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BackgroundDevelopment of severe immune-related adverse events (irAEs) is a major predicament to stop treatment with immune checkpoint inhibitors, even though tumor progression is suppressed. However, no effective early phase biomarker has been established to predict irAE until now.MethodThis study retrospectively used the data of four international, multi-center clinical trials to investigate the application of blood test biomarkers to predict irAEs in atezolizumab-treated advanced non-small cell lung cancer (NSCLC) patients. Seven machine learning methods were exploited to dissect the importance score of 21 blood test biomarkers after 1,000 simulations by the training cohort consisting of 80%, 70%, and 60% of the combined cohort with 1,320 eligible patients.ResultsXGBoost and LASSO exhibited the best performance in this study with relatively higher consistency between the training and test cohorts. The best area under the curve (AUC) was obtained by a 10-biomarker panel using the XGBoost method for the 8:2 training:test cohort ratio (training cohort AUC = 0.692, test cohort AUC = 0.681). This panel could be further narrowed down to a three-biomarker panel consisting of C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), and thyroid-stimulating hormone (TSH) with a small median AUC difference using the XGBoost method [for the 8:2 training:test cohort ratio, training cohort AUC difference = −0.035 (p < 0.0001), and test cohort AUC difference = 0.001 (p=0.965)].ConclusionBlood test biomarkers currently do not have sufficient predictive power to predict irAE development in atezolizumab-treated advanced NSCLC patients. Nevertheless, biomarkers related to adaptive immunity and liver or thyroid dysfunction warrant further investigation.

Chemotherapy-induced peripheral neuropathy (CIPN) is among the most disabling and frustrating problems for cancer survivors. The neurotoxicity caused by cisplatin varies greatly among patients, and few predictors of appearance, duration of symptoms, susceptibility, or severity are available. A deeper understanding of the mechanisms underlying individual differences in status, severity, or sensitivity in response to cisplatin treatment is therefore required. By analyzing the GSE64174 gene expression profile and constructing a weighted gene co-expression network analysis (WGCNA) network, we screened gene modules and hub genes related to CIPN status, severity and sensitivity. We first identified the transcriptome profile of mouse dorsal root ganglion (DRG) samples and transformed their genes to human DRG counterparts. We then constructed WGCNA gene modules via optimal soft-threshold power-identification and module-preservation analysis. Comprehensive analysis and identification of module hub genes were performed via functional-enrichment analysis and significant common hub genes were identified, including "Cytoscape_cytoHubba," "Cytoscape_MCODE," and "Metascape_MCODE." Brown, green, and blue modules were selected to represent CIPN sensitivity, status, and severity, respectively, via trait-module correlational analysis. Additionally, functional enrichment analysis results indicated that these three modules were associated with some crucial biological functions, such as neutrophil migration, chemokine-mediated signaling pathway, and PI3K-Akt signaling pathway. We then identified seven common hub genes via three methods, including CXCL10, CCL21, CCR2, CXCR4, TLR4, NPY1R, and GALR2, related to CIPN status, severity and sensitivity. Our results provide possible targets and mechanism insights into the development and progress of CIPN, which can guide further transformation and pre-clinical research.

