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Self-reported health and survival in older patients diagnosed with multiple myeloma

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Abstract

Purpose

Patient-reported outcomes such as self-reported health (SRH) are important in understanding quality cancer care, yet little is known about links between SRH and outcomes in older patients with multiple myeloma (MM). We evaluated associations between SRH and mortality among older patients with MM.

Methods

We analyzed a retrospective cohort of patients ages ≥ 65 years diagnosed with first primary MM using the Surveillance, Epidemiology, and End Results (SEER)-Medicare Health Outcomes Survey (MHOS) data resource. Pre-diagnosis SRH was grouped as high (excellent/very good/good) or low (fair/poor). We used Cox proportional hazards models to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for associations between SRH and all-cause and MM-specific mortality.

Results

Of 521 MM patients with mean (SD) age at diagnosis of 76.8 (6.1) years, 32% reported low SRH. In multivariable analyses, low SRH was suggestive of modest increased risks of all-cause mortality (HR 1.32, 95% CI 1.02–1.71) and MM-specific mortality (HR 1.22, 95% CI 0.87–1.70) compared to high SRH.

Conclusion

Findings suggest that low pre-diagnosis SRH is highly prevalent among older patients with MM and is associated with modestly increased all-cause mortality. Additional research is needed to address quality of life and modifiable factors that may accompany poor SRH in older patients with MM.

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References

  1. Kyle RA, Rajkumar SV (2008) Multiple myeloma. Blood 111(6):2962–2972

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Kazandjian D (2016) Multiple myeloma epidemiology and survival: a unique malignancy. Semin Oncol 43(6):676–681

    Article  PubMed  PubMed Central  Google Scholar 

  3. Howlader N, Noone AM, Krapcho M, Miller D, Brest A, Yu M, Ruhl J, Tatalovich Z, Mariotto A, Lewis DR, Chen HS, Feuer EJ, Cronin KA (eds) (2019) SEER Cancer Statistics Review, 1975–2016, National Cancer Institute. Bethesda, MD, https://seer.cancer.gov/csr/1975_2016/, based on November 2018 SEER data submission, posted to the SEER web site, April 2019

  4. Colson K (2015) Treatment-related symptom management in patients with multiple myeloma: a review. Support Care Cancer 23(5):1431–1445

    Article  PubMed  Google Scholar 

  5. Gay F, Palumbo A (2010) Multiple myeloma: management of adverse events. Med Oncol 27(3):646–653

    Article  CAS  PubMed  Google Scholar 

  6. Molenaar S, Oort F, Sprangers M et al (2004) Predictors of patients' choices for breast-conserving therapy or mastectomy: a prospective study. Br J Cancer 90(11):2123–2130

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Engelhardt EG, Revesz D, Tamminga HJ et al (2018) Clinical usefulness of tools to support decision-making for palliative treatment of metastatic colorectal cancer: a systematic review. Clin Colorectal Cancer 17(1):e1–e12

    Article  PubMed  Google Scholar 

  8. Latini DM, Hart SL, Knight SJ et al (2007) The relationship between anxiety and time to treatment for patients with prostate cancer on surveillance. J Urology 178(3):826–831

    Article  Google Scholar 

  9. Wisloff F, Hjorth M (1997) Health-related quality of life assessed before and during chemotherapy predicts for survival in multiple myeloma. Nordic Myeloma Study Group. Br J Haematol 97(1):29–37

    Article  CAS  PubMed  Google Scholar 

  10. Dubois D, Dhawan R, van de Velde H et al (2006) Descriptive and prognostic value of patient-reported outcomes: the bortezomib experience in relapsed and refractory multiple myeloma. J Clin Oncol 24(6):976–982

    Article  CAS  PubMed  Google Scholar 

  11. Efficace F, Gaidano G, Breccia M et al (2015) Prognostic value of self-reported fatigue on overall survival in patients with myelodysplastic syndromes: a multicentre, prospective, observational, cohort study. Lancet Oncol 16(15):1506–1514

    Article  PubMed  Google Scholar 

  12. Stover AM, Basch EM (2016) Using patient-reported outcome measures as quality indicators in routine cancer care. Cancer 122(3):355–357

    Article  PubMed  Google Scholar 

  13. Murthy HS, Wood WA (2015) The value of patient reported outcomes and other patient-generated health data in clinical hematology. Curr Hematol Malig Rep 10(3):213–224

