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Georgia Salanti

Publications and source records attributed to Georgia Salanti.

15 recordsLinked to original sources
PubMed2026

Improving access to antipsychotic medications for schizophrenia in Ethiopia, Nigeria, Rwanda, and South Africa: an evidence-based global consensus.

There are disparities in access to antipsychotics for schizophrenia across different country settings. Improving access to a wider and more equitable range of medications in low-income and middle-income countries is a priority. A multidisciplinary team of international experts, including individuals with lived experience, appraised the most relevant and recent information on antipsychotics in schizophrenia and contextualised it to four African countries (Ethiopia, Nigeria, Rwanda, and South Africa) using a validated consensus methodology. We recommended a list of drugs to prioritise to guide clinical implementation and research, and market shaping. We identified key evidence gaps: little of the existing evidence comes from the countries of interest, trials generally involve highly selected populations, and the complexity of real-world settings is not reflected. However, this methodology highlights a route forward to prioritise the best available evidence on pharmacological treatments for schizophrenia at a global scale, which could also be applied to treatments for other mental health conditions.

Humans↗
PubMed2007

Bayesian meta-analysis and meta-regression for gene-disease associations and deviations from Hardy-Weinberg equilibrium.

Violation of Hardy-Weinberg equilibrium (HWE) can raise doubts about the validity of the conclusions from genetic association studies. However, for most currently performed gene-disease association studies, the available tests have low power to detect deviations from HWE. We consider this issue from a meta-analysis perspective, and suggest an approach to estimate the deviation and investigate its relationship with the observed genetic effects. Different degrees of deviation from HWE have previously been proposed as a potential source of heterogeneity across studies. We present a hierarchical meta-regression model that can be applied to test this assumption, using the concept of the fixation coefficient. We re-analyse seven meta-analyses to illustrate these methods. The uncertainty in the genetic effect estimate tended to increase once the fixation coefficient was taken into account. Dependence of the genetic effect size on the deviation from HWE was found in one meta-analysis, while in the other six examples, deviations from HWE did not clearly explain between-study heterogeneity in the genetic effects. The proposed hierarchical models allow the synthesis of data across gene-disease association studies with appropriate consideration of HWE issues.

Alleles↗
PubMed2006

Bayesian synthesis of epidemiological evidence with different combinations of exposure groups: application to a gene-gene-environment interaction.

Meta-analysis to investigate the joint effect of multiple factors in the aetiology of a disease is of increasing importance in epidemiology. This task is often challenging in practice, because studies typically concentrate on studying the effect of only one exposure, sometimes may report the interaction between two exposures, but rarely address more complex interactions that involve more than two exposures. In this paper, we develop a meta-analysis framework that combines estimates from studies of multiple exposures. A key development is an approach to combining results from studies that report information on any subset or combination of the full set of exposures. The model requires assumptions to be made about the prevalence of the specific exposures. We discuss several possible model specifications and prior distributions, including information internal and external to the meta-analysis data set, and using fixed-effect and random-effects meta-analysis assumptions. The methodology is implemented in an original meta-analysis of studies relating the risk of bladder cancer to two N-acetyltransferase genes, NAT1 and NAT2, and smoking status.

Arylamine N-Acetyltransferase↗
PubMed2006

Survival benefits with diverse chemotherapy regimens for ovarian cancer: meta-analysis of multiple treatments.

BACKGROUND: Numerous randomized trials have compared different chemotherapy regimens in women with ovarian cancer. Although ovarian cancer survival has improved in recent years, the magnitude of these incremental benefits across diverse regimens is unclear. METHODS: We used multiple-treatment meta-analysis methodology to combine information from direct and indirect comparisons of all chemotherapy regimens used in randomized trials of ovarian cancer in the last 40 years. Chemotherapy was categorized by the use or not of platinum and/or taxanes, combinations of agents, and intraperitoneal administration. Monte Carlo simulations were used to determine which regimen most improved survival. Analyses of trials that examined first- and second-line treatments were also performed separately. RESULTS: We found 198 trials (N = 38,440 women) involving 120 different chemotherapy regimens published in 1971-2006. Eighty-two trials compared different types of chemotherapy, among which 60 had usable survival information (N = 15,609 women). Monte Carlo simulations showed a 92% probability that the regimen that best prolonged survival is a platinum and taxane combination with intraperitoneal administration; this regimen resulted in a 55% relative risk reduction (95% confidence interval [CI] = 39% to 67%) for mortality as compared with nonintraperitoneal monotherapy using neither platinum nor taxane. Against that same monotherapy comparator, platinum-based combinations with and without intraperitoneal administration achieved 40% (95% CI = 21% to 54%) and 30% (95% CI = 20% to 38%) relative risk reductions for mortality, respectively, and combinations involving platinum and taxane without intraperitoneal administration achieved a 42% (95% CI = 31% to 51%) relative risk reduction. Results were similar when analyses were limited to first-line treatment. Data on second-line treatment were consistent with the superiority of platinum and taxane combinations. CONCLUSIONS: Distinct incremental improvements in survival have been achieved for ovarian cancer chemotherapy over time, with the possibility to achieve a doubling or more of time to mortality with platinum and taxane combinations, especially when intraperitoneal administration is used.

