Search

BackgroundRenal cell carcinoma (RCC) is a highly metastatic urological cancer. RCC with liver metastasis (LM) carries a dismal prognosis. The objective of this study is to develop a machine learning (ML) model that predicts the risk of RCC with LM, which is used to assist clinical treatment.MethodsThe retrospective study data of 42,547 patients with RCC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. ML includes algorithmic methods and is a fast-rising field that has been widely used in the biomedical field. Logistic regression (LR), Gradient Boosting Machine (GBM), Extreme Gradient Boosting (XGB), random forest (RF), decision tree (DT), and naive Bayesian model [Naive Bayes Classifier (NBC)] were applied to develop prediction models to predict the risk of RCC with LM. The six models were 10-fold cross-validated, and the best-performing model was selected based on the area under the curve (AUC) value. A web online calculator was constructed based on the best ML model.ResultsBone metastasis, lung metastasis, grade, T stage, N stage, and tumor size were independent risk factors for the development of RCC with LM by multivariate regression analysis. In addition, the correlation of the relative proportions of the six clinical variables was shown by a heat map. In the prediction models of RCC with LM, the mean AUC of the XGB model among the six ML algorithms was 0.947. Based on the XGB model, the web calculator (https://share.streamlit.io/liuwencai4/renal_liver/main/renal_liver.py) was developed to evaluate the risk of RCC with LM.ConclusionsThis XGB model has the best predictive effect on RCC with LM. The web calculator constructed based on the XGB model has great potential for clinicians to make clinical decisions and improve the prognosis of RCC patients with LM.

Postoperative nausea and vomiting (PONV) is one of the most common and unpleasant postoperative complications in children. This study aims to evaluate the efficacy and safety of using dexamethasone alone or combined other drugs on the incidence of PONV in children. A systematic search of the literature was conducted from inception until March, 2019. Literature selection and data extraction were conducted by two independent reviewers. Statistical analysis was performed using the software package Review Manager Version 5.3.3. Twenty studies with total 2505 participants were included. The pooled analysis used a random-effect model showed that dexamethasone had significantly greater efficacy in incidence of POV and PON in postoperative 24 h than control. Subgroup analysis indicated the RR of dexamethasone ≥0.5 mg/kg group was the lowest compared subgroup dexamethasone ≤0.3 mg/kg and 0.3–0.5 mg/kg. There was no difference for early POV between dexamethasone and placebo groups. Dexamethasone combined with others also could significantly reduce the incidence of POV in postoperative 24 h. Few adverse effects were reported. This study indicates that dexamethasone is effective for preventing incidence of PONV in children. And multimodal approaches have shown more effectively to prevent the incidence of POV.

Different analytical methods or models can often find completely different prognostic biomarkers for the same cancer. In the study of prognostic molecular biomarkers of ovarian cancer (OvCa), different studies have reported a variety of prognostic gene signatures. In the current study, based on geometric concepts, the linearity-clustering phase diagram with integrated P-value (LCP) method was used to comprehensively consider three indicators that are commonly employed to estimate the quality of a prognostic gene signature model. The three indicators, namely, concordance index, area under the curve, and level of the hazard ratio were determined via calculation of the prognostic index of various gene signatures from different datasets. As evaluation objects, we selected 13 gene signature models (Cox regression model) and 16 OvCa genomic datasets (including gene expression information and follow-up data) from published studies. The results of LCP showed that three models were universal and better than other models. In addition, combining the three models into one model showed the best performance in all datasets by LCP calculation. The combination gene signature model provides a more reliable model and could be validated in various datasets of OvCa. Thus, our method and findings can provide more accurate prognostic biomarkers and effective reference for the precise clinical treatment of OvCa.

Importance. Acupuncture can help reduce unpleasant side effects associated with endocrine therapy for breast cancer. Nevertheless, comprehensive evaluation of current evidence from randomized controlled trials(RCTs) is lacking. Objective. To estimate the efficacy of acupuncture for the reduction of hormone therapy-related side effects in breast cancer patients. Evidence review. RCTs of acupuncture in breast cancer patients that examined reductions in hormone therapy–related side effects were retrieved from PubMed, EMBASE, Web of Science, Ovid MEDLINE, and Cochrane Library databases through April 2016. The quality of the included studies was evaluated according to the 5.2 Cochrane Handbook standards, and CONSORT and STRICTA (Revised Standards for Reporting Interventions in Clinical Trials of Acupuncture) statements. Intervention . Interventions included conventional acupuncture treatment compared with no treatment, placebo, or conventional pharmaceutical medication. Major outcome measures were the alleviation of frequency and symptoms and the presence of hormone therapy–related side effects. Findings/Results. A total of 17 RCTs, including a total of 810 breast cancer patients were examined. The methodological quality of the trials was relatively rigorous in terms of randomization, blinding, and sources of bias. Compared with control therapies, the pooled results suggested that acupuncture had moderate effects in improving stiffness. No significant differences were observed in hot flashes, fatigue, pain, gastrointestinal symptoms, Kupperman index, general well-being, physical well-being, tumor necrosis factor (TNF), and interleukin (IL). Conclusions. Acupuncture therapy appears to be potentially useful in relieving functional stiffness. However, further large-sample trials with evidence-based design are still needed to confirm these findings.

Background: The PRISMA statement was rarely used in the field of acupuncture, possibly because of knowledge gaps and the lack of items tailored for characteristics of acupuncture. And with an increasing number of systematic reviews in acupuncture, it is necessary to develop an extension of PRISMA for acupuncture. And this study was the first step of our project, of which the aim was to investigate the need for information of clinical evidence on acupuncture from the perspectives of evidence users. Methods: We designed a questionnaire based on a pilot survey and a literature review of acupuncture systematic review or meta-analysis(SR/MA). Participants from five cities (Lanzhou, Chengdu, Shanghai, Nanjing and Beijing) representing the different regions of China, including clinicians, researchers and postgraduates in their second year of Master studies or higher level, were surveyed. Results: A total of 269 questionnaires were collected in 18 hospitals, medical universities and research agencies, and 251 (93 %) with complete data were used for analysis. The average age of respondents was 33 years (SD 8.959, range 25-58) with male 43 % and female 57 %. Most respondents had less than 5 years of working experience on acupuncture, and read only one to five articles per month. Electronic databases, search engines and academic conferences were the most common sources for obtaining information. Fifty-six percent of the respondents expressed low satisfaction of the completeness of information from the literature. The eight items proposed for acupuncture SR/MAs received all high scores, and five of the items scored higher than eight on a scale zero to ten. The differences for the scores of most items between postgraduates and non-postgraduates were not statistically significant. Conclusions: The majority of the respondents were not very satisfied with the information provided in acupuncture SRs. Most of the items proposed in this questionnaire received high scores, and opinions from postgraduates and non-postgraduates tended to agree on most items. Comments from the respondents can promote future work. [ABSTRACT FROM AUTHOR]