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Symptom clusters in patients with nasopharyngeal carcinoma during radiotherapy

European Journal of Oncology Nursing, June 2017, Pages 7 - 13

Abstract

Purpose

Despite the improvement in radiotherapy (RT) technology, patients with nasopharyngeal carcinoma (NPC) still suffer from numerous distressing symptoms simultaneously during RT. The purpose of the study was to investigate the symptom clusters experienced by NPC patients during RT.

Methods

First-treated Chinese NPC patients (n = 130) undergoing late-period RT (from week 4 till the end) were recruited for this cross-sectional study. They completed a sociodemographic and clinical data questionnaire, the Chinese version of the M. D. Anderson Symptom Inventory - Head and Neck Module (MDASI-HN-C) and the Chinese version of the Functional Assessment of Cancer Therapy - Head and Neck Scale (FACT-H&N-C). Principal axis factor analysis with oblimin rotation, independent t-test, one-way analysis of variance (ANOVA) and Pearson product-moment correlation were used to analyze the data.

Results

Four symptom clusters were identified, and labelled general, gastrointestinal, nutrition impact and social interaction impact. Of these 4 types, the nutrition impact symptom cluster was the most severe. Statistically positive correlations were found between severity of all 4 symptom clusters and symptom interference, as well as weight loss. Statistically negative correlations were detected between the cluster severity and the QOL total score and 3 out of 5 subscale scores.

Conclusion

The four clusters identified reveal the symptom patterns experienced by NPC patients during RT. Future intervention studies on managing these symptom clusters are warranted, especially for the nutrition impact symptom cluster.

Highlights

  • Four symptom clusters were identified in NPC patients during radiotherapy.
  • The nutrition impact symptom cluster was the most severe.
  • Symptom clusters correlated positively with weight loss and symptom interference.
  • Symptom clusters correlated negatively with quality of life.

Keywords: Symptom clusters, Factor analysis, Nasopharyngeal carcinoma, Radiotherapy, Quality of life.

1. Introduction

Nasopharyngeal carcinoma (NPC) is endemic in South-East Asia (Torre et al., 2015), with the highest rates observed in the Cantonese population of southern China (Chang and Adami, 2006 and Jia et al, 2006). For this reason, NPC is called “Cantonese cancer” (Jia, 2008). Radiotherapy (RT) alone for early stage patients and combined chemoradiotherapy for locoregionally advanced cases of the disease are the main treatments for NPC (Agulnik and Epstein, 2008 and Xia et al, 2013). With RT techniques advanced and transformed from conventional 2-dimensional (2D) RT to 3-dimensional (3D) conformal or intensity-modulated RT (IMRT), the curative effect of treatment has increased and the 5-year overall survival rate of NPC patients can reach up to 70–80%. (Cao et al, 2011 and Tsai et al, 2012).

However, significant disease- and treatment-related symptoms such as taste change, dry mouth, sticky saliva, sore throat, lack of appetite and difficulty in swallowing remain of major concern to NPC patients undergoing treatment (Chan et al, 2003, Han et al, 2010, Huang et al, 2000, and Liu and Qin, 2011). During the widely practiced 6- to 7-week course of the RT regimen for treating NPC, it was found that most symptoms escalated at week 3 and continued to worsen throughout the RT course (Huang et al., 2000). Further, the severity and duration of symptoms increased when chemotherapy (CTX) was combined with RT (Agulnik and Epstein, 2008, Qiu et al, 2011, and Sumitsawan et al, 2009), leading to treatment interruption, psychological distress, decreased functional status and poor quality of life (QOL) (Chen et al, 2000, Fang et al, 2002, and Wu et al, 2007). Timely identification and management of these symptoms can yield better patient outcomes (Chan et al, 2014 and Lenz and Pugh, 2013).

