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. Author manuscript; available in PMC: 2011 Dec 1.
Published in final edited form as: J Nurs Healthc Chronic Illn. 2010 Dec;2(4):271–280. doi: 10.1111/j.1752-9824.2010.01068.x

SI RLTD: Risk Scores and Decision Making: The Anatomy of a Decision to Reduce Breast Cancer Risk

Christine Holmberg 1, Mary Daly 2, Worta McCaskill-Stevens 3
PMCID: PMC3124706  NIHMSID: NIHMS293783  PMID: 21731580

Abstract

Aim

To report the use of a risk score for risk treatment decision-making in women at risk for breast cancer in order to better understand their decision-making situation.

Background

Tamoxifen and Raloxifene are medications that have been proven to reduce the risk of breast cancer. However, women who understand their personal net benefit from Tamoxifen use chose not to take the medication. To understand this decision, the paper investigates the use of epidemiological risk information in the decision-making process for risk-reducing treatments.

Methods

The narratives of two women are analyzed as they recall their risk score and explain their decision-making process concerning participation in the Study of Tamoxifen and Raloxifene (STAR). Both in-depth interviews follow a narrative approach and were recorded in a U.S. cancer center in 2005.

Results

Thinking about risk by analyzing the chances of developing a disease is specific to complex decision-making situations. The associated risk-benefit analysis has to be conducted qualitatively as epidemiological risk information cannot know all details of a woman’s life. In addition, a woman’s decision is based on the perception of the condition as risk or as disease. Women are willing to treat risk that is perceived as disease, especially when it is based on bodily measurements on which the treatment has an effect. Women are not willing to treat a risk not perceived as disease.

Conclusion

The net benefit of a treatment as calculated based on epidemiological data cannot easily be translated onto an individual’s life. Thus, the complex experience of a woman’s life at risk is highly important in decision-making situations.

Relevance to clinical practice

The ambiguity of statistical risk estimates should be acknowledged and the women’s evaluation of her risk valued in risk treatment decision-making.

Keywords: Breast cancer, decision-making, qualitative study, risk assessment

INTRODUCTION

Many women worry about developing breast cancer. Women with a family history of the disease are especially concerned and may engage in frequent visits to their health care provider. There are only a few proven strategies for women to reduce the risk of breast cancer, among them prophylactic mastectomy, oophorectomy, and in the United States (US) chemoprevention with Tamoxifen or Raloxifene (Fisher et al. 1998, Hartmann et al. 1999, Rebbeck et al. 1999, Kauff et al. 2002, Rebbeck et al. 2002, Rebbeck et al. 2004, Vogel et al. 2006, Vogel et al. 2010). None of these interventions are without serious side-effects. The side effects of Tamoxifen and Raloxifene include an increased risk of uterine cancer and thromboembolic events. In addition, Tamoxifen increases the risk of cataracts. The risk profile of Raloxifene is overall lower than that of Tamoxifen but it may also not be as effective as Tamoxifen in long-term breast cancer risk reduction (Vogel et al. 2010). Women who are interested in one of the proven risk reduction strategies need to carefully assess which one may be most appropriate for them (Ozanne et al. 2006). In this paper we report an analysis of the use of breast cancer risk scores for decision-making about chemoprevention for breast cancer risk reduction.

BACKGROUND

Cancer centers in the U.S. often offer programs for women at increased risk for breast cancer to participate in regular screening, treatment counseling, and clinical studies. In these centers cancer risk scores are calculated during counseling. Risk scores are marketed as an opportunity to improve knowledge, decision-making, and preventive health behavior (Holmberg & Parascandola 2010), Muller-Riemenschneider et al. 2010, Freedman et al. 2005, Fosket 2004). Risk scores estimate the probability of an individual to develop a cancer over a certain time period (http://riskfactor.cancer.gov/cancer_risk_prediction/about.html). The Gail model (Costantino et al. 1999, Gail & Costantino 2001) is the most widely spread cancer risk assessment model in the U.S. (Fosket 2004, Holmberg & Parascandola 2010). It calculates the five-year risk for a woman to develop breast cancer based on the number of first degree female relatives with breast cancer, age at first live birth or nulliparity, number of benign breast biopsies, atypical hyperplasia, age at menarche, and race (Costantino et al. 1999). It was first developed to aid clinicians in their decision-making for women but is now widely used in the prevention setting (Fosket 2004).

