55 resultados para Modal interval analysis

em Université de Lausanne, Switzerland


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As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

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Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

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PURPOSE: To assess the sensitivity and false positive rate (FPR) of neurological examination and somatosensory evoked potentials (SSEPs) to predict poor outcome in adult patients treated with therapeutic hypothermia after cardiopulmonary resuscitation (CPR). METHODS: MEDLINE and EMBASE were searched for cohort studies describing the association of clinical neurological examination or SSEPs after return of spontaneous circulation with neurological outcome. Poor outcome was defined as severe disability, vegetative state and death. Sensitivity and FPR were determined. RESULTS: A total of 1,153 patients from ten studies were included. The FPR of a bilaterally absent cortical N20 response of the SSEP could be calculated from nine studies including 492 patients. The SSEP had an FPR of 0.007 (confidence interval, CI, 0.001-0.047) to predict poor outcome. The Glasgow coma score (GCS) motor response was assessed in 811 patients from nine studies. A GCS motor score of 1-2 at 72 h had a high FPR of 0.21 (CI 0.08-0.43). Corneal reflex and pupillary reactivity at 72 h after the arrest were available in 429 and 566 patients, respectively. Bilaterally absent corneal reflexes had an FPR of 0.02 (CI 0.002-0.13). Bilaterally absent pupillary reflexes had an FPR of 0.004 (CI 0.001-0.03). CONCLUSIONS: At 72 h after the arrest the motor response to painful stimuli and the corneal reflexes are not a reliable tool for the early prediction of poor outcome in patients treated with hypothermia. The reliability of the pupillary response to light and the SSEP is comparable to that in patients not treated with hypothermia.

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BACKGROUND: Invasive fungal infections (IFIs) are life-threatening complications in patients with hemato-oncological malignancies, and early diagnosis is crucial for outcome. The compound 1,3-β-D-glucan (BG), a cell wall component of most fungal species, can be detected in blood during IFI. Four commercial BG antigenemia assays are available (Fungitell, Fungitec-G, Wako, and Maruha). This meta-analysis from the Third European Conference on Infections in Leukemia (ECIL-3) assessed the performance of BG assays for the diagnosis of IFI in hemato-oncological patients. METHODS: Studies reporting the performance of BG antigenemia assays for the diagnosis of IFI (European Organization for Research and Treatment of Cancer and Mycoses Study Group criteria) in hemato-oncological patients were identified. The analysis was focused on high-quality cohort studies with exclusion of case-control studies. Meta-analysis was performed by conventional meta-analytical pooling and bivariate analysis. RESULTS: Six cohort studies were included (1771 adult patients with 414 IFIs of which 215 were proven or probable). Similar performance was observed among the different BG assays. For the cutoff recommended by the manufacturer, the diagnostic performance of the BG assay in proven or probable IFI was better with 2 consecutive positive test results (diagnostic odds ratio for 2 consecutive vs one single positive results, 111.8 [95% confidence interval {CI}, 38.6-324.1] vs 16.3 [95% CI, 6.5-40.8], respectively; heterogeneity index for 2 consecutive vs one single positive results, 0% vs 72.6%, respectively). For 2 consecutive tests, sensitivity and specificity were 49.6% (95% CI, 34.0%-65.3%) and 98.9% (95% CI, 97.4%-99.5%), respectively. Estimated positive and negative predictive values for an IFI prevalence of 10% were 83.5% and 94.6%, respectively. CONCLUSIONS: Different BG assays have similar accuracy for the diagnosis of IFI in hemato-oncological patients. Two consecutive positive antigenemia assays have very high specificity, positive predictive value, and negative predictive value. Because sensitivity is low, the test needs to be combined with clinical, radiological, and microbiological findings.

