Introduction
Ovarian cancer is the fifth most common cause of gynecologic cancer-related death in women (Torre et al., 2018). The incidence of ovarian cancer has increased over the last decade in China, with 52,100 new cases and 22,500 cancer-related deaths in 2015 (Chen et al., 2016). Given that the anatomical location of the ovary is hidden, more than 70% of patients with ovarian cancer are diagnosed at an advanced stage, together with abdominal metastasis (Moore et al., 2019). Despite the availability of effective therapies, the prognosis of patients with ovarian cancer is still poor, with a 5-year survival rate of only 29%, thus posing a serious threat to women's health (Siegel et al., 2018).
The National Comprehensive Cancer Network guidelines recommend ovary and fallopian tube removal as an initial treatment for patients with ovarian cancer at International Federation of Gynecology and Obstetrics Stage I and/or low invasive carcinoma, and debulking surgery as the primary treatment modality for patients at International Federation of Gynecology and Obstetrics Stages II-IV (Morgan et al., 2016). Besides, adjuvant therapy, especially chemotherapy, has been used to reduce the recurrence rate and improve the survival rate of patients with ovarian cancer (O'Donnell et al., 2018). These patients often present with more than one symptom, including severe fatigue, sadness, depression, nausea, pain, vomiting, weight loss, and change in body appearance during and after chemotherapy (Cortez et al., 2018; Hwang et al., 2016). A symptom cluster is defined as two or more symptoms that occur simultaneously and are closely associated with each other (Dodd et al., 2001). In comparison with a single symptom, the symptoms within and among clusters may exert synergistic and intensifying effects (Hadi et al., 2008). The consequence of symptom clusters is not simply the cumulative effect of single symptoms but rather a doubling trend, which may eventually affect patients' quality of life (QoL), functional status, and prognosis (Ore et al., 2017; Smith et al., 2018).
Previous studies have reported that patients with ovarian cancer continuously experience somatization symptoms such as weight loss, pain, fatigue, sleep disturbance, and emotional distress as well as difficulties in resuming work and interpersonal relationships after diagnosis (Cheung et al., 2009; Fox & Lyon, 2007; Tsai et al., 2010). Furthermore, ovarian cancer survivors may experience treatment-related symptoms after surgery such as dry mouth, urination pain, and abdominal discomfort (Kim et al., 2018). Huang et al. (2016) designed a longitudinal study to investigate 111 patients with ovarian cancer at four time points during chemotherapy and ultimately identified six symptom clusters (i.e., pain-related, psychological, menopausal, gastrointestinal, body image, and peripheral neurologic symptoms). It has been reported that patients' health status and their demographic/clinical factors explained only 10%-25% of the variance in QoL. However, the inclusion of more symptoms may affect QoL by 15%-41% in patients with ovarian cancer (Fox & Lyon, 2007). In addition, these symptoms may appear at different time points. For example, somatization symptoms and psychological symptoms may exist before treatment (Huang et al., 2016), treatment-related symptoms and body image symptoms typically occur after surgery, and peripheral neurologic symptoms and gastrointestinal symptoms may present in the early and middle stages of chemotherapy (Nho et al., 2017).
Patients with ovarian cancer often bear the burden of various symptoms caused by disease progression, treatment-related side effects, and long-term outcomes (Kim et al., 2018). The importance of the various types of symptom distress in patients with ovarian cancer differs at different stages of the treatment, and the occurrence of symptoms reveals stage-specific characteristics (Ferrell et al., 2003). Most studies of ovarian-cancer-related symptoms in patients have focused on a specific time point during treatment (Ore et al., 2017; Smith et al., 2018), especially for patients with specific disease stage and different age distribution (Kim et al., 2018). However, only a few longitudinal studies have been conducted in China to assess the symptoms of patients with ovarian cancer before surgery, after surgery, and at the initial stage of chemotherapy. Symptom clusters are often viewed as a dynamic construct (Hadi et al., 2008), and diverse symptoms have been found in patients with ovarian cancer who have received active treatment regimens such as surgery and chemotherapy (Kim et al., 2018). To evaluate the symptoms present at different treatment stages of ovarian cancer and to develop appropriate treatment-stage-related interventions for the most common and clinically important symptom clusters, it is necessary to validate the reported symptom clusters at different treatment stages and determine whether these symptoms hold true across the entire patient population.
