OBJECTIVES: To analyze survival outcomes in patients with oropharygeal cancer treated with primary intensity modulated radiotherapy (IMRT) using decision tree algorithms. METHODS: A total of 273 patients with newly diagnosed oropharyngeal cancer were identified between March 2010 and December 2016. The data set contained nine predictor variables and a dependent variable (overall survival (OS) status). The open-source R software was used. Survival outcomes were estimated by Kaplan-Meier method. Important explanatory variables were selected using the random forest approach. A classification tree that optimally partitioned patients with different OS rates was then built. RESULTS: The 5 year OS for the entire population was 78.1%. The top three important variables identified were HPV status, N stage and early complete response to treatment. Patients were partitioned in five groups on the basis of these explanatory variables. CONCLUSION: The proposed classification tree could help to guide future research in oropharyngeal cancer field. ADVANCES IN KNOWLEDGE: Decision tree method seems to be an appropriate tool to partition oropharyngeal cancer patients.

Analyzing oropharyngeal cancer survival outcomes: a decision tree approach / De Felice, F.; Humbert-Vidan, L.; Lei, M.; King, A.; Guerrero Urbano, T.. - In: BRITISH JOURNAL OF RADIOLOGY. - ISSN 0007-1285. - 93:1111(2020). [10.1259/bjr.20190464]

Analyzing oropharyngeal cancer survival outcomes: a decision tree approach

De Felice F.
Primo
;
2020

Abstract

OBJECTIVES: To analyze survival outcomes in patients with oropharygeal cancer treated with primary intensity modulated radiotherapy (IMRT) using decision tree algorithms. METHODS: A total of 273 patients with newly diagnosed oropharyngeal cancer were identified between March 2010 and December 2016. The data set contained nine predictor variables and a dependent variable (overall survival (OS) status). The open-source R software was used. Survival outcomes were estimated by Kaplan-Meier method. Important explanatory variables were selected using the random forest approach. A classification tree that optimally partitioned patients with different OS rates was then built. RESULTS: The 5 year OS for the entire population was 78.1%. The top three important variables identified were HPV status, N stage and early complete response to treatment. Patients were partitioned in five groups on the basis of these explanatory variables. CONCLUSION: The proposed classification tree could help to guide future research in oropharyngeal cancer field. ADVANCES IN KNOWLEDGE: Decision tree method seems to be an appropriate tool to partition oropharyngeal cancer patients.
2020
adult; aged; aged, 80 and over; decision trees; female; fluorodeoxyglucose F18; humans; Kaplan-Meier estimate; magnetic resonance imaging; male; middle aged; oropharyngeal neoplasms; papillomavirus infections; positron emission tomography computed tomography; radiopharmaceuticals; radiotherapy, intensity-modulated; retrospective studies; squamous cell carcinoma of head and neck; treatment outcome
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Analyzing oropharyngeal cancer survival outcomes: a decision tree approach / De Felice, F.; Humbert-Vidan, L.; Lei, M.; King, A.; Guerrero Urbano, T.. - In: BRITISH JOURNAL OF RADIOLOGY. - ISSN 0007-1285. - 93:1111(2020). [10.1259/bjr.20190464]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1556416
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