Further, instead of occurring in isolation, there is ample evidence that symptoms often occur in clusters, which may exacerbate the overall symptom experience (Cheng et al, 2009, Cleeland, 2007, and Kwekkeboom et al, 2010). A symptom cluster has been defined as 2 or more related symptoms which occur together and form a stable group, relatively independent of other clusters (Kim et al., 2005). Because cancer patients seldom present with a single symptom, understanding and managing symptom clusters could be of considerable clinical significance. Further, there is evidence that symptom clusters can have synergistic effects on important patient outcomes, including functional status (Dodd et al, 2010 and Oh et al, 2012), QOL (Dodd et al, 2010, So et al, 2009, and Wang and Fu, 2014), emotional status (Breen et al., 2009) and even survival (Aktas et al, 2012 and Jiménez et al, 2011). Managing a symptom cluster as a whole could therefore be more efficient and effective than managing single symptoms (Chan et al, 2011, Chan et al, 2013, and Kwekkeboom et al, 2010). However, there seems to be no information on symptom clusters in NPC patients during RT. Studies to examine symptom clusters in NPC patients are needed, which is the first step to be taken before testing any interventions to manage them.

The current study was guided by the updated Theory of Unpleasant Symptoms (TOUS) (Lenz et al., 1997), which consists of 3 main reciprocal elements: symptoms, influencing factors and functional performance. Symptoms form the central concept. In this study, we investigate symptom clusters experienced by NPC patients. In respect of influencing factors, we focus on patients’ sociodemographic and clinical characteristics. Functional performance is the consequence of the symptom experience. In the current study, symptom interference with daily living is the outcome of particular interest. QOL is also examined because it was considered as another important outcome of symptom experience by the TOUS developers (Lenz and Pugh, 2013).

The purpose of the study was to identify symptom clusters experienced by NPC patients undergoing RT, with or without CTX, and to examine the relationships between symptom clusters and patients’ sociodemographic and clinical characteristics, as well as key patient outcomes, including symptom interference and QOL.

2. Methods

2.1. Patient recruitment

In this cross-sectional study, patients were recruited consecutively from the NPC department of Sun Yat-sen University Cancer Center (SYSUCC). The inclusion criteria were: (1) first-treated Chinese NPC patients; (2) currently in the late period (from week 4 till the end) of RT because symptoms are obvious then; (3) 18 years old or above; and (4) able to understand either Mandarin or Cantonese. Patients with other serious diseases, including diagnosed psychiatric morbidity and other types of cancer, were excluded. Ethical approval was obtained from the Survey and Behavioural Research Ethics Committee (SBREC) of the Chinese University of Hong Kong before data collection began. All participants signed consent forms.

2.2. Treatment regimen

In SYSUCC, IMRT is currently the mainstay RT modality for NPC. The primary gross tumor volume (GTVnx) and the involved lymph nodes (GTVnd) include all known gross disease as determined by imaging, clinical and endoscopic findings. The clinical target volume-1 (CTV-1) is defined as the high-risk region that includes GTV plus a 5- to 10-mm margin. It also includes the entire nasopharyngeal mucosa plus 5-mm submucosal volume. The CTV-2 is designed for potentially involved regions, which include CTV-1 plus a 5- to 10-mm margin. High-risk nodal regions are also included. Generally, the prescribed RT doses for GTVnx, GTVnd, CTV-1 and CTV-2 are 68–70 Gy, 60–70 Gy, 60–64 Gy and 54–58 Gy respectively, in 30–32 fractions. In SYSUCC, RT is delivered at 1 fraction per day, 5 days per week, and lasts for 6–7 weeks.

For patients with locoregionally advanced NPC, concurrent CTX with or without neoadjuvant CTX is adopted. The typical regimen for neoadjuvant CTX uses a combination of cisplatin (80–100 mg/m2, d1) and 5-fluorouracil (total dose: 4000 mg/m2, d1-5) administered intravenously every 3 weeks in 2 cycles before RT starts. While for concurrent CTX the regimen delivers cisplatin (80–100 mg/m2, d1) alone at the same time as RT every 3 weeks in 2 or 3 cycles.

2.3. Study instruments

The instruments consisted of a sociodemographic and clinical data questionnaire, a weighing scale, the Chinese version of the M. D. Anderson Symptom Inventory - Head and Neck Module (MDASI-HN-C), and the Chinese version of the Functional Assessment of Cancer Therapy - Head and Neck Scale (FACT-H&N-C) (version 4).

