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Communicating prognosis in early breast cancer: do women understand the language used?

Elizabeth A Lobb, Phyllis N Butow and Dianna T Kenny
Med J Aust 1999; 171 (6): 290-294.
Research

Communicating prognosis in early breast cancer: do women understand the language used?

Elizabeth A Lobb, Phyllis N Butow, Dianna T Kenny and Martin H N Tattersall

MJA 1999; 171: 290-294
For related articles see Maguire, Prince & Naganathan et al

Abstract - Introduction - Methods - Results - Discussion - Acknowledgements - References - Authors' details
- - More articles on Oncology


Abstract Objectives: To determine the degree to which women with early breast cancer understand the prognostic information communicated by clinicians after breast cancer diagnosis, and their preferences for how this information is presented.
Design: Cross-sectional survey conducted within two months of breast cancer diagnosis, using a self-administered written questionnaire.
Participants and setting: One hundred women attending five Sydney teaching hospitals and one country hospital, who were diagnosed with early stage breast cancer between January and December 1997.
Results: The 100 respondents represented 70% of the 143 women originally approached to participate. Many respondents did not fully understand the language typically used by surgeons and cancer specialists to describe prognosis: 53% could not calculate risk reduction (with adjuvant therapy) relative to absolute risk; 73% did not understand the term "median" survival; and 33% believed a cancer specialist could predict an individual patient's outcome. Women in professional/ paraprofessional occupations understood more prognostic information than non-professional women. There was no agreement on the descriptive equivalent of a "30%" risk, nor the numerical interpretation of a "good" chance of survival. Forty-three per cent of women preferred positively framed messages (eg, "chance of cure"), and 33% negatively framed messages (eg, "chance of relapse"). The information women most wanted was that relating to probability of cure, staging of their cancer, chances of treatment being successful, and 10-year survival figures with and without adjuvant therapy.
Conclusions: Our results suggest that misunderstanding is responsible for women's confusion about breast cancer prognosis. Clinicians should use a variety of techniques to communicate prognosis and risk, and need to verify that the information has been understood.


Introduction To make informed decisions women with breast cancer must understand what their prognosis is without systemic treatment, and the likely advantages and disadvantages of treatment.

While most Australian doctors now tell cancer patients their diagnosis,1 prognosis is less commonly discussed.2 Reticence to provide prognostic information is often based on concerns that the information will be overwhelming, not understood or will destroy hope.3,4 However, it is not clear whether the information itself, or the language used, is the critical feature.

Many patients have a poor understanding of their disease and their prognosis,5,6 or have difficulty recalling the information they have been given about their disease.7,8 Similarly, women at risk of developing breast cancer commonly misreport individual and population risk.9 Denial and minimisation of risk are also common psychological reactions to cancer risk notification after screening procedures.10 If it were possible to determine whether patients cannot understand the terminology or mathematics of risk information, or, rather, prefer not to be told or do not absorb the information, clearer directions for best clinical practice in discussing prognosis could be established.

Most previous studies on risk communication in cancer have not dealt specifically with issues pertinent to women with breast cancer. In two studies that did, the women surveyed were well down the treatment path and their experience of learning their prognosis was long past.5,11 To our knowledge, there are no reports of women's understanding of specific prognostic information in early breast cancer.

We investigated women's understanding of prognostic information and their preferences for the way the information on the risk of their breast cancer recurring after surgery is presented to them.


Methods

Survey subjects
Women were recruited through their treating physician. To ensure input from a range of women, five urban centres attracting referrals from populations with different socioeconomic profiles (Royal Prince Alfred, Royal North Shore, Prince of Wales, St George, and Westmead hospitals, all in Sydney, New South Wales) and one rural centre (Tamworth Hospital, Tamworth, NSW) were approached to participate in the study. Thirteen breast surgeons and 13 medical oncologists from these centres were invited to participate in the study and all agreed.

One hundred and forty-three consecutive women newly diagnosed with stage I or II breast cancer at any of the six treatment centres between January and December 1997 were contacted by letter to request their participation. The women received the letter within 2-4 weeks of making their own decisions about adjuvant treatment and within 2 months of their initial diagnosis. (The timing of questionnaire administration was carefully considered to maximise the saliency of the issues while avoiding distressing women making their own treatment decisions.) The letter was followed up by a phone call from the research coordinator, who obtained verbal consent for participation and then sent out the questionnaire by mail. One centre opted to send women a letter signed by their oncologist inviting them to participate in the study.

