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At least 361 records · Page 20Linked to original sources
PubMed2003

[Fluindione-induced acute exanthematous pustulosis with renal involvement].

INTRODUCTION: Fluindione (Previscan) is an oral anti-vitamin K anticoagulant, widely prescribed in France. Contrary to phenindione, which is also an indanedione derivative, very few cases of immunoallergic reactions have been described. CASE REPORT: A 68 year-old man, treated with fluindione for cardiac arrhythmia, presented with a pustular eruption and erythema twenty days after initiation of treatment. The eruption was associated with hyperthermia, arthralgia, neutrophilia (11,000/mm2), hepatic cytolysis and renal involvement including acute renal failure, hematuria and proteinuria. In view of the absence of any earlier case in the literature, we did not impute fluindione and the drug was reintroduced and led to the rapid recurrence of all the same manifestations. DISCUSSION: These manifestations were consistent with an immunoallergic reaction to fluindione (probable intrinsic imputability I3) and acute interstitial nephritis (probable intrinsic imputability I3). We believe this is the first case of acute generalized exanthematous pustulosis induced by fluindione (intrinsic imputability Bo). A few rare cases of fluindione-induced hypersensitivity reactions and acute interstitial nephritis, however, have been described.

Acute Disease↗
PubMed2005

[Recognition of occupational cancers: review of existing methods and perspectives].

Occupational risk factors represent a significant part of cancer causes and are involved in all type of cancers. Nonetheless, the frequency of these cancers is largely under-estimated. Parallel to the epidemiological approach (collective), the concept of occupational cancer is often linked (at the individual level) to the compensation of occupational diseases. To give rise to a financial compensation, the occupational origin of the exposition has to be established for a given cancer. Whatever the method used to explore an occupational cause, the approach is that of an imputation. The aim of this work is to synthesize and describe the main principles of recognition of occupational cancers, to discuss the limits of available methods and to consider the research needed to improve these methods. In France, the recognition of a cancer's occupational origin consists in tables of occupational diseases that are based on presumption of causality. These tables consist in medical, technical and administrative conditions that are necessary and sufficient for the recognition of an occupational disease and its financial compensation. Whenever causality presumption does not apply, imputation is based on case analyses run by experts within regional committees of occupational diseases recognition that lack reproducibility. They do not allow statistical quantization and do not always take into account the weight of associated factors. Nonetheless, reliability and validity of the expertise could be reinforced by the use of formal consensus techniques. This process could ideally lead to the generation of decision-making algorithms that could guide the user towards the decision of imputing or not the cancer to an occupational exposure. This would be adapted to the build-up of new tables. The imputation process would be better represented by statistical methods based on the use of Bayes' theorem. The application of these methods to occupational cancers is promising but remains limited due to the lack of epidemiological data. Acquiring these data and diffusing these methods should become research and development priorities in the cancer field.

Causality↗
PubMedDate not supplied

Incomplete quality of life data in randomized trials: missing items.

Missing data has been a problem in many quality of life studies. This paper focuses upon the issues involved in handling forms which contain one or more missing items, and reviews the alternative procedures. One of the most widely practised approaches is imputation using the mean of all observed items in the same subscale. This, together with the related estimation of the subscale score, is based upon traditional psychometric approaches to scale design and analysis. We show that it may be an inappropriate method for many of the items in quality of life questionnaires, and would result in biased or misleading estimates. We provide examples of items and subscales which violate the psychometric foundations that underpin simple mean imputation. A checklist is proposed for examining the adequacy of simple imputation, and some alternative procedures are indicated.

Female↗
PubMed2000

On the inclusion of prevalent cases in HIV/AIDS natural history studies through a marker-based estimate of time since seroconversion.

