Effects of low‐level laser therapy on burning mouth syndrome

To investigate low‐level laser therapy (LLLT) applied to treat burning mouth syndrome (BMS). This prospective, comparative, partially blinded, single‐centre, clinical trial of GaAlAs Laser, with 815 nm wavelength, included 44 BMS patients divided randomly into three groups: Group I (n = 16): GaAlAs laser 815 nm wavelength, 1 W output power, continuous emissions, 4 s, 4 J and fluence rate 133·3 J cm^?2; Group II (n = 16): GaAlAs infrared laser, 815 nm wavelength, 1 W output power, continuous emissions, 6 s, 6 J and fluence rate 200 J cm^?2; Group III (n = 12) placebo group, sham laser. All groups received a weekly dose for 4 weeks. Pain intensity was recorded using a 10‐cm visual analogue scale; patients responded to the oral health impact profile (OHIP‐14), xerostomia severity test and the hospital anxiety–depression scale (HAD). These assessments were performed at baseline, 2 and 4 weeks. LLLT decreased pain intensity and improved OHIP‐14 scores significantly from baseline to 2 weeks in groups I and II compared with the placebo group. No statistically significant differences were found from 2 to 4 weeks. Overall improvements in visual analogue scale (VAS) scores from baseline to the end of treatment were as follows: Group I 15·7%; Group II 15·6%; Group III placebo 7·3%. LLLT application reduces symptoms slightly in BMS patients.     

Farmacocinética poblacional de doxorubicina aplicada a la personalización de su dosificación en pacientes oncológicos

ObjectiveTo develop and internally validate a population pharmacokinetic model for doxorubicin and to evaluate its predictive performance for dose individualization in cancer patients.MethodsDoxorubicin plasma concentrations were determined in thirty-three cancer patients treated with intravenous doxorubicin. A three-compartment pharmacokinetic model was implemented in the NONMEN VI programme to determine the doxorubicin pharmacokinetic parameters. The identifiability of the parameters was assessed by parametric bootstrap and model validation was performed using nonparametric bootstrap, visual predictive check, and numerical predictive check. The final model‘s predictive performance was evaluated in terms of accuracy and precision of plasma concentration predictions during the first and second cycles of chemotherapy.ResultsDoxorubicin clearance was 58.8L/h, with interpatient variability of 29.2% and intrapatient variability of 18.9%. The estimated volume of distribution at steady state was 2294L, with inter-and intrapatient variability of 7.3% and 26.1%, respectively. Internal validation confirmed that the population pharmacokinetic model is appropriate to describe the time course of the doxorubicin plasma concentrations and its variability in this population. The accuracy and precision of an a posteriori prediction of doxorubicin plasma concentrations improved by 63% and 41% compared to the a priori prediction.ConclusionThe Bayesian population pharmacokinetic model characterised the time course of doxorubicine plasma concentrations and can be accurately and precisely used to optimise doxorubicine dosing regimens in cancer patients.