Early lesion-specific 18F-FDG PET response to chemotherapy predicts time to lesion progression in locally advanced non-small cell lung cancer

Research output: Contribution to journalJournal articleResearchpeer-review

BACKGROUND AND PURPOSE: We hypothesize that the lesion-to-lesion variability in FDG-PET response after one cycle of chemotherapy for NSCLC in an individual patient may inform radiation dose redistribution. To test this hypothesis, we investigate if time to lesion-progression in patients with multiple lesions is dependent on lesion-specific response to chemotherapy.

MATERIALS AND METHODS: We analyzed 81 patients with 184 lesions referred to curative chemo-radiotherapy for NSCLC 2010-2012. (18)F-FDG PET scans were performed at diagnosis and after one series of chemotherapy. Response of each lesion was assessed as the change in FDG peak standardized uptake value. Variance of lesion response was compared within and between patients. Time to progression for each lesion was analyzed using the Kaplan-Meier method and the Cox proportional hazards model.

RESULTS: Within-patient variability in lesion responses was of the same magnitude as the between-patient variability. Lesion-specific time to progression was longer in lesions with a better response (log-rank p=0.038). Nodal lesions had a much lower risk of progression than T-site lesions (HR=0.09, p<0.0001).

CONCLUSIONS: Recording an overall patient response involves a loss of biological information on heterogeneity between lesions. Poor lesion-specific response after one cycle chemotherapy may identify lesions that would benefit from an individualized radiotherapy strategy.

Original languageEnglish
JournalRadiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Issue number3
Pages (from-to)460-464
Number of pages5
Publication statusPublished - Mar 2016

    Research areas

  • Adult, Aged, Aged, 80 and over, Carcinoma, Non-Small-Cell Lung, Chemoradiotherapy, Disease Progression, Female, Fluorodeoxyglucose F18, Humans, Lung Neoplasms, Male, Middle Aged, Positron-Emission Tomography, Proportional Hazards Models, Radiopharmaceuticals, Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't

ID: 179168731