Department of Hematology, The First Affiliated Hospital of University of Science and Technology of China, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, China.
Anhui Provincial Key Laboratory of Blood Research and Applications, Hefei, Anhui, 230001, China.
Stem Cell Res Ther. 2023 Oct 23;14(1):304. doi: 10.1186/s13287-023-03538-7.
Umbilical cord blood transplantation (UCBT) is a curable therapy for hematological disease; however, the impact of nutritional status on UCBT outcomes remains controversial. To evaluate the joint effect of clinical characteristics and nutritional status on the prognosis of patients who underwent UCBT, we screened various factors to establish a predictive model of overall survival (OS) after UCBT.
We performed an integrated clinical characteristic and nutritional risk factor analysis and established a predictive model that could be used to identify UCBT recipients with poor OS. Internal validation was performed by using the bootstrap method with 500 repetitions.
Four factors, including disease status, conditioning regimen, calf skinfold thickness and albumin level, were identified and used to develop a risk score for OS, which showed a positive predictive value of 84.0%. A high-risk score (≥ 2.225) was associated with inferior 3-year OS post-UCBT [67.5% (95% CI 51.1-79.4%), P = 0.001]. Then, we built a nomogram based on the four factors that showed good discrimination with a C-index of 0.833 (95% CI 0.743-0.922). The optimism-corrected C-index value of the bootstrapping was 0.804. Multivariate analysis suggested that a high calf skinfold thickness (≥ 20.5 mm) and a low albumin level (< 33.6 g/L) conferred poor disease-free survival (DFS).
The predictive model combining clinical and nutritional factors could be used to predict OS in UCBT recipients, thereby promoting preemptive treatment.
脐带血移植（UCBT）是治疗血液系统疾病的一种有治愈希望的疗法；然而，营养状况对 UCBT 结局的影响仍存在争议。为了评估临床特征和营养状况对 UCBT 后患者预后的联合影响，我们筛选了各种因素，建立了 UCBT 后总生存率（OS）的预测模型。
我们进行了综合的临床特征和营养风险因素分析，并建立了一个预测模型，可用于识别 OS 较差的 UCBT 受者。采用 bootstrap 方法重复 500 次进行内部验证。
确定了 4 个因素，包括疾病状态、预处理方案、小腿皮褶厚度和白蛋白水平，用于制定 OS 风险评分，该评分具有 84.0%的阳性预测值。高风险评分（≥2.225）与 UCBT 后 3 年 OS 较差相关[67.5%（95%CI 51.1-79.4%），P=0.001]。然后，我们基于四个因素建立了一个列线图，具有良好的区分度，C 指数为 0.833（95%CI 0.743-0.922）。bootstrap 的校正后 C 指数值为 0.804。多变量分析表明，小腿皮褶厚度高（≥20.5mm）和白蛋白水平低（<33.6g/L）与无病生存（DFS）较差相关。
结合临床和营养因素的预测模型可用于预测 UCBT 受者的 OS，从而促进预防性治疗。
