|Year : 2016 | Volume
| Issue : 4 | Page : 370-381
Impact of symptom clusters on quality of life outcomes in patients from japan with advanced nonsmall cell lung cancers
Tamami Hamada1, Hiroko Komatsu2, Margaret Quinn Rosenzweig3, Naohiko Chohnabayashi4, Naoki Nishimura4, Satoshi Oizumi5, Dianxu Ren6
1 Department of Nursing, Asahikawa Medical University, Asahikawa, Hokkaido, Japan
2 Faculty of Nursing and Medical Care, Keio University, Tokyo, Japan
3 Departments of Acute and Tertiary Care, University of Pittsburgh School of Nursing, Pennsylvania, USA
4 Division of Pulmonary Medicine, Thoracic Center, St. Luke's International Hospital, Tokyo, Japan
5 Department of Medicine, School of Medicine, Hokkaido University, Sapporo, Japan
6 Departments of Health and Community Systems, University of Pittsburgh School of Nursing, Pennsylvania, USA
|Date of Submission||03-Jun-2016|
|Date of Acceptance||04-Oct-2016|
|Date of Web Publication||22-Dec-2016|
Department of Nursing, Asahikawa Medical University, Asahikawa, Hokkaido; 2-1-1 Midorigaoka Higashi, Asahikawa, Hokkaido 078-8510
Source of Support: None, Conflict of Interest: None
Objective: Identify symptom clusters based on symptoms experienced by patients with advanced nonsmall cell lung cancers (NSCLCs), and examine the relationship between the symptom clusters and impairment in everyday life and quality of life (QOL). Methods: Using the M.D. Anderson Symptom Inventory, 9 symptom items and the QOL Questionnaire (QLQ-C-30) evaluation apparatus from the European Organization for Research and Treatment of Cancer, we evaluated symptom severity, interference in daily life, and QOL. Factor analysis and multiple regression analysis techniques were used. Results: Sixty patients with advanced NSCLCs seen in pulmonary medicine departments were included in the study. The average age of patients was 64.33 (standard deviation = 11.40). Thirty-six were male and 24 were female. Three symptom clusters were identified as fatigue/anorexia cluster (dry mouth, altered the sense of taste, drowsiness, fatigue/tiredness, and lack of appetite), pain cluster (anxiety, sadness, and pain), numbness cluster (numbness, leg weakness, and distress). The pain cluster had the strongest influence (adjusted R2 = 0.355) on daily life (emotions) while the numbness cluster most strongly affected walking. The fatigue/anorexia cluster explained 22.7% of role function variance. This symptom clustering may be unique among patients with advanced NSCLCs. Conclusions: Each of these clusters affected QOL and everyday life with varying degrees of influence. In clinical screening assessments, focusing on symptom clusters could provide tailored management strategies for patients with advanced NSCLCs. These care strategies may improve outcomes specifically for advanced NSCLCs patients.
Keywords: Advanced nonsmall cell lung cancer, cross-sectional, factor analysis, impairment of everyday life, quality of life, symptom clusters
|How to cite this article:|
Hamada T, Komatsu H, Rosenzweig MQ, Chohnabayashi N, Nishimura N, Oizumi S, Ren D. Impact of symptom clusters on quality of life outcomes in patients from japan with advanced nonsmall cell lung cancers. Asia Pac J Oncol Nurs 2016;3:370-81
|How to cite this URL:|
Hamada T, Komatsu H, Rosenzweig MQ, Chohnabayashi N, Nishimura N, Oizumi S, Ren D. Impact of symptom clusters on quality of life outcomes in patients from japan with advanced nonsmall cell lung cancers. Asia Pac J Oncol Nurs [serial online] 2016 [cited 2020 Nov 27];3:370-81. Available from: https://www.apjon.org/text.asp?2016/3/4/370/196489
| Introduction|| |
Lung cancer has been the leading cause of cancer-related deaths in Japan, the USA, and Europe, with higher mortality rates than other forms of cancer. ,, There are standard chemotherapies and biotherapies effective at prolonging life in patients with nonsmall cell lung cancers (NSCLCs). , Cancer and these therapies present unique symptom profiles, including a large number of symptoms which can be distressing to the patient and family and negatively impact functionality, quality of life (QOL), and other important outcomes. ,, One way to improve the symptoms in patients with advanced lung cancer and patient outcomes may be to gain a better understanding of symptoms occurring concurrently, as in symptom clusters.
