Predicting esophagitis after chemoradiation therapy for non-small cell lung cancer: an individual patient data...

Concurrent chemoradiation therapy (CCRT) improves survival compared with sequential treatment for locally advanced non-small cell lung cancer, but it increases toxicity, particularly radiation esophagitis (RE). Validated predictors of RE for clinical use are lacking. We performed an individual-patient-data meta-analysis to determine factors predictive of clinically significant RE.

After a systematic review of the literature, data were obtained on 1082 patients who underwent CCRT, including patients from Europe, North America, Asia, and Australia. Patients were randomly divided into training and validation sets (2/3 vs 1/3 of patients). Factors predictive of RE (grade≥2 and grade≥3) were assessed using logistic modeling, with the concordance statistic (c statistic) used to evaluate the performance of each model.

The median radiation therapy dose delivered was 65 Gy, and the median follow-up time was 2.1 years. Most patients (91%) received platinum-containing CCRT regimens. The development of RE was common, scored as grade 2 in 348 patients (32.2%), grade 3 in 185 (17.1%), and grade 4 in 10 (0.9%). There were no RE-related deaths. On univariable analysis using the training set, several baseline factors were statistically predictive of RE (P<.05), but only dosimetric factors had good discrimination scores (c>.60). On multivariable analysis, the esophageal volume receiving ≥60 Gy (V60) alone emerged as the best predictor of grade≥2 and grade≥3 RE, with good calibration and discrimination. Recursive partitioning identified 3 risk groups: low (V60<0.07%), intermediate (V60 0.07% to 16.99%), and high (V60≥17%). With use of the validation set, the predictive model performed inferiorly for the grade≥2 endpoint (c=.58) but performed well for the grade≥3 endpoint (c=.66).

Clinically significant RE is common, but life-threatening complications occur in <1% of patients. Although several factors are statistically predictive of RE, the V60 alone provides the best predictive ability. Efforts to reduce the V60 should be prioritized, with further research needed to identify and validate new predictive factors.