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Audacious goals for health and biomedical informatics in the new millennium.

The 1998 Scientific Symposium of the American College of Medical Informatics (ACMI) was devoted to developing visions for the future of health care and biomedicine and a strategic agenda for health and biomedical informatics in support of those visions. This symposium focus was prompted by the many major changes currently underway in health care delivery, education, and research, as well as in our health and biomedical enterprises, and by the constantly increasing role of information technology in both shaping and enabling these changes. The three audacious goals developed for 2008 are a virtual health care databank, a national health care knowledge base, and a personal clinical health record.

Artificial Intelligence↗
PubMed2005

European myeloma network: the value of collaborative research.

The European Myeloma Network was established as a result of collaboration and cooperation between myeloma physicians and researchers. The initial impetus that brought this group together came from the Sixth Framework Programme (2002), as the group initially formed to apply for funding from this source. Although the application was unsuccessful, it provided encouragement to continue the activities, and the network was formally established in October 2003. The basic idea was to create interaction between the people working in different areas of myeloma (for example, basic science, clinical trials and patient education) and build an interface to establish standardisation of laboratory techniques such as fluorescent in-situ hybridisation (FISH) techniques for these groups. The aim of the network is to bring these groups together in some way, to deliver better quality research. Resources need to be used wisely, with priorities being set. Establishing a common databank of trials from the European Community where trial data is pooled is one such priority. This project can then extend into the future to analyse clinical, biological and genetic prognostic factors. Looking ahead to other potential benefits of the network, there may be opportunities to examine orphan treatments, and it has the potential to act as the intermediate organisation, helping pharmaceutical companies and tumour working groups in a variety of countries to establish the most appropriate clinical trials.

Biomedical Research↗
PubMed2003

Predicting major neurological improvement with intravenous recombinant tissue plasminogen activator treatment of stroke.

BACKGROUND AND PURPOSE: In the National Institute of Neurological Disorders and Stroke (NINDS) rt-PA Stroke Study, major neurological improvement within 24 hours (MNI) occurred significantly more frequently with recombinant tissue plasminogen activator (rtPA) treatment than with placebo. We explored the relationship between MNI and 3-month favorable outcome and sought clinical predictors of MNI. METHODS: Data from 312 rtPA-treated patients from the NINDS trial were used to assess the ability of MNI to predict favorable outcome at 3 months as defined by a modified Rankin Scale score of 0 to 1. Next, a multivariable predictive model was developed for MNI within the same data set. Clinical variables examined included age, time to treatment (TTT), diabetes, pretreatment glucose, baseline National Institutes of Health Stroke Scale score, pretreatment blood pressure, history of atrial fibrillation, weight >100 kg, and a dense artery sign. Finally, this model was used to forecast into the placebo group of the NINDS trial to assess the uniqueness of the predictors in the rtPA-treated group. RESULTS: MNI had a positive predictive value and negative predictive value of 0.70 for predicting favorable 3-month outcome. Only age [odds ratio (OR), 0.68; 95% confidence interval (CI), 0.47 to 0.99] and TTT (OR, 0.56; 95% CI, 0.34 to 0.91) appear to be independently associated with MNI. The model performed only moderately well (area under the receiver-operating characteristic curve, 0.66). Age (OR, 0.67; 95% CI, 0.45 to 0.99) but not TTT was associated with MNI in the placebo group. CONCLUSIONS: MNI may be a useful surrogate for thrombolytic activity and is predictive of favorable 3-month outcome. When rates of MNI in different populations of stroke patients treated with thrombolysis are compared, adjustments for age and TTT may be necessary.

Age Factors↗
PubMed2001

Mathematical biology and medical statistics: contributions to the understanding of AIDS epidemiology.

Some of the many ways in which mathematical biology and statistics have been used in investigating the acquired immunodeficiency syndrome (AIDS) epidemic are reviewed. Aspects of the spread of the disease via social and sexual networks are discussed. The different kinds of data involved are critically compared. Some studies of the incubation period are briefly reviewed and some comments made on the role of adherence to therapy.

Acquired Immunodeficiency Syndrome↗
PubMed2006

Dental flossing and interproximal caries: a systematic review.

