Early Prediction Of Clinical Outcome Research Articles

Clinical outcome prediction with an automated EEG trend, Brain State of the Newborn, after perinatal asphyxia

ObjectiveTo evaluate the utility of a fully automated deep learning -based quantitative measure of EEG background, Brain State of the Newborn (BSN), for early prediction of clinical outcome at four years of age. MethodsThe EEG monitoring data from eighty consecutive newborns was analyzed using the automatically computed BSN trend. BSN levels during the first days of life (a of total 5427 hours) were compared to four clinical outcome categories: favorable, cerebral palsy (CP), CP with epilepsy, and death. The time dependent changes in BSN-based prediction for different outcomes were assessed by positive/negative predictive value (PPV/NPV) and by estimating the area under the receiver operating characteristic curve (AUC). ResultsThe BSN values were closely aligned with four visually determined EEG categories (p < 0·001), as well as with respect to clinical milestones of EEG recovery in perinatal Hypoxic Ischemic Encephalopathy (HIE; p < 0·003). Favorable outcome was related to a rapid recovery of the BSN trend, while worse outcomes related to a slow BSN recovery. Outcome predictions with BSN were accurate from 6 to 48 hours of age: For the favorable outcome, the AUC ranged from 95 to 99% (peak at 12 hours), and for the poor outcome the AUC ranged from 96 to 99% (peak at 12 hours). The optimal BSN levels for each PPV/NPV estimate changed substantially during the first 48 hours, ranging from 20 to 80. ConclusionsWe show that the BSN provides an automated, objective, and continuous measure of brain activity in newborns. SignificanceThe BSN trend discloses the dynamic nature that exists in both cerebral recovery and outcome prediction, supports individualized patient care, rapid stratification and early prognosis.

Early Prediction of Treatment Response By Circulating Tumor DNA Profiling in Patients with Diffuse Large B-Cell Lymphoma Receiving CAR T-Cell Therapy

Introduction Patients with relapsed or refractory diffuse large B-cell lymphoma (r/r DLBCL) are characterized by a particularly poor prognosis. Anti-CD19 chimeric antigen receptor (CAR) T-cell therapy has improved outcomes of patients with r/r DLBCL, yet a substantial proportion of patients still experiences relapse or progression after CAR T-cell treatment. Identifying patients at high risk of CAR T-cell therapy resistance or future lymphoma progression remains challenging. Here, we explored the value of circulating tumor DNA (ctDNA) as a prognostic biomarker at baseline and early into treatment in DLBCL patients undergoing standard-of-care CAR T-cell therapy, without the need for matched tumor genotypes. We further investigated associations between ctDNA and other known clinical risk factors. Methods We applied targeted next-generation sequencing (NGS) to a total of 53 samples from r/r DLBCL patients receiving CAR T-cell therapy (axicabtagene ciloleucel and tisagenlecleucel, n=16) at the University Medical Center Freiburg (Germany), using a modified version of the AVENIO ctDNA analysis workflow (Roche; Research Use Only) that covered ~314kb and targeted 466 distinct genes recurrently mutated in DLBCL (based on the CAPP-Seq workflow, Kurtz DM et al. J Clin Oncol 2018). Tumor genotypes were assessed noninvasively from plasma samples obtained at baseline before lymphodepletion with matched germline controls. Concentrations of ctDNA were quantified at baseline and early after CAR T-cell therapy at day 7-10. Initial treatment response was assessed by conventional PET-CT obtained 4-6 weeks after treatment based on the Lugano criteria. Results At baseline prior to lymphodepletion, we detected somatic mutations in 100% of plasma samples by noninvasive genotyping, with a median of 19.5 mutations per patient (range: 3-97). The most frequently mutated genes were IGHV, IGLL5, BCL2, MYC, BTG1, CREBBP, and TP53. Patients with high baseline ctDNA concentrations (mean allele frequency [AF] &amp;gt;= 1%) showed shorter progression-free survivial (PFS) and overall survival (OS) than patients with ctDNA levels below this threshold (median PFS: 86.5 days vs. not reached, p=0.04, HR: 6.3, 95% CI: 1.7-23.6; median OS: 219 days vs. not reached, p=0.048, HR: 4.1, 95% CI 1.0-16.6, Figure 1). Pretreatment ctDNA levels were significantly correlated with LDH concentrations ( p=0.049, r=0.5). We further found significantly higher ctDNA concentrations in patients with transformed DLBCL (vs. non-transformed, p=0.008) and in those with 3 or more prior treatment lines (vs. 1-2, p=0.04). At day 7-10 after CAR T-cell therapy, ctDNA levels dropped a median of 10-fold compared to the pretreatment time point ( p=0.008). Patients achieving a complete (CMR) or partial metabolic response (PMR) by PET-CT after 4-6 weeks showed a significant decrease of ctDNA ( p=0.001), while those with a stable (SD) or progressive disease (PD) had no significant ctDNA reduction at day 7-10 after CAR T-cell infusion. Vice versa, while 100% of patients with a &amp;gt;1.5-log-fold drop of ctDNA level between the pretreatment and interim time point revealed a CMR or PMR in early PET-CT scans, only 62% of patients with a smaller ctDNA decline responded to treatment according to PET-CT. Conclusions Our data suggests, together with previously published studies (Sworder BJ et al., Cancer Cell, 2023; Frank MJ et al. J Clin Oncol, 2021), that ctDNA profiling may allow robust noninvasive genotyping, accurate risk-stratification, and early prediction of clinical outcomes in r/r DLBCL patients undergoing CAR T-cell therapy. Although limited by small sample size, this pilot study highlights a potential future role of ctDNA measurements for personalized treatment selection and guidance in clinical trials.

