A cost outcome study of varicocoele embolisation and future pregnancy in an Australian public hospital setting

INTRODUCTION

Varicocoele is commonly encountered in males with infertility. Studies have shown that varicocoele repair (surgery or embolisation) can improve the rate of subsequent pregnancy. In Australia, there have been no studies assessing the cost of varicocoele embolisation and current practice is based on international data. This study aimed to assess the cost of varicocoele embolisation and estimate the treatment cost per pregnancy.

METHODS

Retrospective cost-outcome study of patients treated by embolisation between January 2018 and 2023. A bottom-up approach was used to calculate procedure costs whereas a top-down approach was used to calculate costs for all other patient services, including direct and indirect costs. To calculate cost per pregnancy, costs were adjusted according to existing published data on the rate of pregnancy after embolisation.

RESULTS

Costing data from 18 patients were included, of median age 33.5 years (range 26-60) and median varicocoele grade 2.5 (range 1-3). All patients had unilateral treatment, most commonly via right internal jugular (16 patients, 89%) and using a 0.035″ system (17 patients, 94%). The median cost for the entire treatment including procedural, non-procedural, ward and peri-procedural costs was AUD$2208.10 (USD$1405 or EUR€1314), range AUD$1691-7051. The projected cost to the healthcare system per pregnancy was AUD$5387 (USD$3429 or EUR€3207).

CONCLUSION

Total varicocoele embolisation cost and the cost per-pregnancy were lower than for both embolisation and surgical repair in existing international studies. Patients undergoing varicocoele treatment should have the option to access an interventional radiologist to realise the benefits of this low-cost pinhole procedure.

Drug repurposing and prediction of multiple interaction types via graph embedding

BACKGROUND

Finding drugs that can interact with a specific target to induce a desired therapeutic outcome is key deliverable in drug discovery for targeted treatment. Therefore, both identifying new drug-target links, as well as delineating the type of drug interaction, are important in drug repurposing studies.

RESULTS

A computational drug repurposing approach was proposed to predict novel drug-target interactions (DTIs), as well as to predict the type of interaction induced. The methodology is based on mining a heterogeneous graph that integrates drug-drug and protein-protein similarity networks, together with verified drug-disease and protein-disease associations. In order to extract appropriate features, the three-layer heterogeneous graph was mapped to low dimensional vectors using node embedding principles. The DTI prediction problem was formulated as a multi-label, multi-class classification task, aiming to determine drug modes of action. DTIs were defined by concatenating pairs of drug and target vectors extracted from graph embedding, which were used as input to classification via gradient boosted trees, where a model is trained to predict the type of interaction. After validating the prediction ability of DT2Vec+, a comprehensive analysis of all unknown DTIs was conducted to predict the degree and type of interaction. Finally, the model was applied to propose potential approved drugs to target cancer-specific biomarkers.

CONCLUSION

DT2Vec+ showed promising results in predicting type of DTI, which was achieved via integrating and mapping triplet drug-target-disease association graphs into low-dimensional dense vectors. To our knowledge, this is the first approach that addresses prediction between drugs and targets across six interaction types.