The Inflammation-Based Index Can Predict Response and Improve Patient Selection in NETs Treated With PRRT: A Pilot Study
The Inflammation-Based Index Can Predict Response and Improve Patient Selection in NETs Treated With PRRT: A Pilot Study
复制标题
DOI：
10.1210/jc.2018-01214
复制
发表时间：
2019-02-01
影响因子：
5.8
通讯作者：
Sharma, Rohini
中科院分区：
文献类型：
--
作者：
Black, James R. M.;Atkinson, Stephen R.;Sharma, Rohini
背景：肽受体放射性核素治疗（PRRT）是治疗某些转移性神经内分泌肿瘤（NETs）的有效方法。肿瘤缓解是高度可变的;临床实践中没有生物标志物被证明可以可靠地预测结果。基于炎症的指数（IBI），来自血清C-反应蛋白和白蛋白水平，预测患者的生存和治疗反应，在几种癌症类型，因此在这种setting.Materials和方法进行了探讨：临床病理数据从患者接受PRRT转移NET收集在基线和治疗期间。主要终点为无进展生存期（PFS），次要终点为总生存期（OS）。考克斯回归分析测试基线变量和他们的动态变化和PFS和OS之间的关联。决策曲线分析（DCA）被用来确定净效益与治疗策略确定的基线IBI和无反应PRRT.Results：55例患者被招募。基线IBI > 0与PFS（风险比，14.2; 95%CI，5.25 - 38.5; P < 0.001）和OS（P < 0.001）较差相关。多变量分析证实IBI和PFS之间存在独立相关性（P = 0.001）。结论：基线IBI评分及其在治疗过程中的动态变化与PFS和OS均相关，在与目前公认的治疗无效率相当的风险阈值下，实施这种容易获得的评分可以避免大量无效治疗。这些发现应在其他独立队列中得到验证。
Background: Peptide 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.Materials and Methods: Clinico-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.Results: Fifty-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.Conclusion: Baseline 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.