The sociodemographic and clinical data questionnaire was designed to collect information on gender, age, place of residence, educational level, marital status, occupational status, monthly household income, body weight before RT, co-morbidities, stage of disease, type of RT, number of times of RT, and whether being treated with CTX. The data were collected by participants’ self-reporting and review of medical records.

Patients’ current body weight was measured by a weighing scale. The weighing scale has an electronic screen and the body weight can be displayed on it directly. The unit for body weight is kilogram with one digit after the decimal point. Patients were required to weigh themselves twice to assure the accuracy of reading. Weight loss was calculated by subtracting current body weight from the body weight before RT.

The MDASI-HN-C was used to examine symptom clusters among NPC patients. The 28-item MDASI-HN is a validated head and neck cancer (HNC) specific instrument (Rosenthal et al., 2007) with 3 subscales: 13 core MDASI items that assess the severity of generic cancer related symptoms, 9 HNC-specific items that rate the severity of symptoms associated with HNC, and 6 interference items that evaluate the influence of symptoms on daily living activities. All symptoms are rated on a 0–10 scale to indicate the presence and severity of the symptoms in the last 24 h, with 0 indicating “not present” and 10 “as bad as you can imagine”. The interference items are also measured on a 0–10 scale, with 0 indicating “did not interfere” and 10 “interfered completely”. In this study, the Cronbach's α coefficients were 0.91, 0.85 and 0.88 for the 13 core MDASI items, the 9 HNC-specific items, and the 6 interference items, respectively.

The 39-item FACT-H&N (version 4) is a validated HNC-specific QOL instrument (List et al, 1996 and Ringash et al, 2008) consisting of 5 subscales that measure patients' physical well-being (7 items), social/family well-being (7 items), emotional well-being (6 items), functional well-being (7 items) and HNC-specific QOL issues (12 items) in the past 7 days. The score ranges from 0 to 4 (0 = not at all; 1 = a little bit; 2 = somewhat; 3 = quite a bit; 4 = very much). The Cronbach's α coefficient was 0.87 for the FACT-H&N-C in the current study.

2.4. Data analysis

The Statistical Package for Social Sciences version 21 software (SPSS Inc., Chicago, IL) was used for data analysis, and the level of significance set at 0.05. Descriptive statistics, including the mean, standard deviation (SD) and frequency (%), were used to describe the study sample. Principal axis factor analysis with oblimin rotation was adopted to identify symptom clusters of NPC patients from the 13 core symptoms and 9 HNC-specific symptoms in the MDASI-HN-C respectively, to keep in line with the instrument development methods as well as for empirical reasons. Kaiser's criterion was employed to retain factors with an eigenvalue greater than 1.0. A cutoff value of 0.3 for factor loading was chosen to determine which items belonged to a certain factor (Pallant, 2013). Pearson product-moment correlation was adopted to assess the intercorrelations of symptoms within clusters. Independent t-test, one-way analysis of variance (ANOVA) and Pearson product-moment correlation were used, as appropriate, to examine the relationships between symptom clusters and patients' sociodemographic and clinical characteristics, symptom interference and QOL.

3. Results

3.1. Sociodemographic and clinical characteristics

A total of 144 patients were approached, of whom 14 declined to participate. Most (72.3%) were male, and the mean age was 43.22 ± 9.75 (mean ± SD), with a range of 18–65. Most had received junior high school or higher levels of education (86.9%), and were married (91.5%) and employed (59.2%). With respect to clinical characteristics, participants on average lost 5.13 ± 3.58 kg of their body weight. The majority (87.7%) were in a late stage (III or IV) of the disease according to the 7th edition of the tumor node metastasis (TNM) classification (Sobin et al., 2009). All participants received IMRT, with an average of 21.48 ± 4.80 (range: 15–32) times at recruitment and almost all of them (97.7%) had been or were being treated with CTX, within which 3.8% received neoadjuvant CTX only, 44.6% concurrent only, and the rest 49.2% of participants received both neoadjuvant and concurrent CTX. Detailed information on patients’ sociodemographic and clinical characteristics is presented in Table 1.

Table 1

Sociodemographic and clinical characteristics of the sample (n = 130).

