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multiple logistic regression models  (STATA Corporation)


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    STATA Corporation multiple logistic regression models
    Multiple Logistic Regression Models, supplied by STATA Corporation, used in various techniques. Bioz Stars score: 99/100, based on 47697 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/multiple logistic regression models/product/STATA Corporation
    Average 99 stars, based on 47697 article reviews
    multiple logistic regression models - by Bioz Stars, 2026-05
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    Prediction of CDPS and the correlation <t>between</t> <t>proteomics</t> and clinical characteristics. A . Heatmap of the correlation among expression of co-expression protein modules, expression of CDPS key proteins and clinical characteristics (IFX, response to infliximab; UST, response to ustekinumab; PS, psoriasis; NEUT, neutrophils; CRP, C-reactive protein; WBC, white blood cell; ESR, erythrocyte sedimentation rate; ALB, albumin; SES-CD, simple endoscopic score for Crohn's Disease); ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. B . Heatmap of correlation between immune cell infiltration and expression of co-expression modules and CDPS key proteins; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. C . Box plot of expression of co-expression modules in response (R) and non-response (NR) group (UST, ustekinumab; IFX, infliximab); UST (NR) n = 6, UST (R) n = 11; IFX (NR) n = 13, IFX (R) n = 6, Wilcoxon rank-sum test, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. D . Box plot of level of immune cells infiltration in response (R) and non-response (NR) group (UST: ustekinumab; IFX, infliximab); UST (NR) n = 6, UST (R) n = 11; IFX (NR) n = 13, IFX (R) n = 6, Wilcoxon rank-sum test, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. E . Heatmap of correlation between immune cells infiltration and each of the following: response to ustekinumab, response to infliximab, and the occurrence of psoriasis (IFX, response to infliximab; UST, response to ustekinumab; PS, psoriasis); ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. F . ROC curves of prediction models (validation group) for the likelihood of achieving an endoscopic response by intestinal mucosa proteomics; activated CD8 T cell AUC: 0.675 (95% CI: 0.333–1.000), turquoise AUC: 0.750 (95% CI: 0.500–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000). G . ROC curves of prediction models (validation group) for the likelihood of achieving an endoscopic response by body fluids proteomics; HGFAC (plasma) AUC: 0.780 (95% CI: 0.333–1.000), HGFAC (urine) AUC: 0.780 (95% CI: 0.333–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000). H . ROC curves of prediction models (validation group) for likelihood of the development of CDPS constructed using selected features by <t>lasso</t> regression; turquoise AUC: 0.960 (95% CI: 0.750–1.000), KRT7 AUC: 0.622 (95% CI: 0.333–1.000), HGFAC (plasma) AUC: 0.750 (95% CI: 0.500–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000).
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    Prediction of CDPS and the correlation between proteomics and clinical characteristics. A . Heatmap of the correlation among expression of co-expression protein modules, expression of CDPS key proteins and clinical characteristics (IFX, response to infliximab; UST, response to ustekinumab; PS, psoriasis; NEUT, neutrophils; CRP, C-reactive protein; WBC, white blood cell; ESR, erythrocyte sedimentation rate; ALB, albumin; SES-CD, simple endoscopic score for Crohn's Disease); ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. B . Heatmap of correlation between immune cell infiltration and expression of co-expression modules and CDPS key proteins; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. C . Box plot of expression of co-expression modules in response (R) and non-response (NR) group (UST, ustekinumab; IFX, infliximab); UST (NR) n = 6, UST (R) n = 11; IFX (NR) n = 13, IFX (R) n = 6, Wilcoxon rank-sum test, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. D . Box plot of level of immune cells infiltration in response (R) and non-response (NR) group (UST: ustekinumab; IFX, infliximab); UST (NR) n = 6, UST (R) n = 11; IFX (NR) n = 13, IFX (R) n = 6, Wilcoxon rank-sum test, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. E . Heatmap of correlation between immune cells infiltration and each of the following: response to ustekinumab, response to infliximab, and the occurrence of psoriasis (IFX, response to infliximab; UST, response to ustekinumab; PS, psoriasis); ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. F . ROC curves of prediction models (validation group) for the likelihood of achieving an endoscopic response by intestinal mucosa proteomics; activated CD8 T cell AUC: 0.675 (95% CI: 0.333–1.000), turquoise AUC: 0.750 (95% CI: 0.500–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000). G . ROC curves of prediction models (validation group) for the likelihood of achieving an endoscopic response by body fluids proteomics; HGFAC (plasma) AUC: 0.780 (95% CI: 0.333–1.000), HGFAC (urine) AUC: 0.780 (95% CI: 0.333–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000). H . ROC curves of prediction models (validation group) for likelihood of the development of CDPS constructed using selected features by lasso regression; turquoise AUC: 0.960 (95% CI: 0.750–1.000), KRT7 AUC: 0.622 (95% CI: 0.333–1.000), HGFAC (plasma) AUC: 0.750 (95% CI: 0.500–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000).

