Clinical Relevance of Pathologic Regression IN Lymph Node for Locally Advanced Rectal Cancer

This large-scale, multi-center cohort study investigates the clinical significance of Pathologic Regression in lymph nodes (LNs) of patients with Locally Advanced Rectal Cancer (LARC) following Neoadjuvant Chemoradiotherapy (NCRT). Additionally, it compares the efficacy of diverse NCRT regimens in achieving pathologic regression and improving survival outcomes.

Study Design Type: Retrospective and prospective observational cohort study. Setting: Multi-center collaboration across 14 academic and community hospitals. Timeframe: Data from patients treated between 2014 and 2025 will be analyzed, with prospective follow-up ongoing until 2026.

Primary Objectives

Clarify the clinical significance of tumor regression in LN:

Define MPR thresholds for both primary tumor (e.g., ≤10% residual viable tumor) and lymph nodes (e.g., complete LN regression [ypN-Reg+] versus residual LN disease [ypN+]).

Correlate MPR status in the primary tumor and LNs with long-term outcomes:

Primary endpoints: Progression-Free Survival (PFS), Overall Survival (OS). Secondary endpoints: Local recurrence rate, distant metastasis-free survival.

Compare NCRT regimens:

Evaluate differences in MPR rates and survival outcomes between fluoropyrimidine-based, oxaliplatin-containing, and immunotherapy-augmented NCRT protocols.

Assess the impact of radiation dose escalation (e.g., 50.4 Gy vs. 45 Gy) on pathologic regression.

Study Population

Inclusion criteria

Adults (≥18 years) with histologically confirmed LARC (clinical stage II-III). Completion of NCRT followed by total mesorectal excision (TME). Availability of standardized pathologic reports and digitized whole-slide images (WSIs) for both primary tumor and LNs.

Exclusion criteria

Metastatic disease at diagnosis. Incomplete NCRT or surgical resection. Data Collection

Clinical Variables:

Demographics, NCRT regimen (drugs, doses, duration), surgical complications, adjuvant therapy, recurrence patterns.

Pathologic Variables:

Primary tumor: Residual viable tumor percentage, necrosis extent, tumor-infiltrating lymphocyte (TLS) density.

Lymph nodes: Regression grading (ypN-Reg+/-), number of regressed vs. metastatic LNs.

AI-driven quantitative analysis: Necrosis-to-tumor ratio (NECR-TD), TLS-to-necrosis ratio (T/NR), and spatial distribution of regressive features (Figure S2).

Imaging and Biomarkers:

Pre-treatment MRI-based tumor staging, post-treatment radiomic features (if available).

Statistical Analysis

Survival Analysis:

Kaplan-Meier curves and multivariable Cox regression to identify predictors of DFS/OS, adjusting for age, stage, and treatment regimen.

Subgroup analysis of LN regression (ypN-Reg+ vs. ypN-Reg-) in patients with ypN0 status.

Comparative Effectiveness:

Propensity score matching to balance baseline characteristics across NCRT regimens.

Meta-analysis of pooled multi-center data to assess heterogeneity in treatment effects.

Machine Learning:

Develop prognostic models integrating MPR status, histopathologic parameters, and clinical variables.

Ethical Considerations Approved by the Institutional Review Boards (IRBs) of all participating centers Innovation and Impact

Dual Focus on Primary Tumor and LNs:

First study to evaluate MPR thresholds simultaneously in primary tumor and LNs, addressing their independent prognostic roles.

Translational Insights:

Link LN regression to systemic immune responses (e.g., abscopal effect) and molecular heterogeneity between primary and metastatic sites.

Clinical Utility:

Provide evidence for standardizing MPR definitions in LARC and optimizing NCRT regimens based on tumor biology.

Inclusion criteria

• Adults (≥18 years) diagnosed with locally advanced rectal adenocarcinoma (clinical stage II-III).

Completion of NCRT followed by curative-intent surgery. Availability of pre- and post-treatment histopathologic data, including standardized regression grading and digitized whole-slide images (WSIs).

Exclusion criteria

• distant Metastatic disease at diagnosis. Incomplete clinical or pathologic records.