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Hoffmann, R. A wiki for the life sciences where authorship matters. Nature Genetics (2008)
 
MeSH Review

Logistic Models

 
 
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Disease relevance of Logistic Models

 

Psychiatry related information on Logistic Models

 

High impact information on Logistic Models

 

Chemical compound and disease context of Logistic Models

  • (a) A logistic regression analysis showed that a formulation of time was an independent statistically significant variable (P = 0.025) in addition to the total number of sites of metastasis (P less than 0.001) and pretreatment values of human chorionic gonadotropin (P less than 0.001) and lactate dehydrogenase (P = 0.002) [16].
  • There was a trend to higher tumor response rates in patients treated with MTX before 5-FU (45% v 33% overall; 65% v 39% in patients with previously untreated head and neck cancer), but these differences were not significant, either by chi-square test or by multivariate stepwise logistic regression [17].
  • No significant association was observed between either short-term (1-14 years) or long-term (15+ years) menthol use and lung cancer in logistic regression analyses adjusting for covariates [18].
  • A multivariate logistic regression analysis of the confirmed complete remissions on pentostatin showed the following factors to be important for achieving a complete remission: high hemoglobin level (two-tailed P = .024), young age (P = .0085), and no or little splenomegaly (P = .0029) [19].
  • A logistic regression model, validated by Monte Carlo simulation, identified 3 factors, proteinuria, elevated ESR, and low carbon monoxide diffusing capacity, that in combination, had an accuracy of >80% in predicting mortality [20].
 

Biological context of Logistic Models

 

Anatomical context of Logistic Models

  • Postmenopausal estrogen replacement was a significant independent protective factor for coronary artery disease in a multivariate logistic regression model (P = 0.037) [26].
  • Among nine clinical, 20 hemodynamic, and six procedural variables, stepwise logistic regression analysis selected the following as independent predictors of AS: smaller increases in valve area (p = 0.01) after PMV, absence of previous surgical commissurotomy (p = 0.02), mitral valve calcification (p = 0.02), and smaller left atria (p = 0.06) [27].
  • In a forward stepwise Cox logistic regression analysis, clinical stage IIIB or greater (hazard ratio of 4.5, P <.001), pathologic involvement of four or more lymph nodes (hazard ratio of 2.7, P =.008), and no use of tamoxifen (hazard ratio of 3.9, P =.027) independently predicted for LRR [28].
  • G-CSF accelerated recovery to > or = 1,000 neutrophils (P < .0001; median, 34 days for FA, 21 days for FLAG), but logistic regression provided no evidence that the CR rate was higher with FLAG than with FA (P = .50), with unadjusted CR rates of 63% and 53%, respectively [29].
  • The logistic regression analysis presented in this paper illustrates that those individuals who showed large increases in retinol, riboflavin, and zinc blood levels were more likely to have a histologically normal esophagus at the end of the trial [30].
 

Associations of Logistic Models with chemical compounds

 

Gene context of Logistic Models

  • Stepwise logistic-regression analysis showed that the association could be explained by either DRB1 or DQA1 but not by DQB1 [36].
  • Logistic regression analysis of SNP data across GRIN2A and ABAT showed a trend toward haplotypic differences between cases and controls [37].
  • Finally, these results were also consistent with the results from the conditional logistic regression, which confirmed the interaction between GABRA4 and GABRB1 (odds ratio = 2.9 for interaction term; P = .002) [38].
  • Multiple logistic regression demonstrated an increased risk of AMD in carriers of the G allele at TLR4 residue 299 (odds ratio=2.65, P=0.025), but lack of an independent effect by T399I variant [39].
  • Multivariate logistic regression analysis showed that engraftment was associated with marrow matched at HLA-A, HLA-B, and DRB1; higher cell dose; younger recipient; male recipient; and recipient from a non-African American ethnic group [40].
 

Analytical, diagnostic and therapeutic context of Logistic Models

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