Future Directions in Symptom Cluster Research

Seminars in Oncology Nursing

Volumn 32, Issue 4, 2016, Pages 405-415

  Miaskowski, Christine ^a  

^a NONE

Author keywords

cluster analysis; latent class analysis; patient reported outcomes; quality of life; symptom clusters; symptoms

Indexed keywords

CANCER EPIDEMIOLOGY; CLUSTER ANALYSIS; HUMAN; INTERVENTION STUDY; MEDICAL SOCIETY; NURSING PRACTICE; ONCOLOGY; PATIENT-REPORTED OUTCOME; PRACTICE GUIDELINE; QUALITY OF LIFE; SYMPTOM; COMPLICATION; NEOPLASM; SYNDROME;

CLUSTER ANALYSIS; HUMANS; MEDICAL ONCOLOGY; NEOPLASMS; SYNDROME;

EID: 84992694358     PISSN: 07492081     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.soncn.2016.08.006     Document Type: Review

References (64)

1. 1 Dodd, M.J., Miaskowski, C., Paul, S.M., Symptom clusters and their effect on the functional status of patients with cancer. Oncol Nurs Forum 28 (2001), 465–470.
2. 2 Given, B., Given, C., Azzouz, F., Stommel, M., Physical functioning of elderly cancer patients prior to diagnosis and following initial treatment. Nurs Res 50 (2001), 222–232.
3. 3 Esther Kim, J.E., Dodd, M.J., Aouizerat, B.E., Jahan, T., Miaskowski, C., A review of the prevalence and impact of multiple symptoms in oncology patients. J Pain Symptom Manage 37 (2009), 715–736.
4. 4 Cleeland, C.S., Symptom burden: multiple symptoms and their impact as patient-reported outcomes. J Natl Cancer Inst Monogr 37 (2007), 16–21.
5. 5 Gilbertson-White, S., Aouizerat, B.E., Jahan, T., Miaskowski, C., A review of the literature on multiple symptoms, their predictors, and associated outcomes in patients with advanced cancer. Palliat Support Care 9 (2011), 81–102.
6. 6 Miaskowski, C., Aouizerat, B.E., Dodd, M., Cooper, B., Conceptual issues in symptom clusters research and their implications for quality-of-life assessment in patients with cancer. J Natl Cancer Inst Monogr 37 (2007), 39–46.
7. 7 Doong, S.H., Dhruva, A., Dunn, L.B., et al. Associations between cytokine genes and a symptom cluster of pain, fatigue, sleep disturbance, and depression in patients prior to breast cancer surgery. Biol Res Nurs 17 (2015), 237–247.
8. 8 Huang, J., Gu, L., Zhang, L., Lu, X., Zhuang, W., Yang, Y., Symptom clusters in ovarian cancer patients with chemotherapy after surgery: a longitudinal survey. Cancer Nurs 39 (2016), 106–116.
9. 9 Yates, P., Miaskowski, C., Cataldo, J.K., et al. Differences in composition of symptom clusters between older and younger oncology patients. J Pain Symptom Manage 49 (2015), 1025–1034.
10. 10 Baggott, C., Cooper, B.A., Marina, N., Matthay, K.K., Miaskowski, C., Symptom cluster analyses based on symptom occurrence and severity ratings among pediatric oncology patients during myelosuppressive chemotherapy. Cancer Nurs 35 (2012), 19–28.
11. 11 Kim, E., Jahan, T., Aouizerat, B.E., et al. Changes in symptom clusters in patients undergoing radiation therapy. Support Care Cancer 17 (2009), 1383–1391.
12. 12 Molassiotis, A., Zheng, Y., Denton-Cardew, L., Swindell, R., Brunton, L., Symptoms experienced by cancer patients during the first year from diagnosis: patient and informal caregiver ratings and agreement. Palliat Support Care 8 (2010), 313–324.
13. 13 Yennurajalingam, S., Kwon, J.H., Urbauer, D.L., Hui, D., Reyes-Gibby, C.C., Bruera, E., Consistency of symptom clusters among advanced cancer patients seen at an outpatient supportive care clinic in a tertiary cancer center. Palliat Support Care, 2013, 1–8.
14. 14 Cheung, W.Y., Le, L.W., Zimmermann, C., Symptom clusters in patients with advanced cancers. Support Care Cancer 17 (2009), 1223–1230.
15. 15 Wang, S.Y., Tsai, C.M., Chen, B.C., Lin, C.H., Lin, C.C., Symptom clusters and relationships to symptom interference with daily life in Taiwanese lung cancer patients. J Pain Symptom Manage 35 (2008), 258–266.
16. 16 Chen, M.L., Lin, C.C., Cancer symptom clusters: a validation study. J Pain Symptom Manage 34 (2007), 590–599.
17. 17 Franceschini, J., Jardim, J.R., Fernandes, A.L., Jamnik, S., Santoro, I.L., Relationship between the magnitude of symptoms and the quality of life: a cluster analysis of lung cancer patients in Brazil. J Bras Pneumol 39 (2013), 23–31.