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Prior genome-wide association studies (GWAS) of major depressive disorder (MDD) have met with limited success. We sought to increase statistical power to detect disease loci by conducting a GWAS mega-analysis for MDD. In the MDD discovery phase, we analyzed more than 1.2 million autosomal and X chromosome single-nucleotide polymorphisms (SNPs) in 18 759 independent and unrelated subjects of recent European ancestry (9240 MDD cases and 9519 controls). In the MDD replication phase, we evaluated 554 SNPs in independent samples (6783 MDD cases and 50 695 controls). We also conducted a cross-disorder meta-analysis using 819 autosomal SNPs with P<0.0001 for either MDD or the Psychiatric GWAS Consortium bipolar disorder (BIP) mega-analysis (9238 MDD cases/8039 controls and 6998 BIP cases/7775 controls). No SNPs achieved genome-wide significance in the MDD discovery phase, the MDD replication phase or in pre-planned secondary analyses (by sex, recurrent MDD, recurrent early-onset MDD, age of onset, pre-pubertal onset MDD or typical-like MDD from a latent class analyses of the MDD criteria). In the MDD-bipolar cross-disorder analysis, 15 SNPs exceeded genome-wide significance (P<5 × 10(-8)), and all were in a 248 kb interval of high LD on 3p21.1 (chr3:52 425 083-53 822 102, minimum P=5.9 × 10(-9) at rs2535629). Although this is the largest genome-wide analysis of MDD yet conducted, its high prevalence means that the sample is still underpowered to detect genetic effects typical for complex traits. Therefore, we were unable to identify robust and replicable findings. We discuss what this means for genetic research for MDD. The 3p21.1 MDD-BIP finding should be interpreted with caution as the most significant SNP did not replicate in MDD samples, and genotyping in independent samples will be needed to resolve its status.

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BACKGROUND: VeriStrat(®) is a serum proteomic test used to determine whether patients with advanced non-small cell lung cancer (NSCLC) who have already received chemotherapy are likely to have good or poor outcomes from treatment with gefitinib or erlotinib. The main objective of our retrospective study was to evaluate the role of VS as a marker of overall survival (OS) in patients treated with erlotinib and bevacizumab in the first line. PATIENTS AND METHODS: Patients were pooled from two phase II trials (SAKK19/05 and NTR528). For survival analyses, a log-rank test was used to determine if there was a statistically significant difference between groups. The hazard ratio (HR) of any separation was assessed using Cox proportional hazards models. RESULTS: 117 patients were analyzed. VeriStrat classified patients into two groups which had a statistically significant difference in duration of OS (p=0.0027, HR=0.480, 95% confidence interval: 0.294-0.784). CONCLUSION: VeriStrat has a prognostic role in patients with advanced, nonsquamous NSCLC treated with erlotinib and bevacizumab in the first line. Further work is needed to study the predictive role of VeriStrat for erlotinib and bevacizumab in chemotherapy-untreated patients.

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The major mood disorders, which include bipolar disorder and major depressive disorder (MDD), are considered heritable traits, although previous genetic association studies have had limited success in robustly identifying risk loci. We performed a meta-analysis of five case-control cohorts for major mood disorder, including over 13,600 individuals genotyped on high-density SNP arrays. We identified SNPs at 3p21.1 associated with major mood disorders (rs2251219, P = 3.63 x 10(-8); odds ratio = 0.87; 95% confidence interval, 0.83-0.92), with supportive evidence for association observed in two out of three independent replication cohorts. These results provide an example of a shared genetic susceptibility locus for bipolar disorder and MDD.

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Objective: Resection of lung metastases (LM) from colorectal cancer (CRC)¦is increasingly performed with a curative intent.Most series report small groups¦of patients, and it is currently not possible to identify those CRC patients who¦may benefit the most of surgical management. It is clinically relevant to assess¦risk factors for prolonged survival after this type of procedures.¦Methods: A meta analysis of 24 series published between 2000 and 2011¦which focused on surgical management of LM from CRC and included more¦than 40 patients each, with or without prior resection of in transit liver¦metastases. Random effects were calculated for five variables considered as¦potential prognostic factors.¦Results: A total of 2815 patients who underwent surgery with a curative¦intent were considered in this analysis. Four parameters were associated with¦a decreased survival: 1) a short disease-free interval between primary tumor¦resection and development of LM (HR = 1·59, 95% CI 1·27-1·98); 2) multiple¦LM (HR = 2·04, 95%CI 1·72-2·41); 3) positive hilar/mediastinal lymph nodes¦(HR = 1·65, 95% CI 1·35-2·02); and 4) a high prethoracotomy CEA value (HR¦=1·91, 95% CI 1·57-2·32). By comparison, a history of resected liver metastases¦(HR = 1·36, 95% CI 0·92-2·03) did not achieve statistical significance.¦Conclusion: Risk factors for poor clinical outcome after surgery for lung¦metastases in CRC patients include: 1) synchronous lung metastases; 2) high¦pre-thoracotomy CEA; 3) hilar nodes involvement; and 4) multiple pulmonary¦lesions.

