尽管当前已知准确评估原发肾上腺淋巴瘤（primary adrenal lymphoma, PAL）患者的总体生存（overall survival, OS）和疾病特定生存（disease-specific survival, DSS）对其预后有影响，但目前尚无稳定且有效的预测模型存在。本研究旨在开发预测模型来评估生存情况。本研究纳入了来自SEER计划的5448名肾上腺肿块患者。采用最小绝对收缩和选择算子回归模型（least absolute shrinkage and selection operator regression model, LASSO）和Fine和Gray模型（Fine and Gray model, FGM）选择影响因素。此外，建立了预测图。使用接受者操作特征曲线和自主抽样方法验证了预测图的区分度和一致性。通过LASSO和FGM选择了PAL生存的独立影响因素，并构建了3个模型：OS模型、DSS模型和FGS模型（通过FGM进行DSS分析）。曲线下面积和决策曲线分析结果表明这些模型是有效的。本研究开发了预测PAL患者OS和DSS的生存预测模型。FGS模型在短期内比DSS模型更准确。总而言之，这些模型应该能够为PAL患者在治疗方式选择和生存评估方面提供益处。© 2023. Springer Nature Limited.

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.© 2023. Springer Nature Limited.