Predictive Value For Patient Outcome Research Articles

Abstract 6826: Comparative analysis of a predictive transcriptomic model and functional gene expression signatures (FGES) for tertiary lymphoid structure (TLS) detection in lung adenocarcinoma (LUAD)

Abstract Background: TLS are recognized as significant biomarkers for patient prognosis and therapy selection. In current clinical practice, TLS are often detected by manual assessment of H&E slides, which has been associated with reproducibility issues. Here, we developed a transcriptomic model using TLS density to stratify LUAD patients into TLS-high and -low groups and compared it with 5 published TLS FGES to assess the predictive value for patient outcomes. Design: A regression model to predict TLS density (units(u)/mm²) was created using RNA expression data and histological mapping of 415 TCGA-LUAD samples. Features were chosen based on differential gene expression analysis of sample groups with low (<Q1, 0.26 u/mm²) and high (>Q3, 2.04 u/mm²) TLS density. The model was trained on 269 samples and independently validated on 146 TCGA and 9 internal samples. The RNA model and five previously reported TLS FGES were compared by Wilcoxon paired test to Spearman’s ρ and F1-scores from bootstrapped validation set. The resulting predictions stratified immunotherapy-treated samples from SU2C-MARK (n=58) and GSE182328 (n=28) into TLS-high and TLS-low groups by Q2 threshold for TLS density (0.78 u/mm²) for further univariate (Kaplan-Meier) and multivariate (Cox model, adjusted for age and sex) analyses for overall survival (OS) with log-rank tests. P-values were adjusted with Bonferroni correction, and 95% confidence intervals (CIs) were provided. Results: Statistically significant upregulated genes in samples with high TLS density included FDCSP, MS4A1, and CXCL13 (logFC ≥ 0.95, FDR<0.01). The transcriptomic model showed confident superiority in correlation with TLS density compared to the best FGES in TCGA samples (ρ=0.53±0.03 vs 0.41±0.03, p<0.001). The TLS model also outperformed the highest performing FGES when stratifying TCGA samples into TLS-high and TLS-low groups (F1=0.73±0.02 vs 0.69±0.02, p<0.005). In the internal cohort, the model demonstrated robust performance (F1=0.76±0.05, ρ=0.81±0.04) and outperformed all FGES except one (FGES F1=0.78±0.05, ρ=0.86±0.05). The TLS-high group defined by the TLS RNA model had a significantly better prognosis on immunotherapy cohorts (p=0.01; 1 year OS 49% for TLS-low vs 70% for TLS-high), whereas no discernible difference in OS was identified for the 5 TLS FGES. The TLS model had a log hazard ratio (logHR) of -3.11 (CI:-5.31,-0.91; p<0.05, Harrell's C-index=0.64), indicative of a stronger association with OS than of the TLS FGES (logHR=-2.11; CI:-4.1,-0.08; p=ns; C-index=0.59). Conclusions: Comparative analysis of the proposed transcriptomic model for TLS detection in LUAD samples demonstrated improved performance metrics and prognostic value compared to previously reported TLS FGES, affirming its potential for guiding therapeutic decision-making. Citation Format: Nadezhda Lukashevich, Daniil Dymov, Aleksandr Sarachakov, Sofya Kust, Anna Love, Ivan Valiev, Dmitry Ivchenkov, Alexander Bagaev, Viktor Svekolkin, Nikita Kotlov, Vladimir Kushnarev. Comparative analysis of a predictive transcriptomic model and functional gene expression signatures (FGES) for tertiary lymphoid structure (TLS) detection in lung adenocarcinoma (LUAD) [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6826.

Expression of mir-25-3p, CARD9 and Surviving in Acute Pancreatitis and Predictive Value for Patient Outcome.

The clinical data of 246 patients with acute pancreatitis who met the inclusion and exclusion criteria in our hospital from May 2018 to May 2020 were collected as the modeling group, and 96 patients were used as the model validation group. To observe the expression of mir-25-3p, CARD9 and Survivin in patients with acute pancreatitis. To analyze the prognostic factors of acute pancreatitis by univariate and multivariate analysis, and to establish and validate the prognostic model of acute pancreatitis. Results: There was no significant difference in general data between the two groups (P>0.05). Of 246 AP patients, 217 survived and 29 died. The APACHEI score, BISAP score, CRP, lipase, lactate, mir-25-3p, CARD9 and Survivin in the survival group were lower than those in the death group, and the differences were statistically significant (P<0.05). There was no significant difference in other indexes (P>0.05). APACHEI score, BISAP score, CRP, lipase, lactate, mir-25-3p, CARD9 and Survivin were included in multivariate logistic regression analysis. Survival =1 and death =0 were the dependent variables. BISAP score, CRP, lipase, lactate, mir-25-3p, CARD9 and Survivin were all protective factors for the survival of AP patients. Log(P)=-1.648×BISAP score -0.045×CRP-0.013× lipase-0.205 × lactate-1.339 × Mir-25-3P-2.701 ×CARD9-1.663×Survivin+43.925. The survival protective factors of AP patients were incorporated into R software to establish the nomogram prediction model.

