Prognostic Indicator Of Outcome Research Articles

Prognostic indicators of outcome in nonambulatory beef cattle presented to 2 referral hospitals: A retrospective study of 63 cases.

Down cow syndrome is commonly described in dairy cattle. The diagnosis and treatment of nonambulatory cattle is challenging and prognostic indicators of this condition in beef cattle have not been determined. Evaluate records of beef cattle (≥2 years of age) presented to 2 referral hospitals for inability to stand and identify prognostic indicators for survival to discharge. Sixty-three adult beef cattle treated for inability to stand at 2 referral hospitals. Medical records of 63 beef cattle presented for inability to stand between January 2010 and December 2022 were retrospectively analyzed. Continuous and categorical variables were included in univariate and multivariate regression models to evaluate their association with outcome. Of 63 animals included in the study, 19% (12/63) were discharged, and the remaining 81% (n = 51) either died (11.1%) or were euthanized (69.8%). The odds of being discharged increased with each additional day of hospitalization (odds ratio [OR], 2.66; 95% confidence interval [CI], 1.39-6.89) and with each additional flotation therapy session (OR, 2.108; 95% CI, 1.209-4.219). Down beef cattle with a diagnosis of calving peripheral nerve paralysis and capable of walking out the tank after the first flotation session were 6.66 (95% CI, 1.58-35.51) and 30 (95% CI, 4.4-614.98) times more likely to be discharged compared with cattle that had other diagnoses and those that were unable to walk out the tank, respectively. Treatment of nonambulatory beef cattle carries a poor prognosis. Practitioners can use information from our study as a guide for treatment or euthanasia decisions of nonambulatory beef cattle.

Total Bilirubin Yields Prognostic Information Following a Myocardial Infarction in the Elderly.

Total bilirubin consists of an unconjugated form, solubilized by its binding to albumin, and a conjugated form representing a minor part of the circulating bilirubin. As total bilirubin in physiological concentrations is a powerful antioxidant, its concentration gradient may reflect the health status of an individual, and serve as a prognostic indicator of outcome in primary and secondary cardiovascular disease prevention. The aim of this study was to assess the association between total bilirubin and incident cardiovascular events following a myocardial infarction. Total bilirubin in serum was measured at baseline 2-8 weeks after hospitalization for an MI in 881 patients, aged 70 to 82 years, included in the OMEMI (Omega-3 Fatty acids in Elderly with Myocardial Infarction) study, where patients were followed-up for up to 2 years. The first major adverse clinical event (MACE) was the primary endpoint and consisted of nonfatal MI, unscheduled coronary revascularization, stroke, hospitalization for heart failure or all-cause death. As total bilirubin was non-normally distributed, log-transformed values and quartiles of bilirubin were analyzed using Cox regression models. The median (Q1, and Q3) baseline concentration of bilirubin was 11 (9, and 14) µmol/L, and higher log-transformed concentrations were associated with male sex, lower New York Heart Association (NYHA) class and non-smoking. MACE occurred in 177 (20.1%) patients during the follow-up. Higher concentrations of bilirubin were associated with a lower risk of MACE: HR 0.67 (95%CI 0.47-0.97) per log-unit increase, p = 0.032. Patients in the lowest quartile of bilirubin (<9 µmol/L) had the highest risk with HR 1.61 (95%CI 1.19-2.18), p = 0.002, compared to quartiles 2-4. This association remained significant even after adjusting for age, sex, body mass index (BMI), smoking status, NYHA class and treatment allocation: HR 1.52 (1.21-2.09), p = 0.009. Low concentrations of bilirubin (<9 µmol/L) are associated with increased nonfatal cardiovascular events or death in elderly patients with a recent myocardial infarction.

Admission hyperglycaemia as a prognostic indicator of outcome in major trauma patients at Bugando Medical Centre, Mwanza, Tanzania

Background: Admission hyperglycemia has been reported to be associated with poor outcomes among patients with major trauma. However, most of the available literature on this subject has been conducted in the developed world. This study aimed to determine the association between admission hyperglycemia and the outcome of major trauma patients admitted to Bugando Medical Centre.&#x0D; Methods: This was a prospective cohort study, involving major trauma patients admitted to Bugando Medical Centre (BMC) within 6 months from Sept 2017 to February 2018. The exposure was admission hyperglycemia (&gt;11.1mmol/l) and non-exposure was normoglycemia (≤11.1mmol/l).&#x0D; Results: A total of 217 patients (M: F ratio = 4.1: 1) were recruited. Their ages ranged from 4 to 97 years with a median age of 31 years. Out of 217 patients, 106 (48.8%) were hyperglycemic and the remaining 111(51.2%) were normoglycemic. The overall median days of length of hospital stay (LOS) was 15 days. There was no statistically significant association between admission hyperglycemia and LOS (p =0.875). In this study, 73 patients died giving a mortality of 33.6%. Patients with admission hyperglycemia (&gt;11.1mmol/l) had significantly higher mortality as compared to normoglycemic patients (≤11.1mmol/l) (p &lt; 0.001).&#x0D; Conclusion: This study found that admission hyperglycemia was statistically significantly associated with increased mortality among major trauma patients at BMC. Therefore, there is a need to institute regular monitoring of blood sugar levels among these patients and give appropriate treatment to those found with elevated blood sugar levels.

