An optimized lymph node yield leads to better survival in colon cancer, but extended lymphadenectomy is not associated with survival benefits. Lymphatic mapping shows several colon cancers feature aberrant drainage pathways inducing local recurrence when not resected. Currently, different protocols exist for lymphatic mapping procedures. This meta-analysis assessed which protocol has the best capacity to detect tumor-draining and possibly metastatic lymph nodes. A systematic review was conducted according to PRISMA guidelines, including prospective trials with in vivo tracer application. The risk of bias was evaluated using the QUADAS-2 tool. Traced lymph nodes, total resected lymph nodes, and aberrant drainage detection rate were analyzed. Fifty-eight studies met the inclusion criteria, of which 42 searched for aberrant drainage. While a preoperative tracer injection significantly increased the traced lymph node rates compared to intraoperative tracing (30.1% (15.4, 47.3) vs. 14.1% (11.9, 16.5), p = 0.03), no effect was shown for the tracer used (p = 0.740) or the application sites comparing submucosal and subserosal injection (22.9% (14.1, 33.1) vs. 14.3% (12.1, 16.8), p = 0.07). Preoperative tracer injection resulted in a significantly higher rate of detected aberrant lymph nodes compared to intraoperative injection (26.3% [95% CI 11.5, 44.0] vs. 2.5% [95% CI 0.8, 4.7], p < 0.001). Analyzing 112 individual patient datasets from eight studies revealed a significant impact on aberrant drainage detection for injection timing, favoring preoperative over intraoperative injection (OR 0.050 [95% CI 0.010–0.176], p < 0.001) while indocyanine green presented itself as the superior tracer (OR 0.127 [95% CI 0.018–0.528], p = 0.012). Optimized lymphatic mapping techniques result in significantly higher detection of aberrant lymphatic drainage patterns and thus enable a personalized approach to reducing local recurrence.

Objective: We audited deployment readiness of an end-of-surgery postoperative infection model across clinically relevant subgroups and assessed mitigation of subgroup miscalibration. Materials and Methods: We analyzed out-of-fold predictions from 10 719 procedures (2014-2022) with 504 present-on-admission (POA)–coded postoperative infection events across recorded sex, age, and a clinical physiological-reserve proxy. We assessed discrimination, calibration, threshold-specific errors, and decision-curve net benefit, treating t = 0.10 as a reference anchor. We compared no recalibration with common and group-specific cross-fitted isotonic recalibration, evaluated a refit without the Synthetic Minority Oversampling Technique (SMOTE), and performed a temporal-holdout analysis. Results: Overall area under the receiver operating characteristic curve (AUROC) was 0.876, with similar sex-marginal discrimination in women and men (0.878 vs 0.875). Calibration-in-the-large was −1.02 overall, −0.86 in frail, and −1.34 in prefrail patients; the 6-event nonfrail stratum was not estimable. At t = 0.10, net benefit was positive in frail and negative in prefrail patients in the source cohort, but negative prefrail utility did not persist in the ascertainable-period (2018-2022) and temporal analyses. Common recalibration moved overall calibration-in-the-large from −1.020 to −0.007. Removing SMOTE shifted overall calibration but did not reduce the reserve gradient. Temporal-holdout AUROC was 0.851 with persistent overprediction. Present-on-admission coding was effectively absent before 2018; prevalence-dependent results were therefore additionally reported for the ascertainable 2018-2022 period, and ascertainment differed by physiological reserve. Discussion: Discrimination-only or sex-marginal evaluation would have missed deployment-relevant subgroup heterogeneity, while endpoint ascertainment affected prevalence-dependent interpretation. Conclusion: Joint subgroup evaluation can identify deployment-relevant limitations missed by aggregate metrics. Prospective validation with comparable outcome ascertainment remains necessary before clinical deployment.