Correlation of Serum IL-18, BDNF, and IL-1β with Depression and Prognosis after Acute Exacerbation of Chronic Obstructive Pulmonary Disease.

Objective To explore the correlation of serum IL-18, BDNF, and IL-1β with depression and prognosis after acute exacerbation of chronic obstructive pulmonary disease (COPD). Methods By means of retrospective analysis, the data of 240 patients at the acute exacerbation of COPD treated in our hospital (February 2018-February 2021) were analyzed. All patients received conventional treatment 1 d after admission, patients' serological indicators were measured before treatment, and after 30 d of follow-up, the patients were divided into the survival group (SG) and death group (DG) according to their clinical outcomes, the Beck's Depression Inventory (BDI) scores of the surviving patients were investigated, the correlation of IL-18, BDNF, and IL-1β levels with depression was analyzed by R analytics, and the correlation of IL-18, BDNF, and IL-1β levels with prognosis was analyzed by ROC curve analysis. Results The results of 30 d follow-up showed that 220 patients survived (91.7%) and 20 patients died (8.3%). Among the surviving patients, 95 patients had depression and 125 patients did not have depression; the BDI scores of the depressed subjects and the nondepressed subjects were 10.35 ± 1.25 points and 2.06 ± 0.76 points, respectively; significant differences in IL-18, BDNF, and IL-1β levels between SG and DG were observed (P < 0.05); significant differences in IL-18, BDNF, and IL-1β levels between the depressed subjects and the nondepressed subjects were observed (538.43 ± 19.02 vs. 515.32 ± 9.65, 7.54 ± 0.56 vs. 12.11 ± 2.41, and 8.70 ± 0.98 vs. 8.12 ± 0.87; P < 0.001); among the depressed patients, the IL-18 and IL-1β levels were positively correlative with the BDI scores (r = 0.781, r = 0.2583, P < 0.001, P = 0.012), and the BDNF level was negatively correlative with the BDI scores (r = −0.3277, P = 0.001) before treatment; according to the ROC analysis, the AUC (95% CI) of IL-18, BDNF, and IL-1β in predicting prognosis was 0.8770 (0.8281-0.9260), 0.7723 (0.6879-0.8567), and 0.7165 (0.6080-0.8250) (P < 0.05), respectively. Conclusion In regard to the depression in COPD patients after acute exacerbation, IL18 and IL-1β show positive correlation, and BDNF presents negative correlation. All three indicators have predictive value for patient outcome.

Association between serum β2-microglobulin and mortality in Japanese peritoneal dialysis patients: A cohort study.

Higher serum β2-microglobulin (B2M) concentrations are associated with higher mortality in the general population, non-dialyzed chronic kidney disease patients and patients receiving hemodialysis (HD). However, this relationship among patients on peritoneal dialysis (PD) has not been validated. We collected baseline data for 3,011 prevalent PD patients from a nationwide dialysis registry in Japan at the end of 2010. Clinical outcomes for 9 years were then evaluated using the registry at the end of 2011 to 2019. All-cause and cardiovascular (CV) mortality was assessed using Cox regression analysis and competing-risks regression analysis, respectively. We used multiple imputation to deal with missing covariate data. During a median follow-up of 87 months, 2,054 patients transferred to combined therapy with PD and HD or HD directly. A total of 3,011 patients, 1,235 (41.0%) died, including 437 patients (14.5%) from CV causes. Among them, 612 patients died after transfer to other dialysis modalities. Univariate analyses revealed no significant association between serum B2M and mortality, whereas higher serum B2M was independently associated with both all-cause and CV mortalities in adjusted models. However, the significant association between serum B2M and CV mortality disappeared in analysis treating serum B2M as a categorical variable. The effect of serum B2M on all-cause mortality was significantly higher among patients with higher urinary volume and a significant interaction was evident. Using a large-scale registry, we found that serum B2M contributes tenuously but significantly to worse outcome and residual kidney function significantly affects this relationship. On the contrary, serum B2M per se had no predictive value for patient outcome in prevalent PD patients.

Heart rate complexity: An early prognostic marker of patient outcome after cardiac arrest

ObjectiveEarly prognostication in comatose patients after cardiac arrest (CA) is difficult but essential to inform relatives and optimize treatment. Here we investigate the predictive value of heart-rate variability captured by multiscale entropy (MSE) for long-term outcomes in comatose patients during the first 24 hours after CA. MethodsIn this retrospective analysis of prospective multi-centric cohort, we analyzed MSE of the heart rate in 79 comatose patients after CA while undergoing targeted temperature management and sedation during the first day of coma. From the MSE, two complexity indices were derived by summing values over short and long time scales (CIs and CIl). We splitted the data in training and test datasets for analysing the predictive value for patient outcomes (defined as best cerebral performance category within 3 months) of CIs and CIl. ResultsAcross the whole dataset, CIl provided the best sensitivity, specificity, and accuracy (88%, 75%, and 82%, respectively). Positive and negative predictive power were 81% and 84%. ConclusionsCharacterizing the complexity of the ECG in patients after CA provides an accurate prediction of both favorable and unfavorable outcomes. SignificanceThe analysis of heartrate variability by means of MSE provides accurate outcome prediction on the first day of coma.