In most cohort studies of HIV infection and AIDS, seroprevalent cases provide a substantial amount of information. Inclusion of these people in natural history studies requires a fairly unbiased method to estimate their seroconversion distribution. When a cohort-based estimate is not feasible, an alternative is to estimate individual seroconversion distributions, based on marker values at entry. In this paper, a non-parametric marker-based estimation method is developed. The method is applied to data from the Amsterdam cohort study on homosexual men. For seroprevalent cases who entered the study between October 1984 and April 1985, individual seroconversion distributions are estimated based on their first measured CD4 count. In subsequent survival analyses, dates of seroconversion are estimated via conditional mean imputation. Inclusion of these seroprevalent cases greatly improves the quality of the data. Age at seroconversion is a significant cofactor for disease progression, a result not found when analysis is restricted to those who seroconvert. To incorporate the uncertainty in the imputed date of seroconversion, a bootstrap procedure is developed for the computation of p-values and confidence intervals. In our analyses, standard procedures, which ignore the uncertainty in the imputed date of seroconversion, perform almost as well.

Acquired Immunodeficiency Syndrome↗
PubMed2001

Maximum likelihood inference for left-censored HIV RNA data.

Left-censored data are characteristic of many bioassays due to inherent limit of detection and limit of quantitation (LOQ) in the assays. This paper examines how the left-censoring of plasma HIV RNA measurements, collected for the Hemophilia Growth and Development Study, affects the quantification of viral load and the assessment of its association with a continuous or dichotomous outcome. Data analyses using maximum likelihood estimation are compared to analyses where the LOQ or LOQ/2 value is substituted for the left-censored observations, and also to other methods like multiple imputation. A Gaussian distribution is assumed for the log-transformed plasma HIV RNA data, and simulations are used to explore the sensitivity of the results to changes in the model parameters. The robustness of the estimators is also investigated when the data are generated from a mixture of two Gaussian distributions. Maximum likelihood is in general the least biased method. However, multiple imputation assuming a censored Gaussian imputation model and substituting the censored values with the expectation of its conditional predictive distribution are also competitive to maximum likelihood, and may be appealing because of their simpler computational algorithms.

Adolescent↗
PubMed2005

Accounting for haplotype uncertainty in matched association studies: a comparison of simple and flexible techniques.

Population-based case-control studies measuring associations between haplotypes of single nucleotide polymorphisms (SNPs) are increasingly popular, in part because haplotypes of a few "tagging" SNPs may serve as surrogates for variation in relatively large sections of the genome. Due to current technological limitations, haplotypes in cases and controls must be inferred from unphased genotypic data. Using individual-specific inferred haplotypes as covariates in standard epidemiologic analyses (e.g., conditional logistic regression) is an attractive analysis strategy, as it allows adjustment for nongenetic covariates, provides omnibus and haplotype-specific tests of association, and can estimate haplotype and haplotype x environment interaction effects. In principle, some adjustment for the uncertainty in inferred haplotypes should be made. Via simulation, we compare the performance (bias and mean squared error of haplotype and haplotype x environment interaction effect estimates) of several analytic strategies using inferred haplotypes in the context of matched case-control data. These strategies include using only the most likely haplotype assignment, the expectation substitution approach described by Stram et al. ([2003b] Hum. Hered. 55:179-190) and others, and an improper version of multiple imputation. For relatively uncomplicated haplotype structures and moderate haplotype relative risks (</=2), all methods performed comparably well (small bias with appropriately-sized confidence intervals). For larger relative risks, the most likely haplotype and multiple imputation strategies showed noticeable bias towards the null; the expectation substitution strategy still performed well. When there was more uncertainty in the inferred haplotypes, the most likely and multiple imputation strategies showed even more bias towards the null, while the expectation substitution method had slightly smaller than nominal confidence intervals for larger relative risks (>/=5). An application to progesterone-receptor haplotypes and endometrial cancer further illustrates that the performance of all these methods depends on how well the observed haplotypes "tag" the unobserved causal variant.

Algorithms↗
PubMed2006

Simple estimates of haplotype relative risks in case-control data.

