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Objectives Accurate survival predictions and early interventional therapy are crucial for people with clear cell renal cell carcinoma (ccRCC). Methods In this retrospective study, we identified differentially expressed immune-related (DE-IRGs) and oncogenic (DE-OGs) genes from The Cancer Genome Atlas (TCGA) dataset to construct a prognostic risk model using univariate Cox regression and least absolute shrinkage and selection operator (LASSO) analysis. We compared the immunogenomic characterization between the high- and low-risk patients in the TCGA and the PUCH cohort, including the immune cell infiltration level, immune score, immune checkpoint, and T-effector cell- and interferon (IFN)-γ-related gene expression. Results A prognostic risk model was constructed based on 9 DE-IRGs and 3 DE-OGs and validated in the training and testing TCGA datasets. The high-risk group exhibited significantly poor overall survival compared with the low-risk group in the training ( P < 0.0001), testing ( P = 0.016), and total ( P < 0.0001) datasets. The prognostic risk model provided accurate predictive value for ccRCC prognosis in all datasets. Decision curve analysis revealed that the nomogram showed the best net benefit for the 1-, 3-, and 5-year risk predictions. Immunogenomic analyses of the TCGA and PUCH cohorts showed higher immune cell infiltration levels, immune scores, immune checkpoint, and T-effector cell- and IFN-γ-related cytotoxic gene expression in the high-risk group than in the low-risk group. Conclusion The 12-gene prognostic risk model can reliably predict overall survival outcomes and is strongly associated with the tumor immune microenvironment of ccRCC.

Objective: To observe the clinical efficacy of Chinese herbal medicine combined with Liuzijue exercise on the physiological symptoms and quality of life (QoL) in postoperative patients with early-stage lung cancer. Methods: One hundred and eighty-three lung cancer patients who underwent video-assisted thoracoscopic surgery (VATS) were categorize into either a traditional Chinese medicine treatment group (CM) or a control group (non-traditional Chinese medicine treatment, NC), among whom 73 underwent Chinese herbal medicine and Liuzijue therapy, while 110 underwent no comprehensive treatment with traditional Chinese medicine. The propensity score matching (PSM) method with a 1:2 ratio was used to balance the baseline characteristics and evaluate the efficacy of CM in improving postoperative symptoms and QoL. Results: Cough, dyspnea, chest pain, and fatigue were the most common clinical symptoms after VATS. Except for chest pain, they were all correlated with the scope of operation ( P .05). In the domain of global health status, the improvement in QoL in CM was greater than that in NC (6.06 ± 15.83 vs −1.06 ± 14.68, P = .005). In terms of symptoms, improvements in cough (1.69 ± 3.15 vs 0.38 ± 2.63, P = .006), dyspnea during climbing stairs (−10.30 ± 16.82 vs −1.82 ± 17.97, P = .004), and pain (−0.76 ± 1.32 vs −0.08 ± 1.31, P = .002) in CM were better than in NC. Conclusion: Comprehensive treatment with traditional Chinese medicine (TCM) can provide therapeutic benefits in physiological rehabilitation after VATS for cancer.

Objective To investigate the diagnostic values of D-dimer, plasminogen activator inhibitor-1 (PAI-1), thrombin–antithrombin (TAT), and prothrombin fragment F1 + 2 (F1 + 2) for predicting venous thromboembolism (VTE) after total knee arthroplasty (TKA). Methods Ultrasonography and CTPA were performed to diagnose VTE in 252 patients who underwent TKAs. Plasma D-dimer, PAI-1, TAT, and F1 + 2 levels were assessed 1–3 days prior to operation (T1), second hour (T2), first (T3), and third day (T4) after the operation. Receiver–operating characteristic curves (ROC) analysis was conducted and pairwise compared to evaluate the diagnostic value of those biomarkers. Results Plasma D-dimer levels differed between patients with and without VTE significantly on T4, PAI-1, TAT, and F1 + 2 levels differed on T3 and T4. The areas under ROC of D-dimer, PAI-1, TAT and F1 + 2 levels were 0.645, 0.773, 0.771 and 0.797, respectively. The most feasible cutoff values of D-dimer, PAI-1, TAT and F1 + 2 in predicting VTE after TKA were 2.24 ug/ml, 35.96 ng/ml, 13.36 ng/mg and 11.1 ng/ml, respectively. Pairwise comparison of ROC curves revealed that D-dimer level had the lowest diagnostic accuracy, whereas PAI-1, TAT and F1 + 2 level had similar diagnostic accuracy. There were significant differences in duration of tourniquet time and duration of anesthesia between patients with and without VTE. Conclusion After TKA, using 2.24ug/mL as the threshold value of D-dimer is more accurate than using 0.5ug/mL in the monitoring of VTE, PAI-1, TAT and F1 + 2 are more valuable than D-dimer in predicting VTE. Duration of tourniquet and duration of anesthesia are risk factors for the development of VTE.