Skip to main content

Advertisement

Log in

A detailed description of the distress trajectory from pre- to post-treatment in breast cancer patients receiving neoadjuvant chemotherapy

  • Clinical trial
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Purpose

To characterize the distress trajectory in patients with newly diagnosed, non-metastatic breast cancer from pre-neoadjuvant chemotherapy until 12 months after onset of treatment and to identify demographic and clinical predictors of distress in these patients.

Methods

In a retrospective, longitudinal study, chart review data were abstracted for 252 eligible patients treated at a comprehensive cancer care center. The center screens for distress at least monthly with the distress thermometer; the highest distress score per month was included in the analyses. The growth trajectory was established using mixed modeling and predictors were added to the initial growth model in subsequent models.

Results

Distress showed a cubic growth trajectory with highest distress prior to treatment onset followed by a steep decline in the first three months of treatment. A slight increase in distress was apparent over months 6–10. Being Hispanic was associated with a stronger increase in distress in the second half of the year (p = 0.012). NACT was associated with lower distress and surgery with higher distress (both: p < 0.001).

Conclusion

Distress is at its peak prior to treatment onset and rapidly decreases once treatment has started. Oncologist should be aware that both completion of NACT and undergoing surgery are associated with increases in distress and Hispanic patients may be more at risk for an increase in distress at these times; this suggests that careful monitoring of distress during the treatment trajectory and in Hispanic patients in particular in order to provide timely support.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1

Similar content being viewed by others

Data availability

The data that support the findings of this study are available on reasonable request form the corresponding author.

References

  1. National Comprehensive Cancer Network I. 2022. Distress Management. NCCN Clinical Practice Guidelines in Oncology 2022.

  2. Mehnert A, Hartung TJ, Friedrich M, Vehling S et al (2017) One in two cancer patients is significantly distressed: prevalence and indicators of distress. Psychooncology. https://doi.org/10.1002/pon.4464

    Article  Google Scholar 

  3. Zabora J, BrintzenhofeSzoc K, Curbow B, Hooker C et al (2001) The prevalence of psychological distress by cancer site. Psychooncology 10(1):19–28. https://doi.org/10.1002/1099-1611(200101/02)10:1%3c19::AID-PON501%3e3.0.CO;2-6

    Article  CAS  Google Scholar 

  4. Härtl K, Engel J, Herschbach P, Reinecker H et al (2010) Personality traits and psychosocial stress: quality of life over 2 years following breast cancer diagnosis and psychological impact factors. Psychooncology 19(2):160–169. https://doi.org/10.1002/pon.1536

    Article  Google Scholar 

  5. Hegel MT, Moore CP, Collins ED, Kearing S et al (2006) Distress, psychiatric syndromes, and impairment of function in women with newly diagnosed breast cancer. Cancer 107(12):2924–2931. https://doi.org/10.1002/cncr.22335

    Article  Google Scholar 

  6. Lutgendorf SK, Sood AK, Antoni MH (2010) Host factors and cancer progression: biobehavioral signaling pathways and interventions. J clin oncol 28(26):4094–4099. https://doi.org/10.1200/JCO.2009.26.9357

    Article  CAS  Google Scholar 

  7. Oh H-M, Son C-G (2021) The risk of psychological stress on cancer recurrence: a systematic review. Cancers 13(22):5816. https://doi.org/10.3390/cancers13225816

    Article  Google Scholar 

  8. Groenvold M, Petersen MA, Idler E, Bjorner JB et al (2007) Psychological distress and fatigue predicted recurrence and survival in primary breast cancer patients. Breast Cancer Res Treat 105(2):209–219. https://doi.org/10.1007/s10549-006-9447-x

    Article  Google Scholar 

  9. Adeyemi OJ, Gill TL, Paul R, Huber LB (2021) Evaluating the association of self-reported psychological distress and self-rated health on survival times among women with breast cancer in the U.S. PLoS ONE 16(12):e0260481. https://doi.org/10.1371/journal.pone.0260481

    Article  CAS  Google Scholar 

  10. Antoni MH, Lechner SC, Kazi A, Wimberly SR et al (2006) How stress management improves quality of life after treatment for breast cancer. J Consult Clin Psychol 74(6):1143–1152. https://doi.org/10.1037/0022-006x.74.6.1152

    Article  Google Scholar 

  11. Andersen BL, Yang H-C, Farrar WB, Golden-Kreutz DM et al (2008) Psychologic intervention improves survival for breast cancer patients: a randomized clinical trial. Cancer 113(12):3450–3458. https://doi.org/10.1002/cncr.23969

    Article  Google Scholar 

  12. Yang H-C, Thornton LM, Shapiro CL, Andersen BL (2008) Surviving recurrence: psychological and quality-of-life recovery. Cancer 112(5):1178–1187. https://doi.org/10.1002/cncr.23272

    Article  Google Scholar 

  13. Kant J, Czisch A, Schott S, Siewerdt-Werner D et al (2018) Identifying and predicting distinct distress trajectories following a breast cancer diagnosis—from treatment into early survival. J Psychosom Res 115:6–13. https://doi.org/10.1016/j.jpsychores.2018.09.012

    Article  Google Scholar 

  14. Renna ME, Shrout MR, Madison AA, Alfano CM et al (2020) Within-person changes in cancer-related distress predict breast cancer survivors’ inflammation across treatment. Psychoneuroendocrinology 121:104866. https://doi.org/10.1016/j.psyneuen.2020.104866

    Article  CAS  Google Scholar 

  15. Culver JL, Arena PL, Antoni MH, Carver CS (2002) Coping and distress among women under treatment for early stage breast cancer: comparing african americans, hispanics and non-hispanic whites. Psychooncology 11(6):495–504. https://doi.org/10.1002/pon.615

