Background: Several studies have investigated the efficacy of neoadjuvant imatinib treatment (NAT) for gastrointestinal stromal tumors (GISTs); however, research on pathological regression and the prognostic factors affecting survival is limited. Thus, this study aimed to examine pathological regression and assess the prognostic factors associated with survival in GIST patients who received NAT.
Methods: The data of patients who received NAT for primary GISTs with a tumor size larger than 5.0 cm from January 2007 to December 2022 were retrospectively reviewed. Five grades of pathological regression were proposed. A survival analysis was conducted using the Kaplan-Meier method, and a Cox proportional hazards model was used to identify the independent prognostic factors.
Results: In total, 80 patients were enrolled in the study, of whom 54 (67.5%) were men and 26 (32.5%) were women. The median age of the patients was 60 (range, 39-75) years. The median duration of NAT was 7.0 (range, 0.4-23) months, and the median tumor size decreased from 9.4 to 6.2 cm. Pathological regression was found to be significantly correlated with a decrease in both tumor size (P=0.008) and tumor density (P<0.001). With a median follow-up time of 69 months, the estimated 5-year progression-free survival (PFS) and overall survival (OS) rates were 86.4% and 95.4%, respectively. The multivariate analysis identified pre-neoadjuvant tumor size [hazard ratio (HR) =5.263, 95% confidence interval (CI): 1.552-17.849, P=0.008], tumor location (HR =3.522, 95% CI: 1.161-10.683, P=0.03), mitotic count (HR =3.647, 95% CI: 1.070-12.428, P=0.04), and post-operative imatinib treatment (HR =0.124, 95% CI: 0.027-0.571, P=0.007) as independent prognostic factors.
Conclusions: Pre-neoadjuvant tumor size, tumor location, mitotic count, and post-operative imatinib treatment were identified as prognostic factors for GIST patients who received NAT. Pathological regression was associated with radiological changes in the tumor, but it was not correlated with long-term patient prognosis.
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