Purpose
The aims of this longitudinal study were as follows: (a) identify the general and disease-related characteristics of patients with ovarian cancer; (b) determine the incidence and severity of symptoms in patients with ovarian cancer at three different time points, namely, 3 days before surgery (T1), 2 days after surgery (T2), and the first day after the completion of chemotherapy cycle 1 (T3); and (c) explore the components and dynamic evolution of symptom clusters in patients with ovarian cancer at T1, T2, and T3.
Methods
Study Design
A quantitative research approach and a longitudinal survey design guided by the Strengthening the Reporting of Observational Studies in Epidemiology checklist were used.
Sample and Setting
A convenience sampling strategy was used to recruit patients with ovarian cancer from one tertiary hospital in China from March 2016 to March 2018. Four hundred thirty patients were qualified under the following selection criteria: (a) aged >= 18 years; (b) diagnosed with primary ovarian cancer; (c) treatment plan of surgery combined with chemotherapy; (d) able to read Chinese characters and/or communicate in Chinese; (e) able to complete the scale evaluation; (f) no disease recurrence at the time of enrollment; (g) not treated using radiotherapy, biotherapy, or other adjuvant treatment; and (h) willing to participate in this study. Data from 56 participants were unavailable for analysis, as 29 had dropped out at T2 because of transfer to an intensive care unit or unwillingness to continue participation and 27 had dropped out at T3 because of transfer to an intensive care unit, death, radiotherapy treatment, or unwillingness to continue participation. Thus, 374 participants completed T1-T3, giving a withdrawal rate of 13.02%. Statistical analysis showed no significant differences in demographic and disease-related data between the patients who had completed the study and those who had been lost to follow-up.
Measures
Clinical and demographic information sheets were designed by the researchers, which included age, marital status, educational level, employment status, monthly income, medical payment status, cancer stage, and pathological type.
The symptom scales of the M. D. Anderson Symptom Inventory (MDASI) module for use in patients with ovarian cancer (MDASI-OC) were employed to identify the symptom clusters in the sample. The 27-item MDASI-OC is a reliable and specific tool with three subscales: MDASI core items designed to evaluate the severity of generic cancer-related symptoms (13), ovarian-cancer-specific items designed to assess the severity of ovarian cancer symptoms (8), and interference items designed to determine the impact of ovarian cancer symptoms on activity of daily living (6). Each of the symptoms was scored between 0 and 10, with 0 indicating "not present" and 10 indicating "as bad as you can imagine," with higher scores indicating higher levels of symptom perception. The interference items were also scored between 0 and 10, with 0 indicating "no interference" and 10 indicating "complete interference" (Sailors et al., 2013). The Cronbach's [alpha] coefficients of the 13 MDASI core items, eight ovarian-cancer-specific module items, and six interference items were .89, .88, and .84, respectively, in this study.
Ethical Considerations
This study was approved by the ethics committee of the West China Second University Hospital, Sichuan University (Approval No. 2019071). All of the patients provided written informed consent before enrollment.
Procedures
A longitudinal survey method was used in this quantitative research. Patients with ovarian cancer who met the inclusion criteria were invited to participate. The purpose and significance of this study were introduced, and written informed consent was obtained from all participants before enrollment. To increase the credibility of the longitudinal survey, three research assistants were assigned to conduct face-to-face interviews. Questionnaires were distributed and collected at the three aforementioned time points: T1, T2, and T3. The reason for selecting the first day after the completion of Chemotherapy Cycle 1 as the third data collection time point was based on the actual clinical situation, as patients in the survey hospital are regularly scheduled for discharge on the second day after the end of chemotherapy. All of the research assistants received unified training. The questionnaires were designed to be filled out by the participants. For those unable to complete the questionnaires on their own, the research assistants assisted by reading the neutral, nonsuggestive words item by item.
Data Analyses
Statistical analysis was conducted using SPSS Version 17.0 (SPSS, Inc., Chicago, IL, USA). The demographic characteristics, clinical characteristics, and severity ratings for the symptoms of patients with ovarian cancer were presented as frequencies, percentages, means, and standard deviations. The extraction of symptom clusters was performed using exploratory factor analysis (EFA; Kaiser, 1974). Before conducting the EFA, the Kaiser-Meyer-Olkin (KMO) test was carried out to evaluate the adequacy of the sample size (p > .50 indicates sufficient samples for factor analysis; Kaiser, 1974). The principal component method and maximum variance orthogonal rotation were performed, and a Bartlett spherical test was used as the applicability test (p < .05 indicates the model is a unit matrix). The extracted factors should conform to the following principles: (a) characteristic value is > 1, (b) coefficient conforms to Cartel's "steep step" test principle, and (c) each factor must consist of at least two projects with a project factor loading value > .40 (Kaiser, 1974).