Added value of the PG-SGA in detection of malnutrition in overweight and obese hospitalized patients

AbstractTraditional malnutrition screening instruments, such as the Malnutrition Universal Screening Tool (MUST), strongly rely on criteria regarding low BMI and critical weight loss for risk assessment. In an increasingly overweight and obese population, this may result in underdetection of malnutrition. The Patient-Generated Subjective Global Assessment (PG-SGA) was developed in the broader context of anabolic competence and includes assessment of other aspects of malnutrition, such as nutrition impact symptoms and metabolic demand. We therefore aimed to compare MUST and PG-SGA in assessing prevalence of malnutrition in overweight and obese hospitalized patients. We measured risk for malnutrition (MUST score: 0 = low risk, 1 = medium risk, ≥ 2 = high risk) and nutritional status (PG-SGA Categories: A = well nourished, B = moderate/suspected malnutrition, C = severe malnutrition) at admission, in adult patients, on four hospital wards of a university hospital. We compared results for patients with BMI &lt; 25 kg/m2 and overweight or obese patients (BMI ≥ 25 kg/m2). Data were obtained in 387 patients (age 59 ± 16 years, 52% male). BMI was 27.1 ± 5.6 kg/m2, 35% was overweight and 26% was obese. According to MUST, 16% of patients had risk for malnutrition (MUST score ≥ 1), while according to PG-SGA 31% of patients were malnourished (PG-SGA Stage B/C). In patients with BMI &lt; 25 kg/m2 (N = 153), MUST identified 31% as at risk for malnutrition, while PG-SGA assessed 39% as malnourished. In patients with BMI ≥ 25 kg/m2 (N = 234), MUST identified 6% as at risk for malnutrition, while PG-SGA assessed 26% as malnourished. Of the 60 malnourished overweight or obese patients according to the PG-SGA, 52 (87%) were categorized as low risk by the MUST. According to assessment by PG-SGA, a quarter of overweight or obese patients is malnourished at hospital admission. Most of these patients are not identified as having risk for malnutrition by the screening tool MUST. Future research is needed to evaluate the current results in relation to predictive value for patient outcomes, and to further optimize hospital nutritional care policies.

Development of an Algorithm to Predict Mortality in Patients With Sepsis and Coagulopathy.

Sepsis is a systemic response to infection with a high rate of mortality and complex pathophysiology involving inflammation, infection response, hemostasis, endothelium, and platelets. The purpose of this study was to develop an equation incorporating biomarker levels at intensive care unit (ICU) admission to predict mortality in patients with sepsis, based on the hypothesis that a combination of biomarkers representative of multiple physiological systems would provide improved predictive value. Plasma samples and clinical data were collected from 103 adult patients with sepsis at the time of ICU admission. Biomarker levels were measured using commercially available methods. A 28-day mortality was used as the primary end point. Stepwise linear regression modeling was performed to generate a predictive equation for mortality. Differences in biomarker levels between survivors were quantified using the Mann-Whitney test and the area under the receiver operating curve (AUC) was used to describe predictive ability. Significant differences (P < .05) were observed between survivors and nonsurvivors for plasminogen activator inhibitor 1 (AUC = 0.70), procalcitonin (AUC = 0.77), high mobility group box 1 (AUC = 0.67), interleukin (IL) 6 (AUC = 0.70), IL-8 (AUC = 0.70), protein C (AUC = 0.71), angiopoietin-2 (AUC = 0.76), endocan (AUC = 0.58), and platelet factor 4 (AUC = 0.70). A predictive equation for mortality was generated using stepwise linear regression modeling, which incorporated procalcitonin, vascular endothelial growth factor, the IL-6:IL-10 ratio, endocan, and platelet factor 4, and demonstrated a better predictive value for patient outcome than any individual biomarker (AUC = 0.87). The use of mathematical modeling resulted in the development of a predictive equation for sepsis-associated mortality with performance than any individual biomarker or clinical scoring system which incorporated biomarkers representative of multiple systems.

Diagnostic Parameters of Adenoviremia in Pediatric Stem Cell Transplant Recipients.