Dodd et al. proposed the idea of symptom clusters as a way to gain a clearer understanding of symptoms and phenomena that interfere with various everyday activities and impair the QOL.  Symptom clusters are defined as two or more symptoms that are manifested simultaneously and affect key patient outcomes such as QOL. 
Currently, there is sufficient evidence to support the concept of symptom clusters in patients with cancer generally; however in lung cancer, symptom cluster research is ongoing and no generally accepted cluster symptoms have been determined. ,,,,,,, Chen et al. indicated that symptom clusters in lung cancer patients lack quantitative and structural consistency, and demonstrated discrepancies in sample population characteristics and methodologies, such as in the assessment tools and analysis techniques.  Specifically, in lung cancer, empirical research studies have identified four symptom clusters comprising 2 to 11 distinct symptoms, and specific symptom clusters have been named [Table 1]. ,,,,,,
To date, the sample sizes of patients with lung cancer enrolled in the published reports of symptom clusters have ranged from 60 to 400. Among these reports, the only study that focused on patient groups of the same kind of NSCLCs  included recurrent and secondary lung cancers as well as primary NSCLCs, and 75% of this group received surgical treatment.
While there has been some descriptive work reported for early and unspecified stages of lung cancers, there has been little work examining symptom clusters in exclusively advanced stage (IIIB or IV) lung cancers. In that sample, ,,,,,, the percentage of patients with advanced stage (IIIB or IV) disease was either unspecified or relatively limited, ranging from 3.0% to 60.0%. Focusing on the group with the same type of advanced stage (IIIB or IV) who received standard therapies (chemotherapy and biotherapy), the most seriously ill NSCLCs patients, with arguably the highest symptom burdens, were underrepresented. The purposes of this study were to identify: (1) symptom clusters, (2) relationships between symptom clusters and the effects on daily life, and (3) relationships between symptom clusters and QOL among advanced stage (IIIB or IV) NSCLCs patients.
| Methods|| |
Study sample and procedures
This study is a cross-sectional, descriptive correlation design. As an appropriate sample size for explanatory factor analysis has not been established, it is something that is still being discussed.  This study set the sample size as 60 based on previous nursing studies that conducted exploratory factor analysis to examine symptom clusters of advanced lung cancer patients by setting the sample sizes as 60-400. ,,,,, This study was approved by the Medical University Ethics Committee and the two participating institutions. Using a convenience sampling, patients were recruited from two institutions, a regional university hospital, and a general hospital in the Tokyo metropolitan area. Eligibility criteria are as follows: adult patients (over 20-year-old), with no other diagnosed malignancies, no cognitive impairment, and patients who were being administered standard therapy for advanced (Stage IIIB or IV) primary NSCLCs. Clinicians explained about the access of researchers (nurses) to patients who met the eligibility criteria, and the researchers (nurses) provided information about the study participation orally and in writing to patients who had permitted the access of researchers (nurses).
After signing the informed consent documents, participants were provided with a survey form and a reply-paid envelope and instructed to fill in the form; the participants filled in the survey form in the early evening of the same day and posted it back to the research team within 1 week. Researchers (nurses) assisted participants who needed help with completing the survey form due to numbness in the hands, by reading out the answer choices at the interview, and indicating the choice by circling the corresponding number. The participants sealed and posted the envelopes by themselves.