The survey sample included patients of surgeons and medical oncologists in both private and public practice. Women from a non-English-speaking background with insufficient knowledge of English to complete the questionnaire, and women presenting with a second cancer, were excluded.

Questionnaire We gathered the data using a self-administered written 17-item questionnaire, designed on the basis of a review of the literature; an analysis of 20 audiotapes of initial oncology consultations with breast cancer patients (collected from two centres -- Royal Prince Alfred Hospital and Westmead Hospital -- during another study undertaken between 1995 and 199712); and expert consultation (a working party set up by the National Breast Cancer Centre). The 20 audiotapes were transcribed and the contents analysed to identify the range of ways in which prognosis was conveyed to patients (eg, absolute and relative risk, cumulative risk, numerical or non-numerical probability, and individual versus population risk).

The questionnaire investigated women's understanding of and preferences for these different formats used by doctors for disclosing prognosis and risk information. In addition, a standard hypothetical scenario of adjuvant therapy in early stage breast cancer was included, and women responded to questions applying to that scenario (Box 1).

Six of the questions explored women's understanding of different ways in which the risk of breast cancer recurring after surgery could be presented. Two sample questions are shown in Box 2. A "don't know" option was not offered in the items relating to "understanding" in order to force a choice and allow an analysis of common errors in interpretation.

The remaining questions focused on the importance of different prognostic information to women's decision making, and on their preferences for presentation of risk - for example:

  • percentages versus numbers (eg, "70%" v. "7 in 10");

  • numerical versus verbal descriptions of risk (eg, "30%" v. "small"); and

  • positively framed versus negatively framed statements (eg, "70% chance of remaining free of cancer" v. "30% chance of the cancer coming back").

The questionnaire also elicited the women's demographic data and details of their breast cancer diagnosis and treatment (Box 3).

Statistical analysis
Appropriate sample sizes were calculated using the SAM sample size software package.13 Sample size calculations were based on effect sizes from related studies in patients' level of recall after a variety of interventions. In an Australian study measuring understanding of information presented in an oncology consultation, a sample size of 47 per group was sufficient to detect statistically significant differences of 7% (P < 0.005) in recall between groups. Thus, in a comparison of two patient subgroups (eg, young v. old), a total sample size of 100 would allow us to detect a similar difference in responses in the two groups. A sample size of 100 would also allow detection of a difference of 30% or more (felt to be clinically significant) between subgroups in the proportion of women preferring one presentation of risk versus another, with a power of 0.8 and a significance level of 0.05.

A "total understanding" score was calculated by summing correct responses to the six items assessing "understanding". The summary score was normally distributed (K-S Lilliefors .0514). Descriptive statistics were used to identify the percentage of patients understanding and preferring different risk information. Analysis of variance (ANOVA), Student's t tests and χ2 tests of association were used to examine the relationship between demographic variables and outcomes, as appropriate; two-sided tests were used.15

Ethical approval
Approval was granted for this study by the Ethics Committee of the University of Sydney, the Central Sydney Area Health Service, the Southern Sydney Area Health Service, and individual hospital ethics committees at Westmead, Royal North Shore and Tamworth hospitals.


Results Of the 118 women who agreed to participate in the survey, 100 returned questionnaires (70% of the original 143 women contacted).

Demographic data
Demographic characteristics of the participants are presented in Box 3. Their mean age was 56 years and most were city dwellers. Just over half had completed the Higher School Certificate, university or some form of tertiary training. The percentage of women with tertiary qualifications was 42% (compared with 37% in the general Australian population16)..Nearly two-thirds worked (or had worked) in professional or paraprofessional occupations, and 22% were working in occupations related to medicine (eg, doctor, nurse, medical receptionist, technician).

Questionnaire responses
A summary of the women's responses to the questionnaire is given in Box 4.


Discussion We have identified some of the problems women with breast cancer experience when trying to interpret prognostic information presented by their doctors. Our results support the hypothesis that it is misunderstanding, not denial, that causes confusion. A considerable number of women in our study did not clearly understand some of the language used to describe the risk of breast cancer recurrence after surgery or how additional treatment might benefit them. Moreover, the response from this group of relatively highly educated women probably represents a "best case" scenario, and, if anything, one might expect understanding to be poorer in the general population of women with breast cancer.

