10.3390/polym8030084

Vollständiger Abstract

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The expansion of neoadjuvant immune checkpoint blockade, chemoimmunotherapy, and targeted therapies in oncogene-driven tumors is reshaping the management of resectable non-small cell lung cancer (NSCLC). Major pathologic response (MPR) and pathologic complete response (pCR), defined respectively as 10% or less residual viable tumor (RVT) within the primary tumor bed and the complete absence of viable tumor in both the resected primary tumor and sampled regional lymph nodes, have become widely adopted early efficacy endpoints. Both are consistently associated with favorable survival outcomes at the patient level, although their validity as trial-level surrogates for long-term outcomes remains incompletely established. Accurate pathologic response assessment requires rigorous standardization of gross specimen handling, tumor bed sampling, and microscopic quantification of viable tumor, necrosis, and stroma. International recommendations have improved methodological harmonization, and reproducibility studies have demonstrated good interobserver agreement when standardized protocols are applied. Increasing evidence also indicates that RVT behaves as a continuous prognostic variable and that integration of primary-tumor and nodal response may improve postoperative risk stratification. Beyond quantification of RVT alone, additional histologic characteristics of the residual tumor, together with stromal and immune therapy-related features, may provide complementary prognostic information. Digital pathology and artificial intelligence may support more reproducible quantitative assessment, whereas circulating tumor DNA-based molecular residual disease evaluation may capture systemic risk not represented by the resection specimen. These emerging approaches remain investigational and require prospective validation. This review critically examines the methodological standardization, biological interpretation, and prognostic validation of pathologic response in resectable NSCLC, and discusses future strategies integrating histopathologic, digital, and molecular variables into post-neoadjuvant risk assessment.

Abstract: PubMed · Datensatz