Prognostic significance of Naples prognostic score in non-small-cell lung cancer patients with brain metastases.

Aims: The authors aimed to evaluate the prognostic value of Naples prognostic score (NPS) in advanced non-small-cell lung cancer patients with brain metastases. Materials & methods: A total of 186 consecutive advanced non-small-cell lung cancer patients were retrospectively analyzed. Kaplan-Meier survival analysis and Cox proportional regression models were used to assess the significance of NPS in overall survival and disease-free survival. Results: Multivariate Cox proportional regression analysis revealed that NPS was a significant independent predictive indicator for overall survival (hazard ratio: 1.897; 95% CI: 1.184-3.041; p=0.008) and disease-free survival (hazard ratio: 2.169; 95% CI: 1.367-3.44; p=0.001). Conclusion: NPS was a powerful prognostic indicator for outcome in advanced non-small-cell lung cancer patients with brain metastases.

POS-506 ROLE OF PLASMAPHERESIS IN RAT KILLER PASTE POISONING

Yellow phosphorus containing rat killer paste causes toxic hepatitis and coagulopathy in humans. It is a common mode of self-harm in a developing country like India. Till date, only liver transplant is the definitive treatment of fulminant liver failure caused by rat killer paste poison. Plasmapheresis replaces the main functions of the failing liver and removes proinflammatory cytokines that are responsible for multi-organ failure. The replacement fluid replenishes the coagulation factors, albumin and immunoglobulins. The complete process improves the microenvironment of the liver, which in turn accelerates the regeneration and helps in the functional recovery. In this study, we have tried plasmapheresis as an innovative approach for the management of liver failure cases due to rat killer paste poisoning. This prospective study was conducted in Madurai Medical College. The dialysis machine used was 4008 S Fresenius and the filter used was Plasma Flux P2 filter. 76 cases (Male-47, Female-29) with a definite history of rat killer paste poisoning who had INR more than 3, hepatic encephalopathy and 10-fold elevation in the liver enzymes were taken up for plasmapheresis and the outcomes compared. Pre and post plasmapheresis liver function tests (LFTs) and coagulation profile were compared, and Model for End stage Liver Disease (MELD) score was calculated. Delta MELD was calculated as the difference between pre and post plasmapheresis MELD score. The population was subjected to a minimum of 1 session and a maximum of 3 sessions of plasmapheresis. The replacement fluid was Fresh Frozen Plasma (FFP) according to the body weight. All the patients were also treated with iv glutathione and N-Acetyl cysteine. The median age was 23 years (19-32) (Median with Interquartile Range). The overall survival rate was 63.2 %. 88.2 % of the population had hyponatremia (survivors- 131.5 mEq/L, non-survivors- 129.57 mEq/L), which was found to be statistically significant with regards to outcome (p <0.001). Incidence of hypokalemia, leucopenia and thrombocytopenia were 51.3%, 52.6% and 47.4% respectively, though not statistically significant. Comparison of the pre and post plasmapheresis LFTs were found to be significant to outcome (p-0.001) [Total Bilirubin (12.4mg/dl, 6.8mg/dl), SGOT (1126 IU/L, 108 IU/L), SGPT (876 IU/L, 116 IU/L), PT (51.1s, 18.4s), INR (4.6, 1.5), APTT (48s, 30.2s)]. Median Delta MELD was found to be 12.08 in survivors, whereas it was 8.7 in non survivors, and was found to be statistically significant with regards to outcome (p- 0.001). The total number of plasmapheresis sessions conducted also correlated with outcome (p-0.001). The Median Survival Time in non-survivors was 199.585 hours (95% Confidence Interval). Plasmapheresis can be a therapeutic option for the treatment for acute liver failure due to rat killer paste poisoning. This is supported by the fact that there is a significant improvement in the liver functions and the coagulation parameters post plasmapheresis. Delta MELD may be used as a prognostic indicator of outcome.