    Article  PubMed  Google Scholar 

  14. Ul-Haq Z, Mackay DF, Pell JP (2014) Association between self-reported general and mental health and adverse outcomes: a retrospective cohort study of 19,625 Scottish adults. PLoS ONE 9(4):e93857

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Benjamins MR, Hummer RA, Eberstein IW, Nam CB (2004) Self-reported health and adult mortality risk: an analysis of cause-specific mortality. Soc Sci Med 59(6):1297–1306

    Article  PubMed  Google Scholar 

  16. Giltay EJ, Vollaard AM, Kromhout D (2012) Self-rated health and physician-rated health as independent predictors of mortality in elderly men. Age Ageing 41(2):165–171

    Article  PubMed  Google Scholar 

  17. Hoffman RM, Koyama T, Albertsen PC et al (2015) Self-reported health status predicts other-cause mortality in men with localized prostate cancer: results from the prostate cancer outcomes study. J Gen Intern Med 30(7):924–934

    Article  PubMed  PubMed Central  Google Scholar 

  18. Stenholm S, Kivimaki M, Jylha M et al (2016) Trajectories of self-rated health in the last 15 years of life by cause of death. Eur J Epidemiol 31(2):177–185

    Article  PubMed  Google Scholar 

  19. Shadbolt B, Barresi J, Craft P (2002) Self-rated health as a predictor of survival among patients with advanced cancer. J Clin Oncol 20(10):2514–2519

    Article  PubMed  Google Scholar 

  20. Mohan R, Beydoun HA, Beydoun MA et al (2011) Self-rated health as a tool for estimating health-adjusted life expectancy among patients newly diagnosed with localized prostate cancer: a preliminary study. Qual Life Res 20(5):713–721

    Article  PubMed  Google Scholar 

  21. Ganna A, Ingelsson E (2015) 5 year mortality predictors in 498,103 UK Biobank participants: a prospective population-based study. Lancet 386(9993):533–540

    Article  PubMed  Google Scholar 

  22. McGee DL, Liao Y, Cao G, Cooper RS (1999) Self-reported health status and mortality in a multiethnic US cohort. Am J Epidemiol 149(1):41–46

    Article  CAS  PubMed  Google Scholar 

  23. Jylha M (2009) What is self-rated health and why does it predict mortality? Towards a unified conceptual model. Soc Sci Med 69(3):307–316

    Article  PubMed  Google Scholar 

  24. Knauper B, Turner PA (2003) Measuring health: improving the validity of health assessments. Qual Life Res 12(Suppl 1):81–89

    Article  PubMed  Google Scholar 

  25. Institute NC (2020) Brief description of the SEER-MHOS data resource. https://healthcaredelivery.cancer.gov/seer-mhos/overview/. Published 2018. Accessed 19 Mar 2020

  26. Kent EE, Ambs A, Mitchell SA, Clauser SB, Smith AW, Hays RD (2015) Health-related quality of life in older adult survivors of selected cancers: data from the SEER-MHOS linkage. Cancer 121(5):758–765

    Article  PubMed  Google Scholar 

  27. Ambs A, Warren JL, Bellizzi KM, Topor M, Haffer SC, Clauser SB (2008) Overview of the SEER—medicare health outcomes survey linked dataset. Health Care Financ Rev 29(4):5–21

    PubMed  PubMed Central  Google Scholar 

  28. Institute NC (2020) What is a cancer registry? https://seer.cancer.gov/registries/cancer_registry/index.html. Published 2019. Accessed 19 Mar 2020

  29. Iqbal S, Rogers W, Selim A, et al. The Veterans rand 12 item health survey (VR-12): what it is and how it is used. https://www.bu.edu/sph/files/2015/01/veterans_rand_12_item_health_survey_vr-12_2007.pdf. Accessed 19 Mar 2020

  30. Ware JE Jr, Sherbourne CD (1992) The MOS 36-item short-form health survey (SF-36). I. Conceptual framework and item selection. Med Care 30(6):473–483

    Article  PubMed  Google Scholar 

  31. Selim A, Rogers W, Qian S, Rothendler JA, Kent EE, Kazis LE (2018) A new algorithm to build bridges between two patient-reported health outcome instruments: the MOS SF-36(R) and the VR-12 Health Survey. Qual Life Res 27(8):2195–2206

