Originally published as JCO Early Release 10.1200/JCO.2008.17.3914 on December 1 2008

This Article Full Text Full Text (PDF) Purchase Article View Shopping Cart Alert me when this article is cited Alert me if a correction is posted Services Email this article to a colleague Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Save to my personal folders Download to citation manager Rights & Permissions Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Ozanne, E. M. Articles by Belkora, J. Search for Related Content PubMed PubMed Citation Articles by Ozanne, E. M. Articles by Belkora, J. Social Bookmarking                            What's this?

Sensitivity to Input Variability of the Adjuvant! Online Breast Cancer Prognostic Model

Elissa M. Ozanne, Dejana Braithwaite, Karen Sepucha, Dan Moore, Laura Esserman, Jeffrey Belkora

From the Institute for Technology Assessment and Health Decision Research Unit, Massachusetts General Hospital, Harvard Medical School, Boston, MA; and the Departments of Biostatistics and Epidemiology and Surgery, University of California at San Francisco, San Francisco, CA

Corresponding author: Elissa M. Ozanne, PhD, Institute for Technology Assessment at Massachusetts General Hospital, 101 Merrimac St, 10th Fl, Boston, MA 02114; e-mail: elissa{at}mgh-ita.org

Purpose Adjuvant! Online (www.adjuvantonline.org) is a software model that predicts the benefit of adjuvant therapy for women with early-stage breast cancer. The model has been validated, is widely consulted, and has been shown to influence patient choices in the clinical setting. Adjuvant! requires the clinician to input patient age, tumor size, grade, hormone receptor status, number of positive lymph nodes, and comorbidity level. Because comorbidity is strongly and independently associated with survival, this study tested the hypothesis that Adjuvant! predictions would be sensitive to comorbidity inputs.

Methods Investigators used single-variable deterministic sensitivity analysis to evaluate the effect of varying each input of the model independently for three representative case examples based on National Comprehensive Cancer Network guidelines (NCCN). The main outcome of interest was 10-year mortality prediction.

Results The analyses show that Adjuvant!'s 10-year mortality predictions are most sensitive to patients’ comorbidity levels and the extent of nodal involvement for the cases, particularly among older women. Comorbidity was the most influential input except in younger women, aged 40 years.

Conclusion The Adjuvant! model is sensitive to patient comorbidity, and impact on the model outputs are significant enough that they are likely to affect physician recommendations and patients’ treatment choices. For example, incorrect assessments of comorbidities could lead physicians to overtreat or undertreat a patient who is in a gray zone relative to the NCCN guidelines. These results point to the importance of accurately assessing comorbidities in patients with breast cancer when using Adjuvant! and highlight the need for a standardized process of comorbidity ascertainment.

published online ahead of print at www.jco.org on December 1, 2008

Supported in part by Grant No. MRSG112037 from the American Cancer Society E.M.O.).

Presented in part at the 4th International Shared Decision Making Conference, May 30-June 1, 2007, Freiburg, Germany.

Authors’ disclosures of potential conflicts of interest and author contributions are found at the end of this article.

CiteULike    Complore    Connotea    Del.icio.us    Digg    Facebook    Reddit    Technorati    Twitter    What's this?

This article has been cited by other articles:

				P. G. Morris, H. L. McArthur, C. T. Dang, and C. A. Hudis Selection of Appropriate Patients for Anthracycline Therapy ASCO Educational Book, January 1, 2009; 2009(1): 11 - 18. [Abstract] [Full Text] [PDF]