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BACKGROUND: Data for trends in glycaemia and diabetes prevalence are needed to understand the effects of diet and lifestyle within populations, assess the performance of interventions, and plan health services. No consistent and comparable global analysis of trends has been done. We estimated trends and their uncertainties in mean fasting plasma glucose (FPG) and diabetes prevalence for adults aged 25 years and older in 199 countries and territories. METHODS: We obtained data from health examination surveys and epidemiological studies (370 country-years and 2·7 million participants). We converted systematically between different glycaemic metrics. For each sex, we used a Bayesian hierarchical model to estimate mean FPG and its uncertainty by age, country, and year, accounting for whether a study was nationally, subnationally, or community representative. FINDINGS: In 2008, global age-standardised mean FPG was 5·50 mmol/L (95% uncertainty interval 5·37-5·63) for men and 5·42 mmol/L (5·29-5·54) for women, having risen by 0·07 mmol/L and 0·09 mmol/L per decade, respectively. Age-standardised adult diabetes prevalence was 9·8% (8·6-11·2) in men and 9·2% (8·0-10·5) in women in 2008, up from 8·3% (6·5-10·4) and 7·5% (5·8-9·6) in 1980. The number of people with diabetes increased from 153 (127-182) million in 1980, to 347 (314-382) million in 2008. We recorded almost no change in mean FPG in east and southeast Asia and central and eastern Europe. Oceania had the largest rise, and the highest mean FPG (6·09 mmol/L, 5·73-6·49 for men; 6·08 mmol/L, 5·72-6·46 for women) and diabetes prevalence (15·5%, 11·6-20·1 for men; and 15·9%, 12·1-20·5 for women) in 2008. Mean FPG and diabetes prevalence in 2008 were also high in south Asia, Latin America and the Caribbean, and central Asia, north Africa, and the Middle East. Mean FPG in 2008 was lowest in sub-Saharan Africa, east and southeast Asia, and high-income Asia-Pacific. In high-income subregions, western Europe had the smallest rise, 0·07 mmol/L per decade for men and 0·03 mmol/L per decade for women; North America had the largest rise, 0·18 mmol/L per decade for men and 0·14 mmol/L per decade for women. INTERPRETATION: Glycaemia and diabetes are rising globally, driven both by population growth and ageing and by increasing age-specific prevalences. Effective preventive interventions are needed, and health systems should prepare to detect and manage diabetes and its sequelae. FUNDING: Bill & Melinda Gates Foundation and WHO.

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BACKGROUND: Numerous trials of the efficacy of brief alcohol intervention have been conducted in various settings among individuals with a wide range of alcohol disorders. Nevertheless, the efficacy of the intervention is likely to be influenced by the context. We evaluated the evidence of efficacy of brief alcohol interventions aimed at reducing long-term alcohol use and related harm in individuals attending primary care facilities but not seeking help for alcohol-related problems. METHODS: We selected randomized trials reporting at least 1 outcome related to alcohol consumption conducted in outpatients who were actively attending primary care centers or seeing providers. Data sources were the Cochrane Central Register of Controlled Trials, MEDLINE, PsycINFO, ISI Web of Science, ETOH database, and bibliographies of retrieved references and previous reviews. Study selection and data abstraction were performed independently and in duplicate. We assessed the validity of the studies and performed a meta-analysis of studies reporting alcohol consumption at 6 or 12 months of follow-up. RESULTS: We examined 19 trials that included 5639 individuals. Seventeen trials reported a measure of alcohol consumption, of which 8 reported a significant effect of intervention. The adjusted intention-to-treat analysis showed a mean pooled difference of -38 g of ethanol (approximately 4 drinks) per week (95% confidence interval, -51 to -24 g/wk) in favor of the brief alcohol intervention group. Evidence of other outcome measures was inconclusive. CONCLUSION: Focusing on patients in primary care, our systematic review and meta-analysis indicated that brief alcohol intervention is effective in reducing alcohol consumption at 6 and 12 months.