 

Characteristics Mean (SD) Frequency (%)
Gender
 Male 94 (72.3)
 Female 36 (27.7)
Age (years) 43.22 (9.75)
Place of birth
 Guangdong 97 (74.6)
 Elsewhere 33 (25.4)
Place of residence
 Urban area 67 (51.5)
 Rural area 63 (48.5)
Educational level
 Primary 17 (13.1)
 Junior high 39 (30.0)
 Senior high 39 (30.0)
 Tertiary or above 35 (26.9)
Marital status
 Single or widowed 11 (8.5)
 Married 119 (91.5)
Occupational status
 Unemployed 53 (40.8)
 Employed 77 (59.2)
Monthly household income (RMB)
 0–2000 27 (21.3)
 2001–6000 52 (40.9)
 6001–10,000 22 (17.3)
 >10,000 26 (20.5)
Weight loss (kg) 5.13 (3.58)
Co-morbidities
 No 90 (69.2)
 Yes 40 (30.8)
Clinical stage
 I 1 (0.8)
 II 15 (11.5)
 III 74 (56.9)
 IV 40 (30.8)
T stage
 T1 10 (7.7)
 T2 21 (16.2)
 T3 72 (55.4)
 T4 27 (20.8)
N stage
 N0 10 (7.7)
 N1 53 (40.8)
 N2 52 (40.0)
 N3 15 (11.5)
M stage
 M0 124 (95.4)
 M1 6 (4.6)
Type of RT
 IMRT 130 (100)
Number of times of RT 21.48 (4.80)
Type of CTX
 No CTX 3 (2.3)
 Neoadjuvant 5 (3.8)
 Concurrent 58 (44.6)
 Neoadjuvant + concurrent 64 (49.2)

3.2. Symptom prevalence, severity and interference

The 5 most prevalent symptoms reported by the participants were problem with mucus (99.2%), difficulty swallowing/chewing (98.5%), having a dry mouth (97.7%), problem with tasting food (96.9%) and mouth/throat sores (96.9%). The 5 most severe symptoms were problem with tasting food (mean ± SD, 6.78 ± 2.62), problem with mucus (6.41 ± 2.22), having a dry mouth (6.32 ± 2.37), difficulty swallowing/chewing (6.15 ± 2.36) and lack of appetite (6.11 ± 2.85). As to symptom interference, work was interfered with the most (4.08 ± 3.25), and relation with other people the least (2.48 ± 2.57). The prevalence, severity and interference of symptoms are set out in Table 2.

Table 2

Symptom prevalence, severity and interference of NPC patients during RT (n = 130).

 

MDASI-HN-C Mean of severity SD Prevalence (%)
Symptoms
Problem with tasting food 6.78 2.62 96.9
Problem with mucus 6.41 2.22 99.2
Having a dry mouth 6.32 2.37 97.7
Difficulty swallowing/chewing 6.15 2.36 98.5
Lack of appetite 6.11 2.85 95.4
Mouth/throat sores 5.99 2.38 96.9
Nausea 4.89 2.95 91.5
Disturbed sleep 4.66 2.74 94.5
Vomiting 4.58 3.35 81.5
Fatigue 4.30 2.25 93.8
Feeling drowsy 4.27 2.57 90.8
Feeling of being distressed 4.12 2.76 86.0
Pain 4.08 2.81 83.8
Difficulty with voice/speech 3.88 2.69 85.4
Constipation 3.82 3.21 76.9
Feeling sad 3.74 2.90 82.3
Problem with teeth or gums 3.73 2.73 82.3
Choking/coughing 3.30 2.97 73.8
Skin pain/burning/rash 2.94 2.61 76.7
Shortness of breath 2.47 2.41 67.7
Numbness or tingling 2.30 2.48 60.5
Problem with remembering things 1.85 2.18 56.2
Interference
Work 4.08 3.25 82.3
Enjoyment of life 3.93 2.88 86.2
Mood 3.49 2.56 86.2
General activity 2.99 2.84 69.2
Walking 2.60 2.61 66.2
Relations with other people 2.48 2.57 68.5

