Stepwise Multivariate Cox Regression Research Articles

A Novel Immune-Related lncRNA-Based Model for Survival Prediction in Clear Cell Renal Cell Carcinoma.

Background Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer whose incidence and mortality rate are increasing. Identifying immune-related lncRNAs and constructing a model would probably provide new insights into biomarkers and immunotherapy for ccRCC and aid in the prognosis prediction. Methods The transcription profile and clinical information were obtained from The Cancer Genome Atlas (TCGA). Immune-related gene sets and transcription factor genes were downloaded from GSEA website and Cistrome database, respectively. Tumor samples were divided into the training set and the testing set. Immune-related differentially expressed lncRNAs (IDElncRNAs) were identified from the whole set. Univariate Cox regression, LASSO, and stepwise multivariate Cox regression were performed to screen out ideal prognostic IDElncRNAs (PIDElncRNAs) from the training set and develop a multi-lncRNA signature. Results Consequently, AC012236.1, AC078778.1, AC078950.1, AC087318.1, and AC092535.4 were screened to be significantly related to the prognosis of ccRCC patients, which were used to establish the five-lncRNA signature. Its wide diagnostic capacity was revealed in different subgroups of clinical parameters. Then AJCC-stage, Fuhrman-grade, pharmaceutical, age, and risk score regarded as independent prognostic factors were integrated to construct a nomogram, whose good performance in predicting 3-, 5-, and 7-year overall survival of ccRCC patients was revealed by time-dependent ROC curves and verified by the testing sets and ICGC dataset. The calibration plots showed great agreement of the nomogram between predicted and observed outcomes. Functional enrichment analysis showed the signature and each lncRNA were mainly enriched in pathways associated with regulation of immune response. Several kinds of tumor-infiltrating immune cells like regulatory T cells, T follicular helper cells, CD8+ T cells, resting mast cells, and naïve B cells were significantly correlated with the signature. Conclusion Therefore, we constructed a five-lncRNA model integrating clinical parameters to help predict the prognosis of ccRCC patients. The five immune-related lncRNAs could potentially be therapeutic targets for immunotherapy in ccRCC in the future.

The Clinical Significance of Procalcitonin Elevation in Patients over 75 Years Old Admitted for COVID-19 Pneumonia.

Aim To investigate the clinical significance of procalcitonin (PCT) elevation on hospital admission for coronavirus disease-19 (COVID-19) and its association with mortality in oldest old patients (age > 75 years). Methods The clinical records of 1074 patients with chest high-resolution computed-tomography (HRCT) positive for interstitial pneumonia and symptoms compatible for COVID-19, hospitalized in medical wards during the first pandemic wave in a single academic center in Northern Italy, were retrospectively analyzed. All patients had serum PCT testing performed within six hours from admission. Information on COVID-19-related symptoms, comorbidities, drugs, autonomy in daily activities, respiratory exchanges, other routine lab tests, and outcomes were collected. Clinical characteristics were compared across different admission PCT levels and ages. The association of admission PCT with mortality was tested separately in participants aged > 75 and ≤75 years old by stepwise multivariate Cox regression model with forward selection. Results With increasing classes of PCT levels (<0.05, 0.05-0.49, 0.5-1.99, and ≥2 ng/ml), there was a significant trend (P < 0.0001) towards older age, male gender, wider extension of lung involvement on HRCT, worse respiratory exchanges, and several other laboratory abnormalities. Each incremental PCT class was associated with increased risk of hospital death at multivariate models in subjects older than 75 (hazard ratio for PCT ≥ 2 vs. <0.05 ng/ml: 30.629, 95% confidence interval 4.176-224.645, P = 0.001), but not in subjects aged 75 or younger. Conclusions In patients admitted for COVID-19, PCT elevation was associated with several clinical, radiological, and laboratory characteristics of disease severity. However, PCT elevation was strongly associated with hospital mortality only in oldest old subjects (age > 75).

Prognostic value of stress cardiovascular magnetic resonance in asymptomatic patients without known coronary artery disease.

