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| Home > Publications database > Association of integrated biomarkers and progression-free survival prediction in patients with gastroenteropancreatic neuroendocrine tumors undergoing [177Lu]Lu-DOTA-TATE therapy |
| Home > Publications database > Association of integrated biomarkers and progression-free survival prediction in patients with gastroenteropancreatic neuroendocrine tumors undergoing [177Lu]Lu-DOTA-TATE therapy |
| Journal Article | DKFZ-2025-01196 |
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2025
Ivyspring
Wyoming, NSW
Abstract: Integrated biomarkers that predict survival in patients with gastroenteropancreatic neuroendocrine tumors (GEP-NET) receiving peptidereceptor radionuclide therapy (PRRT) are still limited. This study aims to identify predictors of progression-free survival (PFS) in patientswith GEP-NET undergoing two cycles of PRRT.Methods: This single-center retrospective study included 178 patients with GEP-NET (G1 and G2) who received at least twoconsecutive cycles of PRRT with [177Lu]Lu-DOTA-TATE and underwent somatostatin receptor (SSTR)-PET/CT before and aftertherapy. At baseline, Krenning score (KS) > 2, clinical, pathological and laboratory parameters were collected and correlated to PFS.Survival predictors were analyzed using univariate and multivariate models. For goodness-of-fit analysis, the Akaike information criterionand Harrell concordance index were determined. To determine the impact on the regression model the Wald-Test was performed.Results: In univariate analysis, KS 3 (vs. KS 4; HR, 2.02; 95% CI, 1.27–3.22; p = 0.012), Ki-67 > 5 % (HR, 2.00; 95% CI, 1.31–3.04; p =0.008), CgA > 200 ng/mL (HR, 1.77; 95% CI, 1.14–2.76; p = 0.027) and NSE > 35 ng/mL (HR, 2.37; 95% CI, 1.44–3.89; p < 0.008) weresignificantly associated with shorter PFS, with CgA providing the highest C-index (0.6). In multivariate analysis , KS 3 (vs. KS 4; HR, 1.94;95% CI, 1.17–3.21; p = 0.01), CgA > 200 ng/mL (HR, 1.76; CI, 1.08–2.87; p = 0.024), NSE > 35 ng/mL (HR, 1.98; 95% CI, 1.17–3.36; p =0.011), and Ki-67 > 5 % (HR, 1.89; 95% CI, 1.18–3.02; p = 0.008) were significantly associated with reduced PFS. Including KS intomultivariate analysis significantly improved the Cox regression model performance, as shown by a reduction in Akaike InformationCriterion (592/596) and an increase in concordance index (0.66/0.65). The Wald test for individual variables supported the significance ofboth Ki-67 (7.1) and KS (6.7) as independent predictors of PFS.Conclusions: NSE, CgA, KS and Ki-67 emerged as independent predictors of PFS in GEP-NET patients scheduled for two cycles of PRRT,thereby emphasizing the importance of integrated diagnostics including in- and ex-vivo biomarkers to identify high-risk individuals proneto disease progression.
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