow-up (median, IQR: 16·7, 69·1), 4,274 (51%) started ART with CD4<200 cells/μL. Median %tCD4<200 was 0% (IQR: 0, 15%). We identified 195 (2·3%) deaths and 584 (7·2%) patients with ADE/SNADE. For an increased %tCD4<200 of 15% (e.g., 15% vs. 0%), the adjusted relative hazard (aHR) of death was 1·27 (95% confidence interval [CI]: 1·19 − 1·35), of ADE/SNADE was 1·13 (95%CI: 1·09 − 1·17), of SNADE was 0·96 (95%CI: 0·89 − 1·02) and of death/ADE/SNADE was 1·11 (95%CI: 1·07 − 1·14). Estimates were similar after adjusting for time updated CD4 count.InterpretationIn virologically suppressed PWH, increased time living with severe immunosuppression had an increased risk of death and ADE/SNADE in this Latin American cohort, independently of time updated CD4 count.FundingThis work was supported by the NIH-funded Caribbean, Central and South America network for HIV epidemiology (CCASAnet, U01AI069923), a member cohort of the International Epidemiologic Databases to Evaluate AIDS (leDEA). This award is funded by the following institutes: Eunice Kennedy Shriver National Institute Of Child Health & Human Development (NICHD), National Cancer Institute (NCI), National Institute Of Allergy And Infectious Diseases (NIAID), National Institute Of Mental Health (NIMH), the National Heart, Lung, and Blood Institute (NHLBI), the National Institute on Alcohol Abuse and Alcoholism (NIAAA), the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), and the Fogarty International Center (FIC). Specific funding was provided from the Fogarty International Center (FIC) for lead author, Yanink Caro-Vega, for the Fogarty-IeDEA Mentorship Program (FIMP).

Extremity Soft Tissue Sarcoma: A Multi-Institutional Validation of Prognostic Nomograms.

Prognostic nomograms for patients with resected extremity soft tissue sarcoma (STS) include the Sarculator and Memorial Sloan Kettering (MSKCC) nomograms. We sought to validate these two nomograms within a large, modern, multi-institutional cohort of resected primary extremity STS patients. Resected primary extremity STS patients from 2000 to 2017 were identified across nine high-volume U.S. institutions. Predicted 5- and 10-year overall survival (OS) and distant metastases cumulative incidence (DMCI), and 4-, 8-, and 12-year disease-specific survival (DSS) were calculated with Sarculator and MSKCC nomograms, respectively. Predicted survival probabilities stratified in quintiles were compared in calibration plots to observed survival assessed by Kaplan-Meier estimates. Cumulative incidence was estimated for DMCI. Harrell's concordance index (C-index) assessed discriminative ability of nomograms. A total of 1326 patients underwent resection of primary extremity STS. Common histologies included: undifferentiated pleomorphic sarcoma (35%), fibrosarcoma (13%), and leiomyosarcoma (9%). Median tumor size was 8.0 cm (IQR 4.5-13.0). Tumor grade distribution was: Grade 1 (13%), Grade 2 (9%), Grade 3 (78%). Median OS was 172 months, with estimated 5- and 10-year OS of 70% and 58%. C-indices for 5- and 10-year OS (Sarculator) were 0.72 (95% CI 0.70-0.75) and 0.73 (95% CI 0.70-0.75), and 0.72 (95% CI 0.69-0.75) for 5- and 10-year DMCI. C-indices for 4-, 8-, and 12-year DSS (MSKCC) were 0.71 (95% CI 0.68-0.75). Calibration plots showed good prognostication across all outcomes. Sarculator and MSKCC nomograms demonstrated good prognostic ability for survival and recurrence outcomes in a modern, multi-institutional validation cohort of resected primary extremity STS patients. External validation of these nomograms supports their ongoing incorporation into clinical practice.

Genetic and Histopathological Heterogeneity of Neuroblastoma and Precision Therapeutic Approaches for Extremely Unfavorable Histology Subgroups.