3.3. Symptom clusters

Factor analysis was conducted on the 13 core and 9 HNC-specific symptoms. In the former case, 2 factors were revealed with eigenvalues greater than 1.0, explaining 47.25% and 8.79% of the variance respectively. Factor 1 comprised 11 symptoms: feeling drowsy, shortness of breath, feeling of being distressed, feeling sad, numbness or tingling, disturbed sleep, fatigue, problem with remembering things, pain, lack of appetite and having a dry mouth. Factor 2 consisted of 2 symptoms: nausea and vomiting. Among the 9 HNC-specific symptoms, another 2 factors with eigenvalues exceeding 1.0 were identified, explaining 47.65% and 11.48% of the variance respectively. Factor 3 covered 6 symptoms: problem with mucus, mouth/throat sore, difficulty swallowing/chewing, problem with tasting food, problem with teeth or gums and constipation. Factor 4 covered 3 symptoms: choking/coughing, difficulty with voice/speech and skin pain/burning/rash. After examining the nature of each factor's symptoms, we named factors 1, 2, 3 and 4 as general, gastrointestinal, nutrition impact and social interaction impact symptom clusters, respectively. Patterns of factor loadings determined by principal axis factor analysis are shown in Table 3 and Table 4.

Table 3

Factor analysis of 13 core items of the MDASI-HN-C.

 

13 core symptoms Factor 1 (general symptom cluster) Factor 2 (gastrointestinal symptom cluster)
Feeling drowsy 0.833 0.084
Shortness of breath 0.799 0.104
Feeling of being distressed 0.797 0.052
Feeling sad 0.714 0.059
Numbness or tingling 0.596 0.018
Disturbed sleep 0.530 −0.163
Fatigue 0.527 −0.227
Problem with remembering things 0.510 −0.106
Pain 0.490 −0.072
Lack of appetite 0.479 −0.280
Having a dry mouth 0.322 −0.276
Nausea 0.009 −0.925
Vomiting 0.057 −0.853

Extraction method: principal axis factoring; rotation method: oblimin with Kaiser normalization.

Numbers in bold indicate the loadings for the factor indicated.

Table 4

Factor analysis of 9 HNC-specific items of the MDASI-HN-C.

 

9 HNC-specific symptoms Factor 1 (nutrition impact symptom cluster) Factor 2 (social interaction impact symptom cluster)
Problem with mucus 0.878 −0.025
Mouth/throat sore 0.694 0.162
Difficulty swallowing/chewing 0.576 0.239
Problem with tasting food 0.571 −0.109
Problem with teeth or gums 0.436 0.148
Constipation 0.374 0.260
Choking/coughing −0.023 0.750
Difficulty with voice/speech 0.073 0.736
Skin pain/burning/rash 0.033 0.551

Extraction method: principal axis factoring; rotation method: oblimin with Kaiser normalization.

Numbers in bold indicate the loadings for the factor indicated.

Intercorrelations of symptoms within clusters were all statistically significant (all p < 0.05). The correlation coefficients ranged from 0.190 to 0.680 for the general symptom cluster. For the gastrointestinal symptom cluster, the coefficient was 0.823. For the nutrition impact and social interaction impact symptom clusters, the coefficients ranged from 0.298 to 0.695 and 0.408 to 0.556, respectively.

The severity of symptom clusters was computed by averaging the severity scores of the symptoms included. Among the 4 clusters, the nutrition impact type was the most severe (5.48 ± 1.88), followed by the gastrointestinal (4.73 ± 3.01), general (3.97 ± 1.77) and social interaction impact types (3.36 ± 2.24).

3.4. Relationships between symptom clusters and sociodemographic and clinical characteristics, symptom interference and QOL

The associations between the severity of symptom clusters and sociodemographic and clinical characteristics, in most cases, were not statistically significant. However, all 4 clusters correlated significantly with weight loss (rgeneral = 0.291, rgastrointestinal = 0.310, rnutrition = 0.274, rsocial interaction = 0.214; all p < 0.05). Participants who lost more weight during treatment experienced more severe symptom clusters. Occupational status was found to correlate significantly with 2 clusters: nutrition impact (t = 2.096; p < 0.05) and social interaction impact clusters (t = 2.641; p < 0.01). The severity scores of these 2 clusters were higher in participants who did not have jobs. Only the severity of the social interaction impact cluster correlated positively with the number of times RT had been received (r = 0.336, p < 0.01).