Development and Utility of Practical Indicators of Critical Outcomes in Dengue Patients Presenting to Hospital: A Retrospective Cross-Sectional Study

Global travel and climate change have drastically increased the number of countries with endemic or epidemic dengue. The largest dengue outbreak in Taiwan, with 43,419 cases and 228 deaths, occurred in 2015. Practical and cost-effective tools for early prediction of clinical outcomes in dengue patients, especially the elderly, are limited. This study identified the clinical profile and prognostic indicators of critical outcomes in dengue patients on the basis of clinical parameters and comorbidities. A retrospective cross-sectional study was conducted in a tertiary hospital from 1 July 2015 to 30 November 2015. Patients diagnosed with dengue were enrolled, and the initial clinical presentations, diagnostic laboratory data, details of the underlying comorbidities, and initial management recommendations based on 2009 World Health Organization (WHO) guidelines were used to evaluate prognostic indicators of critical outcomes in dengue patients. Dengue patients from another regional hospital were used to evaluate accuracy. A group B (4 points) classification, temperature < 38.5 °C (1 point), lower diastolic blood pressure (1 point), prolonged activated partial thromboplastin time (aPTT) (2 points), and elevated liver enzymes (1 point) were included in the scoring system. The area under the receiver operating characteristic curve of the clinical model was 0.933 (95% confidence interval [CI]: 0.905-0.960). The tool had good predictive value and clinical applicability for identifying patients with critical outcomes.

Motor progression marker for newly diagnosed drug-naïve patients with Parkinson's disease: A resting-state functional MRI study.

The effective early prediction of clinical outcomes of Parkinson's disease (PD) is of great significance in the implementation of appropriate interventions. We aimed to propose a method based on the use of baseline resting-state functional characteristics (i.e., fractional amplitude of low-frequency fluctuations, fALFF) to predict motor progression in PD patients. Resting-state functional magnetic resonance imaging was performed on 48 newly-diagnosed drug-naïve PD patients and 27 age- and sex- matched healthy controls (HCs). Two PD subgroups were defined with different annual increase of Unified PD Rating Scale Part III motor scores. Least absolute shrinkage and selection operator regression analysis was performed to explore the baseline region-functional indicators for PD discrimination as well as the predictors for future motor deficits. Two significant models composed of baseline fALFF values from cerebral subregions were proposed. The classification model that distinguished PD patients from HCs (area under the curve [AUC]=0.897) showed the most significant imaging characteristics in the putamen and precentral gyrus. The other prediction model that evaluated the degree of future deterioration of motor symptoms in PD patients (AUC=0.916) showed the most significant imaging characteristics in the superior occipital gyrus and caudate nucleus. Furthermore, the increased regional function in bilateral caudate nuclei was correlated with the lower annual increase in motor deficits in all PD patients. The caudate nucleus might be the core region responsible for future motor deficits in newly-diagnosed PD patients, which may aid the development of disease progression preventive strategies in clinical practice.

A Novel Patent Ductus Arteriosus Severity Score to Predict Clinical Outcomes in Premature Neonates.

Background: Patent Ductus Arteriosus (PDA) in premature neonates has been associated with comorbidities including chronic lung disease (CLD), and death. However, the treatment of PDA remains controversial. There have been several echocardiographic variables previously used to determine the hemodynamic significance of PDA but their utility in early prediction of clinical outcomes is not well studied. Objective: The objective of our study was to evaluate the use of a severity scoring system incorporating markers of systemic under perfusion, pulmonary over perfusion and left ventricular (LV) function in predicting clinical outcomes in premature neonates. Methods: It is a single center prospective observational study involving newborns < 32 weeks’ gestation. An echocardiogram was done within seven days of life to measure variables previously known to predict severity of shunting in PDA including pulmonary perfusion index (PPI). Predictors of CLD/death were identified using multivariate logistic regression. A severity score was derived and its ability to predict clinical outcomes was tested using a receiver operating characteristic curve. Results: We studied 98 infants with a mean (SD) gestation of 28.9 ± 1.91 weeks and birth weight of 1228.06 ± 318.94 g, respectively. We identified five echocardiographic variables along with gestational age that was independently associated with the outcome variable (PPI, LV output, Superior Mesenteric Artery [SMA] Velocity Time Integral [VTI], Peak diastolic flow velocity in Pulmonary Vein [PV Vd], and reversal of flow in diastole in descending aorta [DFR]). The range of severity score was 0 (low risk) to 12 (high risk). A higher score was associated with the primary outcome variable of CLD/death (7.5 [1.2] vs. 3.6 [1.5], p < 0.001). Our severity score had an area under the curve of 0.97 (95% CI 0.93–0.99, p < 0.001) for predicting CLD/death. Conclusion: Our new PDA severity score of 5.5 has a sensitivity and specificity of 94% and 93%, and positive and negative predictive values of 94% and 93%, respectively.