IntroductionImmune checkpoint inhibitor (ICI) therapy is a major breakthrough in non-small cell lung cancer (NSCLC) treatment. However, valid predictive biomarkers are lacking. Blood cell count test (BCT) provides a direct quantification of various types of immune cells (ICs) to reveal the immune landscape to predict ICI treatment.MethodsThis study analyzed four international, multi-center clinical trials (OAK, BIRCH, POPLAR and FIR trials) to conduct post-hoc analyses of NSCLC patients undergoing atezolizumab (anti-PD-L1) single-agent treatment (n = 1,479) or docetaxel single-agent treatment (n = 707). BCT was conducted at three timepoints: pre-treatment (T1), the first day of treatment cycle 3 (T2), and first day of treatment cycle 5 (T3). Univariate and multivariate Cox regression analyses were conducted to identify early BCT biomarkers to predict atezolizumab treatment outcomes in NSCLC patients.ResultsThe BCT biomarkers of neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) at timepoint T3 and neutrophil-to-monocyte ratio (NMR) at timepoint T2 were identified as strong predictive biomarkers for atezolizumab (Ate)-treated NSCLC patients in comparison to docetaxel (Dtx)-treated patients regarding overall survival (OS) (BCTscore low-risk: HR Ate vs Dtx = 1.54 (95% CI: 1.04-2.27), P = 0.036; high-risk: HR Ate vs Dtx = 0.84 (95% CI: 0.62-1.12), P = 0.236). This identified BCTscore model showed better OS AUC in the OAK (AUC12month=0.696), BIRCH (AUC12month=0.672) and POPLAR+FIR studies (AUC12month=0.727) than that of each of the three single BCT biomarkers.ConclusionThe BCTscore model is a valid predictive and prognostic biomarker for atezolizumab-treated NSCLC patients.

ObjectiveThis study is to investigate the relationship between marital status and prognosis of patients with ovarian serous carcinoma.ResultsWe performed data analysis from 19,276 patients identified from the SEER database of the National Cancer Center of the United States. 57.8% of the patients were married, 13.0% unmarried, and 29.2% separated/ divorced/widowed (SDW). The median overall survival time ofthe unmarried group and the married group are 48 months and 52 months respectively. Univariate Cox regression analysis showed that the patients with serous ovarian cancer in the unmarried group resulted in a hazard ratio (HR) of 1.14 (95% CI: 1.08–1.19%;P P = 0.26). However, the SDW group was not statistically significantly different from the married group. (median 32 vs 52 months). Multivariate Cox regression analysis presented the unmarried group leading to a HR of 1.05 (95% CI: 1.00–1.11%;P = 0.05), and the SDW group was not significant with a HR of 0.99 (95% CI: 0.95–1.03%;P = 0.57).ConclusionUnmarried patients with ovarian serous carcinoma have higherHRof overall survival. After controlling age, race, grade, radiation and year of diagnosis, unmarried patients were found to have a significantly higher risk of OS. Consequently, these patients are suggested to obtain more focused healthcare for the management of ovarian serous carcinoma.

BACKGROUND AND OBJECTIVE Periodontitis is a multifactorial disease that can lead to the progressive destruction of dental support tissue. However, the detailed mechanisms and specific biomarkers involved in periodontitis remain to be further studied. Recently, long non-coding RNAs (lncRNAs) have been found to play a more important role than other types of RNAs. In our study, we analysed the expression of lncRNAs in periodontitis by analysing GSE16134. MATERIAL AND METHODS We identified highly correlated genes by analysing GSE16134 with weighted gene co-expression network analysis (WGCNA) and identified 50 hub lncRNAs that were dysregulated. Then, we used the Linear Models for Microarray Data (Limma) package to identify the hub lncRNAs that were differentially expressed (DElncRNAs). The ceRNA co-expression network data were obtained from several sites, including miRcode, and were used to assess the potential WGCNA function of hub DElncRNAs in periodontitis. Besides, we divided the samples into LBX2-AS1 high and low expression group by the expression level of LBX2-AS1 and calculated DEG by Limma package. Furthermore, we performed GO function, KEGG pathway and GSEA enrichment of DEGs. RESULTS In the analysis, we identified 50 hub lncRNAs that may play important roles in periodontitis. Then, we used the Limma package to identify 3 hub DElncRNAs (LINC00687, LBX2-AS1 and LINC01566). We elucidated the potential function of the hub DElncRNA LBX2-AS1 in periodontitis by constructing a co-expression network of lncRNA-miRNA-mRNA interactions. Totally, 573 DEGs (354 up- and 219 downregulated) in periodontitis samples were identified. DEGs were enriched in different GO terms and pathways, such as neutrophil degranulation, neutrophil activation, neutrophil activation involved in immune response, neutrophil-mediated immunity, antigen processing and presentation, JAK-STAT signalling pathway, natural killer cell-mediated cytotoxicity, EGFR tyrosine kinase inhibitor resistance, phosphatidylinositol signalling system and Vascular Endothelial Growth Factor (VEGF) signalling pathway. CONCLUSION In our study, we found that 3 hub DElncRNAs (LINC00687, LBX2-AS1 and LINC01566) may be involved in the pathogenesis of periodontitis based on WGCNA and Limma analysis. Our study aimed to elucidate the mechanisms involved in periodontitis at the genetic and epigenetic levels by constructing a ceRNA network associated with lncRNA. Besides, identification DEGs of differential LBX2-AS1 and functional annotation showed that LBX2-AS1 might be associated with periodontitis.

