Graphical probabilistic analysis of the combination of items of evidence

Unlike the evaluation of single items of scientific evidence, the formal study and analysis of the jointevaluation of several distinct items of forensic evidence has to date received some punctual, ratherthan systematic, attention. Questions about the (i) relationships among a set of (usually unobservable)propositions and a set of (observable) items of scientific evidence, (ii) the joint probative valueof a collection of distinct items of evidence as well as (iii) the contribution of each individual itemwithin a given group of pieces of evidence still represent fundamental areas of research. To somedegree, this is remarkable since both, forensic science theory and practice, yet many daily inferencetasks, require the consideration of multiple items if not masses of evidence. A recurrent and particularcomplication that arises in such settings is that the application of probability theory, i.e. the referencemethod for reasoning under uncertainty, becomes increasingly demanding. The present paper takesthis as a starting point and discusses graphical probability models, i.e. Bayesian networks, as frameworkwithin which the joint evaluation of scientific evidence can be approached in some viable way.Based on a review of existing main contributions in this area, the article here aims at presentinginstances of real case studies from the author's institution in order to point out the usefulness andcapacities of Bayesian networks for the probabilistic assessment of the probative value of multipleand interrelated items of evidence. A main emphasis is placed on underlying general patterns of inference,their representation as well as their graphical probabilistic analysis. Attention is also drawnto inferential interactions, such as redundancy, synergy and directional change. These distinguish thejoint evaluation of evidence from assessments of isolated items of evidence. Together, these topicspresent aspects of interest to both, domain experts and recipients of expert information, because theyhave bearing on how multiple items of evidence are meaningfully and appropriately set into context.

Bayesian networks and the evaluation of scientific evidence in forensic science

Résumé Ce travail de thèse étudie des moyens de formalisation permettant d'assister l'expert forensique dans la gestion des facteurs influençant l'évaluation des indices scientifiques, tout en respectant des procédures d'inférence établies et acceptables. Selon une vue préconisée par une partie majoritaire de la littérature forensique et juridique - adoptée ici sans réserve comme point de départ - la conceptualisation d'une procédure évaluative est dite 'cohérente' lors qu'elle repose sur une implémentation systématique de la théorie des probabilités. Souvent, par contre, la mise en oeuvre du raisonnement probabiliste ne découle pas de manière automatique et peut se heurter à des problèmes de complexité, dus, par exemple, à des connaissances limitées du domaine en question ou encore au nombre important de facteurs pouvant entrer en ligne de compte. En vue de gérer ce genre de complications, le présent travail propose d'investiguer une formalisation de la théorie des probabilités au moyen d'un environment graphique, connu sous le nom de Réseaux bayesiens (Bayesian networks). L'hypothèse principale que cette recherche envisage d'examiner considère que les Réseaux bayesiens, en concert avec certains concepts accessoires (tels que des analyses qualitatives et de sensitivité), constituent une ressource clé dont dispose l'expert forensique pour approcher des problèmes d'inférence de manière cohérente, tant sur un plan conceptuel que pratique. De cette hypothèse de travail, des problèmes individuels ont été extraits, articulés et abordés dans une série de recherches distinctes, mais interconnectées, et dont les résultats - publiés dans des revues à comité de lecture - sont présentés sous forme d'annexes. D'un point de vue général, ce travail apporte trois catégories de résultats. Un premier groupe de résultats met en évidence, sur la base de nombreux exemples touchant à des domaines forensiques divers, l'adéquation en termes de compatibilité et complémentarité entre des modèles de Réseaux bayesiens et des procédures d'évaluation probabilistes existantes. Sur la base de ces indications, les deux autres catégories de résultats montrent, respectivement, que les Réseaux bayesiens permettent également d'aborder des domaines auparavant largement inexplorés d'un point de vue probabiliste et que la disponibilité de données numériques dites 'dures' n'est pas une condition indispensable pour permettre l'implémentation des approches proposées dans ce travail. Le présent ouvrage discute ces résultats par rapport à la littérature actuelle et conclut en proposant les Réseaux bayesiens comme moyen d'explorer des nouvelles voies de recherche, telles que l'étude de diverses formes de combinaison d'indices ainsi que l'analyse de la prise de décision. Pour ce dernier aspect, l'évaluation des probabilités constitue, dans la façon dont elle est préconisée dans ce travail, une étape préliminaire fondamentale de même qu'un moyen opérationnel.

New prognostic factors and calculators for outcome prediction in patients with recurrent glioblastoma: A pooled analysis of EORTC Brain Tumour Group phase I and II clinical trials.