A few studies suggest a significant prognostic value of silent myocardial ischaemia detected in asymptomatic patients. However, the current guidelines do not recommend stress testing in asymptomatic individuals. To assess the long-term prognostic value of vasodilator stress perfusion cardiovascular magnetic resonance (CMR) in asymptomatic individuals without known coronary artery disease (CAD). Between 2009 and 2011, a retrospective cohort study with a median follow-up of 9.2years (interquartile range: 7.8-9.6) included 1,027 consecutive asymptomatic individuals with ≥ 2 cardiovascular risk factors but without known known CAD referred for stress CMR. Major adverse cardiovascular events (MACE) included cardiovascular mortality and nonfatal myocardial infarction (MI). Among 1,027 asymptomatic subjects, 903 (87.9%) (mean age 70.6 ± 12.4years and 46.2% males) completed the follow-up, and 91 had MACE (10.1%). Using Kaplan-Meier analysis, silent ischaemia and unrecognised MI were associated with MACE (hazard ratio [HR]: 8.70; 95% CI: 5.79-13.10 and HR: 3.40; 95% CI: 2.15-5.38, respectively; both p < 0.001). In multivariable stepwise Cox regression, silent ischaemia and unrecognised MI were independent predictors of MACE (HR: 6.66; 95% CI 4.41-9.23; and HR: 2.42; 95% CI 1.23-3.21, respectively; both p < 0.001). The addition of silent ischaemia and unrecognised MI led to improved model discrimination for MACE (change in C statistic from 0.66 to 0.82; NRI = 0.497; IDI = 0.070). Silent ischaemia and unrecognised MI are good long-term predictors for the incidence of MACE in selected asymptomatic individuals with multiple risk factors and without known CAD. These stress CMR parameters have incremental long-term prognostic value to predict MACE over traditional risk factors. • Silent ischaemia and unrecognised myocardial infarction defined by stress CMR are good long-term predictors of cardiovascular events in asymptomatic individuals without known coronary artery disease. • The addition of stress cardiac MR imaging led to improved model discrimination for cardiovascular events over traditional risk factors in this specific population.

Prognostic Value of Vasodilator Stress Perfusion Cardiovascular Magnetic Resonance in Patients With Prior Myocardial Infarction

ObjectivesThis study sought to assess the incremental prognostic value of vasodilator stress cardiovascular magnetic resonance (CMR) in patients with prior myocardial infarction (MI). BackgroundRecurrent MI is a major cause of mortality and morbidity among MI survivors. MethodsBetween 2008 and 2019, consecutive patients with prior MI referred for stress CMR were followed up for the occurrence of major adverse cardiovascular events (MACE), defined by cardiovascular mortality or recurrent nonfatal MI. Uni- and multivariable Cox regressions were performed to determine the prognostic value of inducible ischemia and the extent of myocardial scar. ResultsAmong 1,594 patients with prior MI and myocardial scar on CMR, 1,401 (92%) (68.2 ± 11.0 years; 61.4% men) completed the follow-up (median: 6.2 years), and 205 had MACE (14.6%). Patients without inducible ischemia experienced a lower annual rate of MACE (3.1%) than those with 1–2 (4.9%), 3–5 (21.5%), or ≥6 segments of ischemia (45.7%) (all p < 0.01). Using Kaplan-Meier analysis, the presence of inducible ischemia and the extent of scar were associated with MACE (hazard ratio [HR]:3.52; 95% confidence interval [CI]: 2.67 to 4.65 and HR: 1.66; 95% CI: 1.53 to 2.18, respectively; both p < 0.001). In multivariable stepwise Cox regression, the presence of ischemia and the extent of scar were independent predictors of MACE (HR: 2.84; 95% CI: 2.14 to 3.78 and HR: 1.57; 95% CI: 1.44 to 1.72, respectively; both p < 0.001). These findings were significant in both symptomatic and asymptomatic patients. The addition of CMR parameters to the model including traditional risk factors resulted in a better discrimination for MACE (C-statistic: 0.76 vs. 0.62). ConclusionsIn patients with prior MI, vasodilator stress CMR has independent and incremental prognostic value over traditional risk factors.

A Combined RNA Signature Predicts Recurrence Risk of Stage I-IIIA Lung Squamous Cell Carcinoma

ObjectiveRecurrence remains the main cause of the poor prognosis in stage I-IIIA lung squamous cell carcinoma (LUSC) after surgical resection. In the present study, we aimed to identify the long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) related to the recurrence of stage I-IIIA LUSC. Moreover, we constructed a risk assessment model to predict the recurrence of LUSC patients.MethodsRNA sequencing data (including miRNAs, lncRNAs, and mRNAs) and relevant clinical information were obtained from The Cancer Genome Atlas (TCGA) database. The differentially expressed lncRNAs, miRNAs, and mRNAs were identified using the “DESeq2” package of the R language. Univariate Cox proportional hazards regression analysis and Kaplan-Meier curve were used to identify recurrence-related genes. Stepwise multivariate Cox regression analysis was carried out to establish a risk model for predicting recurrence in the training cohort. Moreover, Kaplan-Meier curves and receiver operating characteristic (ROC) curves were adopted to examine the predictive performance of the signature in the training cohort, validation cohort, and entire cohort.ResultsBased on the TCGA database, we analyzed the differentially expressed genes (DEGs) among 27 patients with recurrent stage I-IIIA LUSC and 134 patients with non-recurrent stage I-IIIA LUSC, and identified 431 lncRNAs, 36 miRNAs, and 746 mRNAs with different expression levels. Out of these DEGs, the optimal combination of DEGs was finally determined, and a nine-joint RNA molecular signature was constructed for clinical prediction of recurrence, including LINC02683, AC244517.5, LINC02418, LINC01322, AC011468.3, hsa-mir-6825, AC020637.1, AC027117.2, and SERPINB12. The ROC curve proved that the model had good predictive performance in predicting recurrence. The area under the curve (AUC) of the prognostic model for recurrence-free survival (RFS) was 0.989 at 3 years and 0.958 at 5 years (in the training set). The combined RNA signature also revealed good predictive performance in predicting the recurrence in the validation cohort and entire cohort.ConclusionsIn the present study, we constructed a nine-joint RNA molecular signature for recurrence prediction of stage I-IIIA LUSC. Collectively, our findings provided new and valuable clinical evidence for predicting the recurrence and targeted treatment of stage I-IIIA LUSC.

