Scoping review identifying interventions that have been tested to optimise the experience of people from ethnic minority groups receiving systemic anticancer therapy (SACT).

Background: Disparities have been identified in many aspects of the cancer care pathway for people from minority ethnic groups (MEGs). Adherence to systemic anticancer therapies (SACTs) has been shown to impact morbidity and mortality, and therefore, inequitable experiences can have a detrimental effect on outcomes.

Objectives: To identify interventions that focused on improving the experiences and clinical outcomes in people from MEG receiving SACT treatments.

Enablers and barriers of clinical trial participation in adult patients from minority ethnic groups: a systematic review.

Background: Clinical trials are essential to the development of healthcare innovations that advance life expectancy and improve quality of life. However, there exists a pronounced disparity in ethnic representation among trial participants. This imbalance, particularly in relation to minority ethnic groups, can lead to a limited understanding of how therapies affect diverse populations.

From prediction to practice: mitigating bias and data shift in machine-learning models for chemotherapy-induced organ dysfunction across unseen cancers.

Objectives: Routine monitoring of renal and hepatic function during chemotherapy ensures that treatment-related organ damage has not occurred and clearance of subsequent treatment is not hindered; however, frequency and timing are not optimal. Model bias and data heterogeneity concerns have hampered the ability of machine learning (ML) to be deployed into clinical practice. This study aims to develop models that could support individualised decisions on the timing of renal and hepatic monitoring while exploring the effect of data shift on model performance.

Association of pre-existing cardiovascular disease with administration of fluoropyrimidine chemotherapy in patients with gastrointestinal malignancies.

Objective: Fluoropyrimidine chemotherapy is a first-line treatment for many gastrointestinal (GI) cancers, however, cardiotoxicity concerns may limit administration in patients with pre-existing cardiovascular disease (CVD). This study investigated the association of pre-existing CVD with use of fluoropyrimidine chemotherapy in tumour-eligible GI cancer patients.

Methods And Analysis: National cancer registry data from the Virtual Cardio-Oncology Research Initiative from England between 2014 and 2018 was used to identify GI cancer patients eligible to receive fluoropyrimidine chemotherapy.

Performance of machine learning versus the national early warning score for predicting patient deterioration risk: a single-site study of emergency admissions.

Objectives: Increasing operational pressures on emergency departments (ED) make it imperative to quickly and accurately identify patients requiring urgent clinical intervention. The widespread adoption of electronic health records (EHR) makes rich feature patient data sets more readily available. These large data stores lend themselves to use in modern machine learning (ML) models.