The U.S. Food and Drug Administration has approved Tamoxifen use for breast cancer risk reduction in women with a Gail score of 1.7. or higher. Together with information on Tamoxifen, the Gail model was used to develop a risk-benefit index for Tamoxifen use in at risk women. To present the epidemiological risk-benefit index in a format that adheres to the best practices in health communication, the National Cancer Institute (NCI) conducted a risk communication workshop in 1999 (JNCI 1999). Based on the results of the workshop, the National Surgical Adjuvant Breast and Bowel Project (NSABP) developed a two-page handout to assist the decision-making process about Tamoxifen use for chemoprevention. The handout includes a calculation of the Gail score and a risk-benefit analysis of the use of Tamoxifen for chemoprevention. Women received the NSABP handout as part of the risk assessment for potential participation in the “Study of Tamoxifen and Raloxifene” (STAR) as an aide for deciding about STAR participation. STAR was a double-blind, randomized chemoprevention trial designed to determine whether Raloxifene or Tamoxifen is more effective in preventing breast cancer in postmenopausal women at increased risk of developing breast cancer (Vogel 2006).

Approximately two million US women are projected to have a net benefit from taking Tamoxifen preventively (Freedman 2003). Despite this large number of women who could potentially benefit from Tamoxifen intake, the uptake of breast cancer chemoprevention remains small (Waters et al. 2010). Considering that breast cancer is a concern for many women and that breast cancer risk is generally overestimated, this is surprising. However, it is consistent with studies that show that interest in preventive treatments is very low as soon as these have side effects, regardless of net benefit (Waters et al. 2007).

These findings may be explained by the difficulty people have in understanding the net benefit of a treatment since they have to combine the likelihood of positive and negative outcomes. This explanation suggests that women with a net benefit from Tamoxifen intake may not understand the information given to them. Numeracy is not very high in the general public (Fagerlin et al. 2007, Lipkus et al. 2001). It may also suggest that researchers and the lay public evaluate risk and benefits differently. This fact has been repeatedly established in risk perception research (Kahnemann et al. 1982, Irwin & Wynne 1996, Ropeik & Slovic 2003). A lot of effort is put into presenting objective epidemiological risk information in formats understandable to women at risk for breast cancer (Timmermans et al. 2008, Zikmund-Fisher et al. 2008, Kurz-Milcke et al. 2008, Hopwood et al. 2003). Health behavior theory suggests that risk perception plays an important part in health decision-making and it is assumed that once a net benefit is perceived health behavior may change (Becker 1974, Janz & Becker 1984, Leventhal et al. 1999). The thought then is that a better understanding of the epidemiological information will lead to better health decisions. Such an assumption disregards the different meanings the term risk has in the everyday life compared to in the scientific setting (Samerski 2002).

As Hay et al. (2005) have shown the relationship between decision-making and risk perception is more complex than health behavior theories suggest. Qualitative work has shown that a person’s understanding of epidemiological risk information is influenced by their feelings, intuitions, experiences of cancer, life-stage, sense of their own body, and the ways they are able to incorporate cancer risk into their identity (Lipworth et al. 2010). In what ways risk perception may influence decision-making will differ depending on what the trade-offs are. These trade-offs cannot be depicted in numerical values (Mills et al 2008, Hay et al. 2005). In a study on a decision-aid for Tamoxifen use in at risk women Fagerlin et al. (2010) show that the women are unwilling to take Tamoxifen for breast cancer risk reduction even if their knowledge about Tamoxifen and breast cancer risk are accurate. If a woman decides against chemoprevention after she understands the net benefit then we need to ask how the risk information is used in the decision-making process about breast cancer chemoprevention. Living a life at risk is all-encompassing. Thus a decision about risk treatment cannot be understood without understanding the context in which the decision is made (Hamilton et al. 2009).

