The value of personalised risk information: A qualitative study of the perceptions of patients with prostate cancer

BMJ Open

Volumn 3, Issue 9, 2013, Pages

  Han, Paul K J ^a,b   Hootsmans, Norbert ^a   Neilson, Michael ^b   Roy, Bethany ^b   Kungel, Terence ^c   Gutheil, Caitlin ^a   Diefenbach, Michael ^d   Hansen, Moritz ^a,b  

^a MAINE MEDICAL CENTER   (United States)

^b TUFTS UNIVERSITY SCHOOL OF MEDICINE   (United States)

^c Maine Coalition to Fight Prostate Cancer   (United States)

^d MOUNT SINAI SCHOOL OF MEDICINE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL MARKER;

AGED; ARTICLE; CANCER PATIENT; CANCER RISK; CLINICAL ARTICLE; CONTROLLED STUDY; EDUCATION; EMOTION; GEOGRAPHY; HIGH RISK POPULATION; HUMAN; INFORMATION PROCESSING; MALE; MEDICAL RESEARCH; NARRATIVE; PATIENT DECISION MAKING; PERCEPTION; PERSONALISED RISK INFORMATION; PERSONALIZED MEDICINE; PHYSICIAN; PRACTICE GUIDELINE; PREDICTION; PROSTATE CANCER; QUALITATIVE RESEARCH; RISK ASSESSMENT; RURAL AREA; SEMI STRUCTURED INTERVIEW;

EID: 84885348500     PISSN: None     EISSN: 20446055     Source Type: Journal    
DOI: 10.1136/bmjopen-2013-003226     Document Type: Article

References (83)

