Predictors of diagnosis and survival in idiopathic pulmonary fibrosis and connective tissue disease-related usual interstitial pneumonia

Background

Although usual interstitial pneumonia (UIP) appears to portend better survival when associated with connective tissue disease (CTD-UIP), little is known about the presenting clinical, radiologic, and pathologic features that differentiate pathologically confirmed UIP with CTD from idiopathic pulmonary fibrosis (IPF). In patients with atypical radiologic and clinical features, what specific findings predict underlying IPF vs. CTD-UIP diagnosis and their respective long term survival?

Methods

A large retrospective cohort analysis was done of consecutive patients seen from 1995 through 2010 with biopsy confirmed UIP completed or reviewed at our institution. CTD-UIP was defined by independent rheumatology consultation with exclusion of all other secondary causes of lung fibrosis. Primary clinical data was collected and compared for IPF and CTD-UIP along with logistic regression performed for predictors of disease likelihood and Cox proportional hazards analysis for predictors of survival.

Results

Six hundred and twenty five patients were included in the study of which 89 had diagnosed CTD-UIP representing 7 disease entities. Survival was better among those with CTD-UIP except in UIP associated with rheumatoid arthritis, which had similar presenting features and survival to IPF. Predictors of underlying CTD included female gender, younger age, positive autoimmune serology, and inconsistent presenting radiologic findings. Only age and forced vital capacity corrected for a priori covariates were predictive of survival in CTD-UIP.

Conclusions

UIP pathology occurs frequently among patients with atypically presenting clinical and radiologic features, and may represent IPF or CTD-UIP with improved prognosis if underlying CTD is diagnosed. Presenting radiologic and pathologic features alone are not predictive of underlying secondary cause or survival between the two groups.     

A New Model to Estimate Prognosis in Patients with Hepatocellular Carcinoma after Yttrium-90 Radioembolization

Aims

The current prognostic model to estimate the survival in hepatocellular carcinoma (HCC) patients treated with transarterial hepatic selective internal radiotherapy (SIRT) is not fully characterized. The aim of this study was to establish a new scoring model including assessment of both tumor responses and therapy-induced systemic changes in HCC patients to predict survival at an early time point post-SIRT.

Methods and materials

Between 2008 and 2012, 149 HCC patients treated with SIRT were included into this study. CT images and biomarkers in blood tested at one month post-SIRT were analyzed and correlated with clinical outcome. Tumor responses were assessed by RECIST 1.1, mRECIST, and Choi criteria. Kaplan-Meier methods were used to estimate survival curves. Cox regression was used in uni- and multivariable survival analyses and in the establishment of a prognostic model.

Results

A multivariate proportional hazards model was created based on the tumor response, the number of tumor nodules, the score of the model for end stage liver disease (MELD), and the serum C-reactive protein levels which were independent predictors of survival in HCC patients at one month post-SIRT. This prognostic model accurately differentiated the outcome of patients with different risk scores in this cohort (P<0.001). The model also had the ability to assign a predicted survival probability for individual patients.

Conclusions

A new model to predict survival of HCC patients mainly based on tumor responses and therapy-induced systemic changes provides reliable prognosis and accurately discriminates the survival at an early time point after SIRT in these patients.     

The Value of CT for Disease Detection and Prognosis Determination in Combined Pulmonary Fibrosis and Emphysema (CPFE)

Background and Purpose

Several imaging-based indices were constructed quantitatively using the emphysema index (EI) and fibrosis score (FS) on high-resolution computed tomography (HRCT). We evaluated the ability of these indices to predict mortality compared to physiologic results. Additionally, prognostic predictive factors were compared among subgroups with biopsy-proven fibrotic idiopathic interstitial pneumonia (IIP) (biopsy-proven CPFE) and in a separate cohort with subclinical CPFE.

Materials and Methods

Three chest radiologists independently determined FS. EI was automatically quantified. PFTs, smoking history, and composite physiologic index (CPI) were reviewed. Predictors of time to death were determined based on clinico-physiologic factors and CT-based CPFE indices.