The detailed analysis of the narratives of the two women in our case study shows that risk is not a concept that individuals use in their everyday life. Thinking about risk by analyzing the chances of developing a disease is specific to complex decision-making situations. The associated risk-benefit analysis has to be conducted qualitatively as epidemiological risk information cannot know all details of a woman’s life.

In addition, a woman’s decision is based on the perception of the condition as risk or as disease. A disease needs treatment, especially when it is based on bodily measurements on which the treatment has an effect. In the case of a disease neither of the women consider this a choice or a decision for them to make. When disease is a probability they have a choice, in which case they choose not to take medication.

AIM

This case study analyzes the narratives of two women recalling their risk score and explaining their decision-making process concerning STAR participation (Yin 2003).

METHOD

The case study is based on narrative theory (Good 1994, Bruner 1986, Ricoeur 1981). Narratives enable learning about what is important about a topic from the actor’s perspective (Brody 1988, Gerhardt 1990, Greenhalgh & Hurwitz 1999, Mattingly & Garro 2000). The case study captures the experience of living with breast cancer risk over time. In patient-centered studies the collection of personal stories is the most valuable source for understanding the experience of an event (Thomas 2009, Kleinman 1988). Thus, to conceptualize and understand the meaning of the risk scores for decision-making from the perspective of those considered at risk, narratives are particularly useful.

DATA COLLECTION

The narratives of the two women were chosen from a sample of 40 interviews with women who considered participation in STAR. These were collected in 2005. For the purpose of this study, we needed to be certain that the women understood their statistical risk for developing breast cancer over the next five years. Only in two of the 40 narratives the Gail score was remembered correctly and incorporated into the decision-making process. Thus in both narratives we can be certain that the women knew their numerical risk score.

Both women were recruited through an invitation letter followed by a phone call by C.H. who described the study and asked permission to interview them. C.H. did not know either of the women prior to the telephone conversation because she came from an outside institution. Rapport was established during the telephone conversation and both women were willing to be interviewed.

The in-depth interviews followed a narrative approach (Kohler Riessman 2008, Honer 1993). This means that each interview begins with the same question. The interview then evolves around the themes the interviewee brings into the conversation. The interviewer intervenes when necessary to move the conversation along (Kvale 1996). Both interviews were conducted one-on-one at the study site. The interviews were transcribed verbatim.

ETHICAL CONSIDERATIONS

Prior to data collection the study was reviewed and approved by the Institutional Review Board of the cancer center.

ANALYSIS

The analysis of the narratives included the contextualization of the decision-making, the justifications for the decisions, and the use of the risk score in the narratives. The analysis was conducted using MAXQDA, a software program for qualitative data (Kuckartz 2010). Both interviews first were coded with content codes relating to the research questions (Mayring 2007). Then generic and theoretical codes were developed from the findings of the content in each segment (Charmaz 2009). The analysis resulted in the generation of the following concepts: the meaning of being at risk, risk assessment and personal risk assessment, the conscious possibility of getting breast cancer, and treatment of the risk of coronary heart disease versus the treatment of breast cancer risk. Both women are very different from each other and tell unique stories about their lives, about their experiences and about their decision-making. Through these differences regarding the use of the risk score and the decision-making process in both narratives facets of the decision-making situation can be fleshed out that highlight the inherent problems of using risk scores for decision-making in an individual’s life.

FINDINGS

Sociodemographics

Mrs. Wiler is 73 years old and has a Gail score of 5.3. She has a mother who had breast cancer at age 75. She has a diagnosis of fibrocystic breasts and has had one biopsy approximately 40 years ago, when the second of her two daughters was born.

Mrs. Wiler has been going for twice-yearly breast exams and a yearly mammogram for the past 40 years. Mrs. Wiler is the only one in the sample of 40 women who remembers her risk estimate correctly without checking her records.

