scholarly journals Gaze behaviour to lateral face stimuli in infants who do and do not receive an ASD diagnosis

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Georgina Donati ◽  
Rachael Davis ◽  
Gillian S. Forrester
Keyword(s):  
Risk Group ◽  
Risk Groups ◽  
Cognitive Outcomes ◽  
Low Risk ◽  
Motor Ability ◽  
Vertebrate Species ◽  
Gaze Behaviour ◽  
Face Stimuli ◽  
The Right ◽  
Infant Study

Abstract Cerebral lateralisation of function is a common characteristic across vertebrate species and is positively associated with fitness of the organism, in humans we hypothesise that it is associated with cognitive fitness. This investigation evaluated the early development of lateralised gaze behaviour for face stimuli in infants at high and low risk for autism from the British Autism Sibling Infant Study (BASIS). The BASIS cohort includes a low risk group and three high-risk groups who at age 3 were developing (i) typically, (ii) atypically or (iii) had received a diagnosis for ASD. Using eye-tracking data derived from a face pop-out task at 6 and 14 months of age, all non-ASD groups showed a bias for stimuli on the left at both timepoints. At 6 months the ASD group demonstrated a preference for stimuli on the right and were slower than their neurotypical counterparts to look at faces on the left. However, by 14 months these differences disappear. Longitudinal associations between lateral looking behaviour at 6 months and language and motor ability at 14 months were also found. Results suggest that infants who go on to be diagnosed with autism exhibit early differences in gaze behaviour that may be associated with subsequent cognitive outcomes.

Short-term risk stratification using CADILLAC risk score in patients with ST elevation myocardial infarction

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
T Satou ◽  
H Kitahara ◽  
K Ishikawa ◽  
T Nakayama ◽  
Y Fujimoto ◽  
...  
Keyword(s):  
Myocardial Infarction ◽  
High Risk ◽  
Adverse Events ◽  
Risk Score ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Short Term ◽  
Recurrent Myocardial Infarction ◽  
St Elevation

Abstract Background The recent reperfusion therapy for ST-elevation myocardial infarction (STEMI) has made the length of hospital stay shorter without adverse events. CADILLAC risk score is reportedly one of the risk scores predicting the long-term prognosis in STEMI patients. Purpose To invenstigate the usefulness of CADILLAC risk score for predicting short-term outcomes in STEMI patients. Methods Consecutive patients admitted to our university hospital and our medical center with STEMI (excluding shock, arrest case) who underwent primary PCI between January 2012 and April 2018 (n=387) were enrolled in this study. The patients were classified into 3 groups according to the CADILLAC risk score: low risk (n=176), intermediate risk (n=87), and high risk (n=124). Data on adverse events within 30 days after hospitalization, including in-hospital death, sustained ventricular arrhythmia, recurrent myocardial infarction, heart failure requiring intravenous treatment, stroke, or clinical hemorrhage, were collected. Results In the low risk group, adverse events within 30 days were significantly less observed, compared to the intermediate and high risk groups (n=13, 7.4% vs. n=13, 14.9% vs. n=58, 46.8%, p<0.001). In particular, all adverse events occurred within 3 days in the low risk group, although adverse events, such as heart failure (n=4), recurrent myocardial infarction (n=1), stroke (n=1), and gastrointestinal bleeding (n=1), were substantially observed after day 4 of hospitalization in the intermediate and high risk groups. Conclusions In STEMI patients with low CADILLAC risk score, better short-term prognosis was observed compared to the intermediate and high risk groups, and all adverse events occurred within 3 days of hospitalization, suggesting that discharge at day 4 might be safe in this study population. CADILLAC risk score may help stratify patient risk for short-term prognosis and adjust management of STEMI patients. Initial event occurrence timing Funding Acknowledgement Type of funding source: None

scholarly journals Immune‐related Long Noncoding RNA Signature for Patients with Cervical Cancer

