Identifying high-risk candidates for prolonging progression-free survival in primary gastric carcinoma subject to “double invasion”: an analytical approach utilizing lasso-cox regression

We developed a Lasso-Cox regression-based nomogram to stratify PFS risk in gastric carcinoma patients with double invasion. While the model outperformed AJCC staging in training, validation cohort results highlight the need for further refinement. This tool holds potential for guiding tailored therapeutic strategies, though broader validation is warranted to confirm clinical applicability.