Mrs. Wayne is 52 years old and has a Gail score of 3.94. She has a mother and a sister who have had breast cancer. At the age of 25 she had a breast biopsy. After the biopsy she received twice yearly breast exams and a yearly mammogram. Since her sister’s diagnosis 10 years ago, her check-up schedule increased to a three-monthly cycle. Mrs. Wayne demonstrates a clear understanding of the nature of the risk assessment during the interview. She also has the print-outs of all her risk assessments with her and explains them during the interview.

Both women were patients of a family risk assessment program at a cancer center. The program provided counseling sessions to the women about their risk, has given them options for breast cancer risk reduction, and both women come to six-monthly screening appointments to the program. Women in the program fill out yearly questionnaires about their eating habits and other events in their lives and they have the opportunity to participate in a number of breast cancer related studies.

The meaning of being at risk

For Mrs. Wayne and Mrs. Wiler being at risk for breast cancer means a close, long-term relationship with the health care system. Both had a biopsy a long time ago and have been to twice yearly or more breast check-ups per year. Both have a family history of breast cancer albeit no breast cancer deaths in the family. Mrs Wayne’s biopsy and her mother’s breast cancer diagnosis coincided. Mrs. Wiler’s mother had breast cancer at an older age, an age that Mrs. Wiler now approaches. The possibility of developing breast cancer is more present in her mind. Though, both have thought about what it may mean to develop breast cancer, only Mrs. Wayne is seriously concerned about the disease at this point in time.

For a long time, these two women have lived with the conscious possibility of developing breast cancer and have managed their risk with regular breast checkups. Risk is a long-term process in both women’s lives, one that is only marginally influenced by receiving an epidemiologically derived risk score. Risk as the conscious possibility to get breast cancer has long been part of the two women’s lives. The epidemiological risk information they have received through the NSABP hand-out is just one piece in a life of being at risk for developing breast cancer.

Epidemiological risk assessment and personal risk assessment

Mrs. Wiler uses the epidemiological risk information given to her to decide about STAR participation. She accepts her Gail score and interprets five out of 100 to be a small risk. She does not evaluate the risk score or incorporate it into her life circumstances to create a personal risk assessment.

Mrs. Wayne in contrast reflects on her breast cancer risk beyond the epidemiological risk assessment of 3.94 given to her. She uses the term risk and discusses her potential breast cancer risk at length. While it was not possible for her to have genetic testing, she does believe that her genetic make-up may be different from her sister’s and mother’s. In her personal risk assessment, she includes possible genetic differences between herself and her family, her hormone replacement therapy (HRT), birth control pill use, and her current life circumstances. Thus, she integrates other breast cancer risk factors not included in the Gail model into her personal assessment of her chances of developing breast cancer and the consequences thereof. She compares her personal assessment with the risks of a possible Tamoxifen intake, which she associates with not only the known side-effects but with unknown ones and with the severe side-effects her sister experienced.

Risk and the conscious possibility of getting breast cancer

Mrs. Wiler in her narrative only talks about risk in relation to the Gail score. However, she does discuss the possibility of being diagnosed with breast cancer. Since she believes that breast cancer would be detected early and that current breast cancer treatments are effective, this is of little concern to her. In her decision-making about Tamoxifen, she explicitly refers to her Gail score that she considers being small. Thus, she sees no necessity in considering Tamoxifen further. Especially, because it is a medication and she already experiences severe side-effects from blood pressure medication she is taking.

Mrs. Wayne’s narrative on the other hand includes the term risk frequently. It is obvious that she does not want to take Tamoxifen. But she is also very concerned about a possible breast cancer diagnosis precisely because of the treatments available to her. Both her mother and her sister experienced severe side-effects from breast cancer treatment. This is the dilemma she is in. Tamoxifen is a breast cancer treatment, one under which her sister suffered. Now Tamoxifen is being offered to her to reduce her breast cancer risk. She does not want to take the medication but she is not sure if she may need its risk-reducing capabilities. For that reason Mrs. Wayne in contrast to Mrs. Wiler needs to qualify her risk further. For her, risk is important because precise knowledge about it may tell her something about her real chances of developing the disease and through that aid her in her decision about Tamoxifen.