Results
Demographic and Disease-Related Characteristics
The 430 initially enrolled participants had a mean age of 49.02 (SD = 10.71) years, ranging from 18 to 68 years. Most were married (n = 385, 89.5%), were unemployed (n = 295, 68.6%), and had completed a junior high school education (n = 141, 32.8%). Nearly half (n = 194, 45.1%) reported earning a family income of 1,001-3,000 RMB per month, and most were covered by health insurance (n = 412, 95.8%). Ovarian cancer stage III (n = 146, 34.0%) was the most common pathological diagnosis, and the most frequently observed pathological type was serous adenocarcinoma (n = 186, 43.3%). All of the demographic and disease-related characteristics are presented in Table 1.
Occurrence Rates and Severity Ratings of Symptom Clusters
The symptoms of the participants were investigated at T1, T2, and T3, and the symptoms with an occurrence rate >20% ranged from 13 to 21. Before surgery, the top five symptoms within the occurrence rate were distress, sadness, pain, sleep disturbance, and fatigue, and the mean scores for symptom severity ranged from 1.45 (SD = 1.03) to 6.67 (SD = 2.75). After 3 days of surgery, the top five symptoms within the occurrence rate were pain, feeling bloated, pain in abdomen, fatigue, and sadness, and the mean scores for symptom severity ranged from 2.15 (SD = 1.16) to 7.13 (SD = 3.13). After the first cycle of chemotherapy, all of the symptoms were present, with the top five symptoms within the occurrence rate including sadness, nausea, sleep disturbance, fatigue, and distress and a mean symptom severity score range of 1.45 (SD = 0.48) to 6.98 (SD = 2.89). Of particular note, fatigue and sadness both appeared in the top five symptoms lists for all three time points. Further details are given in Table 2.
Symptom Clusters Before Surgery
The 13 symptoms identified in the 430 participants were analyzed using EFA (occurrence rate >= 20%). Symptom clusters were extracted using principal component analysis and maximum variance orthogonal rotation. On the basis of the results of KMO = .826 and Bartlett test p < .001, a positive correlation was identified among the variables, showing the suitability of the data for factor analysis. The numbers of factors was determined using eigenvalues. Four of the factors had eigenvalues > 1.00, and the cumulative variance contribution rate was 51.47%. Factor 1, named the pain-related symptom cluster, included back pain, pain in the abdomen, pain, and disturbed sleep. Factor 2, named the emotional symptom cluster, included feeling sad, being distressed, and fatigue. Factor 3, named the cognitive symptom cluster, included attention problems, difficulty remembering, and feeling drowsy. Factor 4, named the disease-related symptom cluster, included leg cramps/leg muscle pain, shortness of breath, and urinary urgency. The Cronbach's [alpha] coefficients of the four symptom clusters were .82, .81, .77, and .80, respectively (Table 3).
Symptom Clusters After 3 Days of Surgery
As presented in Table 4, data from 401 patients were analyzed, with 16 symptoms obtained and five factors extracted at T2 (KMO = .795; Bartlett test, p < .001), accounting for 58.32% of the total variance. At this stage, a new symptom cluster, named the treatment-related symptom cluster, emerged, encompassing feeling bloated, dry mouth, and pain/burning during urination. The Cronbach's [alpha] coefficients of pain-related, emotional, cognitive, disease-related, and treatment-related symptom clusters were found to be .80, .79, .81, .76, and .81, respectively.
Symptom Clusters After the First Cycle of Chemotherapy
As presented in Table 5, data from 374 participants were analyzed, 21 symptoms were obtained, and six factors were extracted at T3 (KMO = .812; Bartlett test, p < .001), accounting for 61.19% of the total variance. At this stage, a new symptom cluster, named the gastrointestinal symptom cluster, emerged, encompassing vomiting, nausea, constipation, and lack of appetite. Numbness was categorized into the treatment-related symptom cluster based on the factor-loading cutoff values. In addition, the factor loading of disturbed sleep was greater than .4 in both pain-related and treatment-related clusters. Considering the close relationship between disturbed sleep and pain related to both the disease and surgical procedure, this variable, rather than being eliminated, was categorized into the pain-related cluster with a higher factor loading. The Cronbach's [alpha] coefficients of pain-related, emotional, cognitive, disease-related, treatment-related, and gastrointestinal symptom clusters were .83, .82, .78, .79, .80, and .85, respectively.