BACKGROUND: Prognostic models have been developed to predict survival of patients with newly diagnosed glioblastoma (GBM). To improve predictions, models should be updated with information at the recurrence. We performed a pooled analysis of European Organization for Research and Treatment of Cancer (EORTC) trials on recurrent glioblastoma to validate existing clinical prognostic factors, identify new markers, and derive new predictions for overall survival (OS) and progression free survival (PFS).¦METHODS: Data from 300 patients with recurrent GBM recruited in eight phase I or II trials conducted by the EORTC Brain Tumour Group were used to evaluate patient's age, sex, World Health Organisation (WHO) performance status (PS), presence of neurological deficits, disease history, use of steroids or anti-epileptics and disease characteristics to predict PFS and OS. Prognostic calculators were developed in patients initially treated by chemoradiation with temozolomide.¦RESULTS: Poor PS and more than one target lesion had a significant negative prognostic impact for both PFS and OS. Patients with large tumours measured by the maximum diameter of the largest lesion (⩾42mm) and treated with steroids at baseline had shorter OS. Tumours with predominant frontal location had better survival. Age and sex did not show independent prognostic values for PFS or OS.¦CONCLUSIONS: This analysis confirms performance status but not age as a major prognostic factor for PFS and OS in recurrent GBM. Patients with multiple and large lesions have an increased risk of death. With these data prognostic calculators with confidence intervals for both medians and fixed time probabilities of survival were derived.

Probabilistic evidential assessment of gunshot residue particle evidence (Part I): likelihood ratio calculation and case pre-assessment using Bayesian networks

Well developed experimental procedures currently exist for retrieving and analyzing particle evidence from hands of individuals suspected of being associated with the discharge of a firearm. Although analytical approaches (e.g. automated Scanning Electron Microscopy with Energy Dispersive X-ray (SEM-EDS) microanalysis) allow the determination of the presence of elements typically found in gunshot residue (GSR) particles, such analyses provide no information about a given particle's actual source. Possible origins for which scientists may need to account for are a primary exposure to the discharge of a firearm or a secondary transfer due to a contaminated environment. In order to approach such sources of uncertainty in the context of evidential assessment, this paper studies the construction and practical implementation of graphical probability models (i.e. Bayesian networks). These can assist forensic scientists in making the issue tractable within a probabilistic perspective. The proposed models focus on likelihood ratio calculations at various levels of detail as well as case pre-assessment.

May absorbable suture anchors increase the rate of recurrent dislocations after shoulder stabilization?

Introduction: Absorbable anchors are frequently used in shoulder surgery. Mechanisms of absorption induce a local inflammatory reaction. It is not clear if this process may disturb healing of the capsule and ligaments. The purpose of the study was to compare the rate of recurrent dislocation following open shoulder stabilization when using absorbable or non-absorbable suture anchors. Methods: Between 1999 and 2003, 83 open Bankart repairs were performed by the same surgeon. All patients had recurrent traumatic anterior shoulder instability. All had preoperative arthro-MRI or arthro-CT which did not reveal any significant bony Bankart lesion or rotatorcuff tear. Thirty-four patients were treated with absorbable anchors (Panalok®) and sutures (Panacryl®) and 49 with non-absorbable anchors (Mitek GII®) and sutures (Ethibond®). The same surgical technique and rehabilitation protocol were used. The incidence of sports ability and recurrent instability were recorded. We defined instability as true dislocation. Results: Five patients on 34 were lost to follow-up in the absorbable group and 7 on 49 in the non-absorbable group. The mean age of absorbable group was 25 years (range, 17-39 years). At a mean follow-up of 66 months (range, 54-76 months), 86% could resume sports activity. Five patients on 29 (17%) reported recurrent instability and two did need revision surgery. The mean age in non-absorbable group was 28 year (range, 18-47 years). At a mean follow-up of 78 months (range, 49-82 months), 93% could resume sports activity. Three patients on 42 (7%) reported recurrent instability and one did need revision surgery. Conclusion: This clinical study showed a clear tendency to a higher recurrence rate of dislocation when using absorbable suture anchors (17% in absorbable vs 7% in non-absorbable group). It is known that Panacryl® may be responsible for a major local inflammatory response. However, it is still unclear if this could be the failure etiology. Consequently, we prefer to use systematically non-absorbable sutureanchors for shoulder stabilization.

Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.

Multi institutional phase II study of concomitant stereotactic reirradiation and cetuximab for recurrent head and neck cancer.