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Objectives: Gentamicin is one of the most commonly prescribed antibiotics for suspected or proven infection in newborns. Because of age-associated (pre- and post- natal) changes in body composition and organ function, large interindividual variability in gentamicin drug levels exists, thus requiring a close monitoring of this drug due to its narrow therapeutic index. We aimed to investigate clinical and demographic factors influencing gentamicin pharmacokinetics (PK) in a large cohort of unselected newborns and to explore optimal regimen based on simulation. Methods: All gentamicin concentration data from newborns treated at the University Hospital Center of Lausanne between December 2006 and October 2011 were retrieved. Gentamicin concentrations were measured within the frame of a routine therapeutic drug monitoring program, in which 2 concentrations (at 1h and 12h) are systematically collected after the first administered dose, and a few additional concentrations are sampled along the treatment course. A population PK analysis was performed by comparing various structural models, and the effect of clinical and demographic factors on gentamicin disposition was explored using NONMEM®. Results: A total of 3039 concentrations collected in 994 preterm (median gestational age 32.3 weeks, range 24.2-36.5 weeks) and 455 term newborns were used in the analysis. Most of the data (86%) were sampled after the first dose (C1 h and C12 h). A two-compartment model best characterized gentamicin PK. Average clearance (CL) was 0.044 L/h/kg (CV 25%), central volume of distribution (Vc) 0.442 L/kg (CV 18%), intercompartmental clearance (Q) 0.040 L/h/kg and peripheral volume of distribution (Vp) 0.122 L/kg. Body weight, gestational age and postnatal age positively influenced CL. The use of both gestational age and postnatal age better predicted CL than postmenstrual age alone. CL was affected by dopamine and furosemide administration and non-significantly by indometacin. Body weight, gestational age and dopamine coadminstration significantly influenced Vc. Model based simulation confirms that preterm infants need higher dose, superior to 4 mg/kg, and extended interval dosage regimen to achieve adequate concentration. Conclusions: This study, performed on a very large cohort of neonates, identified important factors influencing gentamicin PK. The model will serve to elaborate a Bayesian tool for dosage individualization based on a single measurement.

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BACKGROUND: Chronic kidney disease (CKD) represents an increasing health burden. We present the population-based prevalence of CKD and compare the CKD Epidemiology collaboration (CKD-EPI) and modification of diet in renal disease (MDRD) equations to estimate the glomerular filtration rate, using the revised CKD classification with three albuminuria classes. We also explore factors associated with CKD. METHODS: The Swiss population-based, cross-sectional CoLaus study conducted in Lausanne (2003-2006) included 2810 men and 3111 women aged 35-75. CKD prevalence was assessed using CKD-EPI and MDRD equations and albuminuria estimated by the albumin-to-creatinine ratio in spot morning urine. Multivariate logistic regression was used to analyse determinants of CKD. RESULTS: Prevalence [95% confidence interval (CI)] of all stages CKD was 10.0% (9.2-10.8%) with CKD-EPI and 13.8% (12.9-14.6%) with MDRD. Using the revised CKD classification, the prevalence of low-, medium-, high- and very high-risk groups was 90.0, 8.46, 1.18 and 0.35% with CKD-EPI, respectively. With MDRD, the corresponding values were 86.24, 11.86, 1.55 and 0.35%. Using the revised classification, CKD-EPI systematically reclassified people in a lower risk category than MDRD. Age and obesity were more strongly associated with CKD in men [odds ratio (95% CI): 2.23(1.95; 2.56) per 10 years and 3.05(2.08;4.47), respectively] than in women [1.46 (1.29; 1.65) and 1.78 (1.30;2.44), respectively]. Hypertension, type 2 diabetes, serum homocysteine and uric acid were positively independently associated with CKD in men and women. CONCLUSIONS: One in 10 adults suffers from CKD in the population of Lausanne. CKD-EPI systematically reclassifies people in a lower CKD risk category than MDRD. Serum homocysteine and uric acid levels are associated with CKD independently of classical risk factors such as age, hypertension and diabetes.

