Interdisciplinary research for the analysis and risk assesment : the case of the municipality of Uspantan Guatemala

Short description of the proposed presentation * lees than 100 words This paper describes the interdisciplinary work done in Uspantán, Guatemala, a city vulnerable to natural hazards. We investigated local responses to landslides that happened in 2007 and 2010 and had a strong impact on the local community. We show a complete example of a systemic approach that incorporates physical, social and environmental aspects in order to understand risks. The objective of this work is to present the combination of social and geological data (mapping), and describe the methodology used for identification and assessment of risk. The article discusses both the limitations and methodological challenges encountered when conducting interdisciplinary research. Describe why it is important to present this topic at the Global Platform in less than 50 words This work shows the benefits of addressing risk in an interdisciplinary perspective, in particular how integrating social sciences can help identify new phenomena and natural hazards and assess risk. It gives a practical example of how one can integrate data from different fields. What is innovative about this presentation? * The use of mapping to combine qualitative and quantitative data. By coupling approaches, we could associate a hazard map with qualitative data gathered by interviews with the population. This map is an important document for the authorities. Indeed, it allows them to be aware of the most dangerous zones, the affected families and the places where it is most urgent to intervene.

Interaction between tobacco and alcohol use and the risk of head and neck cancer: pooled analysis in the International Head and Neck Cancer Epidemiology Consortium.

BACKGROUND: The magnitude of risk conferred by the interaction between tobacco and alcohol use on the risk of head and neck cancers is not clear because studies have used various methods to quantify the excess head and neck cancer burden. METHODS: We analyzed individual-level pooled data from 17 European and American case-control studies (11,221 cases and 16,168 controls) participating in the International Head and Neck Cancer Epidemiology consortium. We estimated the multiplicative interaction parameter (psi) and population attributable risks (PAR). RESULTS: A greater than multiplicative joint effect between ever tobacco and alcohol use was observed for head and neck cancer risk (psi = 2.15; 95% confidence interval, 1.53-3.04). The PAR for tobacco or alcohol was 72% (95% confidence interval, 61-79%) for head and neck cancer, of which 4% was due to alcohol alone, 33% was due to tobacco alone, and 35% was due to tobacco and alcohol combined. The total PAR differed by subsite (64% for oral cavity cancer, 72% for pharyngeal cancer, 89% for laryngeal cancer), by sex (74% for men, 57% for women), by age (33% for cases <45 years, 73% for cases >60 years), and by region (84% in Europe, 51% in North America, 83% in Latin America). CONCLUSIONS: Our results confirm that the joint effect between tobacco and alcohol use is greater than multiplicative on head and neck cancer risk. However, a substantial proportion of head and neck cancers cannot be attributed to tobacco or alcohol use, particularly for oral cavity cancer and for head and neck cancer among women and among young-onset cases.

Risk dominance selects the leader. An experimental analysis

Coordination games arise very often in studies of industrial organization and international trade. This type of games has multiple strict equilibria, and therefore the identification of testable predictions isvery difficult. We study a vertical product differentiation model with two asymmetric players choosing first qualities and then prices. This game has two equilibria for some parameter values. However, we apply the risk dominance criterion suggested by Harsanyi and Selten and show that it always selects the equilibrium where the leader is the firm having some initial advantage. We then perform an experimental analysis totest whether the risk dominance prediction is supported by the behaviour oflaboratory agents. We show that the probability that the risk dominance prediction is right depends crucially on the degree of asymmetry of the game. The stronger the asymmetries the higher the predictive power of the risk dominance criterion.