Methods of varying complexity have been proposed to efficiently estimate haplotype relative risks in case-control data. Our goal was to compare methods that estimate associations between disease conditions and common haplotypes in large case-control studies such that haplotype imputation is done once as a simple data-processing step. We performed a simulation study based on haplotype frequencies for two renin-angiotensin system genes. The iterative and noniterative methods we compared involved fitting a weighted logistic regression, but differed in how the probability weights were specified. We also quantified the amount of ambiguity in the simulated genes. For one gene, there was essentially no uncertainty in the imputed diplotypes and every method performed well. For the other, approximately 60% of individuals had an unambiguous diplotype, and approximately 90% had a highest posterior probability greater than 0.75. For this gene, all methods performed well under no genetic effects, moderate effects, and strong effects tagged by a single nucleotide polymorphism (SNP). Noniterative methods produced biased estimates under strong effects not tagged by an SNP. For the most likely diplotype, median bias of the log-relative risks ranged between -0.49 and 0.22 over all haplotypes. For all possible diplotypes, median bias ranged between -0.73 and 0.08. Results were similar under interaction with a binary covariate. Noniterative weighted logistic regression provides valid tests for genetic associations and reliable estimates of modest effects of common haplotypes, and can be implemented in standard software. The potential for phase ambiguity does not necessarily imply uncertainty in imputed diplotypes, especially in large studies of common haplotypes.

Algorithms↗
PubMed2005

Polymorphisms of the DNA repair genes XPD (Lys751Gln) and XRCC1 (Arg399Gln and Arg194Trp): relationship to breast cancer risk and familial predisposition to breast cancer.

Family history is a risk factor for breast cancer and could be due to shared environmental factors or polymorphisms of cancer susceptibility genes. Deficient function of DNA repair enzymes may partially explain familial risk as polymorphisms of DNA repair genes have been associated, although inconsistently, with breast cancer. This population based case-control study examined the association between polymorphisms in XPD (Lys751Gln) and XRCC1 (Arg399Gln and Arg194Trp) genes, and breast cancer. Breast cancer cases (n=321) and controls (n=321) were matched on age and menopausal status. Conditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI). The analysis was conducted omitting observations with missing data, and by using imputation methods to handle missing data. No significant association was observed between the XPD 751Gln/Lys (OR 1.37, 95% CI 0.96-1.96) and Gln/Gln genotypes (OR 1.08, 95% CI 0.62-1.86) (referent Lys/Lys), XRCC1 399Arg/Gln (OR 1.48, 95% CI 0.92-2.38) and Gln/Gln genotypes (1.11, 95% CI 0.67-1.83) (referent Arg/Arg) or the XRCC1 Arg/Trp and Trp/Trp genotypes (OR 1.12, 95% CI 0.69-1.83) (referent Arg/Arg) and breast cancer. In multivariate analysis, the adjusted odds ratios for the XPD and XRCC1 399 polymorphisms increased and became statistically significant, however, were attenuated when imputation methods were used to handle missing data. There was no interaction with family history. These results indicate that these polymorphisms in XPD and XRCC1 genes are only weakly associated with breast cancer. Without imputation methods for handling missing data, a statistically significant association was observed between the genotypes and breast cancer, illustrating the potential for bias in studies that inadequately handle missing data.

Adult↗
PubMed2006

Comparison of statistical models for analyzing genotype, inferred haplotype, and molecular haplotype data.

This report compares statistical models based on molecular and inferred haplotypes of the human paraoxonase-1 gene (PON1). In a study of 402 women comprising three race/ethnicities, 137 women had ambiguous inferred haplotypes. The inferred haplotypes (the one with highest posterior probability) for 20 of these women differed from molecular haplotypes, while based on the posterior distribution from the imputation method, 30 discrepancies were expected. We examined the proportion of the variance in PON1 enzymatic activity (phenotype) explained by genotype, and by inferred and molecular haplotype information. For Caucasians, there was an improvement in adjusted R(2) from 16% for the genotype count model, to 29% for imputed haplotypes, and a further improvement to 33% for molecular haplotypes. For Hispanics and African-Americans, there was no indication that haplotypes helped in explaining PON1 activity, and the imputed model gave essentially the same R(2) as the molecular model. For African-Americans, none of the models had adjusted R(2) that exceeded 4%, while for Hispanics they were all about 21-22%. We propose a new parsimonious model which uses all the genotype information and selected haplotype information. For PON1, this model achieves essentially the same adjusted R(2) as the all-haplotype model, with a potential cost savings and without giving the extreme predictions for uncommon haplotype combinations that the all-haplotype models provides.

