Medical care disruptions during the first six months of the COVID-19 pandemic: the experience of older breast cancer survivors

A Dilawari, K E Rentscher, W Zhai, X Zhou, T A Ahles, J Ahn, T N Bethea, J E Carroll, H J Cohen, D A Graham, H S L Jim, B McDonald, Z M Nakamura, S K Patel, J C Root, B J Small, A J Saykin, D Tometich, K Van Dyk, J S Mandelblatt, Thinking and Living with Cancer Study, A Dilawari, K E Rentscher, W Zhai, X Zhou, T A Ahles, J Ahn, T N Bethea, J E Carroll, H J Cohen, D A Graham, H S L Jim, B McDonald, Z M Nakamura, S K Patel, J C Root, B J Small, A J Saykin, D Tometich, K Van Dyk, J S Mandelblatt, Thinking and Living with Cancer Study

Abstract

Purpose: Older cancer survivors required medical care during the COVID-19 pandemic, but there are limited data on medical care in this age group.

Methods: We evaluated care disruptions in a longitudinal cohort of non-metastatic breast cancer survivors aged 60-98 from five US regions (n = 321). Survivors completed a web-based or telephone survey from May 27, 2020 to September 11, 2020. Care disruptions included interruptions in seeing or speaking to doctors, receiving medical treatment or supportive therapies, or filling prescriptions since the pandemic began. Logistic regression models evaluated associations between care disruptions and education, medical, psychosocial, and COVID-19-related factors. Multivariate models included age, county COVID-19 death rates, comorbidity, and post-diagnosis time.

Results: There was a high response rate (n = 262, 81.6%). Survivors were 32.2 months post-diagnosis (SD 17.5, range 4-73). Nearly half (48%) reported a medical disruption. The unadjusted odds of care disruptions were higher with each year of education (OR 1.22, 95% CI 1.08-1.37, p = < 0.001) and increased depression by CES-D score (OR 1.04, CI 1.003-1.08, p = 0.033) while increased tangible support decreased the odds of disruptions (OR 0.99, 95% CI 0.97-0.99, p = 0.012). There was a trend between disruptions and comorbidities (unadjusted OR 1.13 per comorbidity, 95% CI 0.99-1.29, p = 0.07). Adjusting for covariates, higher education years (OR1.23, 95% CI 1.09-1.39, p = 0.001) and tangible social support (OR 0.98 95% CI 0.97-1.00, p = 0.006) remained significantly associated with having care disruptions.

Conclusion: Older breast cancer survivors reported high rates of medical care disruptions during the COVID-19 pandemic and psychosocial factors were associated with care disruptions. CLINICALTRIALS.

Gov identifier: NCT03451383.

Keywords: Breast cancer; COVID; Cancer survivors; Medical care disruptions; Older adults.

Conflict of interest statement

AAD attended the Cardinal Health 2020 Advisor Board Oncology Committee. HSJ: Consulting or Advisory Role: Janssen Pharmaceuticals and RedHill Biopharma. DG: Stock and Other Ownership Interests: Cota. AJS: Consulting or Advisory Role: Bayer AG Research Funding: Eli Lilly (Inst).

© 2021. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Figures

Fig. 1
Fig. 1
A sample for evaluation of medical disruptions in older breast cancer survivors. Participants were excluded if they were not active (i.e., had completed the study, dropped out, or deceased) since the start of survey data collection. The percentage who completed and refused was calculated among those active and eligible to complete the survey. 1Participants were ineligible if they had a COVID-19 diagnosis or were missing information about chemotherapy or hormonal treatment for breast cancer