Can the trabecular bone score (TBS) be considered as a major clinical risk factor (CRF) of osteoporotic fractures? A meta-like analysis

Abstract: To have an added value over BMD, a CRF of osteoporotic fracture must be predictable of the fracture, independent of BMD, reversible and quantifiable. Many major recognized CRF exist.Out of these factorsmany of themare indirect factor of bone quality. TBS predicts fracture independently of BMD as demonstrated from previous studies. The aim of the study is to verify if TBS can be considered as a major CRF of osteoporotic fracture. Existing validated datasets of Caucasian women were analyzed. These datasets stem from different studies performed by the authors of this report or provided to our group. However, the level of evidence of these studies will vary. Thus, the different datasets were weighted differently according to their design. This meta-like analysis involves more than 32000 women (≥50 years) with 2000 osteoporotic fractures from two prospective studies (OFELY&MANITOBA) and 7 crosssectional studies. Weighted relative risk (RR) for TBS was expressed for each decrease of one standard deviation as well as per tertile difference (TBS=1.300 and 1.200) and compared with those obtained for the major CRF included in FRAX®. Overall TBS RR obtained (adjusted for age) was 1.79 [95%CI-1.37-2.37]. For all women combined, RR for fracture for the lowest comparedwith themiddle TBS tertilewas 1.55[1.46- 1.68] and for the lowest compared with the highest TBS tertile was 2.8[2.70-3.00]. TBS is comparable to most of the major CRF (Fig 1) and thus could be used as one of them. Further studies have to be conducted to confirm these first findings.

History of diabetes and risk of head and neck cancer: a pooled analysis from the international head and neck cancer epidemiology consortium.

BACKGROUND: A history of diabetes is associated with an increased risk of several types of cancers. Whether diabetes is a risk factor for head and neck cancer (HNC) has received little attention. METHODS: We pooled data from 12 case-control studies including 6,448 cases and 13,747 controls, and estimated odds ratios (OR) and 95% confidence intervals (CI) for the associations between diabetes and HNC, adjusted for age, education level, sex, race/ethnicity, study center, cigarette smoking, alcohol use and body mass index (BMI). RESULTS: We observed a weak association between diabetes and the incidence of HNC overall (OR, 1.09; 95% CI, 0.95-1.24). However, we observed a modest association among never smokers (OR, 1.59; 95% CI, 1.22-2.07), and no association among ever smokers (OR, 0.96; 95% CI, 0.83-1.11); likelihood ratio test for interaction p=0.001. CONCLUSIONS: A history of diabetes was weakly associated with HNC overall, but we observed evidence of effect modification by smoking status, with a positive association among those who never smoked cigarettes. Impact: This study suggests that glucose metabolism abnormalities may be a HNC risk factor in subgroups of the population. Prospective studies incorporating biomarkers are needed to improve our understanding of the relationship between diabetes and HNC risk, possibly providing new strategies in the prevention of HNC.

Risk factors for survival after lung metastasectomy in colorectal cancer patients: a systematic review and meta-analysis.

BACKGROUND: Resection of lung metastases (LM) from colorectal cancer (CRC) is increasingly performed with a curative intent. It is currently not possible to identify those CRC patients who may benefit the most from this surgical strategy. The aim of this study was to perform a systematic review of risk factors for survival after lung metastasectomy for CRC. METHODS: We performed a meta-analysis of series published between 2000 and 2011, which focused on surgical management of LM from CRC and included more than 40 patients each. Pooled hazard ratios (HR) were calculated by using random effects model for parameters considered as potential prognostic factors. RESULTS: Twenty-five studies including a total of 2925 patients were considered in this analysis. Four parameters were associated with poor survival: (1) a short disease-free interval between primary tumor resection and development of LM (HR 1.59, 95 % confidence interval [CI] 1.27-1.98); (2) multiple LM (HR 2.04, 95 % CI 1.72-2.41); (3) positive hilar and/or mediastinal lymph nodes (HR 1.65, 95 % CI 1.35-2.02); and (4) elevated prethoracotomy carcinoembryonic antigen (HR 1.91, 95 % CI 1.57-2.32). By comparison, a history of resected liver metastases (HR 1.22, 95 % CI 0.91-1.64) did not achieve statistical significance. CONCLUSIONS: Clinical variables associated with prolonged survival after surgery for LM in CRC patients include prolonged disease-free interval between primary tumor and metastatic spread, normal prethoracotomy carcinoembryonic antigen, absence of thoracic node involvement, and a single pulmonary lesion.

