Univariate Cox Research Articles

One-Month Duration Compared with Twelve-Month Duration of Dual Antiplatelet Therapy in Elective Angioplasty for Coronary Artery Disease: Bleeding and Ischaemic Outcomes.

Background/Objectives: The need to determine the safest duration of dual antiplatelet therapy duration after elective angioplasty to reduce bleeding events without an adverse effect on major adverse cardiovascular events (MACE) remains a challenge. Methods: In this investigator-initiated, single-centre cohort study, we identified all patients who underwent PCI for de novo coronary disease for stable angina between January 2015 and November 2019. We compared 1-month and 12-month durations of dual antiplatelet therapy (DAPT) to determine if there was any difference in the primary outcome of major bleeding. The secondary outcome was a patient-oriented composite endpoint of all-cause mortality; any myocardial infarction, stroke, or revascularisation; and the individual components of this composite endpoint. Data were analysed using Cox regression models and cumulative hazard plots. Results: A total of 1025 patients were analysed, of which 340 received 1 month of DAPT and 685 received 12 months of DAPT. There was no difference in major bleeding between the two groups (2.6% vs. 2.5% respectively). On univariable cox regression analysis, no characteristics were predictors of major bleeding. A proportion of 99.7% of patients in the 1-month DAPT arm were treated with a DCB strategy, whilst 93% in the 12-month DAPT group were treated with a DES. There was no difference between the two groups with regards to the composite patient-oriented MACE (11% vs. 12%, respectively) or any individual component of this. These results were unchanged after propensity score matched analysis. Conclusions: A 1-month duration of DAPT, for which 99.7% of patients were treated with a DCB strategy, appears safe and effective when compared with a 12-month duration of DAPT with no difference in major bleeding or MACE.

Natural course and predictors of consciousness recovery in children with prolonged disorder of consciousness

Prolonged disorder of consciousness (DoC) is a rising challenge. Pediatric data on diagnosis and prognosis of prolonged DoC were too limited and heterogeneous, making it difficult to define the natural course and evaluate the prognosis. The present study explored the emergence from the Minimally Conscious State (eMCS) incidence at different months postinjury drawing the natural course, and detected the predictors of the incidence in children with prolonged DoC. A hospital-based prospective cohort study was conducted. Kaplan–Meier curves, as well as univariate and multivariate COX regression analysis, were performed. The study enrolled 383 pediatric DoC individuals, including 220 males (57.4%), with an average age of 3.9 (1.9–7.3) years. The median duration between onset and rehabilitation is 30.0 (21.0–46.0) days. At enrollment, the ratio of vegetative state/unresponsive wakefulness syndrome (VS/WUS) to MCS is 78.9%–21.1%. Traumatic brain injury and infection are the major etiologies (36.8% and 37.1%, respectively), followed by hypoxia cerebral injury (12.3%). For children with prolonged DoC, the cumulative incidence of eMCS at months 3, 6, 12, and 24 was 0.510, 0.652, 0.731, 0.784 VS 0.290, 0.418, 0.539, 0.603 in the traumatic VS non-traumatic subgroup, respectively. For children in a persistent vegetative state (PVS), the cumulative incidence of emergence at months in 3, 6, 12, 24, 36 and 48 was testified as 0.439, 0.591, 0.683, 0.724, 0.743 and 0.743 in the traumatic subgroup, and 0.204, 0.349, 0.469, 0.534, 0.589 and 0.620 in the non-traumatic subgroup. Participants who exhibit any of the following four demographical and/or clinical characteristics—namely, older than 4 years at onset, accepted rehabilitation within 28 days of onset, remained MCS at enrollment, or with etiology of traumatic brain injuries—had a significantly positive outcome of consciousness recovery (eMCS). Moreover, both prolongation of the central somatosensory conductive time (CCT) (level 2) and absence of N20 (level 3) independently predict a negative outcome. In children with prolonged DoC, we found that 12 months postinjury was critical to eMCS, and a preferred timepoint to define chronic vegetative state (VS). The characteristics including age, etiology, time before rehabilitation, consciousness state, and SEP results were useful predictors of conscious recovery.Trial registration Registered 06/11/2018, the registration number is chiCTR1800019330 (chictr.org.cn). Registered prospectively.