The survey included input from the M.D. Anderson Symptom Inventory (MDASI), a brief measure of the severity and impact of cancer-related symptoms. The MDASI is in English and is a self-rating multiple symptom assessment scale comprising 13 symptom items and 6 interference items.  The scale utilized in this study was created by combining the 13-item Japanese version of the MDASI (MDASI-J)  plus an advanced NSCLCs symptom scale comprising nine symptom items (altered sense of taste, weight loss, leg weakness, cough, rash, impaired concentration, irritability, anxiety, and depression), developed by the authors based on a preliminary study of symptoms experienced by patients with advanced NSCLCs. Impairment in everyday life was evaluated using the 6-item MDASI-J system in the same order as in the MDASI.
With the MDASI-J and the NSCLCs symptom modules, the participants rate the severity of symptoms during the previous 24 h by circling a number between 0 and 10, where 0 stands for "not present" and 10 is "as bad as can be imagined." The responses in the advanced NSCLCs symptom module are reported in the same manner. Cronbach's alpha values were 0.87 for this study population, 0.88 for the MDASI-J, 0.83 for the advanced NSCLCs symptom module, and 0.92 for the combined total of 22 categories.
For the QOL scale, we employed the Japanese version of the Core QOL Questionnaire (QLQ-C30), with permission from the European Organization for Research and Treatment of Cancer (EORTC). , We analyzed five functions (physical, role, cognitive, emotional, and social) and global QOL. Data, including age, gender, disease, and treatment details, including diagnosis (tissue type), cancer stage (tumor, node, metastasis classification), comorbidities, current treatment regimen, time since diagnosis (in days), use of analgesic medications (yes/no), and the Eastern Cooperative Oncology Group Performance Status (ECOG PS),  were extracted from electronic medical records. Participants were also asked to fill in a demographic background form providing details such as educational level, work history, marital state, and persons they are living together with.
Regarding the inconsistencies in the symptom clusters identified in lung cancer patients in different studies, Chen et al. pointed out the inconsistency in the analytical methods to identify symptom clusters. Henoch et al. suggest that a factor analysis is the most suitable tool for the empirical exploration of potential symptom clusters. Five (71%) ,,,,, among previous studies shown in [Table 1] used factor analysis and evaluated Cronbach's alpha and Pearson's correlation.  Therefore, we assumed that identification of symptom clusters by factor analysis would be effective to overcome the problem of inconsistency in the study method and determined to use factor analysis in this study. We also used the Promax rotation method that describes correlations between factors, assuming that there are correlations between symptom clusters.
Following the definition of Kim et al. that there is a better correlation between symptom items in the symptom clusters, we determined symptoms with significant correlations within a factor for the factors belonging to a symptom cluster. Therefore, this study identified symptom clusters by estimating the number of factors through an exploratory factor analysis (principal factor analysis: Promax rotation). The magnitude of a factor pattern was set to 0.3 or higher based on Gift et al.,  who reported at least one factor. Cronbach's alpha was calculated for each factor, along with the number of clustered symptoms, and Pearson's correlation coefficients between symptoms to evaluate the internal consistency of symptom clusters identified.
Following the definition of Kim et al.,  we evaluated the influence of symptom clusters on important outcomes of patients, everyday life, and QOL. Correlations between the symptom clusters and impairment in daily life and QOL were analyzed by calculating Pearson's r correlation coefficients for the average scores for each symptom within the cluster, average scores on the 6-point MDASI-J everyday life impairment inventory, the EORTC QLQ-C30 five-function scale (physical, role, cognitive, emotional, and social), and the average global QOL scores.
To determine the impact on outcomes, we performed a stepwise multiple regression analysis. The independent variables were the symptom cluster base score. The variables were demographic (age and education status) and clinical (ECOG PS, comorbid conditions, and time since diagnosis) entered simultaneously into the regression analyses. The score for each identified symptom cluster was converted to a symptom cluster base score to generate an independent variable. , The dependent variables were the MDASI-J (impairment of everyday life score), and the standardized scores for the EORTC QLQ-C30 five functions and the global QOL. A higher score of these standardized scores (range, 1-100) indicates a better QOL.  There was no multicollinearity effect (minimum tolerance of 0.2) as per Yanai and Ogata. 