18. 18 Kim, H.J., Barsevick, A.M., Beck, S.L., Dudley, W., Clinical subgroups of a psychoneurologic symptom cluster in women receiving treatment for breast cancer: a secondary analysis. Oncol Nurs Forum 39 (2012), E20–E30.
19. 19 Portenoy, R.K., Thaler, H.T., Kornblith, A.B., et al. The Memorial Symptom Assessment Scale: an instrument for the evaluation of symptom prevalence, characteristics and distress. Eur J Cancer 30A (1994), 1326–1336.
20. 20 Cleeland, C.S., Mendoza, T.R., Wang, X.S., et al. Assessing symptom distress in cancer patients: the M.D. Anderson Symptom Inventory. Cancer 89 (2000), 1634–1646.
21. 21 Daut, R.L., Cleeland, C.S., Flanery, R.C., Development of the Wisconsin Brief Pain Questionnaire to assess pain in cancer and other diseases. Pain 17 (1983), 197–210.
22. 22 Lee, K.A., Hicks, G., Nino-Murcia, G., Validity and reliability of a scale to assess fatigue. Psychiatry Res 36 (1991), 291–298.
23. 23 Lee, K.A., Self-reported sleep disturbances in employed women. Sleep 15 (1992), 493–498.
24. 24 Radloff, L.S., The CES-D scale: a self-report depression scale for research in the general population. Appl Psychol Meas 1 (1977), 385–401.
25. 25 Everitt, B.S., Landau, S., Leese, M., Cluster Analysis. 4th ed., 2001, Oxford University Press, New York.
26. 26 Vermunt, J.K., Magdison, J., Hagenaars, J.A., McCutcheon, A.L., (eds.) Latent Class Cluster Analyses, 2002, Cambridge University Press, New York.
27. 27 Lanza, S.T., Flaherty, B.P., Collins, L.M., (eds.) Latent Class and Latent Transition Analysis, 2003, John Wiley & Sons, Hoboken, NJ.
28. 28 Nylund, K.L., Asparouhov, T., Muthen, B.O., Deciding on the number of classes in latent class analysis and growth mixture modeling: a Monte Carlo simulation study. Struct Equ Modeling 14 (2007), 535–569.
29. 29 Jung, T., Wickrama, K.A.S., An introduction to latent class growth analysis and growth mixture modeling. Soc Personal Psychol Compass 2 (2008), 302–317.
30. 30 Skerman, H.M., Yates, P.M., Battistutta, D., Identification of cancer-related symptom clusters: an empirical comparison of exploratory factor analysis methods. J Pain Symptom Manage 44 (2012), 10–22.
31. 31 Skerman, H.M., Yates, P.M., Battistutta, D., Cancer-related symptom clusters for symptom management in outpatients after commencing adjuvant chemotherapy, at 6 months, and 12 months. Support Care Cancer 20 (2012), 95–105.
32. 32 Miaskowski, C., Cooper, B.A., Aouizerat, B., et al. The symptom phenotype of oncology outpatients remains relatively stable from prior to through 1 week following chemotherapy. Eur J Cancer Care (Engl), 2016, 10.1111/ecc.12437.
33. 33 Cleeland, C.S., Cancer-related symptoms. Semin Radiat Oncol 10 (2000), 175–190.
34. 34 Skerman, H.M., Yates, P.M., Battistutta, D., Multivariate methods to identify cancer-related symptom clusters. Res Nurs Health 32 (2009), 345–360.
35. 35 Walsh, D., Rybicki, L., Symptom clustering in advanced cancer. Support Care Cancer 14 (2006), 831–836.
36. 36 Gift, A.G., Jablonski, A., Stommel, M., Given, C.W., Symptom clusters in elderly patients with lung cancer. Oncol Nurs Forum 31 (2004), 202–212.
37. 37 Miaskowski, C., Aouizerat, B.E., Is there a biological basis for the clustering of symptoms?. Semin Oncol Nurs 23 (2007), 99–105.
38. 38 Barsevick, A.M., The elusive concept of the symptom cluster. Oncol Nurs Forum 34 (2007), 971–980.
39. 39 Lee, B.N., Dantzer, R., Langley, K.E., et al. A cytokine- based neuroimmunologic mechanism of cancer-related symptoms. Neuroimmunomodulation 11 (2004), 279–292.
40. 40 Miaskowski, C., Dodd, M., Lee, K., Symptom clusters: the new frontier in symptom management research. J Natl Cancer Inst Monogr 32 (2004), 17–21.
41. 41 Poon, D.C., Ho, Y.S., Chiu, K., Wong, H.L., Chang, R.C., Sickness: from the focus on cytokines, prostaglandins, and complement factors to the perspectives of neurons. Neurosci Biobehav Rev 57 (2015), 30–45.
42. 42 Harrison, N.A., Brydon, L., Walker, C., et al. Neural origins of human sickness in interoceptive responses to inflammation. Biol Psychiatry 66 (2009), 415–422.
43. 43 Deo, R.C., Machine learning in medicine. Circulation 132 (2015), 1920–1930.
44. 44 Tighe, P.J., Harle, C.A., Hurley, R.W., Aytug, H., Boezaart, A.P., Fillingim, R.B., Teaching a machine to feel postoperative pain: combining high-dimensional clinical data with machine learning algorithms to forecast acute postoperative pain. Pain Med 16 (2015), 1386–1401.
