The Inflammation-Based Index Can Predict Response and Improve Patient Selection in NETs Treated With PRRT: A Pilot Study

Abstract

Background\nPeptide receptor radionuclide therapy (PRRT) is an effective treatment of certain patients with metastatic neuroendocrine tumors (NETs). Tumor response is highly variable; no biomarker in clinical practice has been demonstrated to reliably predict outcome. The inflammation-based index (IBI), derived from serum C-reactive protein and albumin levels, predicts survival and response to treatment in patients in several cancer types and was therefore explored in this setting.\n\n\nMaterials and Methods\nClinico-pathological data from patients undergoing PRRT for metastatic NETs were collected at baseline and during treatment. The primary endpoint was progression-free survival (PFS) with a secondary endpoint of overall survival (OS). Cox regression analysis tested associations between baseline variables and their dynamic changes and PFS and OS. Decision curve analysis (DCA) was used to determine the net benefit associated with a treatment strategy determined by the baseline IBI and nonresponse to PRRT.\n\n\nResults\nFifty-five patients were recruited. Baseline IBI > 0 was associated with inferior PFS (hazard ratio, 14.2; 95% CI, 5.25 to 38.5; P < 0.001) and OS (P < 0.001). Multivariate analysis confirmed an independent association between IBI and PFS (P = 0.001). DCA indicated a net clinical benefit at risk thresholds between 0.03 and 0.58.\n\n\nConclusion\nBaseline IBI score and its dynamic change through treatment are associated with both PFS and OS. At a risk threshold equivalent to the currently accepted rate of nonresponse to therapy, implementation of this easily derived score could avoid a substantial number of futile treatments. These findings should be validated in additional independent cohorts.