Despite recent progress in the diagnostic risk assessment of human adenovirus (HAdV) infections in immunocompromised patients, clinical complications mediated by these viruses continue contributing to significant morbidity and mortality, particularly in the pediatric hematopoietic allogeneic stem cell transplant (HSCT) setting. Current data highlight the importance of monitoring stool samples to assess the risk of invasive HAdV infections in children undergoing HSCT. The advent of novel, more effective antiviral treatment options might permit successful virus control even at the stage of systemic infection, thus increasing the interest in optimized HAdV monitoring in peripheral blood (PB). We have screened over 300 pediatric HCST recipients by serial monitoring of stool and PB specimens, and identified 31 cases of invasive HAdV infection by quantitative pan-adenovirus RQ-PCR analysis of consecutive PB specimens. The diagnostic parameters assessed included HAdV peak levels (PL) and the time-averaged area under the curve (AAUC) of virus copy numbers. The predictive value for patient outcome reflected by non-relapse and HAdV-related mortality was determined. The patients were assigned to quartiles based on their PL and AAUC, and the readouts were highly correlated (p < 0.0001). Non-relapse mortality in patients by AAUC quartile (lowest to highest) was 26, 50, 75, and 86%, respectively, and AAUC was strongly correlated with non-relapse mortality (p < 0.0001), while the association between PL and non-relapse mortality was less pronounced (p = 0.013). HAdV-related mortality was absent or very low in patients within the two lower quartiles of both PL and AAUC, and increased to ≥70% in the upper two quartiles. Despite the significant correlation of PL and AAUC with patient outcome, it is necessary to consider that the risk of non-relapse mortality even within the lowest quartile was still relatively high, and it might be difficult therefore to translate the results into differential treatment approaches. By contrast, the correlation with HAdV-related mortality might permit the identification of a low-risk patient subset. Nevertheless, the well-established correlation of HAdV shedding into the stool and intestinal expansion of the virus with the risk of invasive infection will expectedly remain an essential diagnostic parameter in the pediatric HSCT setting.

Development of an Algorithm to Predict Mortality in Patients with Sepsis and Coagulopathy

Introduction: Sepsis is a systemic response to infection which results in a high rate of mortality worldwide. The pathophysiology of sepsis is complex; although sepsis is often defined on the basis of the overwhelming host inflammatory response, this disease process also involves infection response, hemostatic dysregulation, endothelial dysfunction, and platelet activation. Improved ability to predict mortality in sepsis patients would have implications for the appropriate administration of therapies in this population. Several approaches to this problem have been tried, focused on clinical scoring systems or biomarkers of a single physiological system, with modest success. The purpose of this study was to develop an equation incorporating biomarker levels at intensive care unit (ICU) admission to predict mortality in patients with sepsis, based on the hypothesis that a combination of biomarkers representative of multiple physiological systems would provide improved predictive value over a single biomarker or system.Materials and Methods: Plasma samples were collected from 103 adult patients with sepsis at the time of ICU admission. Levels of 28 biomarkerss were measured using commercially available, standardized methods. Clinical data, including the ISTH overt DIC score, SOFA score, and APACHE II score was also collected. 28-day mortality was used as the primary endpoint. Stepwise linear regression modeling was performed. This modeling approach used an iterative mathematical process to select the most relevant biomarkers to include in an equation to predict patient survival vs. non-survival.Results: Differences in biomarker levels between survivors were quantified and using the Mann-Whitney test and the area under the receiver operating curve (AUC) was used to describe predictive ability. Significant differences (p<0.05) were observed between survivors and non-survivors for PAI-1 (AUC=0.70), procalcitonin (AUC=0.77), HMGB-1 (AUC=0.67), IL-6 (AUC=0.70), IL-8 (AUC=0.70), protein C (AUC=0.71), Angiopoietin-2 (AUC=0.76), endocan (AUC=0.58), and platelet factor 4 (AUC=0.70). A predictive equation for mortality was generated using stepwise linear regression modeling. This model incorporated procalcitonin, VEGF, the IL-6:IL-10 ratio, endocan, and PF4, and demonstrated a better predictive value for patient outcome than any individual biomarker (AUC=0.87). This supports the hypothesis that a panel of biomarkers representative of multiple physiological systems would perform better than biomarkers representative of a single system. This model accounts for infection response (procalcitonin), inflammation and the balance of pro- vs. anti-inflammatory factors (VEGF, IL-6:IL-10 ratio), endothelial function (endocan), and platelet function (PF4). Incorporation of clinical data such as SOFA or APACHE II scores did not result in improved model performance; the model developed including this information incorporated white blood cell count, APACHE II score, and procalcitonin had an AUC of 0.84.Conclusions: The use of a mathematical modeling approach resulted in the development of a predictive equation for sepsis-associated mortality with better accuracy than any individual biomarker or clinical scoring system. In addition, this equation incorporates biomarkers representative of multiple physiological systems that are involved in the pathogenesis of sepsis and may better represent the complete pathophysiology of this syndrome to predict the high mortality that exists in these patients.[MTR1]Would add a sentence on the mortality endpoint DisclosuresNo relevant conflicts of interest to declare.