    Article  Google Scholar 

  16. Fayanju OM, Yenokyan K, Ren Y, Goldstein BA et al (2019) The effect of treatment on patient-reported distress after breast cancer diagnosis. Cancer 125(17):3040–3049. https://doi.org/10.1002/cncr.32174

    Article  CAS  Google Scholar 

  17. Fayanju OM, Ren Y, Stashko I, Power S et al (2021) Patient-reported causes of distress predict disparities in time to evaluation and time to treatment after breast cancer diagnosis. Cancer 127(5):757–768. https://doi.org/10.1002/cncr.33310

    Article  CAS  Google Scholar 

  18. Wittenberg L, Yutsis M, Taylor S, Giese-Davis J et al (2010) Marital status predicts change in distress and well-being in women newly diagnosed with breast cancer and their peer counselors. Breast J 16(5):481–489. https://doi.org/10.1111/j.1524-4741.2010.00964.x

    Article  Google Scholar 

  19. Mertz BG, Bistrup PE, Johansen C, Dalton SO et al (2012) Psychological distress among women with newly diagnosed breast cancer. Eur J Oncol Nurs 16(4):439–443. https://doi.org/10.1016/j.ejon.2011.10.001

    Article  Google Scholar 

  20. Politi MC, Enright TM, Weihs KL (2007) The effects of age and emotional acceptance on distress among breast cancer patients. Support Care Cancer 15(1):73–79. https://doi.org/10.1007/s00520-006-0098-6

    Article  Google Scholar 

  21. Pirl WF, Fann JR, Greer JA, Braun I et al (2014) Recommendations for the implementation of distress screening programs in cancer centers: report from the American psychosocial oncology society (APOS), association of oncology social work (AOSW), and oncology nursing society (ons) joint task force. Cancer 120(19):2946–2954. https://doi.org/10.1002/cncr.28750

    Article  Google Scholar 

  22. Ma X, Zhang J, Zhong W, Shu C et al (2014) The diagnostic role of a short screening tool–the distress thermometer: a meta-analysis. Support Care Cancer 22(7):1741–1755. https://doi.org/10.1007/s00520-014-2143-1

    Article  Google Scholar 

  23. Ploos van Amstel FK, Tol J, Sessink KH, van der Graaf WTA et al (2017) A specific distress cutoff score shortly after breast cancer diagnosis. Cancer Nurs 40(3):E35-e40. https://doi.org/10.1097/ncc.0000000000000380

    Article  Google Scholar 

  24. Corporation I. IBM SPSS Statistics for Windows 1989. 2016 Armon, N.Y

  25. Kuznetsova A, Brockhoff PB, Christensen RHB (2017) lmerTest package: tests in linear mixed effects models. J Stat Softw 82(13):1–26. https://doi.org/10.18637/jss.v082.i13

    Article  Google Scholar 

  26. Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. J Stat Softw 67(1):1–48. https://doi.org/10.18637/jss.v067.i01

    Article  Google Scholar 

  27. Wang J, Haiyi X, Fisher JH (2012) Application of multilevel modelling to longitudinal data, in Multilevel Models. Applications using SAS. Higher Eduction Press and Walter de Gruyter GmbH & Co., Berlin

    Google Scholar 

  28. Helgeson VS, Snyder P, Seltman H (2004) Psychological and physical adjustment to breast cancer over 4 years: identifying distinct trajectories of change. Health Psychol 23(1):3

    Article  Google Scholar 

  29. Assari S, Khoshpouri P, Chalian H (2019) Combined effects of race and socioeconomic status on cancer beliefs, cognitions, and emotions. Healthcare (Basel, Switzerland) 7(1):17. https://doi.org/10.3390/healthcare7010017

    Article  Google Scholar 

  30. Ashing-Giwa KT, Padilla G, Tejero J, Kraemer J et al (2004) Understanding the breast cancer experience of women: a qualitative study of African American, Asian American. Lat Cauc Cancer Surviv Psychooncology 13(6):408–428. https://doi.org/10.1002/pon.750

    Article  Google Scholar 

  31. Thomas EJ, Elliott R (2009) Brain imaging correlates of cognitive impairment in depression. Front Hum Neurosci. https://doi.org/10.3389/neuro.09.030.2009

    Article  Google Scholar 

  32. Spencer SM, Lehman JM, Wynings C, Arena P et al (1999) Concerns about breast cancer and relations to psychosocial well-being in a multiethnic sample of early-stage patients. Health Psychol 18(2):159–168. https://doi.org/10.1037/0278-6133.18.2.159

    Article  CAS  Google Scholar 

Download references

Funding

This work was supported by the National Institutes of Health/National Cancer Institute under award number (Grant No. P30CA016672).

Author information

Authors and Affiliations

Authors

Contributions

TL and DT contributed to the study conception and design. Material preparation and data collection were performed by TL and ET. Analyses were performed by TL. The first draft of the manuscript was written by TL and ZK. All authors commented on previous versions of the manuscript and read and approved the final manuscript.

Corresponding author

Correspondence to Tamara E. Lacourt.

Ethics declarations

Conflict of interest

The authors have no relevant financial or non-financial interests to disclose.

Ethical approval

This observational study and a corresponding waiver for consent was approved by the institution’s Internal Review Board.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lacourt, T.E., Koncz, Z., Tullos, E.A. et al. A detailed description of the distress trajectory from pre- to post-treatment in breast cancer patients receiving neoadjuvant chemotherapy. Breast Cancer Res Treat 197, 299–305 (2023). https://doi.org/10.1007/s10549-022-06805-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10549-022-06805-y

Keywords

Navigation