Symptom Clustering and Its Effect on Functional Status in Lymphoma Patients

Sezgi̇n, Merve Gozde; Bektaş, Hicran

doi:10.5152/fnjn.2020.19107

Cited by 7 publications

(14 citation statements)

References 21 publications

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“…Of the 23 studies included in this review, 13 used a cross-sectional design to identify symptom clusters in oncology patients receiving chemotherapy (online supplemental table 1). Seven studies were conducted in the USA,29 32–37 two in China,38 39 two in Thailand,40 41 one in Austria,42 and one in Turkey 43. Sample sizes ranged from 9641 to 1328 29.…”

Section: Resultsmentioning

confidence: 99%

“…Five studies evaluated for symptom clusters in patients with heterogeneous types of cancer 29 32 33 35 42. Of the eight studies that evaluated for clusters in patients with homogeneous types of cancer, four evaluated patients with breast cancer,34 36 40 41 one with bladder cancer,39 one with leukaemia,38 one with lymphoma,43 and one with lung cancer 37…”

Section: Resultsmentioning

confidence: 99%

“…In terms of the instruments, nine of the 13 studies used the Memorial Symptom Assessment Scale (MSAS) 29 32 33 35–38 40 43. Of these nine studies, six used a modified version of the MSAS29 32 33 35–37 and one used a condensed version 38.…”

Section: Resultsmentioning

confidence: 99%

“…Nine of the 13 studies used EFA to identify symptom clusters 32–37 39 41 42. Of the remaining studies, two used principal component analysis (PCA),38 40 one used HCA43 and one used NA 29…”

Section: Resultsmentioning

confidence: 99%

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Symptom clusters in patients receiving chemotherapy: A systematic review

Harris

Kober

Conley

et al. 2021

BMJ Support Palliat Care

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Background and purposeSince 2001, symptom cluster research has grown considerably. However, because multiple methodological considerations remain, ongoing synthesis of the literature is needed to identify gaps in this area of symptom science. This systematic review evaluated the progress in symptom clusters research in adults receiving primary or adjuvant chemotherapy since 2016.MethodsEligible studies were published in English between 1 January 2017 and 17 May 2021; evaluated for and identified symptom clusters ‘de novo;’ and included only adults being treated with primary or adjuvant chemotherapy. Studies were excluded if patients had advanced cancer or were receiving palliative chemotherapy; symptoms were measured after treatment; symptom clusters were pre-specified or a patient-centred analytic approach was used. For each study, symptom instrument(s); statistical methods and symptom dimension(s) used to create the clusters; whether symptoms were allowed to load on more than one factor; method used to assess for stability of symptom clusters and associations with secondary outcomes and biomarkers were extracted.ResultsTwenty-three studies were included. Memorial Symptom Assessment Scale was the most common instrument and exploratory factor analysis was the most common statistical method used to identify symptom clusters. Psychological, gastrointestinal, and nutritional clusters were the most commonly identified clusters. Only the psychological cluster remained relatively stable over time. Only five studies evaluated for secondary outcomes.DiscussionWhile symptom cluster research has evolved, clear criteria to evaluate the stability of symptom clusters and standardised nomenclature for naming clusters are needed. Additional research is needed to evaluate the biological mechanism(s) for symptom clusters.PROSPERO registration numberCRD42021240216.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Symptom clusters in patients receiving chemotherapy: A systematic review

Harris

Kober

Conley

et al. 2021

BMJ Support Palliat Care

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“…Web‐based intervention programs have the potential to eliminate barriers to psychosocial care in patients diagnosed with lymphoma. Therefore, healthcare professionals adopt the strategies of web‐based intervention programs to control the quality and safety of care provided to patients with lymphoma (Graetz et al, 2018; Grandi et al, 2018; Sezgin & Bektas, 2020; Taylor et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

The effect of web‐based intervention programs on self‐management and symptom management in patients with lymphoma: A systematic review of randomized controlled trials

Sezgi̇n

Bektaş

2021

Japan Journal Nursing Sci

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Aim This systematic review aimed to systematically summarize studies obtained through a database search and examine the effect of web‐based intervention programs on self‐management and symptom management in patients with lymphoma. Methods A systematic review of randomized controlled trials was carried out. Cochrane Central Register of Controlled Trials, Web of Science, PubMed, CINAHL, Scopus, ProQuest, Science Direct, and Ovid databases were reviewed until January 2021. The flow chart of the Preferred Reporting Items for Systematic Review and Meta‐Analysis checklist was used in the search procedure without setting a year limit. Population, Intervention, Comparison, Outcomes and Study criteria were determined by two independent investigators and published randomized controlled studies in English with lymphoma diagnosis and web‐based intervention programs for self‐management and symptom management were included in the systematic review. The included studies were examined for their risk of bias with the help of the Cochrane Collaboration tool. A narrative synthesis of study findings was performed. Results Six randomized controlled trials with 2382 participants were included in the systematic review. Web‐based intervention programs in patients diagnosed with lymphoma were found to be generally implemented for determining the levels of self‐management and symptom management. In all of the studies reviewed, it was found that the interventions had treatment outcomes. The risk of Bias 2 was evaluated as high risk in two studies that did not meet the criteria for blinding outcome evaluations. The included studies, while evaluating the effects of web‐based intervention programs on patient outcomes, could not provide information about the underlying mechanisms by which these effects occur and how they occur. Conclusions All of the studies included were found to apply a technology designed to improve outcomes in patients with lymphoma. It is recommended that web‐based intervention programs be individualized by adapting them to lymphoma types and stages, and serve as a guide for effective symptom management.

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