Development of an ovarian cancer screening decision model that incorporates disease heterogeneity - Havrilesky - 2010 - Cancer - Wiley Online Library

Development of an ovarian cancer screening decision model that incorporates disease heterogeneity†
Implications for potential mortality reduction

1. Laura J. Havrilesky MD, MHSc1,*,‡,
2. Gillian D. Sanders PhD2,3,4,
3. Shalini Kulasingam PhD5,6,
4. Junzo P. Chino MD7,
5. Andrew Berchuck MD1,
6. Jeffrey R. Marks PhD8,
7. Evan R. Myers MD, MPH2,9

Article first published online: 13 DEC 2010

DOI: 10.1002/cncr.25624

Copyright © 2010 American Cancer Society

Havrilesky, L. J., Sanders, G. D., Kulasingam, S., Chino, J. P., Berchuck, A., Marks, J. R. and Myers, E. R. , Development of an ovarian cancer screening decision model that incorporates disease heterogeneity. Cancer, n/a. doi: 10.1002/cncr.25624

Author Information

1. 1 Division of Gynecologic Oncology, Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina
2. 2 Duke Evidence Based Practice Center, Duke University Medical Center, Durham, North Carolina
3. 3 Duke Clinical Research Institute, Duke University Medical Center, Durham, North Carolina
4. 4 Department of Medicine, Duke University Medical Center, Durham, North Carolina
5. 5 Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota
6. 6 School of Public Health, University of Minnesota, Minneapolis, Minnesota
7. 7 Department of Radiation Oncology, Duke University Medical Center, Durham, North Carolina
8. 8 Department of Surgery, Duke University Medical Center, Durham, North Carolina
9. 9 Division of Clinical and Epidemiological Research, Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina

Email: Laura J. Havrilesky MD, MHSc (havri001@mc.duke.edu)

*Correspondence: Laura J. Havrilesky MD, MHSc, Department of Obstetrics and Gynecology, Box 3079, Department of Obstetrics and Gynecology, Duke University Medical Center, Durham NC 27710

1. † See editorial on pages 000–000, this issue.
2. ‡ Fax: (919)694-8719

Publication History

1. Article first published online: 13 DEC 2010
2. Manuscript Accepted: 16 JUL 2010
3. Manuscript Revised: 15 JUL 2010
4. Manuscript Received: 3 MAY 2010


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Keywords:

* ovarian carcinoma;
* phenotype;
* screening;
* simulation model

Abstract
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. © 2010 American Cancer Society.
Development of an ovarian cancer screening decision model that incorporates disease heterogeneity - Havrilesky - 2010 - Cancer - Wiley Online Library



GINECOLOGÍA
Actualidad Ultimas noticias - JANOes
Para reducir la mortalidad por cáncer de ovario debería mejorarse en la prevención

JANO.es · 27 Diciembre 2010 09:16

Un trabajo publicado en "Cancer" señala que hasta que no se desarrollen pruebas de detección más sensibles, otras estrategias como una mejor prevención y tratamiento son necesarias para reducir significativamente la cifra de muertes.


Un estudio reciente, publicado en Cancer ha hallado que la evaluación del cáncer de ovario disponible reduce apenas ligeramente la cantidad de muertes a causa de la enfermedad. Hasta que no se desarrollen pruebas de detección más sensibles, otras estrategias, como mejor prevención y tratamiento, son necesarias para reducir significativamente las muertes por cáncer de ovario, aseguraron los investigadores del Duke University School of Medicine (Estados Unidos).

El equipo del estudio utilizó un modelo informático de la progresión del cáncer de ovario para valorar la manera en que la evaluación efectiva reduce las muertes por causa de la enfermedad. El modelo tuvo en cuenta que algunos tipos de cáncer de ovario se desarrollan lentamente, mientras que otros lo hacen con más rapidez.

La evaluación anual conduce apenas a una reducción modesta de las muertes por cáncer de ovario, según halló el estudio. "Si suponemos que los cánceres de ovario se desarrollan y se propagan a velocidades distintas, la mejor estrategia de evaluación disponible únicamente reducirá la cantidad de mujeres que mueren por causa de este cáncer en 11%. Esto se debe parcialmente a que los cánceres de desarrollo más lento tienen más probabilidades de ser detectados por una prueba de detección", aseguró en un comunicado de prensa en la revista la Dra. Laura Havrilesky, investigadora principal del equipo.

Los hallazgos apoyan la opinión ampliamente aceptada de que muchos cánceres de ovario permanecen en sus etapas iniciales durante largo tiempo, mientras que los de etapa avanzada tienden a propagarse rápidamente.


Cancer 2010;DOI:10.1002/cncr.25624
Development of an ovarian cancer screening decision model that incorporates disease heterogeneity - Havrilesky - 2010 - Cancer - Wiley Online Library

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