Peripheral neuroblastic tumors (neuroblastoma, ganglioneuroblastoma and ganglioneuroma) are heterogeneous and their diverse and wide range of clinical behaviors (spontaneous regression, tumor maturation and aggressive progression) are closely associated with genetic/molecular properties of the individual tumors. The International Neuroblastoma Pathology Classification, a biologically relevant and prognostically significant morphology classification distinguishing the favorable histology (FH) and unfavorable histology (UH) groups in this disease, predicts survival probabilities of the patients with the highest hazard ratio. The recent advance of neuroblastoma research with precision medicine approaches demonstrates that tumors in the UH group are also heterogeneous and four distinct subgroups—MYC, TERT, ALT and null—are identified. Among them, the first three subgroups are collectively named extremely unfavorable histology (EUH) tumors because of their highly aggressive clinical behavior. As indicated by their names, these EUH tumors are individually defined by their potential targets detected molecularly and immunohistochemically, such as MYC-family protein overexpression, TERT overexpression and ATRX (or DAXX) loss. In the latter half on this paper, the current status of therapeutic targeting of these EUH tumors is discussed for the future development of effective treatments of the patients.

Patient age affects sex-based differences in post-traumatic mortality: a national trauma registry study in Japan

PurposeSex-based differences in post-traumatic mortality have been widely discussed for quite some time. We hypothesized that age-related pathophysiologic changes would affect sex-based differences in post-traumatic mortality and aimed to verify the hypothesis using a nationwide trauma registry in Japan.MethodsThis was a retrospective analysis of trauma patients registered in The Japanese Trauma Data Bank. We stratified the study population into the following three subsets based on age: (1) pediatric subset (age ≤ 14), (2) adult subset (age 15–50) and (3) senior adult subset (age ≥ 51). We evaluated both sex-based differences in mortality in each subset separately using multivariate logistic regression analysis and the two-way interaction effect for predicted survival between the continuous increase of age and the sexes using a nonlinear multivariate regression model.ResultsWe included 122,819 trauma patients who fulfilled the inclusion criteria and classified them into the 3 subsets according to age. Male patients were more likely to die compared to female patients only in the senior adult subset (adjusted odds ratio: 1.26; 95% confidence interval: 1.18–1.36), whereas there were no statistically significant differences in the other two subsets. Furthermore, non-linear logistic regression analysis revealed that predicted survival probability in male patients decreased more sharply in accordance with the increase of age compared to that in female patients (p for interaction: 0.051).ConclusionAge-related change in post-traumatic mortality was significantly different between males and females, and male patients had a relatively higher risk of death in the older population.

Pattern of distant metastases and predictive nomograms in colorectal mucinous adenocarcinoma: a SEER analysis.

We evaluated the metastatic patterns and explored the prognostic value of distant metastasis pattern in patients with metastatic colorectal mucinous adenocarcinoma (MC) using the Surveillance, Epidemiology, and End Results (SEER) database. Between 2010 and 2015, newly diagnosed colorectal MC patients were selected using the SEER database. Patient prognosis was compared based on the clinicopathological parameters, treatment method, and the site and number of metastatic organs. Cox analyses were used to identify factors associated with overall survival (OS). A nomogram was built to predict the patient's survival. Harrell's concordance index (c-index) and calibration curves were used to analyze the discriminative ability of the prognostic factors. Of 3,088 patients diagnosed with colorectal MC, the liver was the only metastatic organ in 78.4% (997/1,271) of all liver metastasis cases, the lung was the only metastatic organ in 41.0% (164/400) of all lung metastasis cases, bone was the only metastatic organ in 26.6% (29/109) of all bone metastasis cases, and the brain was the only metastatic organ in 23.5% (4/17) of all brain metastasis cases. Compared with the untreated cases, those treated with chemotherapy, surgery, and radiotherapy had better OS (P<0.001). There were marked OS differences (P<0.001) between patients with and without liver and bone metastases. Patients with bone metastasis had the best survival, while those with brain metastasis had the worst survival (P<0.001). Patients with one metastatic site had better prognosis compared to those with two or three (P<0.001). Patients with liver metastasis had the best survival, while those with bone and brain metastasis had the worst survival (P<0.001). Multivariate analysis showed that age <65 years, non-black race, grade I, N0 stage, chemotherapy, radiation, surgery, liver metastasis, and bone metastasis were independent prognostic factors. A nomogram was constructed to predict survival probability. The c-index value was up to 0.745. The calibration plot showed that the nomogram was clinically useful. Metastatic MC (mMC) patients had a characteristic distant metastasis pattern. This study constructed a new and sufficiently accurate prognostic model of mMC based on population-based data. These findings can be utilized to predict prognosis and guide mMC patient management.