Integrating a Touchscreen-Based Assessment and Screening Tool for Adults with Multiple Myeloma

Background: More than 60% of multiple myeloma (MM) diagnoses and nearly 75% of deaths occur in patients over 65 years old. Because older adults (OAs) experience more treatment-related toxicities, treatment disruptions or dose reductions may be based on age and performance status alone, despite their poor predictive value for patient outcomes. Comprehensive Geriatric Assessment (CGA), including frailty indices, has shown predictive validity for toxicity and survival in OAs with MM, but is not routinely used in practice due to time and complexity, a lack of clarity about optimal tools and technologies to implement them, and clinician knowledge gaps on how to incorporate CGA into decision-making and care.Purpose: This project aims to address these gaps by pilot testing a tablet-based modified (m)CGA in 120 patients that presents compiled CGA results, including a frailty score, back to clinicians interacting with patients at the time of a treatment decision. Outcomes include feasibility, usability, utility, and impact on treatment decision-making, from both patient and provider perspectives. Pre-study implementation processes and milestones, including development of the mCGA, clinical workflow planning processes, training and other site-initiation activities are presented herein.Methods: The mCGA was developed using an iterative and dynamic consensus-driven process that included: 1) literature review and expert input to identify CGA domains for potential inclusion and 2) consensus building within a multi-disciplinary panel of gero-oncology experts, nurse scientists, and psychometricians. Domains and measures were selected based on predictive ability, length, and ability to administer via patient self-report so as to reduce clinician assessment burden. Study training and implementation procedures were developed using the same approach, as well as through workflow analysis and clinical team consensus building at the participating sites.Results: The Palumbo frailty index (FI) was chosen as the core of the mCGA tool given correlation with clinical outcomes specifically in OAs with MM. In addition to the 4 mGA measures comprising the Palumbo FI (age, comorbidity, ADL, and IADL), other GA variables were also chosen based on their strong predictive ability, clinical feasibility, and relevance to the MM population. This summary of results is displayed for ease of provider use within the Carevive dashboard (see Figure 1). Given prevalent knowledge gaps in use of CGA for MM treatment decision-making and care, a certified medical education self-study course was developed for training prior to the study intervention. Four geographically-dispersed academic and community hospitals who treat high volumes of diverse MM patients are participating to date. All 4 sites developed a process for ensuring treating providers would have easy access to the platform.Conclusions: Real-world, comprehensive and innovative solutions, combining education, geriatric assessment (GA) tools to determine a patient's fit/frailty status, realistic clinical work flow processes, and technology tools are needed to support and enhance treatment-decision making for patients with MM as well as their providers. [Display omitted] DisclosuresWildes:Carevive Systems: Consultancy. Stricker:Carevive Systems, Inc.: Employment, Equity Ownership. Dudley:Carevive Systems, Inc.: Consultancy. Harris:Carevive Systems, Inc.: Consultancy. Nathwani:Carevive Systems, Inc.: Research Funding. Brant:Carevive Systems, Inc.: Research Funding. Kurtin:Carevive Systems, Inc.: Research Funding. Hurria:Boehringer Ingelheim Pharmaceuticals: Consultancy; GTx, Inc: Consultancy; Carevive: Consultancy; Celgene: Other: Research; Optum Health Care SOlutions: Consultancy, Other: Conference panel, research; Sanofi: Consultancy; Novartis: Other: Research.

Genomic Analysis of Salmonella enterica Serovar Typhimurium Characterizes Strain Diversity for Recent U.S. Salmonellosis Cases and Identifies Mutations Linked to Loss of Fitness under Nitrosative and Oxidative Stress

ABSTRACTSalmonella enterica serovar Typhimurium is one of the most common S. enterica serovars associated with U.S. foodborne outbreaks. S. Typhimurium bacteria isolated from humans exhibit wide-ranging virulence phenotypes in inbred mice, leading to speculation that some strains are more virulent in nature. However, it is unclear whether increased virulence in humans is related to organism characteristics or initial treatment failure due to antibiotic resistance. Strain diversity and genetic factors contributing to differential human pathogenicity remain poorly understood. We reconstructed phylogeny, resolved genetic population structure, determined gene content and nucleotide variants, and conducted targeted phenotyping assays for S. Typhimurium strains collected between 1946 and 2012 from humans and animals in the United States and abroad. Strains from recent U.S. salmonellosis cases were associated with five S. Typhimurium lineages distributed within three phylogenetic clades, which are not restricted by geography, year of acquisition, or host. Notably, two U.S. strains and four Mexican strains are more closely related to strains associated with human immunodeficiency virus (HIV)-infected individuals in sub-Saharan Africa than to other North American strains. Phenotyping studies linked variants specific to these strains in hmpA and katE to loss of fitness under nitrosative and oxidative stress, respectively. These results suggest that U.S. salmonellosis is caused by diverse S. Typhimurium strains circulating worldwide. One lineage has mutations in genes affecting fitness related to innate immune system strategies for fighting pathogens and may be adapting to immunocompromised humans by a reduction in virulence capability, possibly due to a lack of selection for its maintenance as a result of the worldwide HIV epidemic.

