Elsevier

Annals of Epidemiology

Volume 27, Issue 10, October 2017, Pages 672-676
Annals of Epidemiology

Review article
Faulty BRCA1, BRCA2 genes: how poor is the prognosis?

https://doi.org/10.1016/j.annepidem.2017.09.005Get rights and content

Abstract

We take a critical look at the meaning behind the number 87% given to 25-year-old Sophie, a BRCA1 and BRCA2 carrier. Sophie has been told she has an 87% chance of getting breast cancer. She is contemplating a preventive double mastectomy after genetic counseling and her physician's advice. Some 92% of British general practitioners are in favor of prophylactic mastectomy as a treatment option for women similar to Sophie. The treatment decision results, to a very large extent, from the size of the number (87%) alone. The central argument of this study is that physicians, their patients, and the public need a much better understanding on what is meant by probability estimates of 0.87. The figure on its own does not tell us much, and we need to be very cautious in its interpretation. It is important to know that the very same genetic and statistical models, and observed data, resulting in a verdict of an 87% lifetime chance of getting breast cancer, based on BRCA1, BRCA2, and familial information, simultaneously show Sophie to have a greater than 99% chance of surviving beyond the next 5 years cancer free. If she succeeds—the chances are overwhelmingly in her favor—then, given that fact, her chances of surviving a further 5 years are once again greater than 98%. Her chances of not dying due to breast cancer over the next 20 years are greater than 97%, a percentage that changes little if instead of 20 we write the number 30. In a word, although the diagnosis of a faulty BRAC gene may be a disappointment, there is no immediate peril and no need for undue alarm. Sophie, and her primary care providers, can carefully consider her options without feeling that they are under any kind of acute pressure. Whatever the threat, it is not an imminent one.

Introduction

Cancer centers throughout the United States, and, almost certainly, a number of other countries have recently registered a significant increase in demand by women to be tested for the presence of one or two of the genes associated with breast cancer, BRCA1 and BRCA2. The publicity surrounding the elective preventive mastectomy of the well-known actress, Angelina Jolie, will at least in part have contributed to this phenomenon. Other recent highly visible cases—former X Factor judge, Sharon Osbourne, that of Allyn Rose, Miss Maryland, USA, Miss District of Columbia, and a Miss America contestant—have put the spotlight on the question of prophylactic surgery for carriers. In this study, we consider the case of Sophie, a 25-year-old carrier of BRCA1 and BRCA2, who has been advised to undergo a prophylactic mastectomy. According to the U.K.'s National Health Service, a woman with a faulty gene has a 0.5 to 0.85 probability of developing breast cancer. This figure prompted Ms. Osbourne to say that choosing the surgery was a “no-brainer.” One supporter, 38-year-old Emma Parlons who underwent the procedure 3 years ago, made the observation “if somebody said your flight was 87% likely to come down, you wouldn't get on that plane.” Dr. Manny Alvarez, senior medical consultant for Fox News, summarizes Ms. Jolie's decision as “a courageous one, but also likely the right one.” Some 92% of British general practitioners are in favour of prophylactic mastectomy as a treatment option for women similar to Sophie [1]. There appears to be a strong consensus. However …

After a test for the presence of BRCA1 and BRCA2, any woman—in most cases perfectly healthy up to this point—will need to make a decision about what to do next. This decision will be made, for the most part, on the basis of a number given to her. The number lies between 0 and 1 and, in the case of Sophie, was equal to 0.87. As usual, the woman (at this point, we might refer to her already as a patient) and her physician will be involved in any such decision. In addition, at least one other party will be involved in the initial discussions, her genetic counselor. Depending on the outcome of discussions between these three, then others, such as clinical oncologists, surgeons in particular, as well as cosmetic reconstruction surgeons, will become part of a team providing care for Sophie.

