BackgroundPhysical exercise is an intervention that might protect against doxorubicin‐induced cardiotoxicity. In this meta‐analysis and systematic review, we aimed to estimate the effect of exercise on doxorubicin‐induced cardiotoxicity and to evaluate mechanisms underlying exercise‐mediated cardioprotection using (pre)clinical evidence.Methods and ResultsWe conducted a systematic search in PubMed, Embase, and Cochrane Central Register of Controlled Trials (CENTRAL) databases. Cochrane's and Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) risk‐of‐bias tools were used to assess the validity of human and animal studies, respectively. Cardiotoxicity outcomes reported by ≥3 studies were pooled and structured around the type of exercise intervention. Forty articles were included, of which 3 were clinical studies. Overall, in humans (sample sizes ranging from 24 to 61), results were indicative of exercise‐mediated cardioprotection, yet they were not sufficient to establish whether physical exercise protects against doxorubicin‐induced cardiotoxicity. In animal studies (n=37), a pooled analysis demonstrated that forced exercise interventions significantly mitigated in vivo and ex vivo doxorubicin‐induced cardiotoxicity compared with nonexercised controls. Similar yet slightly smaller effects were found for voluntary exercise interventions. We identified oxidative stress and related pathways, and less doxorubicin accumulation as mechanisms underlying exercise‐induced cardioprotection, of which the latter could act as an overarching mechanism.ConclusionsAnimal studies indicate that various exercise interventions can protect against doxorubicin‐induced cardiotoxicity in rodents. Less doxorubicin accumulation in cardiac tissue could be a key underlying mechanism. Given the preclinical evidence and limited availability of clinical data, larger and methodologically rigorous clinical studies are needed to clarify the role of physical exercise in preventing cardiotoxicity in patients with cancer.RegistrationURL: https://www.crd.york.ac.uk/prospero; Unique identifier: CRD42019118218.
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INTRODUCTION: Innovations in head and neck cancer (HNC) treatment are often subject to economic evaluation prior to their reimbursement and subsequent access for patients. Mapping functions facilitate economic evaluation of new treatments when the required utility data is absent, but quality of life data is available. The objective of this study is to develop a mapping function translating the EORTC QLQ-C30 to EQ-5D-derived utilities for HNC through regression modeling, and to explore the added value of disease-specific EORTC QLQ-H&N35 scales to the model.METHODS: Data was obtained on patients with primary HNC treated with curative intent derived from two hospitals. Model development was conducted in two phases: 1. Predictor selection based on theory- and data-driven methods, resulting in three sets of potential predictors from the quality of life questionnaires; 2. Selection of the best out of four methods: ordinary-least squares, mixed-effects linear, Cox and beta regression, using the first set of predictors from EORTC QLQ-C30 scales with most correspondence to EQ-5D dimensions. Using a stepwise approach, we assessed added values of predictors in the other two sets. Model fit was assessed using Akaike and Bayesian Information Criterion (AIC and BIC) and model performance was evaluated by MAE, RMSE and limits of agreement (LOA).RESULTS: The beta regression model showed best model fit, with global health status, physical-, role- and emotional functioning and pain scales as predictors. Adding HNC-specific scales did not improve the model. Model performance was reasonable; R2 = 0.39, MAE = 0.0949, RMSE = 0.1209, 95% LOA of -0.243 to 0.231 (bias -0.01), with an error correlation of 0.32. The estimated shrinkage factor was 0.90.CONCLUSIONS: Selected scales from the EORTC QLQ-C30 can be used to estimate utilities for HNC using beta regression. Including EORTC QLQ-H&N35 scales does not improve the mapping function. The mapping model may serve as a tool to enable cost-effectiveness analyses of innovative HNC treatments, for example for reimbursement issues. Further research should assess the robustness and generalizability of the function by validating the model in an external cohort of HNC patients.
Inhibition of the sodium−glucose cotransporter 2 (SGLT2) by canagliflozin in type 2 diabetes mellitus results in large between-patient variability in clinical response. To better understand this variability, the positron emission tomography (PET) tracer [18F]canagliflozin was developed via a Cu-mediated 18F-fluorination of its boronic ester precursor with a radiochemical yield of 2.0 ± 1.9% and a purity of >95%. The GMP automated synthesis originated [18F]canagliflozin with a yield of 0.5−3% (n = 4) and a purity of >95%. Autoradiography showed [18F]canagliflozin binding in human kidney sections containing SGLT2. Since [18F]canagliflozin is the isotopologue of the extensively characterized drug canagliflozin and thus shares its toxicological and pharmacological characteristics, it enables its immediate use in patients.