Results

The prevalence of biopsy-proven CPFE was 26% (66/254), with an EI of 9.1±7.1 and a FS of 19.3±14.2. In patients with CPFE, median survival and 5-year survival rates were 6.0 years and 34.8%, respectively, whereas those in fibrotic IIP without emphysema were 10.0 years and 60.9% (p = 0.013). However, the extent of fibrosis did not differ significantly between the two cohorts. In subclinical CPFE, prevalence was 0.04% (93/20,372), EI was 11.3±10.4, and FS was 9.1±7.1. FVC and a fibrosis-weighted CT index were independent predictors of survival in the biopsy-proven CPFE cohort, whereas only the fibrosis-weighted CT index was a significant prognostic factor in the subclinical CPFE cohort.

Conclusions

Recognition and stratification using CT quantification can be utilized as a prognostic predictor. Prognostic factors vary according to fibrosis severity and among cohorts of patients with biopsy-proven and subclinical CPFE.     

Prognostic Role of Common MicroRNA Polymorphisms in Cancers: Evidence from a Meta-Analysis

Background

The morbidity and mortality of cancer increase remarkably every year. It''s a heavy burden for family and society. The detection of prognostic biomarkers can help to improve the theraputic effect and prolong the lifetime of patients. microRNAs have an influential role in cancer prognosis. The results of articles discussing the relationship between microRNA polymorphisms and cancer prognosis are inconsistent.

Methods

We conduct a meta-analysis of 19 publications concerning the association of four common polymorphisms, mir-146a rs2910164, mir-149 rs2292832, mir-196a2 rs11614913 and mir-499 rs3746444, with cancer prognosis. Pooled Hazard Ratios with 95% Confidence Intervals for the relationship between four genetic polymorphisms and Overall Survival, Recurrence-free Survival, Disease-free survival, recurrence are calculated. Subgroup analysis by population and type of tumor are conducted.

Results

GG genotype of mir-146a may be the protective factor for overall survival, especially in Caucasian population. C-containing genotypes of mir-196a2 act as a risk role for overall survival. The same result exists in Asian population, in Non-Small Cell Lung Cancer and digestive cancer. The patients with C allele of mir-149 have a better overall survival, especially in Non-Small Cell Lung Cancer. No significant results are obtained for mir-499 polymorphisms.

Conclusions

Genetic polymorphisms in mir-146a, mir-196a2 and mir-149 may be associated with overall survival. This effect varies with different types of cancer. Genetic polymorphism in mir-499 may have nothing to do with cancer prognosis.     

Incremental effects of endocrine and metabolic biomarkers and abdominal obesity on cardiovascular mortality prediction

Background

Biomarkers may help clinicians predict cardiovascular risk. We aimed to determine if the addition of endocrine, metabolic, and obesity-associated biomarkers to conventional risk factors improves the prediction of cardiovascular and all-cause mortality.

Methodology/Principal Findings

In a population-based cohort study (the Study of Health in Pomerania) of 3,967 subjects (age 20–80 years) free of cardiovascular disease with a median follow-up of 10.0 years (38,638 person-years), we assessed the predictive value of conventional cardiovascular risk factors and the biomarkers thyrotropin; testosterone (in men only); insulin-like growth factor-1 (IGF-1); hemoglobin A1c (HbA1c); creatinine; high-sensitive C-reactive protein (hsCRP); fibrinogen; urinary albumin-to-creatinine ratio; and waist-to-height ratio (WHtR) on cardiovascular and all-cause death.During follow-up, we observed 339 all-cause including 103 cardiovascular deaths. In Cox regression models with conventional risk factors, the following biomarkers were retained as significant predictors of cardiovascular death after backward elimination: HbA1c, IGF-1, and hsCRP. IGF-1 and hsCRP were retained as significant predictors of all-cause death.For cardiovascular death, adding these biomarkers to the conventional risk factors changed the C-statistic from 0.898 to 0.910 (p = 0.02). The net reclassification improvement was 10.6%. For all-cause death, the C-statistic changed from 0.849 to 0.853 (P = 0.09).

Conclusions/Significance

HbA1c, IGF-1, and hsCRP predict cardiovascular death independently of conventional cardiovascular risk factors. These easily assessed endocrine and metabolic biomarkers might improve the ability to predict cardiovascular death.     

