Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, People's Republic of China,; Key Laboratory of Obstetrics and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, People's Republic of China.
Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, People's Republic of China,; Key Laboratory of Obstetrics and Gynecologic and Pediatric Diseases and Birth Defects of Ministry of Education, West China Second University Hospital, Sichuan University, Chengdu, People's Republic of China,.
Gynecol Oncol. 2021 Aug;162(2):339-344. doi: 10.1016/j.ygyno.2021.06.003. Epub 2021 Jun 17.
To externally validate the performance of the Mayo triage algorithm applied to treatment strategy management in advanced epithelial ovarian cancer (AEOC) patients.
AEOC patients who underwent primary debulking surgery (PDS) were included and were divided into two groups based on the Mayo triage algorithm: "high risk" and "triage appropriate". The surgery outcomes and complications of the patients were compared between the two groups.
179 consecutive AEOC patients were enrolled for analysis, including 32 patients in the high-risk group and 147 patients in the triage-appropriate group. The results showed that patients in the high-risk group were older, had worse physical status and had lower preoperative serum albumin than those in the triage-appropriate group (P<0.01). The high-risk group had a lower proportion of women who underwent intermediate/high complexity surgery (38% vs. 72%, P<0.01) as well as a lower proportion of women who underwent optimal resection (50% vs. 71%, P<0.05). Furthermore, the incidence of 30-day complications (28% vs. 5%, P<0.01) and the proportion of patients who were unable to undergo adjuvant chemotherapy after PDS (22% vs. 2%, P<0.01) were both significantly higher in the high-risk group than in the triage-appropriate group. In addition, compared to the triage-appropriate group, the 90-day mortality rate in the high-risk group was also notably higher, but the difference was not statistically significant (6% vs. 1%, P=0.15).
The validity of the Mayo triage algorithm for treatment decision-making in AEOC was externally confirmed in this study. This short-term complication assessment tool could be effectively used for the individualized primary management of high-risk AEOC patients. The feasibility of the Mayo triage algorithm for use in long-term management should be further explored.
对外验证 Mayo 分诊算法在高级别上皮性卵巢癌（AEOC）患者治疗策略管理中的应用效能。
纳入接受初次肿瘤细胞减灭术（PDS）的 AEOC 患者，根据 Mayo 分诊算法分为“高危”和“分诊合适”两组。比较两组患者的手术结局和并发症。
共纳入 179 例连续 AEOC 患者进行分析，其中高危组 32 例，分诊合适组 147 例。结果显示，高危组患者年龄较大，身体状况较差，术前血清白蛋白水平较低（P<0.01）。高危组行中/高复杂度手术的患者比例较低（38% vs. 72%，P<0.01），行最佳减瘤术的患者比例较低（50% vs. 71%，P<0.05）。此外，高危组 30 天并发症发生率（28% vs. 5%，P<0.01）和 PDS 后无法接受辅助化疗的患者比例（22% vs. 2%，P<0.01）均显著高于分诊合适组。此外，与分诊合适组相比，高危组 90 天死亡率也明显更高，但差异无统计学意义（6% vs. 1%，P=0.15）。
本研究外部验证了 Mayo 分诊算法在 AEOC 治疗决策中的有效性。该短期并发症评估工具可有效用于高危 AEOC 患者的个体化初级管理。应进一步探索 Mayo 分诊算法在长期管理中的可行性。
