Cancer nursing · 2026
Association of Inflammation-Related Biomarkers With Symptom Burden Subgroups in Patients With Gastrointestinal Cancers: A Latent Profile Analysis.
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Li Jianxin, Wu Xinyu, Yang Yiting, Dong Yajun, Wang Teng, Teng Liping
Аннотация
BACKGROUND: Patients with gastrointestinal (GI) cancers often face a high symptom burden, which may be closely linked to systemic inflammation. However, the heterogeneity of symptom burden and its association with inflammation-related biomarkers remains unclear.
OBJECTIVE: The aim of this study was to identify subgroups of symptom burden among patients with GI cancers, examine their heterogeneity, and explore potential associations with inflammation-related biomarkers.
METHODS: This cross-sectional study included 522 patients with GI cancers who completed the Memorial Symptom Assessment Scale. Inflammation-related biomarker data were calculated from blood laboratory measurements. Latent profile analysis was used to identify different subgroups of symptom burden. Binary logistic regression assessed the associations between high symptom burden and inflammation-related biomarkers. Receiver operating characteristic curve analysis evaluated their predictive performance.
RESULTS: Two symptom burden profiles were identified: low and high. Patients in the high symptom burden subgroup were more likely to lack medical insurance and have colon or rectal cancer. The platelet-to-lymphocyte ratio (PLR) and the prognostic nutritional index (PNI) were independently associated with high symptom burden, with areas under the curve of 0.714 and 0.734, respectively, and optimal cutoffs of 103.97 and 36.66.
CONCLUSION: Patients with GI cancers exhibited 2 distinct subgroups in symptom burden. Inflammation-related biomarkers, such as PLR and PNI, demonstrated independent predictive value for identifying patients with a high symptom burden.
IMPLICATIONS FOR PRACTICE: Identifying PLR and PNI as predictors of high symptom burden can aid early screening and risk stratification. Their incorporation into clinical assessments may promote targeted symptom management and personalized care for patients with GI cancers.
OBJECTIVE: The aim of this study was to identify subgroups of symptom burden among patients with GI cancers, examine their heterogeneity, and explore potential associations with inflammation-related biomarkers.
METHODS: This cross-sectional study included 522 patients with GI cancers who completed the Memorial Symptom Assessment Scale. Inflammation-related biomarker data were calculated from blood laboratory measurements. Latent profile analysis was used to identify different subgroups of symptom burden. Binary logistic regression assessed the associations between high symptom burden and inflammation-related biomarkers. Receiver operating characteristic curve analysis evaluated their predictive performance.
RESULTS: Two symptom burden profiles were identified: low and high. Patients in the high symptom burden subgroup were more likely to lack medical insurance and have colon or rectal cancer. The platelet-to-lymphocyte ratio (PLR) and the prognostic nutritional index (PNI) were independently associated with high symptom burden, with areas under the curve of 0.714 and 0.734, respectively, and optimal cutoffs of 103.97 and 36.66.
CONCLUSION: Patients with GI cancers exhibited 2 distinct subgroups in symptom burden. Inflammation-related biomarkers, such as PLR and PNI, demonstrated independent predictive value for identifying patients with a high symptom burden.
IMPLICATIONS FOR PRACTICE: Identifying PLR and PNI as predictors of high symptom burden can aid early screening and risk stratification. Their incorporation into clinical assessments may promote targeted symptom management and personalized care for patients with GI cancers.