Risk factors for cardiovascular mortality in patients with systemic lupus erythematosus,a prospective cohort study

Introduction

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease. Cardiovascular disease (CVD) is common and a major cause of mortality. Studies on cardiovascular morbidity are abundant, whereas mortality studies focusing on cardiovascular outcomes are scarce. The aim of this study was to investigate causes of death and baseline predictors of overall (OM), non-vascular (N-VM), and specifically cardiovascular (CVM) mortality in SLE, and to evaluate systematic coronary risk evaluation (SCORE).

Methods

208 SLE patients were included 1995-1999 and followed up after 12 years. Clinical evaluation, CVD risk factors, and biomarkers were recorded at inclusion. Death certificates and autopsy protocols were collected. Causes of death were divided into CVM (ischemic vascular and general atherosclerotic diseases), N-VM and death due to pulmonary hypertension. Predictors of mortality were investigated using multivariable Cox regression. SCORE and standardized mortality ratio (SMR) were calculated.

Results

During follow-up 42 patients died at mean age of 62 years. SMR 2.4 (CI 1.7-3.0). 48% of deaths were caused by CVM. SCORE underestimated CVM but not to a significant level. Age, high cystatin C levels and established arterial disease were the strongest predictors for all- cause mortality. After adjusting for these in multivariable analyses, only smoking among traditional risk factors, and high soluble vascular cell adhesion molecule-1 (sVCAM-1), high sensitivity C-reactive protein (hsCRP), anti-beta2 glycoprotein-1 (abeta2GP1) and any antiphospholipid antibody (aPL) among biomarkers, remained predictive of CVM.

Conclusion

With the exception of smoking, traditional risk factors do not capture the main underlying risk factors for CVM in SLE. Rather, cystatin C levels, inflammatory and endothelial markers, and antiphospholipid antibodies (aPL) differentiate patients with favorable versus severe cardiovascular prognosis. Our results suggest that these new biomarkers are useful in evaluating the future risk of cardiovascular mortality in SLE patients.     

Evaluation of Circulating Proteins and Hemodynamics Towards Predicting Mortality in Children with Pulmonary Arterial Hypertension

Background

Although many predictors have been evaluated, a set of strong independent prognostic mortality indicators has not been established in children with pediatric pulmonary arterial hypertension (PAH). The aim of this study was to identify a combination of clinical and molecular predictors of survival in PAH.

Methods

This single-center, retrospective cohort study was performed from children with PAH between 2001 and 2008 at Children''s Hospital Colorado. Blood samples from 83 patients (median age of 8.3 years-old) were obtained. We retrospectively analyzed 46 variables, which included 27 circulating proteins, 7 demographic variables and 12 hemodynamic and echocardiographic variables for establishing the best predictors of mortality. A data mining approach was utilized to evaluate predictor variables and to uncover complex data structures while performing variable selection in high dimensional problems.

Results

Thirteen children (16%) died during follow-up (median; 3.1 years) and survival rates from time of sample collection at 1 year, 3 years and 5 years were 95%, 85% and 79%, respectively. A subset of potentially informative predictors were identified, the top four are listed here in order of importance: Tissue inhibitors of metalloproteinases-1 (TIMP-1), apolipoprotein-AI, RV/LV diastolic dimension ratio and age at diagnosis. In univariate analysis, TIMP-1 and apolipoprotein-AI had significant association with survival time (hazard ratio [95% confidence interval]: 1.25 [1.03, 1.51] and 0.70 [0.54–0.90], respectively). Patients grouped by TIMP-1 and apolipoprotein-AI values had significantly different survival risks (p<0.01).

Conclusion

Important predictors of mortality were identified from a large number of circulating proteins and clinical markers in this cohort. If confirmed in other populations, measurement of a subset of these predictors could aid in management of pediatric PAH by identifying patients at risk for death. These findings also further support a role for the clinical utility of measuring circulating proteins.     

Biopsy-Controlled Liver Fibrosis Staging Using the Enhanced Liver Fibrosis (ELF) Score Compared to Transient Elastography

Background and Aims

Chronic liver diseases are characterized by inflammatory and fibrotic liver injuries that often result in liver cirrhosis with its associated complications such as portal hypertension and hepatocellular carcinoma. Liver biopsy still represents the reference standard for fibrosis staging, although transient elastography is increasingly used for non-invasive monitoring of fibrosis progression. However, this method is not generally available and is associated with technical limitations emphasizing the need for serological biomarkers staging of liver fibrosis. The enhanced liver fibrosis (ELF) score was shown to accurately predict significant liver fibrosis in different liver diseases, although extracellular matrix components detected by this score may not only mirror the extent of liver fibrosis but also inflammatory processes.