Myeloid cell differentiation-related gene signature for predicting clinical outcome, immune microenvironment, and treatment response in lung adenocarcinoma

Considering the key role of myeloid cell differentiation—related genes in the tumor microenvironment (TME), we aimed to build a prognostic risk model using these genes for Lung adenocarcinoma (LUAD). The mRNA gene expression profiles of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases were downloaded as the training and validation sets. Then, “edgeR” R package was applied to screen out the differentially expressed genes (DEGs) and univariate cox regression, backward stepwise selection analyses were performed to construct a prognostic model for LUAD. ESTIMATE, TIMER, XCELL, CIBERSORT abs, QUANTISEQ, MCPCOUNTER, EPIC, and CIBERSORT algorithms were conducted to access the association of risk levels with the stromal and immune cell infiltration levels in LUAD. Six genes (F2RL1, PRKDC, TNFSF11, INHA, PLA2G3 and TUBB1) were utilized to construct the prognostic model. The risk model showed excellent prognostic performance for LUAD in both TCGA and GEO datasets. Also, compared to the low-risk patients, the high-risk patients had higher expression of immune checkpoint molecules and showed a lower IC50 value to the chemotherapy agents. Our findings provided a myeloid cell differentiation—related gene signature that could effectively predict prognosis and guide treatment strategies for LUAD patients.

The Magnetic Resonance Imaging of the Psoas Muscle Area as the Prognostic Factor for Survival and Adverse Events in Spinal Metastasis Surgery.

Retrospective study. This study aimed to evaluate the ability of the mortality and adverse events prediction following metastatic spinal surgery of MRI-based cross-sectional psoas muscle area (PMA). A retrospective chart review, 120 patients who had undergone metastatic spinal surgery were included. The cross-sectional area identified the PMA under MR-imaging at the L3 or L4 pedicle level, which was classified into 3 tertiles. We used univariate and multivariate cox proportional hazard regression to assess whether PMA was associated with 30-day, 90-day, 1-year, and overall mortality. The small psoas tertile group populations had a higher mortality rate than the large psoas tertile group. PMA in T1 and T2 had a probability of a higher 90-d mortality rate than PMA in T3 (T1 VS T3: P = .29 and T2 VS T3: P = .12). The median survival time was 7months, 9months, and 10months in PMA T1, T2, and T3, respectively. PMA in tertile 2 had a significantly higher mortality rate of 38% compared to PMA in tertile 3 (HR 1.38, 95% CI .83-2.32, P = .02). Considering PMA as a continuous variable, every 1mm2 increment of PMA resulted in the increase survivorship of 1% (HR .99 with 95% CI .99-1). The MRI-based cross-sectional PMA tends to predict the 90-d mortality rate and overall mortality rate in spinal metastasis patients who underwent spinal surgery. The PMA should be considered one of the prognostic factors in the treatment of metastatic spinal patients.

Pan-cancer analysis of TMEM45A and exploration of its prognostic value and mechanism in gastric cancer.

Cancer is a major category of diseases that need to be addressed urgently, bringing a huge burden to the world. Gastric cancer (GC) is a frequent malignant tumor of the digestive system with the highest incidence and mortality rate among all tumors. The purpose of this study was to explore the mechanism of action of TMEM45A in pan-cancer and gastric cancer. First, GEO and TCGA database were employed to analyze the expression of TMEM45A in GC patients. Then, we determined the association between TMEM45A expression and survival of GC patients using the Kaplan-Meier Plotter database and TCGA database and verified the accuracy of TMEM45A in predicting prognosis. Next, we analyzed the effect of CTHRC expression on TIICs in GC tissues. A prognostic model was constructed using immunomodulatory genes associated with TMEM45A. The specificity and accuracy of the model were verified. TMEM45A expression was markedly higher in GC tissue than in normal tissue. GC patients with TMEM45A overexpression had a poor prognosis. The AUC value of 5-year survival on the ROC curve was 0.705, indicating that TMEM45A is a reliable prognostic factor and can be used as a clinicopathological indicator alone to predict patient prognosis. Three high-risk immunomodulatory genes (CXCR4 and TGFB1) and one low-risk immunomodulatory gene (PDCD1) were obtained using both univariate and multivariate COX methods. These three immunomodulatory molecules were used to construct prognostic models. GC patients with TMEM45A overexpression have a poor prognosis and are associated with immune cell infiltration. Hence, TMEM45A is a fairly reliable independent prognostic marker.

