Immunoglobulin light chain (AL) amyloidosis is a multisystem disease with varied treatment options and disease-related outcomes. Current staging systems rely on a limited number of cardiac, renal, and plasma cell dyscrasia biomarkers. To improve prognostication for all-cause mortality and end-stage kidney disease (ESKD), we applied unsupervised machine learning using a comprehensive set of clinical and laboratory parameters. Our study cohort comprised 2067 patients with newly diagnosed, biopsy-proven AL amyloidosis from the Boston University Amyloidosis Center. Variables included 31 clinical symptoms and 28 baseline laboratory values. Our clustering algorithm identified three subgroups of AL amyloidosis (low-risk, intermediate-risk, and high-risk) with distinct clinical phenotypes and median overall survival (OS) estimates of 6.1, 3.7, and 1.2 years, respectively. The 10-year adjusted cumulative incidences of all-cause mortality were 66.8% (95% CI 63.4–70.1), 75.4% (95% CI 72.1–78.6), and 90.6% (95% CI 87.4–93.3) for low, intermediate, and high-risk subgroups. The 10-year adjusted cumulative incidences of end-stage kidney disease (ESKD) were 20.4% (95% CI 6.1–24.5), 37.6% (95% CI 31.8–43.8), and 6.7% (95% CI 2.8–11.3) for low-risk, intermediate-risk, and high-risk subgroups. Finally, we trained a classifier for external validation with high cross-validation accuracy (85% [95% CI 83–86]) using a subset of easily obtainable clinical parameters. This marks an initial stride toward integrating precision medicine into risk stratification of AL amyloidosis for both all-cause mortality and ESKD.

中文翻译：

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基于机器学习的 AL 淀粉样变性亚组以及死亡率和终末期肾病的累积发生率


免疫球蛋白轻链 （AL） 淀粉样变性是一种多系统疾病，具有不同的治疗选择和疾病相关结果。当前的分期系统依赖于有限数量的心脏、肾脏和浆细胞恶液质生物标志物。为了改善全因死亡率和终末期肾病 （ESKD） 的预后，我们使用一套全面的临床和实验室参数应用了无监督机器学习。我们的研究队列包括来自波士顿大学淀粉样变性中心的 2067 名新诊断、经活检证实的 AL 淀粉样变性患者。变量包括 31 种临床症状和 28 种基线实验室值。我们的聚类算法确定了 AL 淀粉样变性的三个亚组 （低风险、中风险和高风险），具有不同的临床表型，中位总生存期 （OS） 估计分别为 6.1 、 3.7 和 1.2 年。低、中、高风险亚组的 10 年校正全因累积发生率为 66.8% （95% CI 63.4-70.1）、75.4% （95% CI 72.1-78.6） 和 90.6% （95% CI 87.4-93.3）。低风险、中风险和高风险亚组的终末期肾病 （ESKD） 的 10 年校正累积发病率为 20.4% （95% CI 6.1-24.5）、37.6% （95% CI 31.8-43.8） 和 6.7% （95% CI 2.8-11.3）。最后，我们使用易于获得的临床参数子集训练了一个用于外部验证的分类器，具有很高的交叉验证准确性 （85% [95% CI 83–86]）。这标志着将精准医学整合到全因死亡率和 ESKD 的 AL 淀粉样变性风险分层中迈出了第一步。