Literature DB >> 19147245

The importance of patient characteristics for the prediction of radiation-induced lung toxicity.

Cary Dehing-Oberije1, Dirk De Ruysscher, Angela van Baardwijk, Shipeng Yu, Bharat Rao, Philippe Lambin.   

Abstract

PURPOSE: Extensive research has led to the identification of numerous dosimetric parameters as well as patient characteristics, associated with lung toxicity, but their clinical usefulness remains largely unknown. We investigated the predictive value of patient characteristics in combination with established dosimetric parameters. PATIENTS AND METHODS: Data from 438 lung cancer patients treated with (chemo)radiation were used. Lung toxicity was scored using the Common Toxicity Criteria version 3.0. A multivariate model as well as two single parameter models, including either V(20) or MLD, was built. Performance of the models was expressed as the AUC (Area Under the Curve).
RESULTS: The mean MLD was 13.5 Gy (SD 4.5 Gy), while the mean V(20) was 21.0% (SD 7.3%). Univariate models with V(20) or MLD both yielded an AUC of 0.47. The final multivariate model, which included WHO-performance status, smoking status, forced expiratory volume (FEV(1)), age and MLD, yielded an AUC of 0.62 (95% CI: 0.55-0.69).
CONCLUSIONS: Within the range of radiation doses used in our clinic, dosimetric parameters play a less important role than patient characteristics for the prediction of lung toxicity. Future research should focus more on patient-related factors, as opposed to dosimetric parameters, in order to identify patients at high risk for developing radiation-induced lung toxicity more accurately.

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Year:  2009        PMID: 19147245     DOI: 10.1016/j.radonc.2008.12.002

Source DB:  PubMed          Journal:  Radiother Oncol        ISSN: 0167-8140            Impact factor:   6.280


  29 in total

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