The level of statistical significance was set at 0.05. Descriptive statistics was used to evaluate sample characteristics. All statistical analyses were performed using SPSS® , version 19.0 (IBM® , New York, NY, USA).
| Results|| |
Patients were recruited from April to November 2010. Of the 67 potential participants who met the eligibility criteria, 61 agreed to participate. The participants were asked to complete a written questionnaire. Complete responses were received from sixty participants and were used as the data in the analysis. As shown in [Table 2], the average age of the sixty participants was 64.33 years, (standard deviation [SD] =11.40 years). The median ECOG PS was 1.0. For standard therapies, 88.3% of the participants received a combination therapy of platinum (cisplatin or carboplatin), a maintenance therapy, gefitinib, or erlotinib at the baseline of the study. Six (10%) were not undergoing chemotherapy because they were in a follow-up period between the previous treatment and being evaluated for progressive disease. Further, one participant (1.7%) was under palliative radiotherapy proceeding to a chemotherapy period. Fifty-five percent of the participants were outpatients who filled in the survey themselves while 45.0% asked the researchers to fill in the survey in an interview setting due to neuropathy limiting the ability to write.
|Table 2: Participant demographic characteristics and medical characteristics (n=60)|
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The average symptom severities (ranked in order) were 3.77 (fatigue/tiredness, SD = 3.02), 3.12 (drowsiness, SD = 2.62), and 3.05 (lack of appetite, SD = 2.91). The prevalence (%) was highest for both fatigue/tiredness and drowsiness, at approximately 80.0%. Over 30.0% of participants experienced all symptoms excluding the lowest two as shown in [Figure 1]. The two least severe symptoms - rash (average severity 0.83, SD = 1.63) and vomiting (average severity 0.80, SD = 1.98) - were excluded due to low reliability. Analyses were based on the scores for the remaining twenty symptoms.
As shown in [Table 3], the average impairment scores (ranked in order) were 3.71 (enjoyment of life, SD = 3.10), 3.37 (life in general, SD = 3.11), and 3.35 (walking, SD = 2.94). The averages of the standardized scores for the EORTC QLQ C-30 five functions (ranked in order) that patients reported as poorest were 57.78 (role, SD = 32.25), 67.66 (physical, SD = 22.99), 74.16 (social, SD = 25.93), and 49.58 (global QOL, SD = 24.52).
|Table 3: Impairment scores and standardized European Organization for Research and Treatment of Cancer Quality of Life Questionnaire - Core 30 scores (n=60)|
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The Promax rotation principal factor analysis identified five factors from the scores of the twenty symptoms: Factor A includes impaired concentration, irritability, depression, weight loss, difficulty in remembering, and shortness of breath. Factor B includes dry mouth, altered sense of taste, drowsiness, fatigue/tiredness, and lack of appetite. Factor C includes Anxiety, sadness, and pain. Factor D includes sleep disturbance, nausea, and cough. Factor E includes numbness, leg weakness, and distress. As shown in [Table 4], Cronbach's alpha coefficients for the five factors were in the range of 0.73-0.84.
Peason's correlation coefficients among symptoms within a factor
As [Table 5] shows, three of the factors showed statistically significant correlations (P < 0.05) between all the constituent symptoms. Based on these results, it was determined that three symptom clusters could be identified fatigue/anorexia cluster (dry mouth, altered sense of taste, drowsiness, fatigue/tiredness, and lack of appetite), pain cluster (anxiety, sadness, and pain), and numbness cluster (numbness, leg weakness, and distress).
|Table 5: Pearson's correlation coefficient between symptoms within each factor (n=60)|
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Effects of symptom clusters on outcomes (interference of daily life and quality of life)
As seen in [Table 6], the three symptom clusters explained 5.2%-35.5% of the variance in impairment of everyday life quality. The pain cluster is the only cluster influencing all five subscales of the impairment in everyday life (excluding walking). It is more likely that the fatigue/anorexia cluster and the pain cluster only influenced enjoyment of life, but did not impair other aspects of everyday life. The pain cluster had the strongest influence on the emotion parameter with the adjusted R2 = 0.355. The numbness cluster had the strongest influence on the walking parameter, with the adjusted R2 = 0.281.
