Objectives: To explore the relationship between 16 symptom clusters (SCs), clinical and demographic influencing factors, and clinical outcomes over time in patients with pancreatic cancer (PC) undergoing surgical resection.
Sample & Setting: 143 patients with stage II PC undergoing surgical resection were recruited to participate in this longitudinal, exploratory study conducted at Thomas Jefferson University Hospital, a National Cancer Institute–designated cancer center.
Methods & Variables: Quality of life was measured preoperatively and at three, six, and nine months postoperatively. Statistical methods included simple linear and Cox proportional hazard regression.
Results: Preoperative pain was significantly associated with the pain–gastrointestinal SC, and preoperative worry was significantly associated with the mood SC. The strongest negative association with emotional well-being across all study time points was found with the preoperative mood SC. The insomnia–digestive problems SC and the nutritional problems SC demonstrated a trend toward poor survival.
Implications for Nursing: Findings provide evidence that preoperative worry and pain are associated with SC severity and that SCs may have a detrimental effect on quality of life and survival in patients with PC undergoing surgical resection.
Patients with pancreatic cancer (PC) experience a wide range of symptoms as a result of the cancer itself and its treatments. Commonly reported PC symptoms include fatigue, pain, weight loss, nausea, anorexia, constipation, diarrhea, trouble digesting food, insomnia, depression, anxiety, and symptoms of diabetes (Huang et al., 2000; Noquez, 2008; Reyes-Gibby et al., 2007; Sun et al., 2008; Yeo et al., 2012). Patients with PC were found to experience some of the highest levels of psychological distress, fatigue, and pain when compared to patients with other cancer types (Carlson et al., 2004; Noquez, 2008; Zabora, BrintzenhofeSzoc, Curbow, Hooker, & Piantadosi, 2001). Evidence suggests that symptoms rarely occur alone; in fact, patients undergoing surgical resection for PC experience, on average, 5–10 symptoms simultaneously (Yeo et al., 2012).
The presence of two or more interrelated, concurrent symptoms that may or may not have a common causative mechanism is called a symptom cluster (SC) (Dodd, Miaskowski, & Lee, 2004; Kim, McGuire, Tulman, & Barsevick, 2005). SCs have been identified in patients with virtually every cancer type, including patients with breast (Sullivan et al., 2018), ovarian (Huang et al., 2016), prostate (Dirksen, Belyea, Wong, & Epstein, 2016), lung (Franceschini, Jardim, Fernandes, Jamnik, & Santoro, 2013), colorectal (Agasi-Idenburg, Thong, Punt, Stuiver, & Aaronson, 2017), and PC (Yeo et al., 2012). Patients with cancer experience SCs before (Browall et al., 2017; Kim, Barsevick, & Tulman, 2009), during (Kim, Barsevick, Tulman, & McDermott, 2008; Sullivan et al., 2018), and even years after treatment (Zucca, Boyes, Linden, & Girgris, 2012).
The presence or severity of SCs has been found to be influenced by several demographic and clinical factors: age, gender, race/ethnicity, marital status, tobacco use, cancer stage, treatment type, and comorbid conditions in patients with cancer (Cheville et al., 2011; Kim et al., 2009; Nho, Reul Kim, & Nam, 2017; Reyes-Gibby, Aday, Anderson, Mendoza, & Cleeland, 2006; Xiao et al., 2012). A relationship has also been observed between poor quality of life (QOL) and a higher number (Lin, Chen, Yang, & Zhou, 2013) and greater severity of SCs (Franceschini et al., 2013; Nho et al., 2017; Sanford et al., 2014). Certain SCs were also found to be predictors of poor QOL in specific cohorts, including older adults with cancer (Cheng & Lee, 2011), newly diagnosed patients undergoing active treatment (Pirri et al., 2013), and patients with advanced cancers (Dong et al., 2016). Likewise, an association has been observed between SCs and reduced survival in patients with lung (Cheville et al., 2011), esophageal (Wikman, Johar, & Lagergren, 2014), and advanced cancers (Aktas, Walsh, & Rybicki, 2012). Given these important relationships, SCs have become a priority focus of oncology nursing research (Knobf et al., 2015).
The body of research regarding factors that influence SCs and the relationship between SCs and clinical outcomes in many cancer types is rapidly growing: however, research focused on these phenomena in patients with PC remains limited. To date, only three studies have examined the factors that influence the SC experience or the effect of SCs on clinical outcomes in patients with various cancer types, including patients with PC. Gender, cancer type, and marital status were found to be significantly associated with SC intensity (Noquez, 2008), whereas age, race and C-reactive protein levels were found to not be significantly related to SCs (Laird et al., 2011; Noquez, 2008). SCs were found to be associated with poor clinical outcomes, including decreased physical functioning (Laird et al., 2011) and reduced median survival (Yeo et al., 2012).
The management of SCs is a concern for oncology nurses and for patients with cancer and their family members, who must assume responsibility for the day-to-day management of symptoms. Understanding factors that influence SCs is not only critical to ensure that appropriate symptom management strategies are implemented, but also to enhance counseling and anticipatory guidance provided to patients with PC and their family members. Gaining an understanding of the clinical and demographic factors that influence SC severity may also help explain causative mechanisms of SCs and assist clinicians in identifying patients at increased risk for more severe SCs postoperatively (Kim et al., 2009). In addition, understanding the factors that influence the severity of SCs and their relationship to QOL and survival may enable clinicians to identify high-risk patients and implement earlier SC interventions, which may reduce the severity or prevent the occurrence of SCs entirely, therefore improving clinical outcomes in this population (Sanford et al., 2014).
