Objectives The purpose of this study was to develop and validate a simple-to-use nomogram for prediction of 5-, 10-, and 15-year survival among asymptomatic adults.

Background Simple-to-use prognostication tools that incorporate robust methods such as coronary artery calcium scoring (CACS) for predicting near-, intermediate- and long-term mortality are warranted.

Methods In a consecutive series of 9,715 persons (mean age: 53.4 ± 10.5 years; 59.3% male) undergoing CACS, we developed a nomogram using Cox proportional hazards regression modeling that included: age, sex, smoking, hypertension, dyslipidemia, diabetes, family history of coronary artery disease, and CACS. We developed a prognostic index (PI) summing the number of risk points corresponding to weighted covariates, which was used to configure the nomogram. Validation of the nomogram was assessed by discrimination and calibration applied to a separate cohort of 7,824 adults who also underwent CACS.

Results A total of 936 and 294 deaths occurred in the derivation and validation sets at a median follow-up of 14.6 years (interquartile range: 13.7 to 15.5 years) and 9.4 years (interquartile range: 6.8 to 11.5 years), respectively. The developed model effectively predicted 5-, 10-, and 15-year probability of survival. The PI displayed high discrimination in the derivation and validation sets (C-index 0.74 and 0.76, respectively), indicating suitable external performance of our nomogram model. The predicted and actual estimates of survival in each dataset according to PI quartiles were similar (though not identical), demonstrating improved model calibration.

Conclusions A simple-to-use nomogram effectively predicts 5-, 10- and 15-year survival for asymptomatic adults undergoing screening for cardiac risk factors. This nomogram may be considered for use in clinical care.

目的本研究的目的是开发并验证一种简单易用的列线图，用于预测无症状成人的 5 年、10 年和 15 年生存率。

背景需要采用简单易用的预测工具，结合冠状动脉钙化评分 (CACS) 等稳健方法来预测近期、中期和长期死亡率。

方法在连续 9,715 名接受 CACS 的人（平均年龄：53.4 ± 10.5 岁；59.3% 男性）中，我们使用 Cox 比例风险回归模型开发了列线图，其中包括：年龄、性别、吸烟、高血压、血脂异常、糖尿病、家庭冠状动脉疾病史和 CACS。我们开发了一个预后指数 (PI)，对加权协变量对应的风险点数量进行求和，用于配置列线图。通过对同样接受 CACS 的 7,824 名成年人进行区分和校准来评估列线图的验证。

结果推导组和验证组中，中位随访时间分别为 14.6 年（四分位距：13.7 至 15.5 年）和 9.4 年（四分位距：6.8 至 11.5 年），总共发生了 936 例和 294 例死亡。开发的模型有效预测了 5 年、10 年和 15 年的生存概率。 PI 在推导集和验证集中表现出较高的辨别力（C 指数分别为 0.74 和 0.76），表明我们的列线图模型具有合适的外部性能。根据 PI 四分位数，每个数据集中的预测和实际生存估计相似（尽管不相同），这表明模型校准得到了改进。

结论简单易用的列线图可以有效预测接受心脏危险因素筛查的无症状成人的 5 年、10 年和 15 年生存率。该列线图可考虑用于临床护理。