Endoscopic ultrasonography lesion thickness predicts deep invasion in gastric cancer: Development and temporal validation of a preoperative model

Figure 1 Study flowchart of patient selection, cohort construction, and temporal validation. The development cohort included consecutive patients with biopsy-proven gastric adenocarcinoma who underwent preoperative endoscopic ultrasonography (EUS) and curative-intent gastrectomy at Sun Yat-sen University Cancer Center between January 2017 and December 2020 (screened, n = 600). After exclusion of patients with gastro-oesophageal junction carcinoma, indeterminate pathological diagnosis, incomplete EUS reports (especially missing lesion thickness), or receipt of neoadjuvant therapy before EUS, the final derivation cohort comprised 518 patients. The temporal validation cohort consisted of consecutive eligible patients from a later, non-overlapping calendar period (2021-2025) at the same institution, assembled using the same eligibility criteria; the final temporal validation cohort included 246 patients. The primary outcome in both cohorts was pathological stage dichotomised as pT1-2 vs ≥ pT3 on the resection specimen. The pre-specified uniformly shrunk model developed in the derivation cohort was applied to the temporal validation cohort without refitting. EUS: Endoscopic ultrasonography; SYSUCC: Sun Yat-sen University Cancer Center.

Figure 2 Association between endoscopic ultrasonography lesion thickness and pathological ≥ pT3. The upper panel shows the restricted cubic spline function for endoscopic ultrasonography lesion thickness (mm) from the multivariable logistic regression model, illustrating the adjusted relationship between thickness and the log odds of pathological ≥ pT3. The solid curve represents the point estimate and the shaded band indicates the 95% confidence interval. The P value for nonlinearity is reported on the plot. The vertical dashed red line marks the median lesion thickness in the cohort (10.1 mm). The lower panel displays the histogram of endoscopic ultrasonography lesion thickness values (frequency distribution) in the study population. EUS: Endoscopic ultrasonography.

Figure 3 Performance of the preoperative prediction model for pathological ≥ pT3 gastric cancer. A: Receiver-operating characteristic curve of the full multivariable logistic regression model in the development cohort (n = 518), with area under the receiver-operating characteristic curve and 95% confidence interval shown. The model includes endoscopic ultrasonography lesion thickness modelled with restricted cubic splines and routinely available clinical variables (Lauren classification, age, sex, tumour site, carcinoembryonic antigen, and carbohydrate antigen 19-9). The diagonal dashed line indicates no discrimination; B: Bootstrap calibration curve for the full model, comparing predicted probabilities with observed proportions of pathological ≥ pT3; the 45° line represents perfect calibration. Apparent performance is shown alongside the optimism-corrected calibration estimate; C: Decile-based calibration plot: Each point represents one decile of predicted risk, plotted as mean predicted probability (X-axis) against observed proportion of pathological ≥ pT3 (Y-axis), with point size reflecting group size. The reported slope and intercept are from logistic recalibration; D: Decision-curve analysis comparing net benefit across threshold probabilities (high-risk thresholds) for the full model vs a thickness-only model; “all” and “none” represent treat-all and treat-none strategies, respectively. AUC: Area under the receiver-operating characteristic curve; CI: Confidence interval.