Nomogram to predict survival of patients with advanced and metastatic pancreatic Cancer

BackgroundNomograms are rarely employed to estimate the survival of patients with advanced and metastatic pancreatic cancer (PC). Herein, we developed a comprehensive approach to using a nomogram to predict survival probability in patients with advanced and metastatic PC.Methods: A total of 323 patients with advanced and metastatic PC were identified from the Chinese People’s Liberation Army (PLA) General Hospital. A baseline nomogram was constructed using baseline variables of 323 patients. Additionally, 233 patients, whose tumors showed initial responses to first-line chemotherapy, were enrolled in the chemotherapy response-based model. 128 patients and 108 patients with advanced and metastatic PC from January 2019 to April 2021 were selected for external validating baseline model and chemotherapy response-based model. The 1-year and 2-year survival probability was evaluated using multivariate COX regression models. The discrimination and calibration capacity of the nomograms were assessed using C-statistic and calibration plots. The predictive accuracy and net benefit of the nomograms were evaluated using ROC curve and DCA, respectively.ResultsIn the baseline model, six variables (gender, KPS, baseline TB, baseline N, baseline WBC and baseline CA19–9) were used in the final model. In the chemotherapy response-based model, nine variables (KPS, gender, ascites, baseline N, baseline CA 19–9, baseline CEA, change in CA 19–9 level at week, change in CEA level at week and initial response to chemotherapy) were included in the final model. The C-statistics of the baseline nomogram and the chemotherapy response-based nomogram were 0.67 (95% CI, 0.62–0.71) and 0.74 (95% CI, 0.69–0.77), respectively.ConclusionThese nomograms were constructed to predict the survival probability of patients of advanced and metastatic PC. The baseline model and chemotherapy response-based model performed well in survival prediction.

An Aging-Related Gene Signature-Based Model for Risk Stratification and Prognosis Prediction in Breast Cancer.

BackgroundAging, an inevitable process characterized by functional decline over time, is a significant risk factor for various tumors. However, little is known about aging-related genes (ARGs) in breast cancer (BC). We aimed to explore the potential prognostic role of ARGs and to develop an ARG-based prognosis signature for BC.MethodsRNA-sequencing expression profiles and corresponding clinicopathological data of female patients with BC were obtained from public databases in The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). An ARG-based risk signature was constructed in the TCGA cohort based on results of least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression analysis, and its prognostic value was further validated in the GSE20685 cohort.ResultsA six ARG-based signature, including CLU, DGAT1, MXI1, NFKBI, PIK3CA and PLAU, was developed in the TCGA cohort and significantly stratified patients into low- and high-risk groups. Patients in the former group showed significantly better prognosis than those in the latter. Multivariate Cox regression analysis demonstrated that the ARG risk score was an independent prognostic factor for BC. A predictive nomogram integrating the ARG risk score and three identified factors (age, N- and M-classification) was established in the TCGA cohort and validated in the GSE20685 cohort. Calibration plots showed good consistency between predicted survival probabilities and actual observations.ConclusionA novel ARG-based risk signature was developed for patients with BC, which can be used for individual prognosis prediction and promoting personalized treatment.

Prognostic factors and nomogram prediction of survival probability in primary spinal cord astrocytoma patients.

Knowledge on the management of spinal cord astrocytoma (SCA) remains scarce. Here, the authors constructed and validated a predictive nomogram, often used for individualized prognosis and evaluations, to estimate cancer-specific survival (CSS) and overall survival (OS) for patients with SCA. Epidemiological characteristics were compared between low-grade SCA (LGSCA) and high-grade SCA (HGSCA) patients from the Surveillance, Epidemiology, and End Results (SEER) database. Risk factors for CSS and OS were determined using univariate and multivariate analyses and Kaplan-Meier curves. A nomogram was developed to individually predict the 3-, 5-, and 10-year CSS and OS rates. The clinical usefulness of the nomogram was assessed using calibration plots, the concordance index (C-index), and time-dependent receiver operating characteristic curves. A total of 468 LGSCA and 165 HGSCA patients were eligible for inclusion. LGSCA and HGSCA patients demonstrated differences in age, tumor extension, insurance status, adjuvant treatment, and survival. Multivariate analysis demonstrated that in the LGSCA group, tumor extension, surgery type, and adjuvant therapy were individually associated with CSS. The distance of tumor extension and WHO grade were individually associated with CSS in the HGSCA group. The prognostic variables were further demonstrated using the Kaplan-Meier method, which also suggested that adjuvant treatment provided no advantage to HGSCA patients. A nomogram was constructed, and the C-index for CSS was 0.84 by internal validation (95% CI 0.79-0.90). This research suggests that the distance of tumor extension, type of surgery, and adjuvant therapy are significant risk factors for CSS using multivariate analysis in the LGSCA group. Adjuvant treatment provided no advantages for CSS or OS in patients with HGSCAs. The nomogram may be clinically useful to healthcare providers.