No research has examined factors that influence SCs or the effect of SCs on clinical outcomes over time in patients with PC undergoing surgical resection. Therefore, the purpose of this article is to describe the relationship between the severity of 16 previously identified SCs (Burrell et al., 2018) and (a) demographic and clinical influencing factors and (b) clinical outcomes of QOL and survival over time in patients with stage II PC undergoing surgical resection.
The Theory of Unpleasant Symptoms (TOUS) served as the theoretical framework for this study (Lenz, Pugh, Milligan, Gift, & Suppe, 1997). The TOUS is comprised of three major concepts: (a) the singular or multiple symptoms that the patient is experiencing, (b) the clinical and demographic variables that influence the patient’s perception of symptoms (the physiologic, psychological, and situational influencing factors), and (c) the effect that symptoms have on clinical outcomes (performance). The relationship among these three concepts is viewed as dynamic, interactive, and reciprocal in nature. The TOUS was used to conceptualize SCs, determine influencing and performance variables to include in this study, and explore the relationships among these variables.
Design, Sample, and Setting
This nested, longitudinal, descriptive study was conducted within a randomized, controlled trial (the parent study) at a National Cancer Institute–designated comprehensive cancer center at Thomas Jefferson University Hospital in Philadelphia, Pennsylvania. The parent study (Lavu et al., 2015) evaluated the effectiveness of an intraoperative celiac alcohol nerve block, a pain-relieving intervention, in 485 patients undergoing surgical resection of pancreas and periampullary cancers.
The current article adds to previously reported findings of a descriptive, longitudinal study that explored self-reported symptom profiles to identify the (a) presence of and changes in SCs, (b) factors that influence patients’ perceptions of the SCs, and (c) effect of SCs on QOL and survival over time in patients with stage II PC undergoing surgical resection. Because of the large volume of data generated in the study, the findings are being presented in two parts. Self-reported symptom profiles and SCs identified in the study were previously reported (Burrell et al., 2018). This article describes the relationship between 16 previously identified SCs, demographic and clinical influencing factors, and clinical outcomes over time in patients with PC undergoing surgical resection, and serves as a follow-up article that extends the analysis from the prior report (Burrell et al., 2018).
The current study examined a sub-sample of patients with stage IIa or IIb PC undergoing surgical resection with or without adjuvant therapy recruited through convenience sampling techniques used in the parent study (Lavu et al., 2015). Of the 143 patients who participated in the current study, 17% (n = 24) did not complete the final nine-month questionnaire. Twenty-three patients died, and one patient declined continued participation. Participant response rates were 76% (n = 109) at three months, 64% (n = 92) at six months, and 62% (n = 89) at nine months postoperatively. Based on the use of factor analyses to identify SCs in this study, subject-to-variable guidelines requiring at least five participants for each variable were followed to determine an adequate sample size (Gorsuch, 1983). Therefore, a sample size of 85 participants at each study time point was deemed adequate to conduct a reliable factor analysis. The all-available data approach was used to address missing data to preserve patient variation in the data set and to ensure that inferences are representative of patients with stage II PC undergoing surgery (Nakai & Ke, 2011).
As previously described in greater detail (Burrell et al., 2018), most patients in this study were male (n = 82, 57%) and married (n = 107, 75%), with a mean age of 67.3 (SD = 10.4) years. Most were White (n = 129, 90%), non-Hispanic/non-Latino (n = 134, 94%) with at least one comorbid condition (n = 140, 98%). All patients were diagnosed with stage IIa (n = 28, 20%) or IIb (n = 115, 80%) PC. All patients underwent surgical resection for PC, with the most common surgical procedure being the pylorus-preserving pancreaticoduodenectomy (n = 92, 64%); 38% (n = 54) experienced postoperative complications. Following surgical resection, 82% (n = 117) received adjuvant treatment.
Measures and Variables
Patient-reported QOL was measured by the Functional Assessment of Cancer Therapy–Hepatobiliary (FACT-Hep), a patient-reported instrument designed to measure QOL in patients with hepatobiliary cancers (Heffernan et al., 2002). The FACT-Hep consists of the FACT–General (FACT-G), which assesses generic QOL, and a hepatobiliary-specific subscale, which assesses disease-specific QOL. The 27-item FACT-G assesses four dimensions of QOL: physical, social, emotional, and functional well-being. The hepatobiliary-specific subscale includes an additional 18 questions that assess symptoms and issues pertinent to patients with hepatobiliary cancer. All FACT-Hep items are assessed on a five-point severity scale ranging from 0 (not at all) to 4 (very much). FACT-Hep has demonstrated high internal consistency (Cronbach alpha range = 0.72–0.94), good test-retest reliability (Spearman correlation range = 0.84–0.91), and divergent and convergent validity (Heffernan et al., 2002).
QOL data were collected through mailed questionnaires at four points in time: preoperatively (T1) and at three (T2), six (T3), and nine months (T4) postoperatively. Survival outcome data were collected at T2, T3, and T4 and again at the time of data analysis. Survival outcome data included date of death, as reported by the Social Security Administration’s online death index, obituaries, or through family reports. Demographic and clinical data were obtained from electronic health records. Study questionnaires and supportive documentation of patient demographic and clinical data were copied, de-identified, given a unique identification number, and stored in individual patient study folders. Institutional review board approval was obtained for this study from Thomas Jefferson University Hospital and Villanova University.