    Article  PubMed  Google Scholar 

  32. Usman Iqbal S, Rogers W, Selim A, et al (2007) The Veterans Rand 12 Item Health Survey (Vr-12): what it is and how it is used. Technical Report

  33. Farivar SS, Cunningham WE, Hays RD (2007) Correlated physical and mental health summary scores for the SF-36 and SF-12 Health Survey V.I. Health Qual Life Outcomes 5:54

    Article  PubMed  PubMed Central  Google Scholar 

  34. Gooley TA, Leisenring W, Crowley J, Storer BE (1999) Estimation of failure probabilities in the presence of competing risks: new representations of old estimators. Stat Med 18(6):695–706

    Article  CAS  PubMed  Google Scholar 

  35. Varadhan R, Weiss CO, Segal JB, Wu AW, Scharfstein D, Boyd C (2010) Evaluating health outcomes in the presence of competing risks: a review of statistical methods and clinical applications. Med Care 48(6 Suppl):S96–105

    Article  PubMed  Google Scholar 

  36. Fine JP, Gray RJ (1999) A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc 94(446):496–509

    Article  Google Scholar 

  37. Foundation IM (2020) Multiple myeloma drug guide. https://www.myeloma.org/multiple-myeloma-drugs. Published 2017. Accessed 19 Mar 2020

  38. Roydhouse JK, Gutman R, Keating NL, Mor V, Wilson IB (2018) Proxy and patient reports of health-related quality of life in a national cancer survey. Health Qual Life Outcomes 16(1):6

    Article  PubMed  PubMed Central  Google Scholar 

  39. Wolinsky FD, Jones MP, Wehby GL (2012) Gathering data from older adults via proxy respondents: research challenges. J Comp Eff Res 1(6):467–470

    Article  PubMed  Google Scholar 

  40. Rottenberg Y, Litwin H, Manor O, Paltiel A, Barchana M, Paltiel O (2014) Prediagnostic self-assessed health and extent of social networks predict survival in older individuals with cancer: a population based cohort study. J Geriatr Oncol 5(4):400–407

    Article  PubMed  Google Scholar 

  41. Bamia C, Orfanos P, Juerges H et al (2017) Self-rated health and all-cause and cause-specific mortality of older adults: Individual data meta-analysis of prospective cohort studies in the CHANCES Consortium. Maturitas 103:37–44

    Article  PubMed  Google Scholar 

  42. Mian HS, Wildes TM, Fiala MA (2018) Development of a medicare health outcomes survey deficit-accumulation frailty index and its application to older patients with newly diagnosed multiple myeloma. JCO Clin Cancer Inf. https://doi.org/10.1200/CCI.18.00043

    Article  Google Scholar 

  43. Idler EL, Benyamini Y (1997) Self-rated health and mortality: a review of twenty-seven community studies. J Health Soc Behav 38(1):21–37

    Article  CAS  PubMed  Google Scholar 

  44. Kaplan G, Barell V, Lusky A (1988) Subjective state of health and survival in elderly adults. J Gerontol 43(4):S114–120

    Article  CAS  PubMed  Google Scholar 

  45. Mossey JM, Shapiro E (1982) Self-rated health: a predictor of mortality among the elderly. Am J Public Health 72(8):800–808

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. German RR, Fink AK, Heron M et al (2011) The accuracy of cancer mortality statistics based on death certificates in the United States. Cancer Epidemiol 35(2):126–131

    Article  PubMed  Google Scholar 

  47. Smith AW, Reeve BB, Bellizzi KM et al (2008) Cancer, comorbidities, and health-related quality of life of older adults. Health Care Financ Rev 29(4):41–56

    PubMed  PubMed Central  Google Scholar 

  48. Riley G (2000) Two-year changes in health and functional status among elderly Medicare beneficiaries in HMOs and fee-for-service. Health Serv Res 35(5 Pt 3):44–59

    CAS  PubMed  PubMed Central  Google Scholar 

  49. Keyes KM, Rutherford C, Popham F, Martins SS, Gray L (2018) How Healthy are survey respondents compared with the general population? Using survey-linked death records to compare mortality outcomes. Epidemiology 29(2):299–307

    Article  PubMed  PubMed Central  Google Scholar 

  50. Koshiaris C, Oke J, Abel L, Nicholson BD, Ramasamy K, Van den Bruel A (2018) Quantifying intervals to diagnosis in myeloma: a systematic review and meta-analysis. BMJ Open 8(6):e019758