Identification and Prognostic Value Exploration of Cyclophosphamide (Cytoxan)-Centered Chemotherapy Response-Associated Genes in Breast Cancer.

In this study, we aimed to explore cyclophosphamide (Cytoxan) response-associated genes and constructed a model to predict the prognosis of breast cancer (BRCA) patients. Samples obtained from TCGA and GEO databases were subjected to Weighted Gene Coexpression Network Analysis (WGCNA) and univariate Cox and LASSO Cox regression analysis to identify and validate the Cytoxan response-related prognostic signature. Moreover, multivariate Cox regression analysis was performed to analyze the independence of factors, and the nomogram model was constructed by including all the independent factors. WGCNA revealed that 159 genes are significantly correlated with Cytoxan response in BRCA samples, and the samples with a different prognosis could be effectively distinguished based on the expression of those 159 genes. Ten genes were further selected to be related to the prognosis of BRCA patients, including PCDHB2, GRIK2, FRMD7, CCSER1, PCDHGA1, PCDHA1, LRRC37A6P, PCDHGA12, ZNF486, and PCDHGB5, based on the Risk Score model. Among them, PCDHA1 expression was validated in cells and patient samples. Multivariate Cox regression analysis confirmed that the Risk Score is an independent factor. Furthermore, the nomogram model showed that the predicted survival probability is closely related to the actual survival probability. In conclusion, we identified 159 genes potentially correlated with the Cytoxan response of BRCA patients, which had prognostic value in BRCA.

Prognostic and Predictive Value of Transcription Factors Panel for Digestive System Carcinoma.

PurposeDigestive system carcinoma is one of the most devastating diseases worldwide. Lack of valid clinicopathological parameters as prognostic factors needs more accurate and effective biomarkers for high-confidence prognosis that guide decision-making for optimal treatment of digestive system carcinoma. The aim of the present study was to establish a novel model to improve prognosis prediction of digestive system carcinoma, with a particular interest in transcription factors (TFs).Materials and MethodsA TF-related prognosis model of digestive system carcinoma with data from TCGA database successively were processed by univariate and multivariate Cox regression analyses. Then, for evaluating the prognostic prediction value of the model, ROC curve and survival analysis were performed by external data from GEO database. Furthermore, we verified the expression of TFs expression by qPCR in digestive system carcinoma tissue. Finally, we constructed a TF clinical characteristics nomogram to furtherly predict digestive system carcinoma patient survival probability with TCGA database.ResultsBy Cox regression analysis, a panel of 17 TFs (NFIC, YBX2, ZBTB47, ZNF367, CREB3L3, HEYL, FOXD1, TIGD1, SNAI1, HSF4, CENPA, ETS2, FOXM1, ETV4, MYBL2, FOXQ1, ZNF589) was identified to present with powerful predictive performance for overall survival of digestive system carcinoma patients based on TCGA database. A nomogram that integrates TFs was established, allowing efficient prediction of survival probabilities and displaying higher clinical utility.ConclusionThe 17-TF panel is an independent prognostic factor for digestive system carcinoma, and 17 TFs based nomogram might provide implication an effective approach for digestive system carcinoma patient management and treatment.

Identification of IGF2BP3 as an Adverse Prognostic Biomarker of Gliomas.

