ObjectiveNumerous studies have suggested that microRNA-126 (miR-126) is involved in development of various cancer types as well as in malignant proliferation and invasion. However, its role in human prostate cancer (PCa) is still unclear. The aim of this study was to investigate miR-126 expression in PCa and its prognostic value for PCa patients undergoing radical prostatectomy.MethodsA series of 128 cases with PCa were evaluated for the expression levels of miR-126 by quantitative reverse-transcription PCR (qRT-PCR). Kaplan-Meier analysis and Cox proportional hazards regression models were used to investigate the correlation between miR-126 expression and prognosis of PCa patients.ResultsCompared with non-cancerous prostate tissues, the expression level of miR-126 was significantly decreased in PCa tissues (PCa vs. non-cancerous prostate: 1.05 ± 0.63 vs. 2.92 ± 0.98, P < 0.001). Additionally, the loss of miR-126 expression was dramatically associated with aggressive clinical pathological features, including advanced pathological stage (P = 0.001), positive lymph node metastasis (P = 0.006), high preoperative PSA (P = 0.003) and positive angiolymphatic invasion (P = 0.001). Moreover, Kaplan–Meier survival analysis showed that PCa patients with low miR-126 expression have shorter biochemical recurrence (BCR)-free survival than those with high miR-126 expression. Furthermore, multivariate analysis indicated that miR-126 expression was an independent prognostic factor for BCR-free survival after radical prostatectomy.ConclusionThese findings suggest for the first time that the loss of miR-126 expression may play a positive role in the malignant progression of PCa. More importantly, the downregulation of miR-126 may serve as an independent predictor of BCR-free survival in patients with PCa.Virtual slidesThe virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/1740080792113255.
Background Blunt chest trauma patients with pulmonary contusion are susceptible to pulmonary complications, and severe cases may develop respiratory failure. Some studies have suggested the extent of pulmonary contusion to be the main predictor of pulmonary complications. However, no simple and effective method to assess the severity of pulmonary contusion has been available yet. A reliable prognostic prediction model would facilitate the identification of high-risk patients, so that early intervention can be given to reduce pulmonary complications; however, no suitable model based on such an assumption has been available yet. Methods In this study, a new method for assessing lung contusion by the product of the three dimensions of the lung window on the computed tomography (CT) image was proposed. We conducted a retrospective study on patients with both thoracic trauma and pulmonary contusion admitted to 8 trauma centers in China from January 2014 to June 2020. Using patients from 2 centers with a large number of patients as the training set and patients from the other 6 centers as the validation set, a prediction model for pulmonary complications was established with Yang’s index and rib fractures, etc., being the predictors. The pulmonary complications included pulmonary infection and respiratory failure. Results This study included 515 patients, among whom 188 developed pulmonary complications, including 92 with respiratory failure. Risk factors contributing to pulmonary complications were identified, and a scoring system and prediction model were constructed. Using the training set, models for adverse outcomes and severe adverse outcomes were developed, and area under the curve (AUC) of 0.852 and 0.788 were achieved in the validation set. In the model performance for predicting pulmonary complications, the positive predictive value of the model is 0.938, the sensitivity of the model is 0.563 and the specificity of the model is 0.958. Conclusions The generated indicator, called Yang’s index, was proven to be an easy-to-use method for the evaluation of pulmonary contusion severity. The prediction model based on Yang’s index could facilitate early identification of patients at risk of pulmonary complications, yet the effectiveness of the model remains to be validated and its performance remains to be improved in further studies with larger sample sizes.
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