Methods

In this prospective biopsy-controlled study we evaluated the utility of the ELF score in comparison to transient elastography to predict different stages of fibrosis in 102 patients with chronic liver diseases.

Results

Both techniques revealed similar area under receiver operating characteristic curve values for prediction of advanced fibrosis stages. Compared to transient elastography, the ELF score showed a broader overlap between low and moderate fibrosis stages and a stronger correlation with inflammatory liver injury.

Conclusions

Both the ELF score as well as transient elastography allowed for high quality fibrosis staging. However, the ELF score was less discriminative in low and moderate fibrosis stages and appeared more strongly influenced by inflammatory liver injury. This should be considered when making clinical interpretations on the basis of ELF score values.     

Significance of Pulmonary Arterial Pressure as a Prognostic Indicator in Lung-Dominant Connective Tissue Disease

Background

Lung-dominant connective tissue disease (LD-CTD) is a new concept for classifying the subset of patients with interstitial pneumonia who have clinical features suggesting an associated CTD, but whose features fall short of a clear diagnosis of CTD under the current rheumatologic classification systems. The impact of mean pulmonary arterial pressure (MPAP) in LD-CTD has not been sufficiently elucidated.

Objectives

To evaluate the survival impact of MPAP measured during the initial evaluation in patients with LD-CTD.

Methods

We retrospectively analyzed the initial evaluation data of 100 LD-CTD patients undergoing pulmonary function test, 6-min walk test (6MWT), and right heart catheterization (RHC).

Results

The mean MPAP was 16.2±4.4 mm Hg, and 18 patients had MPAP≥20 mm Hg. A univariate Cox proportional hazard model showed that MPAP and several variables have a statistically significant impact on survival. With stepwise, multivariate Cox proportional analysis, MPAP (HR  = 1.293; 95% CI 1.130–1.480; p<0.001) and mean forced vital capacity (FVC) % predicted (HR = 0.958; 95% CI 0.930–0.986; p = 0.004) were shown to be independent determinants of survival.

Conclusions

Higher MPAP and lower %FVC at the initial evaluation were significant independent prognostic factors of LD-CTD. MPAP evaluation provides additional information of disease status and will help physicians to predict mortality in LD-CTD.     

High-resolution CT scoring system-based grading scale predicts the clinical outcomes in patients with idiopathic pulmonary fibrosis

Background

The 2011 idiopathic pulmonary fibrosis (IPF) guidelines are based on the diagnosis of IPF using only high-resolution computed tomography (HRCT). However, few studies have thus far reviewed the usefulness of the HRCT scoring system based on the grading scale provided in the guidelines. We retrospectively studied 98 patients with respect to assess the prognostic value of changes in HRCT findings using a new HRCT scoring system based on the grading scale published in the guidelines.

Methods

Consecutive patients with IPF who were diagnosed using HRCT alone between January 2008 and January 2012 were evaluated. HRCT examinations and pulmonary function tests were performed at six-month intervals for the first year after diagnosis. The HRCT findings were evaluated using the new HRCT scoring system (HRCT fibrosis score) over time. The findings and survival rates were analyzed using a Kaplan-Meier analysis.

Results

The HRCT fibrosis scores at six and 12 months after diagnosis were significantly increased compared to those observed at the initial diagnosis (p < 0.001). The patients with an elevated HRCT fibrosis score at six months based on a receiver operating characteristic (ROC) curves analysis had a poor prognosis (log-rank, hazard ratio [HR] 2.435, 95% CI 1.196-4.962; p = 0.0142). Furthermore, among the patients without marked changes in %FVC, those with an elevated score above the cut-off value had a poor prognosis (HR 2.192, 95% CI 1.003-4.791; p = 0.0491).

Conclusions

Our data demonstrate that the HRCT scoring system based on the grading scale is useful for predicting the clinical outcomes of IPF and identifying patients with an adverse prognosis when used in combination with spirometry.     