Abstract PR-05: Leveraging graphs to do novel hypothesis and data-driven research using multiplex immunofluorescence images

Abstract Characterization of the location and phenotype of cells in the tumor microenvironment (TME) is important to inform the development and monitoring of anti-cancer therapeutic interventions, especially immunotherapies designed to stimulate the immune system to have an anti-cancer effect. Multiplex immunofluorescence (mIF) imaging is being increasingly employed to simultaneously label multiple cell types and subtypes in the tumor microenvironment, but interpretation of these images to gain a robust understanding of tumor and immune cell interactions remains a complicated and challenging process. The rich phenotypic information contained in mIF images has to be taken into account with the spatial topology of the cells in order to be able to distil potential predictive indicators of patient response to therapies as well as prognostic indicators of outcome. While contemporary computational methods allow pathologists to view aggregated phenotypical information and cell interactions on a limited, generally one-to-one basis, these methods have been largely descriptive and geared toward addressing hypotheses as opposed to holistically leveraging the spatial and phenotypic data into a single predictive model. Additional methods are needed to provide a fuller picture of the spatial structure of the TME as captured in mIF images. In this work, we propose a novel pipeline that uses graphs generated from image analysis results and user-defined distance criteria to represent the tumor cellular microstructure. This graph-based approach complements existing mIF analysis techniques by providing information on the spatial, phenotypic, and morphological features of cells in the context of their neighborhood. These graphs subsequently enable characterization of protein expression in detail, description of interactions between individual cells or cell types and their neighbors, interactive tissue querying, and exploration of the cell-level biodiversity. The graph approach not only allows pathologists to efficiently interrogate data contained in mIF images in a hypothesis-driven manner, but importantly also supports more holistic data-driven approaches which, by leveraging state of the art graph convolutional neural networks to obtain numerical embeddings representing each graph and its nodes, enable additional downstream activities such as cell similarity search, and the development of predictive models for patient outcomes and response to therapies. Citation Format: Jason Hipp, Christopher Innocenti, Zhenning Zhang, Jake Cohen-Setton, Balaji Selvaraj, Michalis Frangos, Carlos Pedrinaci, Michael Surace, Laura Dillon, Khan Baykaner. Leveraging graphs to do novel hypothesis and data-driven research using multiplex immunofluorescence images [abstract]. In: Proceedings of the AACR Virtual Special Conference on Artificial Intelligence, Diagnosis, and Imaging; 2021 Jan 13-14. Philadelphia (PA): AACR; Clin Cancer Res 2021;27(5_Suppl):Abstract nr PR-05.

Visceral fat is associated with high-grade complications in patients undergoing minimally invasive partial nephrectomy for small renal masses.

Introduction:Minimally invasive partial nephrectomy is standard of care treatment for small renal masses.Objective:We evaluated the relationship between subcutaneous and visceral obesity with high-grade postoperative 30-day complications in patients undergoing minimally invasive partial nephrectomy.Methods:We retrospectively identified 98 patients at our institution from 2014 to 2017 who underwent laparoscopic or robotic-assisted partial nephrectomy due to suspected renal cell carcinoma. Patients were stratified based on presence or absence of high-grade (Clavien ≥ IIIa) 30-day postoperative complications. Means were compared with the independent t test and proportions with chi-square analysis. Multivariate logistic regression was performed to determine independent predictors of high-grade 30-day complications.Results:Mean nephrometry score was 6.7 with 21 (21.4%) patients having hilar tumors. Mean estimation of blood loss was 207 mL, mean operating time was 223 min, and mean warm ischemia time was 23 min. The majority of patients had clear renal cell carcinoma (n = 83, 84.7%) and pT1a disease (n = 76, 77.6%) with negative margins (n = 89, 90.8%) on pathology. There were 5 (5.1%) patients who experienced a high-grade postoperative 30-day complication. Mean visceral fat index was an independent predictor of high-grade 30-day complications (odds ratio: 1.02; 95% confidence interval: 1.002–1.03; p = 0.027).Conclusions:Visceral obesity should be considered as a prognostic indicator of outcomes in patients undergoing surgical treatment for a small renal mass.

CASPASE-DEPENDENT ACTIVATION OF CASCADE CYTOKINES IN YOUNG PATIENTS WITH AUTOIMMUNE THYROIDITIS IN COMBINATION WITH GASTROESOPHAGEAL REFLUX DISEASE

The aim of the study: to assess the role of caspase-1 and IL-18 in the implementation of the inflammatory response in young patients with autoimmune thyroiditis (AIT) associated with gastroesophageal reflux disease (GERD).&#x0D; Materials and methods. The study was conducted in two groups of patients homogeneous by gender and age. The first group included 42 patients with an isolated AIT and the second group – 120 patients with a comorbid course of AIT and GERD. The contingent of the surveyed was students. Median age was from 18 to 25 years: 23.1±1.2 years in group with isolated AIT and 21.9±2.7 years in group with combined pathology. The activity of caspase-1 was determined using “Elabscience” kits, USA (China) by immunoassay method. The content of IL-18 was investigated using commercial kits “Bender MedSystems GmbH” (Austria) according to the proposed methods by immunoassay method. Statistical data processing was carried out using the local universal software package Statistica Basic Academic 13 for Windows En Local. Methods of non-parametric statistics were used: Kruskal-Wallis test, median test, Mann-Whitney test.&#x0D; Results. It has been found that caspase-1 is activated in patients both in the isolated course of AIT and in its combination with GERD. At the same time, a significant increasing in the synthesis of IL-18 was established, which has pro-inflammatory and autoimmune effects. Re-examination after 2 months of caspase-1 and IL-18 in examined persons determined decreasing their levels, but control results were not achieved.&#x0D; Conclusion. In young patients, the combination of GERD and AIT, as well as an isolated AIT is accompanied by an increasing the levels of caspase-1 and IL-18 in blood serum related to inflammatory process in the thyroid gland and esophageal mucosa with autoimmune component. These biomarkers may reflect the severity of clinical course of diseases and serve as prognostic indicator of outcome in case of comorbidity.