Profiling of Circulating Tumor DNA for Noninvasive Disease Detection, Risk Stratification, and MRD Monitoring in Patients with CNS Lymphoma

Abstract Introduction: Clinical outcomes for patients with central nervous system lymphoma (CNSL) are remarkably heterogeneous, yet identification of patients at high risk for treatment failure remains challenging with existing methods. In addition, diagnosis of CNSL requires invasive neurosurgical biopsies that carry procedural risks and often cannot be performed in frail or elderly patients. Circulating tumor DNA (ctDNA) has shown great potential as a noninvasive biomarker in systemic lymphomas. Yet, previous studies revealed low ctDNA detection rates in blood plasma of CNSL patients. In this study, we utilized ultrasensitive targeted high-throughput sequencing technologies to explore the role of ctDNA for disease classification, MRD detection, and early prediction of clinical outcomes in patients with CNSL. Methods: We applied Cancer Personalized Profiling by Deep Sequencing (CAPP-Seq) and Phased Variant Enrichment and Detection Sequencing (PhasED-Seq, Kurtz et al, Nat Biotech 2021) to 85 tumor biopsies, 131 plasma samples, and 62 CSF specimens from 92 CNSL patients and 44 patients with other brain cancers or inflammatory cerebral diseases, targeting 794 distinct genetic regions. Concentrations of ctDNA were correlated with radiological measures of tumor burden and tested for associations with clinical outcomes at distinct clinical time points. We further developed a novel classifier to noninvasively distinguish CNS lymphomas from other CNS tumors based on their mutational landscapes in plasma and CSF, using supervised training of a machine learning approach from tumor whole genome sequencing data and own genotyping analyses, followed by its independent validation. Results: We identified genetic aberrations in 100% of CNSL tumor biopsies (n=63), with a median of 262 mutations per patient. Pretreatment plasma ctDNA was detectable in 78% of plasma samples and in 100% of CSF specimens (Fig. 1a), with ctDNA concentrations ranging from 0.0004 - 5.94% allele frequency (AF, median: 0.01%) in plasma and 0.0049 - 50.47% AF (median: 0.62%) in CSF (Fig. 1b). Compared to ctDNA concentrations in patients with systemic diffuse large B-cell lymphoma (DLBCL, data from Kurtz et al., J Clin Oncol, 2018), plasma ctDNA levels in CNSL were in median more than 200-fold lower (Fig. 1b). We observed a significant correlation of ctDNA concentrations with total radiographic tumor volumes (TRTV) measured by MRI (Fig. 1c,d), but no association with clinical risk scores (i.e., MSKCC score) or concurrent steroid treatment. Assessment of ctDNA at pretreatment time points predicted progression-free survival (PFS) and overall survival (OS), both as continuous and binary variable (Fig. 1e,f). Notably, patients could be stratified into risk groups with particularly favorable or poor prognoses by combining ctDNA and TRTV as pretreatment biomarkers (Fig. 1g). Furthermore, ctDNA positivity during curative-intent induction therapy was significantly associated with clinical outcomes, both PFS and OS (Fig. 1h). Finally, we applied our novel machine learning classifier to 207 specimens from an independent validation cohort of CNSL and Non-CNSL patients. We observed high specificity (100%) and positive predictive value (100%) for noninvasive diagnosis of CNSL, with a sensitivity of 57% for CSF and 21% for plasma, suggesting that a significant subset of CNSL patients might be able to forego invasive surgical biopsies. Conclusions: We demonstrate robust and ultrasensitive detection of ctDNA at various disease milestones in CNSL. Our findings suggest that ctDNA accurately mirrors tumor burden and serves as a valuable clinical biomarker for risk stratification, outcome prediction, and surgery-free lymphoma classification in CNSL. We foresee an important potential future role of ctDNA as a decision-making tool to guide treatment in patients with CNSL. Figure 1 Figure 1. Disclosures Esfahani: Foresight Diagnostics: Current holder of stock options in a privately-held company. Kurtz: Genentech: Consultancy; Roche: Consultancy; Foresight Diagnostics: Consultancy, Current holder of stock options in a privately-held company. Schorb: Riemser Pharma GmbH: Honoraria, Research Funding; Roche: Research Funding; AbbVie: Research Funding. Diehn: BioNTech: Consultancy; RefleXion: Consultancy; Roche: Consultancy; AstraZeneca: Consultancy; Foresight Diagnostics: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; CiberMed: Current holder of stock options in a privately-held company, Patents &amp; Royalties; Illumina: Research Funding; Varian Medical Systems: Research Funding. Alizadeh: Foresight Diagnostics: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Gilead: Consultancy; Roche: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Janssen Oncology: Honoraria; CAPP Medical: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Forty Seven: Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Cibermed: Consultancy, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Bristol Myers Squibb: Research Funding.

D-Dimer as Biomarker for Early Prediction of Clinical Outcomes in Patients With Severe Invasive Infections Due to Streptococcus Pneumoniae and Neisseria Meningitidis.

