Lung stereotactic ablative radiotherapy (SABR): dosimetric considerations for chest wall toxicity

OBJECTIVE: To investigate chest wall pain in patients with peripheral early stage lung cancer treated with stereotactic ablative radiotherapy (SABR), and to identify factors predictive of Common Terminology Criteria of Adverse Events Grade 2 + chest wall pain. METHODS: Patients who received 55 Gy in five fractions were included. A chest wall structure was retrospectively defined on planning scans, and chest wall dosimetry and tumour-related factors recorded. Logistic regression was performed to identify factors predictive of ≥Grade 2 chest wall pain. RESULTS: 182 patients and 187 tumours were included. There were 20 (10.9%) episodes of ≥Grade 2 chest wall pain. Multivariate logistic regression demonstrated that the maximum dose received by 1 cm3 of chest wall (Dmax1 cm3) and tumour size were significant predictors of ≥Grade 2 chest wall pain [Dmax1 cm3 odds ratio : 1.104, 95% confidence interval : 1.012–1.204, p = 0.025; tumour size (mm) odds ratio : 1.080, 95% confidence interval : 1.026–1.136, p = 0.003]. This model was an adequate fit to the data (Hosmer and Lemeshow test non-significant) and a fair discriminator for chest wall pain (area under receiver-operating characteristic curve: 0.74). Using the multivariate logistic regression model, parameters for Dmax1 cm3 are provided, which predict <10% and <20% risks of ≥Grade 2 chest wall pain for different tumour sizes. CONCLUSION: Grade 2+ chest wall pain is an uncommon side effect of lung SABR. Larger tumour size and increasing Dmax1 cm3 are significant predictors of ≥Grade 2 chest wall pain. When planning lung SABR, it is prudent to try to avoid hot volumes in the chest wall, particularly for larger tumours. ADVANCES IN KNOWLEDGE: This article demonstrates that Grade 2 or greater chest wall pain following lung SABR is more common when the tumour is larger in size and the Dmax1 cm3 of the chest wall is higher. When planning lung SABR, the risk of chest wall pain may be reduced if maximum doses are minimized, particularly for larger tumours

Decipher identifies men with otherwise clinically favorable-intermediate risk disease who may not be good candidates for active surveillance

BackgroundWe aimed to validate Decipher to predict adverse pathology (AP) at radical prostatectomy (RP) in men with National Comprehensive Cancer Network (NCCN) favorable-intermediate risk (F-IR) prostate cancer (PCa), and to better select F-IR candidates for active surveillance (AS).MethodsIn all, 647 patients diagnosed with NCCN very low/low risk (VL/LR) or F-IR prostate cancer were identified from a multi-institutional PCa biopsy database; all underwent RP with complete postoperative clinicopathological information and Decipher genomic risk scores. The performance of all risk assessment tools was evaluated using logistic regression model for the endpoint of AP, defined as grade group 3-5, pT3b or higher, or lymph node invasion.ResultsThe median age was 61 years (interquartile range 56-66) for 220 patients with NCCN F-IR disease, 53% classified as low-risk by Cancer of the Prostate Risk Assessment (CAPRA 0-2) and 47% as intermediate-risk (CAPRA 3-5). Decipher classified 79%, 13% and 8% of men as low-, intermediate- and high-risk with 13%, 10%, and 41% rate of AP, respectively. Decipher was an independent predictor of AP with an odds ratio of 1.34 per 0.1 unit increased (p value = 0.002) and remained significant when adjusting by CAPRA. Notably, F-IR with Decipher low or intermediate score did not associate with significantly higher odds of AP compared to VL/LR.ConclusionsNCCN risk groups, including F-IR, are highly heterogeneous and should be replaced with multivariable risk-stratification. In particular, incorporating Decipher may be useful for safely expanding the use of AS in this patient population