Breast Cancer Research and Treatment

, Volume 161, Issue 3, pp 557–565 | Cite as

Recurrence risk perception and quality of life following treatment of breast cancer

  • Sarah T. Hawley
  • Nancy K. Janz
  • Kent A. Griffith
  • Reshma Jagsi
  • Christopher R. Friese
  • Allison W. Kurian
  • Ann S. Hamilton
  • Kevin C. Ward
  • Monica Morrow
  • Lauren P. Wallner
  • Steven J. Katz
Epidemiology

Abstract

Purpose

Little is known about different ways of assessing risk of distant recurrence following cancer treatment (e.g., numeric or descriptive). We sought to evaluate the association between overestimation of risk of distant recurrence of breast cancer and key patient-reported outcomes, including quality of life and worry.

Methods

We surveyed a weighted random sample of newly diagnosed patients with early-stage breast cancer identified through SEER registries of Los Angeles County & Georgia (2013–14) ~2 months after surgery (N = 2578, RR = 71%). Actual 10-year risk of distant recurrence after treatment was based on clinical factors for women with DCIS & low-risk invasive cancer (Stg 1A, ER+, HER2−, Gr 1–2). Women reported perceptions of their risk numerically (0–100%), with values ≥10% for DCIS & ≥20% for invasive considered overestimates. Perceptions of “moderate, high or very high” risk were considered descriptive overestimates. In our analytic sample (N = 927), we assessed factors correlated with both types of overestimation and report multivariable associations between overestimation and QoL (PROMIS physical & mental health) and frequent worry.

Results

30.4% of women substantially overestimated their risk of distant recurrence numerically and 14.7% descriptively. Few factors other than family history were significantly associated with either type of overestimation. Both types of overestimation were significantly associated with frequent worry, and lower QoL.

Conclusions

Ensuring understanding of systemic recurrence risk, particularly among patients with favorable prognosis, is important. Better risk communication by clinicians may translate to better risk comprehension among patients and to improvements in QoL.

Keywords

Breast cancer Risk Perception Quality of life 

Notes

Acknowledgements

This work was funded by Grant P01 CA163233 to the University of Michigan from the National Cancer Institute. The collection of Los Angeles County cancer incidence data used in this study was supported by the California Department of Public Health pursuant to California Health and Safety Code Section 103 885; Centers for Disease Control and Prevention’s (CDC) National Program of Cancer Registries, under cooperative agreement 5NU58DP003862-04/DP003862; the National Cancer Institute’s Surveillance, Epidemiology and End Results Program under Contract HHSN261201000140C awarded to the Cancer Prevention Institute of California, Contract HHSN261201000035C awarded to the University of Southern California, and Contract HHSN261201000034C awarded to the Public Health Institute. The ideas and opinions expressed herein are those of the author(s) and endorsement by the State of California, Department of Public Health, the National Cancer Institute, and the CDC or their Contractors and Subcontractors is not intended nor should be inferred. The collection of cancer incidence data in Georgia was supported by Contract HHSN261201300015I, Task Order HHSN26100006 from the NCI and cooperative agreement 5NU58DP003875-04-00 from the CDC. The ideas and opinions expressed herein are those of the author(s) and endorsement by the States of California and Georgia, Department of Public Health the National Cancer Institute, and the Centers for Disease Control and Prevention or their Contractors and Subcontractors is not intended nor should be inferred. We acknowledge the outstanding work of our project staff (Mackenzie Crawford, M.P.H. and Kiyana Perrino, M.P.H. from the Georgia Cancer Registry; Jennifer Zelaya, Pamela Lee, Maria Gaeta, Virginia Parker, B.A., and Renee Bickerstaff-Magee from USC; Rebecca Morrison, M.P.H., Rachel Tocco, M.A., Alexandra Jeanpierre, M.P.H., Stefanie Goodell, B.S., and Rose Juhasz, Ph.D. from the University of Michigan). We acknowledge with gratitude the breast cancer patients who responded to our survey.

Compliance with ethical standards

Conflict of interest

Dr. Kurian has received research funding for work performed outside of the present study from Myriad Genetics, Invitae, Ambry Genetics, GeneDx, and Genomic Health. All the other authors have no conflict to disclose.

Ethical standards

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Informed consent

Informed consent was obtained from all individual participants included in the study through their return of a completed survey.

