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Automated behavior analysis are promising tools to overcome current assessment limitations in psychiatry. At 9 months of age, we recorded 32 infants with West syndrome (WS) and 19 typically developing (TD) controls during a standardized mother–infant interaction. We computed infant hand movements (HM), speech turn taking of both partners (vocalization, pause, silences, overlap) and motherese. Then, we assessed whether multimodal social signals and interactional synchrony at 9 months could predict outcomes (autism spectrum disorder (ASD) and intellectual disability (ID)) of infants with WS at 4 years. At follow-up, 10 infants developed ASD/ID (WS+). The best machine learning reached 76.47% accuracy classifying WS vs. TD and 81.25% accuracy classifying WS+ vs. WS−. The 10 best features to distinguish WS+ and WS− included a combination of infant vocalizations and HM features combined with synchrony vocalization features. These data indicate that behavioral and interaction imaging was able to predict ASD/ID in high-risk children with WS.

Introduction/Background Clinical trials in Epithelial Ovarian Cancer (EOC) frequently examine treatment at a particular phase of the patient’s disease trajectory. Few major studies have examined the management of patients from diagnosis to death. This international network was developed to compare treatment sequencing and outcomes from six centres across Europe and South Korea. Methodology This retrospective cohort study used longitudinal data collected from electronic medical records from 6 European and South Korean treatment centres. A standard protocol & common data model was developed to capture consistent data for patients diagnosed between January 2012 and December 2018, with a minimum of 12 months follow-up. Full treatment data was collected and categorized in programmes of care based on exemplar patient narratives. An extensive data harmonization process was implemented to ensure different country and site medical records were interpreted in a common manner. Overall survival (OS) and time to next treatment (TTNT) were estimated using Kaplan Meier methodology and outcomes stratified by categories of interest. Each site analysed their own EMR data and shared aggregated results for comparison. Results Table 1 demonstrates patient characteristics from six sites. In total the overall study cohort includes 2889 patients. Median age for each centre ranged from 53 to 67 years. The majority of patients were FIGO stage III (range 31% to 66%) and high-grade serous morphology (52% to 69.9%) Additional data on treatment pathways and outcomes for each centre will be presented. Conclusion Preliminary analysis from this network suggests a consistent profile of adults treated for EOC across most contributing treatment centres in Europe, but with some substantial differences compared to patients treated at centres in South Korea and Romania. The establishment of a common data model between sites across five different countries allows for detailed exploration of the factors influencing differences in patient management and treatment outcomes in ovarian cancer patients. Disclosures Sue Cheeseman: I receive consultancy fees from IQVIA Bethany Levick: I am an employee of IQVIA Eunji Nam: I have no conflict of interest to disclose Dongkyu Kim: I have no conflict of interest to disclose Roman Rouzier: I have no conflict of interest to disclose Claire Bonneau: I have no conflict of interest to disclose Paul Kubelac: served on a speaker’s bureau for Roche, Bristol-Myers Squibb, AstraZeneca, Novartis. Patriciu Achimas-Cadariu: I have no conflict of interest to disclose Jean-Marc Classe: I have no conflict of interest to disclose Francois Bocquet: I have no conflict of interest to disclose Sven Becker: I have no conflict of interest to disclose Mariana Guergova-Kuras: I am an employee of IQVIA Geoff Hall: I receive grant support and consultancy fees from IQVIA