Factors Associated with Durable Progression-Free Survival in Relapsed or Refractory Multiple Myeloma Patients after Potent Anti-BCMA CAR-T Cell Therapy

Background: B-cell maturation antigen (BCMA) chimeric antigen receptor T (CAR-T) cell therapy results in high remission rates in patients with relapsed/refractory (R/R) multiple myeloma (MM). However, the factors associated with prognosis following CAR-T cell therapy are unknown. Methods: Between July 1, 2018, and July 31, 2020, 61 patients with R/R MM received anti-BCMA CAR-T cell therapy (Chictr.org number, ChiCTR1800017404). Stepwise multivariate Cox regression and competing risk analyses were conducted to identify poor prognosis-associated risk factors. Findings: Sixty patients (98·4%) experienced cytokine release syndrome (CRS), including seven, 26, 23, and four cases of CRS grades 1, 2, 3, and 4, respectively. Only five cases of reversible neurological toxicities occurred. The objective response rate (ORR) was 98·3%, and the complete response (CR) rate was 70·3%. With a median follow-up period of 21·1 months, the one-year overall survival (OS) and progression-free survival (PFS) rates were 78·0% and 50·2%, respectively. The median PFS was 12·7 months. Multivariate Cox modeling revealed that poor PFS was associated with extramedullary disease (hazard ratio (HR)=2 ·59, 95% confidence interval (95%CI)=1·29–5·21, P =0·008), light chain MM (HR=2·53, 95%CI=1·03–5·97, P =0·035), high-risk cytogenetics (HR=2·80, 95%CI=1·27–6·14, P =0·01), and prior treatment with >3 therapeutic lines (HR=3·14, 95%CI=1·34–7·34, P =0·008). Among the 41 complete remission cases, competing risk analyses demonstrated higher relapse predispositions in those with extramedullary disease (HR=4·51, 95%CI=1·86 –10·9, P =0·001), light chain MM (HR=4·89, 95%CI=1·52 –15·7, P =0·008), or high-risk cytogenetics (HR=5·09, 95%CI=1·63 –15·9, P =0·005). Furthermore, patients with more risk factors had worse outcomes. Interpretation: Anti-BCMA CAR-T cell therapy is safe and effective for R/R MM. For patients with high-risk factors, improvements to extend remission and more specific individualized therapies are needed. Funding: Natural Science Foundation of China, Key Project of Science and Technology Department of Zhejiang Province, Key R&D Project of Zhejiang Science and Technology Department, National Key Basic Research Program of China, National Natural Science Foundation of China. Declaration of Interest: AHC is a founding member of Shanghai YaKe Biotechnology Ltd., a biotechnology company focused on research and development of tumor cellular immunotherapy. The remaining authors declare no conflict of interest. Ethical Approval: The protocol was approved by the 1st Affiliated Hospital, School of Medicine, Zhejiang University Institutional Review Board. All patients provided written informed consent to participate in the study.

Prognosis and Characterization of Immune Microenvironment in Acute Myeloid Leukemia Through Identification of an Autophagy-Related Signature.

Acute myeloid leukemia (AML) is one of the most common hematopoietic malignancies that has an unfavorable outcome and a high rate of relapse. Autophagy plays a vital role in the development of and therapeutic responses to leukemia. This study identifies a potential autophagy-related signature to monitor the prognoses of patients of AML. Transcriptomic profiles of AML patients (GSE37642) with the relevant clinical information were downloaded from Gene Expression Omnibus (GEO) as the training set while TCGA-AML and GSE12417 were used as validation cohorts. Univariate regression analyses and multivariate stepwise Cox regression analysis were respectively applied to identify the autophagy-related signature. The univariate Cox regression analysis identified 32 autophagy-related genes (ARGs) that were significantly associated with the overall survival (OS) of the patients, and were mainly rich in signaling pathways for autophagy, p53, AMPK, and TNF. A prognostic signature that comprised eight ARGs (BAG3, CALCOCO2, CAMKK2, CANX, DAPK1, P4HB, TSC2, and ULK1) and had good predictive capacity was established by LASSO–Cox stepwise regression analysis. High-risk patients were found to have significantly shorter OS than patients in low-risk group. The signature can be used as an independent prognostic predictor after adjusting for clinicopathological parameters, and was validated on two external AML sets. Differentially expressed genes analyzed in two groups were involved in inflammatory and immune signaling pathways. An analysis of tumor-infiltrating immune cells confirmed that high-risk patients had a strong immunosuppressive microenvironment. Potential druggable OS-related ARGs were then investigated through protein–drug interactions. This study provides a systematic analysis of ARGs and develops an OS-related prognostic predictor for AML patients. Further work is needed to verify its clinical utility and identify the underlying molecular mechanisms in AML.

