Clinical Persona Inc., East Palo Alto, California.
Telomere Diagnostics, Menlo Park, California.
Biol Blood Marrow Transplant. 2018 Jun;24(6):1299-1306. doi: 10.1016/j.bbmt.2018.01.038. Epub 2018 Feb 2.
The survival of patients undergoing hematopoietic cell transplantation (HCT) from unrelated donors for acute leukemia exhibits considerable variation, even after stringent genetic matching. To improve the donor selection process, we attempted to create an algorithm to quantify the likelihood of survival to 5 years after unrelated donor HCT for acute leukemia, based on the clinical characteristics of the donor selected. All standard clinical variables were included in the model, which also included average leukocyte telomere length of the donor based on its association with recipient survival in severe aplastic anemia, and links to multiple malignancies. We developed a multivariate classifier that assigned a Preferred or NotPreferred label to each prospective donor based on the survival of the recipient. In a previous analysis using a resampling method, recipients with donors labeled Preferred experienced clinically compelling better survival compared with those labeled NotPreferred by the test. However, in a pivotal validation study in an independent cohort of 522 patients, the overall survival of the Preferred and NotPreferred donor groups was not significantly different. Although machine learning approaches have successfully modeled other biological phenomena and have led to accurate predictive models, our attempt to predict HCT outcomes after unrelated donor transplantation was not successful.
异基因造血细胞移植（HCT）治疗急性白血病患者的存活率存在显著差异，即使在严格的遗传匹配后也是如此。为了改进供者选择过程，我们尝试根据选择的供者的临床特征，建立一种算法来量化异基因 HCT 后 5 年急性白血病患者的存活率。该模型纳入了所有标准的临床变量，还纳入了供者白细胞端粒长度平均值，因为它与重型再生障碍性贫血患者的受体存活率相关，并且与多种恶性肿瘤相关。我们开发了一种多变量分类器，根据受体的存活率，为每个潜在供者分配“首选”或“不首选”标签。在前一项使用重采样方法的分析中，与被标记为“不首选”的供者相比，被标记为“首选”的供者的受体具有更显著的临床生存获益。然而，在一项独立的 522 例患者队列的关键验证研究中，首选和不首选供者组的总生存率没有显著差异。尽管机器学习方法已经成功地模拟了其他生物学现象，并导致了准确的预测模型，但我们预测异基因无关供者移植后 HCT 结局的尝试并不成功。