Methylation and transcriptome analyses construct a prognostic model and reveal the suppressor role of VMO1 in lung adenocarcinoma

BackgroundDNA methylation is an important epigenetic mechanism of gene regulation. The aberrant DNA methylation has been found to play an important role in the initiation and progression of tumors. ResultsTranscriptome and DNA methylation data of lung adenocarcinoma (LUAD) patients were co-analyzed and 95 methylation-driven genes (MDGs) was found in relation to LUAD. A prognostic model based on 3 MDGs (GMNN, SPINK2 and VMO1) was constructed by Univariate and Multivariate cox regression analyses. The risk score generated from the prognostic model could be used to classify LUAD patients into high and low risk groups. Furthermore, it was found that the risk score was associated with tumor microenvironment (TME) and clinical characteristics (survival status and T stage) of patients. Interestingly, we identified and validated that the patients in the low-risk group responded better to immunotherapy treatment. Then, a nomogram model based on the risk score and clinical characteristics was established which showed significant prediction value. The down-regulation and hypermethylation levels of vitelline membrane outer layer protein 1 homolog (VMO1) were verified in paired LUAD tumor and non-tumor tissues by pyrosequencing assay and RT-qPCR. Furthermore, MTT, migration and wound healing assays were performed with lentivector-mediated ectopic over-expression and 5-Aza-dC demethylation followed by siRNA rescue experiments to investigate the role of VMO1 in LUAD cells. Our results indicated that VMO1 could inhibit proliferation and migration of A549 and NCI-H1299 cells. ConclusionsIn summary, our experiments constructed a prognostic model with high capacity for risk prediction in LUAD patients. VMO1 had a malignant suppressor role in LUAD cells. The correlation between risk score and TME might elucidate a potential mechanism of oncogenesis and provide an avenue for further therapeutic targets.

Cobalt Serum Level as a Biomarker of Cause-Specific Survival among Prostate Cancer Patients.

Prostate cancer is the most common cancer diagnosed in men and the second leading cause of death in male cancer patients. The WHO suggests that cobalt is involved in the carcinogenesis of prostate cancer. There are, however, no studies associating cobalt levels and prostate cancer patient survival. In this study, 261 Polish prostate cancer (n = 261) patients were recruited into a prospective cohort between 2009 and 2015. Serum cobalt levels were measured using ICP-MS after prostate cancer diagnosis and before treatment. All study participants were assigned into quartiles (QI-QIV) based on the distribution of serum cobalt levels among censored patients. Univariable and multivariable COX regression models were used to calculate hazard ratios (HRs) for each serum cobalt level quartile. We found a significant relationship between high serum cobalt levels and poor prostate cancer patient total survival (HR = 2.60; 95% CI: 1.17-5.82; p = 0.02). In relation to prostate cancer patients who died as a result of other non-cancer causes, the association with high levels of cobalt was even stronger (HR = 3.67; 95% CI: 1.03-13.00; p = 0.04). The impact of high serum cobalt levels on overall survival of prostate cancer-specific-related deaths was not statistically significant.

Preoperative blood-based nutritional biomarkers as significant prognostic factors after intravesical BCG therapy in patients with non-muscle-invasive bladder cancer.

The aim of this study was to investigate the prognostic role of blood-based nutritional biomarkers, including red blood cell (RBC count), hemoglobin (Hb), total protein (TP), albumin, the serum albumin to globulin ratio (AGR) and the prognostic nutritional index (PNI) in patients who underwent intravesical treatment for non-muscle invasive bladder cancer (NMIBC). A total of 501 NMIBC patients who received intravesical Bacillus Calmette-Guerin (BCG) treatment following transurethral resection of bladder tumor (TURBT) were included. The optimal cutoff values for these nutrition-based indicators were determined using receiver operating characteristic curve analysis. We observed a significantly higher recurrence-free survival (RFS) rate in patients with elevated levels of RBC count, Hb, TP, and albumin. Cox univariate and multivariate Cox regression analyses demonstrated that serum albumin (P = 0.002, HR = 0.51, 95%CI: 0.33-0.78), RBC count (P = 0.002, HR = 0.50, 95%CI: 0.32-0.77), TP (P = 0.028, HR = 0.62, 95%CI: 0.41-0.95), Hb (P = 0.004, HR = 0.53, 95%CI: 0.33-0.84), AGR (P = 0.003, HR = 0.46, 95%CI: 0.27-0.76) and PNI (P = 0.019, HR = 0.56, 95%CI: 0.35-0.91) were significant independent factors predicting RFS. These cost-effective and convenient blood-based nutritional biomarkers have the potential to serve as valuable prognostic indicators for predicting recurrence in NMIBC patients undergoing BCG-immunotherapy.