Antineoplastic Agents↗
PubMed2006

Family-based versus unrelated case-control designs for genetic associations.

The most simple and commonly used approach for genetic associations is the case-control study design of unrelated people. This design is susceptible to population stratification. This problem is obviated in family-based studies, but it is usually difficult to accumulate large enough samples of well-characterized families. We addressed empirically whether the two designs give similar estimates of association in 93 investigations where both unrelated case-control and family-based designs had been employed. Estimated odds ratios differed beyond chance between the two designs in only four instances (4%). The summary relative odds ratio (ROR) (the ratio of odds ratios obtained from unrelated case-control and family-based studies) was close to unity (0.96 [95% confidence interval, 0.91-1.01]). There was no heterogeneity in the ROR across studies (amount of heterogeneity beyond chance I(2) = 0%). Differences on whether results were nominally statistically significant (p < 0.05) or not with the two designs were common (opposite classification rates 14% and 17%); this reflected largely differences in power. Conclusions were largely similar in diverse subgroup analyses. Unrelated case-control and family-based designs give overall similar estimates of association. We cannot rule out rare large biases or common small biases.

Case-Control Studies↗
PubMed2006

Impact of violations and deviations in Hardy-Weinberg equilibrium on postulated gene-disease associations.

The authors evaluated whether statistically significant violations of Hardy-Weinberg equilibrium (HWE) or the magnitude of deviations from HWE may contribute to the problem of replicating postulated gene-disease associations across different studies. Forty-two gene-disease associations assessed in meta-analyses of 591 studies were examined. Studies with disease-free controls in which HWE was violated gave significantly different results from HWE-conforming studies in five instances. Exclusion of the former studies resulted in loss of statistical significance of the overall meta-analysis in three instances and more than a 10% change in the summary odds ratio in six. Exclusion of HWE-violating studies changed the formal significance of the estimated between-study heterogeneity in three instances. After adjustment for the magnitude of the deviation from HWE for the controls, formal significance was lost in another three instances. Studies adjusted for the magnitude of deviation from HWE tended to become more heterogeneous among themselves, and, for seven gene-disease associations, between-study heterogeneity became significant, while it was not so in the unadjusted analyses. Gene-disease association studies and meta-analyses thereof should routinely scrutinize the potential impact of HWE violations as well as nonsignificant deviations from the exact frequencies expected under HWE. Postulated genetic associations with modest-sized odds ratios and borderline statistical significance may not be robust in such sensitivity analyses.

Bias↗
PubMed2006

A road map for efficient and reliable human genome epidemiology.

Networks of investigators have begun sharing best practices, tools and methods for analysis of associations between genetic variation and common diseases. A Network of Investigator Networks has been set up to drive the process, sponsored by the Human Genome Epidemiology Network. A workshop is planned to develop consensus guidelines for reporting results of genetic association studies. Published literature databases will be integrated, and unpublished data, including 'negative' studies, will be captured by online journals and through investigator networks. Systematic reviews will be expanded to include more meta-analyses of individual-level data and prospective meta-analyses. Field synopses will offer regularly updated overviews.

Databases, Factual↗
PubMed2005

A non-parametric framework for estimating threshold limit values.