45. 45 Nemati, S., Orr, J., Malhotra, A., Data-driven phenotyping: graphical models for model-based phenotyping of sleep apnea. IEEE Pulse 5 (2014), 45–48.
46. 46 Pud, D., Ben Ami, S., Cooper, B.A., et al. The symptom experience of oncology outpatients has a different impact on quality-of-life outcomes. J Pain Symptom Manage 35 (2008), 162–170.
47. 47 Miaskowski, C., Cooper, B.A., Paul, S.M., et al. Subgroups of patients with cancer with different symptom experiences and quality-of-life outcomes: a cluster analysis. Oncol Nurs Forum 33 (2006), E79–F89.
48. 48 Miaskowski, C., Dunn, L., Ritchie, C., et al. Latent class analysis reveals distinct subgroups of patients based on symptom occurrence and demographic and clinical characteristics. J Pain Symptom Manage 50 (2015), 28–37.
49. 49 Miaskowski, C., Cooper, B.A., Melisko, M., et al. Disease and treatment characteristics do not predict symptom occurrence profiles in oncology outpatients receiving chemotherapy. Cancer 120 (2014), 2371–2378.
50. 50 Herrmann, C., International experiences with the Hospital Anxiety and Depression Scale–a review of validation data and clinical results. J Psychosom Res 42 (1997), 17–41.
51. 51 Bjelland, I., Dahl, A.A., Haug, T.T., Neckelmann, D., The validity of the Hospital Anxiety and Depression Scale. An updated literature review. J Psychosom Res 52 (2002), 69–77.
52. 52 Illi, J., Miaskowski, C., Cooper, B., et al. Association between pro- and anti-inflammatory cytokine genes and a symptom cluster of pain, fatigue, sleep disturbance, and depression. Cytokine 58 (2012), 437–447.
53. 53 Collins, L.M., Lanza, S.T., Latent Class and Latent Transition Analysis: With Applications in the Social, Behavioral, and Health Science. 2010, John Wiley & Sons, Hoboken, NJ.
54. 54 Muthen, B., Muthen, L.K., Integrating person-centered and variable-centered analyses: growth mixture modeling with latent trajectory classes. Alcohol Clin Exp Res 24 (2000), 882–891.
55. 55 Velicer, W.F., Martin, R.A., Collins, L.M., Latent transition analysis for longitudinal data. Addiction 91:suppl (1996), S197–S209.
56. 56 Kwekkeboom, K.L., Abbott-Anderson, K., Cherwin, C., Roiland, R., Serlin, R.C., Ward, S.E., Pilot randomized controlled trial of a patient-controlled cognitive-behavioral intervention for the pain, fatigue, and sleep disturbance symptom cluster in cancer. J Pain Symptom Manage 44 (2012), 810–822.
57. 57 Sprod, L.K., Fernandez, I.D., Janelsins, M.C., et al. Effects of yoga on cancer-related fatigue and global side-effect burden in older cancer survivors. J Geriatr Oncol 6 (2015), 8–14.
58. 58 Mustian, K.M., Sprod, L.K., Janelsins, M., Peppone, L.J., Mohile, S., Exercise recommendations for cancer-related fatigue, cognitive impairment, sleep problems, depression, pain, anxiety, and physical dysfunction: a review. Oncol Hematol Rev 8 (2012), 81–88.
59. 59 Lengacher, C.A., Reich, R.R., Paterson, C.L., et al. Examination of broad symptom improvement resulting from mindfulness-based stress reduction in breast cancer survivors: a randomized controlled trial. J Clin Oncol 34 (2016), 2827–2834.
60. 60 Lengacher, C.A., Reich, R.R., Post-White, J., et al. Mindfulness based stress reduction in post-treatment breast cancer patients: an examination of symptoms and symptom clusters. J Behav Med 35 (2012), 86–94.
61. 61 Collins, L.M., Murphy, S.A., Strecher, V., The multiphase optimization strategy (MOST) and the sequential multiple assignment randomized trial (SMART): new methods for more potent eHealth interventions. Am J Prev Med 32:suppl 5 (2007), S112–S118.
62. 62 Collins, L.M., Nahum-Shani, I., Almirall, D., Optimization of behavioral dynamic treatment regimens based on the sequential, multiple assignment, randomized trial (SMART). Clin Trials, 2014, 11426–11434.
63. 63 Almirall, D., Nahum-Shani, I., Sherwood, N.E., Murphy, S.A., Introduction to SMART designs for the development of adaptive interventions: with application to weight loss research. Transl Behav Med 4 (2014), 260–274.
64. 64 Lei, H., Nahum-Shani, I., Lynch, K., Oslin, D., Murphy, S.A., A “SMART” design for building individualized treatment sequences. Annu Rev Clin Psychol 8 (2012), 21–48.