Time-dependent Receiver Operating Characteristic Analysis Research Articles

The associations between the Geriatric Nutritional Risk Index and all-cause, cancer-specific, and cardiovascular mortality in the U.S. population: a large-scale pooled survey

BackgroundPrevious studies have reported a close association between the Geriatric Nutritional Risk Index (GNRI) and various conditions. However, the association between the GNRI and mortality remains unclear. To examine the correlation between the GNRI and all-cause, cancer-specific, and cardiovascular mortality, this study was performed.MethodsWe analyzed elderly participants in the National Health and Nutrition Examination Survey from 2005 to 2016. The GNRI was calculated using body mass index and serum albumin. Kaplan-Meier survival curves were drawn to compare the survival probability between the normal and decreased GNRI groups. Weighted multivariate Cox regression and restricted cubic spline (RCS) models were employed to determine the linear and non-linear associations of the GNRI with all-cause, cancer-specific, and cardiovascular mortality.ResultsA total of 3,276 participants were included in the analysis. The Kaplan-Meier survival curve showed that the decreased GNRI group had a lower survival probability for all-cause mortality and cancer-specific mortality (P < 0.001) but not for cardiovascular mortality (P > 0.05). In the full regression models, the decreased group had a higher risk of all-cause mortality (HR = 1.67, 95% CI = 1.21–2.30, P = 0.002), and cancer-specific mortality (HR = 2.20, 95% CI = 1.32–3.67, P = 0.003) than the normal group. For cardiovascular mortality, no significant association with GNRI (HR = 1.39, 95% CI = 0.60–3.22, P = 0.436) was detected. Notably, the RCS analysis identified a linear downward trend between the GNRI and all-cause, alongside cancer-specific mortalities (all P for overall < 0.05). The time-dependent Receiver Operating Characteristic (ROC) analysis unveiled the predictive power of the GNRI for 5-year all-cause mortality, cancer mortality, and cardiovascular mortality was 0.754, 0.757, and 0.836, respectively, after adjusting for covariates.ConclusionsIndividuals with a decreased GNRI had increased risks of all-cause, and cancer-specific mortality. There were linear associations of the GNRI with all-cause, and cancer-specific mortality. Nutritional status should be carefully monitored, which may improve the overall prognosis for the general population.

Short- and long-term performance of risk calculation tools for mortality in patients with acute coronary syndrome.

The mortality rate of acute coronary syndrome (ACS) remains high. Therefore, patients with ACS should undergo early risk stratification, for which various risk calculation tools are available. However, it remains uncertain whether the predictive performance varies over time between risk calculation tools for different target periods. This study aimed to compare the predictive performance of risk calculation tools in estimating short- and long-term mortality risks in patients with ACS, while considering different observation periods using time-dependent receiver operating characteristic (ROC) analysis. This study included 404 consecutive patients with ACS who underwent coronary angiography at our hospital from March 2017 to January 2021. The ACTION and GRACE scores for short-term risk stratification purposes and CRUSADE scores for long-term risk stratification purposes were calculated for all participants. The participants were followed up for 36 months to assess mortality. Using time-dependent ROC analysis, we evaluated the area under the curve (AUC) of the ACTION, CRUSADE, and GRACE scores at 1, 6, 12, 24, and 36 months. Sixty-six patients died during the observation periods. The AUCs at 1, 6, 12, 24, and 36 months of the ACTION score were 0.942, 0.925, 0.889, 0.856, and 0.832; those of the CRUSADE score were 0.881, 0.883, 0.862, 0.876, and 0.862; and those of the GRACE score 0.949, 0.928, 0.888, 0.875, and 0.860, respectively. The ACTION and GRACE scores were excellent risk stratification tools for mortality in the short term. The prognostic performance of each risk score was almost similar in the long term, but the CRUSADE score might be a superior risk stratification tool in the longer term than 3 years.

The systemic inflammation response index as a risk factor for hepatic fibrosis and long-term mortality among individuals with metabolic dysfunction-associated steatotic liver disease

Background and aimsThe systemic inflammation response index (SIRI) is associated with various diseases with inflammatory components, but its relationship with the progression of hepatic fibrosis and survival outcomes in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) is still unclear. This study was designed to investigate the potential associations between the SIRI and advanced hepatic fibrosis (AHF) as well as between the SIRI and long-term outcomes in individuals with MASLD. Methods and resultsA prospective cohort study was conducted using data gathered from the National Health and Nutrition Examination Survey (NHANES) spanning from 2005 to 2016. Weighted binary logistic regression, the Cox proportional hazards model, and time-dependent receiver operating characteristic (ROC) analyses were employed to assess the relationships among the SIRI, AHF, and mortality in patients with MASLD. Our study included a total of 5126 patients with MASLD. A higher SIRI was significantly associated with increased odds of AHF (OR 1.55, 95% CI 1.22, 1.96). According to the survival analyses, a higher SIRI was associated with greater all-cause (HR 1.19, 95% CI 1.15, 1.22) and cardiovascular mortality (HR 1.25, 95% CI 1.19, 1.32) after adjustment. The time-dependent ROC analysis indicated that the SIRI had a modest predictive value for discriminating MASLD individuals at higher versus lower mortality risk over 3-year, 5-year, and 10-year follow-up. ConclusionsThe SIRI is a promising tool for identifying MASLD individuals at risk of progressing to AHF and for predicting mortality outcomes.