Right ventricular ejection fraction as predictor of outcome in acute heart failure using RV ellipsoid model: A retrospective analysis of a prospective cross-sectional study.

ObjectivesThe right ventricular (RV) function is an important prognostic factor in acute and chronic heart failure (HF). Echocardiography is an essential imaging modality with established parameters for RV function which are useful and easy to perform. However, these fail to reflect global RV volumes due to reliability on one acoustic window. It is therefore attractive to calculate RV volumes and ejection fraction (RVEF/E) using an ellipsoid geometric model which has been validated against MRI in healthy adults but not in the HF patients.DesignThis is a retrospective analysis of a prospective cross-sectional study enrolling 418 consecutive patients with symptoms of HF according to a predefined study protocol. All patients underwent echocardiographic assessment of RV function using Tricuspid Annular Plane Systolic Excursion (TAPSE) and RV fractional area change (RVFAC) and RVEF/E.SettingSingle centre study with multiple locations for acute in-patients including high dependency units.ParticipantsPatients with acute or exacerbation of chronic HF older than 18 y.o.Main outcome measuresAbility of RVEF/E to predict patient outcomes compared with two established parameters of RV function over two-year follow-up period. Primary outcome measure was all-cause mortality.ResultsRVEF/E is equal to TAPSE & RVFAC in predicting outcome (p ≤ 0.01 vs p ≤ 0.01) and provides additional benefit of RV volume estimation based on standard 2D echo measurements.ConclusionsIn this study we have shown that RVEF/E derived from ellipsoid model is not inferior to well established measures of RV function as a prognostic indicator of outcome in the acute HF.

Abstract 12909: Usefulness of Sarcopenia Index for Predicting Outcomes in Patients Undergoing Transcatheter Aortic Valve Replacement

Introduction: Sarcopenia, a marker of biological senescence, is a robust prognostic indicator of outcomes in patients undergoing transcatheter aortic valve replacement (TAVR) for aortic stenosis (AS). However, there are no serum markers routinely available for estimating skeletal muscle mass (SMM). The present study aimed to describe a new sarcopenia index (SI, serum creatinine value/cystatin C value x 100) and investigate its association with outcomes after TAVR. Methods: The study cohort comprised 100 patients ≥ 65 years of age (mean 83.9±5.7; 36% men) who underwent transfemoral TAVR at Hospital Italiano de Buenos Aires, Argentina from 2016 to 2018. The mean Society of Thoracic Surgeons (STS) score was 3.3±1.7. Sarcopenia was defined according to ROC curve for SI (AUC 0.731, CI 95% 0.599-0.863, p-value=0.001) for predicting the primary endpoint. Both all-cause mortality and/or readmissions for congestive heart failure (CHF) were defined as the primary endpoint within the first year after TAVR. Results: According to SI cutoff, half of the study population (SI ≤66) was sarcopenic before TAVR. The 30-day mortality increased significantly in the lowest SI tertile (sarcopenia+) group (12, 3, and 0%, p=.05, respectively). SI strongly correlated with timed-up and go and gait speed but not with body mass index and baseline C-reactive protein levels. Overall survival was worse (Log-rank test= p=0.02) and CHF readmissions were more prevalent in the lowest SI tertile (Log-rank test=p=0.01). On Cox regression analysis, a low SI (SI ≤66) had a significantly higher risk of the primary endpoint (adjusted hazard ratio: 4.01, 95% CI: 1.31-12.27, p=.015). Conclusions: SI, a novel-non-invasive method for assessing SMM was able to predict mid-term mortality and CHF readmissions. We suggest careful consideration of sarcopenia prior to TAVR in order to decide the best treatment approaches.

