Prediction of 90-day mortality after surgery for colorectal cancer using standardized nationwide quality-assurance data.

BACKGROUND: Personalized risk assessment provides opportunities for tailoring treatment, optimizing healthcare resources and improving outcome. The aim of this study was to develop a 90-day mortality-risk prediction model for identification of high- and low-risk patients undergoing surgery for colorectal cancer. METHODS: This was a nationwide cohort study using records from the Danish Colorectal Cancer Group database that included all patients undergoing surgery for colorectal cancer between 1 January 2004 and 31 December 2015. A least absolute shrinkage and selection operator logistic regression prediction model was developed using 121 pre- and intraoperative variables and internally validated in a hold-out test data set. The accuracy of the model was assessed in terms of discrimination and calibration. RESULTS: In total, 49 607 patients were registered in the database. After exclusion of 16 680 individuals, 32 927 patients were included in the analysis. Overall, 1754 (5.3 per cent) deaths were recorded. Targeting high-risk individuals, the model identified 5.5 per cent of all patients facing a risk of 90-day mortality exceeding 35 per cent, corresponding to a 6.7 times greater risk than the average population. Targeting low-risk individuals, the model identified 20.9 per cent of patients facing a risk less than 0.3 per cent, corresponding to a 17.7 times lower risk compared with the average population. The model exhibited discriminatory power with an area under the receiver operating characteristics curve of 85.3 per cent (95 per cent c.i. 83.6 to 87.0) and excellent calibration with a Brier score of 0.04 and 32 per cent average precision. CONCLUSION: Pre- and intraoperative data, as captured in national health registries, can be used to predict 90-day mortality accurately after colorectal cancer surgery.

Specific Follicular Helper T Cell Signature in Takayasu Arteritis.

OBJECTIVE: Our aim was to compare transcriptome and phenotype profiles of CD4+ T cells and CD19+ B cells in patients with Takayasu arteritis (TAK), patients with giant cell arteritis (GCA), and healthy donors. METHODS: Gene expression analyses, flow cytometry immunophenotyping, T cell receptor (TCR) gene sequencing, and functional assessments of cells from peripheral blood and arterial lesions from TAK patients, GCA patients, and healthy donors were performed. RESULTS: Among the most significantly dysregulated genes in CD4+ T cells of TAK patients compared to GCA patients (n = 720 genes) and in CD4+ T cells of TAK patients compared to healthy donors (n = 1,447 genes), we identified a follicular helper T (Tfh) cell signature, which included CXCR5, CCR6, and CCL20 genes, that was transcriptionally up-regulated in TAK patients. Phenotypically, there was an increase in CD4+CXCR5+CCR6+CXCR3- Tfh17 cells in TAK patients that was associated with a significant enrichment of CD19+ B cell activation. Functionally, Tfh cells helped B cells to proliferate, differentiate into memory cells, and secrete IgG antibodies. Maturation of B cells was inhibited by JAK inhibitors. Locally, in areas of arterial inflammation, we found a higher proportion of tertiary lymphoid structures comprised CD4+, CXCR5+, programmed death 1+, and CD20+ cells in TAK patients compared to GCA patients. CD4+CXCR5+ T cells in the aortas of TAK patients had an oligoclonal α/ß TCR repertoire. CONCLUSION: We established the presence of a specific Tfh cell signature in both circulating and aorta-infiltrating CD4+ T cells from TAK patients. The cooperation of Tfh cells and B cells might be critical in the occurrence of vascular inflammation in patients with TAK.