Validation and comparison of prognostic scoring systems in patients with head and neck squamous cell carcinoma treated with nivolumab.

Several scoring systems have been developed to predict prognosis in patients with refractory cancer. We aimed to validate eight scoring systems and determine the best method for predicting the prognosis of head and neck squamous cell carcinoma treated with nivolumab. This multicentre retrospective study involved 154 patients with recurrent and/or metastatic head and neck squamous cell carcinoma treated with nivolumab between 2017 and 2020. Oncological outcomes were assessed according to the scoring systems, including MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio and Hammersmith scores. Objective response, overall survival and progression-free survival were evaluated using logistic regression and Cox proportional hazards analyses. Receiver operating curve analysis was used to calculate the area under the curve and estimate the efficacy of each score. No significant associations were found between the responses and any score. Seven of the eight scoring systems were associated with disease control (odds ratio, 0.26-0.70). Amongst the eight scoring systems, MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio showed the highest area under the curve for predicting response and disease control. Seven scoring systems were prognostic factors for progression-free survival (hazard ratio, 1.22-1.95). All eight scoring systems were prognostic factors for overall survival (hazard ratio, 1.62-3.83). According to the time-dependent receiver operating characteristics analysis for overall survival, the Hammersmith scoring system had the best predictive ability at 3months, and the MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio scoring system had the highest area under the curve between 6 and 24months. MD Anderson Cancer Center + neutrophil-to-lymphocyte ratio and Hammersmith scoring systems were better predictors of prognosis in patients with head and neck squamous cell carcinoma treated with nivolumab.

A four-gene signature predicts overall survival of patients with esophageal adenocarcinoma.

Esophageal adenocarcinoma (EAC) is an aggressive cancer with poor prognosis. Thus, this study aimed to identify a prognostic molecular signature to predict the overall survival (OS) of patients with EAC. The mRNA microarray data sets GSE13898 and GSE26886 were downloaded from the Gene Expression Omnibus (GEO) database. RNA sequencing profile and clinical data of EAC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) between EAC tissues and adjacent non-cancerous tissues were obtained using R software. DEGs associated with prognosis of OS were assessed by univariate Cox analysis, and a prognostic signature was built using stepwise multivariate Cox analysis. Time-dependent receiver operating characteristic (ROC) analysis and stratification analysis were conducted to evaluate its predictive performance. Functional enrichment analysis was performed for genes co-expressed with the signature to explore its biological functions in EAC. A total of 336 genes were identified to be differentially expressed between EAC tissues and adjacent non-cancerous tissues. After univariate and multivariate Cox regression analysis, four genes (ALAD, ABLIM3, IL17RB and IFI6) were screened out to construct a prognostic signature. According to this signature, patients could be assigned into high-risk and low-risk group with significantly different OS (P=4.92e-05<0.0001). Multivariate Cox regression analysis suggested that the four-gene signature served as an independent factor in OS prediction. In the time-dependent ROC analysis, the areas under the curves (AUCs) were 0.804, 0.792 and 0.695 for 1-, 3- and 5-year survival prediction, respectively, suggesting a good performance. Functional enrichment analysis showed that the signature was mainly clustered in cell proliferation related biological processes or pathways. The four-gene signature identified in the current study may be a potential prognostic factor for predicting OS of EAC patients.

Lack of Association of Plasma Levels of Soluble Programmed Cell Death Protein 1, Programmed Death-Ligand 1, and CTLA-4 With Survival for Stage II to IIIA NSCLC After Complete Resection and Adjuvant Chemotherapy