Serum Profile Of Multiple Cytokines and Adhesion Molecules In Newly Diagnosed AML Patients Differs In Those Who Did Not Reach Complete Remission After Anthracycline/Cytarabine Induction Therapy

BackgroundCytokines and adhesion molecules have been studied as markers of immune system activation in various diseases including AML/MDS. Cytokines are soluble molecules taking part in intercellular communication with a specific role in cell proliferation and differentiation control. Further knowledge gained from multiple cytokine and adhesion molecule analysis should allow better diagnosis and disease management. AimsThe aim of our study was to evaluate baseline serum levels of multiple cytokines and adhesion molecules in Caucasian population AML patients and compare it with standard prognostic indicators in patients with AML. MethodsA total of 28 consecutive newly diagnosed AML patients (11 males, 17 females, age 21 to 71 years, mean 52.3 ± 12.1, median 55.4 years, 8 with better risk, 13 with intermediate risk, 7 with high risk according to cytogenetics and molecular genetics) were administered 3+7 induction regimen with escalated dose of daunorubicin 90mg/m2. We evaluated serum levels of the following 22 cytokines and adhesion molecules: interleukins (IL-1 alpha, IL-1 beta, IL-2, IL-3, IL-4, IL-6, IL-7, IL-8, IL-10, IL-12, IL-13, IL-23), vascular endothelial growth factor (VEGF), tumor necrosis factor-alpha (TNF-alpha), interferon-gamma (IFN-gamma), epidermal growth factor (EGF), monocyte chemotactic protein-1 (MCP-1), E-selectin, L-selectin, P-selectin, intercellular adhesion molecule-1 (ICAM-1), vascular cell adhesion molecule-1 (VCAM-1). All biomarkers were measured by biochip array technology on Evidence Investigator analyzer (Randox) at the diagnosis of AML and compared with standard prognostic indicators in AML. Probability values (p) < 0.05 were considered statistically significant. ResultsAs there was no significant difference between younger and elderly patients, we evaluated the cohort as a whole. Comparing serum cytokine and adhesion molecule levels in patients who did not achieve CR after induction therapy (n=6, 21.5%) to those who achieved CR (n=22, 78,5%) a statistically significant increase in serum IL-2 (5.42 ± 5.42 ng/L vs. 2.02 ± 1.84 ng/L; p < 0,05), IL-7 (11.71 ± 10.77 ng/L vs. 3.50 ± 1.51 ng/L; p < 0.05), IL-8 (241.9 ± 225.3 ng/L vs. 34.31 ± 25.47 ng/L; p < 0.005), IL-10 (7.74 ± 6.83 ng/L vs. 2.83± 2.68 ng/L; p < 0.05) was found. Both groups differed from healthy individuals in serum levels of IL-4, IL-6, IL-13, VCAM-1, ICAM-1, E-selectin and L-selectin. We found moderate inverse correlation between overall survival and levels of VCAM-1 and E-selectin. There was no significant difference in cytokines and adhesion molecules levels among established prognostic subgroups in AML. ConclusionsThe results in general are in agreement with outcome of our pilot trial. Compared with the other studies of cytokine levels in newly diagnosed AML, our data indicate different conclusions. IL-2, IL-4 and IL-10 were more likely to be higher in those who attained remission (Kornblau et al., Blood 2010). We did not find association between IL-6 and IL-10 levels and survival in our studied group (Correa et al, Cytokine 2013). On the other hand we documented inverse correlation between levels of some adhesion molecules and overall survival. Whether these alterations depend on the studied population is not known definitely. To assess their predictive value for patient outcome, further studies in a larger number of patients is necessary. AcknowledgmentThe work was supported by Specific research project “Analysis of defined prognostic factors in acute myeloid leukemia” (FMHS) and by a long-term organisation development plan 1011 (FMHS). Disclosures:No relevant conflicts of interest to declare.

The New Comorbidity Index for Predicting Survival in Elderly Dialysis Patients: A Long-Term Population-Based Study

BackgroundThe worldwide elderly (≥65 years old) dialysis population has grown significantly. This population is expected to have more comorbid conditions and shorter life expectancies than the general elderly population. Predicting outcomes for this population is important for decision-making. Recently, a new comorbidity index (nCI) with good predictive value for patient outcomes was developed and validated in chronic dialysis patients regardless of age. Our study examined the nCI outcome predictability in elderly dialysis patients.Methods and FindingsFor this population-based cohort study, we used Taiwan's National Health Insurance Research Database of enrolled elderly patients, who began maintenance dialysis between January 1999 and December 2005. A total of 21,043 incident dialysis patients were divided into 4 groups by nCI score (intervals ≤3, 4–6, 7–9, ≥10) and followed nearly for 10 years. All-cause mortality and life expectancy were analyzed. During the follow-up period, 11272 (53.55%) patients died. Kaplan-Meier curves showed significant group difference in survival (log-rank: P<0.001). After stratification by age, life expectancy was found to be significantly longer in groups with lower nCI scores.ConclusionThe nCI, even without the age component, is a strong predictor of mortality in elderly dialysis patients. Because patients with lower nCI scores may predict better survival, more attention should paid to adequate dialysis rather than palliative care, especially in those without obvious functional impairments.