    Journal: eBioMedicine

    Article Title: Significance of integrated clinical and proteomic characteristics analysis for pathogenesis and management of Crohn's disease with concomitant psoriasis

    doi: 10.1016/j.ebiom.2025.105981

    Figure Lengend Snippet: Prediction of CDPS and the correlation between proteomics and clinical characteristics. A . Heatmap of the correlation among expression of co-expression protein modules, expression of CDPS key proteins and clinical characteristics (IFX, response to infliximab; UST, response to ustekinumab; PS, psoriasis; NEUT, neutrophils; CRP, C-reactive protein; WBC, white blood cell; ESR, erythrocyte sedimentation rate; ALB, albumin; SES-CD, simple endoscopic score for Crohn's Disease); ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. B . Heatmap of correlation between immune cell infiltration and expression of co-expression modules and CDPS key proteins; ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. C . Box plot of expression of co-expression modules in response (R) and non-response (NR) group (UST, ustekinumab; IFX, infliximab); UST (NR) n = 6, UST (R) n = 11; IFX (NR) n = 13, IFX (R) n = 6, Wilcoxon rank-sum test, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. D . Box plot of level of immune cells infiltration in response (R) and non-response (NR) group (UST: ustekinumab; IFX, infliximab); UST (NR) n = 6, UST (R) n = 11; IFX (NR) n = 13, IFX (R) n = 6, Wilcoxon rank-sum test, ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. E . Heatmap of correlation between immune cells infiltration and each of the following: response to ustekinumab, response to infliximab, and the occurrence of psoriasis (IFX, response to infliximab; UST, response to ustekinumab; PS, psoriasis); ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001. F . ROC curves of prediction models (validation group) for the likelihood of achieving an endoscopic response by intestinal mucosa proteomics; activated CD8 T cell AUC: 0.675 (95% CI: 0.333–1.000), turquoise AUC: 0.750 (95% CI: 0.500–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000). G . ROC curves of prediction models (validation group) for the likelihood of achieving an endoscopic response by body fluids proteomics; HGFAC (plasma) AUC: 0.780 (95% CI: 0.333–1.000), HGFAC (urine) AUC: 0.780 (95% CI: 0.333–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000). H . ROC curves of prediction models (validation group) for likelihood of the development of CDPS constructed using selected features by lasso regression; turquoise AUC: 0.960 (95% CI: 0.750–1.000), KRT7 AUC: 0.622 (95% CI: 0.333–1.000), HGFAC (plasma) AUC: 0.750 (95% CI: 0.500–1.000), multi-omics model AUC: 0.830 (95% CI: 0.500–1.000).

    Article Snippet: Feature selection for the faecal proteomics data was performed using the least absolute shrinkage and selection operator (LASSO) logistic regression model.

    Techniques: Expressing, Sedimentation, Biomarker Discovery, Clinical Proteomics, Construct