Angiopoietin-2 Serum Levels Improve Noninvasive Fibrosis Staging in Chronic Hepatitis C: A Fibrogenic-Angiogenic Link

Aims

Accurate liver fibrosis staging is crucial for the management of chronic hepatitis C (CHC). The invasiveness and cost burden of liver biopsy have driven the search for new noninvasive biomarkers of fibrosis. Based on the link between serum angiopoietin-1 and 2 levels and CHC progression, we aimed to determine the value of these angiogenic factors as noninvasive biomarkers of liver fibrosis.

Methods

Serum levels of angiopoietin-1 and -2 were measured by ELISA in 108 CHC patients who underwent pretreatment liver biopsy. The correlation between angiopoietins and clinical and demographic variables with liver fibrosis was analyzed by univariate regression. Significant factors were then subjected to multivariate analysis, from which we constructed a novel noninvasive liver fibrosis index (AngioScore), whose performance was validated in an independent series of 71 CHC patients. The accuracy of this model was compared with other documented fibrosis algorithms by De Long test.

Results

Angiopoietins correlated significantly with hepatic fibrosis; however, only angiopoietin-2 was retained in the final model, which also included age, platelets, AST, INR, and GGT. The model was validated and behaved considerably better than other fibrosis indices in discriminating all, significant, moderate and severe liver fibrosis (0.886, 0.920, 0.923). Using clinically relevant cutoffs, we classified CHC patients by discarding significant fibrosis and diagnosing moderate and severe fibrosis with greater accuracy, sensitivity, and specificity.

Conclusions

Our novel noninvasive liver fibrosis model, based on serum angiopoietin-2 levels, outperforms other indices and should help substantially in managing CHC and monitoring long-term follow-up prognosis.     

Clinical Value of Prognosis Gene Expression Signatures in Colorectal Cancer: A Systematic Review

Introduction

The traditional staging system is inadequate to identify those patients with stage II colorectal cancer (CRC) at high risk of recurrence or with stage III CRC at low risk. A number of gene expression signatures to predict CRC prognosis have been proposed, but none is routinely used in the clinic. The aim of this work was to assess the prediction ability and potential clinical usefulness of these signatures in a series of independent datasets.

Methods

A literature review identified 31 gene expression signatures that used gene expression data to predict prognosis in CRC tissue. The search was based on the PubMed database and was restricted to papers published from January 2004 to December 2011. Eleven CRC gene expression datasets with outcome information were identified and downloaded from public repositories. Random Forest classifier was used to build predictors from the gene lists. Matthews correlation coefficient was chosen as a measure of classification accuracy and its associated p-value was used to assess association with prognosis. For clinical usefulness evaluation, positive and negative post-tests probabilities were computed in stage II and III samples.

Results

Five gene signatures showed significant association with prognosis and provided reasonable prediction accuracy in their own training datasets. Nevertheless, all signatures showed low reproducibility in independent data. Stratified analyses by stage or microsatellite instability status showed significant association but limited discrimination ability, especially in stage II tumors. From a clinical perspective, the most predictive signatures showed a minor but significant improvement over the classical staging system.

Conclusions

The published signatures show low prediction accuracy but moderate clinical usefulness. Although gene expression data may inform prognosis, better strategies for signature validation are needed to encourage their widespread use in the clinic.     

RAGE Genetic Polymorphisms Are Associated with Risk,Chemotherapy Response and Prognosis in Patients with Advanced NSCLC

Aim

To explore the association between genetic polymorphisms of the receptor for advanced glycation end-products (RAGE) and susceptibility, chemotherapy response rate and prognosis of non-small cell lung cancer (NSCLC).

Method

This is a prospective study in which 562 patients with NSCLC and 764 healthy controls were enrolled. Three RAGE genetic polymorphisms, namely, −429T/C, −374T/A and 82G/S were genotyped. Platinum-based chemotherapy was given to 432 subjects with advanced inoperable NSCLC and their responses to chemotherapy were evaluated.

Results

All the polymorphic genotypes of RAGE polymorphisms were associated with susceptibility for NSCLC. Only the 82G/S polymorphisms denoted a significant difference between responders and non-responders to chemotherapy. The 82SS genotype and 82S allele distribution not only increased the NSCLC risk, but also was associated with a lower chemotherapy response rate and poor prognosis, indicated by overall survival and progression free survival.