Our aim was to assess, systematically, the effect of flossing on interproximal caries risk. Six trials involving 808 subjects, ages 4 to 13 years, were identified. There were significant study-to-study differences and a moderate to large potential for bias. Professional flossing performed on school days for 1.7 years on predominantly primary teeth in children was associated with a 40% caries risk reduction (relative risk, 0.60; 95% confidence interval, 0.48-0.76; p-value, < 0.001). Both three-monthly professional flossing for 3 years (relative risk, 0.93; 95% confidence interval, 0.73-1.19; p-value, 0.32) and self-performed flossing in young adolescents for 2 years (relative risk, 1.01; 95% confidence interval, 0.85-1.20; p-value, 0.93) did not reduce caries risk. No flossing trials in adults or under unsupervised conditions could be identified. Professional flossing in children with low fluoride exposures is highly effective in reducing interproximal caries risk. These findings should be extrapolated to more typical floss-users with care, since self-flossing has failed to show an effect.

Adolescent↗
PubMed2005

Linkage disequilibrium mapping via cladistic analysis of phase-unknown genotypes and inferred haplotypes in the Genetic Analysis Workshop 14 simulated data.

We recently described a method for linkage disequilibrium (LD) mapping, using cladistic analysis of phased single-nucleotide polymorphism (SNP) haplotypes in a logistic regression framework. However, haplotypes are often not available and cannot be deduced with certainty from the unphased genotypes. One possible two-stage approach is to infer the phase of multilocus genotype data and analyze the resulting haplotypes as if known. Here, haplotypes are inferred using the expectation-maximization (EM) algorithm and the best-guess phase assignment for each individual analyzed. However, inferring haplotypes from phase-unknown data is prone to error and this should be taken into account in the subsequent analysis. An alternative approach is to analyze the phase-unknown multilocus genotypes themselves. Here we present a generalization of the method for phase-known haplotype data to the case of unphased SNP genotypes. Our approach is designed for high-density SNP data, so we opted to analyze the simulated dataset. The marker spacing in the initial screen was too large for our method to be effective, so we used the answers provided to request further data in regions around the disease loci and in null regions. Power to detect the disease loci, accuracy in localizing the true site of the locus, and false-positive error rates are reported for the inferred-haplotype and unphased genotype methods. For this data, analyzing inferred haplotypes outperforms analysis of genotypes. As expected, our results suggest that when there is little or no LD between a disease locus and the flanking region, there will be no chance of detecting it unless the disease variant itself is genotyped.

Chromosome Mapping↗
PubMed2005

Identification of susceptibility loci for complex diseases in a case-control association study using the Genetic Analysis Workshop 14 dataset.

Although current methods in genetic epidemiology have been extremely successful in identifying genetic loci responsible for Mendelian traits, most common diseases do not follow simple Mendelian modes of inheritance. It is important to consider how our current methodologies function in the realm of complex diseases. The aim of this study was to determine the ability of conventional association methods to fine map a locus of interest. Six study populations were selected from 10 replicates (New York) from the Genetic Analysis Workshop 14 simulated dataset and analyzed for association between the disease trait and locus D2. Genotypes from 45 single-nucleotide polymorphisms in the telomeric region of chromosome 3 were analyzed by Pearson's chi-square tests for independence to test for association with the disease trait of interest. A significant association was detected within the region; however, it was found 3 cM from the documented location of the D2 disease locus. This result was most likely due to the method used for data simulation. In general, this study showed that conventional case-control association methods could detect disease loci responsible for the development of complex traits.

Case-Control Studies↗
PubMed2005

Comparisons of case-selection approaches based on allele sharing and/or disease severity index: application to the GAW14 simulated data.

For mapping complex disease traits, linkage studies are often followed by a case-control association strategy in order to identify disease-associated genes/single-nucleotide polymorphisms (SNPs). Substantial efforts are required in selecting the most informative cases from a large collection of affected individuals in order to maximize the power of the study, while taking into consideration study cost. In this article, we applied and extended three case-selection strategies that use allele-sharing information method for families with multiple affected offspring to select most informative cases using additional information on disease severity. Our results revealed that most significant associations, as measured by the lowest p-values, were obtained from a strategy that selected a case with the most allele sharing with other affected sibs from linked families ("linked-best"), despite reduction in sample size resulting from discarding unlinked families. Moreover, information on disease severity appears to be useful to improve the ability to detect associations between markers and disease loci.

Alleles↗