IntroductionPerioperative treatment in NSCLC has gained marked attention with the introduction of immune checkpoint inhibitors. Such a paradigm shift has given us additional opportunities to evaluate potential biomarkers in patients with these curable disease stages. MethodsThis study (WJOG12319LTR) was designed as a biomarker study to evaluate whether soluble immune markers were prognostic or predictive on relapse-free survival in patients with stage II to IIIA NSCLC who underwent complete resection and adjuvant chemotherapy with cisplatin plus S-1, which is an oral fluoropyrimidine formulation that consists of tegafur, gimeracil, and oteracil, or S-1 alone in the previous WJOG4107 study. Archived plasma samples were assayed for soluble (s) forms of programmed cell death protein 1 (sPD-1), programmed death-ligand 1(sPD-L1), and CTLA-4 (sCTLA-4) with the highly sensitive HISCL system. Using time-dependent receiver operating characteristic curve analysis, the area under the curves were derived and optimal cutoff values were determined. Using the cutoff values, whether the marker was prognostic or predictive was assessed by survival analysis. ResultsA total of 150 patients were included in the study. The time-dependent receiver operating characteristics analysis revealed that the area under the curves for sPD-1, sPD-L1, and sCTLA-4 were 0.54, 0.51, and 0.58, respectively. The survival analysis did not reject that hazard ratios were 1 in terms of the soluble immune marker and the treatment-marker interaction for all three markers. ConclusionsThere was no proof that circulating concentrations of sPD-1, sPD-L1, and sCTLA-4 were prognostic or predictive factors of the outcome for adjuvant chemotherapy after complete resection in patients with NSCLC.

Assessing the usefulness of a newly proposed metabolic score for visceral fat in predicting future diabetes: results from the NAGALA cohort study.

Visceral adipose tissue assessment holds significant importance in diabetes prevention. This study aimed to explore the association between the newly proposed Metabolic Score for Visceral Fat (METS-VF) and diabetes risk and to further assess the predictive power of the baseline METS-VF for the occurrence of diabetes in different future periods. This longitudinal cohort study included 15,464 subjects who underwent health screenings. The METS-VF, calculated using the formula developed by Bello-Chavolla etal., served as a surrogate marker for visceral fat obesity. The primary outcome of interest was the occurrence of diabetes during the follow-up period. Established multivariate Cox regression models and restricted cubic spline (RCS) regression models to assess the association between METS-VF and diabetes risk and its shape. Receiver operating characteristic (ROC) curves were used to compare the predictive power of METS-VF with body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), and visceral adiposity index (VAI) for diabetes, and time-dependent ROC analysis was conducted to assess the predictive capability of METS-VF for the occurrence of diabetes in various future periods. During a maximum follow-up period of 13 years, with a mean of 6.13 years, we observed that the cumulative risk of developing diabetes increased with increasing METS-VF quintiles. Multivariable-adjusted Cox regression analysis showed that each unit increase in METS-VF would increase the risk of diabetes by 68% (HR 1.68, 95% CI 1.13, 2.50), and further RCS regression analysis revealed a possible non-linear association between METS-VF and diabetes risk (P for non-linearity=0.002). In addition, after comparison by ROC analysis, we found that METS-VF had significantly higher predictive power for diabetes than other general/visceral adiposity indicators, and in time-dependent ROC analysis, we further considered the time-dependence of diabetes status and METS-VF and found that METS-VF had the highest predictive value for predicting medium- and long-term (6-10 years) diabetes risk. METS-VF, a novel indicator for assessing visceral adiposity, showed a significantly positive correlation with diabetes risk. It proved to be a superior risk marker in predicting the future onset of diabetes compared to other general/visceral adiposity indicators, particularly in forecasting medium- and long-term diabetes risk.

Haemodynamic forces predicting remodelling and outcome in patients with heart failure treated with sacubitril/valsartan.

A novel tool for the evaluation of left ventricular (LV) systo-diastolic function through echo-derived haemodynamic forces (HDFs) has been recently proposed. The present study aimed to assess the predictive value of HDFs on (i) 6month treatment response to sacubitril/valsartan in heart failure with reduced ejection fraction (HFrEF) patients and (ii) cardiovascular events. Eighty-nine consecutive HFrEF patients [70% males, 65±9years, LV ejection fraction (LVEF) 27±7%] initiating sacubitril/valsartan underwent clinical, laboratory, ultrasound and cardiopulmonary exercise testing evaluations. Patients experiencing no adverse events and showing ≥50% reduction in plasma N-terminal pro-B-type natriuretic peptide and/or ≥10% LVEF increase over 6months were considered responders. Patients were followed up for the composite endpoint of HF-related hospitalisation, atrial fibrillation and cardiovascular death. Forty-five (51%) patients were responders. Among baseline variables, only HDF-derived whole cardiac cycle LV strength (wLVS) was higher in responders (4.4±1.3 vs. 3.6±1.2; p=0.01). wLVS was also the only independent predictor of sacubitril/valsartan response at multivariable logistic regression analysis [odds ratio 1.36; 95% confidence interval (CI) 1.10-1.67], with good accuracy at receiver operating characteristic (ROC) analysis [optimal cutpoint: ≥3.7%; area under the curve (AUC)=0.736]. During a 33month (23-41) median follow-up, a wLVS increase after 6months (ΔwLVS) showed a high discrimination ability at time-dependent ROC analysis (optimal cut-off: ≥0.5%; AUC=0.811), stratified prognosis (log-rank p<0.0001) and remained an independent predictor for the composite endpoint (hazard ratio 0.76; 95% CI 0.61-0.95; p<0.01), after adjusting for clinical and instrumental variables. HDF analysis predicts sacubitril/valsartan response and might optimise decision-making in HFrEF patients.

