Establishment of a risk prediction model for prolonged mechanical ventilation after lung transplantation: a retrospective cohort study.

BACKGROUND: Prolonged mechanical ventilation (PMV), mostly defined as mechanical ventilation > 72 h after lung transplantation with or without tracheostomy, is associated with increased mortality. Nevertheless, the predictive factors of PMV after lung transplant remain unclear. The present study aimed to develop a novel scoring system to identify PMV after lung transplantation. METHODS: A total of 141 patients who underwent lung transplantation were investigated in this study. The patients were divided into PMV and non-prolonged ventilation (NPMV) groups. Univariate and multivariate logistic regression analyses were performed to assess factors associated with PMV. A risk nomogram was then established based on the multivariate analysis, and model performance was further examined regarding its calibration, discrimination, and clinical usefulness. RESULTS: Eight factors were finally identified to be significantly associated with PMV by the multivariate analysis and therefore were included as risk factors in the nomogram as follows: the body mass index (BMI, P = 0.036); primary diagnosis as idiopathic pulmonary fibrosis (IPF, P = 0.038); pulmonary hypertension (PAH, P = 0.034); primary graft dysfunction grading (PGD, P = 0.011) at T0; cold ischemia time (CIT P = 0.012); and three ventilation parameters (peak inspiratory pressure [PIP, P < 0.001], dynamic compliance [Cdyn, P = 0.001], and P/F ratio [P = 0.015]) at T0. The nomogram exhibited superior discrimination ability with an area under the curve of 0.895. Furthermore, both calibration curve and decision-curve analysis indicated satisfactory performance. CONCLUSION: A novel nomogram to predict individual risk of receiving PMV for patients after lung transplantation was established, which may guide preventative measures for tackling this adverse event.

The predictive value of inflammatory biomarkers for major pathological response in non-small cell lung cancer patients receiving neoadjuvant chemoimmunotherapy and its association with the immune-related tumor microenvironment: a multi-center study.

BACKGROUND: Inflammatory biomarkers in the peripheral blood have been established as predictors for immunotherapeutic efficacy in advanced non-small cell lung cancer (NSCLC). Whether they can also predict major pathological response (MPR) in neoadjuvant setting remains unclear. METHODS: In this multi-center retrospective study, 122 and 92 stage I-IIIB NSCLC patients from six hospitals who received neoadjuvant chemoimmunotherapy followed by surgery were included in the discovery and external validation cohort, respectively. Baseline and on-treatment neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR) and systemic immune-inflammation index (SII) were calculated and associated with MPR. Furthermore, resected tumor samples from 37 patients were collected for RNA-sequencing to investigate the immune-related tumor microenvironment. RESULTS: In both the discovery and validation cohorts, the on-treatment NLR, dNLR, PLR, and SII levels were significantly lower in the patients with MPR versus non-MPR. On-treatment SII remained an independent predictor of MPR in multivariate logistic regression analysis. The area under the curve (AUC) of on-treatment SII for predicting MPR was 0.75 (95%CI, 0.67-0.84) in the discovery cohort. Moreover, the predictive value was further improved by combining the on-treatment SII and radiological tumor regression data, demonstrating an AUC of 0.82 (95%CI, 0.74-0.90). The predictive accuracy was validated in the external cohort. Compared with the SII-high group, patients with SII-Low were associated with the activated B cell receptor signaling pathway and a higher intratumoral immune cell infiltration level. CONCLUSIONS: On-treatment SII was independently associated with MPR in NSCLC patients receiving neoadjuvant chemoimmunotherapy. Further prospective studies are warranted.

A novel CD2 staining-based flow cytometric assay for assessment of natural killer cell cytotoxicity.

BACKGROUND: Assessing cytotoxicity is fundamental to studying natural killer (NK) cell function. Various radioactive and non-radioactive cytotoxicity assays measuring target cell death have been developed. Among these methods, the most commonly used 51 Chromium-release assay (CRA) and flow cytometry-based cytotoxicity assays (FCCs) are the major representatives. Nonetheless, several drawbacks, including dye leakage and the potential effects of prior labeling on cells, curb the broad applicability of the FCCs. METHODS: Here, we report a rapid FCC for quantifying target cell death after co-incubation with NK cells. In this assay, after 4 hours of NK cell-target cell co-incubation, fluorochrome-conjugated CD2 antibody was used to identify NK cells, and SYTOX Green and Annexin V-FITC were further used to detect target cell death in CD2-negative population. In parallel, both CRA and FCC assay using CFSE/ 7-AAD were performed to validate the reproducibility and replicability. RESULTS: We observed that CD2 is exclusively positive on NK cells other than the most common hematological target tumor cells, such as K562, HL60, MOLM13, Raji, NCI-H929, rpmi8226, MM.1S, and KMS11. Assessment of target cell death using the CD2-based FCC shows a significantly higher percent specific lysis of the target cells compared to the standard CRA and the FCC assay using CFSE and 7-AAD. CONCLUSIONS: We demonstrated that this CD2-based FCC is a fast, simple, and reliable method for evaluating NK cell cytotoxicity.