With regard to the relationships between symptom clusters and symptom interference and QOL, the severity of all 4 clusters correlated positively with the degree of symptom interference (rgeneral = 0.666, rgastrointestinal = 0.427, rnutrition = 0.585, rsocial interaction = 0.536; all p < 0.01), and correlated negatively with the total score of the FACT-H&N-C (rgeneral = −0.523, rgastrointestinal = −0.249, rnutrition = −0.453, rsocial interaction = −0.409; all p < 0.01) and 3 out of 5 subscale scores: physical (rgeneral = −0.705, rgastrointestinal = −0.461, rnutrition = −0.563, rsocial interaction = −0.491; all p < 0.01), emotional (rgeneral = −0.370, rgastrointestinal = −0.232, rnutrition = −0.303, rsocial interaction = −0.257; all p < 0.01) and HNC-specific (rgeneral = −0.372, rgastrointestinal = −0.184, rnutrition = −0.387, rsocial interaction = −0.465; all p < 0.05). Only the general cluster was found to correlate significantly with the functional subscale of the FACT-H&N-C (r = −0.228, p < 0.05). No statistically significant correlations were found between any of the 4 clusters and the social/family subscale. Details of the relationships between symptom clusters and sociodemographic and clinical characteristics, symptom interference and QOL are given in Table 5.

Table 5

Relationships between symptom clusters and sociodemographic and clinical characteristics, symptom interference and QOL.

 

Variables Symptom clusters
General Gastrointestinal Nutrition impact Social interaction impact
Mean (SD) t/F/r Mean (SD) t/F/r Mean (SD) t/F/r Mean (SD) t/F/r
Characteristics
Gender
 Male 3.81 (1.69) −1.644 4.51 (2.81) −1.290 5.45 (1.82) −0.250 3.26 (2.13) −0.815
 Female 4.38 (1.93) 5.33 (3.44) 5.55 (2.06) 3.62 (2.52)
Age (years)a 0.045 −0.034 0.064 0.139
Place of birth
 Guangdong 3.85 (1.78) −1.287 4.64 (3.03) −0.586 5.42 (1.94) −0.572 3.43 (2.21) 0.564
 Elsewhere 4.31 (1.74) 5.00 (2.97) 5.64 (1.69) 3.17 (2.35)
Place of residence
 Urban area 3.95 (1.85) −0.137 4.44 (2.90) −1.152 5.36 (1.90) −0.758 3.25 (2.33) −0.595
 Rural area 4.00 (1.70) 5.05 (3.11) 5.61 (1.86) 3.48 (2.15)
Educational levelb
 Primary 4.35 (2.20) 1.890 4.00 (3.67) 1.339 5.67 (2.59) 1.121 3.52 (2.04) 0.774
 Junior high 4.25 (1.59) 5.33 (2.61) 5.77 (1.70) 3.74 (2.43)
 Senior high 3.39 (1.91) 4.22 (3.21) 5.03 (2.01) 2.99 (2.40)
 Tertiary or above 4.07 (1.53) 5.00 (2.79) 5.56 (1.47) 3.28 (1.90)
Marital status
 Single or widowed 3.17 (1.36) −1.575 3.95 (2.59) −0.899 4.79 (2.05) −1.279 2.42 (2.02) −1.459
 Married 4.05 (1.80) 4.81 (3.04) 5.54 (1.86) 3.45 (2.24)
Occupational status
 Unemployed 4.21 (1.89) 1.212 4.87 (3.12) 0.418 5.91 (2.07) 2.096* 3.98 (2.40) 2.641**
 Employed 3.82 (1.69) 4.64 (2.94) 5.19 (1.69) 2.94 (2.03)
Monthly household income (RMB)b
 0–2000 4.32 (1.94) 0.683 5.37 (3.15) 0.553 5.83 (2.10) 0.483 4.14 (2.44) 1.438
 2001–6000 3.76 (1.84) 4.55 (2.77) 5.36 (1.89) 3.10 (2.39)
 6001–10,000 3.93 (1.66) 4.43 (2.89) 5.33 (1.69) 3.06 (1.80)
 >10,000 4.20 (1.65) 4.83 (3.33) 5.33 (1.78) 3.29 (2.09)
Weight loss (kg)a 0.291∗∗ 0.310∗∗ 0.274∗∗ 0.214
Co-morbidities
 No 3.88 (1.68) −0.898 4.71 (2.93) −0.133 5.45 (1.90) −0.251 3.24 (2.25) −0.952
 Yes 4.18 (1.96) 4.79 (3.22) 5.54 (1.86) 3.64 (2.21)
Clinical stage
 Early stage (I & II) 4.02 (1.38) 0.103 4.59 (2.43) −0.199 5.30 (1.84) −0.402 3.46 (1.86) 0.184
 Late stage (III & IV) 3.97 (1.83) 4.75 (3.09) 5.50 (1.89) 3.35 (2.29)
Number of times of RTa 0.010 0.006 0.120 0.336∗∗
Type of CTXb
 No CTX 2.39 (0.78) 1.371 3.17 (2.25) 0.577 4.44 (1.73) 0.728 2.00 (1.45) 0.555
 Neoadjuvant 3.60 (1.94) 4.40 (4.17) 6.17 (3.01) 2.87 (2.69)
 Concurrent 3.83 (1.83) 4.53 (3.22) 5.34 (1.84) 3.52 (2.34)
 Neoadjuvant + concurrent 4.22 (1.72) 5.02 (2.76) 5.60 (1.84) 3.32 (2.15)
Interferencea 0.666∗∗ 0.427∗∗ 0.585∗∗ 0.536∗∗
QOL
 Physical well-beinga −0.705∗∗ −0.416∗∗ −0.563∗∗ −0.491∗∗
 Social/family well-beinga 0.008 0.073 −0.030 −0.043
 Emotional well-beinga −0.370∗∗ −0.232∗∗ −0.303∗∗ −0.257∗∗
 Functional well-beinga −0.228 −0.048 −0.167 −0.078
 HNC-specific QOLa −0.372∗∗ −0.184 −0.387∗∗ −0.465∗∗
 Total score of QOLa −0.523∗∗ −0.249∗∗ −0.453∗∗ −0.409∗∗

