Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina 27710, USA.
Cancer. 2011 Feb 1;117(3):545-53. doi: 10.1002/cncr.25624. Epub 2010 Dec 13.
Pathologic and genetic data suggest that epithelial ovarian cancer may consist of indolent and aggressive phenotypes. The objective of the current study was to estimate the impact of a 2-phenotype paradigm of epithelial ovarian cancer on the mortality reduction achievable using available screening technologies.
The authors modified a Markov model of ovarian cancer natural history (the 1-phenotype model) to incorporate aggressive and indolent phenotypes (the 2-phenotype model) based on histopathologic criteria. Stage distribution, incidence, and mortality were calibrated to data from the Surveillance, Epidemiology, and End Results Program of the US National Cancer Institute. For validation, a Monte Carlo microsimulation (1000,000 events) of the United Kingdom Collaborative Trial of Ovarian Cancer Screening (UKCTOCS) multimodality prevalence screen was performed. Mortality reduction and positive predictive value (PPV) were estimated for annual screening.
In validation against UKCTOCS data, the model-predicted percentage of screen-detected cancers diagnosed at stage I and II was 41% compared with 47% (UKCTOCS data), and the model-predicted PPV of screening was 27% compared with 35% (UKCTOCS data). The model-estimated PPV of a strategy of annual population-based screening in the United States at ages 50 to 85 years was 14%. The mortality reduction using annual postmenopausal screening was 14.7% (1-phenotype model) and 10.9% (2-phenotype model). Mortality reduction was lower with the 2-phenotype model than with the 1-phenotype model regardless of screening frequency or test sensitivity; 68% of cancer deaths are accounted for by the aggressive phenotype.
The current analysis suggested that reductions in ovarian cancer mortality using available screening technologies on an annual basis are likely to be modest. A model that incorporated 2 clinical phenotypes of ovarian carcinoma into its natural history predicted an even smaller potential reduction in mortality because of the more frequent diagnosis of indolent cancers at early stages.
病理和基因数据表明，上皮性卵巢癌可能由惰性和侵袭性表型组成。本研究的目的是估计上皮性卵巢癌的两表型范式对利用现有筛查技术实现的死亡率降低的影响。
作者根据组织病理学标准，在上皮性卵巢癌自然史的马尔可夫模型（单表型模型）的基础上，修改为纳入侵袭性和惰性表型（两表型模型）。分期分布、发病率和死亡率均根据美国国立癌症研究所监测、流行病学和最终结果计划的数据进行校准。为了验证，对英国卵巢癌筛查合作试验（UKCTOCS）多模式患病率筛查的蒙特卡罗微模拟（100 万次事件）进行了 100 万次模拟。对每年筛查的死亡率降低和阳性预测值（PPV）进行了估计。
在与 UKCTOCS 数据的验证中，模型预测的筛查诊断为 I 期和 II 期的癌症比例为 41%，而 UKCTOCS 数据为 47%；模型预测的筛查 PPV 为 27%，而 UKCTOCS 数据为 35%。在美国，50 岁至 85 岁人群每年进行人群筛查的策略的模型估计 PPV 为 14%。使用绝经后每年筛查的死亡率降低率为 14.7%（单表型模型）和 10.9%（两表型模型）。无论筛查频率或测试敏感性如何，两表型模型的死亡率降低均低于单表型模型；侵袭性表型占癌症死亡的 68%。
目前的分析表明，使用现有的筛查技术，每年降低卵巢癌死亡率的幅度可能较小。一个将上皮性卵巢癌的两种临床表型纳入其自然史的模型预测，由于更频繁地在早期诊断出惰性癌症，死亡率降低的可能性更小。
