[18F]-fluoroethyl-L-tyrosine (FET) in glioblastoma (FIG) TROG 18.06 study: protocol for a prospective, multicentre PET/CT trial.

INTRODUCTION: Glioblastoma is the most common aggressive primary central nervous system cancer in adults characterised by uniformly poor survival. Despite maximal safe resection and postoperative radiotherapy with concurrent and adjuvant temozolomide-based chemotherapy, tumours inevitably recur. Imaging with O-(2-[18F]-fluoroethyl)-L-tyrosine (FET) positron emission tomography (PET) has the potential to impact adjuvant radiotherapy (RT) planning, distinguish between treatment-induced pseudoprogression versus tumour progression as well as prognostication. METHODS AND ANALYSIS: The FET-PET in Glioblastoma (FIG) study is a prospective, multicentre, non-randomised, phase II study across 10 Australian sites and will enrol up to 210 adults aged ≥18 years with newly diagnosed glioblastoma. FET-PET will be performed at up to three time points: (1) following initial surgery and prior to commencement of chemoradiation (FET-PET1); (2) 4 weeks following concurrent chemoradiation (FET-PET2); and (3) within 14 days of suspected clinical and/or radiological progression on MRI (performed at the time of clinical suspicion of tumour recurrence) (FET-PET3). The co-primary outcomes are: (1) to investigate how FET-PET versus standard MRI impacts RT volume delineation and (2) to determine the accuracy and management impact of FET-PET in distinguishing pseudoprogression from true tumour progression. The secondary outcomes are: (1) to investigate the relationships between FET-PET parameters (including dynamic uptake, tumour to background ratio, metabolic tumour volume) and progression-free survival and overall survival; (2) to assess the change in blood and tissue biomarkers determined by serum assay when comparing FET-PET data acquired prior to chemoradiation with other prognostic markers, looking at the relationships of FET-PET versus MRI-determined site/s of progressive disease post chemotherapy treatment with MRI and FET-PET imaging; and (3) to estimate the health economic impact of incorporating FET-PET into glioblastoma management and in the assessment of post-treatment pseudoprogression or recurrence/true progression. Exploratory outcomes include the correlation of multimodal imaging, blood and tumour biomarker analyses with patterns of failure and survival. ETHICS AND DISSEMINATION: The study protocol V.2.0 dated 20 November 2020 has been approved by a lead Human Research Ethics Committee (Austin Health, Victoria). Other clinical sites will provide oversight through local governance processes, including obtaining informed consent from suitable participants. The study will be conducted in accordance with the principles of the Declaration of Helsinki and Good Clinical Practice. Results of the FIG study (TROG 18.06) will be disseminated via relevant scientific and consumer forums and peer-reviewed publications. TRIAL REGISTRATION NUMBER: ANZCTR ACTRN12619001735145.

Acupuncture for Cancer Related Pain: Protocol for a Pragmatic Randomised Wait-List Controlled Trial.

BACKGROUND: Acupuncture has been proved effective for cancer related pain (CRP) in China, America and some other countries. However, there is relative lack of evidence to support the use of acupuncture for CRP in Australia. OBJECTIVES: To assess the effectiveness and safety of acupuncture for management of CRP in a real-world setting and to understand cancer patients' experience of undergoing acupuncture for CRP. METHODS: A pragmatic randomised controlled trial will be conducted in South Western Sydney Local Health District (SWSLHD) in NSW, Australia. Adults with cancer related pain (n = 106) will be randomised in a 1:1 ratio to receive the acupuncture intervention up front versus after a wait list period of 4 weeks. Pain level (by Numerical Rating Scale), analgesic use, auricular acupressure frequency and adverse events will be assessed at baseline, mid-treatment and post-treatment. Expectancy on trial outcome (by Credibility and Expectancy questionnaire) will be assessed at baseline. The perspective of the participants (by an interview) will be recorded after the last intervention. EXPECTED OUTCOMES: We hypothesise that acupuncture will relieve cancer related pain at mid-treatment and post-treatment. We also hypothesise that few adverse events will be provoked by acupuncture. TRIAL REGISTRATION: Australia New-Zealand Clinical Trial Registry (ACTRN12620000325909).

Development of Health Pathways to Standardize Cancer Care Pathways Informed by Patient-Reported Outcomes and Clinical Practice Guidelines.

PURPOSE: High-quality symptom management and supportive care are essential components of comprehensive cancer care. We aimed to describe the development of an evidence-based automated decisional algorithm for patients with cancer that had specific, actionable, clinical, evidence-based recommendations to improve patient care, communication, and management. METHODS: We reviewed existing literature and clinical practice guidelines to identify priority domains of patient care and potential clinical recommendations. Two multidisciplinary clinical advisory groups used a two-stage consensus decision-making approach to determine domains of care and patient-reported outcome (PRO) measures and subsequently developed automated algorithms with clear clinical recommendations amendable to intervention in clinical settings. RESULTS: Algorithms were developed to inform management of patient symptoms, distress, and unmet needs. Three PRO measures were chosen: Distress Thermometer and problem checklist, Edmonton Symptom Assessment Scale, and the Supportive Care Needs Survey-Screening Tool 9. PRO items were mapped to five domains of patient well-being: physical, emotional, practical, social and family, and maintenance of well-being. A total of 15 actionable clinical recommendations tailored to specific issues of concern were established. CONCLUSION: Using automated algorithms and clinical recommendations provides a platform for streamlining and systematizing the use of PROs to inform risk-stratified guideline-informed care. The series of algorithms, which set out systematized care pathways for the clinical care of patients with cancer, can be used to potentially inform patient-centered care.