The particular situation Mrs. Wayne is in highlights some of the structural aspects of decision-making situations based on epidemiological risk information. Mrs. Wayne is in a situation in which the decision may matter. Does she need the risk reduction from Tamoxifen or doesn’t she? This question can only be answered in hindsight. Probabilities are probabilities and not certainties. The one likelihood may be larger than the other one. But in her life the range of her risk will be one or zero. Whether the lower probability will be a zero risk in her life cannot be known by epidemiology. Thus, Mrs. Wayne is torn about the decision because there are too many unknowns on both sides of the argument. Through taking Tamoxifen she will not be able to reduce her breast cancer risk to zero and simultaneously will be adding new risks to her health.

Treatment of coronary heart disease risk versus treatment of breast cancer risk

Mrs. Wiler’s narrative shows that she perceives her high blood pressure as a condition that must be treated. She feels that she must lower her blood pressure and therefore accepts the severe side-effects she experiences from the medication. Her efforts to reduce her blood-pressure without medication have remained unsuccessful.

Mrs. Wayne contrasts her decision-making situation about Tamoxifen use for risk reduction with the clinical communication regarding the lowering of her cholesterol level. Her physician told her to take cholesterol-lowering medication. He gave her no choice in the matter. For breast cancer risk reduction she received a Gail score and a NSABP hand-out as the basis for making a decision. This situation is overwhelming for her because she is now given a choice, but with an option that confronts her with new risks that she needs to evaluate. Both women perceive the medication they take to reduce the risk of coronary heart disease, blood pressure and cholesterol level, to be necessary. This stands in contrast to their assessment of Tamoxifen. Both women perceive Tamoxifen to be an option but not a necessity. Both conclude that their breast cancer risk does not warrant treatment. Surveillance suffices the condition in this case.

DISCUSSION

Both women have a net benefit from taking Tamoxifen, but both women decide not to take the medication. Only one of them, Mrs. Wayne, conducts a risk-benefit analysis to help her make the decision. She struggles to make the decision because translating probabilities onto an individual life is very difficult. Mrs. Wiler finds a risk of five percent too low to take action, and therefore does not feel the need to go into a more detailed analysis of the risks and benefits involved. The term risk is not part of her narrative. However, she is aware that she may develop breast cancer, a fact she is braced for.

Epidemiological risk is a theoretical construct that does not correspond with the lifeworlds of people (Austin 2010, Sivell et al. 2008, Samerski 2002, Davison et al. 1991). Risk in everyday language means danger (Han et al. 2009a, Han et al. 2009b, Austin 2010). This is different from a perception that one may develop a disease. The perception of how likely it is for breast cancer to develop in one’s life is influenced by family history, benign breast disease, breast cancer worry, and perceived control (Spector et al. 2009). This is very different from a numerical risk value (Sivell et al. 2008). Based on the two narratives, we argue that the perception of the conscious possibility of getting a disease is conceptually different from the risk talked about and focused on in clinical risk communication research (Hay et al. 2005, Austin 2010).

We argue that thinking about risk by analyzing the chances of developing a disease is necessary only when complex decision-making situations arise in which severe risks exist both when you treat and when you do not treat (Samerski 2002). Only Mrs. Wayne is in this situation because she is worried enough about the disease that she wants to lower her risk as far as possible but is also very worried about the side-effects. She therefore incorporates the epidemiological risk information into her personal risk assessment. This is in line with what other studies have found on how the lay public deals with epidemiological risk information (Lipworth et al. 2010, Hay et al. 2005, Chalmers & Thomson 1996). The difference in the use of the term risk in both narratives is striking. In Mrs. Wiler’s narrative the term is practically absent. In Mrs. Wayne’s narrative it is omnipresent. It is omnipresent in that it defines her impossibility to make a choice about Tamoxifen based on risks.

