Novel Nomograms and Web-Based Tools Predicting Overall Survival and Cancer-specific Survival of Solitary Plasmacytoma of the Spine

Author:

Yang Sheng12,Fan Guoxin345,Feng Chaobo12,Fan Yunshan12,Xu Ningze6,Zhou Hongmin6,Wang Chuanfeng12,Liao Xiang34,He Shisheng12

Affiliation:

1. Department of Orthopedics, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China

2. Spinal Pain Research Institute, Tongji University School of Medicine, Shanghai, China

3. Department of Pain Medicine, Huazhong University of Science and Technology Union Shenzhen Hospital, Shenzhen, China

4. Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, School of Biomedical Engineering, Shenzhen University Medical school

5. Department of Spine Surgery, Third Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

6. Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai, China

Abstract

Study Design. Retrospective analysis. Objective. This study aimed to establish nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in patients with solitary plasmacytoma of the spine (SPS). Summary of Background Data. SPS is a rare type of malignant spinal tumor. A systematic study of prognostic factors associated with survival can provide guidance to clinicians and patients. Consideration of other causes of death (OCOD) in CSS will improve clinical practicability. Methods. A total of 1078 patients extracted from the SEER database between 2000 and 2018 were analyzed. Patients were grouped into training and testing data sets (7:3). Factors associated with OS and CSS were identified by Cox regression and competing risk regression, respectively, for the establishment of nomograms on a training data set. The testing data set was used for the external validation of the performance of the nomograms using calibration curves, Brier’s scores, C-indexes, time-dependent receiver operating characteristic curves, and decision curve analysis (DCA). Results. Age and grade were identified as factors associated with both OS and CSS, along with marital status, radiation for OS, and chemotherapy for CSS. Heart disease, cerebrovascular disease, and diabetes mellitus were found to be the 3 most common causes of OCOD. The nomograms showed satisfactory agreement on calibration plots for both training and testing data sets. Integrated Brier score, C-index, and overall area under the curve on the testing data set were 0.162/0.717/0.789 and 0.173/0.709/0.756 for OS and CSS, respectively. DCA curves showed a good clinical net benefit. Nomogram-based web tools were developed for clinical application. Conclusion. This study provides evidence for risk factors and prognostication of survival in SPS patients. The novel nomograms and web-based tools we developed demonstrated good performance and might serve as accessory tools for clinical decision-making and SPS management. Level of Evidence. 3

Publisher

Ovid Technologies (Wolters Kluwer Health)

Subject

Neurology (clinical),Orthopedics and Sports Medicine

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