Aryldialkylphosphatase↗
PubMed2003

Developing a prognostic model in the presence of missing data: an ovarian cancer case study.

When developing prognostic models in medicine, covariate data are often missing and the standard response is to exclude those individuals whose data are incomplete from the analyses. This practice leads to a reduction in the statistical power, and may lead to biased results. We wished to develop a prognostic model for overall survival from 1,189 primary cases (842 deaths) of epithelial ovarian cancer. A complete case analysis restricted the sample size to 518 (380 deaths). After applying a multiple imputation (MI) framework we included three real values for each one imputed, and constructed a model composed of more statistically significant prognostic factors and with increased predictive ability. Missing values can be imputed in cases where the reason for the data being missing is known, particularly where it can be explained by available data. This will increase the power of an analysis and may produce models that are more statistically reliable and applicable within clinical practice.

Adolescent↗
PubMed2001

Comparison of methods to analyse imprecise faecal coliform count data from environmental samples.

Imprecise values arise when bacterial colonies are too numerous to be counted or when no colonies grow at a specific dilution. Our objective was to show the usefulness of multiple imputation in analysing data containing imprecise values. We also indicate that interval censored regression, which is faster computationally in situations where it applies, can be used, providing similar estimates to imputation. We used bacteriological data from a large epidemiological study in daycare centres to illustrate this method and compared it to a standard method which uses single exact values for the imprecise data. The data consisted of numbers of FC on children's and educators' hands, from sandboxes and from playareas. In general, we found that multiple imputation and interval censored regression provided more conservative intervals than the standard method. The discrepancy in the results highlights both the importance of using a method that best captures the uncertainty in the data and how different conclusions might be drawn. This can be crucial for both researchers and those who are involved in formulating and regulating standards for bacteriological contamination.

Child Day Care Centers↗
PubMed2002

GSTM-1 and NAT2 and genetic alterations in colon tumors.

OBJECTIVE: Phase II metabolizing enzymes such as glutathione S-transferases and N-acetyltransferase are involved in the detoxification of carcinogens. Genetic variants of genes coding for these enzymes have been evaluated as to their association with colon cancer, both as independent risk factors and as effect modifiers for associations with diet and cigarette smoking. In this study, we evaluate associations between the GSTM-1 genotype and the NAT2-imputed phenotype and acquired mutations in tumors. METHODS: Data is taken from a set of 1836 cases and 1958 controls with colon cancer who were part of a large case-control study of colon cancer and whose tumors were previously analyzed for Ki-ras, p53, and microsatellite instability (MSI). We also evaluate the modifying effects of these genetic variants with diet and cigarette smoking, factors previously identified as being associated with specific tumor alterations. RESULTS: Neither GSTM-1 nor the NAT2-imputed phenotype was independently associated with Ki-ras, p53, or MSI. Cigarette smoking significantly increased the risk of tumors involving the MSI pathway. Additionally, cigarette smoking doubled the risk of p53 transversion mutations among those who were GSTM-1 present. Cases were slightly more likely to have a p53 mutation if they frequently consumed red meat and had the imputed NAT2 intermediate/rapid phenotype relative to slow phenotype/infrequent consumers of red meat (OR 2.0, 95% CI 1.3-3.0 for intermediate/rapid). CONCLUSIONS: These data provide support that diet and cigarette smoking may be associated with specific disease pathways, although GSTM-1 and NAT2 do not independently appear to alter susceptibility to these diet and lifestyle factors.

Adult↗
PubMed2004

Cardiac adverse effects associated with psychotropic drugs.