2020 ◽  
Author(s):  
Jianfeng Zheng ◽  
Jinyi Tong ◽  
Benben Cao ◽  
Xia Zhang ◽  
Zheng Niu
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Risk Score ◽  
Immune Cell ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Gene Set Enrichment Analysis ◽  
Training Set ◽  
Score Model

Abstract Background: Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune‐related lncRNAs(IRLs) of CC has never been reported. This study aimed to establish an IRL signature for patients with CC.Methods: The RNA-seq dataset was obtained from the TCGA, GEO, and GTEx database. The immune scores（IS）based on single-sample gene set enrichment analysis (ssGSEA) were calculated to identify the IRLs, which were then analyzed using univariate Cox regression analysis to identify significant prognostic IRLs. A risk score model was established to divide patients into low-risk and high-risk groups based on the median risk score of these IRLs. This was then validated by splitting TCGA dataset(n=304) into a training-set(n=152) and a valid-set(n=152). The fraction of 22 immune cell subpopulations was evaluated in each sample to identify the differences between low-risk and high-risk groups. Additionally, a ceRNA network associated with the IRLs was constructed.Results: A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson’s correlation analysis between immune score and lncRNA expression (P < 0.01). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values (P < 0.05) were identified which demonstrated an ability to stratify patients into low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low‐risk group showed longer overall survival (OS) than those in the high‐risk group in the training-set, valid-set, and total-set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four IRLs signature in predicting the one-, two-, and three-year survival rates were larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Conclusions: Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four-IRLs in the development of CC were ascertained preliminarily.

A Novel Risk Classification Model Predicts Overall Survival and Locoregional Surgery Benefit in Colorectal Patients with Distant Metastasis at the Initial Diagnosis

2020 ◽  
Author(s):  
Mo Chen ◽  
Tian-en Li ◽  
Pei-zhun Du ◽  
Junjie Pan ◽  
Zheng Wang ◽  
...  
Keyword(s):  
Overall Survival ◽  
High Risk ◽  
Distant Metastasis ◽  
Cox Regression ◽  
Risk Group ◽  
Risk Groups ◽  
Risk Classification ◽  
Low Risk ◽  
Classification Model ◽  
Intermediate Risk

Abstract Background and aims: In this research, we aimed to construct a risk classification model to predict overall survival (OS) and locoregional surgery benefit in colorectal cancer (CRC) patients with distant metastasis.Methods: We selected a cohort consisting of 12741 CRC patients diagnosed with distant metastasis between 2010 and 2014, from the Surveillance, Epidemiology and End Results (SEER) database. Patients were randomly assigned into training group and validation group at the ratio of 2:1. Univariable and multivariable Cox regression models were applied to screen independent prognostic factors. A nomogram was constructed and assessed by the Harrell’s concordance index (C-index) and calibration plots. A novel risk classification model was further established based on the nomogram.Results: Ultimately 12 independent risk factors including race, age, marriage, tumor site, tumor size, grade, T stage, N stage, bone metastasis, brain metastasis, lung metastasis and liver metastasis were identified and adopted in the nomogram. The C-indexes of training and validation groups were 0.77 (95% confidence interval [CI] 0.73-0.81) and 0.75 (95% CI 0.72-0.78), respectively. The risk classification model stratified patients into three risk groups (low-, intermediate- and high-risk) with divergent median OS (low-risk: 36.0 months, 95% CI 34.1-37.9; intermediate-risk: 18.0 months, 95% CI 17.4-18.6; high-risk: 6.0 months, 95% CI 5.3-6.7). Locoregional therapies including surgery and radiotherapy could prognostically benefit patients in the low-risk group (surgery: hazard ratio [HR] 0.59, 95% CI 0.50-0.71; radiotherapy: HR 0.84, 95% CI 0.72-0.98) and intermediate risk group (surgery: HR 0.61, 95% CI 0.54-0.68; radiotherapy: HR 0.86, 95% CI 0.77-0.95), but not in the high-risk group (surgery: HR 1.03, 95% CI 0.82-1.29; radiotherapy: HR 1.03, 95% CI 0.81-1.31). And all risk groups could benefit from systemic therapy (low-risk: HR 0.68, 95% CI 0.58-0.80; intermediate-risk: HR 0.50, 95% CI 0.47-0.54; high-risk: HR 0.46, 95% CI 0.40-0.53).Conclusion: A novel risk classification model predicting prognosis and locoregional surgery benefit of CRC patients with distant metastasis was established and validated. This predictive model could be further utilized by physicians and be of great significance for medical practice.