English

Introduction The worldwide elderly (≥65 years old) dialysis population has grown significantly and is expected to have more comorbid conditions and shorter life expectancies than the general elderly population. Predicting outcomes for this population is important for decision-making. There are some studies about comorbidity scoring systems for predicting survival in dialysis patients. To establish a simple and practicable scoring system for predicting survival in the elderly population is increasingly important for physicians worldwide. The aim of this critical review was to discuss the comorbidity scoring systems for predicting survival in elderly dialysis patients and additional management strategies. Conclusion Of the current comorbidity scoring systems for predicting survival in dialysis patients, the Charlson comorbidity index is considered the most predictive one than any other commonly used comorbidity scoring systems. Recently, a new comorbidity index with good predictive value for patient outcomes was developed and validated in chronic dialysis patients. The new comorbidity index, even without the age component, is a strong predictor of mortality in elderly dialysis patients. Using one or both of these scoring systems, a physician may be able to provide some helpful objective opinions and suggestions to elderly patients who must choose between initiating and not initiating dialysis.

Colorectal cancer classifications

Two new studies describe molecular classifications of colorectal cancer that show predictive value for patient outcome and therapy response.

Haemostatic and cranial computed tomography characteristics in patients with acute and delayed coagulopathy after isolated traumatic brain injury

Primary objective: To investigate whether the development of coagulopathy at different stages after isolated traumatic brain injury (TBI) is associated with distinct cranial computed tomography characteristics.Research design: Retrospective cohort study in 226 patients with moderate-to-severe isolated TBI who were categorized as subjects without coagulopathy or with acute temporary, acute sustained or delayed coagulopathy.Methods and procedures: Coagulopathy was defined as an activated partial thromboplastin time >40 seconds and/or prothrombin time (PT) >1.2 and/or platelet count <120*109 l−1. Cranial CT scans were assigned to the six-point Traumatic Coma Data Bank (TCDB) CT-classification.Main outcomes and results: Coagulopathy occurred in 44% of patients in the first 24-hours post-trauma. Patients with acute, sustained coagulopathy showed a prolonged PT (1.64 ± 0.89) when compared to patients without (1.03 ± 0.07), acute temporary (1.27 ± 0.22) or delayed coagulopathy (1.08 ± 0.06; p < 0.05). Patients with acute temporary or delayed coagulopathy had the worst TCDB CT classification scores, while mortality rates were the highest in patients with sustained or delayed coagulopathy.Conclusions: Not only the mere presence of coagulopathy, but also the course of haemostatic alterations following neurotrauma may hold predictive value for patient outcome, irrespective of the severity level of cerebral injury.

Expressed Emotion in Families of Patients with Eating Disorders: A Review of the Literature

Objective: To review studies assessing Expressed Emotion among parents/relatives of patients with Anorexia Nervosa and Bulimia Nervosa. Method: A systematic computerized search was performed in Medline complemented by a manual search of the literature for all studies published between 1981 and 2011. A total of 27 papers in English were reviewed for their methods, instruments used and results. Results: Comparisons were not easy due to methodological disparities in assessments. Levels of Expressed Emotion depend concurrently on parental characteristics (parent assessed, social status and psychological distress), patient characteristics (age, social adjustment) and Eating Disorders characteristics (type of Eating Disorders, duration and severity of illness and previous treatment). Expressed Emotion has a predictive value for patient outcome and for compliance with/ and implication in treatment. Levels of Expressed Emotions vary with the parent assessed. The crosscultural aspects of Expressed Emotion in Eating Disorders are not widely documented. Discussion: Both positive and negative aspects of Expressed Emotion are important therapeutic targets and further research on this topic is needed.

Pulmonary Arterial Hypertension: MR Imaging-derived First-Pass Bolus Kinetic Parameters Are Biomarkers for Pulmonary Hemodynamics, Cardiac Function, and Ventricular Remodeling

