Barczyński Bartłomiej, Frąszczak Karolina, Wnorowski Artur, Kotarski Jan
1st Chair and Department of Oncological Gynaecology and Gynaecology, Medical University in Lublin, 20-081 Lublin, Poland.
Department of Biopharmacy, Medical University in Lublin, 20-081 Lublin, Poland.
Cancers (Basel). 2023 Jan 10;15(2):451. doi: 10.3390/cancers15020451.
Endometrial cancer is the most common female genital tract malignancy in developed countries that occurs predominantly in postmenopausal women. The primary objective of our research was to investigate whether menopause status together with selected conventional prognostic indicators may contribute to overall (all-cause) survival in endometrial cancer patients. For this purpose, we applied the Cox proportional hazards regression model. Patients in advanced FIGO stage showed a relatively poor survival rate. The time since last menstruation and postoperative FSH concentration were identified as unfavorable prognostic factors in our model. Additionally, age at diagnosis, BMI value, adjuvant treatment (brachytherapy), and parity showed no impact on survival. To our knowledge, this is the first study to report a prognostic model for endometrial cancer including exact time from last menstruation as one of the prognostic variables. Due to the fact that there are no stratifying systems to reliably predict survival in patients with endometrial cancer, there is a strong need to revise and update existing models using complementary prognostic indicators. Collection of precise data on various risk factors may contribute to increased accuracy of artificial intelligence algorithms in order to personalize cancer care in the near future.
子宫内膜癌是发达国家最常见的女性生殖道恶性肿瘤，主要发生在绝经后女性中。我们研究的主要目的是调查绝经状态以及选定的传统预后指标是否有助于子宫内膜癌患者的总（全因）生存率。为此，我们应用了Cox比例风险回归模型。国际妇产科联盟（FIGO）晚期患者的生存率相对较低。末次月经时间和术后促卵泡生成素（FSH）浓度在我们的模型中被确定为不良预后因素。此外，诊断时年龄、体重指数（BMI）值、辅助治疗（近距离放疗）和产次对生存率没有影响。据我们所知，这是第一项将末次月经的确切时间作为预后变量之一来报告子宫内膜癌预后模型的研究。由于目前没有可靠预测子宫内膜癌患者生存率的分层系统，因此迫切需要使用补充性预后指标来修订和更新现有模型。收集各种风险因素的精确数据可能有助于提高人工智能算法的准确性，以便在不久的将来实现癌症护理的个性化。