References

    1. Kutikov A, Weinberg DS, Edelman MJ, Horwitz EM, Uzzo RG, Fisher RI. A war on two fronts: cancer care in the time of COVID-19. Ann Intern Med. 2020;172(11):756–758. doi: 10.7326/M20-1133.
    1. Masroor S. Collateral damage of COVID-19 pandemic: delayed medical care. J Card Surg. 2020;35(6):1345–1347. doi: 10.1111/jocs.14638.
    1. Feral-Pierssens AL, Claret PG, Chouihed T. Collateral damage of the COVID-19 outbreak: expression of concern. Eur J Emerg Med. 2020;27(4):233–234. doi: 10.1097/MEJ.0000000000000717.
    1. Al-Shamsi HO, Alhazzani W, Alhuraiji A, et al. A practical approach to the management of cancer patients during the novel coronavirus disease 2019 (COVID-19) pandemic: an international collaborative group. The Oncologist. 2020 doi: 10.1634/theoncologist.2020-0213.
    1. Curigliano G, Banerjee S, Cervantes A, et al. Managing cancer patients during the COVID-19 pandemic: an ESMO multidisciplinary expert consensus. Ann Oncol. 2020;31(10):1320–1335. doi: 10.1016/j.annonc.2020.07.010.
    1. Viale G, Licata L, Sica L, et al. Personalized risk-benefit ratio adaptation of breast cancer care at the epicenter of the COVID-19 outbreak. Oncologist. 2020;25(7):e1013–e1020. doi: 10.1634/theoncologist.2020-0316.
    1. Chong TWH, Curran E, Ames D, Lautenschlager NT, Castle DJ. Mental health of older adults during the COVID-19 pandemic: lessons from history to guide our future. Int Psychogeriatr. 2020;32(10):1249–1250. doi: 10.1017/S1041610220001003.
    1. Yosh Chida Y, Hamer M, Wardle J, et al. Do stress-related psychosocial factors contribute to cancer incidence and survival? Nat Clin Pract Oncol. 2008;5(8):466–475. doi: 10.1038/ncponc1134.
    1. Mandelblatt JS, Small BJ, Luta G, et al. Cancer-related cognitive outcomes among older breast cancer survivors in the thinking and living with cancer study. J Clin Oncol. 2018 doi: 10.1200/JCO.18.00140.
    1. COVID-19 OBSSR Research Tools. NIH Office of Behavioral and Social Sciences Research (OBSSR) with assistance from the NIH Disaster Research program (DR2)
    1. The New York Times. Coronavirus (Covid-19) Data in the United States. . Updated 2020. Accessed Oct 2020
    1. U.S. Department of Agriculture Economic Research Services. Population Estimates for the U.S., States, and Counties, 2010-19. . Updated 2020. Accessed Oct 2020
    1. Bergua V, Meillon C, Potvin O, Bouisson J, Le Goff M, et al. The STAI-Y trait scale: psychometric properties and normative data from a large population-based study of elderly people. Int Psychogeriatr. 2002;24(7):1163–1171. doi: 10.1017/S1041610212000300.
    1. Cosco T, Stubbs Prina M, B,, et al. Reliability and validity of the center for epidemiologic studies depression scale in a population-based cohort of middle-aged U.S. Adults J Nurs Meas. 2017;25(3):476–485. doi: 10.1891/1061-3749.25.3.476.
    1. Priede A, Andreu Y, Martínez P, Conchado A, Ruiz-Torres M, González-Blanch C. The factor structure of the medical outcomes study-social support survey: a comparison of different models in a sample of recently diagnosed cancer patients. J Psychosom Res. 2018;108:32–38. doi: 10.1016/j.jpsychores.2018.02.008.
    1. Cella DF, Tulsky DS, Gray G, et al. The functional assessment of cancer therapy scale: development and validation of the general measure. J Clin Oncol. 1993;11(3):570–579. doi: 10.1200/JCO.1993.11.3.570.
    1. Yang J, Wahner-Roedler DL, Chon TY, Bauer BA (2021) Integrative medicine treatment in times of pandemic coronavirus disease? Med Acupunct 33(1):107–114. 10.1089/acu.2020.1441
    1. Czeisler MÉ, Marynak K, Clarke KE, et al. Delay or avoidance of medical care because of COVID-19–related concerns—United States, 2020. MMWR Morb Mortal Wkly Rep. 2020;69:1250–1257. doi: 10.15585/mmwr.mm6936a4.
    1. Wong SYS, Zhang D, Sit RWS, Yip BHK, Chung RY, Wong CKM, Chan DCC, Sun W, Kwok KO, Mercer SW. Impact of COVID-19 on loneliness, mental health, and health service utilisation: a prospective cohort study of older adults with multimorbidity in primary care. Br J Gen Pract. 2020;70(700):e817–e824. doi: 10.3399/bjgp20X713021.
    1. Sheinfeld Gorin SN, Jimbo M, Heizelman R, et al. The future of cancer screening after COVID-19 may be at home. Cancer. 2020;127(4):498–503. doi: 10.1002/cncr.33274.
    1. Bakouny Z, Paciotti M, Schmidt AL, Lipsitz SR, Choueiri TK, Trinh Q. Cancer Screening tests and cancer diagnoses during the COVID-19 pandemic. JAMA Oncol. 2021;7(3):458–460. doi: 10.1001/jamaoncol.2020.7600.
    1. Yvonne Michael Y, Berkman LF, Colditz AG, et al. Social networks and health-related quality of life in breast cancer survivors: a prospective study. J Psychosom Res. 2002;52(5):285–293. doi: 10.1016/S0022-3999(01)00270-7.
    1. Kroenke CH, Quesenberry C, Kwan ML, Sweeney C, Castillo A, Caan BJ. Social networks, social support, and burden in relationships, and mortality after breast cancer diagnosis in the life after breast cancer epidemiology (LACE) study. Breast Cancer Res Treat. 2013;137(1):261–271. doi: 10.1007/s10549-012-2253-8.
    1. Berkman ND, Sheridan SL, Donahue KE, Halpern DJ, Crotty K. Low health literacy and health outcomes: an updated systematic review. Ann Intern Med. 2011;155(2):97–107. doi: 10.7326/0003-4819-155-2-201107190-00005.

Source: PubMed

3
Abonner