Skip to main content
. 2023 Dec 4;21:878. doi: 10.1186/s12967-023-04670-x

Table 2.

Identification of meaningful metabolites using XGBoost

Putative identification HMBD ID m/z Formula Feature importance Pancreatic cancer incidence/control
Eicosa-11,14,17-trienoic acid HMDB0244373 306.2560 C20H34O2 6.0 1.826
Kynurenic acid HMDB0000715 189.0429 C10H7NO3 6.0 1.069
γ-Glutamyl tyrosine HMDB0011741 310.1166 C14H18N2O6 5.0 1.230
N(6)-Methyllysine HMDB0002038 160.1214 C7H16N2O2 5.0 0.875
LysoPE(18:0/0:0) HMDB0011130 481.3170 C23H48NO7P 5.0 1.040
Trans-3'-hydroxy cotinine HMDB0304504 192.0901 C10H12N2O2 4.0 1.130
Palmitic amide HMDB0012273 255.2563 C16H33NO 4.0 0.915
L-Leucine HMDB0000687 131.0949 C6H13O2 4.0 1.144
Adipic acid HMDB0000448 146.0581 C6H10O4 4.0 0.795
9-Decenoylcarnitine HMDB0013205 313.2254 C17H31NO4 4.0 0.794
5α-Pregnane-3,20-dione HMDB0003759 316.2398 C21H32O2 4.0 0.845

Feature Importance values ​​ > 4.0 are listed in Table 2. Feature Importance value was obtained from the XGBoost model of the training set (n = 209) [accuracy, 0.952; precision, 0.985; AUC 0.998], selecting discriminant metabolites related to pancreatic cancer incidence. The pancreatic cancer incidence/Control value was calculated using the relative abundance of each metabolite