PURPOSE: Recurrent head and neck cancer is associated to a poor survival prognosis. A high toxicity rate is demonstrated when surgery and/or radiotherapy and/or chemotherapy are combined. Furthermore, the duration of treatment is often not ethically compatible with the expected survival (median survival<1year). Normal tissues tolerance limits the use of reirradiation and stereotactic body radiotherapy (SBRT) could offer precise irradiation while sparing healthy tissues. After completion of a feasibility study, results of a multicentric study (Lille, Nancy & Nice) using SBRT with cetuximab are reported. The aim of the study was to deliver non toxic short course SBRT (2weeks) in order to get the same local control as the one demonstrated with longer protocols. METHODS AND MATERIALS: Patients with inoperable recurrent, or new primary tumor in a previously irradiated area, were included (WHO<3). Reirradiation (RT) dose was 36Gy in six fractions of 6Gy to the 85% isodose line covering 95% of the PTV with 5 injections of concomitant cetuximab (CT). All patients had previous radiotherapy, 85% had previous surgery and 48% previous chemotherapy. RESULTS: Between 11/2007 and 08/2010, 60 were included (46 men and 14 women), 56 received CT+RT, 3 were not treated and 1 received only CT. Median age was 60 (42-87)) and all 56 patients had squamous carcinoma and received concomitant cetuximab. Mean time between previous radiotherapy and the start of SBRT was 38months. Cutaneous toxicity was observed for 41 patients. There was one toxic death from hemorrhage and denutrition. Median follow-up was 11.4months. At 3months, response rate was 58.4% (95% CI: 43.2-72.4%) and disease control rate was 91.7% (95% CI: 80.0-97.7%). The one-year OS rate was 47.5% (95% CI: 30.8-62.4). CONCLUSION: These results suggest that short SBRT with cetuximab is an effective salvage treatment with good response rate in this poor prognosis population with previously irradiated HNC. Treatment is feasible and, with appropriate care to limiting critical structure, acute toxicities are acceptable. This combination may be the reference treatment is this population.

Genome-wide association study of recurrent major depressive disorder in two European case-control cohorts.

Major depressive disorder (MDD) is a highly prevalent disorder with substantial heritability. Heritability has been shown to be substantial and higher in the variant of MDD characterized by recurrent episodes of depression. Genetic studies have thus far failed to identify clear and consistent evidence of genetic risk factors for MDD. We conducted a genome-wide association study (GWAS) in two independent datasets. The first GWAS was performed on 1022 recurrent MDD patients and 1000 controls genotyped on the Illumina 550 platform. The second was conducted on 492 recurrent MDD patients and 1052 controls selected from a population-based collection, genotyped on the Affymetrix 5.0 platform. Neither GWAS identified any SNP that achieved GWAS significance. We obtained imputed genotypes at the Illumina loci for the individuals genotyped on the Affymetrix platform, and performed a meta-analysis of the two GWASs for this common set of approximately half a million SNPs. The meta-analysis did not yield genome-wide significant results either. The results from our study suggest that SNPs with substantial odds ratio are unlikely to exist for MDD, at least in our datasets and among the relatively common SNPs genotyped or tagged by the half-million-loci arrays. Meta-analysis of larger datasets is warranted to identify SNPs with smaller effects or with rarer allele frequencies that contribute to the risk of MDD.

Bevacizumab for recurrent ependymoma.

BACKGROUND: Ependymoma is a rare type of glioma, representing 5% of all CNS malignancies. Radiotherapy (RT) is commonly administered, but there is no standard chemotherapy. At recurrence, ependymoma is notoriously refractory to therapy and the prognosis is poor. In recurrent glioblastoma, encouraging responses with bevacizumab have been observed. METHODS: In this Institutional Review Board-approved study, we retrospectively analyzed the records of 8 adult patients treated for recurrent ependymoma and anaplastic ependymoma with bevacizumab containing chemotherapy regimens. We determined radiographic response (Macdonald criteria), median time to progression (TTP), and median overall survival (OS; Kaplan-Meier method). RESULTS: There were 4 men and 4 women with a median age of 40 years (range, 20-65). Prior treatment included surgery (n = 8), RT (8), temozolomide (5), and carboplatin (4). Bevacizumab (5-15 mg/kg every 2-3 weeks) was administered alone (2) or concurrently with cytotoxic chemotherapy including irinotecan (3), carboplatin (2), or temozolomide (1). Six patients achieved a partial response (75%) and 1 remained stable for over 8 months. Median TTP was 6.4 months (95% confidence interval 1.4-7.4) and median OS was 9.4 months (95% confidence interval 7.0-not reached), with a median follow-up of 5.2 months among 5 surviving patients (63%). CONCLUSIONS: The radiographic response rate to bevacizumab-containing regimens is high. A prospective study is warranted.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.

Coordination on Networks: Does Topology Matter?

Effective coordination is key to many situations that affect the well-being of two or more humans. Social coordination can be studied in coordination games between individuals located on networks of contacts. We study the behavior of humans in the laboratory when they play the Stag Hunt game - a game that has a risky but socially efficient equilibrium and an inefficient but safe equilibrium. We contrast behavior on a cliquish network to behavior on a random network. The cliquish network is highly clustered and resembles more closely to actual social networks than the random network. In contrast to simulations, we find that human players dynamics do not converge to the efficient outcome more often in the cliquish network than in the random network. Subjects do not use pure myopic best-reply as an individual update rule. Numerical simulations agree with laboratory results once we implement the actual individual updating rule that human subjects use in our laboratory experiments.