Prognostic scoring system based on eosinophil- and basophil-related markers for predicting the prognosis of patients with stage II and stage III colorectal cancer: a retrospective cohort study.

Systemic inflammation is associated with the prognosis of colorectal cancer (CRC). The current study aimed to construct a comprehensively inflammatory prognostic scoring system named risk score (RS) based on eosinophil- and basophil-related markers and assess its prognostic value in patients with stage II and stage III CRC. A total of 3,986 patients were enrolled from January 2007 to December 2013. The last follow-up time was January 2019. They were randomly assigned to the training set and testing set in a 3:2 split ratio. Least absolute shrinkage and selection operator (LASSO)-Cox regression analysis was performed to select the optimal prognostic factors in the construction of RS. The Kaplan-Meier curve, time-dependent receiver operating characteristic (ROC), and Cox analysis were used to evaluate the association between RS and overall survival (OS). In the training set, all inflammatory markers showed certain prognostic values. Based on LASSO-Cox analysis, nine markers were integrated to construct RS. The Kaplan-Meier curve showed that a higher RS (RS > 0) had a significantly worse prognosis (log-rank p< 0.0001). RS (>0) remained an independent prognostic factor for OS (hazard ratio (HR): 1.70, 95% confidence interval (CI), 1.43-2.03, p< 0.001). The prognostic value of RS was validated in the entire cohort. Time-dependent ROC analysis showed that RS had a stable prognostic effect throughout the follow-up times and could enhance the prognostic ability of the stage by combination. Nomogram was established based on RS and clinicopathological factors for predicting OS in the training set and validated in the testing set. The area under the curve (AUC) values of the 3-year OS in the training and testing sets were 0.748 and 0.720, respectively. The nomogram had a satisfactory predictive accuracy and had better clinical application value than the tumor stage alone. RS might be an independent prognostic factor for OS in patients with stage II and III CRC, which is helpful for risk stratification of patients. Additionally, the nomogram might be used for personalized prediction and might contribute to formulating a better clinical treatment plan.

Exploration of the optimal GS-441524 trough concentration for treating COVID-19

Remdesivir (RDV) is the cornerstone for treating coronavirus disease 2019 (COVID-19). The active metabolite of RDV, GS-441524 (a nucleoside analog), has high inter-individual variability in plasma concentration; however, its concentration-response relationship is still unclear. This study investigated the target GS-441524 trough concentration for symptom improvement in COVID-19 pneumonia. This single-center, retrospective, observational study included COVID-19 pneumonia patients (≥15 years) who were administered RDV for ≥3 days from May 2020 to August 2021 at Saiseikai Futsukaichi Hospital. To determine the cut-off value of GS-441524 trough concentration on day 3, the achievement of the National Institute of Allergy and Infectious Disease Ordinal Scale (NIAID-OS) ≤3 after RDV administration was evaluated using the cumulative incidence function (CIF) with the Gray test and time-dependent receiver operating characteristic (ROC) analysis. Multivariate logistic regression analysis was performed to determine the factors influencing GS-441524 target trough concentrations. Our analysis comprised 59 patients. The CIF revealed that GS-441524 trough concentration ≥70 ng/mL was associated with the achievement of NIAID-OS ≤3 (p = 0.047), which was significant based on the time-dependent ROC analysis. Factors influencing GS-441524 trough concentration ≥70 ng/mL included a decrease in eGFR (adjusted odds ratio [aOR] 0.96, 95% confidence interval [95% CI] 0.92-0.99, p = 0.027) and BMI ≥25 kg/m2 (aOR 0.26, 95% CI 0.07-0.86, p = 0.031). GS-441524 trough concentration ≥70 ng/mL is a predictor of efficacy in COVID-19 pneumonia. The presence of lower eGFR or BMI ≥25 kg/m2 was associated with achieving GS-441524 trough concentration ≥70 ng/mL.

Gradient-based Volumetric PET Parameters on Immediate Pre-ablation FDG-PETPredict Local Tumor Progression in Patients with Colorectal Liver Metastasis Treated by Microwave Ablation.