As previously described by the authors (Burrell et al., 2018), exploratory factor analysis and confirmatory factor analysis (CFA) were used to identify SCs in the current study. SCs at each study time point were determined by the following criteria (a) at least two symptoms with absolute factor loadings greater than or equal to 0.4 (Kim et al., 2008) and (b) congruence between the exploratory factor analysis and confirmatory factor analysis structures. If the same symptom loaded to two different factors (SCs), both symptom loadings were retained to enhance the clinical meaningfulness of SC findings. See Figures 1–4 for a summary of the 16 previously identified SCs. Multiple sets of SC scores were generated, and SAS Proc MIANALYZE was used to combine estimates from the multiple sets for each of the analyses used.
Simple linear regression (SLR) was used to determine if selected physiologic, psychological, and situational factors influenced the severity of the 16 SCs and to examine the relationship between each of the identified SCs and QOL. In the SLR models examining influencing factors, the selected influencing factor served as the independent variable and SC severity served as the dependent variable. In the SLR models examining QOL, SC severity was the independent variable and FACT-Hep physical, social, emotional, and functional well-being subscale scores and total scores (general and disease-specific QOL) were the outcome variables. Both unadjusted models and models adjusted for adjuvant treatment were tested to examine the relationship between SC severity and QOL.
Cox proportional-hazards regression was used to determine if the severity of the identified SCs was predictive of survival after surgery alone or in conjunction with adjuvant therapy. For these models, CFA final factor scores were divided at the median to obtain a high symptom severity and a low severity group for each SC identified at each study time point (T1–T4). Two proportional hazard regression models were constructed: unadjusted model and a model adjusted for variables found to be significantly associated with survival, including neoadjuvant therapy, adjuvant therapy, grade of PC, surgery type, and cancer antigen (CA) 19-9 serum levels.
Given the substantial number of regression models that were tested in this study, p values were adjusted for multiplicity using the method of Benjamini and Hochberg (1995) to control the overall false discovery rate at each study time point at 5%.
Two of the 25 physiologic, psychological, and situational influencing factors examined were found to be significantly associated with SC severity. These were preoperative pain and preoperative worry. Preoperative pain status demonstrated a statistically significant relationship with the pain–gastrointestinal SC (factor 1), consisting of nausea, back pain, abdominal pain/cramping, poor appetite, constipation, and trouble digesting food, preoperatively (T1) (slope = 0.71, 95% confidence interval [CI] [0.31, 1.11], p = 0.036). Because SCs have a standard deviation (SD) of 1 by design, for every 1-point increase in pain severity patients with PC reported preoperatively, there was a 0.71 SD increase in severity of the pain–gastrointestinal SC. Similarly, preoperative worry (an affective reaction to cancer) was significantly related to the mood SC (factor 2), consisting of anxiety and depression, at T1 (slope = 0.34, 95% CI [0.2, 0.48], p = 0.001). Therefore, for every 1-point increase in worry severity that patients with PC reported preoperatively, there was a 0.34 SD increase in severity of the mood SC.
Quality of Life
As shown in Tables 1–4, mean physical and functional well-being scores followed a similar trajectory over time. Physical and functional well-being mean scores decreased from T1 to T2, then gradually increased postoperatively at T3 and T4. Mean functional well-being improved postoperatively. Mean social well-being scores at T1 (24.59 [SD = 3.99]) slightly decreased at T2 (24.31 [SD = 4.24]) and T3 (23.66 [SD = 4.4]) and then slightly increased at T4 (24.09 [SD = 4.56]), but never reached preoperative scores. Mean emotional well-being scores increased from T1 at T2 and T3, then slightly decreased at T4. General QOL total mean scores (FACT-G) gradually increased from T1 at all three postoperative time points. Mean disease-specific QOL scores (FACT-Hep) increased from T1 at T2 and T3, then slightly decreased at T4, with all postoperative mean scores exceeding preoperative scores.
Increased severity of 13 SCs was found to be associated with disease-specific QOL (FACT-Hep scores) in the unadjusted models (results not shown) and models adjusted for adjuvant treatment (see Tables 5–8). Physical well-being scores were most adversely affected by increased severity of the fatigue–pain–nutritional problems SC (factor 3), consisting of a change in taste, dry mouth, fatigue, back pain, and constipation at T4 (adjusted estimate = –3.54, 95% CI [–4.66, –2.42], p < 0.001). Social well-being (adjusted estimate = –1.71, 95% CI [–2.82, –0.61], p = 0.005); general QOL (FACT-G) (adjusted estimate = –11.65, 95% CI [–15.06, –8.23], p < 0.001); and disease-specific QOL (FACT-Hep) were most negatively affected by increased severity of the mood–insomnia–pain–nausea SC (factor 1), consisting of depression, anxiety, nausea, back pain, abdominal pain/cramping, and trouble sleeping at T4. Emotional well-being scores (adjusted estimate = –3.24, 95% CI [–4.07, –2.41], p < 0.001) were most adversely affected by the mood SC (factor 2) at T1. The insomnia–digestive problems SC consisting of loss of bowel control, trouble digesting food, and trouble sleeping (factor 2) at T2 most negatively affected functional well-being scores (adjusted estimate = –4.16, 95% CI [–5.47, –2.84], p < 0.001).
Increased severity of two SCs three months postoperatively was associated with survival in the unadjusted models. These two SCs were the insomnia–digestive problems SC and nutritional problems SC. Postoperative patients who experienced high severity of the insomnia–digestive problems SC had a 60% higher hazard of death (hazard ratio [HR] = 1.6, 95% CI [1.08, 2.36]) when compared to those with low severity of this SC (p = 0.048). Postoperative patients who experienced high severity of the nutritional problems SC, consisting of weight loss, change in taste, dry mouth and itching, had a 53% higher hazard of death (HR = 1.53, 95% CI [1.06, 2.2]) than those who experienced low severity of this SC (p = 0.048).
