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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| S-EPMC10480158 | 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:BackgroundTracheotomy, 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.MethodsProspective 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.ResultsPatients 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.ConclusionSustained 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:Intravascular lymphoma (IVL) is a rare extranodal non-Hodgkin lymphoma. We performed a retrospective analysis of 55 IVL patients who were treated at our institution 2003-2018. Median age at diagnosis was 68 years, and 64% were males. The most frequent presenting symptoms were skin rash 43% and weight loss 30%. MRI brain on IVL patients with CNS involvement (CNS-IVL) showed multifocal involvement in 76% (13/17). 89% (17/19) of non-CNS-IVL patients with abnormal FDG-PET had biopsy of an avid lesion resulting in definitive diagnosis. The top diagnostic biopsy site was the bone marrow (45%). 56% had multiorgan involvement. Based on CNS involvement, 36.5% (20/55) had CNS-IVL and 63.5% (35/55) had non-CNS-IVL. CNS-IVL group consists of clinically isolated CNS involvement (CNS-only IVL) (22%;12/55) and mixed clinical CNS and peripheral site involvement (M-IVL) (14.5%; 8/55). Non-CNS-IVL group consists of clinically isolated skin involvement (skin-only IVL) (9%; 5/55) and peripheral IVL with or without skin involvement (P-IVL); (54.5%; 30/55). Skin involvement was predominantly in the lower extremities. Pathologically, 89% (48/54) were B-cell IVL. Rituximab + high-dose methotrexate-based regimen were used in 75% (12/16) of CNS-IVL patients and RCHOP in 60% (17/28) of non-CNS-IVL patients. Estimated 5-year progression free survival (PFS) and overall survival (OS) for the entire cohort were 38.6% and 52%, respectively. Skin-only IVL was associated with excellent survival. Platelet count <150x109 /L, age > 60Y, and treatment without Rituximab were poor prognostic factors. Further research is necessary to identify novel therapies.
| S-EPMC9541514 | biostudies-literature
Project description:Treatment decisions in primary myelofibrosis (PMF) are guided by numerous prognostic systems. Patient-specific comorbidities have influence on treatment-related survival and are considered in clinical contexts but have not been routinely incorporated into current prognostic models. We hypothesized that patient-specific comorbidities would inform prognosis and could be incorporated into a quantitative score. All patients with PMF or secondary myelofibrosis with available DNA and comprehensive electronic health record (EHR) data treated at Vanderbilt University Medical Center between 1995 and 2016 were identified within Vanderbilt's Synthetic Derivative and BioVU Biobank. We recapitulated established PMF risk scores (eg, Dynamic International Prognostic Scoring System [DIPSS], DIPSS plus, Genetics-Based Prognostic Scoring System, Mutation-Enhanced International Prognostic Scoring System 70+) and comorbidities through EHR chart extraction and next-generation sequencing on biobanked peripheral blood DNA. The impact of comorbidities was assessed via DIPSS-adjusted overall survival using Bonferroni correction. Comorbidities associated with inferior survival include renal failure/dysfunction (hazard ratio [HR], 4.3; 95% confidence interval [95% CI], 2.1-8.9; P = .0001), intracranial hemorrhage (HR, 28.7; 95% CI, 7.0-116.8; P = 2.83e-06), invasive fungal infection (HR, 41.2; 95% CI, 7.2-235.2; P = 2.90e-05), and chronic encephalopathy (HR, 15.1; 95% CI, 3.8-59.4; P = .0001). The extended DIPSS model including all 4 significant comorbidities showed a significantly higher discriminating power (C-index 0.81; 95% CI, 0.78-0.84) than the original DIPSS model (C-index 0.73; 95% CI, 0.70-0.77). In summary, we repurposed an institutional biobank to identify and risk-classify an uncommon hematologic malignancy by established (eg, DIPSS) and other clinical and pathologic factors (eg, comorbidities) in an unbiased fashion. The inclusion of comorbidities into risk evaluation may augment prognostic capability of future genetics-based scoring systems.
| S-EPMC9989522 | biostudies-literature
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:BackgroundStudies have confirmed the validity of malnutrition/inflammation-based indicators among cancer patients compared to chemotherapy patients. Moreover, it is necessary to identify which indicator is the best prognostic predictor for chemotherapy patients. This study attempted to determine the best nutrition/inflammation-based indicator of overall survival (OS) for chemotherapy patients.MethodsIn this prospective cohort study, we collected 16 nutrition/inflammation-based indicators among 3,833 chemotherapy patients. The maximally selected rank statistics were used to calculate the optimal values of cutoffs for continuous indicators. OS was evaluated using the Kaplan-Meier method. The associations of 16 indicators with survival were evaluated using Cox proportional hazard models. The predictive ability of 16 indicators was assessed via time-dependent receiver operating characteristic curves (time-ROC) and the C-index.ResultsAll indicators were significantly associated with worse OS of chemotherapy patients in the multivariate analyses (all P < 0.05). Time-AUC and C-index analyses indicated that the lymphocyte-to-CRP (LCR) ratio (C-index: 0.658) had the best predictive ability for OS in chemotherapy patients. The tumor stage significantly modified the association between inflammatory status and worse survival outcomes (P for interaction < 0.05). Compared to patients with high LCR and I/II tumor stages, patients with low LCR and III/IV tumor stages had a 6-fold higher risk of death.ConclusionsThe LCR has the best predictive value in chemotherapy patients compared with other nutrition/inflammation-based indicators.Clinical trial registrationhttp://www.chictr.org.cn, identifier ChiCTR1800020329.
| S-EPMC9978470 | biostudies-literature
Project description:Background: Tumor pathology can assess patient prognosis based on a morphological deviation of tumor tissue from normal. Digitizing whole slide images (WSIs) of tissue enables the use of deep learning (DL) techniques in pathology, which may shed light on prognostic indicators of cancers, and avoid biases introduced by human experience. Purpose: We aim to explore new prognostic indicators of ovarian cancer (OC) patients using the DL framework on WSIs, and provide a valuable approach for OC risk stratification. Methods: We obtained the TCGA-OV dataset from the NIH Genomic Data Commons Data Portal database. The preprocessing of the dataset was comprised of three stages: 1) The WSIs and corresponding clinical data were paired and filtered based on a unique patient ID; 2) a weakly-supervised CLAM WSI-analysis tool was exploited to segment regions of interest; 3) the pre-trained model ResNet50 on ImageNet was employed to extract feature tensors. We proposed an attention-based network to predict a hazard score for each case. Furthermore, all cases were divided into a high-risk score group and a low-risk one according to the median as the threshold value. The multi-omics data of OC patients were used to assess the potential applications of the risk score. Finally, a nomogram based on risk scores and age features was established. Results: A total of 90 WSIs were processed, extracted, and fed into the attention-based network. The mean value of the resulting C-index was 0.5789 (0.5096-0.6053), and the resulting p-value was 0.00845. Moreover, the risk score showed a better prediction ability in the HRD + subgroup. Conclusion: Our deep learning framework is a promising method for searching WSIs, and providing a valuable clinical means for prognosis.
| S-EPMC9846244 | biostudies-literature
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