Within the drug safety program in psychiatry AMSP ( Arzneimittelsicherheit in der Psychiatrie), severe adverse drug reactions (ADRs) in psychiatric inpatients are assessed in the naturalistic setting of routine treatment. Currently, 35 psychiatric hospitals and departments are participating. This paper focuses on severe cardiovascular ADRs due to psychotropic medications. Related to the number of patients surveyed (122,562 from 1993 to 2000), these are rare events (68 cases or 0.055 %). Imputed drug classes for probable cases were antidepressants in 0.03 % and neuroleptics in 0.019 %, but other drugs were also involved. Within the group of antidepressants, the risk for a cardiac ADR depends much on the class: SSRIs were never imputed alone, but tricyclic antidepressants were imputed alone in 0.05 %. In the group of antipsychotics, the lowest rate of cardiac ADRs was found for the group of phenothiazines (0.003 %). Cardiovascular risk factors elevated the risk for a cardiac ADR from 0.04 % to 0.14 %. Age as an independent factor did not contribute substantially to the risk for a cardiac ADR. The data of the drug safety program in psychiatry allow some estimate of differential risk rates for cardiac ADRs with different psychotropic drug groups. The results of the project can help clinicians select the appropriate drug for patients at risk to develop cardiac ADRs.

Adult↗
PubMed2004

Sensitivity analysis for pattern mixture models.

Incomplete series of data is a common feature in quality-of-life studies, in particular in chronic diseases where attrition of patients is high. Two alternative approaches to modeling longitudinal data with incomplete measurements have frequently been proposed in the literature, selection models and pattern-mixture models. In this paper we focus on, by way of sensitivity analysis, extrapolating incomplete patterns using identifying restrictions. Perhaps the best known ones are so-called complete case missing value restrictions (CCMV), where for a given pattern, the conditional distribution of the missing data, given the observed data, is equated to its counterpart in the completers. Available case missing value (ACMV) restrictions equate this conditional density to the one calculated from the subgroup of all patterns for which all required components have been observed. Neighboring case missing value restrictions (NCMV) equate this conditional density to the one calculated from the the pattern with one additional measurement obtained. In this paper, these three identifying restriction strategies are used to multiply impute missing data in a study in metastatic prostate cancer. Multiple imputation is employed to reduce the uncertainty of single imputation. It is shown how hypothesis testing and sensitivity analyses are carried out in this setting.

Humans↗
PubMed2005

Accounting for missing data in end-of-life research.

End-of-life studies are likely to have missing data because sicker persons are less likely to provide information and because measurements cannot be made after death. Ignoring missing data may result in data that are too favorable, because the sickest persons are effectively dropped from the analysis. In a comparison of two groups, the group with the most deaths and missing data will tend to have the most favorable data, which is not desirable. Results based on only the available data may not be generalizable to the original study population. If most of the missing data are absent because of death, methods that account for the deaths may remove much of the bias. Imputation methods can then be used for the data that are missing for other reasons. An example is presented from a randomized trial involving frail veterans. In that dataset, only two thirds of the subjects had complete data, but 60% of the "missing" data were missing because of death. The available data alone suggested that health improved significantly over time. However, after accounting for the deaths, there was a significant decline in health over time, as had been expected. Imputation of the remaining missing data did not change the results very much. With and without the imputed data, there was never a significant difference between the treatment and control groups, but in two nonrandomized comparisons the method of handling the missing data made a substantive difference. These sensitivity analyses suggest that the main results were not sensitive to the death and missing data, but that some secondary analyses were sensitive to these problems. Similar approaches should be considered in other end-of-life studies.

Aged↗
PubMed2004

The impact of delayed chemotherapy-induced nausea and vomiting on patients, health resource utilization and costs in German cancer centers.