Elderly men are underscreened for primary aldosteronism even in Hypertension Excellence Centre

Purpose The Endocrine Society (ES) guidelines recommend screening for primary aldosteronism (PA) in high risk hypertensive patients presenting with at least one of seven criteria (resistant HTN, hypokalaemia, adrenal nodule, etc.) Although guidelines are clear and screening is simple, compliance rates among clinicians are extremely low. This results in underdiagnosis of early disease, leading to cadiovasculaer complications and the extra-burden of advanced chronic kidney disease. We aimed to evaluate the screening rates in our Nephrology and Hypertension clinics, as an example of a dedicated Hypertension Excellence Centre. Materials and methods Data on adult hypertensive patients was retrieved from January 2018 to December 2020. Included in the study were hypertensive patients who had at least one of the ES criteria for PA screening. Of all suitable patients, we compared those who were screened for PA to patients who were not screened. Univariate and multivariate cox regression analyses were used for comparison between groups. Results Of 661 patients with HTN, 218 patients (33%) met the ES guidelines for PA screening. Forty-six of them (21.1%) were referred for screening. Advanced age and male gender were associated with lower screening referral rates. Odds ratio for age was 0.945 for every year (95% CI 0.915 − 0.975). There was a trend towards decreased referral rate in advanced kidney disease. Conclusions A 21% screening rate, suggests that many cases of PA are likely missed, more often in older patients. We therefore advocate for PA screening of all hypertensive patients, especially elderly patients with CKD, in whom clinicians’ awareness is low but the absolute risk is high.

Screening of genes related to programmed cell death in esophageal squamous cell carcinoma and construction of prognostic model based on transcriptome analysis

ABSTRACT Objectives To screen programmed cell death (PCD)-related genes in esophageal squamous cell carcinoma (ESCC) based on transcriptomic data and to explore its clinical value. Methods Differentially expressed PCD genes (DEPCDGs) were screened from ESCC transcriptome and clinical data in TCGA database. Univariate COX and LASSO COX were performed on prognostically DEPCDGs in ESCC to develop prognostic model. Differences in immune cell infiltration in different RiskScore groups were determined by ssGSEA and CIBERSORT. The role of RiskScore in immunotherapy response was explored using Tumor Immune Dysfunction and Exclusion (TIDE) and IMvigor210 cohorts. Results Fourteen DEPCDGs associated with prognosis were tapped in ESCC. These DEPCDGs form a RiskScore with good predictive performance for prognosis. RiskScore demonstrated excellent prediction accuracy in three data sets. The abundance of M2 macrophages and Tregs was higher in the high RiskScore group, and the abundance of M1 macrophages was higher in the low RiskScore group. The RiskScore also showed good immunotherapy sensitivity. RT-qPCR analysis showed that AUP1, BCAP31, DYRK2, TAF9 and UBQLN2 were higher expression in KYSE-150 cells. Knockdown BCAP31 inhibited migration and invasion. Conclusion A prognostic risk model can predict prognosis of ESCC and may be a useful biomarker for risk stratification and immunotherapy assessment.

Prognostic analysis of anoikis-related genes in bladder cancer: An observational study.

Anoikis is proved to play a crucial role in the development of cancers. However, the impact of anoikis on the prognosis of bladder cancer (BLCA) is currently unknown. Thus, this study aimed to find potential effect of anoikis in BLCA. The Cancer Genome Atlas (TCGA)-BLCA and GSE13507 cohorts were downloaded from TCGA and the Gene Expression Omnibus (GEO) databases, respectively. Differentially expressed genes (DEGs) were screened between BLCA and normal groups, which intersected with anoikis-related genes to yield anoikis-related DEGs (AR DEGs). Univariate COX, rbsurv, and multivariate COX analyses were adopted in order to build a prognostic risk model. The differences of risk score in the different clinical subgroups and the relevance between survival rate and clinical characteristics were explored as well. Finally, chemotherapy drug sensitivity in different risk groups was analyzed. In total, 78 AR DEGs were acquired and a prognostic signature was build based on the 6 characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1), where the patients of low-risk group had longer survival time. The survival rate of BLCA patients was significantly differential in different groups of age, stage, smoking history, pathologic-T, and pathologic-N. The IC50 of 56 drugs showed significant differences between 2 risk groups, such as imatinib, docetaxel, and dasatinib. At last, the results of real time quantitative-polymerase chain reaction (RT-qPCR) demonstrated that the expression trend of CALR, HGF, and INHBB was consistent with the result obtained previously based on public databases. Taken together, this study identified 6 anoikis-related characteristic genes (CALR, FASN, CSPG4, HGF, INHBB, SATB1) for the prognosis of BLCA patients, providing a scientific reference for further research on BLCA.

