Treatment attrition between lines of therapy and its impact on outcomes for well-differentiated neuroendocrine tumors in British Columbia

不列颠哥伦比亚省分化良好的神经内分泌肿瘤患者治疗方案之间的治疗中断及其对预后的影响

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Abstract

BACKGROUND: Neuroendocrine neoplasms are uncommon malignancies with variable prognosis. With a growing number of available therapies and recent data supporting earlier initiation of radioligand therapy, we aimed to characterize attrition between lines of therapy to inform treatment sequencing and establish baseline assumptions for future health technology assessments. PATIENTS AND METHODS: In this retrospective chart review, patients with metastatic gastroenteropancreatic neuroendocrine tumors (NETs) who received one or more systemic therapies from January 2010 to December 2023 were reviewed. The primary endpoint was attrition between treatment lines. Logistic regression model was used to identify predictors of attrition. RESULTS: Among 234 patients, 65 (28%) had pancreatic NETs (pNETs) and 169 (72%) had extra-pancreatic gastrointestinal NETs (ep-GI-NETs); median age at diagnosis was 65 years. Maximum number of treatment lines was six for pNETs and four for ep-GI-NETs. First-to-second-line attrition rates were 22% [95% confidence interval (CI) 13% to 36%] and 34% (95% CI 25% to 44%) for pNETs and ep-GI-NETs, respectively. Somatostatin analogs were the preferred first line in 194 patients (83%). Peptide receptor radionuclide therapy was administered to 13 pNETs (20%) and 42 ep-GI-NETs (25%). Median first-line progression-free survival (PFS) was 8.8 months and 26.1 months for pNETs and ep-GI-NETs, respectively. Patients treated in the latter cohort (2021-2023) had a lower risk of attrition compared with those in the earlier cohort (2010-2020) (odds ratio 0.38, 95% CI 0.14-0.94, P = 0.046). CONCLUSIONS: Despite longer first-line PFS, patients with ep-GI-NETs faced higher attrition rates. These findings emphasize the need to prioritize the most effective therapies early during treatment sequencing to ensure patients are exposed to the most active agents.

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