Conclusion

The 82G/S genetic polymorphism of RAGE gene might be used as a genetic marker to screen for patients sensitive to thermotherapy and to predict the prognosis of NSCLC.     

Performance of Polygenic Scores for Predicting Phobic Anxiety

Context

Anxiety disorders are common, with a lifetime prevalence of 20% in the U.S., and are responsible for substantial burdens of disability, missed work days and health care utilization. To date, no causal genetic variants have been identified for anxiety, anxiety disorders, or related traits.

Objective

To investigate whether a phobic anxiety symptom score was associated with 3 alternative polygenic risk scores, derived from external genome-wide association studies of anxiety, an internally estimated agnostic polygenic score, or previously identified candidate genes.

Design

Longitudinal follow-up study. Using linear and logistic regression we investigated whether phobic anxiety was associated with polygenic risk scores derived from internal, leave-one out genome-wide association studies, from 31 candidate genes, and from out-of-sample genome-wide association weights previously shown to predict depression and anxiety in another cohort.

Setting and Participants

Study participants (n = 11,127) were individuals from the Nurses'' Health Study and Health Professionals Follow-up Study.

Main Outcome Measure

Anxiety symptoms were assessed via the 8-item phobic anxiety scale of the Crown Crisp Index at two time points, from which a continuous phenotype score was derived.

Results

We found no genome-wide significant associations with phobic anxiety. Phobic anxiety was also not associated with a polygenic risk score derived from the genome-wide association study beta weights using liberal p-value thresholds; with a previously published genome-wide polygenic score; or with a candidate gene risk score based on 31 genes previously hypothesized to predict anxiety.

Conclusion

There is a substantial gap between twin-study heritability estimates of anxiety disorders ranging between 20–40% and heritability explained by genome-wide association results. New approaches such as improved genome imputations, application of gene expression and biological pathways information, and incorporating social or environmental modifiers of genetic risks may be necessary to identify significant genetic predictors of anxiety.     

ENCAPP: elastic-net-based prognosis prediction and biomarker discovery for human cancers

Background

With the explosion of genomic data over the last decade, there has been a tremendous amount of effort to understand the molecular basis of cancer using informatics approaches. However, this has proven to be extremely difficult primarily because of the varied etiology and vast genetic heterogeneity of different cancers and even within the same cancer. One particularly challenging problem is to predict prognostic outcome of the disease for different patients.

Results

Here, we present ENCAPP, an elastic-net-based approach that combines the reference human protein interactome network with gene expression data to accurately predict prognosis for different human cancers. Our method identifies functional modules that are differentially expressed between patients with good and bad prognosis and uses these to fit a regression model that can be used to predict prognosis for breast, colon, rectal, and ovarian cancers. Using this model, ENCAPP can also identify prognostic biomarkers with a high degree of confidence, which can be used to generate downstream mechanistic and therapeutic insights.

Conclusion

ENCAPP is a robust method that can accurately predict prognostic outcome and identify biomarkers for different human cancers.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1465-9) contains supplementary material, which is available to authorized users.     

Comparison of Prognostic Genomic Predictors in Colorectal Cancer

Background

Although several prognostic genomic predictors have been identified from independent studies, it remains unclear whether these predictors are actually concordant with respect to their predictions for individual patients and which predictor performs best. We compared five prognostic genomic predictors, the V7RHS, the ColoGuideEx, the Meta163, the OncoDX, and the MDA114, in terms of predicting disease-free survival in two independent cohorts of patients with colorectal cancer.

Study Design

Using original classification algorithms, we tested the predictions of five genomic predictors for disease-free survival in two cohorts of patients with colorectal cancer (n = 229 and n = 168) and evaluated concordance of predictors in predicting outcomes for individual patients.

Results

We found that only two predictors, OncoDX and MDA114, demonstrated robust performance in identifying patients with poor prognosis in 2 independent cohorts. These two predictors also had modest but significant concordance of predicted outcome (r>0.3, P<0.001 in both cohorts).

Conclusions

Further validation of developed genomic predictors is necessary. Despite the limited number of genes shared by OncoDX and MDA114, individual-patient outcomes predicted by these two predictors were significantly concordant.     