A second set of Cox proportional-hazards regression survival models were then constructed adjusting for neoadjuvant therapy, adjuvant therapy, grade of PC, surgery type, and CA 19-9 levels (see Table 9). In these adjusted models, insomnia–digestive problems SC and the nutritional problems SC did not achieve statistical significance (p = 0.149). The magnitude of the HRs between survival and the insomnia–digestive problems SC (HR = 1.64, 95% CI [0.96, 2.81]) and the nutritional problems SC (HR = 1.53, 95% CI [0.91, 2.58]) at three months postoperatively was essentially unchanged.
The TOUS served as a useful framework to examine the relationship between SC severity and influencing factors and clinical outcomes (performance) in resected patients with stage II PC. The TOUS provided a theoretical perspective to conceptualize SCs, determine influencing factors and performance variables to include in this study, and explore the relationships among concepts. Findings from this study provide important insight into the SC experience in patients with PC undergoing surgery.
Physiologic influencing factors: Of the 15 physiologic influencing factors examined, only preoperative pain status was significantly related to a SC. Preoperative pain status has not been previously reported to be an influencing factor for SC occurrence or severity; however, it has been found to be a predictor of reduced survival in patients with PC (Lillemoe et al., 1993) and advanced cancers (Bernhard et al., 2010). These findings are consistent with several studies that failed to find a relationship in cancer populations between SCs and physiologic influencing factors of age, gender, race and ethnicity, comorbid conditions, and type of treatment (Agasi-Idenburg et al., 2017; Kim et al., 2008; Maliski, Kwan, Elashoff, & Litwin, 2008; Noquez, 2008; Tsai, Wu, Chiu, & Chen, 2010). However, Noquez (2008) reported an association between female gender and increased severity of a SC consisting of anxiety, depression, somatization, pain, and fatigue in patients with various cancer types, including PC.
Psychological influencing factors: A history of a mental health disorder, cancer acceptance, and coping were not significantly related to SCs in this study; however, preoperative disease (cancer) worry had a statistically significant relationship with the mood SC (anxiety and depression) at T1. Although the relationship between affective reactions to cancer and SCs has not been previously reported, this finding is not surprising given that increased cancer-related worry has been found to predict depression and anxiety in long-term cancer survivors (Deimling, Bowman, Sterns, Wagner, & Kahana, 2006).
Situational influencing factors: None of the six situational factors examined demonstrated a statistically significant relationship with any of the SCs identified in this study. These findings were consistent with previous research that failed to demonstrate a significant relationship between the identified SCs and social support (So et al., 2009) and marital status (Kim et al., 2009; Maliski et al., 2008). However, Noquez (2008) found that widowed, single, and divorced patients experienced a higher severity of a SC consisting of pain, fatigue, depression, anxiety, and somatization in a large sample of heterogeneous cancer types, including patients with PC. The lack of a significant association between SCs and marital status may also be related to a lack of variability in this study (75% were married or living as married). Previous studies also identified a significant relationship between tobacco use and SCs in patients with lung cancer (Cheville et al., 2011) and head and neck cancers (Xiao et al., 2012). No relationship was noted between tobacco use and SC severity in the current study, which may be because respiratory-related symptoms were not examined.
Clinical Outcomes (Performance)
Quality of life: The current article’s findings suggest a significant relationship between the severity of 13 SCs and disease-specific QOL in patients with stage II PC undergoing surgical resection regardless of type of adjuvant treatment. These findings are consistent with several previous research studies (Ferreira et al., 2008; Franceschini et al., 2013; Pirri et al., 2013; Sanford et al., 2014). The strongest negative association with emotional well-being across all study time points was found with preoperative mood SC (anxiety and depression). The highest prevalence and severity of anxiety and depression occurred in the preoperative period. Therefore, it was not surprising that the mood SC had the strongest relationship to emotional well-being at that time. Several other studies have identified a distinct SC of depression and anxiety (Breen et al., 2009; Cheung, Le, Gagliese, & Zimmermann, 2011); however, none of these studies examined the relationship between this SC and QOL.
Compared to other SCs, the insomnia–digestive problems SC had the strongest negative association with functional well-being scores at T2. The fact that this SC has not been previously identified in the literature is not unexpected given the limited research to date on SCs in patients with PC. Of note is the finding that the unique combination of digestive problems (trouble digesting food and loss of bowel control) and trouble sleeping had a large negative effect on functional well-being. Digestive difficulties are, in part, related to pancreatic enzyme insufficiency preoperatively and postoperatively (Coleman, 2010).
The strongest negative association with social well-being and QOL (general and disease-specific) across all study time points was found with the mood–insomnia–pain–nausea SC at T4. This clustering of symptoms has not been reported in the literature. Of the SCs identified, the mood–insomnia–pain–nausea SC had the strongest negative effect on close personal relationships with friends and family members. Given that family members and friends provide key social support to patients with cancer, it is not surprising that this SC also had the greatest negative relationship with QOL.
Severity of the fatigue–pain–nutritional problems SC had the greatest negative relationship with physical well-being at T4. This distinct SC has not been previously reported in cancer populations. Laird et al. (2011) identified a similar SC consisting of fatigue, pain, and depression associated with reduced physical functioning in a large heterogeneous sample of patients with advanced gastrointestinal, lung, and PC who also experienced cachexia. The relationship identified between physical well-being and the fatigue–pain–nutritional problems SC was not unexpected given that fatigue and pain are the most physically incapacitating symptoms reported by patients with cancer (Hoffman, Given, von Eye, Gift, & Given, 2007; Shute, 2013).