These findings have implications for informed consent. Clinicians need to explain what type of prognostic information can be given, and enquire how much of this information women want to hear. They should check very carefully how women have interpreted the information presented to them, and must not assume that, because a woman has already consulted a number of specialists, her prognosis has been conveyed to her and clearly understood. This applies to all patients with breast cancer, but especially those who work in unskilled occupations.

It might be argued that our sample was not truly representative, as (i) the women surveyed, having recently been told their diagnosis, may not have been in the best frame of mind to answer the questionnaire clearly and impartially; and (ii) we did not include a similar group of women who had never had breast cancer. Furthermore, patient responses may have been different had the questions concerned personal experience rather than a hypothetical case scenario.5,9,10,19

However, data from Degner et al20 suggest that views expressed by people diagnosed with cancer differ considerably from those of the well population, which underscores the importance of surveying those who have actually been diagnosed with cancer. In addition, we felt that a typical case vignette was the most appropriate tool to control for the influence of individual disease variables and treatment protocols; to reduce the positive bias associated with evaluating one's own treatment team; and to examine all aspects of risk communication in adjuvant therapy.

Creative measures to assist women in understanding risk statistics are needed. Bunker et al have recently proposed that a life table constructed from published statistics on national morbidity and mortality may be used to display the likelihood of developing or dying of a disease at any given moment.21 A similar approach could be used to display the likelihood of disease recurrence and premature death after cancer diagnosis. We believe that these and other information aids may contribute to informed patients' involvement in treatment decisions, and a more realistic understanding of prognosis.



Acknowledgements
We thank Dr Afaf Girgis, Dr Lyn Mann, Ms Kate White, Ms Joan Wilson and Ms Kim Hobbs for their assistance and advice; also the 26 clinicians who participated in this project, and the women who so willingly filled out the questionnaire. The research was funded by the National Health and Medical Research Council National Breast Cancer Centre of Australia.


References
  1. Charlton RC. Breaking bad news. Med J Aust 1992; 157: 615-621.
  2. Butow PN, Kazemi J, Beeney LJ, et al. When the diagnosis is cancer: patient communication experiences and preferences. Cancer 1996; 77: 2630-2637.
  3. Oken D. What to tell cancer patients: a study of medical attitudes. JAMA 1961; 175: 1120-1128.
  4. Beisecker AE, Helmig I, Graham D, et al. Attitudes of oncologists, oncology nurses and patients from a women's clinic regarding medical decision making with older and younger breast cancer patients. Gerontologist 1994; 34: 505-512.
  5. Siminoff LA, Fetting JH, Abeloff MD. Doctor-patient communication about breast cancer adjuvant therapy. J Clin Oncol 1989; 7: 1192-1200.
  6. Sheldon JM, Fetting JH, Siminoff LA. Offering the option of randomized clinical trials to cancer patients who overestimate their prognoses with standard therapies. Cancer Invest 1993, 11: 57-62.
  7. Dunn SM, Butow PN, Tattersall MHN, et al. General information tapes inhibit recall of the cancer consultation. J Clin Oncol 1993; 11: 2279-2285.
  8. Mackillop WJ, Stewart WE, Ginsburg AD, Stewart SS. Cancer patients' perceptions of their disease and its treatment. Br J Cancer 1988; 58: 355-358.
  9. Evans DR, Blair V, Greenhalgh R, et al. The impact of genetic counselling on risk perceptions in women with a family history of breast cancer. Br J Cancer 1994; 70: 934-938.
  10. Lerman C, Rimer BK, Engstrom PF. Cancer risk notification: psychosocial and ethical implications. J Clin Oncol 1991; 9: 1275-1282.
  11. Hughes KK. Decision making by patients with breast cancer: the role of information in treatment decision selection. Oncol Nurs Forum 1993; 20: 623-628.
  12. Brown R, Dunn S, Butow P. Meeting patient expectations in the cancer consultation. Ann Oncol 1997; 8: 877-882.
  13. Glasziou P. SAM 2.1: a sample size calculator [computer program]. Sydney: NHMRC Clinical Trials Centre, University of Sydney, 1992.
  14. Armitage P, Berry G. Statistical methods in medical research. Oxford: Blackwell Scientific, 1994: 397.
  15. SPSS Advanced Statistics, TM6.1. Chicago; SPSS Inc, 1994.
  16. Australian women's year book. Canberra: Australian Bureau of Statistics, 1997.
  17. Degner LF, Kristjanson LJ, Bowman D, et al. Information needs and decisional preferences in women with breast cancer. JAMA 1997; 277: 1485-1492.
  18. Bilodeau BA, Degner LF. Informational needs, sources of information, and decisional roles in women with breast cancer. Oncol Nurs Forum 1996; 23: 691-696.
  19. Marteau TM. Framing of information: its influence upon decisions of doctors and patients. Br J Soc Psychol 1989; 28: 89-94.
  20. Degner LF, Sloan JA. Decision making during serious illness: what role do patients really want to play? J Clin Epidemiol 1992; 45: 941-950.
  21. Bunker JP, Houghton J, Baum M. Putting the risk of breast cancer in perspective. BMJ 1998; 317: 1307-1309.

