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Exploring core symptoms and interrelationships among symptoms in children with acute leukemia during chemotherapy: A network analysis

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Abstract

Purpose

Children with acute leukemia have suffered from a considerable symptom burden during chemotherapy. However, few studies have focused on exploring the mechanisms among symptoms in children with acute leukemia. Our study aims to explore core symptoms and describe the interrelationships among symptoms in children with acute leukemia during chemotherapy.

Methods

From January 2021 to March 2023, 469 children with acute leukemia were recruited from 20 Chinese cities. The Memorial Symptom Assessment Scale 10–18 (MSAS 10–18) was used to evaluate the prevalence and severity of symptoms during chemotherapy. A network analysis was performed by the R software based on 31 symptoms. Centrality indices and density were used to explore core symptoms and describe interrelationships among symptoms in the network during chemotherapy.

Results

Worrying and feeling irritable were the central symptoms across the three centrality indices, including strength, closeness, and betweenness. Lack of energy was the most prevalent symptom; however, it was less central than other symptoms. The density of the "induction and remission" network significantly differed from other cycles' counterparts (p < 0.001). Global strength was greater in the " ≥ 8 years group " network than the " < 8 years group " network (p = 0.023).

Conclusion

Network analysis provides a novel approach to identifying the core symptoms and understanding the interrelationships among symptoms. Our study indicates the need to assess emotional symptoms in children with acute leukemia during chemotherapy, especially during the induction and remission phases, as well as in older children. Future research is imperative to construct trajectories of dynamic symptom networks and centrality indices in longitudinal data to investigate the causal relationships among symptoms.

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Data Availability

All relevant data are within the manuscript and its additional file. The data are available from the corresponding author on reasonable request.

References

  1. Allemani C, Matsuda T, Di Carlo V, Harewood R, Matz M, Nikšić M, Bonaventure A, Valkov M, Johnson CJ, Estève J (2018) Global surveillance of trends in cancer survival 2000–14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. The Lancet 391(10125):1023–1075

    Article  Google Scholar 

  2. Almutary H, Douglas C, Bonner A (2017) Towards a symptom cluster model in chronic kidney disease: A structural equation approach. J Adv Nurs 73(10):2450–2461

    Article  PubMed  Google Scholar 

  3. Armour C, Fried EI, Deserno MK, Tsai J, Pietrzak RH (2017) A network analysis of DSM-5 posttraumatic stress disorder symptoms and correlates in U.S. military veterans. J Anxiety Disord 45:49–59

    Article  PubMed  Google Scholar 

  4. Baggott C, Cooper BA, Marina N, Matthay KK, Miaskowski C (2012) Symptom cluster analyses based on symptom occurrence and severity ratings among pediatric oncology patients during myelosuppressive chemotherapy. Cancer Nurs 35(1):19–28

    Article  PubMed  PubMed Central  Google Scholar 

  5. Baggott C, Cooper BA, Marina N, Matthay KK, Miaskowski C (2014) Symptom assessment in pediatric oncology: how should concordance between children’s and parents’ reports be evaluated? Cancer Nurs 37(4):252–262

    Article  PubMed  Google Scholar 

  6. Baggott CR, Dodd M, Kennedy C, Marina N, Matthay KK, Cooper B, Miaskowski C (2011) An evaluation of the factors that affect the health-related quality of life of children following myelosuppressive chemotherapy. Support Care Cancer 19(3):353–361

    Article  PubMed  Google Scholar 

  7. Bleyer A (2007) Young adult oncology: the patients and their survival challenges. CA Cancer J Clin 57(4):242–255

    Article  PubMed  Google Scholar 

  8. Borsboom D (2017) A network theory of mental disorders. World Psychiatry : Off J World Psychiatr Assoc (WPA) 16(1):5–13

    Article  Google Scholar 

  9. Collins JJ, Byrnes ME, Dunkel IJ, Lapin J, Nadel T, Thaler HT, Polyak T, Rapkin B, Portenoy RK (2000) The measurement of symptoms in children with cancer. J Pain Symptom Manage 19(5):363–377

    Article  CAS  PubMed  Google Scholar 

  10. Collins JJ, Devine TD, Dick GS, Johnson EA, Kilham HA, Pinkerton CR, Stevens MM, Thaler HT, Portenoy RK (2002) The measurement of symptoms in young children with cancer: the validation of the Memorial Symptom Assessment Scale in children aged 7–12. J Pain Symptom Manag 23(1):10–16