Active smoking and the risk of type 2 diabetes : a systematic review and meta-analysis

Rapport de synthèse : Introduction : plusieurs études observationnelles suggèrent qu'il existe une association entre le tabagisme actif et l'incidence du diabète de type 2. Toutefois de telles études n'ont jamais été synthétisées de façon systématique. Objectif : conduire une revue systématique avec meta-analyse des études évaluant l'association entre le tabagisme actif et l'incidence du diabète de type 2. Méthode : nous avons effectué une recherche dans les bases de donnée électroniques MEDLINE et EMBASE de 1966 à mai 2007, et l'avons complétée par une recherche manuelle des bibliographies des articles clés retenus ainsi que par la recherche d'abstracts de congrès scientifiques et le contact d'experts. Pour être inclues dans notre revue, les études devaient avoir un design de type cohorte, reporter un risque de glycémies jeun élevée, d'intolérance au glucose ou de diabète de type 2 en relation avec le statut tabagique des participants lors du recrutement et devaient exclure les sujets avec un diabète au début de l'étude. Deux auteurs ont sélectionné de façon indépendante les études et ont extrait les données. Les risques relatifs de diabète étaient ensuite compilés, utilisant un modèle de type « random effect ». Résultats : la recherche a aboutit à 25 études de cohorte prospectives (N=1'165'374 participants) et a reporté en tout 45'844 cas de diabète de type 2 pendant une durée de suivi s'étendant sur 5 à 30 années. Sur les 25 études, 24 reportaient un risque augmenté de diabète chez les fumeurs par comparaison aux non fumeurs. Le risque relatif (RR) commun de toutes les études était de 1.44 (intervalle de confiance (IC) à 95% : 1.31-1.58). Le risque de diabète était plus élevé chez les fumeurs de plus de 20 cigarettes par jour (RR : 1.61, IC 95% : 1.43-1.80) en comparaison aux fumeurs ayant une consommation inférieure (RR : 1.29, IC 95% : 1.13-1.48) et le risque était moindre pour les anciens fumeurs (RR :1.23; IC 95% : 1.14-1.33) comparé aux fumeurs actifs. Ces éléments parlent en faveur d'un effet dose-réponse et donc d'une relation de causalité, sans pour autant la prouver. Conclusion : notre étude révèle que le tabagisme actif est associé avec un risque augmenté de 44% de diabète de type 2. Des recherches futures sont nécessaires pour évaluer si cette association est causale et pour clarifier les mécanismes d'action. Dans l'intervalle, les professionnels de santé devraient mentionner l'éviction du diabète comme une raison supplémentaire d'arrêter de fumer ou de ne pas commencer à fumer.

Analysis of TNF-antagonist switch over time and associated risk factors in the Swiss Inflammatory Bowel Disease Cohort

Abstract Background and aims. Limited data from large cohorts are available on tumor necrosis factor (TNF) antagonists (infliximab, adalimumab, certolizumab pegol) switch over time. We aimed to evaluate the prevalence of switching from one TNF antagonist to another and to identify associated risk factors. Methods. Data from the Swiss Inflammatory Bowel Diseases Cohort Study (SIBDCS) were analyzed. Results. Of 1731 patients included into the SIBDCS (956 with Crohn's disease [CD] and 775 with ulcerative colitis [UC]), 347 CD patients (36.3%) and 129 UC patients (16.6%) were treated with at least one TNF antagonist. A total of 53/347 (15.3%) CD patients (median disease duration 9 years) and 20/129 (15.5%) of UC patients (median disease duration 7 years) needed to switch to a second and/or a third TNF antagonist, respectively. Median treatment duration was longest for the first TNF antagonist used (CD 25 months; UC 14 months), followed by the second (CD 13 months; UC 4 months) and third TNF antagonist (CD 11 months; UC 15 months). Primary nonresponse, loss of response and side effects were the major reasons to stop and/or switch TNF antagonist therapy. A low body mass index, a short diagnostic delay and extraintestinal manifestations at inclusion were identified as risk factors for a switch of the first used TNF antagonist within 24 months of its use in CD patients. Conclusion. Switching of the TNF antagonist over time is a common issue. The median treatment duration with a specific TNF antagonist is diminishing with an increasing number of TNF antagonists being used.