|Table 6: Step - wise regression analysis of the three clusters and daily life interference coefficients (n=60)|
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As [Table 7] shows, multiple regression analysis suggested that fatigue/anorexia and pain clusters alone explained 11.7%-23.6% of the variance in QOL. Fatigue/anorexia and pain clusters influenced three subscales of the QOL score. Particularly, it is more likely that fatigue/anorexia cluster influenced three subscales of the QOL (excluding the physical, emotion, and social functions). It is also more likely that the pain cluster only influenced physical, emotion, and social function, but not any of the other subscales of the QOL. Fatigue/anorexia cluster had the strongest influence on the role function (adjusted R2 = 0.227), with the pain cluster the strongest influence on the emotional function (adjusted R2 = 0.236).
|Table 7: Step - wise regression analysis of the three clusters and quality of life coefficients (n=60)|
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| Discussion|| |
This study uniquely identified three symptom clusters comprised three to five symptoms each from a broad range of symptoms experienced, although the severity was mild and reported at one point in time among patients with exclusively advanced stage (IIIB or IV) NSCLCs. Further, participants in the study by Wang et al. were comprised a wide range of cancers including Stages I and II, the number of participants who were at Stage III among the 108 participants was not reported, and only 21 participants (19.4%) were at the advanced stage (IV). This is different from the present study that focuses exclusively on advanced stage (n = 60; 28.3% Stage IIIB and 71.7% Stage IV) patients. The differences will be smaller if Wang et al. had analyzed only the patients with cancers in the advanced Stages III and IV (n = 64; 97% Stage III and 3% Stage IV). 
Fatigue/anorexia cluster comprises lack of appetite, drowsiness, fatigue/tiredness, altered sense of taste, and dry mouth. This cluster is similar to the pattern 3 (lack of appetite, drowsiness, fatigue, sleep disturbance, dry mouth, and distress) reported by Wang et al.  Okuyama et al. established an explanatory model for this symptom clustering, suggesting that malnutrition could precipitate the lack of appetite, identified as one of the causes of malaise in outpatients with advanced lung cancer.  Dry mouth and altered sense of taste may lead to lack of appetite and malnutrition, causing malaise, and associated drowsiness in a clustering phenomenon.
The pain cluster comprises pain, anxiety, and sadness. Pain is experienced by many lung cancer patients,  and Hopwood and Stephens report that the physiological response to pain can lead to psychological symptoms of anxiety and sadness.  In the USA, 32% of advanced lung cancer patients assessed with MDASI reported moderate to severe pain symptom levels.  With the MDASI-J, 11% of the sample with Japanese cancer patients (n = 252) reported moderate (5-6), and 12% severe (≥ 7) pain levels.  These are lower pain levels than the USA samples where 19% report moderate pain and 15% of the sample report severe pain (n = 527). 
This research project may have more (proportionally) advanced stage (Stage IV: 71.7%) lung cancer patients who received more attention to palliative care needs and symptoms.  This attention may have alleviated the severity in the pain. There may be differences in the symptom expression of pain severity expressed among the Japanese patients with cancer reported by Okuyama et al. This research project is significant because it shows that patients with advanced NSCLCs during the treatment period have experienced symptom clusters although the severity of the pain is mild. Therefore, if alleviation care is not provided actively through monitoring and communication focusing on symptom clusters for patients with advanced NSCLCs in the treatment period, it is not possible to alleviate pain effectively. Specifically, for this Japanese population, this trend may be seen to provide an accurate explanation.
