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Prognostic Potential of Electrocardiographic Parameters in Patients with Multiple Myeloma: A Retrospective Analysis of the Multiple Myeloma Population

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Abstract

Introduction

Patients with multiple myeloma (MM) can develop cardiac abnormalities, predisposing them to the development of heart failure, arrhythmias, or infarction with poor prognosis. The purpose of this study is to evaluate the prognostic potential of electrocardiographic (ECG) parameters in patients with MM.

Methods

This study retrospectively included patients with MM from January 2010 to December 2018 in the First Affiliated Hospital of Xi’an Jiao Tong University. Univariate and multivariate Cox proportional hazard models were conducted to evaluate the relationship between ECG parameters and all-cause mortality in patients with MM.

Results

A total of 409 patients were included (mean age 61.3 ± 9.7 years, 59.2% male). The relationship between ECG parameters (including PR interval, voltage, QRS axis, QRS duration, and QTc interval) and all-cause mortality in patients with MM was evaluated. Overall, patients with QTc interval ≥ 400 ms have a significantly higher all-cause mortality compared to those with QTc interval < 400 ms (P < 0.001). When stratified by the International Staging System (ISS), this relationship was true for stages II and III (P < 0.01), but not stage I (P > 0.05). Patients with MM and QRS duration ≥ 120 ms had a higher all-cause mortality compared to those with QRS duration < 120 ms for women (P < 0.01) but not for men (P > 0.05). PR interval, voltage, and QRS axis did not predict mortality.

Conclusion

QTc interval was independently associated with all-cause mortality in patients with MM, especially when QTc interval was more than 400 ms in more advanced stages II and III. ECG parameters may provide prognostic potential in patients with MM and aid risk stratification of these patients.

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References

  1. Kyle RA, Rajkumar SV. Multiple myeloma. N Engl J Med. 2004;351:1860–73.

    Article  CAS  Google Scholar 

  2. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2013. CA Cancer J Clin. 2013;63:11–30.

    Article  Google Scholar 

  3. Bahlis NJ, Lazarus HM. Multiple myeloma-associated AL amyloidosis: is a distinctive therapeutic approach warranted? Bone Marrow Transplant. 2006;38:7–15.

    Article  CAS  Google Scholar 

  4. Desikan KR, Dhodapkar MV, Hough A, et al. Incidence and impact of light chain associated (AL) amyloidosis on the prognosis of patients with multiple myeloma treated with autologous transplantation. Leuk Lymphoma. 1997;27:315–9.

    Article  CAS  Google Scholar 

  5. Augustson BM, Begum G, Dunn JA, et al. Early mortality after diagnosis of multiple myeloma: analysis of patients entered onto the United Kingdom Medical Research Council trials between 1980 and 2002–Medical Research Council Adult Leukaemia Working Party. J Clin Oncol. 2005;23:9219–26.

    Article  Google Scholar 

  6. Kim D, Lee GY, Choi JO, Kim K, Kim SJ, Jeon ES. Associations of electrocardiographic parameters with left ventricular longitudinal strain and prognosis in cardiac light chain amyloidosis. Sci Rep. 2019;9:7746.

    Article  Google Scholar 

  7. Mohty D, Damy T, Cosnay P, et al. Cardiac amyloidosis: updates in diagnosis and management. Arch Cardiovasc Dis. 2013;106:528–40.

    Article  Google Scholar 

  8. Hidayet Ş, Demir V, Turan Y, Gürel G, Taşolar MH. Evaluation of Tp-e interval, Tp-e/QT ratio, and Tp-e/QTc ratio in patients with Behçet’s disease. Anatol J Cardiol. 2019;22:85–90.

    PubMed  PubMed Central  Google Scholar 

  9. Kumar SK, Callander NS, Alsina M, et al. Multiple myeloma, version 3.2017, NCCN clinical practice guidelines in oncology. J Natl Compr Cancer Netw. 2017;15:230–69.

    Article  Google Scholar 

  10. Greipp PR, San Miguel J, Durie BG, et al. International staging system for multiple myeloma. J Clin Oncol. 2005;23:3412–20.

    Article  Google Scholar 

  11. Palumbo A, Avet-Loiseau H, Oliva S, et al. Revised international staging system for multiple myeloma: a report from international myeloma working group. J Clin Oncol. 2015;33:2863–9.

    Article  CAS  Google Scholar 

  12. Avet-Loiseau H, Attal M, Moreau P, et al. Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myelome. Blood. 2007;109:3489–95.

    Article  CAS  Google Scholar 

  13. Binder M, Rajkumar SV, Ketterling RP, et al. Substratification of patients with newly diagnosed standard-risk multiple myeloma. Br J Haematol. 2019;185:254–60.

    Article  Google Scholar 

  14. Plummer C, Driessen C, Szabo Z, Mateos MV. Management of cardiovascular risk in patients with multiple myeloma. Blood Cancer J. 2019;9:26.

    Article  Google Scholar 

  15. Patel VG, Cornell RF. Cardiovascular complications associated with multiple myeloma therapies: incidence, pathophysiology, and management. Curr Oncol Rep. 2019;21:29.

    Article  Google Scholar 

  16. Buss SJ, Emami M, Mereles D, et al. Longitudinal left ventricular function for prediction of survival in systemic light-chain amyloidosis: incremental value compared with clinical and biochemical markers. J Am Coll Cardiol. 2012;60:1067–76.

    Article  Google Scholar 

  17. Koyama J, Falk RH. Prognostic significance of strain Doppler imaging in light-chain amyloidosis. JACC Cardiovasc Imaging. 2010;3:333–42.