scholarly journals MO048MULTICENTRE PROSPECTIVE VALIDATION OF THE URINARY PEPTIDOME-BASED CLASSIFIER CKD273 AS A PREDICTOR OF RENAL FUNCTION DECLINE IN SUBJECTS WITH TYPE 2 DIABETES

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Morten Lindhardt ◽  
Nete Tofte ◽  
Gemma Currie ◽  
Marie Frimodt-Moeller ◽  
Heiko Von der Leyen ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Renal Function ◽  
High Risk ◽  
Risk Group ◽  
Cox Model ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Renal Function Decline

Abstract Background and Aims In the PRIORITY study, it was recently demonstrated that the urinary peptidome-based classifier CKD273 was associated with increased risk for progression to microalbuminuria. As a prespecified secondary outcome, we aim to evaluate the classifier CKD273 as a determinant of relative reductions in eGFR (CKD-EPI) of 30% and 40% from baseline, at one timepoint without requirements of confirmation. Method The ‘Proteomic prediction and Renin angiotensin aldosterone system Inhibition prevention Of early diabetic nephRopathy In TYpe 2 diabetic patients with normoalbuminuria trial’ (PRIORITY) is the first prospective observational study to evaluate the early detection of diabetic kidney disease in subjects with type 2 diabetes (T2D) and normoalbuminuria using the CKD273 classifier. Setting 1775 subjects from 15 European sites with a mean follow-up time of 2.6 years (minimum of 7 days and a maximum of 4.3 years). Patients Subjects with T2D, normoalbuminuria and estimated glomerular filtration rate (eGFR) ≥ 45 ml/min/1.73m2. Participants were stratified into high- or low-risk groups based on their CKD273 score in a urine sample at screening (high-risk defined as score &gt; 0.154). Results In total, 12 % (n = 216) of the subjects had a high-risk proteomic pattern. Mean (SD) baseline eGFR was 88 (15) ml/min/1.73m2 in the low-risk group and 81 (17) ml/min/1.73m2 in the high-risk group (p &lt; 0.01). Baseline median (interquartile range) urinary albumin to creatinine ratio (UACR) was 5 (3-8) mg/g and 7 (4-12) mg/g in the low-risk and high-risk groups, respectively (p &lt; 0.01). A 30 % reduction in eGFR from baseline was seen in 42 (19.4 %) subjects in the high-risk group as compared to 62 (3.9 %) in the low-risk group (p &lt; 0.0001). In an unadjusted Cox-model the hazard ratio (HR) for the high-risk group was 5.7, 95 % confidence interval (CI) (3.9 to 8.5; p&lt;0.0001). After adjustment for baseline eGFR and UACR, the HR was 5.2, 95 % CI (3.4 to 7.8; p&lt;0.0001). A 40 % reduction in eGFR was seen in 15 (6.9 %) subjects in the high-risk group whereas 22 (1.4 %) in the low-risk group developed this endpoint (p&lt;0.0001). In an unadjusted Cox-model the HR for the high-risk group was 5.0, 95 % CI (2.6 to 9.6; p&lt;0.0001). After adjustment for baseline eGFR and UACR, the HR was 4.8, 95 % CI (2.4 to 9.7; p&lt;0.0001). Conclusion In normoalbuminuric subjects with T2D, the urinary proteomic classifier CKD273 predicts renal function decline of 30 % and 40 %, independent of baseline eGFR and albuminuria.