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection; no current clinical measure adequately reflects the concept of dysregulated response. Coagulation plays a pivotal role in the normal response to pathogens (immunothrombosis), thus the evolution toward sepsis-induced coagulopathy could be individuate through coagulation/fibrinolysis-related biomarkers. We focused on the role of D-dimer assessed within 24 h after admission in predicting clinical outcomes in a cohort of 270 patients hospitalized in a 79 months period for meningitis and/or bloodstream infections due to Streptococcus pneumoniae (n = 162) or Neisseria meningitidis (n = 108). Comparisons were performed with unpaired t-test, Mann-Whitney-test or chi-squared-test with continuity correction, as appropriate, and multivariable logistic regression analysis was performed with Bayesian model averaging. In-hospital mortality was 14.8% for the overall population, significantly higher in S. pneumoniae than in N. meningitidis patients: 19.1 vs. 8.3%, respectively (p = 0.014). At univariable logistic regression analysis the following variables were significantly associated with in-hospital mortality: pneumococcal etiology, female sex, age, ICU admission, SOFA score, septic shock, MODS, and D-dimer levels. At multivariable analysis D-dimer showed an effect only in N. meningitidis subgroup: as 500 ng/mL of D-dimer increased, the probability of unfavorable outcome increased on average by 4%. Median D-dimer was significantly higher in N. meningitidis than in S. pneumoniae patients (1,314 vs. 1,055 ng/mL, p = 0.009). For N. meningitidis in-hospital mortality was 0% for D-dimer <500 ng/mL, very low (3.5%) for D-dimer <7,000 ng/mL, and increased to 26.1% for D-dimer >7,000 ng/mL. Kaplan-Meier analysis of in-hospital mortality showed for N. meningitidis infections a statistically significant difference for D-dimer >7,000 ng/mL compared to values <500 ng/mL (p = 0.021) and 500–3,000 ng/mL (p = 0.002). For S. pneumoniae the mortality risk resulted always high, over 10%, irrespective by D-dimer values. In conclusion, D-dimer is rapid to be obtained, at low cost and available everywhere, and can help stratify the risk of in-hospital mortality and complications in patients with invasive infections due to N. meningitidis: D-dimer <500 ng/mL excludes any further complications, and a cut-off of 7,000 ng/mL seems able to predict a significantly increased mortality risk from much <10% to over 25%.

Role of central venous-arterial PCO2 difference in prediction of clinical outcome in ICU septic patients

ABSTRACT Background: Identification of tissue hypoxia and hypoperfusion plays an important role in the management of critically ill patients. Although the venous-arterial PCO2 difference (ΔPCO2) cannot serve as a marker of tissue hypoxia, it is considered a marker of the adequacy of venous blood flow (Cardiac output). The present study aimed to evaluate the role of venous-arterial PCO2 gradient in prediction of outcome in septic patients admitted to ICU. Patients and methods: 100 adult patients fulfilled the criteria of severe sepsis or septic shock admitted to Emergency Intensive Care Unit, were divided in two groups according to ΔPCO2. The high ΔpCO2 group (ΔpCO2 > 6 mmHg) included 58 patients and the normal ΔpCO2 (ΔpCO2 ≤ 6 mmHg) included 42 patients. Clinical scoring systems were recorded. Clinical outcome including organ dysfunction and mortality was recorded. Results: The high ΔPCO2 group showed significant lower blood glucose level (p = 0.038) than the normal ΔPCO2 group. Serum lactate, heart rate, and APACHE score were significantly higher in high ΔPCO2 group than normal ΔPCO2 group (p, 0.012, 0.013, and 0.020, respectively). As regard to the clinical outcome, patient mortality was significantly higher (p = 0.042) in high ΔPCO2 group than normal ΔPCO2 group and the number of organ dysfunction was higher in high ΔPCO2 group than normal ΔPCO2 group but not reached a significant level (p = 0.625). Conclusions: ΔPCO2 is a reliable index for early prediction of clinical outcome including organ dysfunction and mortality in patients with sepsis and septic shock.

A Method for the Prediction of Clinical Outcome Using Diffusion Magnetic Resonance Imaging: Application on Parkinson’s Disease

Robust early prediction of clinical outcomes in Parkinson’s disease (PD) is paramount for implementing appropriate management interventions. We propose a method that uses the baseline MRI, measuring diffusion parameters from multiple parcellated brain regions, to predict the 2-year clinical outcome in Parkinson’s disease. Diffusion tensor imaging was obtained from 82 patients (males/females = 45/37, mean age: 60.9 ± 7.3 years, baseline and after 23.7 ± 0.7 months) using a 3T MR scanner, which was normalized and parcellated according to the Automated Anatomical Labelling template. All patients were diagnosed with probable Parkinson’s disease by the National Institute of Neurological Disorders and Stroke criteria. Clinical outcome was graded using disease severity (Unified Parkinson’s Disease Rating Scale and Modified Hoehn and Yahr staging), drug administration (levodopa equivalent daily dose), and quality of life (39-item PD Questionnaire). Selection and regularization of diffusion parameters, the mean diffusivity and fractional anisotropy, were performed using least absolute shrinkage and selection operator (LASSO) between baseline diffusion index and clinical outcome over 2 years. Identified features were entered into a stepwise multivariate regression model, followed by a leave-one-out/5-fold cross validation and additional blind validation using an independent dataset. The predicted Unified Parkinson’s Disease Rating Scale for each individual was consistent with the observed values at blind validation (adjusted R2 0.76) by using 13 features, such as mean diffusivity in lingual, nodule lobule of cerebellum vermis and fractional anisotropy in rolandic operculum, and quadrangular lobule of cerebellum. We conclude that baseline diffusion MRI is potentially capable of predicting 2-year clinical outcomes in patients with Parkinson’s disease on an individual basis.

