2022
DOI: 10.1016/j.radonc.2022.01.026
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Establishment and validation of a recursive partitioning analysis based prognostic model for guiding re-radiotherapy in locally recurrent nasopharyngeal carcinoma patients

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Cited by 4 publications
(4 citation statements)
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“…In the present study, multivariate analysis showed that age ≥ 60 years, recurrence interval ≤ 2 years, plasma EBV DNA level > 0 copy/mL, and advanced recurrent T stage were independent predictors of mortality. This result is consistent with previous studies 14 , 29 - 31 . Sun et al found age, hypertension, relapsed T stage, and EBV DNA level to be independent prognostic factors 32 .…”
Section: Discussionsupporting
confidence: 94%
“…In the present study, multivariate analysis showed that age ≥ 60 years, recurrence interval ≤ 2 years, plasma EBV DNA level > 0 copy/mL, and advanced recurrent T stage were independent predictors of mortality. This result is consistent with previous studies 14 , 29 - 31 . Sun et al found age, hypertension, relapsed T stage, and EBV DNA level to be independent prognostic factors 32 .…”
Section: Discussionsupporting
confidence: 94%
“… 23 A total of 531 patients were included to conduct and validate a prognostic model based on a recursive partitioning analysis that divided patients into 3 groups. 36 Salvage RT could benefit rNPC patients in the low- and intermediate-risk groups, while not in the high-risk group. In this study, a predictive model for screening patients who could benefit from salvage RT was developed.…”
Section: Discussionmentioning
confidence: 99%
“…Several models have been constructed for the treatment stratification of patients. 22 , 35 37 A validated salvage radiotherapy outcome score was proposed that identified a low-score subgroup of the female sex, who had previous RT-induced grade 3 and higher-grade late toxicities, and suboptimal performance status. They had a significantly better survival benefit after receiving palliative CT alone than receiving salvage RT.…”
Section: Discussionmentioning
confidence: 99%
“…Variables that demonstrated observably significance in the multivariate analysis were included in a risk stratification model for OS using RPA. The RPA was used to select the best node in each split to get the best patient groups in each step, based on classification and regression tree (CART) analysis [ 23 ]. Each subgroup would be subsequently split into smaller groups until a specified stopping criterion is reached or further divisions could no longer be made.…”
Section: Methodsmentioning
confidence: 99%