Predicting local tumour progression after ablation for colorectal liver metastases: CT-based radiomics of the ablation zone

PurposeTo assess whether CT-based radiomics of the ablation zone (AZ) can predict local tumour progression (LTP) after thermal ablation for colorectal liver metastases (CRLM). Materials and methodsEighty-two patients with 127 CRLM were included. Radiomics features (with different filters) were extracted from the AZ and a 10 mm periablational rim (PAR)on portal-venous-phase CT up to 8 weeks after ablation. Multivariable stepwise Cox regression analyses were used to predict LTP based on clinical and radiomics features. Performance (concordance [c]-statistics) of the different models was compared and performance in an ‘independent’ dataset was approximated with bootstrapped leave-one-out-cross-validation (LOOCV). ResultsThirty-three lesions (26 %) developed LTP. Median follow-up was 21 months (range 6−115).The combined model, a combination of clinical and radiomics features, included chemotherapy (HR 0.50, p = 0.024), cT-stage (HR 10.13, p = 0.016), lesion size (HR 1.11, p = <0.001), AZ_Skewness (HR 1.58, p = 0.016), AZ_Uniformity (HR 0.45, p = 0.002), PAR_Mean (HR 0.52, p = 0.008), PAR_Skewness (HR 1.67, p = 0.019) and PAR_Uniformity (HR 3.35, p < 0.001) as relevant predictors for LTP. The predictive performance of the combined model (after LOOCV) yielded a c-statistic of 0.78 (95 %CI 0.65−0.87), compared to the clinical or radiomics models only (c-statistic 0.74 (95 %CI 0.58−0.84) and 0.65 (95 %CI 0.52−0.83), respectively). ConclusionCombining radiomics features with clinical features yielded a better performing prediction of LTP than radiomics only. CT-based radiomics of the AZ and PAR may have potential to aid in the prediction of LTP during follow-up in patients with CRLM.

Identification of a DNA Repair Gene Signature and Establishment of a Prognostic Nomogram Predicting Biochemical-Recurrence-Free Survival of Prostate Cancer.

Background: The incidence of prostate cancer (PCa) is high and increasing worldwide. The prognosis of PCa is relatively good, but it is important to identify the patients with a high risk of biochemical recurrence (BCR) so that additional treatment could be applied. Method: Level 3 mRNA expression and clinicopathological data were obtained from The Cancer Genome Atlas (TCGA) to serve as training data. The GSE84042 dataset was used as a validation set. Univariate Cox, lasso Cox, and stepwise multivariate Cox regression were applied to identify a DNA repair gene (DRG) signature. The performance of the DRG signature was assessed based on Kaplan–Meier curve, receiver operating characteristic (ROC), and Harrell’s concordance index (C-index). Furtherly, a prognostic nomogram was established and evaluated likewise. Results: A novel four DRG signature was established to predict BCR of PCa, which included POLM, NUDT15, AEN, and HELQ. The ROC and C index presented good performance in both training dataset and validation dataset. The patients were stratified by the signature into high- and low-risk groups with distinct BCR survival. Multivariate Cox analysis revealed that the DRG signature is an independent prognostic factor for PCa. Also, the DRG signature high-risk was related to a higher homologous recombination deficiency (HRD) score. The nomogram, incorporating the DRG signature and clinicopathological parameters, was able to predict the BCR with high efficiency and showed superior performance compared to models that consisted of only clinicopathological parameters. Conclusion: Our study identified a DRG signature and established a prognostic nomogram, which were reliable in predicting the BCR of PCa. This model could help with individualized treatment and medical decision making.

A 15-Gene Signature and Prognostic Nomogram for Predicting Overall Survival in Non-Distant Metastatic Oral Tongue Squamous Cell Carcinoma.