scholarly journals Immune-Related Four-lncRNA Signature for Patients with Cervical Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Jianfeng Zheng ◽  
Benben Cao ◽  
Xia Zhang ◽  
Zheng Niu ◽  
Jinyi Tong
Keyword(s):  
Cervical Cancer ◽  
High Risk ◽  
Immune Cell ◽  
Risk Group ◽  
Pearson Correlation ◽  
Characteristic Curve ◽  
Risk Groups ◽  
High Risk Group ◽  
Low Risk ◽  
Gynecological Malignancy

Cervical cancer (CC) is a common gynecological malignancy for which prognostic and therapeutic biomarkers are urgently needed. The signature based on immune-related lncRNAs (IRLs) of CC has never been reported. This study is aimed at establishing an IRL signature for patients with CC. A cohort of 326 CC and 21 normal tissue samples with corresponding clinical information was included in this study. Twenty-eight IRLs were collected according to the Pearson correlation analysis between the immune score and lncRNA expression ( p < 0.01 ). Four IRLs (BZRAP1-AS1, EMX2OS, ZNF667-AS1, and CTC-429P9.1) with the most significant prognostic values ( p < 0.05 ) were identified which demonstrated an ability to stratify patients into the low-risk and high-risk groups by developing a risk score model. It was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group in the training set, valid set, and total set. The area under the curve (AUC) of the receiver operating characteristic curve (ROC curve) for the four-IRL signature in predicting the one-, two-, and three-year survival rates was larger than 0.65. In addition, the low-risk and high-risk groups displayed different immune statuses in GSEA. These IRLs were also significantly correlated with immune cell infiltration. Our results showed that the IRL signature had a prognostic value for CC. Meanwhile, the specific mechanisms of the four IRLs in the development of CC were ascertained preliminarily.

Validation of Postpartum Hemorrhage Admission Risk Factor Stratification in a Large Obstetrics Population

2020 ◽  
Author(s):  
Halley Ruppel ◽  
Vincent X. Liu ◽  
Neeru R. Gupta ◽  
Lauren Soltesz ◽  
Gabriel J. Escobar
Keyword(s):  
Risk Factors ◽  
Risk Assessment ◽  
High Risk ◽  
Blood Loss ◽  
Postpartum Hemorrhage ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Hemorrhage Risk ◽  
Present On Admission

Abstract Objective This study aimed to evaluate the performance of the California Maternal Quality Care Collaborative (CMQCC) admission risk criteria for stratifying postpartum hemorrhage risk in a large obstetrics population. Study Design Using detailed electronic health record data, we classified 261,964 delivery hospitalizations from Kaiser Permanente Northern California hospitals between 2010 and 2017 into high-, medium-, and low-risk groups based on CMQCC criteria. We used logistic regression to assess associations between CMQCC risk groups and postpartum hemorrhage using two different postpartum hemorrhage definitions, standard postpartum hemorrhage (blood loss ≥1,000 mL) and severe postpartum hemorrhage (based on transfusion, laboratory, and blood loss data). Among the low-risk group, we also evaluated associations between additional present-on-admission factors and severe postpartum hemorrhage. Results Using the standard definition, postpartum hemorrhage occurred in approximately 5% of hospitalizations (n = 13,479), with a rate of 3.2, 10.5, and 10.2% in the low-, medium-, and high-risk groups. Severe postpartum hemorrhage occurred in 824 hospitalizations (0.3%), with a rate of 0.2, 0.5, and 1.3% in the low-, medium-, and high-risk groups. For either definition, the odds of postpartum hemorrhage were significantly higher in medium- and high-risk groups compared with the low-risk group. Over 40% of postpartum hemorrhages occurred in hospitalizations that were classified as low risk. Among the low-risk group, risk factors including hypertension and diabetes were associated with higher odds of severe postpartum hemorrhage. Conclusion We found that the CMQCC admission risk assessment criteria stratified women by increasing rates of severe postpartum hemorrhage in our sample, which enables early preparation for many postpartum hemorrhages. However, the CMQCC risk factors missed a substantial proportion of postpartum hemorrhages. Efforts to improve postpartum hemorrhage risk assessment using present-on-admission risk factors should consider inclusion of other nonobstetrical factors.