e13554 Background: The value of real-world evidence derived from the care of patients managed outside the context of clinical trials is well recognised. However, the ability to link data from multiple centres, especially those from different countries, is complicated by complex legal and information governance differences. The Oncology Evidence Network is a collaboration of large hospital centres, with strong clinical informatics capabilities in six countries in Europe and Asia working with the support of an industrial partner to provide high quality, real world data reflecting routine clinical care. We have developed an efficient workflow based on a study-specific common data model (CDM) clinically validated at each site and analysed with a single analysis script, which embeds a set of data quality rules. Local implementation allows each centre to generate analytical outputs aligned across the different sites without the need for any patient level data to leave the participating site. This approach has been designed and tested in Epithelial Ovarian Cancer (EOC) patients. Methods: A CDM was agreed using expert advisors from each centre. Clinical alignment was achieved through iterative assessment of clinical vignettes, to ensure common definitions of clinical assessment, prognosis, and treatment algorithms in EOC patients. A data guide detailing variable level derivations and validation rules, general data coding principles, and conversions/codes from international coding systems was developed. The analysis scripts were implemented as a bespoke package (OpenOvary) in R. The package includes functions to validate the data against the CDM, and generate a standard output including tables, numerical summaries and Kaplan-Meier analysis of progression and overall survival. Results: 2,925 patient records from 6 centres across 6 countries were included in the study with 27 key data items curated by each centre. Treatment data is available detailing relevant surgical procedures and their outcomes, and regimens of SACT throughout patients’ care from diagnosis to death. Data completeness was generally high for key data items, with missing data ranging from 0-16% for FIGO stage at diagnosis and 0-14% for tumour morphology. The CDM and R script will be made publicly available for other centres to adopt and facilitate analysis of their local data. Conclusions: This collaboration has brought together a substantial body of data describing the care and outcomes for EOC patients. A CDM and flexible shared analysis approach enabled unified analysis and reporting whilst avoiding the transfer of patient level data and its pooling into a common database. The process of clinical and data alignment has generated a replicable model for rapid extension to other study centres to join the EOC study, or application to other disease areas.

5531 Background: Few major studies have examined and compared the management and outcomes of patients from diagnosis to death between countries. We have established an international collaboration across Europe and South Korea to compare treatment and outcomes in Epithelial Ovarian Cancer (EOC). Methods: Patients diagnosed with EOC between January 2012 and December 2018 (age ≥18), were included for analysis. Data from medical records from five European and a single South Korean treatment centre were extracted, standardised to a common data model and analysed at each centre using a common script developed in R. Time to each progression/recurrence event (defined as time to next treatment) and overall survival have been estimated using Kaplan Meier methodology and outcomes stratified by categories of interest. Changes in the use of anti-cancer therapies over time and the incidence of BRCA mutations and incidence/timing of second breast cancers have also been examined. Results: A total cohort of 2925 patients was identified with a median age at each centre of 53 to 67 years. Advanced disease (FIGO stage III - IV) (range 57% to 84%) and high-grade serous morphology (38% to 70%) were most common at each centre. The timing of surgery (primary, interval debulking or delayed) and the proportion of patients undergoing surgery varied with stage. Patients with stage I disease where most likely to undergo surgery (range 73% to 100%) and stage IV the least (range 39% to 84%). Median overall survival for high grade serous cancers ranged from 1.9 to 4.9 years, and for the whole cohort from 2.1 to 5.5 years. Median time to next treatment at first relapse for the whole cohort ranged from 14 to 22 months. Second breast cancers were noted in 6 to 17% of patients and the majority of these occurred before the diagnosis of EOC at a median time of 96 to 118 months prior to diagnosis of EOC. Additional data on treatment pathways, BRCA status and outcomes by line of therapy for each centre will be presented. Conclusions: Preliminary analysis of results across this network suggests a variation in patient populations between sites and substantial differences in both treatments and outcomes. The establishment of a common data model and the use of a common analytic script between sites across six different countries allows for detailed exploration of the factors influencing differences in patient management and treatment outcomes in ovarian cancer patients.