Survival: The current study was the first to explore the prognostic value of SCs over time in patients with stage II PC undergoing surgical resection. SCs identified in this investigation were not found to be significantly associated with overall survival after adjusting for relevant clinical variables. The magnitude of the HR between the insomnia–digestive problems and nutritional problems SCs and survival at T2 were essentially the same in the adjusted and unadjusted models, therefore suggesting that additional study of these relationships is warranted. The absence of a statistically significant association between SCs and survival in patients with PC undergoing surgical resection is not consistent with previous findings in the literature. One possible explanation for lack of statistically significant findings may be the relatively small sample size in the current study. Several studies that controlled for the presence of potentially influencing clinical and demographic factors have found a significant relationship between a greater symptom burden and reduced survival (Teunissen, de Graeff, de Haes, & Voeset, 2006) and that SCs were predictors of decreased survival in cohorts of patients with cancer (Aktas et al., 2012; Wikman et al., 2014).
The main limitations of this study were the limited generalizability of findings related to patient recruitment using convenience sampling techniques from a single high-volume PC center, as well as the lack of sample racial and ethnic diversity and the relatively small sample size.
Implications for Nursing
These findings provide empirical support that may be used to refine the concepts and propositions of the TOUS. SCs are not explicitly included in the TOUS; however, findings from several studies allowed for an expansion of the TOUS’s conceptualization of multiple, concurrent symptoms to include SCs (Fox & Lyon, 2006; Hoffman et al., 2007; Kim et al., 2009). The findings provide additional support for the explicit inclusion of SCs in the TOUS. In addition, increased severity of two SCs were significantly related to physiologic (preoperative pain status) and psychological (cancer-related worry) influencing factors and 13 SCs were significantly related to QOL performance measures, therefore supporting key TOUS propositions.
The findings from this study may be used in oncology nursing practice to enhance the anticipatory guidance and counseling of patients and their family members about what to expect after PC surgery, guide patient and caregiver decision-making regarding treatment options, and inform SC assessment and management in patients with PC undergoing surgical resection. Understanding factors that influence SC severity may assist clinicians in identifying patients at increased risk for experiencing more severe SCs during the postoperative period and help to explain underlying causative SC mechanisms (Kim et al., 2009). Increased attention should be focused on designing management strategies that address clusters rather than isolated symptoms. In addition, understanding the factors that influence the severity of SCs and the SCs associated with poor clinical outcomes may enable clinicians to implement earlier interventions to prevent SCs or reduce their severity, thereby improving QOL and possibly survival outcomes (Sanford et al., 2014).
Several findings from this study have practical applications for current oncology nursing practice. Greater severity of pain and cancer worry during the preoperative period were found to be associated with increased severity of the pain–gastrointestinal SC and mood SC, respectively. These findings underscore the importance of assessing patients for the presence of pain and worry to reduce the severity of or even prevent the presence of SCs in patients prior to surgery. In addition, increased severity of the mood SC, consisting of anxiety and depression, demonstrated a significant association with poor QOL in the current study. This relationship suggests that oncology nursing professionals should also increase attention on screening patients with PC for common affective reactions to cancer, such as anxiety and depression, during the preoperative period. Similarly, given that pain has been found to be an independent predictor of reduced survival (Lillemoe et al., 1993) and that increased severity of several pain-related SCs in this study were associated with poor QOL, it is reasonable to conclude that implementing early, appropriate pain management strategies may improve QOL outcomes in this population.
Increased severity of the insomnia–digestive problems SC and nutritional problems SC demonstrated a significant relationship with QOL. Although the relationship between these SCs and survival did not achieve statistical significance, the trend toward significance is promising. These findings highlight the importance of managing digestive problems and nutrition, which are critical factors in preventing malnutrition and withstanding surgery and subsequent adjuvant therapy in patients beginning at the time of diagnosis. Oncology nurses can play an important role in counseling and educating PC survivors and their caregivers about the importance of adequate nutrition and collaborating with the oncology team in recommending referrals to a nutritional specialist to maximize their QOL and survival potential.
Future research should explore factors that influence SC severity and the effect that SCs have on QOL and survival in patients with PC undergoing surgical resection. The magnitude of the relationship between increased severity of the insomnia–digestive SC and nutritional problems SC and poor survival warrants additional research and clinical awareness by oncology nurses. This study provides a framework for future interprofessional investigations into the role of SCs in QOL and survival in preoperative and postoperative patients with PC.
Findings from this study provide the first data-driven evidence of factors that influence patients’ perceptions of SC severity and the adverse effects of SC severity on QOL and perhaps even survival in patients with stage II PC followed from the time of surgery to nine months after surgical resection. Although causality cannot be determined between the SCs and clinical outcomes in this study, these potentially important associations warrant additional investigation.
