Validity and reliability of the simplified Chinese patient-reported outcomes version of the common terminology criteria for adverse events

Dosiomics Risk Model for Predicting Radiation Induced Temporal Lobe Injury and Guiding Individual Intensity-Modulated Radiation Therapy

PURPOSE

We aimed to assess the value of dose distribution-based dosiomics and planning computed tomography-based radiomics to predict radiation-induced temporal lobe injury (TLI) and guide individualized intensity modulated radiation therapy.

METHODS AND MATERIALS

A total of 5599 nasopharyngeal carcinoma patients were enrolled, including 2503, 1072, 988, and 1036 patients in the training, validation, prospective test, and external test cohorts, respectively. The concordance index (C-index) was used to compare the performance of the radiomics and dosiomics models with that of the quantitative analyses of normal tissue effects in the clinic and Wen's models. The predicted TLI-free survival rates of redesigned simulated plans with the same dose-volume histogram but different dose distributions for same patient in a cohort of 30 randomly selected patients were compared by the Wilcoxon matched-pairs signed-rank test.

RESULTS

The radiomics and dosiomics signatures were constructed based on 30 selected computed tomography features and 10 selected dose distribution features, respectively, which were important predictors of TLI-free survival (all P <.001). However, the radiomics signature had a low C-index. The dosiomics risk model combining the dosiomics signature, D_1cc, and age had favorable performance, with C-index values of 0.776, 0.811, 0.805, and 0.794 in the training, validation, prospective test, and external test cohorts, respectively, which were better than those of the quantitative analyses of normal tissue effects in the clinic model and Wen's model (all P <.001). The dosiomics risk model can further distinguish patients in a same risk category divided by other models (all P <.05). Conversely, the other models were unable to separate populations classified by the dosiomics risk model (all P > .05). Two simulated plans with the same dose-volume histogram but different dose distributions had different TLI-free survival rates predicted by dosiomics risk model (all P ≤ .002).

CONCLUSIONS

The dosiomics risk model was superior to traditional models in predicting the risk of TLI. This is a promising approach to precisely predict radiation-induced toxicities and guide individualized intensity modulated radiation therapy.

GSTP1 c.313A > G mutation is an independent risk factor for neutropenia hematotoxicity induced by anthracycline-/paclitaxel-based chemotherapy in breast cancer patients

Background

The link between glutathione S-transferase P1 (GSTP1) c.313A > G polymorphism and chemotherapy-related adverse events remains controversial. The goal of this study was to assess how this variant affected the toxicity of anthracycline-/paclitaxel-based chemotherapy in patients with breast cancer.

Methods

This study retrospectively investigated pharmacogenetic associations of GSTP1 c.313A > G with chemotherapy-related adverse events in 142 breast cancer patients who received anthracycline and/or paclitaxel chemotherapy.

Results

There were 61 (43.0%), 81 (57.0%), 43 (30.3%), and 99 (69.7%) patients in the T0-T2, T3-T4, N0-N1, and N2-N3 stages, respectively. There were 108 (76.1%) patients in clinical stages I–III and 34 (23.9%) patients in clinical stage IV. The numbers of patients with luminal A, luminal B, HER2 + , and triple-negative breast cancer (TNBC) were 10 (7.0%), 77 (54.2%), 33 (23.2%), and 22 (15.5%), respectively. The numbers of patients who carried GSTP1 c.313A > G A/A, A/G, and G/G genotypes were 94 (66.2%), 45 (31.7%), and 3 (2.1%), respectively. There were no statistically significant differences in the proportion of certain toxicities in patients with A/G, G/G, and A/G + G/G genotypes, except for neutropenia, in which the proportion of patients with A/G + G/G (χ² = 6.586, P = 0.035) genotypes was significantly higher than that with the AA genotype. The logistic regression analysis indicated that GSTP1 c.313A > G mutation (A/G + G/G vs. A/A genotype) (adjusted OR 4.273, 95% CI 1.141–16.000, P = 0.031) was an independent variable associated with neutropenia.

Conclusions

The findings of this study indicate that the GSTP1 c.313A > G mutation is an independent risk factor for neutropenia hematotoxicity in breast cancer patients induced by anthracycline-/paclitaxel-based chemotherapy.