BACKGROUND: Delayed chemotherapy-induced nausea and vomiting (CINV) remains a major adverse effect of cancer chemotherapy. We assessed, under current practice patterns, the occurrence and impact on healthcare resource utilization of CINV in patients receiving emetogenic chemotherapy. An additional aim of this study was to estimate costs imputable to CINV in the German healthcare environment. MATERIALS AND METHODS: This prospective, multi-center, cross-sectional cost-of-illness study was conducted in three hospitals and in three office-based facilities in Germany. Consecutive patients undergoing emetogenic chemotherapy (levels 4 or 5 according to Hesketh classification of emetogenicity) were enrolled. Data were obtained from preplanned chart reviews and from self-administered patient questionnaires. Analysis of direct costs was performed from the perspectives of third party payer (statutory sick fund), provider (hospital) and patients. Indirect costs were assessed on the basis of paid workdays lost. RESULTS: During the 5-day observation period, 134 of 208 chemotherapy cycles observed (64.4%) were associated with at least one episode of nausea or vomiting. More patients experienced delayed than acute CINV (60.7% versus 32.8%), and more patients reported nausea than vomiting (62.5% versus 26.0%). A total of 68 patients (32.6%) utilized healthcare resources due to CINV. The most frequently used resources were rescue medications and outpatient hospital and office physician visits. Only one patient required hospitalization and only three patients lost workdays due to CINV. Average costs imputable to CINV per patient (with or without CINV) per treatment cycle incurred by third party payers and hospital providers were Euro 49 and Euro 48, respectively. Patient or treatment characteristics that were associated with high costs imputable to CINV were as follows: cisplatin-containing regimen; experience of emesis; and presence of delayed CINV. CONCLUSIONS: A substantial proportion of patients continue to experience CINV. This entails not only clinical but also economic consequences, and highlights a continuing need for improved utilization of existing antiemetic agents and for new, more efficacious treatments. The greatest improvements in patient care and potential for cost offset may be realized by preventing delayed CINV.

Antiemetics↗
PubMed2025

FINEMAP-miss: fine-mapping genome-wide association studies with missing genotype information.

MOTIVATION: The most informative genome-wide association studies (GWAS) are meta-analyses that have combined multiple studies to increase the GWAS sample size. Statistical fine-mapping is a key downstream analysis of GWAS to jointly evaluate the probability of causality of all variants in a genomic region of interest. Current fine-mapping methods are miscalibrated in the meta-analysis setting due to variation in sample size across the variants. RESULTS: We introduce FINEMAP-miss, a new fine-mapping method that extends the FINEMAP model to account for variant-specific missingness. We show that FINEMAP-miss is well-calibrated in meta-analysis simulations where the standard fine-mapping fails. Compared to the summary statistics imputation approach, FINEMAP-miss provides clear improvement when the causal variants have low imputation information or when the sample size or complexity of the meta-analysis setting increase. We successfully apply FINEMAP-miss on a breast cancer GWAS meta-analysis where neither the standard fine-mapping nor the summary statistics imputation are applicable. AVAILABILITY: An open source implementation of FINEMAP-miss as an R package ("finemapmiss") is available at https://github.com/JoonasKartau/finemapmiss. The archived version of FINEMAP-miss used for this publication can be found on Zenodo at https://doi.org/10.5281/zenodo.17492622. SUPPLEMENTARY INFORMATION: is available at the journal's web site.

Genome-Wide Association Study↗
PubMed1996

Opportunity wages and workforce adjustments: understanding the cost of in-home elder care.

Time spent providing informal care represents a real cost to caregivers and potentially affects their decisions about alternative activities, including paid work. This study offers estimates of opportunity wages incurred by informal caregivers and explores the impact of these costs on their decisions to reduce or abandon workforce participation. We consider caregivers at two points in time: 1982 and 1989. Our estimates of caregivers' imputed wages vary more widely and range higher than those reported elsewhere, varying from $0.78 to $27.18 per hour, compared to values in the literature ranging from $4.64 to $10.30. In both years, caregivers with higher imputed wages were significantly more likely to work, with this effect stronger in 1989 as all noneconomic factors became less important. However, accommodation (working fewer hours or foregoing job opportunities) decreased with higher imputed wages in 1982 only. In 1989, elders' frailty became a significant determinant of accommodation.

Aged↗