Department of Surgery, Institut Curie, Paris, France.
PLoS One. 2012;7(10):e47390. doi: 10.1371/journal.pone.0047390. Epub 2012 Oct 9.
To decipher the interaction between the molecular subtype classification and the probability of a non-sentinel node metastasis in breast cancer patients with a metastatic sentinel lymph-node, we applied two validated predictors (Tenon Score and MSKCC Nomogram) on two large independent datasets.
Our datasets consisted of 656 and 574 early-stage breast cancer patients with a metastatic sentinel lymph-node biopsy treated at first by surgery. We applied both predictors on the whole dataset and on each molecular immune-phenotype subgroups. The performances of the two predictors were analyzed in terms of discrimination and calibration. Probability of non-sentinel lymph node metastasis was detailed for each molecular subtype.
Similar results were obtained with both predictors. We showed that the performance in terms of discrimination was as expected in ER Positive HER2 negative subgroup in both datasets (MSKCC AUC Dataset 1 = 0.73 [0.69-0.78], MSKCC AUC Dataset 2 = 0.71 (0.65-0.76), Tenon Score AUC Dataset 1 = 0.7 (0.65-0.75), Tenon Score AUC Dataset 2 = 0.72 (0.66-0.76)). Probability of non-sentinel node metastatic involvement was slightly under-estimated. Contradictory results were obtained in other subgroups (ER negative HER2 negative, HER2 positive subgroups) in both datasets probably due to a small sample size issue. We showed that merging the two datasets shifted the performance close to the ER positive HER2 negative subgroup.
We showed that validated predictors like the Tenon Score or the MSKCC nomogram built on heterogeneous population of breast cancer performed equally on the different subgroups analyzed. Our present study re-enforce the idea that performing subgroup analysis of such predictors within less than 200 samples subgroup is at major risk of misleading conclusions.
为了解密分子亚型分类与乳腺癌伴转移性前哨淋巴结患者非前哨淋巴结转移概率之间的相互作用，我们在两个大型独立数据集上应用了两种经过验证的预测器（Tenon 评分和 MSKCC 列线图）。
我们的数据集包括 656 例和 574 例早期乳腺癌伴转移性前哨淋巴结活检的患者，这些患者首先接受手术治疗。我们将这两种预测器应用于整个数据集和每个分子免疫表型亚组。我们分析了这两种预测器的判别和校准性能。详细列出了每个分子亚型的非前哨淋巴结转移概率。
两种预测器都得到了类似的结果。我们表明，在两个数据集的 ER 阳性 HER2 阴性亚组中，判别性能符合预期（MSKCC AUC 数据集 1 = 0.73 [0.69-0.78]，MSKCC AUC 数据集 2 = 0.71 [0.65-0.76]，Tenon 评分 AUC 数据集 1 = 0.7 [0.65-0.75]，Tenon 评分 AUC 数据集 2 = 0.72 [0.66-0.76]）。非前哨淋巴结转移的概率略有低估。在两个数据集的其他亚组（ER 阴性 HER2 阴性、HER2 阳性亚组）中，得到了相反的结果，这可能是由于样本量小的问题。我们表明，合并两个数据集将性能接近 ER 阳性 HER2 阴性亚组。
我们表明，像 Tenon 评分或基于乳腺癌异质人群建立的 MSKCC 列线图这样的经过验证的预测器在分析的不同亚组中表现相同。我们的研究进一步证实了这样的观点，即在少于 200 个样本亚组中对这些预测器进行亚组分析存在误导结论的重大风险。
