The BOADICEA model of genetic susceptibility to breast and ovarian cancer

Antoniou, Antonis C.; Pharoah, Paul; Smith, Paul J.; Easton, Douglas F.

doi:10.1038/sj.bjc.6602175

Cited by 421 publications

(341 citation statements)

References 40 publications

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“…The BOADICEA model of genetic susceptibility to breast and ovarian cancer was developed using complex segregation analysis of breast and ovarian cancer (Antoniou et al, 2002(Antoniou et al, , 2004. We agree with van Asperen et al that as it stands, the model is not easy to use in clinical practice.…”

Section: Sirsupporting

confidence: 69%

“…In the updated version, the average risk of breast cancer in BRCA1 mutation carriers by age 70 varies between 50 and 59% depending on the year of birth. Applying the latest version of the model to the family in Figure 2 of Antoniou et al (2004), the 40-year-old woman is predicted to carry a BRCA1 mutation with probability 41% and a BRCA2 mutation with a probability 1% (very similar to the previous estimates). However, her predicted risk of developing breast cancer by age 70 is now higher, 28%, perhaps closer to the expectations of van Asperen and co-workers.…”

Section: Sirsupporting

confidence: 67%

“…For a clinician, this risk estimation is hard to understand and feels illogical. It seems that in the risk prediction by Antoniou et al (2004) the presence of ovarian cancer is not important for the estimation of the breast cancer risk for this woman. The authors did not discuss this point.…”

Section: Sirmentioning

confidence: 94%

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Remarks on the BOADICEA model of genetic susceptibility to breast and ovarian cancer

2005

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With much interest we read the paper by Antoniou and colleagues (British Journal of Cancer, October 18, p 1580). These researchers described the development of a genetic model for familial breast cancer, named BOADICEA, which takes into account the simultaneous effects of BRCA1, BRCA2 and other genes. There is a considerable need for such predictions for purposes of management of women referred to genetic clinics and for the considerations of eligibility of any prophylactic interventions in both the clinical and research settings.The BOADICEA model requires a computer program for risk estimation, which is not easy to use in clinical practice. Moreover, such a model is mostly hard to understand for clinicians. Understandable risk estimation should, however, be available to clinicians, so that they know what they are actually doing while estimating disease risks. Our concern about this aspect of the BOADICEA model was illustrated in Figure 3. The authors presented a woman aged 40 years and unaffected with cancer. Her mother and maternal aunt developed ovarian cancer and two other maternal aunts developed breast cancer before the age of 50 years. This family is a good example of a typical Hereditary Breast and Ovarian Cancer (HBOC) family. The risk for breast cancer in these families is increased because of the combination of both breast and ovarian cancers in the family, which highly points to BRCA1 mutations. The BRCA1 mutation probability as predicted by the BOADICEA model is high, 40.9%. The model then predicted her risk of breast cancer at only 13%. For a clinician, this risk estimation is hard to understand and feels illogical. It seems that in the risk prediction by Antoniou et al (2004) the presence of ovarian cancer is not important for the estimation of the breast cancer risk for this woman. The authors did not discuss this point.Recently, Jonker et al (2003) have published a genetic model to predict someone's breast cancer risk based on the family history of breast and ovarian cancer. This model can be considered as an extension of the Claus model combined with the BRCAPRO model (Claus et al, 1991;Parmigiani et al, 1998). In the Jonker et al model, the familial clustering of breast and ovarian cancer is explained by three genes, BRCA1, BRCA2 and a hypothetical third gene BRCAu. This third gene was modelled to explain all familial clustering of breast cancer unaccounted for by the BRCA1 and BRCA2 genes. The model parameters were estimated using published estimates of population incidence and relative risks.As well as the BOADICEA model, the Jonker et al model is not easy to use in clinical practice. For this reason, we extended the easy-to-use Claus tables into the 'Claus plus method' based on the Jonker model (Claus et al, 1994;Van Asperen et al, 2004). Our method uses the Claus tables, but also incorporates information on the presence of ovarian cancer, bilateral breast cancer and whether there are more than two affected relatives. The formula we obtained simplifies risk estimation in familial breast ca...

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Section: Sirsupporting

confidence: 69%

Section: Sirsupporting

confidence: 67%

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Remarks on the BOADICEA model of genetic susceptibility to breast and ovarian cancer

2005

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“…They found the best discriminator between carriers and non carriers was BRCAPRO, and this could be enhanced by incorporating pathology data. Antoniou et al [21] studied 195 French-Canadian probands and compared predicted carrier probabilities under the BOADICEA [27] and BRCAPRO computer models. They found, as we did, that BRCAPRO over-predicted carriers with high predicted probabilities.…”

Section: Discussionmentioning

confidence: 99%

Predicting BRCA1 and BRCA2 gene mutation carriers: comparison of LAMBDA, BRCAPRO, Myriad II, and modified Couch models

Lindor

Apicella

et al. 2007

Familial Cancer

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Context-Models have been developed to predict the probability that a person carries a detectable germline mutation in the BRCA1 or BRCA2 genes. Their relative performance in a clinical setting is unclear.Objective-To compare the performance characteristics of four BRCA1/BRCA2 gene mutation prediction models: LAMBDA, based on a checklist and scores developed from data on Ashkenazi Jewish (AJ) women; BRCAPRO, a Bayesian computer program; modified Couch tables based on regression analyses; and Myriad II tables collated by Myriad Genetics Laboratories.Correspondence to: Noralane M. Lindor, nlindor@mayo.edu. NIH Public Access Author ManuscriptFam Cancer. Author manuscript; available in PMC 2010 September 3. Design and setting-Family cancer history data were analyzed from 200 probands from the Mayo Clinic Familial Cancer Program, in a multispecialty tertiary care group practice. All probands had clinical testing for BRCA1 and BRCA2 mutations conducted in a single laboratory.Main outcomes measures-For each model, performance was assessed by the area under the receiver operator characteristic curve (ROC) and by tests of accuracy and dispersion. Cases "missed" by one or more models (model predicted less than 10% probability of mutation when a mutation was actually found) were compared across models.Results-All models gave similar areas under the ROC curve of 0.71 to 0.76. All models except LAMBDA substantially under-predicted the numbers of carriers. All models were too dispersed.Conclusions-In terms of ranking, all prediction models performed reasonably well with similar performance characteristics. Model predictions were widely discrepant for some families. Review of cancer family histories by an experienced clinician continues to be vital to ensure that critical elements are not missed and that the most appropriate risk prediction figures are provided.

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“…In order to maximize both the efficiency of testing and the public health impact of a genetic screening program, many centers offer screening to women when the prior probability of finding a mutation is 10% or greater [7]. Several mathematical models such as BRCAPRO (http://astor.som.jhmi.edu/BayesMendel/brcapro.html) and the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) can be used to estimate the prior probability of carrying a mutation [8,9]. These models consider age of onset and family history of cancer.…”

Section: Genetic Screeningmentioning

confidence: 99%