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. 2013 Jan-Feb;39(1):23-31.
doi: 10.1590/s1806-37132013000100004.

Relationship between the magnitude of symptoms and the quality of life: a cluster analysis of lung cancer patients in Brazil

[Article in English, Portuguese]
Juliana Franceschini  1 , José Roberto Jardim, Ana Luisa Godoy Fernandes, Sérgio Jamnik, Ilka Lopes Santoro
Affiliations

Relationship between the magnitude of symptoms and the quality of life: a cluster analysis of lung cancer patients in Brazil

[Article in English, Portuguese]
Juliana Franceschini et al. J Bras Pneumol. 2013 Jan-Feb.

Abstract
in English, Portuguese

Objective: Lung cancer patients often experience profound physical and psychosocial changes as a result of disease progression or treatment side effects. Fatigue, pain, dyspnea, depression, and sleep disturbances appear to be the most common symptoms in such patients. The objective of the present study was to examine the prevalence of symptoms in lung cancer patients in order to identify subgroups (clusters) of patients, grouped according to the magnitude of the symptoms, as well as to compare the quality of life among the identified subgroups.

Methods: A cross-sectional study involving agglomerative hierarchical clustering. A total of 50 lung cancer patients were evaluated in terms of their demographic characteristics and their scores on three quality of life questionnaires, namely the 30-item European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30), the Functional Assessment of Cancer Therapy-Lung, and the Medical Outcomes Study 36-item Short-form Survey. The cluster analysis took into account the magnitude of the most prevalent symptoms as assessed by the EORTC QLQ-C30 symptom scale scores; those symptoms were fatigue, pain, dyspnea, and insomnia.

Results: Three clusters (subgroups)_of patients were identified on the basis of the magnitude of the four most prevalent symptoms. The three subgroups of patients were as follows: patients with mild symptoms (n = 30; 60%); patients with moderate symptoms (n = 14; 28%); and patients with severe symptoms (n = 6; 12%). The subgroup of patients with severe symptoms had the worst quality of life, as assessed by the total scores and by the integrated domains of all three instruments.

Conclusions: This study highlights the importance of symptom cluster assessment as an important tool to assess the quality of life of patients with chronic diseases, such as lung cancer.

OBJETIVO:: Muitas vezes pacientes com câncer de pulmão vivenciam mudanças físicas e psicossociais profundas que resultam da progressão da doença ou dos efeitos colaterais do tratamento. Fadiga, dor, dispneia, depressão e distúrbios do sono parecem ser os sintomas mais comuns nesses pacientes. O objetivo deste estudo foi examinar a prevalência de sintomas em pacientes com câncer de pulmão a fim de identificar subgrupos (clusters) de pacientes, agrupados de acordo com a magnitude dos sintomas, bem como comparar os subgrupos quanto à qualidade de vida.

MÉTODOS:: Estudo transversal utilizando agrupamento hierárquico aglomerativo. Foram avaliadas as características demográficas de 50 pacientes com câncer de pulmão, bem como sua pontuação em três questionários de qualidade de vida: o 30-item European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30), o Functional Assessment of Cancer Therapy-Lung e o Medical Outcomes Study 36-item Short-form Survey. A análise de agrupamentos (clusters) levou em conta a magnitude dos sintomas de maior prevalência de acordo com as escalas de sintomas do EORTC QLQC-30; esses sintomas foram fadiga, dor, dispneia e insônia.

RESULTADOS:: Foram identificados três agrupamentos (subgrupos) de pacientes, baseados na magnitude dos quatro sintomas mais prevalentes. Os três subgrupos de pacientes foram os seguintes: pacientes com sintomas leves (n = 30; 60%); pacientes com sintomas moderados (n = 14; 28%) e pacientes com sintomas graves (n = 6; 12%). O subgrupo de pacientes com sintomas graves apresentou a pior qualidade de vida, conforme mensurada pelos escores totais e pelas dimensões integradas dos três instrumentos.

CONCLUSÕES:: Este estudo destaca a importância da avaliação de agrupamentos de sintomas como uma ferramenta relevante para medir a qualidade de vida de pacientes com doenças crônicas, como o câncer de pulmão.

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Figures

Figure 1
Figure 1. Dendrogram obtained by using the farthest neighbor method. Clusters were formed on the basis of the distances between individual magnitudes of symptoms.
Figure 2
Figure 2. In A, mean 30-item European Organization for Research and Treatment of Cancer Core Quality of Life Questionnaire (EORTC QLQ-C30) domain scores for the subgroups of patients with mild, moderate, and severe symptoms (as identified by cluster analysis). In B, mean Functional Assessment of Cancer Therapy- Lung (FACT-L) scores, mean Functional Assessment of Cancer Therapy-General (FACT-G) scores, and mean Functional Assessment of Cancer Therapy-Lung Trial Outcome Index (FACT-L TOI) for the subgroups of patients with mild, moderate, and severe symptoms (as identified by cluster analysis).
See this image and copyright information in PMC

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