1. Edwards A, Hood K, Matthews E, et al. The effectiveness of one-to-one risk communication interventions in health care: a systematic review. Med Decis Mak 2000;20:290-7. (Pubitemid 30470724)
2. Steyerberg EW. Clinical prediction models: a practical approach to development, validation, and updating. New York: Springer, 2010.
3. Personalized Health Care: Pioneers, Partnerships, Progress. 2008. http://www.hhs.gov/myhealthcare/ (accessed 12 Mar 2013).
4. Briss P, Rimer B, Reilley B, et al. Promoting informed decisions about cancer screening in communities and healthcare systems. Am J Prev Med 2004;26:67-80. (Pubitemid 38045176)
5. Makoul G, Clayman ML. An integrative model of shared decision making in medical encounters. Patient Educ Couns 2006;60:301-12. (Pubitemid 43287935)
6. Edwards A, Unigwe S, Elwyn G, et al. Effects of communicating individual risks in screening programmes: cochrane systematic review. BMJ 2003;327:703-9.
7. Barry MJ, Edgman-Levitan S. Shared decision making-pinnacle of patient-centered care. N Engl J Med 2012;366:780-1.
8. Elwyn G, Frosch D, Thomson R, et al. Shared decision making: a model for clinical practice. J Gen Intern Med 2012;27:1361-7.
9. Vickers AJ, Basch E, Kattan MW. Against diagnosis. Ann Intern Med 2008;149:200-3.
10. Edwards AG, Naik G, Ahmed H, et al. Personalised risk communication for informed decision making about taking screening tests. Cochrane Database Syst Rev 2013;(2):CD001865.
11. Gillies D. Philosophical theories of probability. London: Routledge, 2000.
12. Hacking I. The taming of chance. Cambridge: Cambridge University Press, 1990.
13. Han PK. Conceptual, methodological, and ethical problems in communicating uncertainty in clinical evidence. Med Care Res Rev 2013;70:14S-36S.
14. Han PK, Klein WM, Arora NK. Varieties of uncertainty in health care: a conceptual taxonomy. Med Decis Mak 2011;31:828-38.
15. Brewer NT, Richman AR, Defrank JT, et al. Improving communication of breast cancer recurrence risk. Breast Cancer Res Treat 2012;133:553-61.
16. Lipkus IM, Samsa G, Rimer BK. General performance on a numeracy scale among highly educated samples. Med Decis Mak 2001;21:37-44. (Pubitemid 32245029)
17. Sheridan SL, Pignone M. Numeracy and the medical student's ability to interpret data. Eff Clin Pract 2002;5:35-40.
18. Schwartz LM, Woloshin S, Black WC, et al. The role of numeracy in understanding the benefit of screening mammography. Ann Intern Med 1997;127:966-72. (Pubitemid 27516607)
19. Wegwarth O, Schwartz LM, Woloshin S, et al. Do physicians understand cancer screening statistics? A national survey of primary care physicians in the United States. Ann Intern Med 2012;156:340-9.
20. Reyna VF, Nelson WL, Han PK, et al. How numeracy influences risk comprehension and medical decision making. Psychol Bull 2009;135:943-73.
21. Han PK, Klein WM, Lehman TC, et al. Laypersons' responses to the communication of uncertainty regarding cancer risk estimates. Med Decis Mak2009;29:391-403.
22. Han PK, Lehman TC, Massett H, et al. Conceptual problems in laypersons' understanding of individualized cancer risk: a qualitative study. Health Expect 2009;12:4-17.
23. Ravdin PM, Siminoff LA, Davis GJ, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol 2001; 19:980-91. (Pubitemid 32176272)
24. Peele PB, Siminoff LA, Xu Y, et al. Decreased use of adjuvant breast cancer therapy in a randomized controlled trial of a decision aid with individualized risk information. Med Decis Mak 2005;25:301-7. (Pubitemid 40696279)
25. Siminoff LA, Gordon NH, Silverman P, et al. A decision aid to assist in adjuvant therapy choices for breast cancer. Psychooncology 2006;15:1001-13. (Pubitemid 44762705)
26. Belkora JK, Rugo HS, Moore DH, et al. Oncologist use of the adjuvant! model for risk communication: a pilot study examining patient knowledge of 10-year prognosis. BMC Cancer 2009;9:127.
27. Hutton DW, Belkora JK, Shachter RD, et al. Are patients getting the 'gist' in risk communication? Patient understanding of prognosis in breast cancer treatment. J Cancer Educ 2009;24:194-9.
28. Lipkus IM, Peters E, Kimmick G, et al. Breast cancer patients' treatment expectations after exposure to the decision aid program adjuvant online: the influence of numeracy. Med Decis Mak 2010;30:464-73.