References

  1. 1.
    Narod SA, Iqbal J, Giannakeas V, Sopik V, Sun P (2015) Breast cancer mortality after a diagnosis of ductal carcinoma in situ. JAMA Oncol 1(7):888–896. doi: 10.1001/jamaoncol.2015.2510 CrossRefPubMedGoogle Scholar
  2. 2.
    Sparano JA, Gray RJ, Makower DF, Pritchard KI, Albain KS, Hayes DF, Geyer CE Jr, Dees EC, Perez EA, Olson JA Jr, Zujewski J, Lively T, Badve SS, Saphner TJ, Wagner LI, Whelan TJ, Ellis MJ, Paik S, Wood WC, Ravdin P, Keane MM, Gomez Moreno HL, Reddy PS, Goggins TF, Mayer IA, Brufsky AM, Toppmeyer DL, Kaklamani VG, Atkins JN, Berenberg JL, Sledge GW (2015) Prospective validation of a 21-gene expression assay in breast cancer. N Engl J Med 373(21):2005–2014. doi: 10.1056/NEJMoa1510764 CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Vaz-Luis I, Ottesen RA, Hughes ME, Mamet R, Burstein HJ, Edge SB, Gonzalez-Angulo AM, Moy B, Rugo HS, Theriault RL, Weeks JC, Winer EP, Lin NU (2014) Outcomes by tumor subtype and treatment pattern in women with small, node-negative breast cancer: a multi-institutional study. J Clin Oncol 32(20):2142–2150. doi: 10.1200/jco.2013.53.1608 CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Worni M, Akushevich I, Greenup R, Sarma D, Ryser MD, Myers ER, Hwang ES (2015) Trends in treatment patterns and outcomes for ductal carcinoma in situ. J Natl Cancer Inst. doi: 10.1093/jnci/djv263 PubMedCentralGoogle Scholar
  5. 5.
    Ruddy KJ, Meyer ME, Giobbie-Hurder A, Emmons KM, Weeks JC, Winer EP, Partridge AH (2013) Long-term risk perceptions of women with ductal carcinoma in situ. Oncologist 18(4):362–368. doi: 10.1634/theoncologist.2012-0376 CrossRefPubMedPubMedCentralGoogle Scholar
  6. 6.
    Partridge A, Adloff K, Blood E, Dees EC, Kaelin C, Golshan M, Ligibel J, de Moor JS, Weeks J, Emmons K, Winer E (2008) Risk perceptions and psychosocial outcomes of women with ductal carcinoma in situ: longitudinal results from a cohort study. J Natl Cancer Inst 100(4):243–251. doi: 10.1093/jnci/djn010 CrossRefPubMedGoogle Scholar
  7. 7.
    Haas JS, Kaplan CP, Des Jarlais G, Gildengoin V, Perez-Stable EJ, Kerlikowske K (2005) Perceived risk of breast cancer among women at average and increased risk. J Women’s Health 14(9):845–851. doi: 10.1089/jwh.2005.14.845 CrossRefGoogle Scholar
  8. 8.
    Liu Y, Perez M, Aft RL, Massman K, Robinson E, Myles S, Schootman M, Gillanders WE, Jeffe DB (2010) Accuracy of perceived risk of recurrence among patients with early-stage breast cancer. Cancer Epidemiol Biomark Prevent 19(3):675–680. doi: 10.1158/1055-9965.epi-09-1051 CrossRefGoogle Scholar
  9. 9.
    Fisher CS, Martin-Dunlap T, Ruppel MB, Gao F, Atkins J, Margenthaler JA (2012) Fear of recurrence and perceived survival benefit are primary motivators for choosing mastectomy over breast-conservation therapy regardless of age. Ann Surg Oncol 19(10):3246–3250. doi: 10.1245/s10434-012-2525-x CrossRefPubMedGoogle Scholar
  10. 10.
    Hawley ST, Jagsi R, Morrow M, Janz NK, Hamilton A, Graff JJ, Katz SJ (2014) Social and clinical determinants of contralateral prophylactic mastectomy. JAMA Surg. doi: 10.1001/jamasurg.2013.5689 Google Scholar
  11. 11.
    Hawley ST, Zikmund-Fisher B, Ubel P, Jancovic A, Lucas T, Fagerlin A (2008) The impact of the format of graphical presentation on health-related knowledge and treatment choices. Patient Educ Couns 73(3):448–455. doi: 10.1016/j.pec.2008.07.023 CrossRefPubMedGoogle Scholar
  12. 12.
    Hamilton AS, Hofer TP, Hawley ST, Morrell D, Leventhal M, Deapen D, Salem B, Katz SJ (2009) Latinas and breast cancer outcomes: population-based sampling, ethnic identity, and acculturation assessment. Cancer Epidemiol Biomark Prevent 18(7):2022–2029. doi: 10.1158/1055-9965.epi-09-0238 CrossRefGoogle Scholar
  13. 13.
    Dillman D, Smyth J, Christian L (2009) Internet, mail, and mixed-mode surveys: the tailored design method, 3rd edn. Wiley, HobokenGoogle Scholar
  14. 14.
    Jagsi R, Griffith KA, Kurian AW, Morrow M, Hamilton AS, Graff JJ, Katz SJ, Hawley ST (2015) Concerns about cancer risk and experiences with genetic testing in a diverse population of patients with breast cancer. J Clin Oncol 33(14):1584–1591. doi: 10.1200/jco.2014.58.5885 CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Janz NK, Hawley ST, Mujahid MS, Griggs JJ, Alderman A, Hamilton AS, Graff JJ, Jagsi R, Katz SJ (2011) Correlates of worry about recurrence in a multiethnic population-based sample of women with breast cancer. Cancer 117(9):1827–1836. doi: 10.1002/cncr.25740 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Hawley ST, Griggs JJ, Hamilton AS, Graff JJ, Janz NK, Morrow M, Jagsi R, Salem B, Katz SJ (2009) Decision involvement and receipt of mastectomy among racially and ethnically diverse breast cancer patients. J Natl Cancer Inst 101(19):1337–1347CrossRefPubMedPubMedCentralGoogle Scholar
  17. 17.
    PROMIS Patient-Reported Outcomes Measurement Information System: dynamic tools to measure health outcomes from the patient perspective. http://www.nihpromis.org. Accessed 24 June 2016
  18. 18.
    Weaver KE, Forsythe LP, Reeve BB, Alfano CM, Rodriguez JL, Sabatino SA, Hawkins NA, Rowland JH (2012) Mental and physical health-related quality of life among U.S. cancer survivors: population estimates from the 2010 National Health Interview Survey. Cancer Epidemiol Biomark Prev 21(11):2108–2117. doi: 10.1158/1055-9965.epi-12-0740 CrossRefGoogle Scholar
  19. 19.
    Raghunathan TE, Lepkowski JM, Van Hoewyk J, Solenberger P (2001) A multivariate technique for multiply imputing missing values using a sequence of regression models. Survey Methodol 27(1):85–96Google Scholar
  20. 20.
    Keller C, Siegrist M, Gutscher H (2006) The role of the affect and availability heuristics in risk communication. Risk Anal 26(3):631–639. doi: 10.1111/j.1539-6924.2006.00773.x CrossRefPubMedGoogle Scholar
  21. 21.
    Peters E, Hart PS, Tusler M, Fraenkel L (2014) Numbers matter to informed patient choices: a randomized design across age and numeracy levels. Med Decis Mak 34(4):430–442. doi: 10.1177/0272989x13511705 CrossRefGoogle Scholar
  22. 22.
    Zikmund-Fisher BJ, Janz NK, Hawley ST, Griffith KA, Sabolch A, Jagsi R (2016) Communication of recurrence risk estimates to patients diagnosed with breast cancer. JAMA Oncol. doi: 10.1001/jamaoncol.2015.6416 Google Scholar
  23. 23.
    Janz NK, Leinberger RL, Zikmund-Fisher BJ, Hawley ST, Griffith K, Jagsi R (2015) Provider perspectives on presenting risk information and managing worry about recurrence among breast cancer survivors. Psycho-oncology 24(5):592–600. doi: 10.1002/pon.3625 CrossRefPubMedGoogle Scholar
  24. 24.
    The Joint Commission (2007) What did the doctor say?: Improving health literacy to protect patient safety. The Joint Commission, Oakbrook TerraceGoogle Scholar
  25. 25.
    Fagerlin A, Zikmund-Fisher BJ, Ubel PA (2011) Helping patients decide: ten steps to better risk communication. J Natl Cancer Inst 103(19):1436–1443CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Politi MC, Clark MA, Ombao H, Dizon D, Elwyn G (2011) Communicating uncertainty can lead to less decision satisfaction: a necessary cost of involving patients in shared decision making? Health Expect 14(1):84–91. doi: 10.1111/j.1369-7625.2010.00626.x CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media New York (outside the USA) 2016

