TY - JOUR
T1 - Network analysis of the multidimensional symptom experience of oncology
AU - Papachristou, Nikolaos
AU - Barnaghi, Payam
AU - Cooper, Bruce
AU - Kober, Kord M.
AU - Maguire, Roma
AU - Paul, Steven M.
AU - Hammer, Marilyn
AU - Wright, Fay
AU - Armes, Jo
AU - Furlong, Eileen P.
AU - McCann, Lisa
AU - Conley, Yvette P.
AU - Patiraki, Elisabeth
AU - Katsaragakis, Stylianos
AU - Levine, Jon D.
AU - Miaskowski, Christine
PY - 2019/2/19
Y1 - 2019/2/19
N2 - Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis (NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients’ symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network.
AB - Oncology patients undergoing cancer treatment experience an average of fifteen unrelieved symptoms that are highly variable in both their severity and distress. Recent advances in Network Analysis (NA) provide a novel approach to gain insights into the complex nature of co-occurring symptoms and symptom clusters and identify core symptoms. We present findings from the first study that used NA to examine the relationships among 38 common symptoms in a large sample of oncology patients undergoing chemotherapy. Using two different models of Pairwise Markov Random Fields (PMRF), we examined the nature and structure of interactions for three different dimensions of patients’ symptom experience (i.e., occurrence, severity, distress). Findings from this study provide the first direct evidence that the connections between and among symptoms differ depending on the symptom dimension used to create the network. Based on an evaluation of the centrality indices, nausea appears to be a structurally important node in all three networks. Our findings can be used to guide the development of symptom management interventions based on the identification of core symptoms and symptom clusters within a network.
KW - oncology patients
KW - network analysis
KW - core symptoms
KW - Pairwise Markov Random Fields (PMRF)
UR - http://www.scopus.com/inward/record.url?scp=85061808131&partnerID=8YFLogxK
UR - https://www.nature.com/srep
U2 - 10.1038/s41598-018-36973-1
DO - 10.1038/s41598-018-36973-1
M3 - Article
SN - 2045-2322
VL - 9
JO - Scientific Reports
JF - Scientific Reports
M1 - 2258
ER -