BACKGROUND: To estimate a threshold limit value for a compound known to have harmful health effects, an 'elbow' threshold model is usually applied. We are interested on non-parametric flexible alternatives. METHODS: We describe how a step function model fitted by isotonic regression can be used to estimate threshold limit values. This method returns a set of candidate locations, and we discuss two algorithms to select the threshold among them: the reduced isotonic regression and an algorithm considering the closed family of hypotheses. We assess the performance of these two alternative approaches under different scenarios in a simulation study. We illustrate the framework by analysing the data from a study conducted by the German Research Foundation aiming to set a threshold limit value in the exposure to total dust at workplace, as a causal agent for developing chronic bronchitis. RESULTS: In the paper we demonstrate the use and the properties of the proposed methodology along with the results from an application. The method appears to detect the threshold with satisfactory success. However, its performance can be compromised by the low power to reject the constant risk assumption when the true dose-response relationship is weak. CONCLUSION: The estimation of thresholds based on isotonic framework is conceptually simple and sufficiently powerful. Given that in threshold value estimation context there is not a gold standard method, the proposed model provides a useful non-parametric alternative to the standard approaches and can corroborate or challenge their findings.

Air Pollutants, Occupational↗
PubMed2005

A network of investigator networks in human genome epidemiology.

The task of identifying genetic determinants for complex, multigenetic diseases is hampered by small studies, publication and reporting biases, and lack of common standards worldwide. The authors propose the creation of a network of networks that include groups of investigators collecting data for human genome epidemiology research. Twenty-three networks of investigators addressing specific diseases or research topics and representing several hundreds of teams have already joined this initiative. For each field, the authors are currently creating a core registry of teams already participating in the respective network. A wider international registry will include all other teams also working in the same field. Independent investigators are invited to join the registries and existing networks and to join forces in creating additional ones as needed. The network of networks aims to register these networks, teams, and investigators; be a resource for information about or connections to the many networks; offer methodological support; promote sound design and standardization of analytical practices; generate inclusive overviews of fields at large; facilitate rapid confirmation of findings; and avoid duplication of effort.

Databases, Genetic↗
PubMed2005

Infant sleeping position and the sudden infant death syndrome: systematic review of observational studies and historical review of recommendations from 1940 to 2002.

BACKGROUND: Before the early 1990s, parents were advised to place infants to sleep on their front contrary to evidence from clinical research. METHODS: We systematically reviewed associations between infant sleeping positions and sudden infant death syndrome (SIDS), explored sources of heterogeneity, and compared findings with published recommendations. RESULTS: By 1970, there was a statistically significantly increased risk of SIDS for front sleeping compared with back (pooled odds ratio (OR) 2.93; 95% confidence interval (CI) 1.15, 7.47), and by 1986, for front compared with other positions (five studies, pooled OR 3.00; 1.69-5.31). The OR for front vs the back position was reduced as the prevalence of the front position in controls increased. The pooled OR for studies conducted before advice changed to avoid front sleeping was 2.95 (95% CI 1.69-5.15), and after was 6.91 (4.63-10.32). Sleeping on the front was recommended in books between 1943 and 1988 based on extrapolation from untested theory. CONCLUSIONS: Advice to put infants to sleep on the front for nearly a half century was contrary to evidence available from 1970 that this was likely to be harmful. Systematic review of preventable risk factors for SIDS from 1970 would have led to earlier recognition of the risks of sleeping on the front and might have prevented over 10 000 infant deaths in the UK and at least 50 000 in Europe, the USA, and Australasia. Attenuation of the observed harm with increased adoption of the front position probably reflects a "healthy adopter" phenomenon in that families at low risk of SIDS were more likely to adhere to prevailing health advice. This phenomenon is likely to be a general problem in the use of observational studies for assessing the safety of health promotion.

Bayes Theorem↗
PubMed2005

C-Met overexpression in node-positive breast cancer identifies patients with poor clinical outcome independent of Her2/neu.

Receptor tyrosine kinases play an important role in malignant transformation of epithelial cells by activating signal transduction pathways important for proliferation, invasion and metastasis. In a pilot study (n = 40), we evaluated expression of the c-Met and Her2/neu receptor tyrosine kinases and the c-Met ligand hepatocyte growth factor/scatter factor (HGF/SF) in primary breast cancers and their lymph node metastases using both conventional immunohistochemistry and confocal immunofluorescence. Neither c-Met and HGF/SF nor Her2/neu expression correlated with established prognostic factors such as age, lymph node involvement, estrogen receptor (ER), progesterone receptor (PR), tumor size, or grade. Both staining methods confirmed a significant correlation between c-Met overexpression and a high risk of disease progression. Furthermore, among tumors with c-Met overexpression, only 50% also overexpress Her2/neu, thus identifying a subset of patients with aggressive disease in addition to Her2/neu. Median disease-free survival in patients with c-Met overexpressing tumors was 8 months compared to 53 months when c-Met expression was low (p = 0.037; RR = 3.0). This significant impact of c-Met on tumor aggressiveness independent of Her2/neu was also confirmed by multivariate analysis. In conclusion, the role of c-Met expression as a prognostic variable and consequently as an interesting target for novel therapeutic approaches deserves further analysis in a larger cohort of patients.