(Received 4 Jan, accepted 11 May, 1999)


Authors' details University of Sydney, Sydney, NSW.
Elizabeth A Lobb, BAdEd, MAppSci, Associate Lecturer, Medical Psychology Unit.
Phyllis N Butow, PhD, MPH, Executive Director, Medical Psychology Unit; and Research Co-ordinator, Department of Psychological Medicine, Royal North Shore Hospital.
Dianna T Kenny, PhD, MA, Associate Professor of Psychology, Faculty of Health Sciences.
Martin H N Tattersall, MD, FRACP, Professor of Cancer Medicine, Department of Medicine.

Reprints: Ms E A Lobb, Associate Lecturer, Medical Psychology Unit, Department of Psychological Medicine, University of Sydney, NSW 2006.
Email: lizlobbATblackburn.med.usyd.edu.au






1: Hypothetical breast cancer scenario used in the questionnaire

Sheila is a 54-year-old woman with breast cancer. Sheila has gone through the menopause. Sheila chose to have her breast cancer (tumour) removed by a lumpectomy, but she also had some of the lymph glands in her armpit removed. Sheila was advised to have radiotherapy after her lumpectomy. Sheila's breast cancer was small, and the lymph nodes under her arm were not affected with cancer. Her tumour contained receptors to oestrogen, suggesting that it may be sensitive to the effects of hormones. Sheila's doctor uses this information to decide if she would benefit from additional treatment.

Sheila understands that any additional treatment other than surgery is called "adjuvant" therapy. Adjuvant therapy means giving treatment now after her surgery to try to prevent the cancer returning in the future. Following her breast cancer surgery, Sheila was told of her risk of having her cancer return (her prognosis) if she has no further treatment. This risk can be expressed in different ways.

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2: Examples of questions to assess women's understanding of relative risk reduction

Example A:
Sheila's doctor told her that 30% of women with a cancer similar to hers will have their cancer come back within 5 years. If Sheila has additional treatment, the risk of her cancer coming back will be reduced by 30%.

Tick one only

  • If Sheila has additional treatment this means the risk of her cancer coming back within 5 years is zero.
  • If Sheila has additional treatment this means the risk of her cancer coming back within 5 years is 21%.
  • If Sheila has additional treatment this means the risk of her cancer coming back within 5 years is 30%.

Example B:
If Sheila's doctor says the median time for her breast cancer to return without further treatment is about 5 years, he/she means:

  • The average time for Sheila's cancer to return is 5 years
  • That 50% of women with breast cancer like Sheila's will have their cancer return within 5 years
  • That the women whose cancer will come back will have it come back within 5 years
  • I don't understand the word "median"
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3: Demographic characteristics of the respondents (n = 100) to a questionnaire about provision of information on breast cancer prognosis*

CategoryNumber of participants

Age (mean, 56 years; range, 35-88 years)
Postcode
 City82
 Country18
Educational level
 Non-tertiary58
 Tertiary42
Occupation
 Professional/paraprofessional63
 Non-professional36
Marital status
 Married58
 Other41
English as first language84
Working in medicine-related occupation22
Time since diagnosis
 1-2 months71
 ≥3 months26
Treatment for breast cancer
 Lumpectomy only14
 Mastectomy only17
 Lumpectomy + R38
 Lumpectomy +R + C15
 Mastectomy + C15
Family member/friend with breast cancer
 Yes61
 No38

