Development and validation of nomograms to predict survival of primary adrenal lymphoma: a population-based retrospective study

作者：Shiwei Sun, Yue Wang, Wei Yao, Yue Peng, Fuyu Guo, Xiaoqian Deng, Jiandong Zhang, Yangang Zhang · 发表于：Scientific Reports · 年份：2023 · DOI：10.1038/s41598-023-41839-2 · 被引用次数：4 · 研究领域：Adrenal and Paraganglionic Tumors、Hormonal Regulation and Hypertension、Ovarian cancer diagnosis and treatment

While it is known that accurate evaluation of overall survival (OS) and disease-specific survival (DSS) for patients with primary adrenal lymphoma (PAL) can affect their prognosis, no stable and effective prediction model exists. This study aimed to develop prediction models to evaluate survival. This study enrolled 5448 patients with adrenal masses from the SEER Program. The influencing factors were selected using the least absolute shrinkage and selection operator regression model (LASSO) and Fine and Gray model (FGM). In addition, nomograms were constructed. Receiver operating characteristic curves and bootstrap self-sampling methods were used to verify the discrimination and consistency of the nomograms. The independent influencing factors for PAL survival were selected by LASSO and FGM, and three models were built: the OS, DSS, and FGS (DSS analysis by FGM) model. The areas under the curve and decision curve analyses indicated that the models were valid. This study developed survival prediction models to predict OS and DSS of patients with PAL. The FGS model was more accurate than the DSS model in the short term. Above all, these models should offer benefits to patients with PAL in terms of the treatment modality choice and survival evaluation.