N6-methyladenosine (m6A) RNA modification can alter gene expression and function by regulating RNA splicing, stability, translocation, and translation. It is involved in various types of cancer. However, its role in gliomas is not well known. This study aimed to determine the prognostic value of the m6A RNA methylation regulator in gliomas and investigate the underlying mechanisms of the aberrant expression of m6A-related genes.mRNA expression profiles and clinical information of 448 glioma samples were obtained from The Cancer Genome Atlas and cBioportal. The expression of m6A-related genes in normal controls and low-grade glioma and glioblastoma was obtained from Gene Expression Profiling Interactive Analysis. Further, m6A-related gene expression and its relationship with prognosis were obtained through The Chinese Glioma Genome Atlas (CGGA). Multivariate Cox regression analyses were performed, and a nomogram was built with potential risk factors based on a multivariate Cox analysis to predict survival probability. Online tools such as Gene Set Enrichment Analysis, STRING, Cytoscape, and Molecular Complex Detection were applied for bioinformatics analysis and to investigate the underlying mechanisms of the aberrant expression of m6A-related genes. The multivariate Cox regression analysis found that higher expression levels of YTHDC2 and insulin-like growth factor 2 mRNA-binding protein 3 (IGF2BP3, also called IMP3) were independent negative and positive prognostic factors for overall survival (OS), respectively. Data from the CGGA database showed that IGF2BP3 expression increased when the tumor grade increased. Receiver operating characteristic (ROC) curve was used to evaluate the predictive specificity and sensitivity. The area under the ROC curve indicated that the OS prediction was 0.92 (1-year) and 0.917 (3-years), indicating that m6A-related genes could predict patient survival. In addition, IGF2BP3 was closely related to the shorter survival period of patients. Copy number variation and DNA methylation, but not somatic mutations, might contribute to the abnormal upregulation of IGF2BP3 in gliomas. Significantly altered genes were identified, and the protein–protein interaction network was constructed. Based on the data presented, our study identified several m6A-related genes, especially IGF2BP3, that could be potential prognostic biomarkers of gliomas. The study unveiled the potential regulatory mechanism of IGF2BP3 in gliomas.

Development and application of a dynamic prediction model for esophageal cancer.

BackgroundCurrent prediction models of esophageal cancer (EC) are limited to predicting at a specific time point, and ignore changes in hazard ratios of predictive variables, known as time-varying effects. Our study aimed to investigate variables with time-varying effects in EC and to develop a prediction model that can update the 5-year predicted dynamic overall survival (DOS) probability during the follow-up period.MethodsFirstly, the clinicopathological information and survival data of 4,541 patients with EC was obtained from the Surveillance, Epidemiology, and End Results (SEER) database between 2007 and 2011 for modeling. Secondly, the time-varying effect of variables was assessed and the dynamic prediction model was developed based on the proportional baselines landmark supermodel.ResultsHere, we found that age at diagnosis, sex, location of primary tumor, histological type, chemotherapy, surgery, and T stage showed significant time-varying effects on overall survival. Thirdly, the prediction model was validated by an internal SEER validation cohort and a Chinese patient cohort, respectively, and achieved promising results as follows: area under the curve (AUC) =0.733 (internal validation) and 0.864 (external validation). The heuristic shrinkage factor was 0.995. Finally, several clear cases were selected as examples for model application to map the patient’s 5-year DOS curves and to respectively demonstrate the impact of different variables’ time-varying effect on survival.ConclusionsOverall, our results suggest that the existence of time-varying effect highlights the importance of updating the predicted survival probability during the follow-up period. Moreover, this prediction model can be used to assist doctors in making more-individualized treatment decisions based on a dynamic assessment of patient prognosis.

The Landscape of the Tumor Microenvironment in Skin Cutaneous Melanoma Reveals a Prognostic and Immunotherapeutically Relevant Gene Signature.