This study aimed to evaluate the optimal method of segmentation of colorectal liver metastasis (CLM) on immediate pre-ablation PET scans and assess the prognostic value of quantitative pre-ablation PET parameters with regards to local tumor control. A secondary objective was to correlate the target tumor size estimation by PET methods with the tumor measurements on anatomical imaging. A prospectively accrued cohort of 55 CLMs (46 patients) treated withreal-time 18F-FDG-PET/CT-guided percutaneous microwave ablation was followed-up for a median of 10.8months (interquartile: 5.5-20.2). Total lesion glycolysis (TLG) and metabolic tumor volume (MTV) values of each CLM were derived from pre-ablation 18F-FDG-PET with gradient and threshold PET segmentation methodologies. The event was defined as local tumor progression (LTP). Time-dependent receiver operating characteristic (ROC) curve analyses were used to assess area under the curves (AUCs). Intraclass correlation (ICC) and 95.0% confidence interval (CI) were performed to measure the linear relationships between the continuous variables. AUCs for prediction of LTP obtained from time-dependent ROC analysis for the gradient technique were higher in comparison to the threshold methodologies (AUCs for TLG and volume were: 0.790 and 0.807, respectively). ICC between PET gradient-based and anatomical measurements were higher in comparison to threshold methodologies (ICC for the longest diameter: 733 (95.0% CI 0.538-0.846), ICC for the shortest diameter: .747 (95.0% CI 0.546-0.859), p-values < 0.001). The gradient-based technique had a higher AUC for prediction of LTP after microwave ablation of CLM and showed the highest correlation with anatomical imaging tumor measurements.

Fatty acids metabolism affects the therapeutic effect of anti-PD-1/PD-L1 in tumor immune microenvironment in clear cell renal cell carcinoma

BackgroundClear cell renal cell carcinoma (ccRCC) is a highly invasive and metastatic subtype of kidney malignancy and is correlated with metabolic reprogramming for adaptation to the tumor microenvironment comprising infiltrated immune cells and immunomodulatory molecules. The role of immune cells in the tumor microenvironment (TME) and their association with abnormal fatty acids metabolism in ccRCC remains poorly understood.MethodRNA-seq and clinical data of KIRC from The Cancer Genome Atlas (TCGA) and E-MTAB-1980 from the ArrayExpress dataset. The Nivolumab group and Everolimus group of the CheckMate 025 study, the Atezolizumab arm of IMmotion150 and the Atezolizumab plus Bevacizumab group of IMmotion151 cohort were obtained for subsequent analysis. After differential expression genes identification, the signature was constructed through univariate Cox proportional hazard regression and simultaneously the least absolute shrinkage and selection operator (Lasso) analysis and the predictive performance of our signature was assessed by using receiver operating characteristic (ROC), Kaplan–Meier (KM) survival analysis, nomogram, drug sensitivity analysis, immunotherapeutic effect analysis and enrichment analysis. Immunohistochemistry (IHC), qPCR and western blot were performed to measure related mRNA or protein expression. Biological features were evaluated by wound healing, cell migration and invasion assays and colony formation test and analyzed using coculture assay and flow cytometry.ResultsTwenty fatty acids metabolism-related mRNA signatures were constructed in TCGA and possessed a strong predictive performance demonstrated through time-dependent ROC and KM survival analysis. Notably, the high-risk group exhibited an impaired response to anti-PD-1/PD-L1 (Programmed death-1 receptor/Programmed death-1 receptor-ligand) therapy compared to the low-risk group. The overall levels of the immune score were higher in the high-risk group. Additionally, drug sensitivity analysis observed that the model could effectively predict efficacy and sensitivity to chemotherapy. Enrichment analysis revealed that the IL6-JAK-STAT3 signaling pathway was a major pathway. IL4I1 could promote ccRCC cells’ malignant features through JAK1/STAT3 signaling pathway and M2-like macrophage polarization.ConclusionThe study elucidates that targeting fatty acids metabolism can affect the therapeutic effect of PD-1/PD-L1 in TME and related signal pathways. The model can effectively predict the response to several treatment options, underscoring its potential clinical utility.

Assessing temporal differences in the predictive power of baseline TyG-related parameters for future diabetes: an analysis using time-dependent receiver operating characteristics

