Multiparametric assays for risk stratification are widely used in the management of both node negative and node positive hormone receptor positive invasive breast cancer. Recent data from multiple sources suggests that different tests may provide different risk estimates at the individual patient level. The TEAM pathology study consists of 3284 postmenopausal ER+ve breast cancers treated with endocrine therapy Using genes comprising the following multi-parametric tests OncotypeDx^®, Prosigna™ and MammaPrint^® signatures were trained to recapitulate true assay results. Patients were then classified into risk groups and survival assessed. Whilst likelihood χ² ratios suggested limited value for combining tests, Kaplan–Meier and LogRank tests within risk groups suggested combinations of tests provided statistically significant stratification of potential clinical value. Paradoxically whilst Prosigna-trained results stratified Oncotype-trained subgroups across low and intermediate risk categories, only intermediate risk Prosigna-trained cases were further stratified by Oncotype-trained results. Both Oncotype-trained and Prosigna-trained results further stratified MammaPrint-trained low risk cases, and MammaPrint-trained results also stratified Oncotype-trained low and intermediate risk groups but not Prosigna-trained results. Comparisons between existing multiparametric tests are challenging, and evidence on discordance between tests in risk stratification presents further dilemmas. Detailed analysis of the TEAM pathology study suggests a complex inter-relationship between test results in the same patient cohorts which requires careful evaluation regarding test utility. Further prognostic improvement appears both desirable and achievable.

用于风险分层的多参数测定广泛用于淋巴结阴性和淋巴结阳性激素受体阳性浸润性乳腺癌的管理。来自多个来源的最新数据表明，不同的测试可能会在个体患者水平上提供不同的风险估计。TEAM 病理学研究包括 3284 例接受内分泌疗法治疗的绝经后 ER+ve 乳腺癌。使用包含以下多参数测试的基因对 OncotypeDx ^®、Prosigna ™ 和 MammaPrint ^®特征进行训练，以重现真实的检测结果。然后将患者分为风险组并评估生存率。而似然χ ²比率表明组合测试的价值有限，风险组内的 Kaplan-Meier 和 LogRank 测试表明测试组合提供了潜在临床价值的统计学显着分层。矛盾的是，虽然 Prosigna 训练的结果将 Oncotype 训练的亚组在低风险和中度风险类别中进行了分层，但只有中等风险的 Prosigna 训练的病例才能通过 Oncotype 训练的结果进一步分层。Oncotype 训练和 Prosigna 训练的结果都进一步对 MammaPrint 训练的低风险病例进行了分层，MammaPrint 训练的结果也将 Oncotype 训练的低风险和中等风险组进行了分层，但没有对 Prosigna 训练的结果进行了分层。现有多参数检验之间的比较具有挑战性，而且风险分层检验之间不一致的证据呈现出进一步的困境。对 TEAM 病理学研究的详细分析表明，同一患者队列中的测试结果之间存在复杂的相互关系，这需要对测试效用进行仔细评估。进一步的预后改善似乎既可取又可实现。