Miao Guiqiang, Li Zhaohui, Chen Linjian, Li Wenyong, Lan Guobo, Chen Qiyuan, Luo Zhen, Liu Ruijia, Zhao Xiaodong
Department of Orthopedics, Foshan Fosun Chancheng Hospital, Foshan, 528010, People's Republic of China.
Int J Gen Med. 2022 Mar 22;15:3255-3264. doi: 10.2147/IJGM.S352761. eCollection 2022.
Bone and bone marrow are the third most frequent sites of metastases from many cancers and are associated with low survival and high morbidity rates. Currently, there are no effective bedside tools to predict the morbidity risk of these patients in general intensive care units (ICUs). The main objective of this study was to establish and validate a nomogram to predict the morbidity risk of patients with bone and bone marrow metastases.
Data on patients with bone and bone marrow metastases were extracted from the Medical Information Mart for Intensive Care III (MIMIC-III) database. The patients were divided into training and validation cohorts. The data were analyzed using univariate and multivariate Cox regression methods. Factors significantly and independently prognostic of survival were used to construct a nomogram predicting 30-day morbidity. The nomogram was validated by various methods, including Harrell's concordance index (C-index), area under the receiver operating characteristic curve (AUC), calibration curve, integrated discrimination improvement (IDI), net reclassification index (NRI), and decision curve analysis (DCA).
The study included 610 patients in the training cohort and 262 in the validation cohort. Multivariate Cox regression analysis showed that temperature, SpO, Sequential Organ Failure Assessment (SOFA) score, Oxford Acute Severity of Illness Score (OASIS), comorbidities with coagulopathy, white blood cell count, heart rate, and respiratory rate were independent predictors of patient survival. The resulting nomogram had good discriminative ability, as shown by high AUCs, and was well calibrated, as demonstrated by calibration curves. Improvements in NRI and IDI values suggested that the nomogram was superior to the SOFA scoring system. DCA curves revealed that the nomogram showed good value in clinical applications.
This prognostic nomogram, based on demographic and laboratory parameters, was predictive of the 30-day morbidity rate in patients with secondary malignant neoplasms of the bone and bone marrow, suggesting its applicability in clinical practice.
骨骼和骨髓是许多癌症转移的第三大常见部位，与低生存率和高发病率相关。目前，在综合重症监护病房（ICU）中，尚无有效的床边工具来预测这些患者的发病风险。本研究的主要目的是建立并验证一种列线图，以预测骨骼和骨髓转移患者的发病风险。
从重症监护医学信息数据库III（MIMIC-III）中提取骨骼和骨髓转移患者的数据。将患者分为训练队列和验证队列。使用单因素和多因素Cox回归方法分析数据。将对生存有显著且独立预后作用的因素用于构建预测30天发病情况的列线图。通过多种方法对列线图进行验证，包括Harrell一致性指数（C指数）、受试者操作特征曲线下面积（AUC）、校准曲线、综合判别改善（IDI）、净重新分类指数（NRI）和决策曲线分析（DCA）。
研究纳入训练队列610例患者和验证队列262例患者。多因素Cox回归分析显示，体温、血氧饱和度（SpO）、序贯器官衰竭评估（SOFA）评分、牛津急性疾病严重程度评分（OASIS）、合并凝血病、白细胞计数、心率和呼吸频率是患者生存的独立预测因素。所得列线图具有良好的判别能力，高AUC值表明了这一点，校准曲线也证明其校准良好。NRI和IDI值的改善表明列线图优于SOFA评分系统。DCA曲线显示列线图在临床应用中具有良好价值。
这种基于人口统计学和实验室参数的预后列线图可预测骨骼和骨髓继发性恶性肿瘤患者的30天发病率，表明其在临床实践中的适用性。