What is unusual—unprecedented in the history of medicine until very recent times—is that “treatment” decisions for someone otherwise perfectly healthy are being based on a simple number not measuring any clinical or physiological characteristic, a number described as a probability when on the scale (0,1) and, otherwise, as a percentage when rescaled by multiplying by 100. Other factors of course will have led, in several cases, the woman to consult in the first place, for example, a belief that the incidence rate of breast, or other, cancers among relatives is higher than that might be expected under an assumption of a random distribution throughout the population. This is not an easy concept to understand and we return to it below. But, whatever the woman's initial perceptions leading her to consult, her ultimate decision, mindful of the advice given by her physician and genetic counselor, will be guided by the number lying between zero and one. All three people await the calculation of this number by genetic experts, and genetic epidemiologists and, finally, when the verdict is in, this number—let's call it θ where 0<θ<1—will be the overwhelming deciding factor on what to do next. If θ is close to 1, as it is for Sophie, then the sentiment is that some kind of preventive action is required.

Section snippets

Lifetime risks

What though does the number given by θ mean? How can we interpret or put any meaning on this value? The number is in fact very difficult to interpret, and this is no less true for a professional mathematician, probabilist, or statistician than for a carrier and her carers. So difficult is this number to interpret, it can be argued, that, on its own, the actual assumed value of the number is close to being meaningless, at least in everyday usage. It is, in any event, not the probability it is

What is not meant by “a lifetime risk of 0.87?”

Let us consider how Sophie will most likely interpret the 87% chance she has of getting breast cancer. We give three interpretations of this number below, the first corresponding to Sophie's instinctive reaction while the other two were explained to her by a friend, a straight A student who got the maximum grades on all her probability and statistics courses.

  • 1.

    Sophie believes that she is in imminent danger. 87% is not far from 100% and so this is something almost certain and something that is

Risks, probabilities, and competing risks model

The hazard rate, λ(t), also referred to as the age-specific failure rate, the instantaneous failure rate, the risk function, or the force of mortality, describes, in a particular way, the distribution of the random variable T, the time until a breast cancer is observed. When nothing else gets in the way, that is, the only cause of death is breast cancer, then the probability that the incidence of breast cancer occurs before time t is given by F(t)=1exp{Λ(t)} where Λ(t)=0tλ(u)du. In practice,

Probability estimates based on registry data

Equation 1 is the basis for estimating probabilities of cancer incidence over given periods. Cancer registry data, such as the SEER [4] data set, provide for the numbers exposed to risk of breast and other cancers and the number of cases observed during those 5-year intervals. These two numbers provide the numerator and the denominator to our conditional probability estimates. We can first use Table 1 to confirm that the widely quoted figure of one woman in eight will have breast cancer in her

Understanding a personalized risk or probability from screening

Sophie and her advisors need more information on the nature of probabilities, life tables, and the simple calculus of probability before putting too much reliance on a number such as 0.87 alone. Rather than lifetime risk, it would be helpful to provide Sophie with much shorter risk assessments such as the 5-year risk starting today at age 25 years, and then, assuming that she does make it to age 30 years without being incident, what are the chances of making it to 35. Such calculations are

Conclusion

Our argument is that the number 87%, for lifetime risk, given to Sophie does not mean very much. On its own, it tells us close to nothing. It cannot even be calculated without making an appeal to a very theoretical and abstract model for survival data, the so-called competing risks model. The difficulties in interpreting this number for lifetime risk should be fully explained to BRCA1 and BRCA2 carriers considering their health options. Estimated probabilities over much shorter time intervals

Acknowledgments

The author would like foremost to acknowledge the support and constant critical input of his colleague, Alexia Iasonos. Several other colleagues have provided valuable input, in particular Patrick Boulongne, Philippe Broet, Pat Kosyl, Philippe Flandre, Mithat Gonen, Daniel Pierre-Loti Viaud. Finally, the author would like to acknowledge the support of the journal and its reviewers for their careful reviews and very helpful suggestions that have led to a clearer presentation.

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