Background This study was to evaluate the predictors of xerostomia and Grade 3 xerostomia in locoregionally advanced nasopharyngeal carcinoma (NPC) patients receiving radical radiotherapy and establish prediction models for xerostomia and Grade 3 xerostomia based on the predictors. Methods Totally, 365 patients with locoregionally advanced NPC who underwent radical radiotherapy were randomly divided into the training set (n = 255) and the testing set (n = 110) at a ratio of 7:3. All variables were included in the least absolute shrinkage and selection operator regression to screen out the potential predictors for xerostomia as well as the Grade 3 xerostomia in locoregionally advanced NPC patients receiving radical radiotherapy. The random forest (RF), a decision tree classifier (DTC), and extreme-gradient boosting (XGB) models were constructed. The sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC) and accuracy were analyzed to evaluate the predictive performance of the models. Results In the RF model for predicting xerostomia, the sensitivity was 1.000 (95%CI 1.000–1.000), the PPV was 0.990 (95%CI 0.975–1.000), the NPV was 1.000 (95%CI 1.000–1.000), the AUC was 0.999 (95%CI 0.997–1.000) and the accuracy was 0.992 (95%CI 0.981–1.000) in the training set. The sensitivity was 0.933 (95%CI 0.880–0.985), the PPV was 0.933 (95%CI 0.880–0.985), and the AUC was 0.915 (95%CI 0.860–0.970) in the testing set. Hypertension, age, total radiotherapy dose, dose at 50% of the left parotid volume, mean dose to right parotid gland, mean dose to oral cavity, and course of induction chemotherapy were important variables associated with the risk of xerostomia in locoregionally advanced NPC patients receiving radical radiotherapy. The AUC of DTC model for predicting xerostomia was 0.769 (95%CI 0.666–0.872) in the testing set. The AUC of the XGB model for predicting xerostomia was 0.834 (0.753–0.916) in the testing set. The RF model showed the good predictive ability with the AUC of 0.986 (95%CI 0.972–1.000) in the training set, and 0.766 (95%CI 0.626–0.905) in the testing set for identifying patients who at high risk of Grade 3 xerostomia in those with high risk of xerostomia. Conclusions An RF model for predicting xerostomia in locoregionally advanced NPC patients receiving radical radiotherapy and an RF model for predicting Grade 3 xerostomia in those with high risk of xerostomia showed good predictive ability.

No abstract

Yinggehai Basin locates in the northern South China Sea. Since the Cainozoic Era, crust has several strong tension: the basin subsides quickly, the deposition is thick, and the crust is thin. In the central basin, formation pressure coefficient is up to 2.1; Yinggehai Basin is a fomous high-temperature overpressure basin. Yinggehai Basin's in-depth, especially high-temperature overpressure stratum has numerous large-scale exploration goals. As a result of high-temperature overpressure basin's perplexing geological conditions and geophysical analysis technical limitations, this field of gas exploration can't be carried out effectively, which affects the process of gas exploration seriously. A pressure prediction model of the high-temperature overpressure basin in different structural positions is summed up by pressure forecast pattern research in recent years, which can be applied to target wells pre-drilling pressure prediction and post drilling pressure analysis of Yinggehai Basin. The model has small erroneous and high rate of accuracy. The Yinggehai Basin A well drilling is successful in 2010, and gas is discovered in high-temperature overpressure stratum, which proved that reservoir can be found in high-temperature overpressure stratum. It is a great theoretical breakthrough of reservoir knowledge.

No abstract

No abstract