建立预测 III 期可切除非小细胞肺癌骨转移的生物标志物模型。
Establishment of a biomarker model for predicting bone metastasis in resected stage III non-small cell lung cancer.
机构信息
Department of Lung Tumor Clinical Medical Center, Shanghai Chest Hospital affiliated to Shanghai Jiaotong University, and Thoracic Tumor Clinical Medicine Center of Shanghai Municipality, Shanghai 200032, China.
出版信息
J Exp Clin Cancer Res. 2012 Apr 26;31(1):34. doi: 10.1186/1756-9966-31-34.
BACKGROUND
This study was designed to establish a biomarker risk model for predicting bone metastasis in stage III non-small cell lung cancer (NSCLC).
METHODS
The model consists of 105 cases of stage III NSCLC, who were treated and followed up. The patients were divided into bone metastasis group (n = 45) and non-bone metastasis group (other visceral metastasis and those without recurrence) (n = 60). Tissue microarrays were constructed for immunohistochemical study of 10 molecular markers associated with bone metastasis, based on which a model was established via logistic regression analysis for predicting the risk of bone metastases. The model was prospectively validated in another 40 patients with stage III NSCLC.
RESULTS
The molecular model for predicting bone metastasis was logit (P) = - 2.538 + 2.808 CXCR4 +1.629 BSP +0.846 OPN-2.939 BMP4. ROC test showed that when P ≥ 0.408, the sensitivity was up to 71% and specificity of 70%. Model validation in the 40 cases in clinical trial (NCT 01124253) demonstrated that the prediction sensitivity of the model was 85.7%, specificity 66.7%, Kappa: 0.618, with a high degree of consistency.
CONCLUSION
The molecular model combining CXCR4, BSP, OPN and BMP4 could help predict the risk of bone metastasis in stage IIIa and IIIb resected NSCLC.
背景
本研究旨在建立一个预测 III 期非小细胞肺癌（NSCLC）骨转移的生物标志物风险模型。
方法
该模型包含 105 例 III 期 NSCLC 患者，对其进行治疗和随访。患者分为骨转移组（n=45）和非骨转移组（其他内脏转移和无复发者）（n=60）。对 10 个与骨转移相关的分子标志物进行免疫组织化学研究，构建组织微阵列，通过逻辑回归分析建立预测骨转移风险的模型。该模型在另外 40 例 III 期 NSCLC 患者中进行了前瞻性验证。
结果
预测骨转移的分子模型为 logit（P）=-2.538+2.808CXCR4+1.629BSP+0.846OPN-2.939BMP4。ROC 检验表明，当 P≥0.408 时，敏感性高达 71%，特异性为 70%。在临床试验（NCT 01124253）的 40 例病例中进行模型验证，结果显示模型的预测敏感性为 85.7%，特异性为 66.7%，Kappa：0.618，具有高度一致性。
结论
联合 CXCR4、BSP、OPN 和 BMP4 的分子模型有助于预测 IIIa 期和 IIIb 期可切除 NSCLC 的骨转移风险。
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