29. Zikmund-Fisher BJ, Fagerlin A, Ubel PA. Improving understanding of adjuvant therapy options by using simpler risk graphics. Cancer 2008;113:3382-90.
30. Zikmund-Fisher BJ. The right tool is what they need, not what we have: a taxonomy of appropriate levels of precision in patient risk communication. Med Care Res Rev2013;70:37S-49S.
31. Reyna VF. A theory of medical decision making and health: fuzzy trace theory. Med Decis Mak 2008;28:850-65.
32. Simon H. Models of man, social and rational: mathematical essays on rational human behavior in a social setting. New York: Wiley, 1957.
33. Cancer Research UK. Prostate Cancer Statistics. 2013. http://www.cancerresearchuk.org/cancer-info/cancerstats/types/prostate/ (accessed 4 Apr 2013).
34. Rothenberg BM, Marbella A, Belinson SE, et al. Future Research Needs for Comparative Effectiveness of Treatments of Localized Prostate Cancer: Identification of Future Research Needs from Comparative Effectiveness Review No. 13. Rockville (MD) 2010.
35. National Cancer Institute. Surveillance, Epidemiology, and End Results (SEER) Stat Facts Sheets: Prostate. 2013; http://seer.cancer.gov/statfacts/html/ prost.html (accessed 4 Apr 2013).
36. Cooperberg MR. Prostate cancer risk assessment: choosing the sharpest tool in the shed. Cancer2008;113:3062-6.
37. Shariat SF, Karakiewicz PI, Roehrborn CG, et al. An updated catalog of prostate cancer predictive tools. Cancer2008;113:3075-99.
38. Lughezzani G, Briganti A, Karakiewicz PI, et al. Predictive and prognostic models in radical prostatectomy candidates: a critical analysis of the literature. Eur Urol2010;58:687-700.
39. Cowen ME, Halasyamani LK, Kattan MW. Predicting life expectancy in men with clinically localized prostate cancer. J Urol 2006;175:99-103. (Pubitemid 41797102)
40. Eastham JA, Scardino PT, Kattan MW. Predicting an optimal outcome after radical prostatectomy: the trifecta nomogram. JUrol 2008;179:2207-10; discussion 2210-2201.
41. Ross RW, Kantoff PW. Predicting outcomes in prostate cancer: how many more nomograms do we need? J Clin Oncol2007;25:3563-4. (Pubitemid 47372589)
42. Lerner Research Institute, Cleveland Clinic. Risk calculators. 2010. http://www.lerner.ccf.org/qhs/risk-calculator/index.php (accessed 12 Nov 2010).
43. Touijer K, Scardino PT. Nomograms for staging, prognosis, and predicting treatment outcomes. Cancer 2009;115(13 Suppl):3107-11.
44. Cegala DJ, Post DM, McClure L. The effects of patient communication skills training on the discourse of older patients during a primary care interview. J Am Geriatr Soc 2001;49:1505-11. (Pubitemid 33051402)
45. nomogram.org. Prostate Cancer. 2010. http://nomogram.org/Prostate/pros- calc.php (accessed 12 Nov 2010).
46. Hoffman A, Montgomery R, Aubry W, et al. How best to engage patients, doctors, and other stakeholders in designing comparative effectiveness studies. Health Aff (Millwood) 2010;29:1834-41.
47. Sofaer S. Qualitative methods: what are they and why use them? Health Serv Res 1999;34(5 Pt 2):1101-18.
48. Kitzinger J. Qualitative research. Introducing focus groups. BMJ 1995;311:299-302.
49. Morgan D. Focus groups in qualitative research. 2nd edn. Thousand Oaks, CA: Sage Publications, 1998.
50. National Comprehensive Cancer Network. NCCN Practice Guidelines for Prostate Cancer. 2010; Version 1: 2010. http://www.nccn.org (accessed 16 Dec 2012).
51. Memorial-Sloan Kettering Center. Prostate Cancer Nomograms: a Tool for Doctors & Patients. 2010. http://www.mskcc.org/mskcc/html/10088.cfm (accessed 12 Nov 2010).
52. Strauss AL, Corbin J. Basics of qualitative research: techniques and procedures for developing grounded theory. 2nd edn. Thousand Oaks, CA: Sage, 1998.
53. Ryan GW, Bernard HR. Data management and analysis methods. In: Denzin NK, Lincoln YS. eds. Collecting and interpreting qualitative materials. Thousand Oaks, CA: Sage, 2003: 259-309.
54. Glaser BG. The constant comparative method of qualitative analysis. Soc Probl 1965;12:436-45.
55. Slovic P, Finucane M, Peters E, et al. The affect heuristic. In: Gilovich T, Griffin D, Kahneman D. eds. Heuristics and biases: the psychology of intuitive judgment. Cambridge: Cambridge University Press, 2002: 397-420.
56. Slovic P, Peters E, Finucane ML, et al. Affect, risk, and decision making. Health Psychol 2005;24(4 Suppl):S35-40. (Pubitemid 41099123)