Background: IGF-1 may be an important factor in bone remodeling, but its mechanism of action on osteoclasts during orthodontic tooth movement is complex and unclear. Methodology: The closed-coil spring was placed between the left maxillary first molar and upper incisors with a force of 50 g to establish an orthodontic movement model. Eighty SD rats were randomized to receive phosphate buffer saline or 400 ng rhIGF-1 in the lateral buccal mucosa of the left maxillary first molar every two days. Tissue sections were stained for tartrate-resistant acidic phosphatase (TRAP), the number of TRAP-positive cells was estimated and tooth movement measured. Results: The rhIGF-1 group exhibited evidential bone resorption and lacuna appeared on the alveolar bone compared to the control group. Moreover, the number of osteoclasts in compression side of the periodontal ligament in the rhIGF-1 group peaked at day 4 (11.37±0.95 compared to 5.28±0.47 in the control group) after the orthodontic force was applied and was significantly higher than that of the control group (p

BackgroundImmune checkpoint inhibitor (ICI) therapy is a major breakthrough for non-small cell lung cancer (NSCLC) treatment given its high efficacy and tolerable toxicity. Although pre-treatment PD-L1 expression levels and tumor mutation burden (TMB) may serve as prognostic biomarkers for patient stratification, effective predictive biomarkers are lacking. Blood cell count test (BCT) is a routine, regular blood test conducted before and during treatment to provide a direct overview of the immune landscape based on the counts of various types of immune cells (ICs). For instance, previous studies showed that neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) both indicate poor treatment outcomes of ICI therapy of NSCLC patients.MethodsThis study analyzed relevant combinations of IC counts from four international, multi-center clinical trials of OAK, BIRCH, POPLAR and FIR to conduct post-hoc analysis of NSCLC patients undergoing atezolizumab (anti-PD-L1) single-agent treatment (n = 1,479), while docetaxel single-agent treatment (n = 707) was used as control. BCT was conducted at three timepoints, T1 to T3, during pre-treatment and on the first day of treatment cycles 3 and 5, which correspond to baseline, 6, and 12 weeks on-treatment, respectively. Univariate and multivariate Cox regression analysis was conducted to identify NLR_T3, PLR_T3 and neutrophil-to-monocyte (NMR) at T2 as early BCT biomarkers that may predict ICI efficacy. Next, univariate and multivariate Cox proportional hazards regression analysis were used to identify any effective combination of BCT biomarkers and their absolute cutoff values that may serve as predictive biomarkers to predict atezolizumab treatment outcomes. Lastly, combinations of these BCT biomarkers were tested to optimize BCTscore model for clinical evaluation.ResultsThe final BCT biomarker combination, comprising of the BCT biomarkers of NLR and PLR at 12 weeks on-treatment (T3) and NMR at 6 weeks on-treatment (T2), was identified to be a strong predictive biomarker for atezolizumab (Ate)-treated NSCLC patients in comparison to docetaxel (Dtx)-treated patients regarding overall survival (OS) (BCTscore low-risk: HR Ate vs Dtx = 1.54 (95% CI: 1.04–2.27), P = 0.036; high-risk: HR Ate vs Dtx = 0.84 (95% CI: 0.62–1.12), P = 0.236). Our BCTscore model consistently exhibited better OS AUC in the OAK (AUC12month=0.696), BIRCH (AUC12month=0.672) and POPLAR+FIR studies (AUC12month=0.727) than that of each of the three BCT biomarkers in these three studies.ConclusionsThe BCTscore of NLR at 12 weeks, PLR at 12 weeks and NMR at 6 weeks is a strong efficacy predictive biomarker for atezolizumab-treated NSCLC patients.AcknowledgementsThe authors declare no conflict of interest. This publication is based on research using data from Genentech, Inc. (one of subsidiaries of Roche Group) that has been made available through Vivli, Inc (Data Request ID: 5935; Lead Investigator: Dr. Jian-Guo Zhou). Vivli has not contributed to or approved, and is not in any way responsible for, the contents of this publication.Trial RegistrationDeidentified individual participant data from the single-arm phase II studies of FIR study (NCT01846416; as of Janurary 7, 2015) [Spigel2018] and BIRCH (NCT02031458; as of May 28, 2015) [Peters2017], and the two-arm randomized controlled trials (RCT) of the POPLAR phase II study (NCT01903993; as of May 8, 2015) [Fehrenbacher2016] and the OAK phase III study (NCT02008227; as of July 7, 2016) [Rittmeyer2017] were made available by Genentech Inc. and accessed through the secure Vivli online platform.Ethics ApprovalBoth studies were approved by the respective national ethics committees and institutional review boards and written informed consent was obtained from all patients.