    Article  Google Scholar 

  11. Dong ST, Butow PN, Costa DS, Lovell MR, Agar M (2014) Symptom clusters in patients with advanced cancer: a systematic review of observational studies. J Pain Symptom Manage 48(3): 411–450

    Article  PubMed  Google Scholar 

  12. Epskamp S, Fried EI (2018) A tutorial on regularized partial correlation networks. Psychol Methods 23(4):617–634

    Article  PubMed  Google Scholar 

  13. Feng FM, Lou JH, Xu H, Zhang BH, Shen NP (2012) Symptom experience among children with cancer: a cross-sectional study. Chin Nurs Manag 12(11):30–34

    Google Scholar 

  14. Friedman J, Hastie T, Tibshirani R (2008) Sparse inverse covariance estimation with the graphical lasso. Biostatistics (Oxford, England) 9(3):432–441

    Article  PubMed  Google Scholar 

  15. Hedén L, Pöder U, von Essen L, Ljungman G (2013) Parents’ perceptions of their child’s symptom burden during and after cancer treatment. J Pain Symptom Manage 46(3):366–375

    Article  PubMed  Google Scholar 

  16. Henly SJ, Kallas KD, Klatt CM, Swenson KK (2003) The notion of time in symptom experiences. Nurs Res 52(6):410–417

    Article  PubMed  Google Scholar 

  17. Hockenberry MJ, Taylor OA, Pasvogel A, Rodgers C, McCarthy K, Gundy P, Montgomery DW, Ribbeck P, Scheurer ME, Moore IM (2014) The influence of oxidative stress on symptom occurrence, severity, and distress during childhood leukemia treatment. Oncol Nurs Forum 41(4):E238-247

    Article  PubMed  PubMed Central  Google Scholar 

  18. Ilowite MF, Al-Sayegh H, Ma C, Dussel V, Rosenberg AR, Feudtner C, Kang TI, Wolfe J, Bona K (2018) The relationship between household income and patient-reported symptom distress and quality of life in children with advanced cancer: A report from the PediQUEST study. Cancer 124(19):3934–3941

    Article  PubMed  Google Scholar 

  19. Irwin DE, Varni JW, Yeatts K, DeWalt DA (2009) Cognitive interviewing methodology in the development of a pediatric item bank: a patient reported outcomes measurement information system (PROMIS) study. Health Qual Life Outcome 7:3

    Article  Google Scholar 

  20. Kazak AE (2005) Evidence-based interventions for survivors of childhood cancer and their families. J Pediatr Psychol 30(1):29–39

    Article  PubMed  Google Scholar 

  21. Kim HJ, McGuire DB, Tulman L, Barsevick AM (2005) Symptom clusters: concept analysis and clinical implications for cancer nursing. Cancer Nurs 28(4):270–282 (quiz 283-274)

    Article  PubMed  Google Scholar 

  22. Lam W, Leung DYP, Li SF, Yi YZ, Wang HX, Zhou L, Yin Y, Chan SCW, Chan KYY, Ho JMC, Wong FKY (2022) parental stress as the mediator between symptom burden and the quality of life of chinese children with cancer. Cancer Nurs 45(5):E775-781

    Article  PubMed  Google Scholar 

  23. Li R, Ma J, Chan Y, Yang Q, Zhang C (2020) Symptom clusters and influencing factors in children with acute leukemia during chemotherapy. Cancer Nurs 43(5):411–418

    Article  PubMed  Google Scholar 

  24. Li R, Yao W, Chan Y, Shen M, Wang X, Wen F, Yang Q (2022) Correlation between symptom clusters and quality of life in children with acute leukemia during chemotherapy. Cancer Nurs 45(2):96–104

    Article  PubMed  Google Scholar 

  25. Llamas-Ramos I, Llamas-Ramos R, Carrillo-González GM, Sepúlveda-Ramírez J, Vargas-Rosero E (2022) symptom prevalence in spanish and colombian oncology patients measured with the MSAS. Cancers 14(7):1624

    Article  PubMed  PubMed Central  Google Scholar 

  26. Miaskowski C, Barsevick A, Berger A, Casagrande R, Grady PA, Jacobsen P, Kutner J, Patrick D, Zimmerman L, Xiao C, Matocha M, Marden S (2017) Advancing symptom science through symptom cluster research: expert panel proceedings and recommendations. J Natl Cancer Inst 109(4):djw253