About the Author(s)
Sherry A. Burrell, PhD, RN, CNE, is an assistant professor in the M. Louise Fitzpatrick College of Nursing at Villanova University in Pennsylvania; Theresa P. Yeo, PhD, MPH, AOCNP-BC®, is co-director of the Jefferson Pancreas Tumor Registry, a nurse practitioner in the Department of Surgery at Thomas Jefferson University Hospital, and an adjunct professor in the Jefferson College of Nursing at Thomas Jefferson University in Philadelphia, PA; Suzanne C. Smeltzer, EdD, RN, ANEF, FAAN, is a professor in the M. Louise Fitzpatrick College of Nursing and director of the Center for Nursing Research at Villanova University; Benjamin E. Leiby, PhD, BA, is an associate professor and director of the Division of Biostatistics at Thomas Jefferson University; Harish Lavu, MD, is the section chief of hepatopancreatobiliary surgery in the Department of Surgery at Thomas Jefferson University Hospital and an associate professor in the Sidney Kimmel Medical College at Thomas Jefferson University; Eugene P. Kennedy, MD, is the chief medical officer at NewLink Genetics in Philadelphia; and Charles J. Yeo, MD, is a professor in the Sidney Kimmel Medical College at Thomas Jefferson University and chair of the Department of Surgery at Thomas Jefferson University Hospital. This research was funded by a doctoral degree scholarship in cancer nursing awarded to Burrell from the American Cancer Society (DSCN 11-195-01). Burrell has previously received honorarium from the Oncology Nursing Society and Wolters Kluwer for review activities. Leiby has previously consulted for Bayer HealthCare. Burrell, T. Yeo, and Lavu completed the data collection. Leiby provided statistical support. Burrell, T. Yeo, Leiby, Lavu, and C. Yeo provided the analysis. All authors contributed to the conceptualization and design and the manuscript preparation. Burrell can be reached at firstname.lastname@example.org, with copy to ONFEditor@ons.org. (Submitted November 2017. Accepted January 12, 2018.)
Agasi-Idenburg, S.C., Thong, M.S., Punt, C.J., Stuiver, M.M., & Aaronson, N.K. (2017). Comparison of symptom clusters associated with fatigue in older and younger survivors of colorectal cancer. Supportive Care in Cancer, 25, 625–632. https://doi.org/10.1007/s00520-016-3451-4
Aktas, A., Walsh, D., & Rybicki, L. (2012). Symptom clusters and prognosis in advanced cancer. Supportive Care in Cancer, 20, 2837–2843. https://doi.org/10.1007/s00520-012-1408-9
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society, 57, 289–300.
Bernhard, J., Dietrich, D., Glimelius, B., Hess, V., Bodoky, G., Scheithauer, W., & Herrmann, R. (2010). Estimating prognosis and palliation based on tumour marker CA 19-9 and quality of life indicators in patients with advanced pancreatic cancer receiving chemotherapy. British Journal of Cancer, 103, 1318–1324. https://doi.org/10.1038/sj.bjc.6605929
Breen, S.J., Baravelli, C.M., Schofield, P.E., Jefford, M., Yates, P.M., & Aranda, S.K. (2009). Is symptom burden a predictor of anxiety and depression in patients with cancer about to commence chemotherapy? Medical Journal of Australia, 190(Suppl. 7), S99–S104.
Browall, M., Brandberg, Y., Nasic, S., Rydberg, P., Bergh, J., Rydén, A., . . . Wengström, Y. (2017). A prospective exploration of symptom burden clusters in women with breast cancer during chemotherapy treatment. Supportive Care in Cancer, 25, 1423–1429. https://doi.org 10.1007/s00520-016-3527-1
Burrell, S.A., Yeo, T.P., Smeltzer, S.C., Leiby, B.E., Lavu, H., Kennedy, E.P., & Yeo, C.J. (2018). Symptom clusters in patients with pancreatic cancer undergoing surgical resection: Part I [Online exclusive]. Oncology Nursing Forum, 45, E36–E52. https://doi.org/10.1188/ONF.18.E36-E52
Carlson, L.E., Angen, M., Cullum, J., Goodey, E., Koopmans, J., Lamont, L., . . . Bultz, B.D. (2004). High levels of untreated distress and fatigue in cancer patients. British Journal of Cancer, 90, 2297–2304. https://doi.org/10.1038/sj.bjc.6601887
Cheng, K.K., & Lee, D.T. (2011). Effects of pain, fatigue, insomnia, and mood disturbance on functional status and quality of life of elderly patients with cancer. Critical Reviews in Oncology/Hematology, 78, 127–137. https://doi.org/10.1016/j.critrevonc.2010.03.002
Cheung, W.Y., Le, L.W., Gagliese, L., & Zimmermann, C. (2011). Age and gender differences in symptom intensity and symptom clusters among patients with metastatic cancer. Supportive Care in Cancer, 19, 417–423. https://doi.org/10.1007/s00520-010-0865-2
Cheville, A.L., Novotny, P.J., Sloan, J.A., Basford, J.R., Wampfler, J.A., Garces, Y.I., . . . Yang, P. (2011). Fatigue, dyspnea, and cough comprise a persistent symptom cluster up to five years after diagnosis with lung cancer. Journal of Pain and Symptom Management, 42, 202–212. https://doi.org/10.1016/j.jpainsymman.2010.10.257
Coleman, J. (2010). Diarrhea. In C.G. Brown (Ed.), A guide to oncology symptom management (pp. 173–195). Pittsburgh, PA: Oncology Nursing Society.