Background: Testicular germ cell tumors (TGCTs) are commonly diagnosed tumors in young men. However, a satisfactory approach to predict relapse of stage I TGCTs is still lacking. Therefore, this study aimed to develop a robust risk score model for stage I TGCTs. Method: RNA-sequence data of stage I TGCTs and normal testis samples were downloaded and analyzed to identify different expression genes. Gene-based prognostic model was constructed in The Cancer Genome Atlas (TCGA) using least absolute shrinkage and selection operator (LASSO) regression analysis and validated in GSE99420 dataset. Potential biological functions of the genes in prognostic model were determined via Gene Set Enrichment Analysis (GSEA) between high-risk and low-risk patients. Results: A total of 9,391 differentially expressed genes and 84 prognosis-related genes were identified. An eight-gene-based risk score model was constructed to divide patients into high or low risk of relapse. The low-risk patients had a significantly better relapse-free survival (RFS) than high-risk patients in both training and validation cohorts (HR = 0.129, 95% CI = 0.059–0.284, P < 0.001; HR = 0.277, 95% CI = 0.116–0.661, P = 0.004, respectively). The area under the receiver operating characteristic curve (AUC) values at 5 years was 0.805 and 0.724 in the training and validation cohorts, respectively. Functional enrichment analyses showed that DNA replication, ribosome, cell cycle, and TGF-beta signaling pathway may contribute to the relapse process. Conclusion: In summary, our analysis provided a novel eight-gene signature that could predict RFS in stage I TGCT patients.

Objectives: We performed a pooled analysis to evaluate the efficacy and adverse events (AEs) of olanzapine combined with dexamethasone plus compared with 5 HT3 RA plus dexamethasone for the prevention and treatment of chemotherapy-induced nausea and vomiting (CINV) in high and moderate emetogenic chemotherapy based on randomized controlled trials (RCTs). Methods: PubMed, EMBASE, Web of Science, the Cochrane Library, China Biomedical Literature database (CBM), WanFang Database, China National Knowledge Infrastructure (CNKI), and Chinese Science and Technology Periodical Database (VIP) (from their inception to April 2019) were searched to capture relevant articles. Relative risk (RR) with 95% confidence intervals (CIs) for CINV and AEs were all extracted or calculated. Result: Eleven studies with 1107 cancer patients were involved in this review. The pooled RR of delayed CINV (RR=0.50, 95%CI: 0.38 0.66, P

