The advanced lung cancer inflammation index (ALI) predicted the postoperative survival rate of patients with non-small cell lung cancer and the construction of a nomogram model.

OBJECTIVE: To investigate the prognostic significance of the advanced lung cancer inflammation index (ALI) in patients with operable non-small-cell lung carcinoma (NSCLC). By constructing the nomogram model, it can provide a reference for clinical work. METHODS: A total of 899 patients with non-small cell lung cancer who underwent surgery in our hospital between January 2017 and June 2021 were retrospectively included. ALI was calculated by body mass index (BMI) × serum albumin/neutrophil to lymphocyte ratio (NLR). The optimal truncation value of ALI was obtained using the receiver operating characteristic (ROC) curve and divided into two groups. Survival analysis was represented by the Kaplan-Meier curve. The predictors of Overall survival (OS) were evaluated by the Cox proportional risk model using single factor and stepwise regression multifactor analysis. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling 1 000 times) was used for internal verification of the nomogram model. The concordance index (C-index) was used to represent the prediction performance of the nomogram model, and the calibration graph method was used to visually represent its prediction conformity. The application value of the model was evaluated by decision curve analysis (DCA). RESULTS: The optimal cut-off value of ALI was 70.06, and the low ALI group (ALI < 70.06) showed a poor survival prognosis. In multivariate analyses, tumor location, pathological stage, neuroaggression, and ALI were independently associated with operable NSCLC-specific survival. The C index of OS predicted by the nomogram model was 0.928 (95% CI: 0.904-0.952). The bootstrap self-sampling method (B = 1000) was used for internal validation of the prediction model, and the calibration curve showed good agreement between the prediction and observation results of 1-year, 2-year, and 3-year OS. The ROC curves for 1-year, 2-year, and 3-year survival were plotted according to independent factors, and the AUC was 0.952 (95% CI: 0.925-0.979), 0.951 (95% CI: 0.916-0.985), and 0.939 (95% CI: 0.913-0.965), respectively. DCA shows that this model has good clinical application value. CONCLUSION: ALI can be used as a reliable indicator to evaluate the prognosis of patients with operable NSCLC, and through the construction of a nomogram model, it can facilitate better individualized treatment and prognosis assessment.

Fibrinogen-to-albumin ratio (FAR) is the best biomarker for the overall survival of patients with non-small-cell lung cancer.

Objective: The inflammatory response and the nutritional status are associated with overall survival (OS) in patients with non-small cell lung cancer (NSCLC), but it is unclear which biomarkers are better suited to predict prognosis. This study sought to determine which of the commonly existing inflammatory and nutritional indicators best predicted the OS. Methods: This study included 15 compound indicators based on inflammation or nutrition, with cutoff points obtained through the receiver operating characteristic (ROC) curve. Univariate and multivariate Cox proportional risk models were used to evaluate the relationship between these predictors and OS. Kaplan-Meier curves were used for survival analysis, and log-rank tests were used to compare differences between groups. The C-index was calculated to evaluate the predictive ability of the different indicators. Results: The study included 899 patients with NSCLC. In the univariate analysis, all 15 measures were significantly associated with the OS of patients (all p < 0.05). The results of the C-index analysis showed that the fibrinogen-to-albumin ratio (FAR), the systemic immune-inflammation index (SII), and the albumin-to-alkaline phosphatase ratio (AAPR) were the three indices with the best predictive performance. Among them, FAR (C-index = 0.639) had the best predictive power for OS in patients with NSCLC. In the different subgroups, FAR had the highest C-index in male, non-smoking, adenocarcinoma, and stage II patients. The C-index of the platelet-to-lymphocyte ratio (PLR) in female patients was the highest. SII was the highest in smokers, in those aged <65 and ≥65 years, and in stage III patients. The C-index of AAPR was the highest in non-adenocarcinomas. The C-index of the pan-immune-inflammation value (PIV) was the highest in stage I patients. In the multivariate Cox regression analysis, among FAR, SII, and AAPR, only FAR was an independent predictor of OS in patients with NSCLC. A high FAR was associated with a higher risk of death in patients with NSCLC (HR = 1.601, 95% CI = 1.028-2.495). In order to further evaluate the potential prognostic value of FAR, SII, and AAPR in patients with different stages, Cox regression analysis was performed for those with stage I-II and stage III NSCLC. The results showed that FAR was an independent prognostic factor for OS in patients with stage I-II NSCLC. Conclusion: For all patients with NSCLC, the prognostic power of FAR was superior to that of other inflammatory and nutritional indicators.

