Division of Gynecologic Oncology and Department of Pathology, Anschutz Medical Campus, University of Colorado School of Medicine, Denver, CO, USA.
Int J Gynecol Cancer. 2011 Nov;21(8):1422-7. doi: 10.1097/IGC.0b013e31822c7704.
Patients who present with an advanced ovarian cancer are typically treated with primary debulking surgery (PDS) or neoadjuvant chemotherapy (NAC) followed by interval debulking surgery. The accurate pretreatment identification of patients best suited for PDS versus NAC is challenging. A paradigm for selecting one approach over the other could improve patient outcomes. In this study, we developed a prediction model for "successful surgery" (defined as optimal residual disease and no major perioperative complication) in patients who underwent PDS.
Preoperative clinical characteristics, laboratory values, computed tomography findings, and surgical outcomes of 106 consecutive medically fit patients with advanced ovarian, tubal, or peritoneal cancer were reviewed. Preoperative predictors of suboptimal residual disease and major perioperative complications were determined using regression analysis. A surgical risk score (SRS) that minimized the false-negative rate (ie, likelihood of incorrectly predicting successful surgery) was constructed.
Sixty (57%) of the 106 patients were optimally cytoreduced. Fifty-six "radical procedures" were performed, and there were a total of 24 major perioperative complications. Diffuse peritoneal studding (P < 0.0001), para-aortic lymphadenopathy (P < 0.0001), and mesenteric involvement (Mes, P = 0.006) were associated with suboptimal (>1 cm) residual disease. Low albumin (P = 0.04) and splenic disease (spleen, P = 0.02) were the only 2 parameters associated with a higher risk of a major perioperative complication. The median SRSs of patients who had successful and "unsuccessful surgery" were 1 (0-4) and 3 (0-6), respectively. The false-negative rate of the SRS was only 7%.
We developed a model that incorporated complications, in addition to residual disease status, into predicting surgical outcome for medically fit patients with advanced ovarian cancer. The SRS might be useful in determining the initial treatment strategy (ie, PDS vs NAC) for these patients. The accuracy of the SRS needs to be validated in a prospective manner.
患有晚期卵巢癌的患者通常接受初次肿瘤细胞减灭术（PDS）或新辅助化疗（NAC）加间隔肿瘤细胞减灭术治疗。准确预测哪些患者适合 PDS 或 NAC 具有挑战性。选择一种方法而不是另一种方法的范例可以改善患者的结局。在这项研究中，我们为接受 PDS 的患者开发了一种“成功手术”（定义为最佳残留疾病和无重大围手术期并发症）的预测模型。
回顾了 106 例连续的身体状况良好的晚期卵巢癌、输卵管癌或腹膜癌患者的术前临床特征、实验室值、计算机断层扫描结果和手术结果。使用回归分析确定了残留疾病不理想和主要围手术期并发症的预测指标。构建了一个手术风险评分（SRS），该评分将假阴性率（即错误预测成功手术的可能性）降至最低。
106 例患者中有 60 例（57%）获得最佳肿瘤细胞减灭术。56 例患者进行了“根治性手术”，共发生 24 例主要围手术期并发症。弥漫性腹膜种植（P < 0.0001）、腹主动脉旁淋巴结病（P < 0.0001）和肠系膜受累（Mes，P = 0.006）与残留疾病不理想（> 1cm）相关。低白蛋白（P = 0.04）和脾脏疾病（脾，P = 0.02）是唯一与主要围手术期并发症风险较高相关的 2 个参数。成功手术和“不成功手术”患者的中位 SRS 分别为 1（0-4）和 3（0-6）。SRS 的假阴性率仅为 7%。
我们开发了一种模型，该模型将并发症以及残留疾病状态纳入预测适合接受医学治疗的晚期卵巢癌患者的手术结果。SRS 可能有助于确定这些患者的初始治疗策略（即 PDS 与 NAC）。需要前瞻性地验证 SRS 的准确性。
