Development of an Ovarian Cancer Screening Decision Model That Incorporates Disease Heterogeneity Implications for Potential Mortality Reduction

被引:27
作者
Havrilesky, Laura J. [1 ]
Sanders, Gillian D. [2 ,3 ,4 ]
Kulasingam, Shalini [5 ,6 ]
Chino, Junzo P. [7 ]
Berchuck, Andrew [1 ]
Marks, Jeffrey R. [8 ]
Myers, Evan R. [2 ,9 ]
机构
[1] Duke Univ, Med Ctr, Dept Obstet & Gynecol, Div Gynecol Oncol, Durham, NC 27710 USA
[2] Duke Univ, Med Ctr, Duke Evidence Based Practice Ctr, Durham, NC 27710 USA
[3] Duke Univ, Med Ctr, Duke Clin Res Inst, Durham, NC 27710 USA
[4] Duke Univ, Med Ctr, Dept Med, Durham, NC 27710 USA
[5] Univ Minnesota, Div Epidemiol & Community Hlth, Minneapolis, MN USA
[6] Univ Minnesota, Sch Publ Hlth, Minneapolis, MN USA
[7] Duke Univ, Med Ctr, Dept Radiat Oncol, Durham, NC 27710 USA
[8] Duke Univ, Med Ctr, Dept Surg, Durham, NC 27710 USA
[9] Duke Univ, Med Ctr, Dept Obstet & Gynecol, Div Clin & Epidemiol Res, Durham, NC 27710 USA
关键词
ovarian carcinoma; phenotype; screening; simulation model; K-RAS PROTOONCOGENE; EPITHELIAL TUMORS; GENE-EXPRESSION; MUTATIONS; CHARACTERIZE; CATENIN; STAGE; BORDERLINE; CARCINOMAS; PATTERNS;
D O I
10.1002/cncr.25624
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. Cancer 2011;117:545-53. (C) 2010 American Cancer Society.
引用
收藏
页码:545 / 553
页数:9
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