BackgroundIt is known that measuring the triglyceride glucose (TyG) index and TyG-related parameters [triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC), and triglyceride glucose-waist to height ratio (TyG-WHtR)] can predict diabetes; this study aimed to compare the predictive value of the baseline TyG index and TyG-related parameters for the onset of diabetes at different future periods.MethodsWe conducted a longitudinal cohort study involving 15,464 Japanese people who had undergone health physical examinations. The subject’s TyG index and TyG-related parameters were measured at the first physical examination, and diabetes was defined according to the American Diabetes Association criteria. Multivariate Cox regression models and time-dependent receiver operating characteristic (ROC) curves were constructed to examine and compare the risk assessment/predictive value of the TyG index and TyG-related parameters for the onset of diabetes in different future periods.ResultsThe mean follow-up period of the current study cohort was 6.13 years, with a maximum of 13 years, and the incidence density of diabetes was 39.88/10,000 person-years. In multivariate Cox regression models with standardized hazard ratios (HRs), we found that both the TyG index and TyG-related parameters were significantly and positively associated with diabetes risk and that the TyG-related parameters were stronger in assessing diabetes risk than the TyG index, with TyG-WC being the best parameter (HR per SD increase: 1.70, 95% CI 1.46, 1.97). In addition, TyG-WC also showed the highest predictive accuracy in time-dependent ROC analysis for diabetes occurring in the short-term (2–6 years), while TyG-WHtR had the highest predictive accuracy and the most stable predictive threshold for predicting the onset of diabetes in the medium- to long-term (6–12 years).ConclusionsThese results suggest that the TyG index combined with BMI, WC, and WHtR can further improve its ability to assess/predict the risk of diabetes in different future periods, where TyG-WC was not only the best parameter for assessing diabetes risk but also the best risk marker for predicting future diabetes in the short-term, while TyG-WHtR may be more suitable for predicting future diabetes in the medium- to long-term.

CT-derived body composition associated with lung cancer recurrence after surgery

ObjectivesTo evaluate the impact of body composition derived from computed tomography (CT) scans on postoperative lung cancer recurrence. MethodsWe created a retrospective cohort of 363 lung cancer patients who underwent lung resections and had verified recurrence, death, or at least 5-year follow-up without either event. Five key body tissues and ten tumor features were automatically segmented and quantified based on preoperative whole-body CT scans (acquired as part of a PET-CT scan) and chest CT scans, respectively. Time-to-event analysis accounting for the competing event of death was performed to analyze the impact of body composition, tumor features, clinical information, and pathological features on lung cancer recurrence after surgery. The hazard ratio (HR) of normalized factors was used to assess individual significance univariately and in the combined models. The 5-fold cross-validated time-dependent receiver operating characteristics analysis, with an emphasis on the area under the 3-year ROC curve (AUC), was used to characterize the ability to predict lung cancer recurrence. ResultsBody tissues that showed a standalone potential to predict lung cancer recurrence include visceral adipose tissue (VAT) volume (HR = 0.88, p = 0.047), subcutaneous adipose tissue (SAT) density (HR = 1.14, p = 0.034), inter-muscle adipose tissue (IMAT) volume (HR = 0.83, p = 0.002), muscle density (HR = 1.27, p < 0.001), and total fat volume (HR = 0.89, p = 0.050). The CT-derived muscular and tumor features significantly contributed to a model including clinicopathological factors, resulting in an AUC of 0.78 (95% CI: 0.75–0.83) to predict recurrence at 3 years. ConclusionsBody composition features (e.g., muscle density, or muscle and inter-muscle adipose tissue volumes) can improve the prediction of recurrence when combined with clinicopathological factors.

Inflammatory and Nutritional Scoring System for Predicting Prognosis in Patients with Newly Diagnosed Multiple Myeloma

We aimed to assess the prognostic value of pretreatment inflammatory and nutritional parameters for predicting overall survival (OS) in patients with newly diagnosed multiple myeloma (NDMM), and to build a new scoring system using the most important variables. We retrospectively analyzed baseline clinical and laboratory data for patients with NDMM, who were randomly grouped into training and validation cohorts at a ratio of 8:2. The Inflammatory Nutritional Score (INS) was developed based on the least absolute shrinkage and selection operator (LASSO) Cox regression. The INS and other independent prognostic factors were entered into a multivariate Cox model and merged to generate a nomogram model for predictive optimization. Performance and predictive accuracy were assessed using the concordance index (C-index), calibration plots, and time-dependent receiver operating characteristic (ROC) curves. In total, 442 eligible patients were enrolled. Six inflammatory/nutritional variables, including the Nutritional Risk Index (NRI), body mass index (BMI), neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), and albumin-alkaline phosphatase ratio (AAPR), were integrated to construct the INS using the LASSO Cox model. The predictive nomogram constructed following the multivariate Cox analysis included INS, performance status, lactate dehydrogenase, age, and C-reactive protein. The model exhibited good predictive performance, with a C-index of 0.708 in the training cohort and 0.749 in the validation cohort. Moreover, the calibration curves also demonstrated excellent consistency between predicted and observed survival in both cohorts. In the time-dependent ROC analysis, our nomogram model exhibited better performance than other staging systems for multiple myeloma. The INS represents an independent prognostic signature in patients with NDMM. Our novel nomogram based on INS may aid in predicting survival probability and stratifying risk.

