Sick Day Management Plans for Aboriginal and/or Torres Strait Islander Peoples With Chronic Kidney Disease on the Cape York Peninsula of Australia: Health Workers' Perspectives.

Objective: This study aimed to explore the perspectives of healthcare professionals on the utility of sick day management plans for people with chronic kidney disease (CKD) in remote communities and collaboratively design a sick day management plan resource.

Design: This qualitative study utilised two phases of data collection: preliminary observational data and semi-structured interviews. The research design and analysis were guided by the normalisation process theory (NPT) framework, tailored for complex interventions in healthcare.

Identifying public health competencies for Australian pharmacists: A modified Delphi study.

Objective: This study aimed to define a set of competencies for public health-related services and activities for pharmacists in Australia.

Methods: A modified Delphi technique of two rounds was used to gain consensus by public health and pharmacy professionals on a set of public health competency statements for Australian pharmacists.

Results: Delphi panellists agreed on the inclusion of 27 competency statements organised into three domains of health promotion and illness prevention, health protection and population health quality improvement.

Salvage Autologous Transplant in Relapsed Multiple Myeloma: Long-Term Follow-Up of the Phase 3 GMMG ReLApsE Trial.

The multicenter, phase III GMMG ReLApsE trial (EudraCT-No:2009-013856-61) randomized relapsed and/or refractory multiple myeloma (RRMM) patients equally to lenalidomide/dexamethasone (LEN/DEX, 25mg days 1-21/40mg weekly, 4-week cycles) re-induction, salvage high dose chemotherapy (sHDCT, melphalan 200mg/m2), autologous stem cell transplantation (ASCT) and LEN maintenance (10mg/day; transplant arm, n=139) versus continuous LEN/DEX (control arm, n=138). Ninety-four percent of patients had received frontline HDCT/ASCT. We report an updated analysis of survival endpoints with a median follow-up of 99 months.

Deployment of a Machine Learning Algorithm in a Real-World Cohort for Quality Control Monitoring of Human Epidermal Growth Factor-2-Stained Clinical Specimens in Breast Cancer.

Context.—: Precise determination of biomarker status is necessary for clinical trial enrollment and endpoint analyses, as well as for optimal treatment determination in real-world practice. However, variabilities may be introduced into this process due to the processing of clinical specimens by different laboratories and assessment by distinct pathologists.