177,331 research outputs found
Survival prediction in mesothelioma using a scalable lasso regression model: instructions for use and initial performance using clinical predictors
Introduction: Accurate prognostication is difficult in malignant pleural mesothelioma (MPM). We developed a set of robust computational models to quantify the prognostic value of routinely available clinical data, which form the basis of published MPM prognostic models.
Methods: Data regarding 269 patients with MPM were allocated to balanced training (n=169) and validation sets (n=100). Prognostic signatures (minimal length best performing multivariate trained models) were generated by least absolute shrinkage and selection operator regression for overall survival (OS), OS <6 months and OS <12 months. OS prediction was quantified using Somers DXY statistic, which varies from 0 to 1, with increasing concordance between observed and predicted outcomes. 6-month survival and 12-month survival were described by area under the curve (AUC) scores.
Results: Median OS was 270 (IQR 140–450) days. The primary OS model assigned high weights to four predictors: age, performance status, white cell count and serum albumin, and after cross-validation performed significantly better than would be expected by chance (mean DXY0.332 (±0.019)). However, validation set DXY was only 0.221 (0.0935–0.346), equating to a 22% improvement in survival prediction than would be expected by chance. The 6-month and 12-month OS signatures included the same four predictors, in addition to epithelioid histology plus platelets and epithelioid histology plus C-reactive protein (mean AUC 0.758 (±0.022) and 0.737 (±0.012), respectively). The <6-month OS model demonstrated 74% sensitivity and 68% specificity. The <12-month OS model demonstrated 63% sensitivity and 79% specificity. Model content and performance were generally comparable with previous studies.
Conclusions: The prognostic value of the basic clinical information contained in these, and previously published models, is fundamentally of limited value in accurately predicting MPM prognosis. The methods described are suitable for expansion using emerging predictors, including tumour genomics and volumetric staging
Homogeneous datasets of triple negative breast cancers enable the identification of novel prognostic and predictive signatures
Background: Current prognostic gene signatures for breast cancer mainly reflect proliferation status and have limited value in triple-negative (TNBC) cancers. The identification of prognostic signatures from TNBC cohorts was limited in the past due to small sample sizes.
Methodology/Principal Findings: We assembled all currently publically available TNBC gene expression datasets generated on Affymetrix gene chips. Inter-laboratory variation was minimized by filtering methods for both samples and genes. Supervised analysis was performed to identify prognostic signatures from 394 cases which were subsequently tested on an independent validation cohort (n = 261 cases).
Conclusions/Significance: Using two distinct false discovery rate thresholds, 25% and <3.5%, a larger (n = 264 probesets) and a smaller (n = 26 probesets) prognostic gene sets were identified and used as prognostic predictors. Most of these genes were positively associated with poor prognosis and correlated to metagenes for inflammation and angiogenesis. No correlation to other previously published prognostic signatures (recurrence score, genomic grade index, 70-gene signature, wound response signature, 7-gene immune response module, stroma derived prognostic predictor, and a medullary like signature) was observed. In multivariate analyses in the validation cohort the two signatures showed hazard ratios of 4.03 (95% confidence interval [CI] 1.71–9.48; P = 0.001) and 4.08 (95% CI 1.79–9.28; P = 0.001), respectively. The 10-year event-free survival was 70% for the good risk and 20% for the high risk group. The 26-gene signatures had modest predictive value (AUC = 0.588) to predict response to neoadjuvant chemotherapy, however, the combination of a B-cell metagene with the prognostic signatures increased its response predictive value. We identified a 264-gene prognostic signature for TNBC which is unrelated to previously known prognostic signatures
Neutrophil gelatinase-associated lipocalin (NGAL) predicts response to neoadjuvant chemotherapy and clinical outcome in primary human breast cancer