The pain scores may be influenced by a phenomenon like the finding in previous research documenting that Japanese respondents avoid polar categories and tend to choose middle range responses.  Further, thinking about the origin of the word "pain," the English origin contains "penalty" and "punishment." However, "pain" (Itami in Japanese) implies "a condition of the extent to which somebody or something experiences distress," and the word is used to express an extreme physical, material, or mental condition. The word "Itami" originally does not include the meaning of punishment.  On this account, efforts of health-care professionals to encourage patients to report symptoms may be insufficient in Japan compared to those in European and American countries where reporting of symptoms is encouraged to receive potential medications striving for alleviation. According to a study that investigated the illness perceptions and QOL of Japanese and Dutch patients with NSCLCs, it is suggested that Japanese patients are more strongly aware of the therapeutic efficacy in controlling illness and more strongly believe in the effectiveness of medical care for lung cancer than Dutch patients.  Further, patients with lung cancer are reported to harbor hopes of being cured.  For the above reasons, for patients with the most advanced stages of NSCLCs like in this study, suffering pain may arouse doubts about the effectiveness of the medical care for their lung cancer, and reduce the efficacy of the medical care due to a perceived mismatch between their expectations and their physical condition, resulting in the passive-sounding report of the pain. Thus, the pain cluster identified in this study may be unique to the Japanese patients with advanced NSCLCs under standard chemotherapy. As Gift et al. have pointed out, it is necessary to examine whether groups of different racial background with different cultural background experience report similar symptom intensities.
The numbness cluster comprises numbness, leg weakness, and distress. Again, Wang et al. report different results from their study, including all stages of patients with lung cancer, probably resulting from the inclusion of earlier stage patients not receiving chemotherapy.  Numbness is a form of peripheral neuropathy (sensory) associated with taxane chemotherapy (paclitaxel and docetaxel) and platinum (cisplatin and carboplatin) agents commonly used in conjunction with standard therapy for patients with advanced NSCLCs. , Numbness was reported by 48.4% of the participants in the study here. It is plausible that the numbness decreased ease of ambulation and was a cause of the resultant distress.
The second aim of the study here was to identify relationships between symptom clusters and the functional status and interference in daily life. The pain cluster contributed to five areas of daily life interference ranked in the order of emotions, life in general, work including housework, interpersonal relationships, and enjoyment of life (respectively β = 0.563, β = 0.484, β = 0.424, β = 0.357, and β = 0.330).
The fatigue/anorexia cluster explained 7.6% of the daily life interference (enjoyment of life) variance and 5.2% of (walking) variance while the pain cluster explained 35.5% of the pain cluster variance, which is the highest value. Therefore, it was suggested that the pain cluster showed a stronger influence on daily life interference (emotions) than the fatigue/anorexia cluster. Our study results agree with two other studies. , Put differently, it became clear that the pain cluster has a negative impact on the functional status which is important for daily life. It seems clear that the pain cluster had an adverse effect on all five areas of daily life interference (ranked in the order: Emotions, life in general, work including housework, interpersonal relationships, and enjoyment of life). Further, as the numbness cluster explained 28.1% of daily life interference (walking), this could be an important symptom cluster to which health-care professionals (nurses) should give special attention to maintain walking ability. Therefore, it is necessary in the nursing to give consideration to the interference of numbness in daily life. In addition, nurses could consider that all of the identified symptom clusters may influence the functional status and daily life.
The third aim of the study was to identify the relationship between symptom clusters and QOL. The fatigue/anorexia cluster explained 11.7% of only one global QOL variance. In addition, the fatigue/anorexia cluster influenced 3 functional areas in QOL, and compared with 2 areas of everyday life interference, it seemed to have a negative impact on QOL. This implies that it is important for health-care professionals to monitor the fatigue/anorexia cluster to prevent deterioration of QOL. Further, the fatigue/anorexia cluster showed a stronger influence on QOL (role function) while the pain cluster showed a stronger influence on QOL (emotional function). Further, the pain cluster was more likely to influence emotional, physical, and social functions. As described above, considering that the fatigue/anorexia cluster influenced only 3 functional areas in QOL while the pain cluster daily life interference influenced 5 areas, it is suggested that difficulty in daily life due to the pain cluster occurs earlier than the influence on QOL. This suggests that the pain cluster may be a precursor to the fatigue/anorexia cluster. In this study, QOL was not influenced by the numbness cluster. These findings agree with those of fox where fatigue was significantly but only mildly correlated with QOL.  In the fox study, pain was not significantly correlated with QOL because many patients had completed active treatment.