Mrs. Wayne is very worried about developing breast cancer. She needs to rationalize why she does not take advantage of another risk-reducing strategy given to her. Studies that have looked at the choices people make about engaging in risky behavior have shown that when deciding to engage in risky behavior people need to rationalize their behavior by re-evaluating their risks (Hay et al. 2005, Werner-Lin 2007). One could argue that this is what Mrs. Wayne is doing. However, in addition Mrs. Wayne’s narrative shows something else. It highlights the structural aspect of the situation someone is put in who receives numbers in order to calculate a net benefit for herself.

Scientific notions of risk are based on scientific measurements and are probabilistic in nature (Beck 1987). Someone’s true risk cannot be known (Rothman & Greenland 1998) because all the individual information necessary can never be available. Risk ranges can only be attributed to a fraction of a population. An individual’s outcome can only be one or zero just as the flip of a coin. A calculated net benefit can only be true for a population, not for an individual (Holmberg & Parascandola 2010). Therefore, if a woman decides her breast cancer risk to be high enough to consider further action, it is reasonable for her to engage in a more detailed risk analysis and to conduct a personal, more qualitative risk assessment to evaluate her situation.

Ripley has shown that decisions are made in context (Ripley 2008): In the life context, with regards to different health care providers, in the context of a personal sense of the condition, and finally in the context of taking medications. Both women have had long-term experiences with taking medicines and this influences their decision profoundly. People act and react according to what they know and this in turn is based on their lived experiences; their knowledges and beliefs (Ziebland & Herxheimer 2008).

Both women live a life at risk for breast cancer, which means they have been going to breast check-ups twice yearly or more for a very long time. Breast cancer risk structures the women’s social relationships and their relation to the health care system (Kenen et al. 2003, Scott et al. 2005). In this long time period there were times with more worry than at the time of the interview. One’s sense of feeling at risk changes over time (Hamilton et al. 2009, Werner-Lin 2007, Chalmers & Thomson 1996) and the possibility of getting breast cancer is part of what their life is about. Both women have found ways to deal with this possibility which does not include medication. Both women have successful risk management in place at this time.

Living with a long-term risk of developing breast cancer profoundly affects the life experience and it has been compared to living a life with chronic illness (Kenen et al. 2003). It is within this context the decision is made.

The way both women talk about their experiences with medication is revealing about an aspect in risk-decision-making that has not been described before. It is the bodiliness of risk. Bodiliness of risk describes those risks that can be measured in one’s body as an objective, medical measurement.

In the two narratives this can be demonstrated by the comparison of blood pressure treatment and breast cancer risk treatment that both women make. This is a very interesting comparison because lowering blood pressure is a risk treatment as its intention is to treat the risk of heart disease (Stamler 1993, Britton et al. 2009). However, both women perceive it differently. For them it is necessary to lower blood pressure or cholesterol level. Indeed, most people today consider high blood pressure a disease (Moynihan et al. 2002). Just as the two women contend, this disease needs treatment. The intake of their blood pressure medication is not a choice and not a decision they had to make. This may be in part explained by a possible difference in the presentation by clinical staff. The treatment of breast cancer risk involves a counseling session on breast cancer risk and the potential treatments. This may not necessarily be the case in the treatment of coronary heart disease risk as Mrs. Wayne’s statement indicates.

However, another issue is strikingly different between the two risk scenarios. Blood pressure is a personal bodily measurement for which there is no room for interpretation. This is unlike the breast cancer risk assessments Mrs. Wayne and Mrs. Wiler have gone through. Their risk assessment is a calculated algorithm, not a bodily measurement. Mrs. Wayne’s narrative clearly demonstrates why this algorithm may not be the most appropriate risk measure for her (Holmberg & Parascandola 2010). The threshold when to lower blood pressure is based on medical population studies and has been defined by the medical community (Stamler et al. 1993, Rosendorff et al. 2007, Graham et al. 2007). The validity of a threshold could be part of negotiations between a health care provider and her patients, but a blood pressure measurement cannot be disputed. Similarly, the treatment of high blood pressure has a direct effect on the blood pressure level. If the treatment works, the blood pressure goes down. So while the treatment of high blood pressure treats the possibility of a future event heart disease and is a risk treatment, it has a measurable effect in the present. Thus a condition in the present is treated that can be measured in one’s body. By contrast the effect of Tamoxifen cannot be measured.