Prognostic factors and predictive model construction in patients with non-small cell lung cancer: a retrospective study.

Objective: The purpose of this study was to construct a nomogram model based on the general characteristics, histological features, pathological and immunohistochemical results, and inflammatory and nutritional indicators of patients so as to effectively predict the overall survival (OS) and progression-free survival (PFS) of patients with non-small cell lung cancer (NSCLC) after surgery. Methods: Patients with NSCLC who received surgical treatment in our hospital from January 2017 to June 2021 were selected as the study subjects. The predictors of OS and PFS were evaluated by univariate and multivariable Cox regression analysis using the Cox proportional risk model. Based on the results of multi-factor Cox proportional risk regression analysis, a nomogram model was established using the R survival package. The bootstrap method (repeated sampling for 1 000 times) was used to internally verify the nomogram model, and C-index was used to represent the prediction performance of the nomogram model. The calibration graph method was used to visually represent its prediction compliance, and decision curve analysis (DCA) was used to evaluate the application value of the model. Results: Univariate and multivariate analyses were used to identify independent prognostic factors and to construct a nomogram of postoperative survival and disease progression in operable NSCLC patients, with C-index values of 0.927 (907-0.947) and 0.944 (0.922-0.966), respectively. The results showed that the model had high predictive performance. Calibration curves for 1-year, 2-year, and 3-year OS and PFS show a high degree of agreement between the predicted probability and the actual observed probability. In addition, the results of the DCA curve show that the model has good clinical application value. Conclusion: We established a predictive model of survival prognosis and disease progression in patients with non-small cell lung cancer after surgery, which has good predictive performance and can guide clinicians to make the best clinical decision.

The Construction of a Nomogram Using the Pan-Immune-Inflammation Value Combined with a PILE Score for Immunotherapy Prediction Prognosis in Advanced NSCLC.

Purpose: The purpose of this study was to investigate the predictive value of Pan-Immune-Inflammation Value (PIV) combined with the PILE score for immunotherapy in patients with advanced non-small cell lung cancer (NSCLC) and to construct a nomogram prediction model to provide reference for clinical work. Patients and Methods: Patients with advanced NSCLC who received ICIs treatment in Qingdao Municipal Hospital from January 2019 to December 2021 were selected as the study subjects. The chi-square test, Kaplan-Meier survival analysis, and Cox proportional risk regression analysis were used to evaluate the prognosis. The results were visualized by a nomogram, and the performance of the model was judged by indicators such as the area under the subject operating characteristic curve (AUC) and C-index. The patients were divided into high- and low-risk groups by PILE score, and the prognosis of patients in different risk groups was evaluated. Results: Multivariate Cox regression analysis showed that immune-related adverse events (irAEs) were prognostic factors for overall survival (OS) improvement, and ECOG PS score ≥2, bone metastases before treatment, and high PIV expression were independent risk factors for OS. The C index of OS predicted by the nomogram model is 0.750 (95% CI: 0.677-0.823), and the Calibration and ROC curves show that the model has good prediction performance. Compared with the low-risk group, patients in the high-risk group of PILE were associated with a higher inflammatory state and poorer physical condition, which often resulted in a poorer prognosis. Conclusion: PIV can be used as a prognostic indicator for patients with advanced NSCLC treated with ICIs, and a nomogram prediction model can be constructed to evaluate the survival prediction of patients, thus contributing to better clinical decision-making and prognosis assessment.

Risk factor analysis and nomogram prediction model construction of postoperative complications of thoracoscopic non-small cell lung cancer.

