Brachytherapy: An emblematic example of extreme hypofractionated regimen

In order to provide more convenient irradiation regimens for patient comfort, radiation facility organization and health expenses, new hypofractionated protocols have been evaluated. Moderately (dose/fraction: 2.3 to 3 Gy), then ultra (dose/fraction: 5.2 to 6.1 Gy) hypofractionated irradiations were first validated. The current question is: is it possible to go forward using extreme hypofractionated regimens (EHR) based on 1 to 3 fractions. Different irradiation techniques are under investigation. However, brachytherapy remains the smartest way to deliver a high dose in a small volume. We report prospective and retrospective study results which evaluated EHR for breast and prostate brachytherapy. While oncological outcome and toxicity profile appear extremely encouraging for low-risk breast cancer after a 1 to 4 fractions (6.25 to 20 Gy/fraction), the use of a single fraction of 19 to 23 Gy appears debatable for prostate cancer. Brachytherapy represents an emblematic example of EHR but longer follow-up and more mature results are awaited in order to specify the right indications and refine the EQD2 calculation method including new biological and technical factors.     

Recreational runners with Achilles tendinopathy have clinically detectable impairments: A case-control study

ObjectivesTo confirm what impairments are present in runners with Achilles tendinopathy (AT) and explore the variance of AT severity in an adequately powered study.DesignCase-control study.SettingTwo private physiotherapy clinics in Australia and Spain.ParticipantsForty-four recreational male runners with AT and 44 healthy controls matched by age, height, and weight.Main outcome measuresDemographics, activity (IPAQ-SF), pain and function (VISA-A), pain during hopping (Hop pain VAS), hopping duration, psychological factors (TSK-11, PASS20), and physical tests regarding lower-limb maximal strength and endurance.ResultsBody mass index (BMI), activity, VISA-A, pain, and duration of hopping, TSK-11, PASS20, standing heel raise to failure, seated heel raise and leg extension 6RM, hip extension and abduction isometric torque were significantly different between groups (P < 0.05) with varied effect sizes (V = 0.22, d range = 0.05–4.18). 46% of AT severity variance was explained by higher BMI (β = −0.41; p = 0.001), weaker leg curl 6RM (β = 0.32; p = 0.009), and higher pain during hopping (β = −0.43; p = 0.001).ConclusionRunners with AT had lower activity levels, lower soleus strength, and were less tall. BMI, pain during hopping, and leg curl strength explained condition severity. This information, identified with clinically applicable tools, may guide clinical assessment, and inform intervention development.     

Performance of risk prediction models for post-operative mortality in patients undergoing liver resection

BackgroundLiver resection is commonly performed for hepatic tumors, however preoperative risk stratification remains challenging. We evaluated the performance of contemporary prediction models for short-term mortality after liver resection in patients with and without cirrhosis.MethodsThis retrospective cohort study examined National Surgical Quality Improvement Program data. We included patients who underwent liver resections from 2014 to 2019. VOCAL-Penn, MELD, MELD-Na, ALBI, and Mayo risk scores were evaluated in terms of model discrimination and calibration for 30-day post-operative mortality.ResultsA total 15,198 patients underwent liver resection, of whom 249 (1.6%) experienced 30-day post-operative mortality. The VOCAL-Penn score had the highest discrimination (area under the ROC curve [AUC] 0.74) compared to all other models. The VOCAL-Penn score similarly outperformed other models in patients with (AUC 0.70) and without (AUC 0.74) cirrhosis.ConclusionThe VOCAL-Penn score demonstrated superior predictive performance for 30-day post-operative mortality after liver resection as compared to existing clinical standards.     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

Prolyl and lysyl hydroxylases in collagen synthesis

Collagens are the most abundant proteins in the extracellular matrix. They provide a framework to build organs and tissues and give structural support to make them resistant to mechanical load and forces. Several intra‐ and extracellular modifications are needed to make functional collagen molecules, intracellular post‐translational modifications of proline and lysine residues having key roles in this. In this article, we provide a review on the enzymes responsible for the proline and lysine modifications, that is collagen prolyl 4‐hydroxylases, 3‐hydroxylases and lysyl hydroxylases, and discuss their biological functions and involvement in diseases.