P256 Anti-glycan antibody seropositivity at diagnosis does not predict future disease course in patients with Crohn’s disease

Abstract Background Biomarkers predictive of a patient’s future disease course are critical for personalised medicine. There are two Crohn’s disease (CD) assays with validated associations to a clinical outcome; seropositivity for anti-glycan antibodies (AGAs, Glycominds) and a transcriptional signature of T-cell exhaustion (PredictSURE-IBD™, PS-IBD). The optimal time to use these tests would be at diagnosis before bowel damage occurs. As AGAs have primarily been measured in patients after therapy it’s unclear if they provide prognostic information at diagnosis. To address this we performed a head-to-head comparison of both tests in newly diagnosed CD patients. Methods We recruited 74 CD patients with active disease; all patients gave written informed consent and were managed using an accelerated step-up strategy in accordance with international guidelines. Active disease was confirmed by one or more objective marker (raised CRP/calprotectin or endoscopic review) and active symptoms. AGA seropositivity was measured at Addenbrooke’s with the IBDX panel (Glycominds) according to manufacturer’s instructions. Patient stratification was also performed using the PS-IBDtest (PredictImmune Ltd) according to manufacturer’s instructions. Results Most (80%–59/74) patients were newly diagnosed; 58% (43/74) were seropositive for at least 1 AGA, 19% (14/74) were positive for ≥2 AGAs. Newly diagnosed patients had fewer AGAs (51%, 30/59) than previously diagnosed (87%, 13/15) patients (p = 0.018). We stratified patients into two groups based on seropositivity for 2 or more AGAs—associated with an increased risk of more severe disease but found no significant difference in time to, or frequency of, treatment escalation between the groups. Stratification of patients into IBDhi and IBDlo groups with PS-IBDrevealed a significant difference in the subsequent disease course with IBDhi patients experiencing more aggressive disease, characterised by a shorter time to treatment escalation compared with IBDlo patients (p = 0.001). Conclusion AGA seropositivity at diagnosis (as assessed using the IBDX antibody panel) did not predict the need to escalate treatment due to frequently-relapsing or chronically-active disease. Lower AGA seropositivity in newly diagnosed patients compared with those with previous diagnoses suggested that the extent of antibody positivity is a function of disease duration. Previously reported associations between AGA positivity and disease outcome may, therefore, reflect retrospective aggressive disease course and are unlikely to be useful for informing treatment decisions in newly diagnosed patients. The PS-IBD test result correlated with subsequent disease course indicating suitability for early prediction of clinical outcome.

Early prediction of clinical outcomes in patients with aneurysmal subarachnoid hemorrhage using computed tomography texture analysis

Radiological evaluation of subarachnoid hemorrhage (SAH) is often subject to interobserver variability. The aim of this study was to retrospectively detect computed tomography (CT) texture parameters in the early postictal state to predict cerebral vasospasm, delayed cerebral ischemia (DCI), and functional outcome in aneurysmal SAH using quantitative CT texture analysis (CTTA) via a commercially available software program and routine CT images. 40 patients with aneurysmal SAH surgically treated at the Keio University Hospital during a four-year period were analyzed. CT texture analyses were performed using a commercially available software program (Synapse Vincent). The following texture parameters of blood clots in the subarachnoid space and cerebral edema were assessed: mean CT value, entropy, skewness, and kurtosis. The mean CT value of blood clots in the subarachnoid space was significantly associated with cerebral vasospasm, DCI, and functional outcome. The mean CT value ≥ 49.64 Hounsfield units (HU) predicted cerebral vasospasm with a sensitivity and specificity of 85.7% and 61.5%, respectively (area under the curve [AUC] = 0.758). The mean CT value ≥ 49.95 HU predicted DCI with a sensitivity and specificity of 100% and 60.6%, respectively (AUC = 0.810). The mean CT value ≥ 53.00 HU predicted poor functional outcome with a sensitivity and specificity of 56.3% and 91.7%, respectively (AUC = 0.747). CTTA using a commercially available software program demonstrated that the mean CT value of clots in the subarachnoid space in the early postictal state could predict vasospasm, DCI, and clinical outcome with a high sensitivity and specificity.

Measuring on-treatment genome-wide tumor copy number alterations in cell-free DNA (cfDNA) in plasma is highly prognostic in metastatic breast cancer.