Diet and the risk of head and neck cancer: a pooled analysis in the INHANCE consortium.

We investigated the association between diet and head and neck cancer (HNC) risk using data from the International Head and Neck Cancer Epidemiology (INHANCE) consortium. The INHANCE pooled data included 22 case-control studies with 14,520 cases and 22,737 controls. Center-specific quartiles among the controls were used for food groups, and frequencies per week were used for single food items. A dietary pattern score combining high fruit and vegetable intake and low red meat intake was created. Odds ratios (OR) and 95% confidence intervals (CI) for the dietary items on the risk of HNC were estimated with a two-stage random-effects logistic regression model. An inverse association was observed for higher-frequency intake of fruit (4th vs. 1st quartile OR = 0.52, 95% CI = 0.43-0.62, p (trend) < 0.01) and vegetables (OR = 0.66, 95% CI = 0.49-0.90, p (trend) = 0.01). Intake of red meat (OR = 1.40, 95% CI = 1.13-1.74, p p (trend) < 0.01) was positively associated with HNC risk. Higher dietary pattern scores, reflecting high fruit/vegetable and low red meat intake, were associated with reduced HNC risk (per score increment OR = 0.90, 95% CI = 0.84-0.97).

Life-course socioeconomic environment and health risk behaviours: a multilevel small-area analysis of young-old persons in an urban neighbourhood in Lausanne, Switzerland

With a life expectancy at the age of 65 of around 20 years, damaging health risk behaviours of young-old adults have become a target for preventive actions. Such risk factors necessitate an accurate understanding of the present and past socioeconomic conditions associated with health risk behaviours. The aim of our study is to assess the impact of certain life events as well as economic and environmental factors on health risk behaviours. We included 1309 participants of the Lausanne Cohort Lc65+ aged 65-70 years and employed logistic regression analyses, with individuals nested within areas. The results illustrate the influences of socioeconomic factors from childhood to young-old age. Life experiences in adulthood and economic resources in young-old age are both associated with unfavourable health behaviours. Neighbourhood is a modest determinant as well, particularly regarding alcohol consumption. Therefore, prevention against health risk behaviours should focus on population subgroups defined on the basis of their socioeconomic and living contexts.

Circulating carotenoids and risk of breast cancer: pooled analysis of eight prospective studies.

Background Carotenoids, micronutrients in fruits and vegetables, may reduce breast cancer risk. Most, but not all, past studies of circulating carotenoids and breast cancer have found an inverse association with at least one carotenoid, although the specific carotenoid has varied across studies. Methods We conducted a pooled analysis of eight cohort studies comprising more than 80% of the world's published prospective data on plasma or serum carotenoids and breast cancer, including 3055 case subjects and 3956 matched control subjects. To account for laboratory differences and examine population differences across studies, we recalibrated participant carotenoid levels to a common standard by reassaying 20 plasma or serum samples from each cohort together at the same laboratory. Using conditional logistic regression, adjusting for several breast cancer risk factors, we calculated relative risks (RRs) and 95% confidence intervals (CIs) using quintiles defined among the control subjects from all studies. All P values are two-sided. Results Statistically significant inverse associations with breast cancer were observed for α-carotene (top vs bottom quintile RR = 0.87, 95% CI = 0.71 to 1.05, Ptrend = .04), β-carotene (RR = 0.83, 95% CI = 0.70 to 0.98, Ptrend = .02), lutein+zeaxanthin (RR = 0.84, 95% CI = 0.70 to 1.01, Ptrend = .05), lycopene (RR = 0.78, 95% CI = 0.62 to 0.99, Ptrend = .02), and total carotenoids (RR = 0.81, 95% CI = 0.68 to 0.96, Ptrend = .01). β-Cryptoxanthin was not statistically significantly associated with risk. Tests for heterogeneity across studies were not statistically significant. For several carotenoids, associations appeared stronger for estrogen receptor negative (ER(-)) than for ER(+) tumors (eg, β-carotene: ER(-): top vs bottom quintile RR = 0.52, 95% CI = 0.36 to 0.77, Ptrend = .001; ER(+): RR = 0.83, 95% CI = 0.66 to 1.04, Ptrend = .06; Pheterogeneity = .01). Conclusions This comprehensive prospective analysis suggests women with higher circulating levels of α-carotene, β-carotene, lutein+zeaxanthin, lycopene, and total carotenoids may be at reduced risk of breast cancer.