Prognostic significance of negative lymph node count in microsatellite instability-high colorectal cancer

BackgroundMicrosatellite instability-high (MSI-H) tumors, with elevated tumor mutational burden and expression of neoantigens, represent a distinct immune-activated subpopulation in colorectal cancer (CRC), characterized by strong lymph node reaction, locally advanced tumor and higher total lymph nodes harvested (TLN), but less metastatic lymph nodes and fewer incidence of III-IV stage. Host immune response to tumor and lymph nodes may be an important prognostic factor. However, N stage and LNR (Lymph-Node Ratio) have limitations in predicting the prognosis of MSI-H patients. Negative lymph node count (NLC) provided a more precise representation of immune activation status and extent of tumor metastasis. The study aims to detect prognostic significance of NLC in MSI-H CRC patients, and compare it with N stage, TLN and LNR.MethodsRetrospective data of 190 consecutive MSI-H CRC patients who received curative resection were collected. Survival analyses were performed using the Kaplan–Meier method. Clinicopathological variables including NLC, N stage, TLN and LNR were studied in univariate and multivariate COX regression analyses. ROC (receiver operating characteristic curve) and concordance index were employed to compare the differences in predictive efficacy between NLC, N stage, TLN and LNR.ResultsPatients with increased NLC experienced a significantly improved 5-years DFS and OS in Kaplan–Meier analysis, univariate analysis, and multivariate analysis, independent of potential confounders examined. Increased NLC corresponded to elevated 5-years DFS rate and 5-years OS rate. AUC (area under curve) and concordance index of NLC in DFS and OS predicting were both significantly higher than N stage, TLN and LNR.ConclusionsNegative lymph node is an important independent prognostic factor for MSI-H patients. Reduced NLC is associated with tumor recurrence and poor survival, which is a stronger prognostic factor than N stage, TLN and LNR.

The prognostic role of an optimal machine learning model based on clinical available indicators in HCC patients.

Although methods in diagnosis and therapy of hepatocellular carcinoma (HCC) have made significant progress in the past decades, the overall survival (OS) of liver cancer is still disappointing. Machine learning models have several advantages over traditional cox models in prognostic prediction. This study aimed at designing an optimal panel and constructing an optimal machine learning model in predicting prognosis for HCC. A total of 941 HCC patients with completed survival data and preoperative clinical chemistry and immunology indicators from two medical centers were included. The OCC panel was designed by univariate and multivariate cox regression analysis. Subsequently, cox model and machine-learning models were established and assessed for predicting OS and PFS in discovery cohort and internal validation cohort. The best OCC model was validated in the external validation cohort and analyzed in different subgroups. In discovery, internal and external validation cohort, C-indexes of our optimal OCC model were 0.871 (95% CI, 0.863-0.878), 0.692 (95% CI, 0.667-0.717) and 0.648 (95% CI, 0.630-0.667), respectively; the 2-year AUCs of OCC model were 0.939 (95% CI, 0.920-0.959), 0.738 (95% CI, 0.667-0.809) and 0.725 (95% CI, 0.643-0.808), respectively. For subgroup analysis of HCC patients with HBV, aged less than 65, cirrhosis or resection as first therapy, C-indexes of our optimal OCC model were 0.772 (95% CI, 0.752-0.792), 0.769 (95% CI, 0.750-0.789), 0.855 (95% CI, 0.846-0.864) and 0.760 (95% CI, 0.741-0.778), respectively. In general, the optimal OCC model based on RSF algorithm shows prognostic guidance value in HCC patients undergoing individualized treatment.

Development of a Cancer-associated Fibroblast Signature for Evaluating Immunotherapy Response and Prognosis of Hepatocellular Carcinoma.

