Background Adequate safe margin in tongue cancer radical surgery is one of the most important prognostic factors. However, the role of peritumoral tissues in predicting lymph node metastasis (LNM) and prognosis using radiomics analysis remains unclear. Purpose To investigate whether magnetic resonance imaging (MRI)‐based radiomics analysis with peritumoral extensions contributes toward the prediction of LNM and prognosis in tongue cancer. Study type Retrospective. Population Two hundred and thirty‐six patients (38.56% female) with tongue cancer (training set, N = 157; testing set, N = 79; 37.58% and 40.51% female for each). Field Strength/Sequence 1.5 T; T2‐weighted turbo spin‐echo images. Assessment Radiomics models (Rprim, Rprim+3, Rprim+5, Rprim+10, Rprim+15) were developed with features extracted from the primary tumor without or with peritumoral extensions (3, 5, 10, and 15 mm, respectively). Clinicopathological characteristics selected from univariate analysis, including MRI‐reported LN status, radiological extrinsic lingual muscle invasion, and pathological depth of invasion (DOI) were further incorporated into radiomics models to develop combined radiomics models (CRprim, CRprim+3, CRprim+5, CRprim+10, CRprim+15). Finally, the model performance was validated in the testing set. DOI was measured from the adjacent normal mucosa to the deepest point of tumor invasion. Statistical Tests Chi‐square test, regression analysis, receiver operating characteristic curve (ROC) analysis, decision analysis, spearman correlation analysis. The Delong test was used to compare area under the ROC (AUC). P < 0.05 was considered statistically significant. Results Of all the models, the CRprim+10 reached the highest AUC of 0.995 in the training set and 0.872 in the testing set. Radiomics features were significantly correlated with pathological DOI (correlation coefficients, −0.157 to −0.336). The CRprim+10 was an independent indicator for poor disease‐free survival (hazard ratio, 5.250) and overall survival (hazard ratio, 17.464) in the testing set. Data Conclusion Radiomics analysis with a 10‐mm peritumoral extension had excellent power to predict LNM and prognosis in tongue cancer.
The gene-guided dosing strategy of warfarin generally leads to over-dose in patients at doses lower than 2 mg/kg, and only 50% of individual variability in daily stable doses can be explained. In this study, we developed a novel population pharmacokinetic (PK) model based on a warfarin dose algorithm for Han Chinese patients with valve replacement for improving the dose prediction accuracy, especially in patients with low doses. The individual pharmacokinetic (PK) parameter - apparent clearance of S- and R-warfarin (CLs) was obtained after establishing and validating the population PK model from 296 recruited patients with valve replacement. Then, the individual estimation of CLs, VKORC1 genotypes, the steady-state international normalized ratio (INR) values and age were used to describe the maintenance doses by multiple linear regression for 144 steady-state patients. The newly established dosing algorithm was then validated in an independent group of 42 patients and was compared with other dosing algorithms for the accuracy and precision of prediction. The final regression model developed was as follows: Dose=-0.023×AGE+1.834×VKORC1+0.952×INR+2.156×CLs (the target INR value ranges from 1.8 to 2.5). The validation of the algorithm in another group of 42 patients showed that the individual variation rate (71.6%) was higher than in the gene-guided dosing models. The over-estimation rate in patients with low doses (<2 mg/kg) was lower than the other dosing methods. This novel dosing algorithm based on a population PK model improves the predictive performance of the maintenance dose of warfarin, especially for low dose (<2 mg/d) patients.
Background Postpartum alanine transaminase (ALT) flares occur frequently in chronic hepatitis B virus (HBV)-infected mothers with antepartum antiviral therapy (AVT). We aimed to characterize the T cell immunity in HBV-infected mothers experiencing postpartum ALT flares. Methods Twenty HBV-infected pregnant women who received AVT at 26–28 weeks of gestation were enrolled and followed up until 15–18 weeks postpartum. Among the 20 HBV-infected pregnant women, 6 experienced postpartum ALT flare (AF mothers), while 14 did not (NAF mothers). T lymphocyte phenotypes and functions were analyzed using flow cytometry. Results Compared to NAF mothers, the quantitative HBsAg levels in AF mothers decreased significantly at 6–8 or 15–18 weeks postpartum. Significant differences in HBeAg levels between these groups were only found at delivery. Regulatory T cell (Treg) numbers in AF mothers were lower than those of NAF mothers before AVT; however, there were no significant differences in Treg numbers at other follow-up points. Expression of other T cell phenotypes were similar between the two groups. T cells in AF mothers produced more pro-inflammatory cytokines (IFN-γ, IL-21, TNF-α, IL-2) or less anti-inflammatory cytokine (IL-10) than those in NAF mothers before, during, or after antiviral treatment. The ratio of IFN-γ to IL-10 producing by CD4+ T cells or CD8+ T cells was higher in AF mothers than that in NAF mothers during pregnancy or after delivery. Conclusions The characteristics of T cell immunity was distinct between mothers with postpartum ALT flare and those without ALT flare from pregnancy to postpartum, which indicated that T cell immunity might get involved in postpartum ALT flare.
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