Estimating and explaining the effect of education and income on head and neck cancer risk : INHANCE consortium pooled analysis of 31 case-control studies from 27 countries

Low socioeconomic status has been reported to be associated with head and neck cancer risk. However, previous studies have been too small to examine the associations by cancer subsite, age, sex, global region, and calendar time, and to explain the association in terms of behavioural risk factors. Individual participant data of 23,964 cases with head and neck cancer and 31,954 controls from 31 studies in 27 countries pooled with random effects models. Overall, low education was associated with an increased risk of head and neck cancer (OR = 2·50; 95%CI 2·02- 3·09). Overall one-third of the increased risk was not explained by differences in the distribution of cigarette smoking and alcohol behaviours; and it remained elevated among never users of tobacco and non-drinkers (OR = 1·61; 95%CI 1·13 - 2·31). More of the estimated education effect was not explained by cigarette smoking and alcohol behaviours: in women than in men, in older than younger groups, in the oropharynx than in other sites, in South/Central America than in Europe/North America, and was strongest in countries with greater income inequality. Similar findings were observed for the estimated effect of low vs high household income. The lowest levels of income and educational attainment were associated with more than 2-fold increased risk of head and neck cancer, which is not entirely explained by differences in the distributions of behavioural risk factors for these cancers, and which varies across cancer sites, sexes, countries, and country income inequality levels. © 2014 Wiley Periodicals, Inc.

Recent misconceptions about the "database search problem": a probabilistic analysis using Bayesian networks

This paper analyses and discusses arguments that emerge from a recent discussion about the proper assessment of the evidential value of correspondences observed between the characteristics of a crime stain and those of a sample from a suspect when (i) this latter individual is found as a result of a database search and (ii) remaining database members are excluded as potential sources (because of different analytical characteristics). Using a graphical probability approach (i.e., Bayesian networks), the paper here intends to clarify that there is no need to (i) introduce a correction factor equal to the size of the searched database (i.e., to reduce a likelihood ratio), nor to (ii) adopt a propositional level not directly related to the suspect matching the crime stain (i.e., a proposition of the kind 'some person in (outside) the database is the source of the crime stain' rather than 'the suspect (some other person) is the source of the crime stain'). The present research thus confirms existing literature on the topic that has repeatedly demonstrated that the latter two requirements (i) and (ii) should not be a cause of concern.

Advanced geostatistical and machine-learning models for spatial data analysis of radioactively contaminated regions

Radioactive soil-contamination mapping and risk assessment is a vital issue for decision makers. Traditional approaches for mapping the spatial concentration of radionuclides employ various regression-based models, which usually provide a single-value prediction realization accompanied (in some cases) by estimation error. Such approaches do not provide the capability for rigorous uncertainty quantification or probabilistic mapping. Machine learning is a recent and fast-developing approach based on learning patterns and information from data. Artificial neural networks for prediction mapping have been especially powerful in combination with spatial statistics. A data-driven approach provides the opportunity to integrate additional relevant information about spatial phenomena into a prediction model for more accurate spatial estimates and associated uncertainty. Machine-learning algorithms can also be used for a wider spectrum of problems than before: classification, probability density estimation, and so forth. Stochastic simulations are used to model spatial variability and uncertainty. Unlike regression models, they provide multiple realizations of a particular spatial pattern that allow uncertainty and risk quantification. This paper reviews the most recent methods of spatial data analysis, prediction, and risk mapping, based on machine learning and stochastic simulations in comparison with more traditional regression models. The radioactive fallout from the Chernobyl Nuclear Power Plant accident is used to illustrate the application of the models for prediction and classification problems. This fallout is a unique case study that provides the challenging task of analyzing huge amounts of data ('hard' direct measurements, as well as supplementary information and expert estimates) and solving particular decision-oriented problems.