SummaryBackgroundGlobal inequalities in access to health care are reflected in differences in cancer survival. The CONCORD programme was designed to assess worldwide differences and trends in population-based cancer survival. In this population-based study, we aimed to estimate survival inequalities globally for several subtypes of childhood leukaemia.MethodsCancer registries participating in CONCORD were asked to submit tumour registrations for all children aged 0–14 years who were diagnosed with leukaemia between Jan 1, 1995, and Dec 31, 2009, and followed up until Dec 31, 2009. Haematological malignancies were defined by morphology codes in the International Classification of Diseases for Oncology, third revision. We excluded data from registries from which the data were judged to be less reliable, or included only lymphomas, and data from countries in which data for fewer than ten children were available for analysis. We also excluded records because of a missing date of birth, diagnosis, or last known vital status. We estimated 5-year net survival (ie, the probability of surviving at least 5 years after diagnosis, after controlling for deaths from other causes [background mortality]) for children by calendar period of diagnosis (1995–99, 2000–04, and 2005–09), sex, and age at diagnosis (<1, 1–4, 5–9, and 10–14 years, inclusive) using appropriate life tables. We estimated age-standardised net survival for international comparison of survival trends for precursor-cell acute lymphoblastic leukaemia (ALL) and acute myeloid leukaemia (AML).FindingsWe analysed data from 89 828 children from 198 registries in 53 countries. During 1995–99, 5-year age-standardised net survival for all lymphoid leukaemias combined ranged from 10·6% (95% CI 3·1–18·2) in the Chinese registries to 86·8% (81·6–92·0) in Austria. International differences in 5-year survival for childhood leukaemia were still large as recently as 2005–09, when age-standardised survival for lymphoid leukaemias ranged from 52·4% (95% CI 42·8–61·9) in Cali, Colombia, to 91·6% (89·5–93·6) in the German registries, and for AML ranged from 33·3% (18·9–47·7) in Bulgaria to 78·2% (72·0–84·3) in German registries. Survival from precursor-cell ALL was very close to that of all lymphoid leukaemias combined, with similar variation. In most countries, survival from AML improved more than survival from ALL between 2000–04 and 2005–09. Survival for each type of leukaemia varied markedly with age: survival was highest for children aged 1–4 and 5–9 years, and lowest for infants (younger than 1 year). There was no systematic difference in survival between boys and girls.InterpretationGlobal inequalities in survival from childhood leukaemia have narrowed with time but remain very wide for both ALL and AML. These results provide useful information for health policy makers on the effectiveness of health-care systems and for cancer policy makers to reduce inequalities in childhood cancer survival.FundingCanadian Partnership Against Cancer, Cancer Focus Northern Ireland, Cancer In...
The distribution of ovarian cancer histology varies widely worldwide. Type I epithelial, germ cell and sex cord-stromal tumours are generally associated with higher survival than type II tumours, so the proportion of these tumours may influence survival estimates for all ovarian cancers combined. The distribution of histological groups should be considered when comparing survival between countries and regions.
Background With characteristic self-renewal and multipotent differentiation, cancer stem cells (CSCs) have a crucial influence on the metastasis, relapse and drug resistance of gastric cancer (GC). However, the genes that participates in the stemness of GC stem cells have not been identified. Methods The mRNA expression-based stemness index (mRNAsi) was analyzed with differential expressions in GC. The weighted gene co-expression network analysis (WGCNA) was utilized to build a co-expression network targeting differentially expressed genes (DEG) and discover mRNAsi-related modules and genes. We assessed the association between the key genes at both the transcription and protein level. Gene Expression Omnibus (GEO) database was used to validate the expression levels of the key genes. The risk model was established according to the least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Furthermore, we determined the prognostic value of the model by employing Kaplan-Meier (KM) plus multivariate Cox analysis. Results GC tissues exhibited a substantially higher mRNAsi relative to the healthy non-tumor tissues. Based on WGCNA, 17 key genes (ARHGAP11A, BUB1, BUB1B, C1orf112, CENPF, KIF14, KIF15, KIF18B, KIF4A, NCAPH, PLK4, RACGAP1, RAD54L, SGO2, TPX2, TTK, and XRCC2) were identified. These key genes were clearly overexpressed in GC and validated in the GEO database. The protein-protein interaction (PPI) network as assessed by STRING indicated that the key genes were tightly connected. After LASSO analysis, a nine-gene risk model (BUB1B, NCAPH, KIF15, RAD54L, KIF18B, KIF4A, TTK, SGO2, C1orf112) was constructed. The overall survival in the high-risk group was relatively poor. The area under curve (AUC) of risk score was higher compared to that of clinicopathological characteristics. According to the multivariate Cox analysis, the nine-gene risk model was a predictor of disease outcomes in GC patients (HR, 7.606; 95% CI, 3.037–19.051; P < 0.001). We constructed a prognostic nomogram with well−fitted calibration curve based on risk score and clinical data. Conclusion The 17 mRNAsi-related key genes identified in this study could be potential treatment targets in GC treatment, considering that they can inhibit the stemness properties. The nine-gene risk model can be employed to predict the disease outcomes of the patients.