Symptom Clusters Across Time Points
Altogether, the findings indicate that six symptom clusters, including pain-related, emotional, cognitive, disease-related, treatment-related, and gastrointestinal symptom clusters, were identified at three time points. Of these, the pain-related, emotional, cognitive, and disease-related symptom clusters were perceived by the participants at T1 and continued through T2 and T3. The treatment-related symptom cluster, which was closely associated with surgical treatment, was found at T2 and continued through T3. The symptom of numbness and the gastrointestinal symptom cluster, which are both closely associated with chemotherapy, were observed initially at T3. The symptom clusters with the highest severities at T1, T2, and T3 were emotional, treatment-related, and gastrointestinal symptom clusters, respectively. Among the symptom clusters at different time points, the participants experienced most from emotional symptoms (see Table 6 for details).
Discussion
Six factors were successfully identified using EFA. Moreover, the results showed the existence of stable symptom clusters that were independent of both pathological type and treatment stage, which is a finding consistent with previous studies (Huang et al., 2016; Lopez et al., 2011). The occurrence of symptom clusters at T2 and T3 may be attributable to the effects of surgery and chemotherapy or to the progression of ovarian cancer.
The symptoms in Factor 1, including back pain, abdominal pain, chronic pain, and sleep disturbance, all were associated with the pain-related cluster. This symptom cluster was present before surgery and persisted through the first cycle of chemotherapy, with a severity that was highest at T1 and lowest at T3. However, other studies elicited slightly different results (Hwang et al., 2016; Matzka et al., 2018; Nho et al., 2017). For instance, Hwang et al. (2016) categorized pain into the fatigue-pain symptom cluster along with lack of energy, fatigue, difficulty in concentrating, nausea, and change in appetite. Moreover, the fatigue-pain symptom cluster reported by Matzka et al. (2018) for patients with cancer contained other symptoms such as tiredness, shortness of breath, lack of energy, and depressed mood. Hypoproteinemia, associated with preoperative consumptive cachexia such as ascites, tissue edema, and visceral fascial swelling, may lead to pain and related symptoms (Cham et al., 2019). Moreover, pain-related factors such as postoperative intestinal adhesion, tissue scar contracture, and secondary ureteral obstruction caused by ureteral injury may have also contributed to the increase in pain symptom cluster severity at T1 and T2 in this study. The severity of the pain-related cluster after the first cycle of chemotherapy was lower than that at baseline, which may be attributed to the therapeutic effects of cytoreductive surgery and adjuvant chemotherapy (Nho et al., 2017).
Factor 2 was termed as the emotional symptom cluster, which involved feeling sad, being distressed, and experiencing fatigue. Patients with ovarian cancer may experience negative emotions such as anxiety, sadness, and inferiority complex, mainly attributable to the postsurgical deformities in female reproductive organs and decrease in estrogen level after ovariectomy (Bodurka-Bevers et al., 2000; Stewart et al., 2001). The highest severity in this cluster was observed at T3, likely because of the 75% rate of ovarian cancer recurrence after surgery and chemotherapy (Bonhof et al., 2018) and because patients at this stage are most worried about their disease prognosis. Furthermore, patients are also worried about the possible influence of ovariectomy on their sexual life (Mayer et al., 2019). Chemotherapy-related side effects such as loss of appetite, nausea, vomiting, and hair loss may increase the psychological burden of patients with ovarian cancer. It should be noted that fatigue symptoms were, based on the results of the factor analysis, included in the emotional symptom cluster (rather than the disease-related or treatment-related symptom clusters) across the three time points. In addition, fatigue was judged by the participants' subjective experiences in the physical and psychological realms. Yu et al. (2016) pointed out that long-term negative emotions such as sadness, anxiety, and depression may lead to persistent fatigue. Notably, sadness may encourage patients into a state of inactivity, resulting in physical and mental exhaustion as well as a lack of energy, whereas anxiety may place patients in a state of stress, which, in turn, may reduce their ability to focus on and solve problems and thus elicit experiences of mental fatigue.