1097 Background: The clinical management of metastatic breast cancer depends on the measurement of tumor response to successive drugs by serial imaging and changes in blood tumor markers, which remain the standard of care despite poor sensitivity and specificity. Highly sensitive and specific cfDNA secreted from the tumor can detect the changes in tumor-specific aberrations that have been shown to be associated with patient response in the metastatic setting. However, most approaches require prior sequencing of the tumor to target specific known mutations. Methods: Using low coverage genomic sequencing, a genomic instability number (GIN) was measured in cfDNA based on the detection of genome-wide tumor-specific DNA copy number alterations for 27 patients with metastatic breast cancer. The GIN value and its variation from baseline before treatment, as well as within 10 days and 3 weeks after start of therapy were compared with tumor response, progression free survival (PFS) and overall survival (OS) of the patients. Patients were followed for a median of 22 months and we used a previously published GIN threshold at 170 for high vs low GIN values. Sequencing was performed blinded to the clinical results. Results: Baseline GIN values were not associated with tumor response at 3or 6 months, but showed a trend towards lower OS with higher GIN (p = 0.12). GIN values fell by an average of 28% in responders (stable disease or response) and 23% in those with progression (p = 0.85), but remained lower at 3 weeks only in the responders. High GIN values within 10 days and 3 weeks were associated with markedly worse OS (p = 0.014 and p = 0.009 respectively) and those at 3 weeks with worse PFS (p = 0.017). Hence the median survival of patients with high GIN at 10 days or 3 weeks was 12 months vs not reached for those with low GIN. The percentage drop of GIN at 10 days but not at 3 weeks was significantly associated with PFS (p = 0.016). Conclusions: These results demonstrate that GIN values of cfDNA measured at early on-treatment time points can predict PFS and OS with a high degree of accuracy. These findings deserve further study in a larger cohort but hold the promise of early prediction of clinical outcomes in a tumor-independent genome-wide approach.

Correlation between fractional anisotropy changes in the targeted ventral intermediate nucleus and clinical outcome after transcranial MR-guided focused ultrasound thalamotomy for essential tremor: results of a pilot study.

This study evaluated changes of fractional anisotropy (FA) in the ventral intermediate nucleus (VIM) of the thalamus after transcranial MR-guided focused ultrasound (TcMRgFUS) thalamotomy and their associations with clinical outcome. Clinical and radiological data of 12 patients with medically refractory essential tremor (mean age 76.5 years) who underwent TcMRgFUS thalamotomy with VIM targeting were analyzed retrospectively. The Clinical Rating Scale for Tremor (CRST) score was calculated before and at 1 year after treatment. Measurements of the relative FA (rFA) values, defined as ratio of the FA value in the targeted VIM to the FA value in the contralateral VIM, were performed before thalamotomy, and 1 day and 1 year thereafter. TcMRgFUS thalamotomy was well tolerated and no long-term complications were noted. At 1-year follow-up, 8 patients demonstrated relief of tremor (improvement group), whereas in 4 others persistent tremor was noted (recurrence group). In the entire cohort, mean rFA values in the targeted VIM before treatment, and at 1 day and 1 year after treatment, were 1.12 ± 0.15, 0.44 ± 0.13, and 0.82 ± 0.22, respectively (p < 0.001). rFA values were consistently higher in the recurrence group compared with the improvement group, and the difference reached statistical significance at 1 day (p < 0.05) and 1 year (p < 0.01) after treatment. There was a statistically significant (p < 0.01) positive correlation between rFA values in the targeted VIM at 1 day after thalamotomy and CRST score at 1 year after treatment. Receiver operating characteristic curve analysis revealed that the optimal cutoff value of rFA at 1 day after thalamotomy for prediction of symptomatic improvement at 1-year follow-up is 0.54. TcMRgFUS thalamotomy results in significant decrease of rFA in the targeted VIM, at both 1 day and 1 year after treatment. Relative FA values at 1 day after treatment showed significant correlation with CRST score at 1-year follow-up. Therefore, FA may be considered a possible imaging biomarker for early prediction of clinical outcome after TcMRgFUS thalamotomy for essential tremor.

Early prediction of clinical outcomes in resected stage II and III colorectal cancer (CRC) through deep sequencing of circulating tumor DNA (ctDNA).

