Stomach Dose-Volume Predicts Acute Gastrointestinal Toxicity in Chemoradiotherapy for Locally Advanced Pancreatic Cancer.

AIMS: Gastrointestinal toxicity impedes dose escalation in chemoradiotherapy for hepatobiliary malignancies. Toxicity risk depends on clinical and radiotherapy metrics. We aimed to identify predictive factors using data from two prospective phase II clinical trials of locally advanced pancreatic cancer (LAPC). MATERIALS AND METHODS: Ninety-one patients with available data from the ARCII (59.4 Gy in 33 fractions with gemcitabine, cisplatin and nelfinavir, n = 23) and SCALOP (50.4 Gy in 28 fractions with capecitabine or gemcitabine, n = 74) trials were studied. The independent variables analysed comprised age, sex, performance status, baseline symptoms, tumour size, weight loss, chemotherapy regimen and dose-volume histogram of stomach and duodenum in 5 Gy bins. The outcome measures used were Common Terminology Criteria of Adverse Events (CTCAE) grade and risk of CTCAE grade ≥2 acute upper gastrointestinal toxicity (anorexia, pain, nausea and/or vomiting). The risk of CTCAE grade ≥2 events was modelled using multivariable logistic regression and prediction of severity grade using ordinal regression. RESULTS: CTCAE grade ≥2 symptoms occurred in 38 patients (42%). On univariate analysis, stomach V35-45Gy was predictive of risk (odds ratio 1.035, 95% confidence interval 1.007-1.063) and grade (1.023, 1.003-1.044) of toxicity. The area under the curve was 0.632 (0.516-0.747) with toxicity risk 33/66 (50%) above and 5/25 (20%) below the optimal discriminatory threshold (7.1 cm3). Using a threshold of 30 cm3, risk was 13/20 (65%) versus 25/71 (35%). The optimal multivariable logistic regression model incorporated patient sex, chemotherapy regimen and stomach V35-45Gy. Receiving gemcitabine rather than capecitabine (odds ratio 3.965, 95% confidence interval 1.274-12.342) and weight loss during induction chemotherapy (1.216, 1.043-1.419) were significant predictors for the SCALOP cohort, whereas age predicted toxicity risk in ARCII only (1.344, 1.015-1.780). Duodenum dose-volume did not predict toxicity risk or severity in any cohort. CONCLUSIONS: In chemoradiotherapy for LAPC the volume of stomach irradiated to a moderately high dose (35-45 Gy) predicts the incidence and severity of acute toxicity. Other predictive factors can include age, sex, recent weight loss and concomitant chemotherapy agents.

The Impact of Cardiac Radiation Dosimetry on Survival After Radiation Therapy for Non-Small Cell Lung Cancer.

PURPOSE: The heart receives high radiation doses during radiation therapy of advanced-stage lung cancer. We have explored associations between overall survival, cardiac radiation doses, and electrocardiographic (ECG) changes in patients treated in IDEAL-CRT, a trial of isotoxically escalated concurrent chemoradiation delivering tumor doses of 63 to 73 Gy. METHODS AND MATERIALS: Dosimetric and survival data were analyzed for 78 patients. The whole heart, pericardium, AV node, and walls of left and right atria (LA/RA-Wall) and ventricles (LV/RV-Wall) were outlined on radiation therapy planning scans, and differential dose-volume histograms (dDVHs) were calculated. For each structure, dDVHs were approximated using the average dDVH and the 10 highest-ranked structure-specific principal components (PCs). ECGs at baseline and 6 months after radiation therapy were analyzed for 53 patients, dichotomizing patients according to presence or absence of "any ECG change" (conduction or ischemic/pericarditis-like change). All-cause death rate (DR) was analyzed from the start of treatment using Cox regression. RESULTS: 38% of patients had ECG changes at 6 months. On univariable analysis, higher scores for LA-Wall-PC6, Heart-PC6, "any ECG change," and larger planning target volume (PTV) were significantly associated with higher DR (P=.003, .009, .029, and .037, respectively). Heart-PC6 and LA-Wall-PC6 represent larger volumes of whole heart and left atrial wall receiving 63 to 69 Gy. Cardiac doses ≥63 Gy were concentrated in the LA-Wall, and consequently Heart-PC6 was highly correlated with LA-Wall-PC6. "Any ECG change," LA-Wall-PC6 scores, and PTV size were retained in the multivariable model. CONCLUSIONS: We found associations between higher DR and conduction or ischemic/pericarditis-like changes on ECG at 6 months, and between higher DR and higher Heart-PC6 or LA-Wall-PC6 scores, which are closely related to heart or left atrial wall volumes receiving 63 to 69 Gy in this small cohort of patients.

3D calculation of radiation-induced second cancer risk including dose and tissue response heterogeneities.

PURPOSE: Tools for comparing relative induced second cancer risk, to inform choice of radiotherapy treatment plan, are becoming increasingly necessary as the availability of new treatment modalities expands. Uncertainties, in both radiobiological models and model parameters, limit the confidence of such calculations. The aim of this study was to develop and demonstrate a software tool to produce a malignant induction probability (MIP) calculation which incorporates patient-specific dose and allows for the varying responses of different tissue types to radiation. METHODS: The tool has been used to calculate relative MIPs for four different treatment plans targeting a subtotally resected meningioma: 3D conformal radiotherapy (3DCFRT), volumetric modulated arc therapy (VMAT), intensity-modulated x-ray therapy (IMRT), and scanned protons. RESULTS: Two plausible MIP models, with considerably different dose-response relationships, were considered. A fractionated linear-quadratic induction and cell-kill model gave a mean relative cancer risk (normalized to 3DCFRT) of 113% for VMAT, 16% for protons, and 52% for IMRT. For a linear no-threshold model, these figures were 105%, 42%, and 78%, respectively. The relative MIP between plans was shown to be significantly more robust to radiobiological parameter uncertainties compared to absolute MIP. Both models resulted in the same ranking of modalities, in terms of MIP, for this clinical case. CONCLUSIONS: The results demonstrate that relative MIP is a useful metric with which treatment plans can be ranked, regardless of parameter- and model-based uncertainties. With further validation, this metric could be used to discriminate between plans that are equivalent with respect to other planning priorities.