Adult↗
PubMed2005

Hardy-Weinberg equilibrium in genetic association studies: an empirical evaluation of reporting, deviations, and power.

We evaluated the testing and reporting of Hardy-Weinberg equilibrium (HWE) in recent genetic association studies, detected how frequently HWE was violated and estimated the power for HWE testing in this literature. Genetic association studies published in 2002 in Nature Genetics, American Journal of Human Genetics, and American Journal of Medical Genetics were assessed. Data were analyzed on 239 biallelic associations using 154 distinct genotype distribution data sets where HWE could be tested. Any information on HWE was given only for 150 (62.8%) associations (92 (59.7%) data sets). Reanalysis of the data showed significant deviation from HWE in the disease-free controls of 20 associations (13 data sets), but only four of them (two data sets) were admitted in the published articles. Another four deviations (in two data sets) were observed in the combined sample of cases and controls of studies where both cases and controls were diseased, and none were reported in the papers. In all six tested multiallelic associations (six data sets), there was violation of HWE, but this was not admitted in the published articles. Power calculations showed that most studies conforming to HWE simply were largely underpowered to detect HWE deviation; for example, power to detect an inbreeding of magnitude F=0.10 exceeded 80% in only 11 (7%) of the data sets being tested. This empirical evidence suggests that, even in high profile genetics journals, testing and reporting for HWE is often neglected and deviations are rarely admitted in the published reports. Moreover, power is limited for HWE testing in most current genetic association studies.

Databases as Topic↗
PubMed2005

Obstacles and opportunities in meta-analysis of genetic association studies.

Genetic association studies have the potential to advance our understanding of genotype-phenotype relationships, especially for common, complex diseases where other approaches, such as linkage, are less powerful. Unfortunately, many reported studies are not replicated or corroborated. This lack of reproducibility has many potential causes, relating to study design, sample size, and power issues, and from sources of true variability among populations. Genetic association studies can be considered as more similar to randomized trials than other types of observational epidemiological studies because of "Mendelian randomization" (Mendel's second law). The rationale and methodology for synthesizing randomized trials is highly relevant to the meta-analysis of genetic association studies. Nevertheless, there are a number of obstacles to overcome when performing such meta-analyses. In this review, the impacts of Type I error, lack of power, and publication and reporting biases are explored, and the role of multiple testing is discussed. A number of special features of association studies are especially pertinent, because they may lead to true variability among study results. These include population dynamics and structure, linkage disequilibrium, conformity to Hardy-Weinberg Equilibrium, bias, population stratification, statistical heterogeneity, epistatic and environmental interactions, and the choice of statistical models used in the analysis. Approaches to dealing with these issues are outlined. The supreme importance of complete and consistent study reporting and of making data readily available is also highlighted as a prerequisite for sound meta-analysis. We believe that systematic review and meta-analysis has an important role to play in understanding genetic association studies and should help us to separate the wheat from the chaff.

Epistasis, Genetic↗
PubMed2003

A nonparametric changepoint model for stratifying continuous variables under order restrictions and binary outcome.

Modelling using monotonic regression can be a useful alternative to parametric approaches when optimal stratification for continuous predictors is of interest. This method is described here in the context of binary response. Within this framework we aim to address two points. First, we propose a method to enhance the parsimony of the model, by applying a reducing procedure based on a sequence of Fisher exact tests and a bootstrap method to select between full monotonic and reduced model. Secondly, we discuss the case of multiple predictors: an iterative algorithm (an extension of the Pool Adjacent Violators Algorithm) can be applied when more than one predictor variable is taken into account. The resulting model is a monotonic surface and can be applied alternatively to the additive monotonic models as described by Morton-Jones and colleagues when the explanatory variables are assumed to interact. The monotonic-surface model provides also a multivariate extension of the monotonic likelihood ratio test. This test is discussed here and an approach based on permutations to assess the p-value is proposed. Finally, we combine both ideas (reduced monotonic regression and monotonic-surface estimation) to a simple and easy to interpret model, which leads to a combination of the predictors in a few constant risk groups. Despite the fact that the proposed approach becomes somewhat cumbersome due to the lack of asymptotic methods to infer, it is attractive because of its simplicity and stability. An application will outline the benefit of using bivariate step functions in modelling.

Air Pollutants, Occupational↗