As described above, the pain cluster affects physical, emotional, and social functions of QOL, whereas the fatigue/anorexia cluster affects role and cognitive functions, affecting different areas. For the pain cluster, as patients cannot look after themselves and have difficulty in doing housework when they are in pain, it becomes difficult to avoid deterioration in physical and social functions. In addition, pain may cause psychological symptoms of anxiety and sadness.  When patients experience such negative feelings, emotional functions deteriorate as patients avoid going out and talking with others due to the worry about life with lung cancer, feeling death to be close, and even feeling fear.  Therefore, the pain cluster can affect three areas: physical, emotional, and social areas. For the fatigue/anorexia cluster, this symptom cluster includes drowsiness. Therefore, patients may be aware of deterioration of cognitive functions, having difficulty in concentrating on watching TV and reading books. Further, fatigue, which there is no effective way to cope with, makes it difficult to continue work and activities of daily living and also hinders hobbies and leisure activities.  Therefore, the fatigue/anorexia cluster can affect the role and cognitive functions.
Although three symptom clusters were identified, the symptom item severity is lower than mild (< 4) among the participants reported here. Regardless of severity, it is a universal desire to improve QOL and mitigate symptoms in patients with advanced NSCLCs. Symptom clusters are important for an understanding of global QOL because the clustering of the symptoms allows the clinician to appreciate the burden of a group of symptoms and the likelihood that symptoms may be occurring together. Treating one symptom without considering the symptom cluster may result in a greater symptom burden and poorer QOL. Nursing care based on individual tendencies suggested by focusing on symptom clusters as well as monitoring and assessing daily life interference may facilitate personalized intervention and contribute to improvement of QOL in a life-extending period as treatment outcomes.
First, this study has several limitations due to it being a convenience sample of patients with advanced NSCLCs undergoing standard therapy (n = 60). Second, it can no more than suggest the existence and influence of the three symptom clusters based on data at one point in time (the time of participation in the study) in a group of patients with advanced NSCLCs undergoing standard therapy (n = 60). This limits the extent to which we can generalize from the findings of this study. Third, it is not possible to rule out selection bias. Fourth, this study used a cross-sectional design, with no consideration of changes over time due to the therapeutic regimen, the disease stage, patient age, and changes in performance status in relation to the symptom clusters in patients with advanced NSCLCs undergoing standard therapy. Fifth, this study has not sufficiently examined the influence of various background factors, such as comorbidity and medication other than pain medications, known as potential factors to play roles in the experience of symptoms. Future studies need to employ a longitudinal design to determine whether the symptom clustering identified here is present across the lung cancer treatment trajectory.
Implications for future research and practice
By illustrating the existence of symptom clusters that influence key patient outcomes, the results of this study may prove useful in the design of ongoing screening assessment procedures. In this Japanese sample, almost 73.0% of patients reported pain severity scores below mild (< 4) lower than the higher levels reported in a USA sample. Because Japanese patients are not likely to express more symptom distress, providing interventions that target specific symptoms based on the standards used in the USA  may not be generally helpful for Japanese patients.
| Conclusion|| |
We identified three symptom clusters, each comprising three to five specific symptoms that influence QOL outcomes to different degrees. The knowledge gap that this paper addresses provides important information for nurses to understand and take into account to personalize the assessment and education of patients and families with advanced (IIIB or IV) NSCLCs. In the care of patients with advanced (IIIB or IV) NSCLCs undergoing standard therapy, clinicians must tailor clinical guidelines to prevent underestimation and intervention delays in the management of complex symptom clusters for patients like the group here with a high rate of mortality.
Financial support and sponsorship
This work was supported by JSPS KAKENHI Grant Number 20592534.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6], [Table 7]
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