BackgroundOral tongue squamous cell carcinoma (OTSCC) is a devastating tumor with poor prognosis. There is an urgent need for reliable biomarkers to help predict prognosis and guide treatment for OTSCC. In the current study, we aimed to develop a robust multi-gene signature and prognostic nomogram to predict the prognosis of patients with non-distant metastatic OTSCC.MethodsOTSCC-related differentially-expressed genes were screened from The Cancer Genome Atlas (TCGA) database. Univariate Cox regression based on 1,000 bootstrap replicates, LASSO regression and stepwise multivariate Cox regression were utilized to develop a novel multi-mRNA signature for predicting overall survival in OTSCC. The concordance index, area under receiver operating characteristic (ROC AUC) and calibration curve were employed to assess the prediction capacity of the novel multi-gene model. In addition, a prognostic nomogram was constructed to facilitate the clinical use of the fitted model. The Kaplan-Meier with log-rank test was employed to assess differences in overall survival.ResultsWe successfully established a novel 15-mRNA prognostic model for predicting overall survival of non-distant metastatic OTSCC, involving ADTRP, ITGA3, RFC4, CCDC96, CYP2J2, NELL2, SPHK1, SPAG16, HBEGF, S100A9, EGFL6, ADGRG6, PDE4D, ABCA4, and CTTN. The prediction ability of this 15-gene signature was independent of other clinicopathological factors, with an HR of 11.5 (95% CI: 4.70–28.3). Moreover, internal validation by bootstrap analysis yielded a C-index of 0.849, with a 3-year AUC of 0.907 and 5-year AUC of 0.944, which implied excellent prediction accuracy of the fitted model. In addition, external validation by using the GEO dataset (GSE41116) yielded a C-index of 0.804, with a 3-year AUC of 0.868 and 5-year AUC of 0.855, which also indicated good prediction ability of the 15-gene model. Finally, a prognostic nomogram integrating risk group, grade, T stage and N stage was established.ConclusionOur results demonstrate our 15-gene signature was independently associated with overall survival in non-distant metastatic OTSCC. Moreover, the prognostic nomogram integrating the 15-gene signature and clinicopathological factors has potential to be developed as a prognostic tool.

A Risk Signature with Nine Stemness Index-Associated Genes for Predicting Survival of Patients with Uterine Corpus Endometrial Carcinoma.

Purpose To identify mRNA expression-based stemness index- (mRNAsi-) related genes and build an mRNAsi-related risk signature for endometrial cancer. Methods We collected mRNAsi data of endometrial cancer samples from The Cancer Genome Atlas (TCGA) and analyzed their relationship with the main clinicopathological characteristics and prognosis of endometrial cancer patients. We screened the top 50% of the genes in TCGA for weighted gene correlation network analysis (WGCNA) to explore mRNAsi-related gene sets. Among these mRNAsi-related genes, we further screened for those related to the prognosis of endometrial cancer patients via univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Using stepwise multivariate Cox regression analysis, a stemness index-related risk signature was constructed. Finally, we identified potential prognostic biomarkers for endometrial cancer by combining the GEO database and immunohistochemical staining. Results The mRNAsi of endometrial cancer samples was significantly higher than that of normal samples and was related to the International Federation of Gynecology and Obstetrics (FIGO) stage, pathological grade, postoperative tumor status, and overall survival of endometrial cancer patients. We identified 21 mRNAsi-related gene modules, and 1,324 genes were obtained from the most relevant module. TCGA samples were divided into training and validation cohorts, and the training cohort was used to construct a nine-mRNAsi-related gene signature (B3GAT2, CD3EAP, DMC1, FRMPD3, LINC01224, LINC02068, LY6H, NR6A1, and TLE2). High-risk and low-risk patients had significant prognostic differences, and the risk signature could accurately predict their 1-, 3-, and 5-year survival. The nomogram composed of risk score and multiple clinicopathological features could accurately predict 1-, 3-, and 5-year survival. Finally, CD3EAP was found to be a novel prognostic biomarker for endometrial cancer. Conclusion Endometrial cancer cell stemness is related to patient prognosis. The nine-gene risk signature is an independent prognostic factor and can accurately predict endometrial cancer patient prognosis.

Prognostic value of stress cardiovascular magnetic resonance in asymptomatic patients with known coronary artery disease

BackgroundSeveral studies have established the prognostic value of vasodilator stress cardiovascular magnetic resonance (CMR) in broad population of patients with suspected or known coronary artery disease (CAD), but this specific population of asymptomatic patients with known CAD have never been formally evaluated. To assess the long-term prognostic value of vasodilator stress perfusion CMR in asymptomatic patients with obstructive CAD.MethodsBetween 2009 and 2011, consecutive asymptomatic patients with obstructive CAD referred for vasodilator stress CMR were followed for the occurrence of major adverse cardiovascular events (MACE), defined by cardiovascular mortality or recurrent non-fatal myocardial infarction (MI). Uni- and multivariable Cox regressions were performed to determine the prognostic value of myocardial ischemia and myocardial infarction defined by late gadolinium enhancement (LGE) with ischemic pattern.ResultsAmong 1529 asymptomatic patients with obstructive CAD, 1342 (87.8%; 67.7 ± 10.5 years, 82.0% males) completed the follow-up (median 8.3 years), and 195 had MACE (14.5%). Patients without stress-induced myocardial ischemia had a low annualized rate of MACE (2.4%), whereas the annualized rate of MACE was higher for patients with mild, moderate, or severe ischemia (7.3%, 16.8%, and 42.2%, respectively; ptrend < 0.001). Using Kaplan–Meier analysis, myocardial ischemia and LGE were associated with MACE (hazard ratio, HR 2.52; 95% CI 1.90–3.34 and HR 2.04; 95% CI 1.38–3.03, respectively; both p < 0.001). In multivariable stepwise Cox regression, myocardial ischemia and LGE were independent predictors of MACE (HR 2.80 95% CI 2.10–3.73, p < 0.001 and HR 1.51; 95% CI 1.01–2.27, p = 0.045; respectively). The addition of myocardial ischemia and LGE led to improved model discrimination for MACE (change in C statistic from 0.61 to 0.68; NRI = 0.207; IDI = 0.021).ConclusionsVasodilator stress CMR-induced myocardial ischemia and LGE are good long-term predictors for the incidence of MACE in asymptomatic patients with obstructive CAD.

