Department of Obstetrics and Gynecology, Division of Gynecologic Surgery, Mayo Clinic, Rochester, MN, United States.
Department of Health Sciences Research, Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN, United States.
Gynecol Oncol. 2020 Jun;157(3):572-577. doi: 10.1016/j.ygyno.2020.03.024. Epub 2020 Apr 1.
We previously reported an algorithm that identifies women at high risk of postoperative morbidity & mortality (M/M) as a tool to triage between neoadjuvant chemotherapy and primary surgery for epithelial ovarian cancer (EOC). We sought to independently validate its performance using multicenter data.
Women who underwent surgery for stage IIIC/IV EOC between 1/1/2014 and 12/31/2017 were identified from the National Surgical Quality Improvement Program database and classified as "high risk" or "triage appropriate" using our algorithm. Outcomes were compared between triage appropriate and high-risk women using the chi-square test.
1777 women met inclusion criteria; the mean age was 62.6 years and 81.9% had stage IIIC disease. Nationally, the surgical complexity scores were low (69.8% low, 25.2% intermediate and 5.0% high). "High risk" women had 2-fold higher rate of severe 30-day complication or death (6.2% vs 3.5%; p = 0.01), a 3-fold higher rate of 30-day mortality (1.4% vs 0.5%; p = 0.08), and a higher risk of death following a severe complication (11.1% vs. 0%, p = 0.11). A sensitivity analysis excluding women with unknown albumin who didn't meet other high risk criteria showed similar results: severe 30-day complications or death (6.2% vs 3.5%; p = 0.02) and 30-day mortality (1.4% vs 0.3%; p = 0.04) for "high risk" vs "triage appropriate" women.
Primary cytoreductive surgery to minimal residual disease remains the goal for EOC. We verify that our algorithm can identify women at risk of M/M using national multicenter data, despite a low complexity surgical setting and using 30-day mortality (vs. 90-day). Objective surgical risk assessment for ovarian cancer should be standard of care and can be incorporated into practice using the Mayo triage algorithm.
我们之前报道了一种算法,该算法可识别术后发病率和死亡率高的女性(M/M),作为对上皮性卵巢癌(EOC)新辅助化疗和直接手术进行分类的工具。我们试图使用多中心数据独立验证其性能。
从国家手术质量改进计划数据库中确定了 2014 年 1 月 1 日至 2017 年 12 月 31 日接受 IIIC/IV 期 EOC 手术的女性,并使用我们的算法将其分类为“高风险”或“分诊适当”。使用卡方检验比较分诊适当和高风险女性之间的结局。
1777 名女性符合纳入标准;平均年龄为 62.6 岁,81.9%为 IIIIC 期疾病。全国范围内,手术复杂程度评分较低(69.8%为低,25.2%为中,5.0%为高)。“高风险”女性严重 30 天并发症或死亡的发生率高 2 倍(6.2% vs 3.5%;p=0.01),30 天死亡率高 3 倍(1.4% vs 0.5%;p=0.08),严重并发症后死亡风险较高(11.1% vs. 0%,p=0.11)。排除不符合其他高风险标准且白蛋白未知的女性进行敏感性分析,结果相似:严重 30 天并发症或死亡(6.2% vs 3.5%;p=0.02)和 30 天死亡率(1.4% vs 0.3%;p=0.04),高风险女性 vs 分诊适当女性。
达到最小残留疾病的主要细胞减灭术仍然是 EOC 的目标。我们使用全国多中心数据验证了我们的算法可以识别有发生 M/M 风险的女性,尽管手术难度低且使用 30 天死亡率(而非 90 天)。卵巢癌的客观手术风险评估应成为标准护理,并可使用 Mayo 分诊算法将其纳入实践。