Background: A series of complications will inevitably occur after thoracoscopic pulmonary resection. How to avoid or reduce postoperative complications is an important research area in the perioperative treatment of thoracic surgery. This study analyzed the risk factors for thoracoscopic postoperative complications of non-small cell lung cancer (NSCLC) and established a nomogram prediction model in order to provide help for clinical decision-making. Methods: Patients with NSCLC who underwent thoracoscopic surgery from January 2017 to December 2021 were selected as study subjects. The relationship between patient characteristics, surgical factors, and postoperative complications was collected and analyzed. Based on the results of the statistical regression analysis, a nomogram model was constructed, and the predictive performance of the nomogram model was evaluated. Results: A total of 872 patients who met the study criteria were included in the study. A total of 171 patients had complications after thoracoscopic surgery, accounting for 19.6% of the study population. Logistic regression analysis showed that thoracic adhesion, history of respiratory disease, and lymphocyte-monocyte ratio (LMR) were independent risk factors for complications after thoracoscopic surgery (P<0.05). Variables with P<0.1 in logistic regression analysis were included in the nomogram model. The verification results showed that the area under curve (AUC) of the model was 0.734 [95% confidence interval (CI): 0.693-0.775], and the calibration curve showed that the model had good differentiation. The decision curve analysis (DCA) curve showed that this model has good clinical application value. In subgroup analysis of complications, gender, history of respiratory disease, body mass index (BMI), type of surgical procedure, thoracic adhesion, and Time of operation were identified as significant risk factors for prolonged air leak (PAL) after surgery. Tumor location and forced expiratory volume in the first second (FEV1) were identified as important risk factors for postoperative pulmonary infection. N stage and thoracic adhesion were identified as significant risk factors for postoperative pleural effusion. The AUC for PAL was 0.823 (95% CI: 0.768-0.879). The AUC of postoperative pulmonary infection was 0.714 (95% CI: 0.627-0.801). The AUC of postoperative pleural effusion was 0.757 (95% CI: 0.650-0.864). The calibration curve and DCA curve indicated that the model had good predictive performance and clinical application value. Conclusions: This study analyzed the risk factors affecting the postoperative complications of NSCLC through thoracoscopic surgery, and the nomogram model built based on the influencing factors has certain significance for the identification and reduction of postoperative complications.

Association between immune-related adverse events and prognosis in patients with advanced non-small cell lung cancer: a systematic review and meta-analysis.

Background: The emergence of immune checkpoint inhibitors (ICIs) provides a variety of options for patients with advanced non-small-cell lung cancer (NSCLC). After the application of ICIs, the immune system of patients was highly activated, and immune-related adverse events (irAEs) could occur in some organ systems, and irAEs seemed to be associated with the survival prognosis of patients. Therefore, we evaluated the association between survival outcomes and irAEs in NSCLC patients and conducted a systematic review and meta-analysis. Methods: We conducted systematic reviews of PubMed, Embase, Cochrane, and Web of Science databases until December 2021. The forest map was constructed by combining the hazard ratio (HR) and 95% confidence interval (CI). I2 estimated the heterogeneity between studies. A meta-analysis was performed using R 4.2.1 software. Results: Eighteen studies included 4808 patients with advanced NSCLC. In pooled analysis, the occurrence of irAEs was found to be a favorable factor for improved prognosis (PFS: HR: 0.48, 95% CI: 0.41-0.55, P <0.01; OS: HR: 0.46, 95% CI: 0.42-0.52, P <0.01). In subgroup analyses, cutaneous irAE, gastrointestinal irAE, endocrine irAE and grade ≥3 irAEs were associated with improvements in PFS and OS, but pulmonary and hepatic irAEs were not. Conclusion: Existing evidence suggests that the occurrence of irAEs may be a prognostic biomarker for advanced NSCLC. However, further research is needed to explore the prospect of irAEs as a prognostic biomarker in patients undergoing immunotherapy. Systematic review registration: https://www.crd.york.ac.uk/PROSPEROFILES/405333_STRATEGY_20240502.pdf, identifier CRD42023405333.

Rapid weather changes are associated with daily hospital visitors for atrial fibrillation accompanied by abnormal ECG repolarization: a case-crossover study.

BACKGROUND: Atrial fibrillation (AF) is highly prevalent in the population, yet the factors contributing to AF events in susceptible individuals remain partially understood. The potential relationship between meteorological factors and AF, particularly with abnormal electrocardiograph (ECG) repolarization, has not been adequately studied. This case-crossover study aims to investigate the association between meteorological factors and daily hospital visits for AF with abnormal ECG repolarization in Shanghai, China. METHODS: The study cohort comprised 10,325 patients with ECG-confirmed AF who sought treatment at Shanghai Sixth People's Hospital between 2015 and 2018. Meteorological and air pollutant concentration data were matched with the patient records. Using a case-crossover design, we analyzed the association between meteorological factors and the daily count of hospital visitors for AF with abnormal ECG repolarization at our AF center. Lag analysis models were applied to examine the temporal relationship between meteorological factors and AF events. RESULTS: The analysis revealed statistically significant associations between AF occurrence and specific meteorological factors. AF events were significantly associated with average atmospheric pressure (lag 0 day, OR 0.9901, 95% CI 0.9825-0.9977, P < 0.05), average temperature (lag 1 day, OR 0.9890, 95% CI 0.9789-0.9992, P < 0.05), daily pressure range (lag 7 days, OR 1.0195, 95% CI 1.0079-1.0312, P < 0.01), and daily temperature range (lag 5 days, OR 1.0208, 95% CI 1.0087-1.0331, P < 0.01). Moreover, a significant correlation was observed between daily pressure range and daily temperature range with AF patients, particularly those with abnormal ECG repolarization, as evident in the case-crossover analysis. CONCLUSION: This study highlights a significant correlation between meteorological factors and daily hospital visits for AF accompanied by abnormal ECG repolarization in Shanghai, China. In addition, AF patients with abnormal ECG repolarization were found to be more vulnerable to rapid daily changes in pressure and temperature compared to AF patients without such repolarization abnormalities.