a Pearson product-moment correlation.

b ANOVA; all other comparisons were made by using independent t-test.

*p < 0.05; **p < 0.01.

4. Discussion

Although NPC patients are severely distressed by a series of symptoms during RT, relevant studies are scarce. This study adopted a novel approach to investigate symptom clusters in NPC patients during RT. Further, the relationships between symptom clusters and patients’ sociodemographic and clinical characteristics, symptom interference and QOL were also examined.

Results on symptom prevalence and severity were similar to those of previous studies conducted with Chinese NPC patients (Han et al, 2010, Huang et al, 2000, and Liu and Qin, 2011). Nutrition-related symptoms were found to be the most prevalent and severe symptoms in both this and previous studies. The degree of symptom interference with daily living was also found to be consistent with Chen and Tseng's findings (2006).

By using principal axis factor analysis, 4 clusters were identified from the 13 core symptoms and 9 HNC-specific symptoms of the MDASI-HN-C. The general and gastrointestinal clusters were identified by examining the internal structure of the 13 core symptoms. This result is in line with several previous studies using the MDASI in patients with general cancers (Cleeland et al, 2000, Lin et al, 2007, and Wang et al, 2004). Another 2 clusters (nutrition impact and social interaction impact) were revealed in the 9 HNC-specific symptoms, consistent with Rosenthal and colleagues’ findings on HNC patients (Rosenthal et al., 2007). Statistically significant correlation coefficients among symptoms within clusters further supported the presence of the 4 identified symptom clusters (Chan et al, 2005 and Kim et al, 2005).

The current study also investigated the severity of the 4 symptom clusters identified. The nutrition impact type was the most distressing, a finding that provides important information for prioritizing interventions. Priority for interventions is recommended for the key symptom clusters which distress patients the most and have the greatest impact on health-related outcomes (Xiao et al., 2016). The upmost importance should therefore be accorded to managing the nutrition impact symptom cluster.

