Contemporaneous symptom networks analysis in lymphoma patients during chemotherapy: protocol for a single-centre prospective cross-sectional study

Introduction

Lymphoma, a type of malignant solid tumour, arises from lymphoid tissues and has emerged as a prevalent form of cancer posing a significant threat to human health. According to the data published by the China National Cancer Center1 and the American Cancer Society,2 there has been a rising trend in the incidence of lymphoma in recent years. The incidence of lymphoma currently ranks eighth among all malignant tumours in China.3 4 Globally, lymphoma ranks as the 8th most common tumour among males and the 10th most common tumour among females.5 While there exist many treatment options for lymphoma patients, chemotherapy remains the primary method of treatment.

Lymphoma patients commonly experience a variety of symptoms, such as nausea, vomiting, loss of appetite, hair loss, fatigue, pain and numbness in the hands and feet, during chemotherapy. In addition to physical discomfort, the complexity, severity and recurrent nature of lymphoma often lead to serious psychological symptoms including anxiety, fear, depression and sadness.6 7 Several studies6 8 9 have reported that most lymphoma patients would experience more than ten symptoms simultaneously or successively during chemotherapy, and these symptoms would produce more negative effects through reinforcement or synergistic effects, thereby seriously affecting the quality of life of the patients. At the same time, the survival period of the patients would be shortened. Hence, the effective management of these symptoms holds particular importance.

Symptom clusters are groups of two or more stable and interrelated symptoms, with stronger correlations observed between symptoms within the same cluster compared with those between different clusters. Each symptom cluster is relatively independent.10 Previous studies have usually managed the symptoms of lymphoma patients in the form of symptom clusters. Researchers have identified 3–7 symptom clusters during chemotherapy in lymphoma patients.7 8 11 However, the number and composition of these clusters vary, and the mechanisms of interaction between symptoms remain unclear. As a consequence, the efficacy and precision of existing symptom management strategies for lymphoma patients are compromised. The existence of multiple symptom clusters in a patient requires the administration of several sets of pharmacological or non-pharmacological interventions, without prioritisation based on the severity or impact of each symptom cluster. In addition, further research on symptom management in cancer patients in recent years has found that cancer symptoms occur in a nested pattern as opposed to distinct clusters.12 13 Therefore, relying solely on symptom clusters for symptom management in lymphoma patients undergoing chemotherapy no longer meets the rigorous standards of modern medicine for efficiency and precision. The optimisation of existing symptom management strategies remains a pressing issue to be solved.

The symptom network analysis involves collectively characterising the disease-related symptoms of a patient and quantitatively studying the network structure, nodes, network indicators, as well as the interrelations between different symptoms using complex network analysis. Contemporaneous symptom networks refer to the symptom networks constructed from the symptoms of the same patient group at a specific measurement time point.14 This method can reflect the mechanisms of interaction and complex relationships among the various symptoms experienced by patients in the real world.15 16 For example, Cramer et al17 constructed a contemporaneous network of 1059 patients with major depressive disorder and generalised anxiety disorder, revealing overlaps in symptoms of sleep disturbances and psychomotor disturbances. Meanwhile, the most influential symptoms in the symptom network can be identified, the core and bridge symptoms can be clarified, and the impact of core symptoms on other symptoms can be discovered, thereby determining specific targets for symptom intervention.18 Targeting core symptoms for intervention treatment can accelerate the deactivation of the network and improve the individualisation and precision of symptom intervention.19 For example, Zhu et al20 constructed a contemporaneous network of 2927 HIV-positive patients and found that the incidence and severity of 16 HIV-related psychological symptoms decreased with the increasing duration of HIV positivity. However, the total connectivity density of the network increased, suggesting that the longer the duration of HIV positivity, the more fragile the patient’s psyche and the easier it would be to activate the other symptoms quickly through one psychological symptom. In a study by Liu et al,21 the anxiety and depression contemporaneous symptom networks of 2016 HIV-infected individuals were analysed, and they found that ‘feeling unhappy’ and ‘feeling fidgety’ were the key bridges connecting the depression and anxiety symptom clusters. This indicates that in managing HIV-infected patients with concurrent anxiety and depression symptoms, attention should be paid to their symptoms of ‘feeling unhappy’ and ‘feeling fidgety’, so as to prevent the anxiety and depression symptom clusters from exacerbating each other. In addition, nurses can predict the prognosis of patients with different characteristics (disease stage, disease type, chemotherapy stage and chemotherapy regimen) based on the density of the symptom network. For instance, a cross-sectional study conducted by Zhu et al22 including 1065 cancer survivors compared the network densities of cancer survivors with different survival times and found that the network density among patients with a survival time of more than 5 years was notably lower compared with those with a survival time of less than 5 years, indicating a more significant difference than observed in symptom severity. A cohort study involving 465 adolescents with depression conducted by Schweren et al23 found that network density could be used as a predictor of longer disease duration. Such information holds important mechanistic implications for devising effective intervention strategies.

Currently, contemporaneous symptom network studies have focused on patients with AIDS,24 psychiatric and psychological disorders,25 26 digestive system tumours,27 multiple myeloma,28 breast cancer,29 as well as head and neck cancer.30 Contemporaneous symptom network during chemotherapy in lymphoma patients remains to be further explored. Therefore, the General Data Questionnaire and Lymphoma Symptom Assessment scale will be hereby employed to conduct a cross-sectional survey of symptoms (incidence, severity, frequency and distress) in lymphoma patients during chemotherapy. The study will be primarily conducted to construct a contemporaneous symptom network in lymphoma patients during chemotherapy, analyse the network centrality indexes, explore the core symptoms within the network and delve into the relationship between symptoms. Overall, these attempts could forge a scientific and reliable theoretical basis for constructing a precise symptom management plan and reducing the symptom burden in lymphoma patients during chemotherapy.