In our previous work we showed that NGAL, a protein involved in the regulation of proliferation and differentiation, is overexpressed in human breast cancer (BC) and predicts poor prognosis. In neoadjuvant chemotherapy (NACT) pathological complete response (pCR) is a predictor for outcome. The aim of this study was to evaluate NGAL as a predictor of response to NACT and to validate NGAL as a prognostic factor for clinical outcome in patients with primary BC. Immunohistochemistry was performed on tissue microarrays from 652 core biopsies from BC patients, who underwent NACT in the GeparTrio trial. NGAL expression and intensity was evaluated separately. NGAL was detected in 42.2% of the breast carcinomas in the cytoplasm. NGAL expression correlated with negative hormone receptor (HR) status, but not with other baseline parameters. NGAL expression did not correlate with pCR in the full population, however, NGAL expression and staining intensity were significantly associated with higher pCR rates in patients with positive HR status. In addition, strong NGAL expression correlated with higher pCR rates in node negative patients, patients with histological grade 1 or 2 tumors and a tumor size <40 mm. In univariate survival analysis, positive NGAL expression and strong staining intensity correlated with decreased disease-free survival (DFS) in the entire cohort and different subgroups, including HR positive patients. Similar correlations were found for intense staining and decreased overall survival (OS). In multivariate analysis, NGAL expression remained an independent prognostic factor for DFS. The results show that in low-risk subgroups, NGAL was found to be a predictive marker for pCR after NACT. Furthermore, NGAL could be validated as an independent prognostic factor for decreased DFS in primary human BC
The prognostic value of cortical magnetic stimulation in acute middle cerebral artery infarction compared to other parameters
The prognostic value of magnetic evoked potentials (MEP), somatosensory evoked potentials (SSEP), age and radiological parameters was determined in 50 patients with acute middle cerebral artery infarction. We performed MEP and SSEP within 4 days and after 6 weeks and 3 months of the infarction and assessed clinical improvement by using the Barthel index (BI) and the Rankin scale. The localization and extent of the infarction was investigated by CT scanning or NMR. All parameters were correlated to clinical outcome and the prognostic significance of each parameter in addition to BI was determined. MEP, SSEP, and age were valuable prognostic parameters in predicting stroke outcome when used together with the BI. However, in stepwise regression analysis using all parameters simultaneously, only MEP and age significantly contributed to clinical outcome in addition to BI. Patients showed a better outcome when their MEP was normal or delayed, measured within 4 days of the infarction, compared to patients with absent MEP. Clinical outcome was better at a younger age
Preoperative neutrophil-lymphocyte ratio and outcome from coronary artery bypass grafting
Background: An elevated preoperative white blood cell count has been associated with a worse outcome after coronary artery bypass grafting (CABG). Leukocyte subtypes, and particularly the neutrophil-lymphocyte (N/L) ratio, may however, convey superior prognostic information. We hypothesized that the N/L ratio would predict the outcome of patients undergoing surgical revascularization. Methods: Baseline clinical details were obtained prospectively in 1938 patients undergoing CABG. The differential leukocyte was measured before surgery, and patients were followed-up 3.6 years later. The primary end point was all-cause mortality. Results: The preoperative N/L ratio was a powerful univariable predictor of mortality (hazard ratio [HR] 1.13 per unit, P 3.36). Conclusion: An elevated N/L ratio is associated with a poorer survival after CABG. This prognostic utility is independent of other recognized risk factors.Peer reviewedAuthor versio
Prognostic value of lymph node ratio and extramural vascular invasion on survival for patients undergoing curative colon cancer resection
There was no study funding. We are grateful to Tony Rafferty (Tailored Information for the People of Scotland, TIPs) for providing survival data.Peer reviewedPublisher PD
Added predictive value of high-throughput molecular data to clinical data, and its validation
