淋巴瘤有不同的病因、治疗方法和预后。对于淋巴瘤患者来说，准确的生存估计具有挑战性，因为他们对非淋巴瘤相关死亡率的敏感性更高。为了克服这一挑战，我们提出了一种新型淋巴瘤分类系统，该系统利用潜在类别分析（LCA）并纳入人口和临床病理因素作为指标。我们使用监测、流行病学和最终结果 (SEER) 数据库中 221,812 名原发性淋巴瘤患者的数据进行了 LCA，并确定了四种不同的 LCA 衍生类别。 LCA 衍生的分类有效地对患者进行了分层，从而调整了由非淋巴瘤相关死亡等竞争风险事件引起的偏差。即使在死因信息有限的情况下，这仍然有效，从而提高了淋巴瘤预后评估的准确性。此外，我们在外部队列中验证了 LCA 衍生的分类模型，并观察到其改善的分子亚型预后分层。我们进一步探索了 LCA 亚组的分子特征，并确定了每个亚组特有的潜在驱动基因。总之，我们的研究引入了一种新型的基于 LCA 的淋巴瘤分类系统，该系统通过考虑竞争风险事件来提供改进的预后预测。拟议的分类系统增强了分子亚型的临床相关性，并提供了对潜在治疗靶点的见解。© 2024 UICC。

Lymphomas have diverse etiologies, treatment approaches, and prognoses. Accurate survival estimation is challenging for lymphoma patients due to their heightened susceptibility to non-lymphoma-related mortality. To overcome this challenge, we propose a novel lymphoma classification system that utilizes latent class analysis (LCA) and incorporates demographic and clinicopathological factors as indicators. We conducted LCA using data from 221,812 primary lymphoma patients in the Surveillance, Epidemiology, and End Results (SEER) database and identified four distinct LCA-derived classes. The LCA-derived classification efficiently stratified patients, thereby adjusting the bias induced by competing risk events such as non-lymphoma-related death. This remains effective even in cases of limited availability of cause-of-death information, leading to an enhancement in the accuracy of lymphoma prognosis assessment. Additionally, we validated the LCA-derived classification model in an external cohort and observed its improved prognostic stratification of molecular subtypes. We further explored the molecular characteristics of the LCA subgroups and identified potential driver genes specific to each subgroup. In conclusion, our study introduces a novel LCA-based lymphoma classification system that provides improved prognostic prediction by accounting for competing risk events. The proposed classification system enhances the clinical relevance of molecular subtypes and offers insights into potential therapeutic targets.© 2024 UICC.