Conflict Resilience

Although large-scale wars and interstate conflicts have almost disappeared, intrastate conflicts remain widespread and result in a high number of victims. During the last ten years, the number of fatalities was substantially higher than in the previous decade. Though these conflicts take place outside the borders of the EU, they can generate important direct and indirect effects. Moreover, they are connected to climate change, can lead to various disasters, geopolitical effects, or material supply disruptions. The concept of resilience has recently gained ground as a framework for addressing contemporary global threats. It has also become the key principle in the EU’s external action. One of its key building blocks is the modelling and monitoring of conflict risk to allow early action. Conflict resilience refers to the capacity of a state to resist a drift towards violence contrary to the structural conditions prevailing (pre-conflict resilience). It also includes the response of a state in the presence of a conflict (post-conflict resilience). Evaluating the pre-conflict resilience of states can provide insights into conflict aversion or enable a warning for the eruption of violence. On the other hand, the study of postconflict resilience may unveil the adaptive and transformative mechanisms that can be followed by other war-torn countries. Climate change and conflicts are closely related. For example, climate change exacerbates current conflict drivers like food insecurity, competition for water and land resources, poverty and internal displacement of people. Adaptation and mitigation policies may lead to new regulations or infrastructures (like new hydropower reservoirs) which can generate tensions and eventually conflicts. Finally, conflict-torn countries are unable to invest in adaptation strategies, which makes them even more vulnerable to climate change effects.JRC.E.1-Disaster Risk Managemen

The Global Conflict Risk Index: Artificial intelligence for conflict prevention

The Global Conflict Risk Index (GCRI), which was designed by the European Commission’s Joint Research Centre (JRC), is the quantitative starting point of the EU’s conflict Early Warning System. Taking into consideration the needs of policy-makers to prioritize actions towards conflict prevention, the GCRI expresses the statistical risk of violent conflict in a given country in the upcoming one to four years. It is based on open source data and grounded in the assumption that the occurrence of conflict is linked to structural conditions, which are used to compute the probability and intensity of conflicts. While the initial GCRI model was estimated by means of linear and logistic regression models, this report presents a new GCRI model based on the Artificial Intelligence (AI) random forest (RF) approach. The models’ hyperparameters are optimized using a ten-fold cross validation. Overall, it is demonstrated that the random forest GCRI models are internally stable, not overfitting, and have a good predictive power. The precision and accuracy metrics are above 98%, both for the national power and subnational power conflict models. The AI GCRI, as a supplementary modelling method for the European conflict prevention policy agenda, is scientifically robust as a baseline quantitative evaluation of armed conflict risk additional to the linear and logistic regression GCRI.JRC.E.1-Disaster Risk Managemen

Dynamic Global Conflict Risk Index

This report presents a dynamic model of the Global Conflict Risk Index (GCRI), a conflict risk model supporting the design of European Union’s (EU) conflict prevention strategies developed by the Joint Research Centre (JRC) of the European Commission (EC) in collaboration with an expert panel of researchers and policy-makers. While most studies as well as the regression GCRI measure conflict intensity by counting the number of causalities, the proposed dynamic GCRI integrates and identifies every stage of the conflict development or de-escalation in its entire complexity. The emergence of conflict related event data sets offers researchers new ways to quantify and predict conflicts through big data. Using country-level actor-based event data sets that signal potential triggers to violent conflict such as demonstrations, strikes, or elections-related violence, the model aims at estimating the occurrence of material conflict events, under the assumption that an increase in material conflict events goes along with a decrease in material and verbal cooperation. Three potential datasets are tested in this report following a political event coding classification: (i) the Global Data on Events Location and Tone (GDELT) project, (ii) the Integrated Crisis Early Warning System (ICEWS) Dataverse dataset and (iii) the Phoenix - Open Event Data Alliance (OEDA)-Phoenix Dataset. The Artificial Intelligence (AI) methodology adopted to model the dynamic GCRI is built upon a Long-Short Term Memory (LSTM) Cell Recurrent Neural Network (RNN). These models are well-suited to classify, process and make predictions based on time series data and forecast near future events. Besides this AI model, we have set up an early warning alarm system to signal abnormal social unrest upheavals. The dynamic GCRI, through the AI and early warning alarm, seems to be able to predict the materialization of a conflict on a monthly basis. This new tool gives policy makers the possibility to observe the situation in a country on a monthly base, taking into consideration both the current and the predicted available information, and to implement preventive actions more rapidly to mitigate conflict exacerbations at an earlier stage of the conflict development cycle.JRC.E.1-Disaster Risk Managemen

Clinical characteristics and outcomes of children with stage 3-5 chronic kidney disease.