To prospectively compare contrast material-enhanced (CE) magnetic resonance (MR) imaging-derived right-to-left ventricle pulmonary transit time (PTT), left ventricular (LV) full width at half maximum (FWHM), and LV time to peak (TTP) between patients with pulmonary arterial hypertension (PAH) and healthy volunteers and to correlate these measurements with survival markers in patients with PAH. This HIPAA-compliant study received institutional review board approval. Written informed consent was obtained from all participants. Forty-three patients (32 with PAH [29 women; median age, 55.4 years], 11 with scleroderma but not PAH [seven women; median age, 58.9 years]) underwent right-sided heart catheterization and 3-T CE cardiac MR imaging. Eighteen age- and sex-matched healthy control subjects (12 women; median age, 51.7 years) underwent only CE MR imaging. A short-axis saturation-recovery gradient-echo section was acquired in the basal third of both ventricles, and right-to-left-ventricle PTT, LV FWHM, and LV TTP were calculated. Statistical analysis included Kruskal-Wallis test, Wilcoxon rank sum test, Spearman correlation coefficient, multiple linear regression analysis, and Lin correlation coefficient analysis. Patients had significantly longer PTT (median, 8.2 seconds; 25th-75th percentile, 6.9-9.9 seconds), FWHM (median, 8.2 seconds; 25th-75th percentile, 5.7-11.4 seconds), and TTP (median, 4.8 seconds; 25th-75th percentile, 3.9-6.5 seconds) than did control subjects (median, 6.4 seconds; 25th-75th percentile, 5.7-7.1 seconds; median, 5.2 seconds; 25th-75th percentile, 4.1-6.1 seconds; median, 3.2 seconds; 25th-75th percentile, 2.8-3.8 seconds, respectively; P < .01 for each) and subjects with scleroderma but not PAH (median, 6.5 seconds; 25th-75th percentile, 5.6-7.0 seconds; median, 5.0 seconds; 25th-75th percentile, 4.0-7.3 seconds; median, 3.6 seconds; 25th-75th percentile, 2.7-4.0 seconds, respectively; P < .02 for each). PTT, LV FWHM, and LV TTP correlated with pulmonary vascular resistance index (P < .01), right ventricular stroke volume index (P ≤ .01), and pulmonary artery capacitance (P ≤ .02). In multiple linear regression models, PTT, FWHM, and TTP were associated with mean pulmonary arterial pressure and cardiac index. CE MR-derived PTT, LV FWHM, and LV TTP are noninvasive compound markers of pulmonary hemodynamics and cardiac function in patients with PAH. Their predictive value for patient outcome warrants further investigation.

Multicenter Evaluation of the Course of Coagulopathy in Patients with Isolated Traumatic Brain Injury: Relation to CT Characteristics and Outcome

This prospective multicenter study investigated the association of the course of coagulation abnormalities with initial computed tomography (CT) characteristics and outcome in patients with isolated traumatic brain injury (TBI). Patient demographics, coagulation parameters, CT characteristics, and outcome data of moderate and severe TBI patients without major extracranial injuries were prospectively collected. Coagulopathy was defined as absent, early but temporary, delayed, or early and sustained. Delayed/sustained coagulopathy was associated with a higher incidence of disturbed pupillary responses (40% versus 27%; p<0.001) and higher Traumatic Coma Data Bank (TCDB) CT classification (5 (2-5) versus 2 (1-5); p=0.003) than in patients without or with early, but short-lasting coagulopathy. The initial CT of patients with delayed/sustained coagulopathy more frequently showed intracranial hemorrhage and signs of raised intracranial pressure (ICP) compared to patients with early coagulopathy only. This was paralleled by higher in-hospital mortality rates (51% versus 33%; p<0.05), and poorer 6-month functional outcome in patients with delayed/sustained coagulopathy. The relative risk for in-hospital mortality was particularly related to disturbed pupillary responses (OR 8.19; 95% CI 3.15,21.32; p<0.001), early, short-lasting coagulopathy (OR 6.70; 95% CI 1.74,25.78; p=0.006), or delayed/sustained coagulopathy (OR 5.25; 95% CI 2.06,13.40; p=0.001). Delayed/sustained coagulopathy is more frequently associated with CT abnormalities and unfavorable outcome at 6 months after TBI than early, short-lasting coagulopathy. Our finding that not only the mere presence but also the time course of coagulopathy holds predictive value for patient outcome underlines the importance of systematic hemostatic monitoring over time in TBI.

The clinical application of 18F‐fluorodeoxyglucose positron emission tomography to predict survival in patients with operable esophageal cancer

Metabolic tumor activity using (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) was believed to have a predictive value for patient outcome in malignancies. The objective of the current study was to assess the prognostic effectiveness of the highest standardized uptake value (SUV) in the primary or regional area (peak SUV) and the number of PET-positive lymph nodes in esophageal cancer. The authors retrospectively reviewed their experience with 184 consecutive esophageal cancer patients imaged preoperatively using FDG-PET scanning. The median peak SUV was 4.5 (range, 1.4-21.9). The survival curve was analyzed using the median peak SUV as the cutoff value. Comparison of each group and clinicopathologic characteristics revealed significant associations between peak SUV and each of the following factors: tumor status (P < .001), lymph node status (P < .001), metastatic status (P < .05), stage of disease (P < .001), number of PET-positive lymph nodes (P < .001), and the number of histologically positive lymph nodes (P < .001). The 5-year overall survival (OS) rate for patients having FDG uptake with a peak SUV > or =4.5 was 47% and that for patients with a peak SUV <4.5 was 76% (P < .0001). On multivariate survival analysis using the Cox proportional hazards model, peak SUV and the number of PET-positive lymph nodes were found to be independent predictive factors for OS. The number of PET-positive lymph nodes was a single prognostic factor predicting both disease-free survival and OS. Pretreatment PET cannot only potentially diagnose the extent of disease, but also may be predictive of patient survival after esophageal cancer resection.