Alcohol abuse, non-alcoholic fatty liver disease (NAFLD), and hepatitis B and C are the main pathogenic factors of hepatocellular carcinoma (HCC). Though the current understanding of risk factors for HCC has been improved, patients with this type of cancer are normally diagnosed at advanced stages, posing significant challenges to effective treatment. This study analyzed the HCC datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database (GSE14520 and GSE116174). Stromal and immune cell infiltration in the tumor microenvironment (TME) was quantified by the ESTIMATE algorithm. To identify gene modules associated with cancer-associated fibroblasts (CAFs), weighted gene co-expression network analysis (WGCNA) was performed to develop gene co-expression networks. A CAF prognosis score (CAFPS) model was established based on the prognostic CAF genes screened by univariate and multivariate Cox regression analyses. To determine the role of the genes in the vital module in HCC, we conducted Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Finally, the relationship between CAFPS and drug sensitivity was analyzed using Genomic Data for Cancer Drug Sensitivity (GDSC). In this study, we found significant differences in immune scores, stromal scores, CAFs scores, and CD4/8 T-cell scores between normal samples and samples with different TNM staging. In particular, the proportion of CAFs was higher than all other cells in normal samples. Gene modules related to CAFs were identified by developing a gene co-expression network using WGCNA analysis. The lightyellow and greenyellow modules showed the highest correlation with CAF scores. Univariate COX analysis identified 12 genes related to HCC prognosis from a total of 191 genes in the two modules. The Kaplan-Meier (KM) survival analysis revealed that a high expression of these genes was associated with a lower survival chance. Based on the 12 genes obtained by univariate COX analysis, multivariate COX analysis was performed to construct a risk score model for the characteristics of CAFs (CAFPS). The KM survival curves of patients in the high CAFPS and low CAFPS groups showed that patients in the low CAFPS group had better survival. CAFs played a crucial role in the pathogenesis and treatment response of HCC. Targeting the CAFs milieu may provide therapeutic benefits, highlighting the importance of CAFS in developing a personalized treatment for HCC patients. Further studies are required to verify the current findings and explore their implications in clinical settings.

A novel LGALS1-depended and immune-associated fatty acid metabolism risk model in acute myeloid leukemia stem cells

Leukemia stem cells (LSCs) are recognized as the root cause of leukemia initiation, relapse, and drug resistance. Lipid species are highly abundant and essential component of human cells, which often changed in tumor microenvironment. LSCs remodel lipid metabolism to sustain the stemness. However, there is no useful lipid related biomarker has been approved for clinical practice in AML prediction and treatment. Here, we constructed and verified fatty acid metabolism-related risk score (LFMRS) model based on TCGA database via a series of bioinformatics analysis, univariate COX regression analysis, and multivariate COX regression analysis, and found that the LFMRS model could be an independent risk factor and predict the survival time of AML patients combined with age. Moreover, we revealed that Galectin-1 (LGALS1, the key gene of LFMRS) was highly expressed in LSCs and associated with poor prognosis of AML patients, and LGALS1 repression inhibited AML cell and LSC proliferation, enhanced cell apoptosis, and decreased lipid accumulation in vitro. LGALS1 repression curbed AML progression, lipid accumulation, and CD8+ T and NK cell counts in vivo. Our study sheds light on the roles of LFMRS (especially LGALS1) model in AML, and provides information that may help clinicians improve patient prognosis and develop personalized treatment regimens for AML.

A five-gene prognosis model based on lysine β-hydroxybutyrylation site genes to predict the survival and therapy response in pancreatic adenocarcinoma