Machine learning imputation of Eastern Cooperative Oncology Group performance status (ECOG PS) scores from data in CancerLinQ discovery.

e19318 Background: ECOG PS is a prognostic indicator of outcomes, and scores of 0-1 (good ECOG PS) are often required for clinical trial enrollment. Patients treated in non-trial settings often lack ECOG PS scores limiting the ability of Real World Data from these patients to be used in external control arms (ECAs) or to provide optimal specificity for clinical effectiveness research. Machine Learning can be used to impute ECOG PS scores from other clinical data at various points during treatment. Methods: We developed a series of models using logistic regression (LR) or XGBoost (XGB) that impute ECOG PS at initial diagnosis, metastatic diagnosis and final evaluation using a curated Non-Small Cell Lung Cancer cohort of 31,425 patients with at least one ECOG PS score. Results: AUC-ROC values of up to 0.81 could be obtained for imputing a patient’s final ECOG PS, with lower AUC values when imputing ECOG PS at initial and metastatic diagnosis using large numbers (i.e. thousands) of features. We developed more interpretable models with 110 or 40 features with reduced but still satisfactory AUC, with accuracy of predicting good ECOG PS scores of around 80%. Key features were obtained from lab tests, physical exams, comorbidities, medications, age and metastatic status. The table below shows the results of several of these models. Where the models misclassify ECOG PS, the error was rarely greater than 1 grade. Conclusions: ECOG PS is subjective, suggesting that ML based cohort assignment will be sufficiently accurate to support their use in research. Further work will be required to assess if the ML predicted cohorts have different outcomes. [Table: see text]

Skeletal muscle mass as a prognostic indicator of outcomes in ovarian cancer: a systematic review and meta-analysis

BackgroundMuscle mass plays a key role in predicting clinical outcomes in cancer. This systematic review and meta-analysis aimed to evaluate whether computed tomography (CT) scan indexes of muscle mass quantity...

What factors indicate prognosis for adults with depression in primary care? A protocol for meta-analyses of individual patient data using the Dep-GP database.

Background: Pre-treatment severity is a key indicator of prognosis for those with depression. Knowledge is limited on how best to encompass severity of disorders. A number of non-severity related factors such as social support and life events are also indicators of prognosis. It is not clear whether this holds true after adjusting for pre-treatment severity as a) a depressive symptom scale score, and b) a broader construct encompassing symptom severity and related indicators: "disorder severity". In order to investigate this, data from the individual participants of clinical trials which have measured a breadth of "disorder severity" related factors are needed. Aims: 1) To assess the association between outcomes for adults seeking treatment for depression and the severity of depression pre-treatment, considered both as i) depressive symptom severity only and ii) "disorder severity" which includes depressive symptom severity and comorbid anxiety, chronicity, history of depression, history of previous treatment, functional impairment and health-related quality of life. 2) To determine whether i) social support, ii) life events, iii) alcohol misuse, and iv) demographic factors (sex, age, ethnicity, marital status, employment status, level of educational attainment, and financial wellbeing) are prognostic indicators of outcomes, independent of baseline "disorder severity" and the type of treatment received. Methods: Databases were searched for randomised clinical trials (RCTs) that recruited adults seeking treatment for depression from their general practitioners and used the same diagnostic and screening instrument to measure severity at baseline - the Revised Clinical Interview Schedule; outcome measures could differ between studies. Chief investigators of all studies meeting inclusion criteria were contacted and individual patient data (IPD) were requested. Conclusions: In total 15 RCTs met inclusion criteria. The Dep-GP database will include the 6271 participants from the 13 studies that provided IPD. This protocol outlines how these data will be analysed. Registration: PROSPERO CRD42019129512 (01/04/2019).

Elevated neutrophil-lymphocyte ratio predicts mortality following elective endovascular aneurysm repair

ObjectiveThe neutrophil-lymphocyte ratio (NLR) is an inexpensive and useful inflammatory marker that incorporates the balance of the innate (neutrophil) and adaptive (lymphocyte) immune responses. Data exist on the association between NLR and mortality in various coronary diseases and in cancer surgery, but there is a paucity of data on the impact of preoperative NLR on vascular surgical outcomes. The aim of this study was to evaluate the relationship between preoperative NLR and elective endovascular aortic aneurysm repair (EVAR) outcome. MethodsA retrospective review of all patients who underwent elective EVAR at a single institution between 2010 and 2018 was conducted (n = 373). Only patients who had a preoperative complete blood count with differential within 30 days of their operation were included. The NLR was computed by dividing the absolute neutrophil count by the absolute lymphocyte count. A receiver operating characteristic curve was used to determine the optimal cutoff value of NLR with the strongest association with mortality. NLR was dichotomized so that patients with NLR above the threshold were at increased risk of mortality compared with those below it. Continuous variables were analyzed using Wilcoxon nonparametric signed-rank test and categorical variables with the Fisher exact test. A comparison of NLR and mortality was completed using Kaplan-Meier survival analysis. Cox regression analysis was used to evaluate factors associated with mortality through 5-year follow-up. ResultsOverall, 108 patients were included in this study. An NLR ≥ 4.0 was found to be associated with mortality (P < .0001). Thirty-two patients composed the High-NLR (NLR ≥ 4.0) group and the remaining 76 patients formed the Low-NLR (NLR < 4.0) group. Baseline characteristics were similar between groups, except that the High-NLR group was older (77.9 vs 74.4; P = .047). At a mean of 36.4 months follow-up, the overall mortality rate was 32.4%. Although there were no differences in the perioperative period, the Kaplan-Meier estimates of mortality were significantly greater in the High-NLR group at 1, 2, and 5 years postoperatively (P < .0001). The mean preoperative NLR of the deceased was higher (5.94 ± 5.20; median, 4.75; interquartile range, 3.17-7.83) than those who survived (2.87 ± 1.61; median, 2.53; interquartile range, 1.97-3.49) (P < .0001). Secondary interventions and sac enlargement rates were similar between groups. On univariable analysis, NLR (hazard ratio [HR], 1.17; 95% confidence interval [CI], 1.10-1.23; P < .0001), age (HR, 1.06; 95% CI, 1.02-1.11; P = .004), and aneurysm diameter (HR, 1.04; 95% CI, 1.01-1.07; P = .003) were associated with mortality. On multivariable analysis, NLR (HR, 1.19; 95% CI, 1.12-1.27; P < .0001), age (HR, 1.06; 95% CI, 1.01-1.11; P = .026), and aneurysm diameter (HR, 1.04; 95% CI, 1.02-1.07; P = .003) were associated with mortality. ConclusionsPatients with an elevated preoperative NLR, irrespective of other comorbidities, may represent a previously unrecognized subset of patients who are at heightened risk of mortality after elective EVAR. A complete blood count with differential is an inexpensive test that may be used as a prognostic indicator for outcome after EVAR. Further research is warranted to identify clinical, pathological, or anatomical factors associated with an elevated NLR and to determine modifiable factors, which may help improve long-term survival.

