Supplementary Tables 1-12 and Figures 1-3 from The Doylestown Algorithm: A Test to Improve the Performance of AFP in the Detection of Hepatocellular Carcinoma
Year: 2023
Type: supplementary-materials
Abstract: Data description and detailed statistical information regarding model development. Supplementary Table 1. Patient information on samples from the University of Michigan. Supplementary Table 2. Patient information on samples from HALT-C. Supplementary Table 3. Patient information on samples from EDRN. Supplementary Table 4. Patient information on samples from Thomas Jefferson University. Supplementary Table 5. Patient information on samples from the University of Texas Southwestern Medical Center. Supplementary Table 6. Odds ratios for each predictor in univariate and multivariate logistic regressions. Supplementary Table 7. Indices of goodness-of-fit and apparent validation of candidate logistic regression models. Supplementary Table 8. Performance of leave one out cross validation (LOOCV). Supplementary Table 9. Cross Validation of bootstrap method. Supplementary Table 10. AUCs and IDIs from 3-fold Cross-Validation. Supplementary Table 11. Summary statistics of Doylestown model. Supplementary Table 12. Comparison of logistic regression, classification and regression tree (CART) and conditional inference tree (CTREE). Supplementary Figure 1. The distribution of AFP in each data set by cases and controls: Supplementary Figure 2. Quartiles for AFP in the individual patient sets. Supplementary Figure 3. Histogram of predictions and observe occurrence proportion of HCC for the top 4 models.
Language: English
Subfield: Hepatology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
OpenAlex ID: W4362484361