Hundreds of ''molecular signatures'' have been proposed in the literature to predict patient outcome in clinical settings from high-dimensional data, many of which eventually failed to get validated. Validation of such molecular research findings is thus becoming an increasingly important branch of clinical bioinformatics. Moreover, in practice well-known clinical predictors are often already available. From a statistical and bioinformatics point of view, poor attention has been given to the evaluation of the added predictive value of a molecular signature given that clinical predictors are available. This article reviews procedures that assess and validate the added predictive value of high-dimensional molecular data. It critically surveys various approaches for the construction of combined prediction models using both clinical and molecular data, for validating added predictive value based on independent data, and for assessing added predictive value using a single data set
ST2 in Stable and Unstable Ischemic Heart Diseases
Circulating suppression of tumorigenicity 2 (ST2) predicts cardiovascular outcomes and mortality in ischemic heart disease (IHD). ST2 does not correlate with traditional risk indicators as closely as N-terminal pro–brain natriuretic peptide (NT-proBNP) and is only weakly correlated with other biomarkers, indicating distinct pathways for stimulus and release. Although of little diagnostic utility in IHD, ST2 does offer prognostic information. In ST elevation myocardial infarction, ST2 levels increase to peak above the normal reference range (within 6 to 18 hours of symptom onset) in about half of patients. Levels in the upper quartile observed in IHD independently predict cardiovascular death and heart failure with an approximate doubling of risk. Similar but weaker associations have been reported in non–ST elevation myocardial infarction, in which ST2 predicts short-term (30-day) and long-term (>1-year) death and heart failure independent of clinical indicators, but these relations are lost if Global Registry of Acute Coronary Events (GRACE) score and NT-proBNP are added to multivariate models. Early postinfarction levels of ST2 (i.e., <24 hours after admission) have the greatest prognostic utility. Early postinfarction ST2 levels and change over 24 weeks are related to infarct extent and remodeling to a similar extent as NT-proBNP and aldosterone, and ST2 may have a significant pathophysiological role in these postinfarction processes. In long-term follow-up of stable IHD, ST2 is predictive of all-cause and cardiovascular mortality independent of accepted clinical indicators and other biomarkers, including NT-proBNP, high-sensitivity C-reactive protein, interleukin-6, high-sensitivitiy cardiac troponin T, and galectin-3. In conclusion, ST2 in combination with NT-proBNP consistently improves risk stratification compared with either marker alone
Prognostic value of echocardiographic indices of left atrial morphology and function in dogs with myxomatous mitral valve disease
Background: The prognostic relevance of left atrial (LA) morphological and functional variables, including those derived from speckle tracking echocardiography (STE), has been little investigated in veterinary medicine. Objectives: To assess the prognostic value of several echocardiographic variables, with a focus on LA morphological and functional variables in dogs with myxomatous mitral valve disease (MMVD). Animals: One-hundred and fifteen dogs of different breeds with MMVD. Methods: Prospective cohort study. Conventional morphologic and echo-Doppler variables, LA areas and volumes, and STE-based LA strain analysis were performed in all dogs. A survival analysis was performed to test for the best echocardiographic predictors of cardiac-related death. Results: Most of the tested variables, including all LA STE-derived variables were univariate predictors of cardiac death in Cox proportional hazard analysis. Because of strong correlation between many variables, only left atrium to aorta ratio (LA/Ao > 1.7), mitral valve E wave velocity (MV E vel > 1.3 m/s), LA maximal volume (LAVmax > 3.53 mL/kg), peak atrial longitudinal strain (PALS < 30%), and contraction strain index (CSI per 1% increase) were entered in the univariate analysis, and all were predictors of cardiac death. However, only the MV E vel (hazard ratio [HR], 4.45; confidence interval [CI], 1.76-11.24; P <.001) and LAVmax (HR, 2.32; CI, 1.10-4.89; P =.024) remained statistically significant in the multivariable analysis. Conclusions and Clinical Importance: The assessment of LA dimension and function provides useful prognostic information in dogs with MMVD. Considering all the LA variables, LAVmax appears the strongest predictor of cardiac death, being superior to LA/Ao and STE-derived variables
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