
Faculty, Staff and Student Publications
Publication Date
1-1-2024
Journal
Modern Pathology
Abstract
Neoadjuvant treatment of non-small cell lung cancer challenges the traditional processing of pathology specimens. Induction therapy before resection allows evaluation of the efficacy of neoadjuvant agents at the time of surgery. Many clinical trials use pathologic tumor response, measured as major pathologic response (MPR, ≤10% residual viable tumor [RVT]) or complete pathologic response (CPR, 0% RVT) as a surrogate of clinical efficacy. Consequently, accurate pathologic evaluation of RVT is crucial. However, pathologic assessment has not been uniform, which is particularly true for sampling of the primary tumor, which instead of the traditional processing, requires different tissue submission because the focus has shifted from tumor typing alone to RVT scoring. Using a simulation study, we analyzed the accuracy rates of %RVT, MPR, and CPR of 31 pretreated primary lung tumors using traditional grossing compared with the gold standard of submitting the entire residual primary tumor and identified the minimum number of tumor sections to be submitted to ensure the most accurate scoring of %RVT, MPR, and CPR. Accurate %RVT, MPR, and CPR calls were achieved in 52%, 87%, and 81% of cases, respectively, using the traditional grossing method. Accuracy rates of at least 90% for these parameters require either submission of all residual primary tumor or at least 20 tumor sections. Accurate %RVT, MPR, and CPR scores cannot be achieved with traditional tumor grossing. Submission of the entire primary tumor, up to a maximum of 20 sections, is required for the most accurate reads.
Keywords
Humans, Lung Neoplasms, Carcinoma, Non-Small-Cell Lung, Neoadjuvant Therapy, Lung, Treatment Outcome, NSCLC, neoadjuvant treatment, pathologic response, tumor processing, MPR, CPR
DOI
10.1016/j.modpat.2023.100353
PMID
37844869
PMCID
PMC10841500
PubMedCentral® Posted Date
1-1-2025
PubMedCentral® Full Text Version
Author MSS
Published Open-Access
yes
Included in
Bioinformatics Commons, Biomedical Informatics Commons, Genetic Phenomena Commons, Medical Genetics Commons, Oncology Commons