3591 Background: Adjuvant chemotherapy is offered to most pts with Stage III CRC, and to a subset with Stage II disease deemed at high-risk for recurrence. Nevertheless, risk stratification strategies remain suboptimal. Detection of minimal residual disease (MRD) through ctDNA analysis has been shown to identify pts at high recurrence risk in Stage II CRC, but not Stage III disease. Methods: The next-generation sequencing based AVENIO ctDNA Surveillance Kit (Research Use Only) was used to identify single nucleotide variants (SNVs) in tumor tissue within a cohort of 145 Stage II and III CRC pts following R0 surgical resection (n = 86 and 59 respectively; median follow-up = 32.1 mo). The same assay was used to monitor ctDNA with a single post-operative blood sample (mean surgery-to-phlebotomy time: 10 days). Regions from 197 genes recurrently mutated in CRC were interrogated, and pts were classified as ctDNA positive (+) or negative (-) in plasma based on the detection of SNVs previously identified in tumor tissue. Results: Variants were identified in 99% of tumors (n = 144) with a median of 4 SNVs/sample (range 1-24) and all post-operative plasma samples were successfully profiled. Pts with detectable ctDNA (n = 12) displayed a significantly shorter 2-year relapse-free survival (RFS; 17% vs 88%; HR 10.3; 95% CI 2.3-46.9; p &lt; 0.00001), time to recurrence (TTR; HR 20.6; 95% CI 3.1-139.0; p &lt; 0.00001) and overall survival (OS; HR 3.4; 95% CI 0.5-25.8; p = 0.041) than ctDNA- pts (n = 132). 11 (92%) of ctDNA+ pts developed recurrence compared to 9 (7%) of ctDNA- pts. Monitoring multiple variants doubled sensitivity of MRD detection compared to tracking a single driver mutation. TTR was shorter in ctDNA+ vs ctDNA- Stage II (HR 23.1, 95% CI 0.28-1900.4; p &lt; 0.00001) and stage III pts (HR 17.9; 95% CI 2.7-117.3, p &lt; 0.00001). TTR of Stage II and III ctDNA- pts was similar (p = 0.7). Conclusions: Our results indicate that ctDNA analysis can detect MRD within days after complete resection of CRC and accurately identifies pts at high risk of recurrence in both Stage II and III CRC. MRD detection via ctDNA sequencing may allow personalization of adjuvant treatment strategies.

MPTP Induces Systemic Parkinsonism in Middle-Aged Cynomolgus Monkeys: Clinical Evolution and Outcomes.

In this study, we developed a systemic PD model in middle-aged cynomolgus monkeys using individualized low-dose MPTP, to explore effective indicators for the early prediction of clinical outcomes. MPTP was not stopped until the animals showed typical PD motor symptoms on days 10 to 13 after MPTP administration when the Kurlan score reached 10; this abrogated the differences in individual susceptibility to MPTP. The clinical symptoms persisted, peaking on days 3 to 12 after MPTP withdrawal (rapid progress stage), and then the Kurlan score plateaued. A Kurlan score at the end of the rapid progress stage >15 reflected stable or slowly-progressive PD, while a score <15 indicated spontaneous recovery. The entire clinical evolution and outcome of the systemic PD model was characterized in this study, thus providing options for therapeutic and translational research.

Diffuse optical measurements of head and neck tumor hemodynamics for early prediction of chemoradiation therapy outcomes.

This study used a hybrid near-infrared diffuse optical instrument to monitor tumor hemodynamic responses to chemoradiation therapy for early prediction of treatment outcomes in patients with head and neck cancer. Forty-seven patients were measured once per week to evaluate the hemodynamic status of clinically involved cervical lymph nodes as surrogates for the primary tumor response. Patients were classified into two groups: complete response (CR) (n=29) and incomplete response (IR) (n=18). Tumor hemodynamic responses were found to be associated with clinical outcomes (CR/IR), wherein the associations differed depending on human papillomavirus (HPV-16) status. In HPV-16 positive patients, significantly lower levels in tumor oxygenated hemoglobin concentration ([HbO2]) at weeks 1 to 3, total hemoglobin concentration at week 3, and blood oxygen saturation (StO2) at week 3 were found in the IR group. In HPV-16 negative patients, significantly higher levels in tumor blood flow index and reduced scattering coefficient (μs′) at week 3 were observed in the IR group. These hemodynamic parameters exhibited significantly high accuracy for early prediction of clinical outcomes, within the first three weeks of therapy, with the areas under the receiver operating characteristic curves (AUCs) ranging from 0.83 to 0.96.

EARLY PREDICTION OF ACUTE ISCHEMIC STROKE OUTCOME BY USING ALBERTA STROKE PROGRAM EARLY CT SCORE (ASPECTS)

Background and Purpose: The Alberta Stroke Program Early CT Score (ASPECTS) scale semiquantitatively assesses extent and location of ischemic changes within the middle cerebral artery (MCA) territory using a 10-point grading system. ASPECTS measured at baseline using noncontrast computed tomography (CT) scan. The aim of this study was to assess early prediction of clinical outcome after acute ischemic stroke by ASPECTS scale. Methods: The study based on convenience sample which included 82 first-ever acute ischemic stroke patients, admitted to Hue Central Hospital within 72 hours of stroke onset, from October 2013 to October 2014. Ischemic territory changes were defined as parenchymal CT hypoattenuation. We assessed all baseline CT scans, dichotomized ASPECTS at ≤ 7 and &gt;7, defined good outcome (0 to 2) and poor outcome (3 to 6) as modified Rankin Scale (mRS) score at discharge. Univariate analysis and multivariable logistic regression analysis were performed to define the independent predictors for stroke outcome. Results: Mean age was 68.35 ± 13.93 years, proportion of male (51.2%) and female (48.8%) are approximately the same. ASPECTS score &gt; 7 in 57 patients and ≤ 7 in 25 patients. Mean ASPECTS was 7.51 ± 2.25. Mean mRS at discharge was 2.28 ± 1.33. Good outcome (mRS ≤ 2) and poor outcome (mRS &gt; 2) at discharge were 63.4% and 36.6% respectively. There is a negative correlation between ASPECTS and mRS (r = -0.86, p &lt; 0.001). In the univariate analysis, atrial fibrillation, Glasgow Coma Scale (GCS) score at admisison, ASPECT score and infarct volume were significantly associated with stroke outcome. All of aforementioned variables underwent multivariate analysis, but none of them was proven to be an independent predictor of early outcome. Conclusion: In patients with first-ever acute ischemic stroke, ASPECT score which bases on conventional computed tomography scan is not independent predictor for clinical outcome at discharge. Key words: ischemic stroke, ASPECTS, outcome

A population pharmacodynamic model for lactate dehydrogenase and neuron specific enolase to predict tumor progression in small cell lung cancer patients.