BackgroundPancreatic adenocarcinoma (PAAD) is one of the most malignancy diseases. Lysine β-hydroxybutyrylation (Kbhb) has been reported to involve various metabolism and cancer progression. MethodsData from online databases (TCGA and GEO) were retrieved for the selection of differential expressed Kbhb site genes (DTRGs). Univariate cox and LASSO analysis were performed to identify the prognostic DTRGs. Based on the optimal DTRGs, a prognostic risk score model was established. Kaplan-Meier and Receiver operator characteristic analysis were conducted to evaluate the predicting ability of the prognosis model. Generated with clinical data, independent analysis and nomogram model were performed. Finally, the differences of survival, immune cell levels, immunotherapy response, drug sensitivity between high- and low-risk groups were explored. ResultsA total of 63 DTRGs were identified in PAAD, and these genes were related to cell division and apoptosis biological functions. Through univariate cox regression and LASSO analysis, 30 DTRGs were selected to be related to prognosis and five (KRT18, ANLN, ECT2, RBM5, and RBM6) were identified as the optimal DTRGs in PAAD. Based on the five optimal DTRGs, a prognostic risk score model was constructed, with promising predictive ability in PAAD survival (AUC >0.70). High-risk group showed lower survival rate (P < 0.05). Moreover, based on the risk score, a nomogram model was also established, which possessed perfect stability. Finally, lower risk score was related to higher immune cell levels, indicating an immune activation in low-risk status, which maybe the reason for the better survival in low-risk group. Furthermore, the immunotherapy response and drug sensitivity were all higher than that in low-risk groups (P < 0.05). ConclusionA five-gene prognosis risk model which exhibit promising predictive ability in survival is constructed for patients with PAAD.

Effect of Preoperative Serum Lactate Dehydrogenase-to-Albumin Ratio on the Survival of Oral Cancer: A Retrospective Study.

Several studies have investigated the relationship between serum lactate dehydrogenase-to-albumin ratio (LAR) and the prognosis of cancers. However, no studies have explored the association between serum LAR and the survival of oral cancer (OC). This study was aimed to determine the association of serum LAR with the overall survival (OS) of OC. One hundred and ninety patients with OC were included in this study between January 2018 and December 2019. Log rank test and Kaplan-Meier method were used to compare the survival rate of OC between the low LAR group and the high LAR group. The association between serum LAR and the survival of OC patients was determined via univariate and multivariate Cox regression analyses. Kaplan-Meier analysis and Log rank test indicated that the OS rate in low LAR group was significantly higher than that in high LAR group (P < 0.05). Univariate cox analysis showed that TNM III-IV stage, serum LDH > 162 U/L, and serum LAR > 3.79 were significantly associated with the OS of OC patients. Multivariate Cox analysis suggested that the TNM III-IV stage (HR, 2.317; 95% CI, 1.423-3.774, P = 0.001) and serum LAR > 3.79 (HR, 5.138; 95% CI, 2.245-11.756, P = 0.000) were independently related with poor OS of OC patients. High serum LAR (>3.79) is an independent predictor of adverse prognosis in OC patients. LAR could be used as a promising marker for predicting the OS of OC patients.

Poster 314: Early Full Knee Extension Predicts Successful Return to Sport Following Anterior Cruciate Ligament Reconstruction

Objectives: To identify predictive factors for successful return to sport (RTS) following anterior cruciate ligament reconstruction (ACL-R) with quadriceps tendon (QT) autograft. Methods: Data was retrospectively collected on consecutive patients who underwent ACL-R with QT autograft at a single institution between 2010-2020. Patient demographics, knee range of motion (ROM), injury characteristics, and intraoperative data were collected from the electronic medical record. Full RTS was defined as the patient returning to their prior level of sport and the presence of a clinical documentation of no further complications. Univariate and multivariate cox regression were utilized to conduct time-to-event analyses to identify predictors of early RTS clearance by surgeon. Additionally, both logistic regression analysis and generalized estimating equations were used to identify significant predictors of successful full RTS. STATA 16SE software was utilized for all analyses with statistical significance set to p &lt; 0.05. Results: A total of 307 patients were included, consisting of 176 males (57.3%) and 131 females (42.7%), with an average of 20.7 ± 7.1 years of age and 14.5 ± 8.9 months follow-up. Ten patients (3.3%) were professional/semi-professional athletes, 38 (12.4%) were collegiate athletes, 144 (46.9%) were high school athletes (46.9%), and 115 (37.5%) were recreational athletes. Complete knee extension was achieved by 64.1% of patients at 6 weeks postoperatively, by 77.7% at 3 months, by 84.4% at 6 months, and by 84.7% at 1 year. Full knee extension at 3 (HR: 1.55, 95% CI: 1.13–2.12, p = 0.007) and 6 months (HR: 1.49, 95% CI: 1.05–2.12, p = 0.025) postoperatively were predictors of a higher rate of RTS clearance. Moreover, patients who achieved full knee extension at 3 months follow-up had a greater rate of RTS (1.02/person-years) compared to patients who did not achieve full knee extension at 3 months (0.83 per person-years). When considering RTS, only full knee extension at 4-6 weeks (OR:2.02, 95% CI:1.02–4.03, p = 0.045) and at 3 months (OR:2.36, 95% CI: 1.12–4.99, p = 0.024) postoperatively were predictive of successful RTS. No other significant predictors were identified. Conclusions: Restoration of full knee extension was strongly associated with higher rates of both surgeon clearance and successful RTS. The role of full knee extension in the ability to regain strength at 6 months, as measured by limb symmetry indices, after ACL-R has been previously described. While both ROM and strength play crucial roles in the rehabilitation process, achieving full ROM typically precedes restoration of full strength. Lack of full extension 3 months postoperatively may require further investigation and serves as a possible opportunity for a goal metric to maximize RTS rates and minimize complications after ACL-R.