Uterine sarcoma (US) is a highly malignant cancer with poor prognosis and high mortality. This study focused on the identification of a RNA-Seq expression signature for prognosis prediction in uterine sarcoma.We obtained RNA-Seq expression profiles from The Cancer Genome Atlas database, and differentially expressed genes were identified between US tissues and normal tissues. Univariate Cox proportional hazards regression analysis and LASSO Cox model were performed to identify and construct the prognostic gene signature. Time-dependent receiver operating characteristic, Kaplan-Meier curve and multivariate Cox regression analysis were used to assess the prognostic capacity of the six-gene signature. The nomogram was developed including prognostic signature and independent clinical factors to predict the overall survival (OS) of US patients. The functional enrichment and somatic mutation analysis were also analyzed by bioinformatics to understand the molecular mechanisms.This study identified a prognostic signature based on 6 genes: FGF23, TLX2, TIFAB, RNF223, HIST1H3A and AADACL4. In the training group, the median OS in the high- and low-risk groups was 19.6 vs 88.1 months (HR, 0.1412, 95% CI: 0.03295 - 0.6054; P = 0.002), respectively. In the testing group, the median OS in the high- and low-risk groups were 30 vs NR (not reach) months (HR,0.0001, 95% CI: 0 - inf; P = 0.03). In all of patients, the low-risk group showed significant better survival compared with the high-risk group in OS, PFI, DSS and DFI. The nomogram based on the gene signature and radiation therapy was developed and successfully predicted the OS of US patients. The patients in the high-risk group displayed distinct mutation signatures comparing to patients in the low-risk group. Functional enrichment analysis indicated that the signature can play a vital role in cancer-related biological processes.Our study established a novel 6-gene signature and nomogram which could improve prognosis prediction in patients with US.

We performed a pooled analysis to evaluate the efficacy and adverse events (AEs) of olanzapine combined with dexamethasone plus 5-hydroxytryptamine type 3 receptor antagonist (5-HT3 RA) compared with 5-HT3 RA plus dexamethasone for the prevention and treatment of chemotherapy-induced nausea and vomiting (CINV) in high and moderate emetogenic chemotherapy based on randomised controlled trials (RCTs). PubMed, EMBASE, Web of Science, the Cochrane Library, China Biomedical Literature database (CBM), WanFang Database, China National Knowledge Infrastructure (CNKI), and Chinese Science and Technology Periodical Database (VIP) (from their inception to April 2019) were searched to capture relevant articles. Relative risk with 95% confidence intervals for CINV and AEs were all extracted or calculated. Eleven studies with 1107 cancer patients were involved in this review. The pooled RR of delayed CINV (RR 0.50, 95% CI 0.38 to 0.66; p

Introduction: Dysregulated genes play a critical role in the development and progression of cancer, suggesting their potential as novel independent biomarkers for cancer diagnosis and prognosis. Prognostic model-based gene expression profiles are not widely utilized in clinical medicine. We investigated the prognostic significance of an expression profile-based gene signature for outcome prediction in patients with malignant pleural mesothelioma (MPM). Methods: The gene expression profiles of a large cohort of patients with MPM were obtained and analyzed by repurposing publicly available microarray data. A gene-based risk score model was developed with the training dataset and then validated with the TCGA-MESO (mesothelioma) dataset. The time-dependent receiver operating characteristic (ROC) curve was used to evaluate the prognostic performance of survival prediction. The biological function of the prognostic genes was predicted using bioinformatics analysis. Results: Three genes in the training dataset ({"type":"entrez-geo","attrs":{"text":"GSE2549","term_id":"2549"}}GSE2549) were identified as significantly associated with the overall survival (OS) of patients with MPM and were combined to develop a three-gene prognostic signature to stratify patients into low-risk and high-risk groups. The MPM patients of the training dataset in the low-risk group exhibited longer OS than those in the high-risk group (HR = 0.25, 95% CI = 0.11–0.56, P < 0.001). Similar prognostic values for the three-gene signature were observed in the validated TCGA-MESO cohort (HR = 0.53 95% CI = 0.33–0.85, P = 0.008). ROC analysis also demonstrated the good performance in predicting 3-year OS in the GEO and TCGA cohorts (KM-AUC for GEO = 0.989, KM-AUC for TCGA = 0.618). The C-statistic for the 3-gene model was 0.761. Validation with TCGA-MESO confirmed the model's ability to discriminate between risk groups in an alternative data set with fair performance (C-statistic: 0.68). Functional enrichment analysis suggested that these three genes may be involved in genetic and epigenetic events with known links to MPM. Conclusions: This study has identified and validated a novel 3-gene model to reliably discriminate patients at high and low risk of death in unselected populations of patients with MPM. Further larger, prospective multi-institutional cohort studies are necessary to validate this model.