The aim of this study was to report on the clinical characteristics and outcomes of Belgian children with chronic kidney disease (CKD). Between 2001 and 2005, we followed 143 new successive patients younger than 20 years of age with a glomerular filtration rate of <60 ml/min/1.73 m(2) prospectively in a Belgian department of pediatric nephrology. The incidence of diagnosed CKD was 11.9 per million child population (pmcp), and the incidence of renal replacement therapy was 6.2 pmcp. There were 67% patients in CKD stage 3, 19% in CKD stage 4 and 14% in CKD stage 5. Patients with congenital anomalies of the kidney and urinary tract (CAKUTs), hereditary diseases and glomerular diseases were diagnosed at a median age of 1, 2 and 10 years, respectively. CAKUTs were the main causes of CKD, accounting for 59% of all cases. After 3, 4 and 5 years of follow-up, 27, 31 and 38% of patients treated conservatively, respectively, reached end-stage renal failure (ESRF). The progression rate to ESRF was eightfold higher in patients with CKD stage 4 than in those with CKD stage 3. Among our patient group, hereditary diseases progressed more rapidly to ESRF than CAKUTs. Transplantation was performed preemptively in 22% of these children. Infections and cardiovascular diseases were the main causes of death

Proportion and stage distribution of screen-detected and non-screen-detected colorectal cancer in nine European countries: an international, population-based study

Background: The effects of recently implemented colorectal cancer screening programmes in Europe on colorectal cancer mortality will take several years to be fully known. We aimed to analyse the characteristics and parameters of screening programmes, proportions of colorectal cancers detected through screening, and stage distribution in screen-detected and non-screen-detected colorectal cancers to provide a timely assessment of the potential effects of screening programmes in several European countries. Methods: We conducted this population-based study in nine European countries for which data on mode of detection were available (Belgium, Denmark, England, France, Italy, Ireland, the Netherlands, Slovenia, and Spain). Data from 16 population-based cancer registries were included. Patients were included if they were diagnosed with colorectal cancer from the year that organised colorectal cancer screening programmes were implemented in each country until the latest year with available data at the time of analysis, and if their age at diagnosis fell within the age groups targeted by the programmes. Data collected included sex, age at diagnosis, date of diagnosis, topography, morphology, clinical and pathological TNM information based on the edition in place at time of diagnosis, and mode of detection (ie, screen detected or non-screen detected). If stage information was not available, patients were not included in stage-specific analyses. The primary outcome was proportion and stage distribution of screen-detected versus non-screen detected colorectal cancers. Findings: 228 667 colorectal cancer cases were included in the analyses. Proportions of screen-detected cancers varied widely across countries and regions. The highest proportions (40–60%) were found in Slovenia and the Basque Country in Spain, where FIT-based programmes were fully rolled out, and participation rates were higher than 50%. A similar proportion of screen-detected cancers was also found for the Netherlands in 2015, where participation was over 70%, even though the programme had not yet been fully rolled out to all age groups. In most other countries and regions, proportions of screen-detected cancers were below 30%. Compared with non-screen-detected cancers, screen-detected cancers were much more often found in the distal colon (range 34·5–51·1% screen detected vs 26·4–35·7% non-screen detected) and less often in the proximal colon (19·5–29·9% screen detected vs 24·9–32·8% non-screen detected) p≤0·02 for each country, more often at stage I (35·7–52·7% screen detected vs 13·2–24·9% non-screen detected), and less often at stage IV (5·8–12·5% screen detected vs 22·5–31·9% non-screen detected) p<0·0001 for each country. Interpretation: The proportion of colorectal cancer cases detected by screening varied widely between countries. However, in all countries, screen-detected cancers had a more favourable stage distribution than cancers detected otherwise. There is still much need and scope for improving early detection of cancer across all segments of the colorectum, and particularly in the proximal colon and rectum. Funding: Deutsche Krebshilfe

Overall and stage-specific survival of patients with screen-detected colorectal cancer in European countries: A population-based study in 9 countries

Background: An increasing proportion of colorectal cancers (CRCs) are detected through screening due to the availability of organised population-based programmes. We aimed to analyse survival probabilities of patients with screen-detected CRC in European countries. Methods: Data from CRC patients were obtained from 16 population-based cancer registries in nine European countries. We included patients with cancer diagnosed from the year organised CRC screening programmes were introduced until the most recent year with available data at the time of analysis, whose ages at diagnosis fell into the age groups targeted by screening. Patients were followed up with regards to vital status until 2016-2020 across the various countries. Overall and CRC-specific survival were analysed by mode of detection and stage at diagnosis for all countries combined and for each country separately using the Kaplan-Meier method. Findings: We included data from 228 134 patients, of whom 134 597 (aged 60-69 years at diagnosis targeted by screening in all countries) were considered in analyses for all countries combined. 22·3% (38 080/134 597) of patients had cancer detected through screening. Most screen-detected cancers were found at stages I-II (65·6% [12 772/19 469 included in stage-specific analyses]), while the majority of non-screen-detected cancers were found at stages III-IV (56·4% [31 882/56 543 included in stage-specific analyses]). Five-year overall and CRC-specific survival rates for patients with screen-detected cancer were 83·4% (95% CI 82·9-83·9) and 89·2% (88·8-89·7), respectively; for patients with non-screen-detected cancer, they were much lower (57·5% [57·2-57·8] and 65·7% [65·4-66·1], respectively). The favourable survival of patients with screen-detected cancer was also seen within each stage – five-year overall survival rates for patients with screen-detected stage I, II, III, and IV cancers were 92.4% (95% CI 91·6-93·1), 87·9% (86·6-89·1), 80·7% (79·3-82·0), and 32·3 (29·4-35·2), respectively. These patterns were also consistently seen for each individual country. Interpretation: Patients with cancer diagnosed at screening have a very favourable prognosis. In the rare case of detection of advanced stage cancer, survival probabilities are still much higher than those commonly reported for all patients regardless of mode of detection. Although these results cannot be taken to quantify screening effects, they provide useful and encouraging information for patients with screen-detected CRC and their physicians. Funding: This study was supported in part by grants from the German Federal Ministry of Education and Research and the German Cancer Aid

