Objective To explore the prognostic value of red cell volume distribution width (RDW) for hematological malignancies. Methods PubMed, Embase, Web of Science, Cochrane Library, China National Knowledge Infrastructure, Wanfang, Chongqing VIP, and SinoMed were searched for related literatures on myelodysplastic syndrome, leukemia and other hematological malignancies and pretreatment RDW from the establishment of databases to April 5, 2022. The main statistical indicators were Hazard ratio (HR) and its 95% confidence interval (CI). Stata 12.0 SE software was used for analysis, and Q test was used to evaluate literature heterogeneity. Subgroup pooled analysis was used to evaluate the prognostic value of RDW. Results A total of 7 articles were included, with a total of 804 patients. A fixed-effect model was selected for meta-analysis, and the results showed that patients with elevated pretreatment RDW had worse overall survival [HR=2.91, 95%CI (2.01, 4.22), I2=0%, P=0.714]. The results of subgroup analysis for different types of diseases showed that in myelodysplastic syndrome group [HR=2.61, 95%CI (1.28, 5.31), I2=22.0%, P=0.258)], chronic myeloid leukemia group [HR= 3.24, 95%CI (1.91, 5.51), I2=0%, P=0.546], and adult T-cell leukemia/lymphoma group [HR=2.64, 95%CI (1.22, 5.70)], the overall survival rate of patients with elevated pretreatment RDW were worse. Sensitivity analysis showed that the study was stable and there was no heterogeneity in the overall study result.Conclusion Elevated pretreatment RDW is associated with overall survival and can be used as an indicator for evaluating the prognosis of hematological malignancies, but large sample studies are still needed to determine the best predictive cutoff for various diseases.
Objective To explore the mode and role of differential expression of circular RNAs (circRNAs) in myelodysplastic syndrome (MDS). Methods We preprocessed and analyzed the circRNA expression profile datasets GSE163386, GSE94591, and GSE81173 in the GEO (Gene Expression Omnibus) database. By using the circBank database and the ENCORI, miRDB, and miRWalk databases to predict microRNAs (miRNAs) that interacted with differentially expressed circRNAs and messenger RNAs (mRNAs), the circRNA-miRNA-mRNA axis was constructed. We retrieved miRNAs related to MDS in PubMed and further obtained competing endogenous RNA (ceRNA) networks related to MDS by taking intersections. Results Through analysis, 128 differentially expressed circRNAs were identified, 48 highly expressed, and 80 low expressed. Among differentially expressed circRNAs with multiple differences>10, 3 were upregulated and 11 were downregulated. Through analysis, 101 differentially expressed mRNA were identified, with 9 upregulated and 92 downregulated. Intersecting with the MDS related miRNAs retrieved by PubMed, we further obtained the MDS related ceRNA network, namely circRNA (has_circ_0061137)-miRNA (has-miR-16-5p)-mRNA (RUBCNL, TBC1D9, SLC16A6) and circRNA (has_circ_0061137)-miRNA (has-miR-125b-5p)-mRNA (CCR5, SLC16A6, IRF4), all of which were downregulated. Conclusion The ceRNA networks revealed in this study may help elucidate the circRNA mechanism in MDS.