Cytoreductive Surgery for Metastatic Gastrointestinal Stromal Tumors Treated With Tyrosine Kinase Inhibitors: A 2-institutional Analysis

酪氨酸激酶抑制剂治疗转移性胃肠道间质瘤的细胞减灭术:一项两中心分析

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Abstract

OBJECTIVE: To refine treatment recommendations for patients with metastatic gastrointestinal stromal tumors (GISTs) treated with tyrosine kinase inhibitors (TKIs) and surgery. BACKGROUND: Early reports suggested that patients with metastatic GIST responding to TKIs treated with surgery may have favorable outcomes. However, identification of prognostic factors was limited by small cohorts. METHODS: Progression-free survival (PFS) and overall survival (OS) from time of surgery and from start of initial TKI was determined. Multivariate analysis was conducted on all patients undergoing GIST metastasectomy between 2001 and 2014 at 2 institutions. RESULTS: We performed 400 operations on 323 patients with metastatic GIST on TKIs. Radiographic response at time of surgery was classified as responsive disease (RD, n = 64, 16%), stable disease (SD, n = 100, 25%), unifocal progressive disease (UPD, n = 132, 33%), and multifocal progressive disease (MPD, n = 104, 26%). For patients on imatinib before surgery, radiographic response was predictive of PFS from time of surgery (RD 36 months, SD 30 months, UPD 11 months, MPD 6 months; P < 0.001) and from imatinib initiation (RD 71 months, SD 51 months, UPD 47 months, MPD 33 months; P < 0.001). Radiographic response was predictive of OS from time of surgery (RD not reached, SD 110 months, UPD 59 months, MPD 24 months; P < 0.001), and from imatinib initiation (RD not reached, SD 144 months, UPD 105 months, MPD 66 months; P = 0.005). Radiographic response was not predictive of PFS/OS for patients on sunitinib. Metastatic mitotic index ≥5/50 HPF, MPD, and R2 resection were prognostic of worse PFS/OS; primary mutation was not. CONCLUSIONS: Surgery in metastatic GIST patients in the absence of MPD on imatinib is associated with outcomes at least comparable with second-line sunitinib and may be considered in select patients.

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