Department of Obstetrics and Gynecology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 135-710, Republic of Korea.
Gynecol Oncol. 2013 Dec;131(3):650-4. doi: 10.1016/j.ygyno.2013.10.003. Epub 2013 Oct 18.
Recurrence is the major cause of death in early cervical cancer. We compared the prediction powers for disease recurrence between the gene set prognostic model and the clinical prognostic model.
A gene set model to predict disease free survival was developed using the cDNA-mediated annealing, selection, extension, and ligation (DASL) assay data set from a cohort of early cervical cancer patients who had been treated with radical surgery with or without adjuvant therapy. A clinical prediction model was also developed using the same cohort, and the ability of predicting recurrence from each model was compared.
Adequate DASL assay profiles were obtained from 300 patients, and we selected 12 genes for the gene set model. When patients were categorized as having a low or high risk by the prognostic score, the Kaplan-Meier curve showed significantly different recurrence rates between the two groups. The clinical model was developed using FIGO stage and post-surgical pathological findings. In multivariate Cox regression analysis of prognostic models, the gene set prognostic model showed a higher hazard ratio than that of the clinical prognostic model.
The genetic quantitative approach may be better in predicting recurrence in early cervical cancer patients.
复发是早期宫颈癌患者死亡的主要原因。我们比较了基因集预后模型和临床预后模型对疾病复发的预测能力。
使用来自接受根治性手术联合或不联合辅助治疗的早期宫颈癌患者队列的 cDNA 介导的退火、选择、延伸和连接（DASL）检测数据集，建立了用于预测无病生存的基因集模型。还使用相同的队列建立了临床预测模型，并比较了每个模型预测复发的能力。
从 300 名患者中获得了足够的 DASL 检测谱，我们选择了 12 个基因用于基因集模型。当根据预后评分将患者分为低风险或高风险时，两组之间的 Kaplan-Meier 曲线显示出明显不同的复发率。临床模型是使用 FIGO 分期和术后病理发现建立的。在预后模型的多变量 Cox 回归分析中，基因集预后模型的风险比高于临床预后模型。
基因定量方法可能更适合预测早期宫颈癌患者的复发。