Deimling, G.T., Bowman, K.F., Sterns, S., Wagner, L.J., & Kahana, B. (2006). Cancer-related health worries and psychological distress among older adult, long-term cancer survivors. Psycho-Oncology, 15, 306–320. https://doi.org/10.1002/pon.955
Dirksen, S.R., Belyea, M.J., Wong, W., & Epstein, D.R. (2016). Transitions in symptom cluster subgroups among men undergoing prostate cancer radiation therapy. Cancer Nursing, 39, 3–11. https://doi.org/10.1097/NCC.0000000000000236
Dodd, M.J., Miaskowski, C., & Lee, K.A. (2004). Occurrence of symptom clusters. Journal of the National Cancer Institute Monographs, 32, 76–78. https://doi.org/10.1093/jncimonographs/lgh008
Dong, S.T., Costa, D.S., Butow, P.N., Lovell, M.R., Agar, M., Velikova, G., . . . Fayers, P.M. (2016). Symptom clusters in advanced cancer patients: An empirical comparison of statistical methods and the impact on quality of life. Journal of Pain and Symptom Management, 51, 88–98. https://doi.org/10.1016/j.jpainsymman.2015.07.013
Ferreira, K.A., Kimura, M., Teixeira, M.J., Mendoza, T.R., da Nóbrega, J.C., Graziani, S.R., & Takagaki, T.Y. (2008). Impact of cancer-related symptom synergisms on health-related quality of life and performance status. Journal of Pain and Symptom Management, 35, 604–16. https://doi.org/10.1016/j.jpainsymman.2007.07.010
Fox, S.W., & Lyon, D.E. (2006). Symptom cluster and quality of life in survivors of lung cancer. Oncology Nursing Forum, 33, 931–936. https://doi.org/10.1188/06.ONF.931-936
Franceschini, J., Jardim, J.R., Fernandes, A.L., Jamnik, S., & Santoro, I.L. (2013). Relationship between the magnitude of symptoms and the quality of life: A cluster analysis of lung cancer patients in Brazil. Jornal Brasileiro de Pneumologia, 39, 23–31.
Gorsuch, R.L. (1983). Factor analysis (2nd ed.). Manwah, NJ: Lawrence Erlbaum Associates.
Heffernan, N., Cella, D., Webster, K., Odom, L., Martone, M., Passik, S., . . . Blumgart, L. (2002). Measuring health-related quality of life in patients with hepatobiliary cancers: The Functional Assessment of Cancer Therapy–Hepatobiliary questionnaire. Journal of Clinical Oncology, 20, 2229–2239. https://doi.org/10.1200/JCO.2002.07.093
Hoffman, A.J., Given, B.A., von Eye, A., Gift, A.G., & Given, C.W. (2007). Relationships among pain, fatigue, insomnia, and gender in persons with lung cancer. Oncology Nursing Forum, 34, 785–792. https://doi.org/10.1188/07.ONF.785-792
Huang, J., Gu, L., Zhang, L., Lu, X., Zhuang, W., & Yang Y. (2016). Symptom clusters in ovarian cancer patients with chemotherapy after surgery: A longitudinal survey. Cancer Nursing, 39, 106–116. https://doi.org/10.1097/NCC.0000000000000252
Huang, J.J., Yeo, C.J., Sohn, T.A., Lillemoe, K.D., Sauter, P.K., Coleman, J., . . . Cameron, J.L. (2000). Quality of life and outcomes after pancreaticoduodenectomy. Annals of Surgery, 231, 890–898.
Kim, E., Jahan, T., Aouizerat, B.E., Dodd, M.J., Cooper, B.A., Paul, S.M., . . . Miaskowski, C. (2009). Changes in symptom clusters in patients undergoing radiation therapy. Supportive Care in Cancer, 17, 1383–1391. https://doi.org/10.1007/s00520-009-0595-5
Kim, H.J., Barsevick, A.M., & Tulman, L. (2009). Predictors of the intensity of symptoms in a cluster in patients with breast cancer. Journal of Nursing Scholarship, 41, 158–165. https://doi.org/10.1111/j.1547-5069.2009.01267.x.
Kim, H.J., Barsevick, A.M., Tulman, L., & McDermott, P.A. (2008). Treatment-related symptom clusters in breast cancer: A secondary analysis. Journal of Pain and Symptom Management, 36, 468–479. https://doi.org/10.1016/j.jpainsymman.2007.11.011
Kim, H.J., McGuire, D.B., Tulman, L. & Barsevick, A.M. (2005). Symptom clusters: Concept analysis and clinical implications for cancer nursing. Cancer Nursing, 28, 270–282.
Knobf, M.T., Cooley, M.E., Duffy, S., Doorenbos, A., Eaton, L., Given, B., . . . Mallory, G. (2015). The 2014–2018 Oncology Nursing Society research agenda. Oncology Nursing Forum, 42, 450–465. https://doi.org/10.1188/15.ONF.450-465
Laird, B.J., Scott, A.C., Colvin, L.A, McKeon, A.L., Murray, G.D., Fearon, K.C., & Fallon, M.T. (2011). Pain, depression, and fatigue as a symptom cluster in advanced cancer. Journal of Pain and Symptom Management, 42, 1–11. https://doi.org/10.1016/j.jpainsymman.2010.10.261
Lavu, H., Lengel, H.B., Sell, N.M., Baiocco, J.A., Kennedy, E.P., Yeo, T.P., . . . Yeo, C.J. (2015). A prospective, randomized, double-blind, placebo controlled trial on the efficacy of ethanol celiac plexus neurolysis in patients with operable pancreatic and periampullary adenocarcinoma. Journal of the American College of Surgeons, 220, 497–508. https://doi.org/10.1016/j.jamcollsurg.2014.12.013
Lenz, E.R., Pugh, L.C., Milligan, R.A., Gift, A.G., & Suppe, F. (1997). The middle-range Theory of Unpleasant Symptoms: An update. Advances in Nursing Science, 19(3), 14–27.
Lillemoe, K.D., Cameron, J.L., Kaufman, H.S., Yeo, C.J., Pitt, H.A., & Sauter, P.K. (1993). Chemical splanchnicectomy in patients with unresectable pancreatic cancer. A prospective randomized trial. Annals of Surgery, 217, 447–455.