* Not all categories sum to 100 because of missing data. R = radiotherapy; C = chemotherapy.
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4: Summary of questionnaire responses

Understanding of risk

Risk concepts tested

  • Absolute risk of relapse:
    -- 86% of respondents gave a correct response.
  • 30% relative risk reduction, with therapy, of an absolute risk of 30% (sample question A, Box 2):
    -- 47% gave a correct response;
    -- 28% thought additional treatment would reduce the risk of relapse to zero; and
    -- 25% thought the risk would remain at 30%.
  • Median 5-year survival (sample question B, Box 2):
    -- 27% answered correctly;
    -- 43% thought it meant "average" survival;
    -- 10% thought that half the women not having adjuvant therapy would have their breast cancer return within 5 years; and
    -- 20% did not understand the term "median".
  • Interpretation of a graphical representation of risk:
    -- 80% of respondents answered correctly.
  • Distinguishing individual risk from population risk:
    -- 66% gave correct response.
    -- The remaining women believed that their cancer specialist knew whether or not they would respond to treatment.

Association with demographic variables

  • Mean number of correct responses, 3.4 (95% CI, 3.08-3.6); only one woman answered all six questions correctly.
  • Women in professional employment (mean number of correct responses, 3.6 [95% CI, 3.2-4.0]) or paraprofessional employment (mean number of correct responses, 3.4 [95% CI, 3.0-3.8]) understood more prognostic information than women in non-professional employment (mean number of correct responses, 2.5 [95% CI, 1.7-3.4] [F2,87 = 4.24, P = 0.02]).
  • No other variables were found to be associated with understanding of risk (eg, working in a medically related field; having tertiary qualifications; having had surgery, radiotherapy and/or chemotherapy for breast cancer; or time elapsed since consultation in which prognosis was discussed).

Interpretation of words versus statistics

  • There was no consistency in respondents' interpretation of "a good chance of remaining free of cancer" in statistical terms, nor agreement on the non-numerical interpretation of "a 30% risk" (17% thought it was a very high or high risk, 34% that it was a medium risk, and 49% that it was a low risk).
Preferences for language
  • 44% of respondents preferred "a 70% chance of cure", 13% preferred "a 7 in 10 chance", and the remainder had no preference.
  • 53% of women preferred "a 30% chance of cancer coming back", 38% preferred "a small chance of cancer coming back", and the remainder had no preference.
  • 49% of non-tertiary-educated women versus 24% of tertiary-educated women preferred the descriptive option (a "small" chance) (χ22 = 8.17, P = 0.02).
  • 43% of women preferred the wording "70% chance of cure", 33% preferred "30% chance of the cancer coming back", and 25% had no preference.
Preferences for framing of information
  • Reasons given for choosing positively framed prognostic information: "a more positive/optimistic statement" and "encourages determination to manage treatment positively".
  • Reasons given for choosing negatively framed prognostic information: "it emphasises the importance of additional treatment" and "more specific/precise".
Importance attributed to prognostic information (Table)

  • Over 90% of respondents regarded information about their chances of being cured, the staging of their cancer, and the chances that the recommended treatment would work as very important to their decision making.
  • Nearly two-thirds of women regarded the 10-year survival rate with adjuvant therapy as very important information, and 45% wanted to know this rate without adjuvant therapy.
  • These percentages are considerably higher than documented in previous studies.17,18

Women's ratings of the importance of different types of prognostic information

Prognostic informationVery importantSomewhat importantNot important

My chances of being cured94%2%4%
What things about my cancer influence my chances of being cured (eg, size of my cancer, whether lymph nodes are involved, etc)92%6%2%
The chances that the recommended treatment will work91%7%2%
How many women in my situation choosing to have the recommended treatment would be alive in 10 years60%29%11%
Statistics about long term outcome of breast cancer50%32%18%
How many women not choosing to have the recommended treatment are alive in 10 years45%35%20%
The longest anyone in my situation has lived34%19%47%
The shortest anyone in my situation has lived30%14%56%
The risk of my cancer shortening my life compared with other life events (eg, heart disease, old age)45%23%32%
The average time people in my situation have lived44%28%28%
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Elizabeth A Lobb
Phyllis N Butow
Dianna T Kenny