Long-term prognostic value of stress perfusion cardiovascular magnetic resonance in patients without known coronary artery disease

BackgroundTo assess the incremental long-term prognostic value of vasodilator stress perfusion cardiovascular magnetic resonance (CMR) in patients without known coronary artery disease (CAD).MethodsBetween 2010 and 2011, consecutive patients with cardiovascular risk factors without known CAD referred for stress CMR were followed for the occurrence of major adverse cardiac events (MACE), defined by cardiovascular mortality or recurrent non-fatal myocardial infarction (MI). Uni- and multivariable Cox regressions were performed to determine the prognostic value of ischemia and unrecognized MI defined by sub-endocardial or transmural late gadolinium enhancement (LGE).ResultsAmong 2,295 patients without known CAD, 2058 (89.7%) (71.2 ± 12.5 years; 37.5% males) completed the follow-up (median [IQR]: 8.3 [7.3–8.7] years), and 203 had MACE (9.9%). Using Kaplan–Meier analysis, ischemia and unrecognized MI were associated with MACE (hazard ratio, HR: 4.64 95% CI: 3.69–6.17 and HR: 2.88; 95% CI: 2.08–3.99, respectively; both p < 0.001). In multivariable stepwise Cox regression, ischemia and unrecognized MI were independent predictors of MACE (HR = 3.71; 95% CI 2.73–5.05, p < 0.001 and HR = 1.73; 95% CI 1.22–2.45, p = 0.002; respectively) and cardiovascular mortality (HR: 3.13; 95% CI: 2.17–4.51, p < 0.001 and HR = 1.73; 95% CI 1.15–2.62, p = 0.009; respectively). The addition of ischemia and unrecognized MI led to an improved model discrimination for MACE (change in C statistic from 0.61 to 0.72; NRI = 0.431; IDI = 0.053).ConclusionsInducible ischemia and unrecognized MI identified by stress CMR have incremental long term prognostic value for the incidence of MACE in patients without known CAD over traditional risk factors and left ventricular ejection fraction.

Enhanced expression of FGF19 predicts poor prognosis in patients with non-small cell lung cancer.

BackgroundLung cancer is one of the most common cancers and a leading cause of cancer-related death worldwide. Although many treatment options exist for lung cancer, some patients still suffer postoperative recurrence, and a consequent reduction of overall survival (OS). Our study aimed to investigate the correlation of FGF19 expression with the clinicopathological features and survival outcomes of non-small cell lung cancer (NSCLC) patients.MethodsBioinformatics analysis was conducted using the data from The Cancer Genome Atlas (TCGA) database to distinguish between the FGF19 levels of tumor and normal tissue and to determine their correlation with the OS. A total of 187 NSCLC patients who underwent radical resection of lung cancer were enrolled, and tissues were collected to determine FGF19 expression by immunohistochemistry (IHC) assay. Clinicopathological features including the survival date were collected for detailed research.ResultsAccording to the analysis based on the TCGA database, we found that the NSCLC tissues exhibited enhanced FGF19 messenger RNA (mRNA) expression and that the FGF19 mRNA levels correlated with shorter OS in NSCLC patients. IHC staining indicated that 88 (47.1%) patients had high FGF19 expression and 99 (52.9%) patients had low FGF19 expression. Meanwhile, survival data showed that high FGF19 expression was correlated with reduced OS (P<0.001). Moreover, both the univariate analysis and the forward stepwise multivariate Cox regression revealed that high FGF19 expression was an independent prognostic factor for decreased OS (P=0.001).ConclusionsThe expression of FGF19 is significantly upregulated in NSCLC, and the overexpression of FGF19 is correlated with poor OS, especially in lung adenocarcinoma (LUAD) cases. FGF19 might serve as a potential biomarker for predicting poor OS in NSCLC patients.