500 HEMODYNAMIC FORCES AS PREDICTORS OF CARDIAC REMODELING AND OUTCOME IN PATIENTS WTH HEART FAILURE WITH REDUCED EJECTION FRACTION TREATED WITH SACUBITRIL/VALSARTAN

Abstract Aims To evaluate the predictive value of echo-derived hemodynamic forces (HDF) compared to other echocardiographic, biohumoral and cardiopulmonary parameters on: a) angiotensin receptor-neprilysin inhibition (ARNI) response to 6-months treatment; b) cardiovascular events at follow-up. Methods Eighty-nine consecutive patients with heart failure with reduced ejection fraction (HFrEF) performed clinical, laboratory, ultrasound, and cardiopulmonary exercise testing. Patients experiencing no adverse events and showing ≥50% reduction in plasma N-terminal pro-B-type natriuretic peptide (NT-proBNP) and/or ≥10% increase in left ventricle ejection fraction over 6 months were considered responders to ARNI. We conducted a clinical follow-up for the composite endpoint of HF-related hospitalization, new-onset atrial fibrillation and cardiovascular death. Results Out of 89 patients, 45 (51%) were ARNI-responders. Among several variables evaluated at baseline, only the whole cardiac cycle left ventricle strength (wLVS) calculated from HDF was found to be higher in responders (4.4±1.3 vs 3.6±1.2; p=0.01) and the only independent predictor of ARNI-response at multivariate logistic regression analysis (odds ratio 1.36; 95% confidence interval 1.10–1.67; p=0.004), with good accuracy at receiver operating characteristic (ROC) analysis (optimal cut-off ≥3.7%; area under the curve [AUC]=0.736, 0.607–0.840; p&amp;lt;0.0001). During a median follow-up of 33 months (interquartile range 23-41), 6-month wLVS increase (ΔwLVS) showed a high discrimination ability at time-dependent ROC analysis (optimal cut-off ≥0.5%; AUC=0.811, 0.69–0.90; p&amp;lt;0.0001), stratified prognosis (log-rank p&amp;lt;0.0001) and remained an independent prognostic predictor for the composite endpoint (hazard ratio 0.76, 0.61–0.95; p&amp;lt;0.01), after adjusting for all clinical, functional and conventional echocardiographic parameters (Figure). Conclusions HDF analysis helps in predicting ARNI-response and optimizing follow-up and medical/device decision-making in patients with HFrEF.

Development of a 4-miRNA prognostic signature for endometrial cancer.

To develop an effective uterine corpus endometrial carcinoma (UCEC) risk assessment tool to monitor treatment outcomes. Limma package was used to analyze differentially expressed microRNAs (miRNAs) between UCEC tissues and normal tissues in the TCGA database. According to univariate Cox risk regression, least absolute shrinkage, and selection operator (LASSO) Cox analysis were performed to screen prognostic miRNAs and construct a risk scoring model. The prognostic performance of signature was evaluated by Kaplan–Meier and receiver operating characteristic. Multivariate Cox regression analysis was used to determine the independent prognostic factors of UCEC. Nomogram was constructed according to age, clinical stage, and risk score. A 4-miRNA signature based on miR-31-5p, miR-34a-5p, miR-26a-1-3p and miR-4772-3p was established. Risk scores of each patient were calculated by the 4-miRNA signature. After z-score, the patients were divided into high- and low-risk groups. The overall survival of high-risk patients was significantly shorter than that of low-risk patients, pointing to the high performance and independence of the 4-miRNA signature in predicting UCEC prognosis. The nomogram showed a high accuracy in predicting overall survival of UCEC patients. We developed a 4-miRNA signature that could effectively predict the prognosis of UCEC.

System analysis based on the pyroptosis-related genes identifies GSDMC as a novel therapy target for pancreatic adenocarcinoma

