Modeling antibiotic resistance to project future rates: quinolone resistance in Escherichia coli.

While the development of resistance to a new antibiotic is expected, the time course and degree of resistance that will develop are uncertain. Some best projections of the future extent of resistance can be highly impactful for activities, such as antimicrobial development, that require significant lead time. We focus on the surge among hospital isolates in fluoroquinolone-resistant Escherichia coli and use data on resistance and consumption to explore and quantify trends in increasing resistance and their relationship to antibiotic use from 2001 to 2007. A mixed-effects logistic regression model produced a good fit to the observed resistance rates during this period in the United States and Europe. The model contained significant effects of time, consumption, and country on developing fluoroquinolone resistance in E. coli. There was a larger projected increase in resistance for high fluoroquinolone-consuming countries projected to 2013: 45% (95% confidence interval [CI]: 38%, 53%) for high consumers vs. 33% (95% CI: 25%, 41%) for low consumers. The model was also used to obtain regional projections of resistance that can be used by local prescribers. In order to better understand and predict trends in antimicrobial resistance, it is vital to implement and expand current surveillance systems.

Analysis of simulated data: evidence for genetic and environmental effects.

We approached the simulation as though it were an international study with similar but not identical information being collected from different populations. In keeping with this we analyzed one replicate from each population. Initially we examined the risk of disease in relatives of cases to determine whether the disease appeared to be "more genetic" in one population than in the others and we examined the evidence for environmental risk factors in each population. Nonparametric linkage analysis and transmission/disequilibrium testing (TDT) were used to search for loci linked to the disease in each population. Using these methods we identified several candidate regions for a susceptibility gene which on examination of the answers are explicable in terms of the underlying model.

Testing for contributions of mitochondrial DNA mutations to complex diseases.

Several complex disorders are suspected of being associated with mitochondrial DNA (mtDNA) mutations. We studied the statistical properties of a test based on proband-relative pairs to identify potential mtDNA mutation involvement in a complex disorder. The test compares the recurrence risk of relatives of probands along the mitochondrial lineage with that of relatives along the nonmitochondrial lineage. If mtDNA mutations are involved, the recurrence risk will be higher among relatives in the mitochondrial lineage. The form of the test is independent of the assumed models of inheritance and interaction of the nuclear autosomal mutations with mtDNA mutations. The power of the test, however, differs among the different models and by the type of proband-relative pairs used in the test. We considered heterogeneity models with and without phenocopies, a three-state heteroplasmic mtDNA transmission model, and a multiplicative epistasis model. Under the heterogeneity model, the power of the test increases as the relationship between the proband and the relative becomes more distant. Under the multiplicative epistasis model, the power of the test decreases as the relationship between the proband and the relative becomes more distant.

Estimation of vaccine efficacy in the presence of waning: application to cholera vaccines.

The authors present a nonparametric method for estimating vaccine efficacy as a smooth function of time from vaccine trials. Use of the method requires a minimum of assumptions. Estimation is based on the smoothed case hazard rate ratio comparing the vaccinated with the unvaccinated. The estimation procedure allows investigators to assess time-varying changes in vaccine-induced protection, such as those produced by waning and boosting. The authors use the method to reanalyze data from a vaccine trial of two cholera vaccines in rural Bangladesh. This analysis reveals the differential protection and waning effects for the vaccines as a function of biotype and age.

PIP: Vaccine efficacy (VE) is typically estimated by the equation VE = 1 minus relative risk (RR), where RR is based on a comparison of vaccinated and unvaccinated groups. However, since vaccine effects do not follow a simplified model such as an exponential decline in protection, estimation of a rate ratio for time-to-event data is difficult. This paper presents a method for nonparametrically estimating VE(t) = 1 - RR(t) from time-to-event data when the protective effects of a vaccine can wane or boost over time. The method, based on smoothing scaled residuals from a proportional hazards model, is then applied to a reanalysis of data from a trial in rural Bangladesh of two cholera vaccines. The placebo and vaccine curves should be roughly parallel for all time if there are no time-varying effects. Application to the data from Bangladesh confirmed this method provides reliable estimation and analysis of field data. The reanalysis revealed the differential protection and waning effects for the vaccines as a function of biotype and age.

Genome scanning for segments shared identical by descent among distant relatives in isolated populations.

In this paper, we address some of the statistical issues concerning false-positive rates that arise when the whole genome, or a portion thereof, is scanned in distantly related individuals, to search for a disease locus. We derive a method for correcting false-positive probabilities for the large number of comparisons that are performed when scanning a large portion of the genome. We consider both the idealized situation of a dense set of fully informative markers and the more realistic data-collection strategy of an initial scan at low resolution to identify promising areas, which then are typed with markers at high resolution. We also examine the accuracy of false-positive rates approximated using a conservative estimate of the separation distance between affected individuals in the current generation and the common ancestral couple. Calculation of false-positive rates when inbreeding is present in the pedigree also is considered.