Prognostic value of fast semi-automated left atrial long-axis strain analysis in hypertrophic cardiomyopathy

BackgroundThe prognostic value of left atrial (LA) size and function in hypertrophic cardiomyopathy (HCM) is well recognized, but LA function is difficult to routinely analyze. Fast LA long-axis strain (LA-LAS) analysis is a novel technique to assess LA function on cine cardiovascular magnetic resonance (CMR). We aimed to assess the association between fast LA-LAS and adverse clinical outcomes in patients with HCM.Methods359 HCM patients and 100 healthy controls underwent routine CMR imaging. Fast LA-LAS was analyzed by automatically tracking the length between the midpoint of posterior LA wall and the left atrioventricular junction based on standard 2- and 4-chamber balanced steady-state free precession cine-CMR. Three strain parameters including reservoir strain (εs), conduit strain (εe), and active strain (εa) were assessed. The endpoint was set as composite adverse events including cardiovascular death, resuscitated cardiac arrest, sudden cardiac death aborted by appropriate implantable cardioverter-defibrillator discharge, and hospital admission related to heart failure.ResultsDuring an average follow-up of 40.9 months, 59 patients (19.7%) reached endpoints. LA strains were correlated with LA diameter, LA volume index (LAVI) and LA empty fraction (LAEF) (all p < 0.05). In the stepwise multivariate Cox regression analysis, εs and εe (hazard ratio, 0.94 and 0.89; p = 0.019 and 0.006, respectively) emerged as independent predictors of the composite adverse events. Fast LA εs and LA εe are stronger prognostic factors than LA size, LAVI and the presence of left ventricular late gadolinium enhancement.ConclusionsFast LA reservoir and conduit strains are independently associated with adverse outcomes in HCM.

Identification and Validation of a Novel Immune-Related Four-lncRNA Signature for Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is a major subtype of lung cancer, the prognosis of patients with which is associated with both lncRNAs and cancer immunity. In this study, we collected gene expression data of 585 LUAD patients from The Cancer Genome Atlas (TCGA) database and 605 subjects from the Gene Expression Omnibus (GEO) database. LUAD patients were divided into high and low immune-cell-infiltrated groups according to the single sample gene set enrichment analysis (ssGSEA) algorithm to identify differentially expressed genes (DEGs). Based on the 49 immune-related DE lncRNAs, a four-lncRNA prognostic signature was constructed by applying least absolute shrinkage and selection operator (LASSO) regression, univariate Cox regression, and stepwise multivariate Cox regression in sequence. Kaplan–Meier curve, ROC analysis, and the testing GEO datasets verified the effectiveness of the signature in predicting overall survival (OS). Univariate Cox regression and multivariate Cox regression suggested that the signature was an independent prognostic factor. The correlation analysis revealed that the infiltration immune cell subtypes were related to these lncRNAs.

MMSE is an independent prognostic factor for survival in primary central nervous system lymphoma

IntroductionTo assess the value of the Mini-Mental State Examination (MMSE)-score at baseline in predicting survival in adult primary central nervous system lymphoma (PCNSL) patients.MethodsIn the HOVON 105/ ALLG NHL 24 phase III study patients with newly-diagnosed PCNSL were randomized between high-dose methotrexate-based chemotherapy with or without rituximab. Data on potential (MMSE-score), and known baseline prognostic factors (age, performance status, serum LDH, cerebrospinal fluid total protein, involvement of deep brain structures, multiple cerebral lesions, and the IELSG-score) were collected prospectively. Multivariable stepwise Cox regression analyses were used to assess the prognostic value of all factors on progression-free survival (PFS) and overall survival (OS) among patients with available MMSE score at baseline. Age was analyzed as continuous variable, the MMSE-score both as a continuous and as a categorical variable.ResultsIn univariable analysis, age, MMSE-score and whether the patient received rituximab were statistically significantly prognostic factors for PFS. Age and MMSE-score were statistically significantly associated with OS. In a multivariable analysis of the univariately significant factors only MMSE-score was independently associated with the survival endpoints, as a continuous variable (HR for PFS 1.04, 95% CI 1.01–1.08; OS 1.06 (95% CI 1.02–1.10) and as categorical variable HR (< 27 versus ≥ 27 for PFS 1.55 (1.02–2.35); OS 1.68 (1.05–2.70). In our population, performance status, serum LDH, and CSF protein level were not of prognostic value.ConclusionNeurocognitive disturbances, measured with the MMSE at baseline, are an unfavorable prognostic factor for both PFS and OS in adult PCNSL patients up to 70 years-old.

Ferroptosis-related gene signature as a prognostic marker for lower-grade gliomas.

Ferroptosis is a newly discovered form of programmed cell death, which has unique biological effects on metabolism and redox biology. In this study, the prognostic value of ferroptosis‐related genes was investigated in lower‐grade gliomas (LGG). We downloaded the ferroptosis‐related genes from the FerrDb dataset. Univariate Cox and LASSO regression analyses were applied to identify genes correlated with overall survival (OS). Subsequently, 12 ferroptosis‐related genes were screened to establish the prognostic signature using stepwise multivariate Cox regression. According to the median value of risk scores, patients were divided into low‐ and high‐risk subgroups. The Kaplan‐Meier curves showed the high‐risk group had a lower OS. The predictive power of the risk model was validated using the CGGA. Functional analysis revealed that the terms associated with plasma membrane receptor complex, immune response and glutamate metabolic process were primarily related to the risk model. Moreover, we established a nomogram that had a strong forecasting ability for the 1‐, 3‐ and 5‐year OS. In addition, we compared the risk scores between different clinical features. We also detected infiltration of macrophages and monocytes in different subgroups. Overall, our study identified the prognostic signature of 12 ferroptosis‐related genes, which has the potential to predict the prognosis of LGG.