The development of individualized therapies poses a major challenge in oncology. Significant hurdles to overcome include better disease monitoring and early prediction of clinical outcome. Current clinical practice consists of using Response Evaluation Criteria in Solid Tumors (RECIST) to categorize response to treatment. However, the utility of RECIST is restricted due to limitations on the frequency of measurement and its categorical rather than continuous nature. We propose a population modeling framework that relates circulating biomarkers in plasma, easily obtained from patients, to tumor progression levels assessed by imaging scans (i.e., RECIST categories). We successfully applied this framework to data regarding lactate dehydrogenase (LDH) and neuron specific enolase (NSE) concentrations in patients diagnosed with small cell lung cancer (SCLC). LDH and NSE have been proposed as independent prognostic factors for SCLC. However, their prognostic and predictive value has not been demonstrated in the context of standard clinical practice. Our model incorporates an underlying latent variable ("disease level") representing (unobserved) tumor size dynamics, which is assumed to drive biomarker production and to be influenced by exposure to treatment; these assumptions are in agreement with the known physiology of SCLC and these biomarkers. Our model predictions of unobserved disease level are strongly correlated with disease progression measured by RECIST criteria. In conclusion, the proposed framework enables prediction of treatment outcome based on circulating biomarkers and therefore can be a powerful tool to help clinicians monitor disease in SCLC.

Abstract T P122: Functional Independence Measure Scores Predict Self-care Levels Required for Post-acute Stroke Patients Classified by the Long-Term Care Insurance System in Japan: A Multicenter Retrospective Cohort Study

Background and purpose: Early prediction of clinical outcomes in stroke patients is socioeconomically important. The aim of this study was to clarify whether Functional Independence Measure (FIM) scores on admission can predict their discharge destinations and future self-care levels required for post-acute stroke patients classified by the Long-Term Care Insurance (LTCI) system, the national insurance plan for care in Japan. Methods: We enrolled post-acute stroke patients admitted to 12 convalescent rehabilitation wards (CRW) from 9 acute stroke centers. A CRW was defined as a specialized ward for intensive rehabilitation to prevent a bedridden state and to promote home rehabilitation by improving ability to perform activities of daily living. We evaluated self-care abilities using FIM scores and modified Rankin Scale (mRS) scores as traditional assessment scales and compared with certified self-care levels within the LTCI system (seven levels; slight impairment to bedridden). We divided patients into those who were discharged home from a CRW and all others. Results: Among 1261 patients (47% female, mean age 75 years), 984 (78%) were discharged home. FIM scores at discharge were significantly correlated with both mRS scores at discharge and certified self-care levels within the LTCI system (P &lt; .001). The cut-off values for home discharge were a FIM score on admission of 50 points and an age of 75 years. On multivariate analysis, FIM scores ≥50 on admission [odds ratio (OR), 95% confidence interval (95% CI); 5.80, 4.30-7.91] and age &lt;75 years (2.16, 1.60-2.95) were independently associated with home discharge. Conclusions: FIM scores in post-acute stroke patients can predict self-care levels within the LTCI system. Early prediction of self-care levels may promote careful preparation of healthcare planning and improve the efficiency of stroke management.

Choi response criteria for early prediction of clinical outcome in patients with metastatic renal cell cancer treated with sunitinib

Background:Because sunitinib can induce extensive necrosis in metastatic renal cell cancer (mRCC), we examined whether criteria defined by Choi might be valuable to predict early sunitinib efficacy.Methods:Computed tomography was used for measurement of tumour lesions in mm and lesion attenuation in Hounsfield units (HUs). According to Choi criteria partial response (PR) was defined as ⩾10% decrease in size or ⩾15% decrease in attenuation.Results:A total of 55 mRCC patients treated with sunitinib were included. At first evaluation, according to the Response Evaluation Criteria in Solid Tumours (RECIST) 7 patients had PR, 38 stable disease (SD), and 10 progressive disease (PD), whereas according to Choi criteria 36 patients had PR, 6 SD and 13 PD. Median tumour attenuation decreased from 66 to 47 HUs (P⩽0.001). In patients with PR, Choi criteria had a significantly better predictive value for progression-free survival and overall survival (both Ps<0.001) than RECIST (P=0.685 and 0.191 respectively). The predictive value for RECIST increased (P=0.001 and <0.001 respectively), when best response during treatment was taken into account.Conclusion:Choi criteria could be helpful to define early mRCC patients who benefit from sunitinib, but the use of these criteria will not change the management of these patients.