    Article  Google Scholar 

  18. Grogan M, Dispenzieri A, Gertz MA. Light-chain cardiac amyloidosis: strategies to promote early diagnosis and cardiac response. Heart. 2017;103:1065–72.

    Article  CAS  Google Scholar 

  19. Cyrille NB, Goldsmith J, Alvarez J, Maurer MS. Prevalence and prognostic significance of low QRS voltage among the three main types of cardiac amyloidosis. Am J Cardiol. 2014;114:1089–93.

    Article  Google Scholar 

  20. Zhao L, Li J, Tian Z, Fang Q. Clinical correlates and prognostic values of pseudoinfarction in cardiac light-chain amyloidosis. J Cardiol. 2016;68:426–30.

    Article  Google Scholar 

  21. Perlini S, Salinaro F, Cappelli F, et al. Prognostic value of fragmented QRS in cardiac AL amyloidosis. Int J Cardiol. 2013;167:2156–61.

    Article  Google Scholar 

  22. Murtagh B, Hammill SC, Gertz MA, Kyle RA, Tajik AJ, Grogan M. Electrocardiographic findings in primary systemic amyloidosis and biopsy-proven cardiac involvement. Am J Cardiol. 2005;95:535–7.

    Article  Google Scholar 

  23. Zhang N, Gong M, Tse G, et al. Prolonged corrected QT interval in predicting atrial fibrillation: a systematic review and meta-analysis. Pacing Clin Electrophysiol PACE. 2018;41:321–7.

    Article  Google Scholar 

  24. Chauhan K, Ackerman MJ, Crowson CS, Matteson EL, Gabriel SE. Population-based study of QT interval prolongation in patients with rheumatoid arthritis. Clin Exp Rheumatol. 2015;33:84–9.

    PubMed  PubMed Central  Google Scholar 

  25. Montanez A, Ruskin JN, Hebert PR, Lamas GA, Hennekens CH. Prolonged QTc interval and risks of total and cardiovascular mortality and sudden death in the general population: a review and qualitative overview of the prospective cohort studies. Arch Intern Med. 2004;164:943–8.

    Article  Google Scholar 

  26. Liu P, Wang L, Han D, Sun C, Xue X, Li G. Acquired long QT syndrome in chronic kidney disease patients. Ren Fail. 2020;42:54–65.

    Article  Google Scholar 

  27. Porthan K, Viitasalo M, Jula A, et al. Predictive value of electrocardiographic QT interval and T-wave morphology parameters for all-cause and cardiovascular mortality in a general population sample. Heart Rhythm. 2009;6(1202):1208.

    Google Scholar 

  28. Buppajarntham S, Seetha Rammohan HR, Junpaparp P, Figueredo VM. Prognostic value of prolonged QTc interval in patients with acute pulmonary embolism. Acta Cardiol. 2014;69:550–5.

    Article  Google Scholar 

  29. Kim I-J, Yang P-S, Kim T-H, et al. Relationship between anemia and the risk of sudden cardiac arrest—a nationwide cohort study in South Korea. Circ J. 2018;82:2962–9.

    Article  Google Scholar 

  30. Xu D, Murakoshi N, Sairenchi T, et al. Anemia and reduced kidney function as risk factors for new onset of atrial fibrillation (from the Ibaraki prefectural health study). Am J Cardiol. 2015;115:328–33.

    Article  Google Scholar 

  31. Cherng NC, Asal NR, Kuebler JP, Lee ET, Solanki D. Prognostic factors in multiple myeloma. Cancer. 1991;67:3150–6.

    Article  CAS  Google Scholar 

  32. Boyd KD, Ross FM, Chiecchio L, et al. Gender disparities in the tumor genetics and clinical outcome of multiple myeloma. Cancer Epidemiol Biomark Prev. 2011;20:1703–7.

    Article  Google Scholar 

  33. Kuiper R, van Duin M, van Vliet MH, et al. Prediction of high- and low-risk multiple myeloma based on gene expression and the International Staging System. Blood. 2015;126:1996–2004.

    Article  CAS  Google Scholar 

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Acknowledgements

We thank the participants of the study.

Funding

This study was funded by the Clinical Research Program of the First Affiliated Hospital of Xi’an Jiaotong University of China (XJTU1AF-CRF-2018-015). The journal’s Rapid Service Fee was funded by the authors.

Authorship

All authors contributed to drafting the manuscript, reviewing the manuscript content critically, and designing and implementation of the research. All named authors meet the International Committee of Medical Journal Editors (ICMJE) criteria for authorship for this article, take responsibility for the integrity of the work as a whole, and have given their approval for this version to be published.

Disclosures

Jie Wang, Jiaqi An, Gary Tse, Pengcheng He, Haibo Liu, Aifeng Zhang, Guoliang Li, Yongxin Li, Chaofeng Sun and Yang Yan have nothing to disclose.

Compliance with Ethics Guidelines

This study analysis was conducted in accordance with the 1964 declaration of Helsinki and its later amendments and was approved by the Ethic Committee of the First Affiliated Hospital of Xi’an Jiao Tong University. Informed consent with consent to use clinical data for research purposes was obtained from all patients or relatives.

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Correspondence to Chaofeng Sun or Yang Yan.

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Wang, J., An, J., Tse, G. et al. Prognostic Potential of Electrocardiographic Parameters in Patients with Multiple Myeloma: A Retrospective Analysis of the Multiple Myeloma Population. Adv Ther 37, 2946–2955 (2020). https://doi.org/10.1007/s12325-020-01343-9

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  • DOI: https://doi.org/10.1007/s12325-020-01343-9

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