Burden and centralised treatment in Europe of rare tumours: results of RARECAREnet - a population-based study

Background Rare cancers pose challenges for diagnosis, treatments, and clinical decision making. Information about rare cancers is scant. The RARECARE project defined rare cancers as those with an annual incidence of less than six per 100 000 people in European Union (EU). We updated the estimates of the burden of rare cancers in Europe, their time trends in incidence and survival, and provide information about centralisation of treatments in seven European countries. Methods We analysed data from 94 cancer registries for more than 2 million rare cancer diagnoses, to estimate European incidence and survival in 2000–07 and the corresponding time trends during 1995–2007. Incidence was calculated as the number of new cases divided by the corresponding total person-years in the population. 5-year relative survival was calculated by the Ederer-2 method. Seven registries (Belgium, Bulgaria, Finland, Ireland, the Netherlands, Slovenia, and the Navarra region in Spain) provided additional data for hospitals treating about 220 000 cases diagnosed in 2000–07. We also calculated hospital volume admission as the number of treatments provided by each hospital rare cancer group sharing the same referral pattern. Findings Rare cancers accounted for 24% of all cancers diagnosed in the EU during 2000–07. The overall incidence rose annually by 0.5% (99·8% CI 0·3–0·8). 5-year relative survival for all rare cancers was 48·5% (95% CI 48·4 to 48·6), compared with 63·4% (95% CI 63·3 to 63·4) for all common cancers. 5-year relative survival increased (overall 2·9%, 95% CI 2·7 to 3·2), from 1999–2001 to 2007–09, and for most rare cancers, with the largest increases for haematological tumours and sarcomas. The amount of centralisation of rare cancer treatment varied widely between cancers and between countries. The Netherlands and Slovenia had the highest treatment volumes. Interpretation Our study benefits from the largest pool of population-based registries to estimate incidence and survival of about 200 rare cancers. Incidence trends can be explained by changes in known risk factors, improved diagnosis, and registration problems. Survival could be improved by early diagnosis, new treatments, and improved case management. The centralisation of treatment could be improved in the seven European countries we studied. Funding The European Commission (Chafea)

Penetrance estimation of Alzheimer disease in SORL1 loss-of-function variant carriers using a family-based strategy and stratification by APOE genotypes

International audienceAbstract Background Alzheimer disease (AD) is a common complex disorder with a high genetic component. Loss-of-function (LoF) SORL1 variants are one of the strongest AD genetic risk factors. Estimating their age-related penetrance is essential before putative use for genetic counseling or preventive trials. However, relative rarity and co-occurrence with the main AD risk factor, APOE -ε4, make such estimations difficult. Methods We proposed to estimate the age-related penetrance of SORL1 -LoF variants through a survival framework by estimating the conditional instantaneous risk combining (i) a baseline for non-carriers of SORL1- LoF variants, stratified by APOE-ε4 , derived from the Rotterdam study ( N = 12,255), and (ii) an age-dependent proportional hazard effect for SORL1- LoF variants estimated from 27 extended pedigrees (including 307 relatives ≥ 40 years old, 45 of them having genotyping information) recruited from the French reference center for young Alzheimer patients. We embedded this model into an expectation-maximization algorithm to accommodate for missing genotypes. To correct for ascertainment bias, proband phenotypes were omitted. Then, we assessed if our penetrance curves were concordant with age distributions of APOE -ε4-stratified SORL1- LoF variant carriers detected among sequencing data of 13,007 cases and 10,182 controls from European and American case-control study consortia. Results SORL1- LoF variants penetrance curves reached 100% (95% confidence interval [99–100%]) by age 70 among APOE -ε4ε4 carriers only, compared with 56% [40–72%] and 37% [26–51%] in ε4 heterozygous carriers and ε4 non-carriers, respectively. These estimates were fully consistent with observed age distributions of SORL1- LoF variant carriers in case-control study data. Conclusions We conclude that SORL1- LoF variants should be interpreted in light of APOE genotypes for future clinical applications