Lin, S., Chen, Y., Yang, L., & Zhou, J. (2013). Pain, fatigue, disturbed sleep and distress comprised a symptom cluster that related to quality of life and functional status of lung cancer surgery patients. Journal of Clinical Nursing, 22, 1281–1290. https://doi.org/10.1111/jocn.12228
Maliski, S.L., Kwan, L., Elashoff, D., & Litwin, M.S. (2008). Symptom clusters related to treatment for prostate cancer. Oncology Nursing Forum, 35, 786–793. https://doi.org/10.1188/08.ONF.786-793
Nakai, M., & Ke, W. (2011). Review of the methods for handling missing data in longitudinal data analysis. International Journal of Mathematical Analysis, 5, 1–13.
Nho, J.H., Reul Kim, S., & Nam, J.H. (2017). Symptom clustering and quality of life in patients with ovarian cancer undergoing chemotherapy. European Journal of Oncology Nursing, 30, 8–14. https://doi.org/10.1016/j.ejon.2017.07.007
Noquez, A.E. (2008). Cancer-related symptom clusters (Doctoral dissertation). Retrieved from ProQuest Dissertation and Theses Database (Publication No. AAT 3314979).
Pirri, C., Bayliss, E., Trotter, J., Olver, I.N., Katris, P., Drummond, P., & Bennett, R. (2013). Nausea still the poor relation in antiemetic therapy? The impact on cancer patients’ quality of life and psychological adjustment of nausea, vomiting and appetite loss, individually and concurrently as part of a symptom cluster. Supportive Care in Cancer, 21, 735–748. https://doi.org/10.1007/s00520-012-1574-9
Reyes-Gibby, C.C., Aday, L.A., Anderson, K.O., Mendoza, T.R., & Cleeland, C.S. (2006). Pain, depression, and fatigue in community-dwelling adults with and without a history of cancer. Journal of Pain and Symptom Management, 32, 118–128. https://doi.org/10.1016/j.jpainsymman.2006.01.008
Reyes-Gibby, C.C., Chan, W., Abbruzzese, J.L., Xiong, H.Q., Ho, L., Evans, D.B., . . . Crane, C. (2007). Patterns of self-reported symptoms in pancreatic cancer patients receiving chemoradiation. Journal of Pain and Symptom Management, 34, 244–252. https://doi.org/10.1016/j.jpainsymman.2006.11.007
Sanford, S.D., Beaumont, J.L., Butt, Z., Sweet, J.J., Cella, D., & Wagner, L.I. (2014). Prospective longitudinal evaluation of a symptom cluster in breast cancer. Journal of Pain and Symptom Management, 47, 721–730. https://doi.org/10.1016/j.jpainsymman.2013.05.010
Shute, C. (2013). The challenges of cancer pain assessment and management. Ulster Medical Journal, 82, 40–42.
So, W.K., Marsh, G., Ling, W.M., Leung, F.Y., Lo, J.C., Yeung, M., & Li, G.K. (2009). The symptom cluster of fatigue, pain, anxiety, and depression and the effect on the quality of life of women receiving treatment for breast cancer: A multicenter study [Online exclusive]. Oncology Nursing Forum, 36, E205–E214. https://doi.org/10.1188/09.ONF.E205-E214
Sullivan, C.W., Leutwyler, H., Dunn, L.B., Cooper, B.A., Paul, S.M., Levine, J.D., . . . Miaskowski, C.A. (2018). Stability of symptom clusters in patients with breast cancer receiving chemotherapy. Journal of Pain and Symptom Management, 55, 39–55. https://doi.org/10.1016/j.jpainsymman.2017.08.008
Sun, V., Ferrell, B., Juarez, G., Wagman, L.D., Yen, Y., & Chung, V. (2008). Symptom concerns and quality of life in hepatobiliary cancers [Online exclusive]. Oncology Nursing Forum, 35, E45–E52. https://doi.org/10.1188/08.ONF.E45-E52
Teunissen, S.C., de Graeff, A., de Haes, H.C., & Voest, E.E. (2006). Prognostic significance of symptoms of hospitalized advanced cancer patients. European Journal of Cancer, 42, 2510–2516. https://doi.org/10.1016/j.ejca.2006.05.025
Tsai, J.S., Wu, C.H., Chiu, T.Y., & Chen, C.Y. (2010). Significance of symptom clustering in palliative care of advanced cancer patients. Journal of Pain and Symptom Management, 39, 655–662. https://doi.org/10.1016/j.jpainsymman.2009.09.005
Wikman, A., Johar, A., & Lagergren, P. (2014). Presence of symptom clusters in surgically treated patients with esophageal cancer: Implications for survival. Cancer, 120, 286–293
Xiao, C., Hanlon, A., Zhang, Q., Ang, K., Rosenthal, D.I., Nguyen-Tan, P.F., . . . Bruner, D.W. (2012). Symptom clusters in patients with head and neck cancer receiving concurrent chemoradiation. Oral Oncology, 49, 360–366. https://doi.org/10.1016/j.oraloncology.2012.10.004
Yeo, T.P., Burrell, S.A., Sauter, P.K., Kennedy, E.P., Lavu, H., Leiby, B.E., & Yeo, C.J. (2012). A progressive postresection walking program significantly improves fatigue and health-related quality of life in pancreas and periampullary cancer patients. Journal of the American College of Surgeons, 214, 463–475. https://doi.org/10.1016/j.jamcollsurg.2011.12.017
Zabora, J., BrintzenhofeSzoc, K., Curbow, B., Hooker, C., & Piantadosi, S. (2001). The prevalence of psychosocial distress by cancer site. Psycho-Oncology, 10, 19–28.
Zucca, A.C., Boyes, A.W., Linden, W., & Girgris, A. (2012). All’s well that ends well? Quality of life and physical symptom clusters in long-term cancer survivors across cancer types. Journal of Pain and Symptom Management, 43, 720–731.