Symptoms in Factor 3 such as attention problems, feeling drowsy, and memory difficulties were classified under the cognitive symptom cluster. This cluster presented before surgery and was more severe at T3 than T2. Patients' experience of cognitive problems may be related to excessive sadness and depression before surgery (Ramirez-Mahaluf et al., 2018). The stage of postoperative chemotherapy initiation in this cluster may be related to low estrogen levels. After an ovariectomy, estrogen levels in a patient with ovarian cancer typically drop sharply, whereas pituitary function elevates to a level of hyperactivity concurrent with high gonadotropin secretion and autonomic nerve dysfunction, resulting in a range of mild to severe symptoms such as inattention and forgetfulness (Huang et al., 2016). In addition, cancer-related fatigue may be another important factor affecting cognitive problems (VAN Vulpen et al., 2020). Before surgery, tumor cells produce somatostatin as well as interleukin-2 and interleukin-6, which may hinder normal metabolism in cells, leading to anemia, cachexia, infection, and other clinical symptoms (Veni et al., 2019). Furthermore, surgery and chemotherapy may contribute directly to cancer-related fatigue. Zargar-Shoshtari et al. (2009) reported that patients experienced frequent cancer-related fatigue after receiving major colonic surgery. O'Regan et al. (2019) showed that 74.8% of participants had a high incidence of cancer-related fatigue after receiving chemotherapy.
In Factor 4, the disease-related symptom cluster, involving leg muscle aches/cramping, shortness of breath, and urinary urgency, was identified. The components of this cluster were relatively consistent across the entire treatment process. Moreover, severity in the disease-related symptom cluster was slightly increased at T2 and T3. When ovarian function is impaired, the levels of estrogen decrease sharply, and consequently, autonomic dysfunction may manifest with numerous clinical symptoms such as urinary urgency, flush, shortness of breath, and sweating (Peng et al., 2015). In addition, prolonged bed rest after surgery may result in leg muscle aches/cramping. As a commonly used chemotherapy drug for ovarian cancer, paclitaxel has been shown to potentially damage myocardial cells and induce cardiotoxicity, leading to palpitations, chest tightness, and shortness of breath (Brain et al., 2019). In Factor 4, the occurrence rate and severity of urinary urgency were 65.34% and 4.78, respectively, and remained high at all the three time points. These values were relatively higher than the findings of Sailors et al. (2013), which found these values to be 45.0% and 1.8, respectively, in a sample of 128 patients with ovarian, peritoneal, and fallopian tube cancer with members who either had received or were not receiving surgery and chemotherapy. This may be attributed to the fact that the highest incidence and severity of urinary urgency in this study occurred 2 days after surgery. At this time, most of the patients had just removed their urinary catheter, and their bladder function was in the recovery stage, which may be an explanatory factor of urinary urgency. However, in Sailors et al., the treatment stage and method were not restricted, and the patients may have had preoperative or postoperative urinary catheterization for a prolonged period, which allowed for the restoration of their bladder function.
Symptoms in Factor 5 such as feeling bloated, dry mouth, and pain/burning with urination were categorized into the treatment-related symptom cluster. Moreover, numbness was classified in the factor analysis as a treatment-related symptom at T3, which differs from clinical considerations. In this cluster, the incidence of feeling bloated and pain/burning with urination was highest at T2 and lowest at T3, which is supported by the increased and decreased severity of this cluster at T2 and T3, respectively. These results were in good agreement with another study that included dry mouth and pain/burning with urination into the treatment-related symptom cluster (Sailors et al., 2013). Given that urethral mucosal impairment is caused by preoperative catheterization and possible urinary tract infection resulting from the indwelling catheter, clinicians may anticipate intense treatment-related urinary symptoms in patients with ovarian cancer (Xie et al., 2020). After abdominal operation, fasting and intestinal function recovery may also lead to abdominal distention and dry mouth as well as increased risk of urinary tract infection. The symptoms of abdominal distention and dry mouth often occur in patients with gastrointestinal mucosal barrier dysfunction after treatment with chemotherapeutic regimens (Huang et al., 2016).