It was found that weight loss correlated positively with the severity of all 4 symptom clusters. On one hand, cancer is a debilitating disease and weight loss in NPC patients during treatment is more severe because of the damage caused by radiation to the head and neck region, which can affect eating ability. Patients generally had insufficient food intake, much lower than the body needed, and it was reported that NPC patients sustained an average 6.9 kg weight loss after completing RT (Qiu et al., 2011). On the other hand, weight loss might also decrease treatment tolerance, delay recovery and aggravate symptoms (Qiu et al., 2011). The correlation between occupational status and symptom clusters was not very strong, and significant correlations were only found with 2 clusters. Patients who were employed had less severe nutrition impact and social interaction impact clusters. One possible explanation for this is that employed patients enjoyed better social support and economic conditions, but further studies are needed to explore this relationship. It is generally believed that symptoms worsen as radiation accumulates. However, it was surprising to find that only the social interaction impact cluster correlated significantly with the number of times RT had been received. There might be 2 possible reasons. First, the homogeneity of participants might have made it difficult to distinguish the difference, as all participants were undergoing late-period RT. Second, CTX could also influence the result, as a confounding variable.

The current study found moderate to high correlations between all 4 clusters and symptom interference. This finding was consistent with other studies which examined the relationships between symptom clusters and various types of functional performance (Dodd et al, 2010 and Oh et al, 2012). A negative relationship was found between symptom clusters and total QOL score, again in line with previous studies (Dodd et al, 2010, So et al, 2009, and Wang and Fu, 2014). For the subscales of QOL, all correlations were statistically significant, except in the case of the social/family and functional types. Social/family well-being did not correlate with any symptom clusters. This result is understandable, and to be expected especially in a Chinese society where family support is strong and stable (Chow et al, 2014 and Gu et al, 2013). For the functional subscale, only the relationship with the general cluster was statistically significant, which might be due to the general functions the subscale measures, such as work, sleep and life satisfaction. However, further studies are needed to learn more about the relationship between these symptom clusters and functional well-being.

This study identified 4 symptom clusters in NPC patients during RT, the cornerstone of effective symptom management. The severity of these 4 clusters was also examined, further underlining the priority of symptom management. For clinical practice, the findings of this study will lead to a better understanding of the symptom patterns experienced by NPC patients during RT, laying a foundation for managing symptom clusters in the future. Research on interventions to manage these identified symptom clusters is needed, especially in the case of the nutrition impact cluster. Apart from the symptom cluster itself, key variables including body weight, symptom interference and QOL also need to be measured in future intervention studies to gauge the effectiveness of the intervention.

There are 2 limitations to the study. First, the composition of a cluster depends on the assessment tools and statistical methods applied. In this study, the MDASI-HN-C adopted is not designed specifically for NPC patients, as there is currently no comprehensive NPC-specific symptom assessment tool available to explore symptom clusters experienced by NPC patients. Second, this study adopted a cross-sectional design, and dynamic changes in symptom clusters and their relationships with patient outcomes were not examined.

5. Conclusion

Despite improvements in RT technology, NPC patients still suffer from numerous distressing symptoms concurrently during RT. By identifying the symptom clusters, this study reveals the underlying interrelationships among symptoms experienced by NPC patients undergoing RT. The findings lead to a potentially more efficient and effective approach to manage the symptom cluster as a whole. As it is the most distressing type, priority in future studies should be given to the management of the nutrition impact symptom cluster.

Conflict of interest statement

The authors have no conflict of interest to disclose.

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Footnotes

a School of Nursing, Guangzhou University of Chinese Medicine, Guangzhou 510006, Guangdong, China

b The Nethersole School of Nursing, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China

c State Key Laboratory of Oncology in South China and Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China

d Department of Nasopharyngeal Carcinoma, Sun Yat-sen University Cancer Center, Guangzhou 510060, Guangdong, China

Corresponding author. 7/F, Esther Lee Building, The Nethersole School of Nursing, The Chinese University of Hong Kong, New Territories, Hong Kong SAR, China.


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