Background We conducted a review to evaluate the efficacy and adverse events (AEs) of olanzapine combined with 5-hydroxytryptamine type 3 (5-HT3) receptor antagonist (RA) plus dexamethasone compared with 5-HT3 RA plus dexamethasone for the prevention and treatment of chemotherapyinduced nausea and vomiting (CINV) in high and moderate emetogenic chemotherapy based on randomized controlled trials (RCTs). Methods PubMed, Web of Science, EMBASE, and The Cochrane Library, WanFang Database, China Biomedical Literature database (CBM), China National Knowledge Infrastructure (CNKI), and Chinese Science and Technology Periodical Database (VIP) (inception to April 2019) were searched to recognize relevant articles. Relative risk (RR) with 95% confidence intervals (CIs) for CINV and AEs were all extracted. Results 11 studies with 1107 cancer patients were involved in this review. The pooled RR of any level acute CINV (RR = 0.60, 95%CI: 0.48–0.75, Z=-4.57, P Conclusions Olanzapine significantly decreased the occurrence of moderate-severe CINV (CINV III and IV) and insomnia for the prevention and treatment of CINV in high and moderately emetogenic chemotherapy. Compared with 10mg per day, 5mg oral may be more appropriate for cancer patients. Legal entity responsible for the study The authors. Funding Has not received any funding. Disclosure All authors have declared no conflicts of interest.

Background Radiation therapy (RT) is not a standard treatment for ovarian cancer (OC). However, it can be used as an adjunctive therapy to control the local recurrent disease. We aimed to investigate whether OC patients could benefit from RT. Methods From 2004 to 2013, the incidence, survival, treatment, and end results data from the SEER were analyzed for cases diagnosed with OC. We examined cause-specific survival (CSS) and overall survival (OS) with 95% confidence intervals (CIs) to estimate the effect of RT from multivariate Cox regression analysis. Performed propensity score matching (PSM) method was used for OC patients who received radiotherapy versus those who did not. Results A total of 11140 cases were enrolled for analysis. The aggregated HR of univariate survival analysis suggested that radiotherapy had unfavorable effects on overall survival (HR 1.315, 95% CI 0.994–1.739, P = 0.055) and cancer-specific survival (HR 1.732, 95% CI 1.285–2.334, P Conclusions In OC patients, RT does not have a proven benefit on CSS and OS overall, and it is especially not suitable for early-stage patients and non-epithelial OC patients. However, further confirmation is needed from well-designed and large-scale RCTs in the future to identify its effect in certain types of epithelial OC patients after the developed techniques. Legal entity responsible for the study The authors. Funding Has not received any funding. Disclosure All authors have declared no conflicts of interest.