The gastrointestinal symptom cluster was identified in Factor 6, which included lack of appetite, constipation, nausea, and vomiting. The components of this cluster occurred at the first cycle of chemotherapy, as reported in previous studies (Huang et al., 2016). Chemotherapeutics induce the release of 5-HT3 from small intestinal chromaffin cells through the cortical pathway and trigger vagus nerve excitation through the 5-HT3 receptor, leading to poor appetite, nausea, and vomiting (Poon et al., 2014). In addition, chemotherapy-related nausea, vomiting, and poor appetite tend to present simultaneously (Huang et al., 2016). Among those symptoms, the incidence and severity of nausea and vomiting were highest at T3, and the overall score for the components of this symptom cluster was much higher than that reported in a previous study (Kim et al., 2018). It is worth noting that tumor-targeting drugs, which usually cause fewer side effects, are not covered by health insurance in China. Therefore, most patients who are unemployed or earn a low family monthly income (i.e., 1,001-3,000 RMB) are likely to opt for more affordable treatments, which are associated with higher risks of adverse effects.
Limitations of This Research
Several limitations are associated with this study. First, only patients with ovarian cancer recruited from a single obstetrics and gynecology center in Southwest China were investigated. Hence, the findings may not be representative of the entire country. Second, the assessment of symptom cluster addressed three time points only (before surgery, postsurgery, and after Chemotherapy Cycle 1). Thus, posttreatment symptom experiences were not explored. Third, because of the clinical situation in the target hospital, the third data collection point was the first day after completion of Chemotherapy Cycle 1. This may lead to a lack of representativeness in the research results. Fourth, this study excluded patients with recurrent ovarian cancer. Therefore, more studies should be conducted to explore whether there are any differences in symptom clusters that exist between primary and recurrent patients with ovarian cancer.
Conclusions
The findings of this study indicate that the symptom clusters perceived by patients with ovarian cancer are dynamic, in which the pain-related, emotional, cognitive, and disease-related symptom clusters occur at T1 and persist through T2 and T3; the treatment-related symptom cluster emerges at T2 and persists through T3; and the numbness symptom and gastrointestinal symptom clusters emerge at T3. Therefore, symptom management interventions should be prioritized based on the most-severe symptom clusters, including the emotional symptom cluster at T1, the treatment-related symptom cluster at T2, and the gastrointestinal symptom cluster at T3.
Implications for Practice
This work is particularly important for clinical nurses providing care to patients with ovarian cancer because of the high mortality associated with this disease. Targeted interventions tailored to the different stages of symptom clusters may improve QoL in patients with ovarian cancer. Several targeted intervention strategies were proposed. (a) Among the four symptom clusters at T1 (before surgery), the emotional symptom cluster was identified as most severe. Psychological counseling should be provided effectively by clinical nurses during the early stage of ovarian cancer. It has been reported that strengthening social support and rebuilding self-confidence may reduce the psychological burden of patients (Ramkisson et al., 2017). Besides, nurses should provide disease- and treatment-related knowledge to help patients better understand their health conditions. In addition, cognitive behavioral therapies such as progressive muscle relaxation training and art therapy may help patients manage their emotions and promote mental well-being (Lebowitz et al., 2019). (b) At T2, the treatment-related symptom cluster earned the highest severity score of the five clusters, and the feeling of being bloated was identified as the most common symptom. The concept of fast-track surgery should be effectively established in the mind of nurses, and nurses should encourage early postoperative activities by instructing patients to watch videos or participate in field teaching to help them restore their intestinal functions and relieve abdominal distention. Moreover, the frequency and severity of urinary urgency were at their most severe at this stage. For post-catheter-removal patients experiencing frequent urination, nurses may apply abdominal hot compresses, acupuncture, or moxibustion to help alleviate related symptoms (Zhong et al., 2019). Angelini (2017) claimed that pelvic floor muscle training also has good effect. (c) Among the six clusters at T3, the gastrointestinal symptom cluster had the greatest severity. Notably, the incidence and severity of nausea, vomiting, constipation, and poor appetite were highest at this stage. Particular attention must be given to these phenomena, and nursing interventions such as psychological care, dietary guidance, and aerobic exercise should be provided to patients with ovarian cancer. Furthermore, secondary or triple antiemetic regimens should be implemented routinely according to vomiting score classification to reduce the incidence of chemotherapy-related gastrointestinal symptoms.
Acknowledgments
This study was supported by the Science and Technology Project of the Health Planning Committee of Sichuan (No. 20PJ083). The authors gratefully acknowledge the supervisors of the hospitals and the 430 patients who volunteered to participate in this study as well as the experts and members of the group for their help and advice.
Author Contributions
Study conception and design: YH, XD
Data collection: XD, YT, LZ, JD
Data analysis and interpretation: XD, YT
Drafting of the article: XD
Critical revision of the article: YT, YH
References