Computational identification of mutator-derived lncRNA signatures of genome instability for improving the clinical outcome of cancers: a case study in breast cancer

2019 ◽  
Vol 21 (5) ◽  
pp. 1742-1755 ◽  
Author(s):  
Siqi Bao ◽  
Hengqiang Zhao ◽  
Jian Yuan ◽  
Dandan Fan ◽  
Zicheng Zhang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Genomic Instability ◽  
Genome Instability ◽  
Risk Group ◽  
Expression Profiles ◽  
Risk Groups ◽  
Low Risk ◽  
A Genome ◽  
Significant Difference

Abstract Emerging evidence revealed the critical roles of long non-coding RNAs (lncRNAs) in maintaining genomic instability. However, identification of genome instability-associated lncRNAs and their clinical significance in cancers remain largely unexplored. Here, we developed a mutator hypothesis-derived computational frame combining lncRNA expression profiles and somatic mutation profiles in a tumor genome and identified 128 novel genomic instability-associated lncRNAs in breast cancer as a case study. We then identified a genome instability-derived two lncRNA-based gene signature (GILncSig) that stratified patients into high- and low-risk groups with significantly different outcome and was further validated in multiple independent patient cohorts. Furthermore, the GILncSig correlated with genomic mutation rate in both ovarian cancer and breast cancer, indicating its potential as a measurement of the degree of genome instability. The GILncSig was able to divide TP53 wide-type patients into two risk groups, with the low-risk group showing significantly improved outcome and the high-risk group showing no significant difference compared with those with TP53 mutation. In summary, this study provided a critical approach and resource for further studies examining the role of lncRNAs in genome instability and introduced a potential new avenue for identifying genomic instability-associated cancer biomarkers.

scholarly journals The ferroptosis and iron-metabolism signature robustly predicts clinical diagnosis, prognosis and immune microenvironment for hepatocellular carcinoma

2020 ◽  
Vol 18 (1) ◽  
Author(s):  
Bufu Tang ◽  
Jinyu Zhu ◽  
Jie Li ◽  
Kai Fan ◽  
Yang Gao ◽  
...  
Keyword(s):  
High Risk ◽  
Iron Metabolism ◽  
Cox Regression ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
Prognostic Models ◽  
Integrated Analysis ◽  
Immune Microenvironment ◽  
Diagnostic Models

Abstract Background In this study, we comprehensively analyzed genes related to ferroptosis and iron metabolism to construct diagnostic and prognostic models and explore the relationship with the immune microenvironment in HCC. Methods Integrated analysis, cox regression and the least absolute shrinkage and selection operator (LASSO) method of 104 ferroptosis- and iron metabolism-related genes and HCC-related RNA sequencing were performed to identify HCC-related ferroptosis and iron metabolism genes. Results Four genes (ABCB6, FLVCR1, SLC48A1 and SLC7A11) were identified to construct prognostic and diagnostic models. Poorer overall survival (OS) was exhibited in the high-risk group than that in the low-risk group in both the training cohort (P < 0.001, HR = 0.27) and test cohort (P < 0.001, HR = 0.27). The diagnostic models successfully distinguished HCC from normal samples and proliferative nodule samples. Compared with low-risk groups, high-risk groups had higher TMB; higher fractions of macrophages, follicular helper T cells, memory B cells, and neutrophils; and exhibited higher expression of CD83, B7H3, OX40 and CD134L. As an inducer of ferroptosis, erastin inhibited HCC cell proliferation and progression, and it was showed to affect Th17 cell differentiation and IL-17 signaling pathway through bioinformatics analysis, indicating it a potential agent of cancer immunotherapy. Conclusions The prognostic and diagnostic models based on the four genes indicated superior diagnostic and predictive performance, indicating new possibilities for individualized treatment of HCC patients. Graphical abstract

scholarly journals Geriatric Nutritional Risk Index as a Tool to Evaluate Impact of Malnutrition Risk on Mortality in Adult Patients with Polytrauma

