Department of Mathematical Sciences, FO 35, University of Texas at Dallas, Richardson, TX 75080-3021, USA.
Breast Cancer Res Treat. 2013 Jun;139(2):571-9. doi: 10.1007/s10549-013-2564-4. Epub 2013 May 21.
Health care providers need simple tools to identify patients at genetic risk of breast and ovarian cancers. Genetic risk prediction models such as BRCAPRO could fill this gap if incorporated into Electronic Medical Records or other Health Information Technology solutions. However, BRCAPRO requires potentially extensive information on the counselee and her family history. Thus, it may be useful to provide simplified version(s) of BRCAPRO for use in settings that do not require exhaustive genetic counseling. We explore four simplified versions of BRCAPRO, each using less complete information than the original model. BRCAPROLYTE uses information on affected relatives only up to second degree. It is in clinical use but has not been evaluated. BRCAPROLYTE-Plus extends BRCAPROLYTE by imputing the ages of unaffected relatives. BRCAPROLYTE-Simple reduces the data collection burden associated with BRCAPROLYTE and BRCAPROLYTE-Plus by not collecting the family structure. BRCAPRO-1Degree only uses first-degree affected relatives. We use data on 2,713 individuals from seven sites of the Cancer Genetics Network and MD Anderson Cancer Center to compare these simplified tools with the Family History Assessment Tool (FHAT) and BRCAPRO, with the latter serving as the benchmark. BRCAPROLYTE retains high discrimination; however, because it ignores information on unaffected relatives, it overestimates carrier probabilities. BRCAPROLYTE-Plus and BRCAPROLYTE-Simple provide better calibration than BRCAPROLYTE, so they have higher specificity for similar values of sensitivity. BRCAPROLYTE-Plus performs slightly better than BRCAPROLYTE-Simple. The Areas Under the ROC curve are 0.783 (BRCAPRO), 0.763 (BRCAPROLYTE), 0.772 (BRCAPROLYTE-Plus), 0.773 (BRCAPROLYTE-Simple), 0.728 (BRCAPRO-1Degree), and 0.745 (FHAT). The simpler versions, especially BRCAPROLYTE-Plus and BRCAPROLYTE-Simple, lead to only modest loss in overall discrimination compared to BRCAPRO in this dataset. Thus, we conclude that simplified implementations of BRCAPRO can be used for genetic risk prediction in settings where collection of complete pedigree information is impractical.
医疗保健提供者需要简单的工具来识别具有乳腺癌和卵巢癌遗传风险的患者。如果将遗传风险预测模型（如 BRCAPRO）纳入电子病历或其他健康信息技术解决方案中，则可以填补这一空白。然而，BRCAPRO 需要对咨询者及其家族病史进行潜在的广泛信息收集。因此，为在不需要详尽遗传咨询的环境中使用提供简化版的 BRCAPRO 可能会很有用。我们探索了 BRCAPRO 的四种简化版本，每个版本都使用比原始模型更少的完整信息。BRCAPROLYTE 仅使用直系亲属的患病信息，最多到二级亲属。它已在临床中使用，但尚未进行评估。BRCAPROLYTE-Plus 通过推断未受影响亲属的年龄来扩展 BRCAPROLYTE。BRCAPROLYTE-Simple 通过不收集家族结构来减少与 BRCAPROLYTE 和 BRCAPROLYTE-Plus 相关的数据收集负担。BRCAPRO-1Degree 仅使用一级亲属中的患病个体。我们使用来自癌症遗传学网络和 MD 安德森癌症中心的七个站点的 2713 个人的数据来比较这些简化工具与家族史评估工具（FHAT）和 BRCAPRO，后者作为基准。BRCAPROLYTE 保持了较高的判别力；然而，由于它忽略了未受影响亲属的信息，因此会高估携带者的概率。BRCAPROLYTE-Plus 和 BRCAPROLYTE-Simple 比 BRCAPRO 提供更好的校准，因此对于相似的灵敏度值，它们具有更高的特异性。BRCAPROLYTE-Plus 的性能略优于 BRCAPROLYTE-Simple。ROC 曲线下面积分别为 0.783（BRCAPRO）、0.763（BRCAPROLYTE）、0.772（BRCAPROLYTE-Plus）、0.773（BRCAPROLYTE-Simple）、0.728（BRCAPRO-1Degree）和 0.745（FHAT）。在这个数据集，与 BRCAPRO 相比，较简单的版本，尤其是 BRCAPROLYTE-Plus 和 BRCAPROLYTE-Simple，导致整体判别力仅略有下降。因此，我们得出结论，在收集完整家系信息不切实际的情况下，可以使用 BRCAPRO 的简化实现进行遗传风险预测。
