Prognostic Indicators for Ebola Patient Survival.
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ABSTRACT:
SUBMITTER: Crowe SJ
PROVIDER: S-EPMC4734506 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BACKGROUND:Tracheotomy, through its ability to wean patients off ventilation, can shorten ICU length of stay and in doing so increase ICU bed capacity, crucial for saving lives during the COVID-19 pandemic. To date, there is a paucity of patient selection criteria and prognosticators to facilitate decision making and enhance precious ICU capacity. METHODS:Prospective study of COVID-19 patients undergoing tracheotomy (n = 12) over a 4-week period (March-April 2020). Association between preoperative and postoperative ventilation requirements and outcomes (ICU stay, time to decannulation, and death) were examined. RESULTS:Patients who sustained FiO2 ???50% and PEEP???8 cm H2 O in the 24?hours pretracheotomy exhibited a favorable outcome. Those whose requirements remained below these thresholds post-tracheotomy could be safely stepped down after 48?hours. CONCLUSION:Sustained FiO2 ???50% and PEEP???8 cm H2 O in the 48?hours post-tracheotomy are strong predictive factors for a good outcome, raising the potential for these patients to be stepped down early, thus increasing ICU capacity.
| S-EPMC7280616 | biostudies-literature
Project description:Although 20% to 30% of melanomas are histopathologically 'nevus associated,' the majority of melanomas arise de novo, ie, in clinically normal skin with no associated nevus. We examined whether these forms of melanoma differed in their associations with clinical and histopathologic features and patient survival.We analyzed two prospective cohorts from our institution with protocol-driven follow-up information (NYU1, n?=?1024; NYU2, n?=?1125). We used univariate and multivariable analyses to examine associations between de novo vs nevus-associated melanoma classification and age, anatomic site, tumor thickness, tumor ulceration, mitotic index, histological subtype, clinical stage, and survival. We tested the associations identified in NYU1 using NYU2 as a replication cohort. All tests of statistical significance were two-sided.In NYU1, de novo melanomas were associated with tumor thickness greater than 1.0?mm (odds ratio [OR] = 1.96, 95% confidence interval [CI] = 1.43 to 2.70, P < .001), ulceration (OR?=?1.65, 95% CI?=?1.10 to 2.54, P = .02), nodular subtype (OR?=?3.26, 95% CI?=?1.70 to 7.11, P = .001), greater than stage I (OR?=?2.35, 95% CI?=?1.65 to 3.40, P < .001), older age (OR?=?1.64, 95% CI?=?1.18 to 2.30, P = .004), and shorter overall survival (HR?=?1.63, 95% CI?=?1.22 to 2.18, P < .001). In NYU2, de novo melanoma was again statistically significantly associated with thickness greater than 1.0?mm (OR?=?2.24, 95% CI?=?1.72 to 2.93, P < .001), ulceration (OR?=?2.88, 95% CI?=?1.95 to 4.37, P < .001), nodular subtype (OR?=?2.41, 95% CI?=?1.75 to 3.37, P < .001), greater than stage I (OR?=?2.42, 95% CI?=?1.80 to 3.29, P < .001), older age (OR?=?1.68, 95% CI?=?1.31 to 2.17, P < .001), and shorter overall survival (HR?=?2.52, 95% CI?=?1.78 to 3.56, P < .001). In multivariable analysis, de novo classification was an independent, poor prognostic indicator in NYU2 (HR?=?1.70, 95% CI?=?1.19 to 2.44, P = .004). Male patients had a statistically significantly worse survival than female patients if their melanoma was de novo (NYU1, P < .001; NYU2, P < .001); unexpectedly, there was no sex difference in survival among patients with nevus-associated tumors.These data suggest that de novo melanomas are more aggressive than nevus-associated melanomas. This classification scheme may also provide a useful framework for investigations into sex differences in melanoma outcomes.
| S-EPMC5939856 | biostudies-other
Project description:BackgroundThe recent Ebola virus disease (EVD) outbreak in West Africa has spread wider than any previous human EVD epidemic. While individual-level risk factors that contribute to the spread of EVD have been studied, the population-level attributes of subnational regions associated with outbreak severity have not yet been considered.MethodsTo investigate the area-level predictors of EVD dynamics, we integrated time series data on cumulative reported cases of EVD from the World Health Organization and covariate data from the Demographic and Health Surveys. We first estimated the early growth rates of epidemics in each second-level administrative district (ADM2) in Guinea, Sierra Leone and Liberia using exponential, logistic and polynomial growth models. We then evaluated how these growth rates, as well as epidemic size within ADM2s, were ecologically associated with several demographic and socio-economic characteristics of the ADM2, using bivariate correlations and multivariable regression models.ResultsThe polynomial growth model appeared to best fit the ADM2 epidemic curves, displaying the lowest residual standard error. Each outcome was associated with various regional characteristics in bivariate models, however in stepwise multivariable models only mean education levels were consistently associated with a worse local epidemic.DiscussionBy combining two common methods-estimation of epidemic parameters using mathematical models, and estimation of associations using ecological regression models-we identified some factors predicting rapid and severe EVD epidemics in West African subnational regions. While care should be taken interpreting such results as anything more than correlational, we suggest that our approach of using data sources that were publicly available in advance of the epidemic or in real-time provides an analytic framework that may assist countries in understanding the dynamics of future outbreaks as they occur.