2020 ◽  
Vol 17 (24) ◽  
pp. 9233
Author(s):  
Cheng-Hsi Yeh ◽  
Shao-Chun Wu ◽  
Sheng-En Chou ◽  
Wei-Ti Su ◽  
Ching-Hua Tsai ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Group ◽  
Risk Index ◽  
Risk Groups ◽  
Low Risk ◽  
Adult Patients ◽  
Nutritional Risk ◽  
Moderate Risk ◽  
Survival Group ◽  
Nutritional Risk Index

Background: Identification of malnutrition is especially important in severely injured patients, in whom hypermetabolism and protein catabolism following traumatic injury worsen their nutritional condition. The geriatric nutritional risk index (GNRI), based on serum albumin level and the current body weight/ideal body weight ratio, is useful for identifying patients with malnutrition in many clinical conditions. This study aimed to explore the association between admission GNRI and mortality outcomes of adult patients with polytrauma. Methods: From 1 January 2009 to 31 December 2019, a total of 348 adult patients with polytrauma, registered in the trauma database of a level I trauma center, were recognized and categorized into groups of death (n = 71) or survival (n = 277) and into four nutritional risk groups: a high-risk group (GNRI < 82, n = 87), a moderate-risk group (GNRI 82 to <92, n = 144), a low-risk group (GNRI 92–98, n = 59), and a no-risk group (GNRI > 98, n = 58). Univariate and multivariate logistic regression analyses were used to identify the independent risk factors for mortality. The mortality outcomes of patients at various nutritional risks were compared to those of patients in the no-risk group. Results: The comparison between the death group (n = 71) and the survival group (n = 277) revealed that there was no significant difference in gender predominance, age, pre-existing comorbidities, injury mechanism, systolic blood pressure, and respiratory rate upon arrival at the emergency room. A significantly lower GNRI and Glasgow Coma Scale score but higher injury severity score (ISS) was observed in the death group than in the survival group. Multivariate logistic regression analysis revealed that Glasgow Coma Scale (GCS), odds ratio (OR), 0.88; 95% confidence interval (CI), 0.83–0.95; p < 0.001), ISS (OR, 1.07; 95% CI, 1.04–1.11; p < 0.001), and GNRI (OR, 0.94; 95% CI, 0.91–0.97; p < 0.001) were significant independent risk factors for mortality in these patients. The mortality rates for the high-risk, moderate-risk, low-risk, and no-risk groups were 34.5%, 20.1%, 8.5%, and 12.1%, respectively. Unlike patients in the moderate-risk and low-risk groups, patients in the high-risk group had a significantly higher death rate than that of those in the no-risk group. Conclusions: This study revealed that the GNRI may serve as a simple, promising screening tool to identify the high risk of malnutrition for mortality in adult patients with polytrauma.

Proteomic Pattern-Based Risk Stratification of Outcome Shows Significant Higher Accuracy Compared to HCT-CI in Patients with AML and MDS,

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 4128-4128
Author(s):  
Christiane E Dobbelstein ◽  
Jochen Metzger ◽  
Elke Dammann ◽  
Uwe Borchert ◽  
Stefanie Buchholz ◽  
...  
Keyword(s):  
Risk Stratification ◽  
Cell Transplantation ◽  
Hematopoietic Cell Transplantation ◽  
Risk Group ◽  
Risk Groups ◽  
Low Risk ◽  
The Other ◽  
Unrelated Donor ◽  
Intermediate Risk ◽  
Significant Difference