Background: Lumican (LUM) is a member of the small leucine-rich proteoglycan family and plays dual roles as an oncogene and a tumor suppressor gene. The effect of LUM on tumors is still controversial. Methods: Gene expression profiles and clinical data of gastric cancer (GC) were downloaded from The Cancer Genome Atlas (TCGA) database. The expression difference of LUM in GC tissues and adjacent nontumor tissues was analyzed by R software and verified by quantitative real-time polymerase chain reaction (qRT-PCR) and comprehensive meta-analysis. The relationship between LUM expression and clinicopathological parameters was assessed by chi-square test and logistic regression. Kaplan-Meier survival analysis and Cox proportional hazards regression model were chosen to assess the effect of LUM expression on survival. Gene set enrichment analysis (GSEA) was used to screen the signaling pathways involved in GC between the low and the high LUM expression datasets. Results: The expression of LUM in GC tissues was significantly higher than that in adjacent nontumor tissues (P < 0.001) from the TCGA database. qRT-PCR (P = 0.022) and comprehensive meta-analysis (standard mean difference = 0.90, 95% CI: 0.34-1.46) demonstrated that LUM was upregulated in GC. The chi-square test showed that the high expression of LUM was correlated with tumor differentiation (P = 0.024) and T stage (P = 0.004). Logistic regression analysis showed that high LUM expression was significantly correlated with tumor differentiation (OR = 1.543 for poor vs. well or moderate, P = 0.043), pathological stage (OR = 3.149 for stage II vs. stage I, P = 0.001; OR = 2.505 for stage III vs. stage I, P = 0.007), and T classification (OR = 13.304 for T2 vs. T1, P = 0.014; OR = 18.434 for T3 vs. T1, P = 0.005; OR = 30.649 for T4 vs. T1, P = 0.001). The Kaplan-Meier curves suggested that patients with high LUM expression had a poor prognosis. Multivariate analysis showed that a high expression of LUM was an important independent predictor of poor overall survival (HR, 1.189; 95% CI, 1.011-1.400; P = 0.037). GSEA indicated that 14 signaling pathways were evidently enriched in samples with the high-LUM expression phenotype. Conclusions: LUM might act as an oncogene in the progression of GC and could be regarded as a potential prognostic indicator and therapeutic target for GC.
Environmental health in subway stations, a typical type of urban underground space, is becoming increasingly important. Ventilation is the principal measure for optimizing the complex physical environment in a subway station. This paper narratively reviews the environmental and health effects of subway ventilation and discusses the relevant engineering, environmental, and medical aspects in combination. Ventilation exerts a notable dual effect on environmental health in a subway station. On the one hand, ventilation controls temperature, humidity, and indoor air quality to ensure human comfort and health. On the other hand, ventilation also carries the potential risks of spreading air pollutants or fire smoke through the complex wind environment as well as produces continuous noise. Assessment and management of health risks associated with subway ventilation is essential to attain a healthy subway environment. This, however, requires exposure, threshold data, and thereby necessitates more research into long-term effects, and toxicity as well as epidemiological studies. Additionally, more research is needed to further examine the design and maintenance of ventilation systems. An understanding of the pathogenic mechanisms and aerodynamic characteristics of various pollutants can help formulate ventilation strategies to reduce pollutant concentrations. Moreover, current comprehensive underground space development affords a possibility for creating flexible spaces that optimize ventilation efficiency, acoustic comfort, and space perception.
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