Publication Details

AFRICAN RESEARCH NEXUS

SHINING A SPOTLIGHT ON AFRICAN RESEARCH

medicine

Pathologic Assessment After Neoadjuvant Chemotherapy for NSCLC: Importance and Implications of Distinguishing Adenocarcinoma From Squamous Cell Carcinoma

Journal of Thoracic Oncology, Volume 14, No. 3, Year 2019

Introduction: Major pathologic response after neoadjuvant chemotherapy (NAC) for NSCLC has been defined as 10% or less residual viable tumor without distinguishing between histologic types. We sought to investigate whether the optimal cutoff percentage of residual viable tumor for predicting survival differs between lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC). Methods: Tumor slides from 272 patients treated with NAC and surgery for clinical stage II-III NSCLC (ADC, n = 192; SCC, n = 80) were reviewed. The optimal cutoff percentage of viable tumor for predicting lung cancer–specific cumulative incidence of death (LC-CID) was determined using maximally selected rank statistics. LC-CID was analyzed using a competing-risks approach. Overall survival was evaluated using Kaplan-Meier methods and Cox proportional hazard analysis. Results: Patients with SCC had a better response to NAC (median percentage of viable tumor: SCC versus ADC, 40% versus 60%; p = 0.027). Major pathologic response (≤10% viable tumor) was observed in 26% of SCC cases versus 12% of ADC cases (p = 0.004). The optimal cutoff percentage of viable tumor for LC-CID was 10% for SCC and 65% for ADC. On multivariable analysis, viable tumor 10% or less was an independent factor for better LC-CID (p = 0.035) in patients with SCC; in patients with ADC, viable tumor 65% or less was a factor for better LC-CID (p = 0.033) and overall survival (p = 0.050). Conclusions: In response to NAC, the optimal cutoff percentage of viable tumor for predicting survival differs between ADC and SCC. Our findings have implications for the pathologic assessment of resected specimens, especially in upcoming clinical trials design.
Statistics
Citations: 76
Authors: 11
Affiliations: 5
Identifiers
Research Areas
Cancer
Environmental
Health System And Policy
Study Design
Cohort Study