What factors indicate prognosis for adults with depression in primary care? A protocol for meta-analyses of individual patient data using the Dep-GP database.

Background: Pre-treatment severity is a key indicator of prognosis for those with depression. Knowledge is limited on how best to encompass severity of disorders. A number of non-severity related factors such as social support and life events are also indicators of prognosis. It is not clear whether this holds true after adjusting for pre-treatment severity as a) a depressive symptom scale score, and b) a broader construct encompassing symptom severity and related indicators: "disorder severity". In order to investigate this, data from the individual participants of clinical trials which have measured a breadth of "disorder severity" related factors are needed. Aims: 1) To assess the association between outcomes for adults seeking treatment for depression and the severity of depression pre-treatment, considered both as i) depressive symptom severity only and ii) "disorder severity" which includes depressive symptom severity and comorbid anxiety, chronicity, history of depression, history of previous treatment, functional impairment and health-related quality of life. 2) To determine whether i) social support, ii) life events, iii) alcohol misuse, and iv) demographic factors (sex, age, ethnicity, marital status, employment status, level of educational attainment, and financial wellbeing) are prognostic indicators of outcomes, independent of baseline "disorder severity" and the type of treatment received. Methods: Databases were searched for randomised clinical trials (RCTs) that recruited adults seeking treatment for depression from their general practitioners and used the same diagnostic and screening instrument to measure severity at baseline - the Revised Clinical Interview Schedule; outcome measures could differ between studies. Chief investigators of all studies meeting inclusion criteria were contacted and individual patient data (IPD) were requested. Conclusions: In total 15 RCTs met inclusion criteria. The Dep-GP database will include the 6271 participants from the 13 studies that provided IPD. This protocol outlines how these data will be analysed. Registration: PROSPERO CRD42019129512 (01/04/2019).

What factors indicate prognosis for adults with depression in primary care? A protocol for meta-analyses of individual patient data using the Dep-GP database

Background: Pre-treatment severity is a key indicator of prognosis for those with depression. Knowledge is limited on how best to encompass severity of disorders. A number of non-severity related factors such as social support and life events are also indicators of prognosis. It is not clear whether this holds true after adjusting for pre-treatment severity as a) a depressive symptom scale score, and b) a broader construct encompassing symptom severity and related indicators: “disorder severity”. In order to investigate this, data from the individual participants of clinical trials which have measured a breadth of “disorder severity” related factors are needed. Aims: 1) To assess the association between outcomes for adults seeking treatment for depression and the severity of depression pre-treatment, considered both as i) depressive symptom severity only and ii) “disorder severity” which includes depressive symptom severity and comorbid anxiety, chronicity, history of depression, history of previous treatment, functional impairment and health-related quality of life. 2) To determine whether i) social support, ii) life events, iii) alcohol misuse, and iv) demographic factors (sex, age, ethnicity, marital status, employment status, level of educational attainment, and financial wellbeing) are prognostic indicators of outcomes, independent of baseline “disorder severity” and the type of treatment received. Methods: Databases were searched for randomised clinical trials (RCTs) that recruited adults seeking treatment for depression from their general practitioners and used the same diagnostic and screening instrument to measure severity at baseline – the Revised Clinical Interview Schedule; outcome measures could differ between studies. Chief investigators of all studies meeting inclusion criteria were contacted and individual patient data (IPD) were requested. Conclusions: In total 15 RCTs met inclusion criteria. The Dep-GP database will include the 6271 participants from the 13 studies that provided IPD. This protocol outlines how these data will be analysed. Registration: PROSPERO CRD42019129512 (01/04/2019)