Background: Gastric cancer (GC) is the third leading cause of cancer death. Early detection is a key factor to reduce its mortality. Methods: We retrospectively collected pre- and postoperative serum samples as well as tumor tissues and adjacent normal tissues from 100 GC patients. Serum samples from non-cancerous patients were served as controls (n=50). A high-throughput protein detection technology, multiplex proximity extension assays (PEA), was applied to measure levels of over 300 proteins. Alteration of each protein was analyzed by univariate analysis. Elastic-net logistic regression was performed to select serum proteins into the diagnostic model. Findings: We identified 19 serum proteins (CEA, CA9, MSLN, CCL20, SCF, TGF-alpha, MMP-1, MMP-10, IGF-1, CDCP1, PPIA, DDAH-1, HMOX-1, FLI1, IL-7, ZBTB-17, APBB1IP, KAZALD-1, and ADAMTS-15) that together distinguish the GC cases from controls with a diagnostic sensitivity of 93%, specificity of 100%, and area under receiver operating characteristic curve (AUC) of 0·99 (95% CI: 0·98-1). Moreover, the 19-serum protein signature provided a satisfactory diagnostic capacity in patients at TNM I-II stage (sensitivity 89%, specificity 100%, AUC 0·988) and in patients with high microsatellite instability (91%, 98%, and 0·990). A large-scale independent cohort of cases and controls will be necessary for validating the proposed protein signature. Interpretation: Based on targeted proteomics and elastic-net logistic regression, we identified a 19-serum protein signature which could contribute to clinical GC diagnosis. Funding Statement: This study was supported by a Marie Curie ITN grant (316929, GastricGlycoExplorer). Funder had no influence on trial design, data evaluation, and interpretation. Declaration of Interests: The authors declare that they have no competing interests. Ethics Approval Statement: This study was conducted following the Declaration of Helsinki. All patients were provided with the informed consent and ethical approval was granted by the Institutional Ethics Committee of University of Siena.

International audience; Introduction: The identification of frequent acquired mutations shows that patients with oligodendrogliomas have divergent biology with differing prognoses regardless of histological classification. A better understanding of molecular features as well as their metabolic pathways is essential.Objectives: The aim of this study was to examine the relationship between the tumor metabolome, six genomic aberrations (isocitrate dehydrogenase1 [IDH1] mutation, 1p/19q codeletion, tumor protein p53 [TP53] mutation, O6-methylguanin-DNA methyltransferase [MGMT] promoter methylation, epidermal growth factor receptor [EGFR] amplification, phosphate and tensin homolog [PTEN] methylation), and the patients' survival time.Methods: We applied 1H high-resolution magic-angle spinning (HRMAS) nuclear magnetic resonance (NMR) spectroscopy to 72 resected oligodendrogliomas.Results: The presence of IDH1, TP53, 1p19q codeletion, MGMT promoter methylation reduced the relative risk of death, whereas PTEN methylation and EGFR amplification were associated with poor prognosis. Increased concentration of 2-hydroxyglutarate (2HG), N-acetyl-aspartate (NAA), myo-inositol and the glycerophosphocholine/phosphocholine (GPC/PC) ratio were good prognostic factors. Increasing the concentration of serine, glycine, glutamate and alanine led to an increased relative risk of death.Conclusion: HRMAS NMR spectroscopy provides accurate information on the metabolomics of oligodendrogliomas, making it possible to find new biomarkers indicative of survival. It enables rapid characterization of intact tissue and could be used as an intraoperative method.

Microsatellite instability (MSI) is a distinct molecular subtype of gastric cancer. In recent years, the clinical consequences of MSI and the therapeutic opportunities to target this peculiar cancer subtype became evident. However, despite the importance of MSI for the stratification of patients, the time and resources required for diagnosis still present an obstacle. In an attempt to identify a new marker for MSI in gastric cancer, we evaluated the expression of five cancer-associated glycan epitopes in a cohort of 13 MSI and 17 microsatellite stable (MSS) cases. Our analysis revealed a highly significant (p < 0.001) association between the expression of the Thomsen-Friedenreich (TF) antigen and MSI status. Hence, we present here the identification of the first single marker for MSI in gastric cancer, excelling with a specificity of 94% (16/17), sensitivity of 69.2% (9/13), negative predictive value of 80% (16/20), and positive predictive value of 90% (9/10). The TF antigen, detected by simple antibody-based assays, is highly specific for carcinoma being undetectable in gastric healthy and premalignant epithelia. This finding lays the basis for new studies and holds promise in improving the rapid identification of MSI in the clinical setting.

Dengue remains an unmet public health burden. We determined risk factors for dengue in-hospital mortality in Brazil. Of 326,380 hospitalised dengue cases in 9-45-year-old individuals, there were 971 deaths. Risk of dying was 11-times higher in the presence of underlying common comorbidities (renal, infectious, pulmonary disease and diabetes), similar to the risk of dying from severe dengue and much higher with the combination. Ensuring access to integrated dengue preventative measures in individuals aged ≥ 9 years including those with comorbidities may help achieve the WHO objective of 50% reduction in mortality and 25% reduction in morbidity due to dengue by 2020.