Both muscle quantity and quality are predictors of waiting list mortality in patients with end-stage liver disease.

Malnutrition is highly prevalent in patients with end-stage liver disease (ESLD) and associated with impaired clinical outcome. Previous studies focused on one component of body composition and not in combination with nutritional intake, while both are components of the nutritional status. We aimed to evaluate the most important risk factors regarding body composition (muscle mass, muscle quality and fat mass) and nutritional intake (energy and protein intake) for waiting list mortality in patients with ESLD awaiting liver transplantation (LTx). Consecutive patients with ESLD listed for LTx between 2007 and 2014 were investigated. Muscle mass quantity (Skeletal Muscle Mass Index, SMI), and muscle quality (Muscle Attenuation, MA), and various body fat compartments were measured on computed tomography using SliceOmatic. Nutritional intake (e.g. energy and protein intake) was assessed. Multivariable stepwise forward Cox regression analysis was used for statistical analysis. 261 Patients (mean age 54 years, 74.7% male) were included. Low SMI and MA were found to be statistically significant predictors of an increased risk for waiting list mortality in patients with ESLD, with a HR of 2.580 (95%CI 1.055-6.308) and HR of 9.124 (95%CI 2.871-28.970), respectively. No association between percentage adipose tissue, and protein and energy intake with waiting list mortality was found in this study. Both low muscle quantity and quality, and not nutritional intake, were independent risk factors for mortality in patients with ESLD.

Feasibility and prognostic value of vasodilator stress perfusion CMR in patients with atrial fibrillation

Abstract Funding Acknowledgements Type of funding sources: None. BACKGROUND Several studies have demonstrated the consistently high diagnostic and prognostic value of stress perfusion imaging with cardiovascular magnetic resonance (CMR). The feasibility and the prognostic value of vasodilator stress perfusion CMR in patients with atrial fibrillation (AF) is unknown, because most studies have excluded arrhythmic patients from analysis. PURPOSE The aim of our study was to assess the technical feasibility and the prognostic value of vasodilator stress perfusion CMR in patients with AF. METHODS Between 2008 and 2018, we prospectively included consecutive patients with AF referred for vasodilator stress perfusion CMR with dipyridamole. They were followed for the occurrence of major adverse cardiovascular events (MACE) defined as cardiac death or non-fatal myocardial infarction (MI). The secondary outcome was all-cause mortality. The diagnosis of AF was confirmed on 12-lead ECG before and after CMR, and patients with sinus rhythm during CMR were excluded. In the CMR protocol, to limit AF-related artifacts on cine images, an arrhythmia rejection algorithm, or real-time sequences were used. Univariable and multivariable Cox regressions for MACE were performed to determine the prognostic value of inducible ischemia or late gadolinium enhancement (LGE) by CMR. RESULTS Of 639 patients with AF and suspected or stable chronic CAD (72 ± 9 years, 77% men), 602 (94%) completed the CMR protocol, and among those 538 (89%) completed the follow-up (median follow-up 5.1 (3.3–7.1) years). Reasons for failure to complete CMR included AF-related ECG-gating problems (n = 17), intolerance to stress agent (n = 7), renal failure (n = 6), declining participation (n = 4) and claustrophobia (n = 3). Stress CMR was well tolerated without occurrence of death or severe disabling adverse event. Patients without inducible ischemia or LGE experienced a substantially lower annual event rate of MACE (1.2%) than those with ischemia and without LGE (8.9%), or those with both ischemia and LGE (9.8%; p &amp;lt; 0.001 for all). Using Kaplan-Meier analysis, the presence of myocardial ischemia identified the occurrence of MACE (hazard ratio HR 7.56 ; 95% confidence interval CI: 4.86 – 11.80; p &amp;lt; 0.001) (Figure). In a multivariable stepwise Cox regression including clinical characteristics and CMR indexes, the presence of inducible ischemia was an independent predictor of a higher incidence of MACE (HR 5.88 ; 95% CI: 3.70 - 10.07; p &amp;lt; 0.001) and all-cause mortality (HR 2.51 ; 95% CI: 1.47 - 4.17; p &amp;lt; 0.001). CONCLUSION Stress CMR is technically feasible and has a good discriminative prognostic value to predict the occurrence of MACE and all-cause mortality in patients with AF. Abstract Figure. Kaplan-Meier curves for MACE