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Several recent studies suggest that obesity may be a risk factor for fracture. The aim of this study was to investigate the association between body mass index (BMI) and future fracture risk at different skeletal sites. In prospective cohorts from more than 25 countries, baseline data on BMI were available in 398,610 women with an average age of 63 (range, 20-105) years and follow up of 2.2 million person-years during which 30,280 osteoporotic fractures (6457 hip fractures) occurred. Femoral neck BMD was measured in 108,267 of these women. Obesity (BMI ≥ 30 kg/m(2) ) was present in 22%. A majority of osteoporotic fractures (81%) and hip fractures (87%) arose in non-obese women. Compared to a BMI of 25 kg/m(2) , the hazard ratio (HR) for osteoporotic fracture at a BMI of 35 kg/m(2) was 0.87 (95% confidence interval [CI], 0.85-0.90). When adjusted for bone mineral density (BMD), however, the same comparison showed that the HR for osteoporotic fracture was increased (HR, 1.16; 95% CI, 1.09-1.23). Low BMI is a risk factor for hip and all osteoporotic fracture, but is a protective factor for lower leg fracture, whereas high BMI is a risk factor for upper arm (humerus and elbow) fracture. When adjusted for BMD, low BMI remained a risk factor for hip fracture but was protective for osteoporotic fracture, tibia and fibula fracture, distal forearm fracture, and upper arm fracture. When adjusted for BMD, high BMI remained a risk factor for upper arm fracture but was also a risk factor for all osteoporotic fractures. The association between BMI and fracture risk is complex, differs across skeletal sites, and is modified by the interaction between BMI and BMD. At a population level, high BMI remains a protective factor for most sites of fragility fracture. The contribution of increasing population rates of obesity to apparent decreases in fracture rates should be explored. © 2014 American Society for Bone and Mineral Research.

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Building on our discovery that mutations in the transmembrane serine protease, TMPRSS3, cause nonsyndromic deafness, we have investigated the contribution of other TMPRSS family members to the auditory function. To identify which of the 16 known TMPRSS genes had a strong likelihood of involvement in hearing function, three types of biological evidence were examined: 1) expression in inner ear tissues; 2) location in a genomic interval that contains a yet unidentified gene for deafness; and 3) evaluation of hearing status of any available Tmprss knockout mouse strains. This analysis demonstrated that, besides TMPRSS3, another TMPRSS gene was essential for hearing and, indeed, mice deficient for Hepsin (Hpn) also known as Tmprss1 exhibited profound hearing loss. In addition, TMPRSS2, TMPRSS5, and CORIN, also named TMPRSS10, showed strong likelihood of involvement based on their inner ear expression and mapping position within deafness loci PKSR7, DFNB24, and DFNB25, respectively. These four TMPRSS genes were then screened for mutations in affected members of the DFNB24 and DFNB25 deafness families, and in a cohort of 362 sporadic deaf cases. This large mutation screen revealed numerous novel sequence variations including three potential pathogenic mutations in the TMPRSS5 gene. The mutant forms of TMPRSS5 showed reduced or absent proteolytic activity. Subsequently, TMPRSS genes with evidence of involvement in deafness were further characterized, and their sites of expression were determined. Tmprss1, 3, and 5 proteins were detected in spiral ganglion neurons. Tmprss3 was also present in the organ of Corti. TMPRSS1 and 3 proteins appeared stably anchored to the endoplasmic reticulum membranes, whereas TMPRSS5 was also detected at the plasma membrane. Collectively, these results provide evidence that TMPRSS1 and TMPRSS3 play and TMPRSS5 may play important and specific roles in hearing.

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Alcohol and tobacco consumption are well-recognized risk factors for head and neck cancer (HNC). Evidence suggests that genetic predisposition may also play a role. Only a few epidemiologic studies, however, have considered the relation between HNC risk and family history of HNC and other cancers. We pooled individual-level data across 12 case-control studies including 8,967 HNC cases and 13,627 controls. We obtained pooled odds ratios (OR) using fixed and random effect models and adjusting for potential confounding factors. All statistical tests were two-sided. A family history of HNC in first-degree relatives increased the risk of HNC (OR=1.7, 95% confidence interval, CI, 1.2-2.3). The risk was higher when the affected relative was a sibling (OR=2.2, 95% CI 1.6-3.1) rather than a parent (OR=1.5, 95% CI 1.1-1.8) and for more distal HNC anatomic sites (hypopharynx and larynx). The risk was also higher, or limited to, in subjects exposed to tobacco. The OR rose to 7.2 (95% CI 5.5-9.5) among subjects with family history, who were alcohol and tobacco users. A weak but significant association (OR=1.1, 95% CI 1.0-1.2) emerged for family history of other tobacco-related neoplasms, particularly with laryngeal cancer (OR=1.3, 95% CI 1.1-1.5). No association was observed for family history of nontobacco-related neoplasms and the risk of HNC (OR=1.0, 95% CI 0.9-1.1). Familial factors play a role in the etiology of HNC. In both subjects with and without family history of HNC, avoidance of tobacco and alcohol exposure may be the best way to avoid HNC.