    Article  PubMed  PubMed Central  Google Scholar 

  51. Pinheiro LC, Zagar TM, Reeve BB (2017) The prognostic value of pre-diagnosis health-related quality of life on survival: a prospective cohort study of older Americans with lung cancer. Qual Life Res 26(7):1703–1712

    Article  PubMed  PubMed Central  Google Scholar 

  52. Doll KM, Pinheiro LC, Reeve BB (2017) Pre-diagnosis health-related quality of life, surgery, and survival in women with advanced epithelial ovarian cancer: A SEER-MHOS study. Gynecol Oncol 144(2):348–353

    Article  PubMed  Google Scholar 

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Acknowledgments

This study used data from the Surveillance, Epidemiology, and End Results (SEER)-Medicare Health Outcomes Survey (MHOS) linked data resource. The authors acknowledge the efforts of the National Cancer Institute; the Centers for Medicare and Medicaid Services; MHOS; Information Management Services, Inc.; and the SEER Program tumor registries in the creation of the SEER-MHOS database. The National Cancer Institute provided suggested edits and approval of the manuscript before final journal submission.

Funding

The project described was supported by the National Institutes of Health, National Center for Advancing Translational Sciences through Grant Number KL2TR002002 (Calip), National Heart, Lung and Blood Institute through Grant Number R21HL140531 (Calip) and National Cancer Institute through Grant Number R01CA223662 (Chiu). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

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Authors and Affiliations

  1. Department of Pharmacy Systems, Outcomes and Policy, Center for Pharmacoepidemiology and Pharmacoeconomic Research, University of Illinois at Chicago, 833 S. Wood St. MC 871, Chicago, IL, 60612, USA

    Nadia A. Nabulsi, Ali Alobaidi, Brian Talon, Alemseged A. Asfaw, Jifang Zhou, Lisa K. Sharp & Gregory S. Calip

  2. Department of Pharmacy Practice, University of Illinois at Chicago, Chicago, IL, USA

    Karen Sweiss

  3. Division of Hematology and Oncology, Department of Medicine, University of Illinois at Chicago, Chicago, IL, USA

    Pritesh R. Patel

  4. Section of Hematology Oncology, Boston University School of Medicine, Boston, MA, USA

    Naomi Y. Ko

  5. Department of Public Health Sciences, The University of Chicago, Chicago, IL, USA

    Brian C.-H. Chiu

  6. Division of Public Health Sciences, Epidemiology Program, Fred Hutchinson Cancer Research Center, Seattle, WA, USA

    Gregory S. Calip

Authors
  1. Nadia A. Nabulsi
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  2. Ali Alobaidi
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  3. Brian Talon
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  4. Alemseged A. Asfaw
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  5. Jifang Zhou
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  6. Lisa K. Sharp
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  7. Karen Sweiss
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  8. Pritesh R. Patel
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  9. Naomi Y. Ko
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  10. Brian C.-H. Chiu
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  11. Gregory S. Calip
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Contributions

Study concepts: NAN, AA, BT, AAA, JZ, LKS, GSC; study design: NAN, AA, BT, AAA, JZ, LKS, GSC; data acquisition: AAA, JZ, GSC; quality control of data and algorithms: NAN, AA, BT, AAA, JZ, LKS, GSC; data analysis and interpretation: NAN, AA, GSC; statistical analysis: NAN, AA, GSC; manuscript preparation: NAN, AA, BT, AAA, JZ, LKS, KS, PRP, NYK, BCHC, GSC; Manuscript editing: NAN, AA, BT, AAA, JZ, LKS, KS, PRP, NYK, BCHC, GSC; manuscript review: NAN, AA, BT, AAA, JZ, LKS, KS, PRP, NYK, BCHC, GSC.

Corresponding author

Correspondence to Gregory S. Calip.

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Conflict of interest

Alobaidi—funded by the UIC/AbbVie Health Economics and Outcomes Research Fellowship (2018–2020); Patel—consultancy (Celgene, Janssen) and honoraria (Celgene, Janssen, Amgen); no other authors have relevant conflicts of interest to disclose.

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Nabulsi, N.A., Alobaidi, A., Talon, B. et al. Self-reported health and survival in older patients diagnosed with multiple myeloma. Cancer Causes Control 31, 641–650 (2020). https://doi.org/10.1007/s10552-020-01305-0

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  • DOI: https://doi.org/10.1007/s10552-020-01305-0

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