Functional and biologic metrics for predicting radiation pneumonitis in locally advanced non-small cell lung cancer patients treated with chemoradiotherapy

• Autores: Dongqing Wang, Jingyu Zhu, J. Sun, Baosheng Li, Zhongtang Wang, Lei Wei, Yong Yin, Hongfu Sun, Zheng Fu, Xingguo Zhang, Zongwei Huo
• Localización: Clinical & translational oncology, ISSN 1699-048X, Vol. 14, Nº. 12, 2012, págs. 943-952
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Objective To study the predictive value of functional and biologic metrics for predicting radiation pneumonitis (RP) in locally advanced non-small cell lung cancer (LANSCLC) patients treated with chemoradiotherapy.

    Methods Between March 2006 and April 2010, 57 LANSCLC patients were enrolled in a prospective study. Fusion of SPECT and computed tomography scans provides perfusion-weighted functional dose�volume histogram (DVH) and associated functional dosimetric parameters. Blood for serum biomarkers�interleukin-6 (IL-6), transforming growth factor-beta1, and superoxide dismutase (SOD)�was drawn pre-RT and then 40 Gy/4 weeks during the treatment. The incidence of RP was related to the functional and biologic metrics. The predictability of predictors was calculated and compared based on the area under receiver-operating characteristic (ROC) curve (AUC).

    Results Relative volumes of functional lung receiving more than a threshold dose of 5�50 Gy at increments of 5 Gy and elevated levels of serum SOD after delivery of 40 Gy/4 weeks were associated with RP (p < 0.05). The best predictive efficacy of SOD was observed for a cutoff value of 56 U/ml, with a sensitivity of 0.80 (95 % CI 0.28�0.99) and a specificity of 0.67 (95 % CI 0.43�0.65) (p = 0.040). Functional DVH provided better predictive outcome (AUC 0.76�0.98) than standard DVH (AUC 0.62�0.86) for patients with poor baseline lung function.

    Conclusion Functional metrics were identified to be better predictors for RP in patients with poor baseline lung function. SOD seemed to be a potential predictor for RP; however, it will need to be further verified using a larger sample size.