The conditional recurrence-free survival after R0 hepatectomy for locally advanced intrahepatic cholangiocarcinoma: A competing risk analysis based on inflammation-nutritional status

BackgroundConditional survival analysis can serve as a dynamic prognostic metric, which helps to estimate the real-time survival probability over time. The present study conducted a conditional recurrence-free survival (CRFS) analysis for locally advanced intrahepatic cholangiocarcinoma (ICC) after R0 hepatectomy from an inflammatory-nutritional perspective using the competing risk method. MethodsWe extracted the medical data of 164 locally advanced ICC patients after R0 resection from Sun Yat-sen University Cancer Center. The calculation formula of the CRFS rate is CRFS(y/x) = RFS(y + x)/RFS(x). Univariable and multivariable COX regression analysis and competing risk analysis were conducted to identify RFS indicators. ResultsConsidering death before recurrence as a competing risk factor, the conditional RFS rates every 6 months gradually increased over time. The 24-month RFS rate increased from 29.2 % to 49.9 %, 68.5 %, and 85.1 % given 6, 12, and 18-month already recurrence-free survival, respectively. Both in multivariate COX regression analysis and competing risk analysis, tumor diameter and number, lymph node metastasis, aggregate systemic inflammation index score (AISI), and albumin-bilirubin score (ALBI) all remained significant. For both AISI and ALBI variables, the CRFS rates in the low-value set were higher than those of the high-value set. ConclusionsConditional RFS rates of locally advanced ICC after R0 hepatectomy dynamically increased over time, which contributed to reducing survivors' psychological distress and facilitating personalized follow-up schedules. In addition, a person's inflammatory and nutritional status significantly impact the recurrence risk. Oncologists should consider the role of inflammation-nutritional status when making decisions for patients with locally advanced ICC.

The Association of Blood Pressure Defined by the 2017 ACC/AHA Guidelines and Cardiovascular Disease Risk for Middle-Aged and Elderly People in China: A Cohort Study.

Cardiovascular disease (CVD) is a series of diseases affecting the heart or blood vessels. To assess the relationship between blood pressure (BP) levels defined by the 2017 American College of Cardiology/American Heart Association (ACC/AHA) guideline and CVD/atherosclerotic cardiovascular disease (ASCVD) risk for middle-aged and elderly people in China. A total of 6,644 middle-aged and elderly people from the China Health and Retirement Longitudinal Study (CHARLS) were finally included. According to the 2017 ACC/AHA guideline, all subjects were divided into four groups: normal BP, elevated BP, stage 1 hypertension, and stage 2 hypertension. The outcome of this study was considered as the risk of CVD and ASCVD. Univariate and multivariate COX regression models were adopted to examine the relationship of the 2017 ACC/AHA BP classification with the risk of CVD. Univariate and multivariate logistic regression models were used to investigate the association between BP levels and ASCVD risk. Subgroup analyses based on age, gender, and use of antihypertensive drugs were performed. P<0.05 was accepted as statistically significant. After adjusting all covariates, compared to middle-aged and elderly patients with normal BP, we found that patients with stage 1/2 hypertension were associated with a higher risk of CVD, separately. Simultaneously, we also observed a positive association between individuals with elevated BP, stage 1 hypertension, stage 2 hypertension, and higher ASCVD risk in the fully adjusted model. The result of subgroup analyses implied that the relationship between stage 1/2 hypertension and CVD/ high ASCVD was robust in different ages and genders, and participants without using antihypertensive drugs. BP classification under the 2017 ACC/AHA BP guidelines may apply to the Chinese population.