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[Introduction] To explore the gene-based logistic kemel-machine regression model and its application in genome-wide association study (GWAS).Using the simulated genome-wide singlenucleotide polymorphism (SNPs) genotypes data,we proposed a practical statistical analysis strategynamed ‘ the logistic kernel-machine regression model',based on the gene levels to assess the association between genetic variations and complex diseases.The results from simulation showed that the P value of genes in related diseases was the smallest among all the genes.The results of simulation indicated that not only it could borrow information from different SNPs that were grouped in genes and reducing the degree of freedom through hypothesis testing,but could also incorporate the covariate effects and the complex SNPs interactions.The gene-based logistic kernel-machine regression model seemed to have certain statistical power for testing the association between genetic genes and diseases in GWAS.
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<p><b>OBJECTIVE</b>To explore the risk factors on relapsing tuberculosis related to smear positive pulmonary tuberculosis which had been cured for five years.</p><p><b>METHODS</b>Patients with smear positive pulmonary tuberculosis registered in 1995 from ten countries in Hubei province were studied and logistic regression was used for data analysis.</p><p><b>RESULTS</b>The 5-year relapse rate of smear positive pulmonary tuberculosis was 3.85 percent. Risk factors related to relapse would include being non-modeled county, negative smear after treated for three months, the class of retreatment, management of non-DOTS, method of chemotherapy and patients that did not get treated by the tuberculosis institute, with odds ratios of 0.15, 4.62, 3.68, 5.88 and 6.47, respectively.</p><p><b>CONCLUSION</b>Effect standard, regulation DOTS and the centralized management measure might have had effects on decreasing the relapse rate.</p>