Authors and Affiliations

  • Sarah T. Hawley
    • 1
    • 2
    • 3
  • Nancy K. Janz
    • 4
  • Kent A. Griffith
    • 5
  • Reshma Jagsi
    • 6
  • Christopher R. Friese
    • 7
  • Allison W. Kurian
    • 8
  • Ann S. Hamilton
    • 9
  • Kevin C. Ward
    • 10
  • Monica Morrow
    • 11
  • Lauren P. Wallner
    • 1
    • 12
  • Steven J. Katz
    • 1
    • 2
  1. 1.Division of General Medicine, Department of Internal MedicineUniversity of MichiganAnn ArborUSA
  2. 2.Department of Health Management and PolicyUniversity of MichiganAnn ArborUSA
  3. 3.Ann Arbor VA Center for Clinical Management Research, Ann Arbor VA Health Care SystemUniversity of MichiganAnn ArborUSA
  4. 4.Department of Health Behavior and Health EducationUniversity of MichiganAnn ArborUSA
  5. 5.Center for Cancer Biostatistics, School of Public HealthUniversity of MichiganAnn ArborUSA
  6. 6.Department of Radiation OncologyUniversity of MichiganAnn ArborUSA
  7. 7.Department of Systems, Populations, and Leadership, School of NursingUniversity of MichiganAnn ArborUSA
  8. 8.Departments of Medicine and Health Research and PolicyStanford UniversityStanfordUSA
  9. 9.Department of Preventive Medicine, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesUSA
  10. 10.Department of Epidemiology, Rollins School of Public HealthEmory UniversityAtlantaUSA
  11. 11.Department of SurgeryMemorial Sloan-Kettering Cancer CenterNew YorkUSA
  12. 12.Department of EpidemiologyUniversity of MichiganAnn ArborUSA

Personalised recommendations