Practical communication of prognosis is pertinent in the clinical setting. Survival analysis techniques are standardly used in cohort studies; however, their results are not straightforward for interpretation as compared to the graspable notion of life expectancy (LE). The present study empirically examines the relationship between Cox regression coefficients (HRs), which reflect the relative risk of the investigated risk factors for mortality, and years of potential life lost (YPLL) values after acute myocardial infarction (AMI). This retrospective population-based study included patients aged 40–80 years, who survived AMI hospitalization from January 1, 2002, to October 25, 2017. A survival analysis approach assessed relationships between variables and the risk for all-cause mortality in an up to 21-year follow-up period. The total score was calculated for each patient as the summation of the Cox regression coefficients (AdjHRs) values. Individual LE and YPLL were calculated. YPLL was assessed as a function of the total score. The cohort (n = 6316, age 63.0 ± 10.5 years, 73.4 % males) was randomly split into training (n = 4243) and validation (n = 2073) datasets. Sixteen main clinical risk factors for mortality were explored (total score of 0–14.2 points). After adjustment for age, sex and nationality, a one-point increase in the total score was associated with YPLL of ∼one year. A goodness-of-fit of the prediction model found 0.624 and 0.585 for the training and validation datasets respectively. This functional derivation for converting coefficients of survival analysis into the comprehensible form of YPLL/LE allows for practical prognostic calculation and communication.

中文翻译：

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基于急性心肌梗死后人群生存分析的预期寿命估计的实证方法

预后的实际交流与临床环境相关。队列研究中标准使用生存分析技术；然而，与可理解的预期寿命（LE）概念相比，他们的结果并不容易解释。本研究实证检验了 Cox 回归系数 (HR) 与急性心肌梗死 (AMI) 后潜在寿命损失年数 (YPLL) 值之间的关系，该系数反映了所调查的死亡风险因素的相对风险。这项基于人群的回顾性研究纳入了 2002 年 1 月 1 日至 2017 年 10 月 25 日期间因 AMI 住院而幸存的 40 至 80 岁患者。生存分析方法评估了变量与全因死亡风险之间的关系。 21年的随访期。将每位患者的总分计算为 Cox 回归系数 (AdjHRs) 值的总和。计算了个体 LE 和 YPLL。 YPLL 根据总分进行评估。该队列（n = 6316，年龄 63.0 ± 10.5 岁，73.4% 为男性）被随机分为训练数据集（n = 4243）和验证数据集（n = 2073）。探讨了 16 个主要的临床死亡危险因素（总分 0-14.2 分）。调整年龄、性别和国籍后，总分增加 1 分与 YPLL 约一年相关。预测模型的训练和验证数据集的拟合优度分别为 0.624 和 0.585。这种将生存分析系数转换为可理解形式的 YPLL/LE 的函数推导允许实际的预后计算和通信。