The tumorigenesis of skin cutaneous melanoma (SKCM) remains unclear. The tumor microenvironment (TME) is well known to play a vital role in the onset and progression of SKCM. However, the dynamic mechanisms of immune regulation are insufficient. We conducted a comprehensive analysis of immune cell infiltration in the TME. Based on the differentially expressed genes (DEGs) in clusters grouped by immune infiltration status, a set of hub genes related to the clinical prognosis of SKCM and tumor immune infiltration was explored.Methods: We analyzed immune cell infiltration in two independent cohorts and assessed the relationship between the internal pattern of immune cell infiltration and SKCM characteristics, including clinicopathological features, potential biological pathways, and gene mutations. Genes related to the infiltration pattern of TME immune cells were determined. Furthermore, the unsupervised clustering method (k-means) was used to divide samples into three different categories according to TME, which were defined as TME cluster-A, -B, and -C. DEGs among three groups of samples were analyzed as signature genes. We further distinguished common DEGs between three groups of samples according to whether differences were significant and divided DEGs into the Signature gene-A group with significant differences and the Signature gene-B group with insignificant differences. The Signature gene-A gene set mainly had exon skipping in SKCM, while the Signature gene-B gene set had no obvious alternative splicing form. Subsequently, we analyzed genetic variations of the two signatures and constructed a competing endogenous RNA (ceRNA) regulatory network. LASSO Cox regression was used to determine the immune infiltration signature and risk score of SKCM. Finally, we obtained 13 hub genes and calculated the risk score based on the coefficient of each gene to explore the impact of the high- and low-risk scores on biologically related functions and prognosis of SKCM patients further. The correlation between the risk score and clinicopathological characteristics of SKCM patients indicated that a low-risk score was associated with TME cluster-A classification (p < 0.001) and metastatic SKCM (p < 0.001). Thirteen hub genes also showed different prognostic effects in pan-cancer. The results of univariate and multivariate Cox analyses revealed that risk score could be used as an independent risk factor for predicting the prognosis of SKCM patients. The nomogram that integrated clinicopathological characteristics and immune characteristics to predict survival probability was based on multivariate Cox regression. Finally, 13 hub genes that showed different prognostic effects in pan-cancers were obtained. According to immunohistochemistry staining results, Ube2L6, SRPX2, and IFIT2 were expressed at higher levels, while CLEC4E, END3, and KIR2DL4 were expressed at lower levels in 25 melanoma specimens.Conclusion: We performed a comprehensive assessment of the immune-associated TME. To elucidate the potential development of immune-genomic features in SKCM, we constructed an unprecedented set of immune characteristic genes (EDN3, CLEC4E, SRPX2, KIR2DL4, UBE2L6, and IFIT2) related to the immune landscape of TME. These genes are related to different prognoses and drug responses of SKCM. The immune gene signature constructed can be used as a robust prognostic biomarker of SKCM and a predictor of an immunotherapy effect.

Nomograms for predicting the overall survival of patients with cerebellar glioma: an analysis of the surveillance epidemiology and end results (SEER) database

At present, our understanding of cerebellar glioma is still insufficient. This study collected information on patients in the SEER database to identify the predictive factors for patients with cerebellar glioma. Data from patients with cerebellar glioma diagnosed from 1975 to 2018 were retrieved from the Surveillance Epidemiology and End Results Database. We randomly divided the patients into a training group and a validation group, established a nomogram based on the training group, and used the validation group data to verify the clinical value of the model. A total of 508 patients were included in this study. Multivariate analysis was performed based on the data before randomization, and the results showed that the patient's age, WHO grade, histological type, and extent were significantly correlated with the survival rate. The C-index of the OS nomograms of the training cohort was 0.909 (95% CI, (0.880–0.938)) and 0.932 (95% CI, (0.889–0.975)) in the validation group. The calibration curve of OS for 3 and 5 years showed that there was good consistency between the actual survival probability and the predicted survival probability. For patients with cerebellar glioma, the age at diagnosis, WHO grade of the glioma, histological type, and extension are the four factors that most strongly affect the overall survival outcomes. Furthermore, our model may be a useful tool for predicting OS in these patients.

Development and external validation of a prognostic model for survival of people living with HIV/AIDS initiating antiretroviral therapy.

