The effect of preoperative external radiotherapy (XRT) on head and neck free‐flap reconstruction is still controversial. In this study, we aimed to determine the impact of preoperative XRT on the outcomes of head and neck microvascular free‐flap reconstruction. A systematic review and meta‐analysis was conducted in concordance with the Systematic reviews and Meta‐Analyses protocol. We searched several databases (PubMed, EMBASE, Web of Science, and Cochrane Library) to find published papers on the topic. The R program was used for data synthesis and statistical heterogeneity evaluation; then, fixed effect or random effect models were used. A total of 37 studies, involving 12 408 patients with 12 668 flaps, were included in this meta‐analysis. The overall flap success rate for all studies was 94.4%. Pooled analysis showed that patients with preoperative XRT were significantly associated with an increased risk of total flap failure (odds ratio [OR] = 1.80, 95% confidence interval [CI] = 1.45‐2.23, P < .001), partial flap failure (OR = 1.90, 95% CI = 1.07‐3.38, P = .029), and postoperative complication rates (OR = 2.22, 95% CI = 1.64‐2.72, P < .001). Our study suggests that preoperative XRT is associated with an increased risk of developing free‐flap failure and an increased postoperative complication rate.

Background. The majority of lung cancers are adenocarcinomas, with the proportion being 40%. The patients are mostly diagnosed in the middle and late stages with metastasis and easy recurrence, which poses great challenge to the treatment and prognosis. Platinum-based chemotherapy is a primary treatment for adenocarcinoma, which frequently causes drug resistance. As a result, it is important to uncover the mechanisms of the chemoresponse of adenocarcinoma to platinum-based chemotherapy. Methods. The genes from the dataset GSE7880 were gathered into gene modules with the assistance of weighted gene coexpression network analysis (WGCNA), the gene trait significance absolute value (|GS|), and gene module memberships (MM). The genes from hub gene modules were calculated with a protein-protein interaction (PPI) network analysis in order to obtain a screening map of hub genes. The hub genes with both a high |GS| and MM and a high degree were selected. Furthermore, genes in the hub gene modules also went through a Gene Ontology (GO) functional enrichment analysis. Results. 11 hub genes in four hub gene modules (LY86, ACTR2, CDK2, CKAP4, KPNB1, RBBP4, SMAD4, MYL6, RPS27, TSPAN2, and VAMP2) were chosen as the significant hub genes. Through the GO function enrichment analysis, it was indicated that four modules were abundant in immune system functions (floralwhite), amino acid biosynthetic process (lightpink4), cell chemotaxis (navajowhite2), and targeting protein (paleturquoise). Four hub genes with the highest |GS| were verified by prognostic analysis.

In the past decades, lung cancer is considered one of the lethal cancers all across the world due to its evidenced greatest mortality and morbidity. Currently, the main clinical treatment methods for lung cancer involve surgery, chemotherapy, radiotherapy, anti-angiogenesis inhibitors and tyrosine kinase inhibitors. In the field of anticancer drugs, a variety of new anticancer drugs have been emerging in recent years. They include chemotherapy drugs with new delivery modes, targeted drugs for tyrosine kinase inhibitors, angiogenesis inhibitors, and immunotherapy drugs that have remained hot. But because cancer cells have complex escape mechanisms, the effectiveness of these single-drug treatments has been disappointing. In this case, a number of new combination therapies have emerged and achieved relatively good results. According to the 2020 third edition of the NCCN guidelines, four multi-therapy regiments (Erlotinib plus ramucirumab, Erlotinib plus bevacizumab, Carboplatin plus albumin-bound paclitaxel plus atezolizumab and Nivolumab plus ipilimumab) have passed clinical trials, adding first-line treatments. In this review, the research provided an overview of these four new approved combining treatment strategies in addition to predicting future drug development directions.