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In Reply

Departments of Oncology, Biostatistics, and Pathology, Johns Hopkins University, Baltimore, MD

Sining Chen

Departments of Environmental Health Sciences and Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD

We agree with De Bock et al that it is important to further explore whether and how penetrance may vary across clinical populations, and that reliable population-specific risk estimates would have a positive impact on counseling practice. Our study¹ is not to belittle the importance of this endeavor, but to provide reasonable compromises to be used in risk assessment while these questions are being addressed.

A possible source of study heterogeneity raised by De Bock et al is a decreasing temporal trend in the estimated penetrances. In Figure 1 in Chen et al,¹ we arranged studies chronologically so readers could form an opinion about this issue. The earliest study yielded higher estimates than the remainder in several age strata. Beyond this observation, however, we find it difficult to detect a clear temporal pattern. A recent population-based study by Risch et al² estimated breast cancer risk of BRCA1 mutation carriers by age 80 at 0.90 (95% CI, 0.77 to 0.97). This further questions the association between risk estimates and year of publication. Similar considerations apply to other sources of heterogeneity examined by the original article, which suggests that we are still at a time when a combined estimate is likely to be useful.

Estimates of the risk of breast cancer for BRCA1 by age 70 range from 0.36 to 0.71. What should a counselor do in the face of this variation? Select one of the estimates according to study characteristics, consider all studies, and present a range or risks, or rely on a compromise? Our software in BayesMendel supports all three options.³ Selecting one of the estimates may open the door to improved tailoring, but may also be prone to errors and arbitrariness. Presenting all estimates has the advantage of being thorough about variation, but the challenge of communicating this variation and properly incorporating it into decision making can be daunting. This leaves a broad range of situations where one size, although it may not fit all, can be currently practical to many.

AUTHORS' DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST

The author(s) indicated no potential conflicts of interest.

REFERENCES

1. Chen S, Parmigiani G: Meta-analysis of BRCA1 and BRCA2 penetrance. J Clin Oncol 25:1329-1333, 2007[Abstract/Free Full Text]

2. Risch HA, McLaughlin JR, Cole DEC, et al: Population BRCA1 and BRCA2 mutation frequencies and cancer penetrances: A kin-cohort study in Ontario, Canada. J Natl Cancer Inst 98:1694-1706, 2006[Abstract/Free Full Text]

3. Chen S, Wang W, Broman K, et al: BayesMendel: An R environment for Mendelian risk prediction. Stat Appl Genet Mol Biol 3: Article 21, 2004

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Related Correspondence

• One Risk Fits All?
  Geertruida H. De Bock, Marian J.E. Mourits, and Jan C. Oosterwijk
  JCO 2007 25: 3383-3384 [Full Text]

This Article 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 Alert me to new issues of the journal Save to my personal folders Download to citation manager Rights & Permissions Citing Articles Citing Articles via Google Scholar Google Scholar Articles by Parmigiani, G. Articles by Chen, S. Search for Related Content PubMed Articles by Parmigiani, G. Articles by Chen, S. Related Articles Related Correspondence Social Bookmarking                            What's this?