Multiple imputation procedures allow the rescue of missing data: An application to determine serum tumor necrosis factor (TNF) concentration values during the treatment of rheumatoid arthritis patients with anti-TNF therapy

Longitudinal studies aimed at evaluating patients clinical response to specific therapeutic treatments are frequently summarized in incomplete datasets due to missing data. Multivariate statistical procedures use only complete cases, deleting any case with missing data. MI and MIANALYZE procedures of the SAS software perform multiple imputations based on the Markov Chain Monte Carlo method to replace each missing value with a plausible value and to evaluate the efficiency of such missing data treatment. The objective of this work was to compare the evaluation of differences in the increase of serum TNF concentrations depending on the ¡308 TNF promoter genotype of rheumatoid arthritis (RA) patients receiving anti-TNF therapy with and without multiple imputations of missing data based on mixed models for repeated measures. Our results indicate that the relative efficiency of our multiple imputation model is greater than 98 percent and that the related inference was significant (p-value < 0.001). We established that under both approaches serum TNF levels in RA patients bearing the G/A ¡308 TNF promoter genotype displayed a significantly (p-value < 0.0001) increased ability to produce TNF over time than the G/G patient group, as they received successively doses of anti-TNF therapy.

Genetic polymorphism at position-308 in the promoter region of the tumornecrosis factor (TNF): implications of its allelic distribution on susceptibility or resistance to diseases in the Chilean population

Several single-nucleotide polymorphisms have been identified in the human TNF gene promoter. The polymorphism at position-308 (TNF-308), which involves substituting G for A and designing the TNF2 allele, leads to a higher rate of TNF gene transcription than the wild-type TNF1 allele in in vitro expression studies. It has also been linked to increased susceptibility to a variety of illnesses. Using PCR-RFLP analysis we detected significant differences in the TNF-308 genotypes of Chilean and other populations. We conclude that there is a gradient in the distribution of the TNF2 allele according to ethnicity; we have also hypothesized that populations bearing a higher proportion of the TNF2 allele may have an increased predisposition toward or incidence of several chronic metabolic, degenerative, inflammatory and autoimmune diseases.