Background: Many primary and secondary studies reported the association between Toll-like receptor 4 (TLR4) polymorphism and periodontitis susceptibility, which mainly focused on TLR4–299A>G or TLR4–399C>T of Caucasian, however, these studies had different conclusions. The aim of this study was to reassess relative studies about TLR4 polymorphism and periodontitis susceptibility, and update meta-analysis. Methods: We searched the electronic database including CNKI (Chinese National Knowledge Infrastructure), PubMed, Embase, and hand searched relative studies until January 4, 2016. Two authors selected studies according to inclusion and exclusion criteria, assessed studies using Newcastle-Ottawa Scale case control study (NOS), and calculated the combined effect size using STATA software, version 12.0. Results: This meta-analysis included 18 studies, containing 2453 healthy participants and 2987 patients with chronic periodontitis (CP) and 462 patients with aggressive periodontitis (AP). There was a significance between TLR4C>G (rs7873784) allele and CP in Asian, and its recessive model was also significant (for C vs G: odds ratio [OR] = 0.72, 95% confidence interval [CI] = 0.54–0.95, I2 = 0%; for CC + CG vs GG: OR = 0.66, 95% CI = 0.49–0.89, I2 = 0%). However, we did not detect any significant relevance between other TLR4 polymorphism and periodontitis susceptibility in overall and subgroup analyses. The sensitive analysis showed that dropping any single studies did not affect the pooled-analysis results. Publication bias was not detected. Conclusions: The meta-analysis found association between TLR4C>G (rs7873784) allele and CP in Asian and it may passed on to offsprings in the form of recessiveness. However, further studies about the association between TLR4C>G (rs7873784) and CP is warranted to confirm.

// Hu Ma 1, * , Wen-Xiu Yao 2, * , Lang Huang 1, * , Su-Han Jin 3 , Da-Hai Liu 1 , Yuan Liu 4 , Xu Tian 5 , Jin-Hui Tian 6 , Jian-Guo Zhou 1 1 Department of Oncology, Affiliated Hospital of Zunyi Medical University, Zunyi 563000, China 2 Department of Oncology, Affiliated Cancer Hospital of Medical School, University of Electronic Science and Technology of China, Sichuan Cancer Hospital and Institute & Cancer, The Second People’s Hospital of Sichuan Province, Chengdu, 610000, China 3 Affiliated Stemmatological Hospital of Zunyi Medical University, Zunyi 563000, China 4 Department of Pharmacology and Key Laboratory of Basic Pharmacology of Ministry of Education, Zunyi Medical University, Zunyi 563000, China 5 Chongqing Cancer Hospital and Institute, Chongqing, 40030, China 6 Evidence-Based Medicine Center of Lanzhou University, Lanzhou, 730000, China * These authors have contributed equally to this work Correspondence to: Jian-Guo Zhou, email: jianguo.zhou@yahoo.com Keywords: NSCLC, D5F3, ALK, diagnostic accuracy, meta-analysis Received: June 06, 2016 Accepted: August 13, 2016 Published: September 01, 2016 ABSTRACT We conducted a pooled analysis comparing the efficacy of an immunohistochemistry (IHC) assay using the D5F3 antibody with that of fluorescence in situ hybridization (FISH) for detecting ALK gene rearrangement in NSCLC patients. A total of 32 studies involving 5805 samples were included in this review. Pooled sensitivity for D5F3 IHC was 0.97 (95%CI: 0.93-0.98), specificity was 0.99 (95%CI: 0.98-1.00), PLR was 119.20 (95%CI: 57.79-245.89), NLR was 0.03 (95%CI: 0.02-0.07), DOR was 3526.66 (95%CI: 1344.71-9249.03), and AUROC was 1.00 (95%CI: 0.99-1.00). Meta-regression revealed that specimen type was a source of heterogeneity for specificity, and specimen type and FISH signal distance were sources of heterogeneity in the joint model. Subgroup analysis revealed that sensitivity and specificity were higher when the FISH signal distance standard was ≥ 2 than when it was ≥ 1. Sensitivity was higher for tumor specimens than for cell specimens; specificity was higher for cell specimens than for tumor specimens. In conclusion, the D5F3 IHC assay was nearly as effective as FISH for detection of ALK gene rearrangement in NSCLC patients.