57. Wegwarth O, Gigerenzer G. Trust-your-doctor: a simple heuristic in need of a proper social environment. In: Hertwig R, Hoffrage U. eds. Simple heuristics in a social world. New York: Oxford University Press, 2013: 67-102.
58. Winterbottom A, Bekker HL, Conner M, et al. Does narrative information bias individual's decision making? A systematic review. Soc Sci Med 2008;67:2079-88.
59. deWit JBF, Das E, Vet R. What works best: objective statistics or a personal testimonial? An assessment of the persuasive effects of different types of message evidence on risk perception. Health Psychol 2008;27:110-15. (Pubitemid 351215354)
60. Shaffer VA, Zikmund-Fisher BJ. All stories are not alike: a purpose-, content-, and valence-based taxonomy of patient narratives in decision AIDS. Med Decis Mak 2013;33:4-13.
61. Gigerenzer G, Selten R. Bounded rationality. Cambridge: MIT Press, 2002.
62. Tversky A, Kahneman D. Judgment under uncertainty: heuristics and biases. Science 1974;185:1124-31.
63. Isaacson W. Steve jobs. New York: Simon and Schuster, 2011.
64. Peters E, Dieckmann N, Dixon A, et al. Less is more in presenting quality information to consumers. Med Care Res Rev 2007;64:169-90. (Pubitemid 46570715)
65. Iyengar SS, Kamenica E. Choice proliferation, simplicity seeking, and asset allocation. J Public Econ 2010;94:530-9.
66. Iyengar SS, Lepper MR. When choice is demotivating: can one desire too much of a good thing? J Pers Soc Psychol 2000;79:995-1006.
67. Legare F, Ratte S, Gravel K, et al. Barriers and facilitators to implementing shared decision-making in clinical practice: update of a systematic review of health professionals' perceptions. Patient Educ Couns 2008;73:526-35.
68. Lin GA, Aaronson DS, Knight SJ, et al. Patient decision aids for prostate cancer treatment: a systematic review of the literature. CA Cancer J Clin 2009;59:379-90.
69. de Vries M, Fagerlin A, Witteman HO, et al. Combining deliberation and intuition in patient decision support. Patient Educ Couns 2013;91:154-60.
70. Spiegelhalter DJ, Riesch H. Don't know, can't know: embracing deeper uncertainties when analysing risks. Philos Transact A Math Phys Eng Sci 2011;369:4730-50.
71. Bilcke J, Beutels P, Brisson M, et al. Accounting for methodological, structural, and parameter uncertainty in decision-analytic models: a practical guide. Med Decis Mak 2011;31:675-92.
72. Han PK. Conceptual, methodological, and ethical problems in communicating uncertainty in clinical evidence. Med Care Res Rev 2013;70(1 Suppl):14S-36S.
73. Gigerenzer G. Gut feelings: the intelligence of the unconscious. New York: Penguin Books, 2007.
74. Elwyn G, Frosch D, Volandes AE, et al. Investing in deliberation: a definition and classification of decision support interventions for people facing difficult health decisions. Med Decis Mak 2010;30:701-11.
75. Stacey D, Bennett CL, Barry MJ, et al. Decision aids for people facing health treatment or screening decisions. Cochrane Database Syst Rev 2011;(10):CD001431.
76. Lipkus IM. Numeric, verbal, and visual formats of conveying health risks: suggested best practices and future recommendations. Med Decis Mak 2007;27:696-713. (Pubitemid 47547606)
77. Visschers VH, Meertens RM, Passchier WW, et al. Probability information in risk communication: a review of the research literature. Risk Anal 2009;29:267-87.
78. Galesic M, Garcia-Retamero R, Gigerenzer G. Using icon arrays to communicate medical risks: overcoming low numeracy. Health Psychol 2009;28:210-16.
79. Garcia-Retamero R, Galesic M. Who profits from visual aids: overcoming challenges in people's understanding of risks [corrected]. Soc Sci Med 2010;70:1019-25.
80. Dolan JG, Qian F, Veazie PJ. How well do commonly used data presentation formats support comparative effectiveness evaluations? Med Decis Mak 2012;32:840-50.
81. Akl EA, Oxman AD, Herrin J, et al. Using alternative statistical formats for presenting risks and risk reductions. Cochrane Database Syst Rev 2011;(3):CD006776.
82. Gigerenzer G, Gaissmaier W, Kurz-Milcke E, et al. Helping doctors and patients make sense of health statistics. Psychol SciPublic Interest 2007;8:53-96.
83. Spiegelhalter D, Pearson M, Short I. Visualizing uncertainty about the future. Science 2011;333:1393-400.