Case studies like this open up space to consider conceptual issues in decision-making about risk treatments. The importance of whether a condition is interpreted as risk or disease and its relationship to treatment decision-making in the prevention setting needs to be focused on in larger studies.

Strengths and limitations

In this paper we analyzed two narratives of women who understood the epidemiological risk information given to them. We were able to carve out the structural aspects of decision-making situations that arise because of epidemiological risk information. Such an analysis is only possible with small case studies for which detailed information is available (Green & Thorogood 2004, Kvale 1996). We can be sure that the women understood the risk information given to them, something that is difficult to assess (Weinstein 1999). Studies in risk communication are seldom able to concentrate on the decision-making situation itself because the concern is on the understanding of the information. Thus we were able to bring to the fore structural and conceptual aspects of the decision-making situation itself.

However, a study with such a small sample size cannot identify factors that are linked to outcomes of decision-making. Similarly, it is not possible to build prediction models for decision outcomes and generalize the findings in such a manner.

Relevance to the clinical practice

Women at risk for breast cancer today are regular patients in the health care system. They are clients of high risk clinics or genetic counseling. Their care in large part is one of continually managing their risk. Clinical research focuses on the best practice of risk communication in patient-provider-interactions, with the assumption that the best understanding of the risk estimates should guide a woman’s decision-making. Such an understanding neglects the ambiguity inherent in risk estimates (Holmberg & Parascandola 2010). While they are conceptualized to express something about an individual, they are in fact saying something about a fraction of a population (Rockhill 2005). The person participating in the counseling session, however, is a person with a particular understanding of themselves and of the condition at hand. This understanding should not be dismissed as lay or false. Instead, there should be greater acknowledgement of the uncertainty inherent in risk-estimates and recognition for the necessity to interpret them based on one’s personal life situation. Methods from narrative medicine (Greenhalgh & Hurwitz 1999) can be incorporated into such an approach.

CONCLUSION

In this study both women clearly understood the epidemiological risk information given to them. Thus for both women there is no need for more education to better their numeracy. Both women have made a conscious decision about the question at hand.

The analysis has shown that living a life at risk is a long term experience. Both women are currently satisfied with their risk management set in place in their lives. At another time the decision may have been made differently.

Both women would rather not take a medication when they feel they have a choice. They feel they have a choice because the information they received is presented as a calculated algorithm (NSABP hand-out) and not in the form of a physical measurement (blood pressure, cholesterol level).

The net benefit of a treatment that is calculated based on epidemiological data is not the same as the net benefit of an individual woman. It only provides probabilities. It is therefore important to take all factors that may be of importance for the decision, such as life history, risk management strategies, personal physical experiences, into account when making a decision about treating risk. The rich experience of a woman’s life at risk needs to be valued, especially when the decision has such momentous implications.

Acknowledgments

Sources of Support:

The work was conducted while the author was a Cancer Prevention Fellow at the National Cancer Institute, Division of Cancer Prevention and was funded by the National Cancer Institute.

This work would not have been possible without the women who so generously shared their stories and their time. The Division of Cancer Prevention, NCI gave us the opportunity to pursue these research questions. The anonymous reviewers and Nina Adelberger strengthen the paper with their thoughtful comments. Finally, Nina Adelberger helped us shape the final version of the paper.

Contributor Information

Christine Holmberg, Berlin School of Public Health, Charité - Universitätsmedizin Berlin, Germany

Mary Daly, Department of Clinical Genetics, Fox Chase Cancer Center, Philadephia, PA, USA

Worta McCaskill-Stevens, Division of Cancer Prevention, National Cancer Institute, Bethesda, MD, USA

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