    Article  PubMed  PubMed Central  Google Scholar 

  27. Murphy S, Xu J, Kochanek K (2013) Deaths: Final data for, (2010) National vital statistics reports. Natl Cent Health Stat 61(4):1–117

    Google Scholar 

  28. Orgel E, Sposto R, Malvar J, Seibel NL, Ladas E, Gaynon PS, Freyer DR (2014) Impact on survival and toxicity by duration of weight extremes during treatment for pediatric acute lymphoblastic leukemia: a report from the Children’s Oncology Group. J Clin Oncol:Off J Am Soc Clin Oncol 32(13):1331–1337

    Article  Google Scholar 

  29. Papachristou N, Barnaghi P, Cooper B, Kober KM, Maguire R, Paul SM, Hammer M, Wright F, Armes J, Furlong EP, McCann L, Conley YP, Patiraki E, Katsaragakis S, Levine JD, Miaskowski C (2019) Network analysis of the multidimensional symptom experience of oncology. Sci Rep 9(1):2258

    Article  PubMed  PubMed Central  Google Scholar 

  30. Pöder U, Ljungman G, von Essen L (2010) Parents’ perceptions of their children’s cancer-related symptoms during treatment: a prospective, longitudinal study. J Pain Symptom Manag 40(5):661–670

    Article  Google Scholar 

  31. Portenoy RK, Thaler HT, Kornblith AB, McCarthy Lepore J, Friedlander-Klar H, Kiyasu E, Sobel K, Coyle N, Kemeny N, Norton L, Scher H (1994) The memorial symptom assessment scale: an instrument for the evaluation of symptom prevalence, characteristics and distress. Eur J Cancer 30(9):1326–1336

    Article  Google Scholar 

  32. Pui CH, Yang JJ, Hunger SP, Pieters R, Schrappe M, Biondi A, Vora A, Baruchel A, Silverman LB, Schmiegelow K, Escherich G, Horibe K, Benoit YC, Izraeli S, Yeoh AE, Liang DC, Downing JR, Evans WE, Relling MV, Mullighan CG (2015) Childhood acute lymphoblastic leukemia: progress through collaboration. J Clin Oncol: Off J Am Soc Clin Oncol 33(27):2938–2948

    Article  CAS  Google Scholar 

  33. Kalantari E, Kouchaki S, Miaskowski C, Kober K, Barnaghi P (2022) Network analysis to identify symptoms clusters and temporal interconnections in oncology patients. Sci Rep 12(1):17052

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Schweren L, van Borkulo CD, Fried E, Goodyer IM (2018) Assessment of symptom network density as a prognostic marker of treatment response in adolescent depression. JAMA Psychiatry 75(1):98–100

    Article  PubMed  Google Scholar 

  35. Shalaby RAH, Agyapong VIO (2020) Peer support in mental health: literature review. JMIR Mental Health 7(6):e15572

    Article  PubMed  PubMed Central  Google Scholar 

  36. Smith MJ, Liehr PR (2018) Middle range theory for nursing. Springer Publishing Company, pp 147-214

  37. Steliarova-Foucher E, Colombet M, Ries LAG, Moreno F, Dolya A, Bray F, Hesseling P, Shin HY, Stiller CA (2017) International incidence of childhood cancer, 2001–10: a population-based registry study. Lancet Oncol 18(6):719–731

    Article  PubMed  PubMed Central  Google Scholar 

  38. Steur LMH, Kaspers GJL, Van Someren EJW, Van Eijkelenburg NKA, Van der Sluis IM, Dors N, Van den Bos C, Tissing WJE, Grootenhuis MA, Van Litsenburg RRL (2020) Sleep-wake rhythm disruption is associated with cancer-related fatigue in pediatric acute lymphoblastic leukemia. Sleep 43(6):zsz320

    Article  PubMed  Google Scholar 

  39. Treadgold CL, Kuperberg A (2010) Been there, done that, wrote the blog: the choices and challenges of supporting adolescents and young adults with cancer. J Clin Oncol 28(32):4842–4849

    Article  PubMed  Google Scholar 

  40. van Borkulo CD, van Bork R, Boschloo L, Kossakowski JJ, Tio P, Schoevers RA, Borsboom D, Waldorp LJ (2022) Comparing network structures on three aspects: A permutation test. Psychol Methods

  41. van Deuren S, Boonstra A, van Dulmen-den Broeder E, Blijlevens N, Knoop H, Loonen J (2020) Severe fatigue after treatment for childhood cancer. Cochrane Database Syst Rev 3(3):Cd012681

