BACKGROUND Patients infected with the Human Immunodeficiency Virus (HIV) are susceptible to many diseases. In these patients, the occurrence of one disease alters the chance of contracting another. Under such circumstances, methods for competing risks are required. Recently, competing risks analyses in the scope of flexible parametric models have risen to address this requirement. These lesser-known analyses have considerable advantages over conventional methods. METHODS Using data from Multi Centre AIDS Cohort Study (MACS), this paper reviews and applies methods of competing risks flexible parametric models to analyze the risk of the first disease (AIDS or non-AIDS) among HIV-infected patients. We compared two alternative subdistribution hazard flexible parametric models (SDHFPM1 and SDHFPM2) with the Fine & Gray model. To make a complete inference, we performed cause-specific hazard flexible parametric models for each event separately as well. RESULTS Both SDHFPM1 and SDHFPM2 provided consistent results regarding the magnitude of coefficients and risk estimations compared with estimations obtained from the Fine & Gray model, However, competing risks flexible parametric models provided more efficient and smoother estimations for the baseline risks of the first disease. We found that age at HIV diagnosis indirectly affected the risk of AIDS as the first event by increasing the number of patients who experience a non-AIDS disease prior to AIDS among > 40 years. Other significant covariates had direct effects on the risks of AIDS and non-AIDS. DISCUSSION The choice of an appropriate model depends on the research goals and computational challenges. The SDHFPM1 models each event separately and requires calculating censoring weights which is time-consuming. In contrast, SDHFPM2 models all events simultaneously and is more appropriate for large datasets, however, when the focus is on one particular event SDHFPM1 is more preferable.

中文翻译：

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竞争风险的方法灵活的参数化模型可用于估计感染HIV的男性中第一病的风险。

背景技术感染了人类免疫缺陷病毒（HIV）的患者易患多种疾病。在这些患者中，一种疾病的发生改变了感染另一种疾病的机会。在这种情况下，需要采取应对风险的方法。最近，在灵活的参数模型范围内进行竞争性风险分析已经可以满足这一要求。这些鲜为人知的分析与传统方法相比具有相当大的优势。方法利用多中心艾滋病队列研究（MACS）的数据，本文回顾并应用竞争风险灵活参数模型的方法来分析HIV感染患者中首发疾病（艾滋病或非艾滋病）的风险。我们将两个替代的子分布危害柔性参数模型（SDHFPM1和SDHFPM2）与Fine和Gray模型进行了比较。为了做出完整的推断，我们还分别为每个事件执行了特定于原因的危险灵活参数模型。结果与从Fine＆Gray模型获得的估计相比，SDHFPM1和SDHFPM2在系数的大小和风险估计方面均提供了一致的结果，但是，竞争风险灵活的参数模型为第一种疾病的基线风险提供了更有效，更平滑的估计。我们发现，在诊断HIV的年龄中，通过增加40年前在AIDS之前经历过非AIDS疾病的患者数量，间接影响了AIDS的风险。其他重要的协变量对艾滋病和非艾滋病的风险有直接影响。讨论适当模型的选择取决于研究目标和计算挑战。SDHFPM1分别对每个事件建模，并需要计算检查权重，这很费时。相反，SDHFPM2同时对所有事件建模，并且更适合于大型数据集，但是，当焦点放在一个特定事件上时，SDHFPM1更可取。