Background: Most existing prognostic models for people living with HIV/AIDS (PLWHA) were derived from cohorts in high-income settings established a decade ago and may not be applicable for contemporary patients, especially for patients in developing settings. The aim of this study was to develop and externally validate a prognostic model for survival in PLWHA initiating ART based on a large population-based cohort in China.Methods: We obtained data for patients from the Chinese National Free Antiretroviral Treatment Program database. The derivation cohort consisted of PLWHA treated between February 2004 and December 2019 in a tertiary center in Guangzhou, South China, and validation cohort of patients treated between February 2004 to December 2018 in another tertiary hospital in Shenyang, Northeast China. We included ART-naive patients aged above 16 who initiated a combination ART regimen containing at least three drugs and had at least one follow-up record. We assessed 20 candidate predictors including patient characteristics, disease characteristics, and laboratory tests for an endpoint of death from all causes. The prognostic model was developed from a multivariable cox regression model with predictors selected using the least absolute shrinkage and selection operator (Lasso). To assess the model's predictive ability, we quantified the discriminative power using the concordance (C) statistic and calibration accuracy by comparing predicted survival probabilities with observed survival probabilities estimated with the Kaplan–Meier method.Findings: The derivation cohort included 16481 patients with a median follow-up of 3·41 years, among whom 735 died. The external validation cohort comprised 5751 participants with a median follow-up of 2·71 years, of whom 185 died. The final model included 10 predictors: age, body mass index, route of HIV acquisition, coinfection with tuberculosis, coinfection with hepatitis C virus, haemoglobin, CD4 cell count, platelet count, aspartate transaminase, and plasma glucose. The C-statistic was 0·84 (95% confidence interval 0·82–0·85) in internal validation after adjustment of optimism and 0·84 (0·82–0·87) in external validation, which remained consistently above 0·75 in all landmark time points within five years of follow up when using time-updated laboratory measurements. The calibration accuracy was satisfactory in both derivation and validation cohorts.Interpretation: We have developed and externally validated a model to predict long-term survival in PLWHA on ART. This model could be applied to individualized patient counseling and management during treatment, and future innovative trial design.Funding: Natural Science Foundation of China Excellent Young Scientists Fund, Natural Science Foundation of China International/Regional Research Collaboration Project, Natural Science Foundation of China Young Scientist Fund, the National Science and Technology Major Project of China,National Special Research Program of China for Important Infectious Diseases, 13th Five-Year Key Special Project of Ministry of Science and Technology, and the Joint-innovation Program in Healthcare for Special Scientific Research Projects of Guangzhou.

Effective Turnaround for SMEs:Interaction between Insolvency Proceedings and Retrenchment Strategies

Extant research on turnaround acknowledges that when a firm begins to experience financial difficulties, retrenchment is the most frequent response. Should this strategy be unsuccessful, the firm proceeds to legal treatment through insolvency proceedings. However, little is known about the fact how firms’ cans consider simultaneously or successively the use of out-of-court and in-court restructuring strategies. The goal of this study is to investigate the impact of the interplay between insolvency proceedings and retrenchment strategies on firm survival. We use a Cox proportional hazards model to predict survival probability on a sample of French SMEs. Our main findings are that the opening of insolvency proceedings has a significant and negative impact on firms’ life expectancy. The influence of retrenchment differs whether it concerns employees or assets. Retrenchment in employees has a general and negative influence on firm’s survival, but we find that this influence is even more pronounced in the presence of insolvency proceedings. In contrast, assets retrenchment increases firms’ life expectancy. In this case, we observe that the insolvency proceedings increase this positive impact on survival likelihood. This research is likely to help researchers, legislators, and managers to better understand the effective use of retrenchment strategies within insolvency proceedings.

Prediction of long-term survival after gastrectomy using random survival forests.

No well validated and contemporaneous tools for personalized prognostication of gastric adenocarcinoma exist. This study aimed to derive and validate a prognostic model for overall survival after surgery for gastric adenocarcinoma using a large national dataset. National audit data from England and Wales were used to identify patients who underwent a potentially curative gastrectomy for adenocarcinoma of the stomach. A total of 2931 patients were included and 29 clinical and pathological variables were considered for their impact on survival. A non-linear random survival forest methodology was then trained and validated internally using bootstrapping with calibration and discrimination (time-dependent area under the receiver operator curve (tAUC)) assessed. The median survival of the cohort was 69 months, with a 5-year survival of 53.2 per cent. Ten variables were found to influence survival significantly and were included in the final model, with the most important being lymph node positivity, pT stage and achieving an R0 resection. Patient characteristics including ASA grade and age were also influential. On validation the model achieved excellent performance with a 5-year tAUC of 0.80 (95 per cent c.i. 0.78 to 0.82) and good agreement between observed and predicted survival probabilities. A wide spread of predictions for 3-year (14.8-98.3 (i.q.r. 43.2-84.4) per cent) and 5-year (9.4-96.1 (i.q.r. 31.7-73.8) per cent) survival were seen. A prognostic model for survival after a potentially curative resection for gastric adenocarcinoma was derived and exhibited excellent discrimination and calibration of predictions.