    PubMed  Google Scholar 

  42. Varni JW, Limbers C, Burwinkle TM (2007) Literature review: health-related quality of life measurement in pediatric oncology: hearing the voices of the children. J Pediatr Psychol 32(9):1151–1163

    Article  PubMed  Google Scholar 

  43. Ward E, DeSantis C, Robbins A, Kohler B, Jemal A (2014) Childhood and adolescent cancer statistics, 2014. CA: Cancer J Clin 64(2):83–103

    PubMed  Google Scholar 

  44. Wu M, Hsu L, Zhang B, Shen N, Lu H, Li S (2010) The experiences of cancer-related fatigue among Chinese children with leukaemia: a phenomenological study. Int J Nurs Stud 47(1):49–59

    Article  PubMed  Google Scholar 

  45. Yeh CH, Wang CH, Chiang YC, Lin L, Chien LC (2009) Assessment of symptoms reported by 10- to 18-year-old cancer patients in Taiwan. J Pain Symptom Manag 38(5):738–746

    Article  Google Scholar 

  46. Zhou Y-L, An J-L, Tian L (2015) Epidemiological analysis of childhood cancer in China. Chin J Contemp Pediatr 17(7):649–654

    Google Scholar 

  47. Zhu Z, Sun Y, Kuang Y, Yuan X, Gu H, Zhu J, Xing W (2022) Contemporaneous symptom networks of multidimensional symptom experiences in cancer survivors: A network analysis. Cancer Med 12(1):663–673

    Article  PubMed  PubMed Central  Google Scholar 

  48. Zhu Z, Xing W, Hu Y, Wu B, So WKW (2022) Paradigm shift: moving from symptom clusters to symptom networks. Asia-Pac J Oncol Nurs 9(1):5–6

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Acknowledgements

The authors thank Miao Hong (a researcher at Guangzhou Women and Children's Medical Center) for her contributions to the study design.

Funding

This article's authors received no financial assistance for its research, writing, or publication.

Author information

Authors and Affiliations

  1. Department of Nursing, Guangzhou Women and Children’s Medical Center, Guangzhou Medical University, Guangdong Provincial Clinical Research Center for Child Health, Guangzhou, China

    Jia Fang, Hai-Ying Huang & Yan Lin

  2. School of Nursing, Guangdong Pharmaceutical University, Guangzhou, China

    Li-Ling Xu & Mei-Xiang Wang

  3. School of Nursing, Guangzhou Medical University, Guangzhou, China

    Chun-Qin Liu, Xia Liu & Qiong Liu

  4. School of Nursing, Fudan University, Shanghai, China

    Zheng Zhu

  5. Fudan University Centre for Evidence-Based Nursing: A Joanna Briggs Institute Centre of Excellence, Fudan University, Shanghai, China

    Zheng Zhu

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  1. Jia Fang
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Contributions

Jia Fang contributed to the conceptualization and design of the study, and data analysis, and original manuscript draft and revision; Zheng Zhu contributed to the conceptualization and design of the study; Mei-Xiang Wang, Qiong Liu, Li-Ling Xu, Xia Liu, and Hai-Ying Huang contributed to the data collection and interpretation of data; Zheng Zhu, Chun-Qin Liu, and Yan Lin contributed to the supervision and reviewed/edited the manuscript; All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Yan Lin.

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Competing interests

The authors declare no competing interests.

Ethical considerations

The ethical approval for the study was obtained from the Institutional Review Board of Guangzhou Women and Children's Medical Center (IRB 2021233A01), and the study was conducted in compliance with the Declaration of Helsinki. Before data collection, written informed consent was obtained from all participants and the primary caregiver.

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Jia Fang, Li-Ling Xu, Chun-Qin Liu, and Mei-Xiang Wang contributed equally to this manuscript.

The study builds on work published in the 'Journal of Nursing (China)' (FANG Jia, XU Li-ling, LIU Chunqin, et al. Contemporaneous symptom networks in children with acute leukemia during chemotherapy: a network analysis [J]. Journal of Nursing (China), 2023, 30(16):1-6. https://doi.org/10.16460/j.issn1008-9969.2023.16.001). The authors have obtained permission to translate and publish material from the first article.

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Fang, J., Xu, LL., Liu, CQ. et al. Exploring core symptoms and interrelationships among symptoms in children with acute leukemia during chemotherapy: A network analysis. Support Care Cancer 31, 578 (2023). https://doi.org/10.1007/s00520-023-08024-7

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