CRISPR screens reveal convergent targeting strategies against evolutionarily distinct chemoresistance in cancer.

Resistance to chemotherapy has been a major hurdle that limits therapeutic benefits for many types of cancer. Here we systematically identify genetic drivers underlying chemoresistance by performing 30 genome-scale CRISPR knockout screens for seven chemotherapeutic agents in multiple cancer cells. Chemoresistance genes vary between conditions primarily due to distinct genetic background and mechanism of action of drugs, manifesting heterogeneous and multiplexed routes towards chemoresistance. By focusing on oxaliplatin and irinotecan resistance in colorectal cancer, we unravel that evolutionarily distinct chemoresistance can share consensus vulnerabilities identified by 26 second-round CRISPR screens with druggable gene library. We further pinpoint PLK4 as a therapeutic target to overcome oxaliplatin resistance in various models via genetic ablation or pharmacological inhibition, highlighting a single-agent strategy to antagonize evolutionarily distinct chemoresistance. Our study not only provides resources and insights into the molecular basis of chemoresistance, but also proposes potential biomarkers and therapeutic strategies against such resistance.

ACLY and ACSS2 link nutrient-dependent chromatin accessibility to CD8 T cell effector responses.

Coordination of cellular metabolism is essential for optimal T cell responses. Here, we identify cytosolic acetyl-CoA production as an essential metabolic node for CD8 T cell function in vivo. We show that CD8 T cell responses to infection depend on acetyl-CoA derived from citrate via the enzyme ATP citrate lyase (ACLY). However, ablation of ACLY triggers an alternative, acetate-dependent pathway for acetyl-CoA production mediated by acyl-CoA synthetase short-chain family member 2 (ACSS2). Mechanistically, acetate fuels both the TCA cycle and cytosolic acetyl-CoA production, impacting T cell effector responses, acetate-dependent histone acetylation, and chromatin accessibility at effector gene loci. When ACLY is functional, ACSS2 is not required, suggesting acetate is not an obligate metabolic substrate for CD8 T cell function. However, loss of ACLY renders CD8 T cells dependent on acetate (via ACSS2) to maintain acetyl-CoA production and effector function. Together, ACLY and ACSS2 coordinate cytosolic acetyl-CoA production in CD8 T cells to maintain chromatin accessibility and T cell effector function.

Effects of low-dose recombinant human brain natriuretic peptide on anterior myocardial infarction complicated by cardiogenic shock

Abstract INTRODUCTION: The mortality due to cardiogenic shock complicating acute myocardial infarction (AMI) is high even in patients with early revascularization. Infusion of low dose recombinant human brain natriuretic peptide (rhBNP) at the time of AMI is well tolerated and could improve cardiac function. OBJECTIVE: The objective of this study was to evaluate the hemodynamic effects of rhBNP in AMI patients revascularized by emergency percutaneous coronary intervention (PCI) who developed cardiogenic shock. METHODS: A total of 48 patients with acute ST segment elevation myocardial infarction (STEMI) complicated by cardiogenic shock and whose hemodynamic status was improved following emergency PCI were enrolled. Patients were randomly assigned to rhBNP (n=25) and control (n=23) groups. In addition to standard therapy, study group individuals received rhBNP by continuous infusion at 0.005 µg kg−1 min−1 for 72 hours. RESULTS: Baseline characteristics, medications, and peak of cardiac troponin I (cTnI) were similar between both groups. rhBNP treatment resulted in consistently improved pulmonary capillary wedge pressure (PCWP) compared to the control group. Respectively, 7 and 9 patients died in experimental and control groups. No drug-related serious adverse events occurred in either group. CONCLUSION: When added to standard care in stable patients with cardiogenic shock complicating anterior STEMI, low dose rhBNP improves PCWP and is well tolerated.