| S-EPMC5061396 | biostudies-literature
Project description:Outcome in melanoma patients with advanced disease is poor and systemic treatment seems to benefit only a subset of patients. Predictive markers identifying these patients are currently not available. Early studies showed an association of immune-related side effects such as vitiligo and autoimmune thyroiditis with response to IL-2 or IFNα treatment. However, conflicting data have been reported as well, mentioning the effect of a higher rate of immune-related toxicities during prolonged administration of the drug in responders. The review discusses the prognostic significance of autoimmunity during various forms of immunotherapy and stresses the importance of correcting for guarantee-time bias. In addition, other immune-related factors which have been associated with melanoma prognosis such as, CRP, white blood cell count, absolute lymphocyte count and human leukocyte antigen will be reviewed as well. A better understanding of the immune system and the host-tumor interactions should ultimately lead to more effective treatment. A major challenge expected to be addressed in future is proving ways to uncouple tumor immunity from autoimmunity.
| S-EPMC5528285 | biostudies-other
Project description:Background: Long noncoding RNAs (lncRNAs) are pervasively transcribed and play a key role in tumorigenesis. The aim of the present study was to determine the lncRNA expression profile in astrocytoma patients and to assess the potential clinical value of the findings. Methods: The global lncRNA expression profile in astrocytoma was measured by lncRNA microarray. Next, the differentially expressed lncRNAs were validated using a Taqman probe-based quantitative real time-PCR (qRT-PCR) assay in 130 astrocytoma and 60 normal adjacent tissue (NAT) samples, which were randomly divided into a training set and a validation set. Finally, the correlation of the lncRNA levels with survival of the astrocytoma patients was estimated by performing a Kaplan-Meier survival analysis and a univariate/multivariate Cox proportional hazard regression analysis. Results: After a two-phase selection and validation process, 7 lncRNAs were found to have a significantly different expression profile in astrocytoma samples compared to the NAT samples. Unsupervised clustering analysis further revealed the potential of the 7-lncRNA profile to differentiate between tumors and NAT samples. Using Kaplan-Meier survival analysis, we found that the low expression of XLOC_005285 and XLOC_010967 and the high expression of HIT000260843.11 were significantly associated with poor patient survival. Moreover, Cox proportional hazard regression analysis revealed that this prognostic impact was independent of other clinicopathological factors. The lncRNA expression profiles of 3 astrocytoma tissues and 3 normal adjacent tissues were studied by microarray.
2014-06-07 | E-GEOD-58276 | biostudies-arrayexpress
Project description:Background: Long noncoding RNAs (lncRNAs) are pervasively transcribed and play a key role in tumorigenesis. The aim of the present study was to determine the lncRNA expression profile in astrocytoma patients and to assess the potential clinical value of the findings. Methods: The global lncRNA expression profile in astrocytoma was measured by lncRNA microarray. Next, the differentially expressed lncRNAs were validated using a Taqman probe-based quantitative real time-PCR (qRT-PCR) assay in 130 astrocytoma and 60 normal adjacent tissue (NAT) samples, which were randomly divided into a training set and a validation set. Finally, the correlation of the lncRNA levels with survival of the astrocytoma patients was estimated by performing a Kaplan-Meier survival analysis and a univariate/multivariate Cox proportional hazard regression analysis. Results: After a two-phase selection and validation process, 7 lncRNAs were found to have a significantly different expression profile in astrocytoma samples compared to the NAT samples. Unsupervised clustering analysis further revealed the potential of the 7-lncRNA profile to differentiate between tumors and NAT samples. Using Kaplan-Meier survival analysis, we found that the low expression of XLOC_005285 and XLOC_010967 and the high expression of HIT000260843.11 were significantly associated with poor patient survival. Moreover, Cox proportional hazard regression analysis revealed that this prognostic impact was independent of other clinicopathological factors.