Elevated Neutrophil-Lymphocyte Ratio Predicts Mortality After Elective Endovascular Aneurysm Repair

The neutrophil-lymphocyte ratio (NLR), computed by dividing the absolute neutrophil count by absolute lymphocyte count, is an inexpensive inflammatory marker that incorporates the balance of the innate (neutrophil) and adaptive (lymphocyte) immune responses. The objective of this study was to determine whether preoperative NLR is associated with mortality after elective endovascular aneurysm repair (EVAR). A retrospective review of patients who underwent elective EVAR between 2010 and 2017 and had a preoperative complete blood count with differential within 30 days of repair was conducted. A receiver operating characteristic curve was used to determine the optimal cutoff value of NLR most predictive of mortality. NLR was therefore dichotomized so that patients above the threshold were at increased risk of mortality compared with those below it. Continuous variables were analyzed using Wilcoxon nonparametric signed rank test and categorical variables with the Fisher exact test. Kaplan-Meier survival analysis was used to compare NLR and mortality. Overall, 108 patients were included. An NLR of ≥4.0 was found to be predictive of mortality (P < .0001); 32 patients composed the high NLR (≥4.0) group, and the remaining 76 patients formed the low NLR (<4.0) group. Baseline characteristics were similar between groups, except that the high NLR group was older. At a mean of 36.4 months of follow-up, the overall mortality rate was 34.3%. Perioperative mortality was similar between groups. However, mortality rates were significantly greater in the high NLR group at 1 year (28.1% vs 3.9%; P = .0008), 2 years (43.8% vs 9.2%; P < .0001), and 5 years (71.9% vs 15.8%; P < .0001; Fig). The mean preoperative NLR of the deceased was higher (5.94 ± 5.20) than the NLR of those who survived (2.87 ± 1.61; P < .0001). Secondary interventions and sac enlargement rates were similar between groups. Patients with an elevated preoperative NLR, irrespective of other comorbidities, may represent a previously unrecognized subset of patients at heightened risk of mortality after elective EVAR. A complete blood count with differential is an inexpensive test that may be used as a prognostic indicator for outcome after EVAR. Further research is warranted to identify clinical, pathologic, and anatomic factors associated with elevated NLR and to determine the modifiable factors of it, which may help improve survival.

Abstract 2273: A machine learning approach to identify a peripheral prognostic cytokine signature via nivolumab clearance in patients with advanced melanoma

Abstract Background: Data suggest that peripheral factors such as circulating cytokines could function as predictive indicators of clinical response to specific therapies or as general prognostic indicators of outcome in patients with cancer. Previous studies have focused on evaluating the association between individual cytokines and clinical outcome. There is no clear consensus on how or which of these cytokines should be selected for prediction of treatment outcome. Clearance of immunotherapeutic agents such as the anti-PD-1 nivolumab (NIVO) has been shown to be a predictor of best overall response and overall survival (OS) across multiple indications. Determination of clearance requires post-treatment pharmacokinetic (PK) samples which negates its utility as a baseline prognostic factor. We investigated a novel machine learning approach to identify a baseline composite cytokine signature that correlates with the established efficacy response relationship for NIVO clearance in advanced melanoma. This approach, which is capable of integrating multivariate factors into a composite feature, may provide a more accurate reflection of underlying biologic factors that contribute to outcome following treatment. Methods: Peripheral serum PK (NIVO clearance) and pharmacodynamic (Myriad Rules Based Medicine-customized inflammatory cytokine panel) data from 2 phase 3 studies (NCT01721772; NCT01844505) of NIVO monotherapy in patients with melanoma (n = 471) were used for machine learning model development (training data set). A third phase 3 study of NIVO in advanced melanoma (NCT01721746) was included in model application (test data set; n = 158). Random forest, a tree-based ensemble learning method, was used for feature selection and classification (low vs high) of NIVO clearance. Kaplan-Meier analyses and log-rank p values were used to assess statistical difference in long-term OS between predicted high- vs low-clearance groups. Results: A panel of ~20 baseline inflammatory cytokines related to immune cell modulation were selected by the machine learning model to predict clearance of NIVO monotherapy in patients with advanced melanoma (area under the curve of receiver operating characteristic: 0.79). The predicted clearance value from the cytokine signature was significantly associated with OS across all 3 studies, including patients treated with NIVO or dacarbazine (control) (p&amp;lt;0.01). Conclusions: We developed a machine learning approach to identify a serum prognostic cytokine signature based on the relationship between NIVO clearance and response. The strong association of the defined cytokine signature with OS from NIVO and dacarbazine suggests a prognostic role for drug clearance. This cytokine signature has the potential to be a prognostic biomarker in melanoma and may be used for balancing and randomization of patients in clinical studies. Citation Format: Rui Wang, Xiao Shao, Junying Zheng, Abdel Saci, Max Qian, Irene Pak, Amit Roy, Akintunde Bello, Jasmine Rizzo, Fareeda Hosein, Rebecca A. Moss, Megan Wind-Rotolo, Yan Feng. A machine learning approach to identify a peripheral prognostic cytokine signature via nivolumab clearance in patients with advanced melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 2273.