BackgroundPancreatic adenocarcinoma (PAAD) is one of the most common malignant tumors of the digestive tract. Pyroptosis is a newly discovered programmed cell death that highly correlated with the prognosis of tumors. However, the prognostic value of pyroptosis in PAAD remains unclear.MethodsA total of 178 pancreatic cancer PAAD samples and 167 normal samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. The “DESeq2” R package was used to identify differntially expressed pyroptosis-related genes between normal pancreatic samples and PAAD samples. The prognostic model was established in TCGA cohort based on univariate Cox and the least absolute shrinkage and selection operator (LASSO) Cox regression analyses, which was validated in test set from Gene Expression Omnibus (GEO) cohort. Univariate independent prognostic analysis and multivariate independent prognostic analysis were used to determine whether the risk score can be used as an independent prognostic factor to predict the clinicopathological features of PAAD patients. A nomogram was used to predict the survival probability of PAAD patients, which could help in clinical decision-making. The R package "pRRophetic" was applied to calculate the drug sensitivity of each samples from high- and low-risk group. Tumor immune infiltration was investigated using an ESTIMATE algorithm. Finally, the pro‐tumor phenotype of GSDMC was explored in PANC-1 and CFPAC-1 cells.ResultOn the basis of univariate Cox and LASSO regression analyses, we constructed a risk model with identified five pyroptosis-related genes (IL18, CASP4, NLRP1, GSDMC, and NLRP2), which was validated in the test set. The PAAD samples were divided into high-risk and low-risk groups on the basis of the risk score's median. According to Kaplan Meier curve analysis, samples from high-risk groups had worse outcomes than those from low-risk groups. The time-dependent receiver operating characteristics (ROC) analysis revealed that the risk model could predict the prognosis of PAAD accurately. A nomogram accompanied by calibration curves was presented for predicting 1-, 2-, and 3-year survival in PAAD patients. More importantly, 4 small molecular compounds (A.443654, PD.173074, Epothilone. B, Lapatinib) were identified, which might be potential drugs for the treatment of PAAD patients. Finally, the depletion of GSDMC inhibits the proliferation, invasion, and migration of pancreatic adenocarcinoma cells.ConclusionIn this study, we developed a pyroptosis-related prognostic model based on IL18, CASP4, NLRP1, NLRP2, and GSDMC , which may be helpful for clinicians to make clinical decisions for PAAD patients and provide valuable insights for individualized treatment. Our result suggest that GSDMC may promote the proliferation and migration of PAAD cell lines. These findings may provide new insights into the roles of pyroptosis-related genes in PAAD, and offer new therapeutic targets for the treatment of PAAD.

Proposal for multiple new lesions as complement of hyperprogressive disease in NSCLC patients treated with PD-1/PD-L1 immunotherapy

BackgroundHyperprogressive disease (HPD) is a progression pattern of rapid increase in tumor burden during immunotherapy. However, current HPD definitions are mainly based on the diameter of target lesions. How to take new lesions into account remains unknown. MethodsIn this retrospectively analysis, 393 patients received PD-1/PD-L1 inhibitors monotherapy. 237 patients were eligible for HPD evaluation based on tumor growth rate (TGR) ratio, ΔTGR or tumor growth kinetic (TGK) ratio. Among them, 214 patients were eligible for evaluation of new lesions. The impact of new lesions on overall survival (OS) was investigated by Kaplan-Meier methods. The optimal threshold for new lesion number was investigated by one-year time-dependent receiver operating characteristic (ROC) curves. Developing more than one new lesions (n ≥ 2) was defined as multiple new lesions (MNL). New HPD was redefined as both developing MNL and meeting the requirement of current HPD definitions (TGR ratio, ΔTGR or TGK ratio). The survival difference between the newly defined HPD and non-HPD patients was investigated. ResultsHPD occurred in 5.1–18.1 % patient based on current definitions (TGR ratio, 15.6 %; ΔTGR, 5.1 %; TGK ratio, 18.1 %). However, there is no significant difference between OS of HPD and non-HPD patient. New lesion was associated with a shorter median OS in PD（with or without HPD) patients (6.1 vs 18.9 months, p = 0.001). Time-dependent ROC analysis suggested that the optimal threshold for new lesion number in survival prediction was two. After the redefinition of HPD, New HPD patients had a significantly shorter median OS compared with non-HPD patients (TGR ratio with MNL: 5.6 vs 11.8 months, p < 0.001; ΔTGR with MNL: 5.0 vs 11.4 months, p = 0.034; TGK ratio with MNL: 5.7 vs 12.3 months, p < 0.001; respectively). ConclusionsCurrent HPD definitions had a better prognostic value when complemented with MNL. MNL should be integrated into the new definition of HPD.

Time-Dependent Receiver Operating Characteristic Analysis and Applications in the Field of Medicine

When there is a time-dependency between the biomarker and the event of interest (death, disease, relapse etc.), classical receiver operating characteristic (ROC) analysis may not be able to estimate the true performance of the biomarker. For such cases, time-dependent ROC, an extended version of the standard ROC, is developed. In this study, the aim is to demonstrate applications of this modified ROC method on medical datasets and find out if it should be preferred over classical ROC for time-dependent situations. Comparison between classical ROC and Kaplan-Meier (KM) estimator, which is one of the two time-dependent ROC estimators, has been made using datasets in this study. Nearest Neighbor Estimator (NNE), the alternative of KM estimator, is also applied on all datasets. Then the findings of these two approaches are compared. It is concluded that time-dependent ROC method is superior to the standard ROC analysis. In general, the closer to the event time, the higher performance is observed. Especially, biomarkers measured at last 12 or 6 months before the event are determined to be better at classification than the earlier measurements. Though in all applications KM and NNE yielded very similar results, the latter is considered to be more appropriate to evaluate the performance of a biomarker when a time dependent data is also censored. Results of this study show that time-dependent ROC analysis performs more accurately when there is a time dependency between the biomarker and the event of interest; therefore, it is recommended.