Child-Na Score: A Predictive Model for Survival in Cirrhotic Patients with Symptomatic Portal Hypertension Treated with TIPS

Background and Aim

Several models have been developed to predict survival in patients with cirrhosis undergoing TIPS; however, few of these models have gained widespread acceptance, especially in the era of covered stents. The aim of this study was to establish an evidence-based model for predicting survival after TIPS procedures.

Methods

A total of 210 patients with cirrhosis treated with TIPS were considered in the study. We comprehensively investigated factors associated with one-year survival and developed a new predictive model using the Cox regression model.

Results

In the multivariate analysis, the Child-Pugh score and serum sodium levels were independent predictors of one-year survival. A new score incorporating serum sodium into the Child-Pugh score was developed: Child-Na score. We compared the predictive accuracy of Child-Na score with that of other scores; only the Child-Na and MELD-Na scores had adequate predictive ability in patients with serum Na levels <138 mmol/L. The best Child-Na cut-off score (15.5) differentiated two groups of patients with distinct prognoses (one-year cumulative survival rates of 80.6% and 45.5%); this finding was confirmed in a validation cohort (n = 86). In a subgroup analysis stratifying patients by indication for TIPS, the Child-Na score distinguished patients with different prognoses.

Conclusions

Patients with variceal bleeding and a Child-Na score ≤15 had a better prognosis than patients with a score ≥16. Patients with refractory ascites and a Child-Na score ≥16 had a high risk of death after the TIPS procedures; caution should be used when treating these patients with TIPS.     

Concordance in a World without a Gold Standard: A New Non-Invasive Methodology for Improving Accuracy of Fibrosis Markers

Background

Assessing liver fibrosis is traditionally performed by biopsy, an imperfect gold standard. Non-invasive techniques, liver stiffness measurements (LSM) and biomarkers [FibroTest® (FT)], are widely used in countries where they are available. The aim was to identify factors associated with LSM accuracy using FT as a non-invasive endpoint and vice versa.

Methods

The proof of concept was taken using the manufacturers recommendations for excluding patients at high risk of false negative/positive. The hypothesis was that the concordance between LSM and FT, would be improved by excluding high-risk patients. Thereafter, the impact of potential variability factors was assessed by the same methods. Liver biopsy and independent endpoints were used to validate the results.

Results

Applying manufacturers'' recommendations in 2,004 patients increased the strength of concordance between LSM and FT (P<0.00001). Among the 1,338 patients satisfying recommendations, the methodology identified a significant LSM operator effect (P = 0.001) and the following variability factors (all P<0.01), related to LSM: male gender, older age, and NAFLD as a cause of liver disease. Biopsy confirmed in 391 patients these results.

Conclusion

This study has validated the concept of using the strength of concordance between non-invasive estimates of liver fibrosis for the identification of factors associated with variability and precautions of use.     

Evaluation of Preoperative Hematologic Markers as Prognostic Factors and Establishment of Novel Risk Stratification in Resected pN0 Non-Small-Cell Lung Cancer

Background

The aims of this study were to investigate whether the preoperative hematologic markers, the neutrophil-lymphocyte ratio (NLR) or the platelet-lymphocyte ratio (PLR) were prognostic indicators and to develop a novel risk stratification model in pN0 non-small-cell lung cancer (NSCLC).

Methods

We performed a retrospective analysis of 400 consecutive pN0 NSCLC patients. Prognostic values were evaluated by Cox proportional hazard model analyses and patients were stratified according to relative risks for patients’ survival.

Results

During the follow-up, 117 patients had cancer recurrence, and 86 patients died. In univariate analysis, age, gender, smoke status and tumor size as well as WBC, NEU, LYM, PLR and NLR were significantly associated with patients’ prognosis. In multivariate analysis, age, tumor size and NLR were independent predictors for patients’ overall survival (P = 0.024, 0.001, and 0.002 respectively). PLR didn’t associated with patients’ survival in multivariate analysis. Patients were stratified into 3 risk groups and the differences among the groups were significant according to disease free survival and overall survival (P = 0.000 and 0.000 respectively).

Conclusions

We confirmed that NLR other than PLR was an independent prognostic factor. Combination of NLR, age and tumor size could stratify pN0 NSCLC patients into 3 risk groups and enabled us to develop a novel risk stratification model.