What factors indicate prognosis for adults with depression in primary care? A protocol for meta-analyses of individual patient data using the Dep-GP database

Background: Pre-treatment severity is a key indicator of prognosis for those with depression. Knowledge is limited on how best to encompass severity of disorders. A number of non-severity related factors such as social support and life events are also indicators of prognosis. It is not clear whether this holds true after adjusting for pre-treatment severity as a) a depressive symptom scale score, and b) a broader construct encompassing symptom severity and related indicators: "disorder severity". In order to investigate this, data from the individual participants of clinical trials which have measured a breadth of "disorder severity" related factors are needed. Aims: 1) To assess the association between outcomes for adults seeking treatment for depression and the severity of depression pre-treatment, considered both as i) depressive symptom severity only and ii) "disorder severity" which includes depressive symptom severity and comorbid anxiety, chronicity, history of depression, history of previous treatment, functional impairment and health-related quality of life. 2) To determine whether i) social support, ii) life events, iii) alcohol misuse, and iv) demographic factors (sex, age, ethnicity, marital status, employment status, level of educational attainment, and financial wellbeing) are prognostic indicators of outcomes, independent of baseline "disorder severity" and the type of treatment received. Methods: Databases were searched for randomised clinical trials (RCTs) that recruited adults seeking treatment for depression from their general practitioners and used the same diagnostic and screening instrument to measure severity at baseline - the Revised Clinical Interview Schedule; outcome measures could differ between studies. Chief investigators of all studies meeting inclusion criteria were contacted and individual patient data (IPD) were requested. Conclusions: In total 13 RCTs were found to meet inclusion criteria. The Dep-GP database was formed from the 6271 participants. This protocol outlines how these data will be analysed. Registration: PROSPERO CRD42019129512 (01/04/2019).

PREVALENCE OF NEUROPSYCHIATRIC SYMPTOMS ACROSS THE COGNITIVE SPECTRUM AND THEIR IMPACT ON FUTURE COGNITIVE DECLINE: Session 203

In the recently published National Institute on Aging and Alzheimer's Association (NIA-AA)’s Research Framework, the definition of Alzheimer's disease (AD) shifts from a syndromal to a biological entity, defined by underlying pathology as evidenced by the presence of AD biomarkers in vivo or on post-mortem examination (Jack et al., 2018, Alzheimers Dement. 2018 Apr;14(4):535-562). The new NIA-AA framework also describes syndromal staging of cognitive continuum to define research cohorts, independent of biomarker profile. With respect to mild cognitive impairment (MCI), the current framework differs from the 2011 NIA-AA definition in its reference to “neurobehavioral” symptoms, defined as symptoms attributable to mood or behavioral disorders, such as anxiety, depression, and apathy, which “commonly coexist and may be a prominent part of the presentation” (Table 3, Jack et al., 2018). We argue that neurobehavioural or neuropsychiatric symptoms (NPS) across the spectrum of AD disease should not be conceptualized as simply co-existing alongside cognitive impairment or attributable to mood or behavioural disorders. Rather, NPS are core features of neurodegenerative cognitive syndromes that may serve as prognostic indicators of outcome. This symposium will review the prevalence of NPS across the cognitive spectrum; namely in subjective cognitive decline (SCD), mild cognitive impairment (MCI), and Alzheimer's disease (AD), and highlight their association with AD biomarkers and contribution to future cognitive decline or disease progression in AD. Dr. Linda Mah will review the prevalence of neurobehavioural symptoms and their association with AD biomarkers and future cognitive decline in older adults who are cognitively unimpaired (CU) or who present with SCD, drawing from the extant literature and new data from an ongoing study of SCD. Dr. Krista L. Lanctôt will review the prevalence of NPS in mild neurocognitive disorder (NCD) and impact on progression. In addition, emerging evidence linking specific NPS with biomarkers of major NCD and the efficacy of interventions including pharmacologic, nonpharmacologic and neuromodulatory during this phase will be highlighted, with emphasis on recent findings. Dr. Corinne E. Fischer will review the prevalence and trajectory, clinical features and treatment approach to neuropsychiatric symptoms (NPS) in patients with established Alzheimer's disease. Particular emphasis will be placed on studies demonstrating the link between disease biomarkers and NPS disease burden, highlighting specific NPS such as apathy, aberrant sleep behavior, psychosis and depression.