2014-06-07 | GSE58276 | GEO
Project description:Breast cancer remains the leading cause of cancer-related mortality in women. Comprehensive genomics, proteomics, and metabolomics studies are emerging that offer an opportunity to model disease biology, prognosis, and response to specific therapies. Although many biomarkers have been identified through advances in data mining techniques, few have been applied broadly to make patient-specific decisions. Here, we review a selection of breast cancer prognostic indicators and their implications. Our goal is to provide clinicians with a general evaluation of emerging computational methodologies for outcome prediction.
| S-EPMC4103923 | biostudies-literature
Project description:We aimed to report patients' survival after surgical resection of eSCC and to ascertain the clinical, imaging, and pathological factors related to patient prognosis. This retrospective study included 435 patients with eSCC of <stage T2 (median follow-up period, 49.3 months). A total of 103 (23.7%) patients died, and 89 (20.5%) experienced recurrence during follow-up. The maximum standardized uptake value (SUVmax) on positron emission tomography (PET)/computed tomography (CT) of the primary tumor was significantly correlated with tumor length, nodal metastasis, and pathologic T stage in a positive linear fashion. In the multivariate analysis, higher SUVmax on PET/CT was a negative prognostic factor for both disease-free survival (DFS) and overall survival (OS). Contrarily, the presence of nodal metastasis was a prognostic factor only for DFS, and pathologic T stage only for OS. By applying SUVmax cut-off, both DFS and OS were significantly different among three groups when divided by cut-off values (A: SUVmax ? 3.05, B: SUVmax 3.06 - 5.64, C: SUVmax ? 5.65). In patients with a surgically resectable eSCC, measuring the SUVmax of the primary tumor during PET/CT can help predict patient survival. Additionally, PET/CT renders triage criterion for endoscopic submucosal dissection (ESD; T1a cancer and SUVmax, ?3.05).
| S-EPMC7081270 | biostudies-literature
Project description:BackgroundGiven the vast range of molecular mechanisms giving rise to breast cancer, it is unlikely universal cures exist. However, by providing a more precise prognosis for breast cancer patients through integrative models, treatments can become more individualized, resulting in more successful outcomes. Specifically, we combine gene expression, pseudogene expression, miRNA expression, clinical factors, and pseudogene-gene functional networks to generate these models for breast cancer prognostics. Establishing a LASSO-generated molecular gene signature revealed that the increased expression of genes STXBP5, GALP and LOC387646 indicate a poor prognosis for a breast cancer patient. We also found that increased CTSLP8 and RPS10P20 and decreased HLA-K pseudogene expression indicate poor prognosis for a patient. Perhaps most importantly we identified a pseudogene-gene interaction, GPS2-GPS2P1 (improved prognosis) that is prognostic where neither the gene nor pseudogene alone is prognostic of survival. Besides, miR-3923 was predicted to target GPS2 using miRanda, PicTar, and TargetScan, which imply modules of gene-pseudogene-miRNAs that are potentially functionally related to patient survival.ResultsIn our LASSO-based model, we take into account features including pseudogenes, genes and candidate pseudogene-gene interactions. Key biomarkers were identified from the features. The identification of key biomarkers in combination with significant clinical factors (such as stage and radiation therapy status) should be considered as well, enabling a specific prognostic prediction and future treatment plan for an individual patient. Here we used our PseudoFuN web application to identify the candidate pseudogene-gene interactions as candidate features in our integrative models. We further identified potential miRNAs targeting those features in our models using PseudoFuN as well. From this study, we present an interpretable survival model based on LASSO and decision trees, we also provide a novel feature set which includes pseudogene-gene interaction terms that have been ignored by previous prognostic models. We find that some interaction terms for pseudogenes and genes are significantly prognostic of survival. These interactions are cross-over interactions, where the impact of the gene expression on survival changes with pseudogene expression and vice versa. These may imply more complicated regulation mechanisms than previously understood.ConclusionsWe recommend these novel feature sets be considered when training other types of prognostic models as well, which may provide more comprehensive insights into personalized treatment decisions.
| S-EPMC7118805 | biostudies-literature
Project description:ObjectivesAccumulating evidence suggests that long non-coding RNA (lncRNA) may affect hepatocellular carcinoma (HCC) progression. However, the mechanism remains unclear. Previous studies have shown that exosomes may promote tumor progression by transporting proteins. Our study aimed to determine the prognostic value of lncRNAs in HCC and the underlying mechanism.MethodsA dataset comprising a HCC cohort of 364 patients from The Cancer Genome Atlas (TCGA) was analyzed to identify lncRNAs with prognostic value. Co-expression and competing endogenous RNA (ceRNA) networks were constructed to investigate the mechanism of exosome-related lncRNAs. To confirm the bioinformatics analysis results, 95 pairs of clinical samples were evaluated by digoxigenin-labeled chromogenic in situ hybridization (CISH).ResultsFive lncRNAs (CTD-2116N20.1, AC012074.2, RP11-538D16.2, LINC00501 and RP11-136I14.5) with significant differences were identified (P<0.001). A prognostic nomogram was constructed with a C-index of 0.701. The co-expression and ceRNA networks showed possible mechanisms for CTD-2116N20.1 and RP11-538D16.2. The CISH results confirmed that CTD-2116N20.1 and RP11-538D16.2 were correlated with a poor prognosis for HCC patients.ConclusionOur findings provide an independent and effective prognostic model to predict the survival rate of HCC patients. RP11-538D16.2 and CTD-2116N20.1 are highlighted as important exosome-related lncRNAs.
| S-EPMC6038086 | biostudies-literature