Abstract Abstract 4128 Objectives: Allogeneic stem cell transplantation (SCT) is an established treatment for many severe disorders of hematopoiesis. Although SCT has considerable curative potential, its application is limited by transplant-related complications such as infections and graft-versus host disease (GvHD) which could lead to high mortality rates especially in older or less fit patients. Therefore, a careful pre-SCT assessment of risk and benefit is mandatory and different scores have recently emerged as helpful tools. We have previously applied proteomics to identify a specific urinary polypeptide patterns (PP) predictive for developing acute GvHD (aGvHD) (Weissinger EM et al, Blood 2007;109:5511–5519). The aim of this study was to investigate whether the PPs can predict overall outcome after allo-SCT and to compare these findings to those of the hematopoietic cell transplantation comorbidity index (HCT-CI) (Sorror M et al, Blood 2005;106:2912–2919). Methods: In this retrospective analysis from Hannover Medical School, the datasets from all patients (pts) with acute myeloid leukemia (AML) and myelodysplastic syndrome (MDS), who were allo-transplanted from a fully matched donor (matched related/unrelated donor (MRD/MUD)) between 2003–2008 and for whom relevant PP data were available, were included. Pts with a pt-donor HLA-mismatch constellation were excluded from this study. PP data from urine samples which were prospectively collected by day ≥ +7 after allo-SCT were correlated with overall survival (OS), aGvHD, non-relapse mortality (NRM), relapse rate and mortality (RM), and compared to the predictive value of the HCT-CI. Results: PP data were available from 111 pts (97 pts with AML, 14 with MDS; median age 52y; median EBMT score 4; 59 male/52 female; 69 MUD/42 MRD). They were grouped in high (PP-HRG), low (PP-LRG) or intermediate risk groups (PP-IRG). Forty-three pts (39%) belonged to the PP-LRG for aGvHD compared to 47 pts (42%) who were classified PP-HRG. Patient characteristics of PP-LRG and PP-HRG were similar in terms of age, sex and EBMT score (median 4 in both groups). OS compared favorably for the PP-LRG with an OS of 72% vs. 49% for the PP-HRG (p=0.03), also if only reduced intensity conditioning (RIC) was considered (73% vs 42%; p=0.01), respectively. There was a trend for higher incidence of NRM in the PP-HRG compared to PP-LRG (30% vs 14%, p=0.07) for the whole cohort, and a significant higher NRM rate, if only RIC was evaluated (35% vs 11%, p=0.01). However, if risk stratification was based on the HCT-CI, there was no significant difference between high risk (S-HRG) and low risk group (S-LRG) in terms of OS and NRM regardless of intensity of conditioning (OS for whole cohort: 57% vs 45%, p=0.4; OS for RIC: 56% vs 36%, p=0.2; NRM for whole cohort: 20% vs 23%, p=0.8; NRM for RIC: 18% vs 29%, p=0.4). Concerning the PP-IRG, there was a difference in OS between PP-IRG and PP-LRG (38% vs 73%, p=0.02). However, there was no significant difference in OS of the PP-IRG compared to the other PP-based risk groups nor between the HCT-CI based risk groups. Further, NRM did not show a significant difference neither for PP-based nor HCT-CI-based intermediate risk group compared to the other risk groups. Thirty vs 15 pts developed aGvHD in PP-HRG and PP-LRG (64% vs 35%, p<0.01) compared to 48% vs 64% (p=0.2) for S-HRG and S-LRG of the whole cohort, respectively. Incidence of aGvHD differed also significantly in the RIC cohort for PP-HRG and PP-LRG (65% vs 32%, p=0.01), but not for HCT-CI-based risk groups (47% vs 64%, p=0.1). Relapse rates and RM were not significantly different between high and low risk groups, neither for PP-based nor HCT-CI based (whole cohort and RIC subgroup), respectively. Conclusion: Risk stratification according to GvHD-match based PP, which has previously been shown to predict aGvHD, now also allows the identification of patient groups with significantly different OS and NRM. In comparison to the HCT-CI, PP-based prediction shows significantly higher accuracy in this rather homogeneous cohort of patients. Since proteomics is a new method which has been available only at a few centers, further multicenter analyses are essential to determinate the value of PP-based prediction of complications and outcome in SCT. Disclosures: Metzger: Mosaiques Diagnostics GmbH: Employment.

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