Competing-risks nomogram for predicting cancer-specific death in upper tract urothelial carcinoma: a population-based analysis

ObjectiveThis study aimed to use a competing-risks model to establish a nomogram to accurately analyse the prognostic factors for upper tract urothelial carcinoma (UTUC) cancer-specific death (CSD).DesignRetrospective observational cohort study.SettingThe...

Occurrence of Cardiotoxicity and the Impact on Outcomes Among Children Treated on the AAML0531 Clinical Trial: A Report from the Children's Oncology Group

Background: Much of the literature on anthracycline-associated cardiotoxicity has focused on late effects of exposure among childhood cancer survivors. Given the high anthracycline exposure in front-line therapy for pediatric acute myeloid leukemia (AML), it is crucial to gain a better understanding of the risk factors for early cardiotoxicity and its impact on subsequent treatment outcomes.Methods: Between August 2006 and June 2010, Children's Oncology Group trial AAML0531 enrolled patients less than 30 years of age for frontline treatment of de novo AML. These analyses excluded Down syndrome patients. Cardiac events over the course of treatment and off-protocol follow-up were ascertained through a combination of passive (traditional adverse event (AE) case report forms) and active (targeted requests for echocardiograms for patients with an AE report for a cardiac event or life-threatening bloodstream infection) adverse event monitoring. The primary outcome of cardiotoxicity was defined as grade 2 or higher left ventricular systolic dysfunction (LVSD) based on Common Terminology Criteria for AE Version 3 definitions (i.e., ejection fraction <50% or fractional shortening <24%). We evaluated risk factors for incident LVSD using multivariable Cox regression analyses. Cox regression models were then used to compare event-free survival (EFS) and overall survival (OS) in patients with documented LVSD, classified as infection-associated and not infection-associated, relative to patients with no documented LVSD. The occurrence of LVSD was considered as a time-varying exposure to avoid immortal and immune person-time bias. Adjusted hazard ratios and corresponding 95% confidence intervals were reported. Cox model predicted survival probabilities were used to plot the OS and EFS curves.Results: These analyses included 1022 AML patients enrolled AAML0531. Compliance with echocardiographic evaluations was higher but more variable during the on-protocol (median: 61.2%, range: 41.1%-85.0%) compared with the off-protocol reporting periods (median: 53.8%, range: 39.1%-56.1%). Compliance did not differ significantly by age, gender, race, ethnicity, BMI, insurance status, AML risk classification, initial white blood cell count, or randomized treatment arm.Approximately 12% of patients had documented grade 2 or higher LVSD over the course of follow-up; 25% of incident events were classified as infection-associated. The cumulative incidence increased approximately linearly during on-protocol therapy from 1% to 8% from Induction I through Intensification III, but plateaued early during off-protocol follow-up (i.e.18 months). The overall incidence increased with age at enrollment (p-value for trend: <0.002), was higher among black compared to white patients (HR=1.73, 95% CI: 1.00, 2.99), among obese compared to normal weight patients (HR=1.64, 95% CI: 1.01, 2.65), and in the setting of a bloodstream infection (HR=1.86, 95% CI: 1.12, 10.9). These overall trends, with the exception of obesity, were driven by on-protocol toxicities.Five-year EFS and OS were significantly lower in patients who experienced on-protocol cardiotoxicity (Table 1, Figure 1). The impact on EFS was similar whether the incident event was determined to be in the presence or absence of infection (absolute differences of 17.5% and 16.1%, respectively), whereas the impact on OS was more pronounced for cardiac toxicity in the absence of infection than cardiac toxicity in the presence of infection (absolute differences of 16.8% and 7.7%, respectively).Conclusions: Our findings demonstrate that early treatment-related cardiotoxicity is associated with decreased EFS and OS possibly through associated reductions in anthracycline exposure. The suggested heterogeneity in the effect on OS by infection status implies that patients who experience LVSD in the context of infection may be more salvageable upon relapse than patients experiencing non-infection related cardiotoxicity. Efforts to improve the outcomes for children with AML should include increased attention to the prevention and mitigation of on-protocol cardiac toxicity. [Display omitted] DisclosuresNo relevant conflicts of interest to declare.