Context Opioid-induced constipation (OIC) is one of the most frequent and severe adverse events (AEs) after treatment with opioids. Recent studies have indicated that fixed-ratio combination prolonged-release oxycodone/naloxone (OXN PR) could decrease OIC with similar pain relief compared with other opioids. Objectives We systematically reviewed (PROSPERO registration numbers: CRD42016036244) the constipation relief of OXN PR compared with other opioids regardless of formulation, prolonged release, or extended release used for the relief of chronic pain. Methods Relevant studies were identified by searching PubMed, EMBASE, Web of Science, and the Cochrane library from inception to May 2016, with an update to December 2016. We quantitatively analyzed OIC (assessed by bowel function index [BFI]), pain intensity, and AEs. Results A total of 167 articles were identified from the databases. Finally seven studies with 3217 patients were included in our meta-analysis, including 1322 patients in OXN PR treatment groups and 1885 patients in prolonged-release oxycodone (OXY PR) or prolonged-release morphine (MOR PR) control group. The relative risk (RR) of OIC was decreased in OXN PR (RR 0.52, 95% CI 0.44; 0.62). Whether BFI was better or worse at baseline, the mean difference (MD) of BFI −17.48 95% CI −21.60; −13.36) was better after treatment with OXN PR with clinical importance at the end of intervention; moreover, the BFI of the OXN PR-treated group was closer to normal BFI scores. However, clinical BFI change from baseline to the end measurement only existed in patients when the baseline BFI was high (mean [SDs] 61.0 [23.39]–67.40 [19.51]), and the MD of the BFI was −15.96 (95% CI −25.56; −15.48). The RR of AEs was also smaller (RR 0.80; 95% CI 0.69–0.93), but the severity or duration of AEs was not reported. Pain intensity was also significantly decreased in the OXN PR treatment groups (MD −3.84, 95% CI −7.14; −0.55), although there was no clinically meaningful difference. Conclusion For people with chronic pain, treatment with OXN PR decreases the incidence of OIC and provides intermediate-term bowel function improvement with clinical importance; in addition, pain relief is not weakened. The OIC after treatment with OXN PR for cancer-related pain and over the long term remains unknown.

The adverse events (AEs) of oxycodone in cancer-related pain were controversial, so we conducted a meta-analysis to determine it. PubMed, Embase, CBM, CNKI, WanFang database, The Cochrane library, Web of Science, and the reference of included studies were searched to recognize pertinent studies. Relative risk (RR) with 95% confidence intervals (CIs) for all AEs were all extracted. The fixed-effects model was used to calculate pooled RRs and 95% CIs. Power calculation was performed using macro embedded in SAS software after all syntheses were completed. We identified 11 eligible trials involving 1211 patients: 604 patients included in oxycodone group and 607 patients involved in control group. Our quantitative analysis included 8 AEs, and the pooled analyses indicated that oxycodone compared with other opioids in cancer-related pain were not significantly decreased RRs of all AEs (dizziness RR = 0.94, 95% CI: 0.69–1.30, Z = 0.35, P = 0.72; nausea RR = 0.88, 95% CI: 0.72–1.07, Z = 1.26, P = 0.21; vomiting RR = 0.89, 95% CI: 0.70–1.15, Z = 0.9, P = 0.37; sleepiness RR = 0.86, 95% CI: 0.38–1.36, Z = 0.36, P = 0.72; constipation RR = 0.98, 95% CI: 0.81–1.19, Z = 0.21, P = 0.83; anorexia RR = 0.97, 95% CI = 0.58–1.62, Z = 0.11, P = 0.91; pruritus RR = 0.76, 95% CI: 0.44–1.30, Z = 1.01, P = 0.31; dysuria RR = 0.33, 95% CI: 0.07–1.62, Z = 1.36, P = 0.1)]. The subgroup analysis shown that Ox controlled-release (CR) had less sleepiness compared with MS-contin (Mc) CR (RR = 0.47, 95% CI: 0.25–0.90, P = 0.02). The power analysis suggests that all AEs have low statistical power. The present meta-analysis detected that no statistically significant difference were found among oxycodone and other opioids in all AEs, but Ox CR may had less sleepiness compared with Mc CR when subgroup analysis were conducted.