Management of pain and cachexia in pancreatic cancer: Protocol for two systematic reviews, network meta-analysis, surveys and focus groups

BACKGROUND:  Approximately 75% of people with pancreatic cancer experience pain, and >50% of them have cachexia (weakness and wasting of the body). However, there is considerable uncertainty regarding the management of these distressing symptoms. OBJECTIVE:  Our primary objectives are to compare the relative benefits and harms of different interventions for pain in people with unresectable pancreatic cancer and for prevention and treatment of cachexia due to pancreatic cancer, through systematic reviews and network meta-analysis. Our secondary objectives are to develop an evidence-based clinical care pathway to manage pain and prevent and treat cachexia in people with pancreatic cancer through surveys and focus groups involving patients, carers, and health care professionals. METHODS:  We will perform 2 systematic reviews of the literature related to pain and cachexia in people with pancreatic cancer using searches from Cochrane Library, MEDLINE, Embase, Science Citation Index, and trial registries. Two researchers will independently screen for eligibility and identify randomized controlled trials (no language or publication status restriction), comparing interventions for pain or cachexia based on full-texts for articles shortlisted during screening. We will assess risk of bias in the trials using the Cochrane risk of bias tool (version 2.0) and obtain data related to baseline prognostic characteristics, potential effect modifiers and outcome data related to overall survival, health-related quality of life, treatment-related complications, and resource utilisation. We aim to conduct network meta-analysis on outcomes with multiple treatment comparisons where possible, otherwise, meta-analysis with direct comparisons, or narrative synthesis. We will perform various subgroup and sensitivity analyses. Using information obtained from both systematic reviews, we will conduct 2 surveys: one directed to patients or carers to assess acceptability of interventions, and the other to health care professionals to assess feasibility of delivery in the National Health Service. Four mixed focus groups will be conducted to evaluate findings and foster consensus in the development of the care pathway. RESULTS:  Funding was awarded from April 2022 (NIHR202727). Both systematic review protocols were prospectively registered on PROSPERO in May 2022. Formal searches began thereafter. Approval by the University College London Research Ethics Committee (23563/001) was received in December 2022. Data collection began in January 2023; data analysis will begin in May 2023 (completion expected by October 2023). CONCLUSIONS:  This study will comprehensively encompass major interventions for management of pain in people with unresectable pancreatic cancer, and prevention and treatment of cachexia in people with pancreatic cancer. Key stakeholders will facilitate the development of an evidence-based care pathway, ensuring both acceptability and feasibility. The project ends in April 2024 and published results are expected within 12 months of completion. We aim to present the findings through patient group websites, conferences, and publications, irrespective of the findings, in a peer-reviewed journal. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/46335

A Characterization Study of the ZE41 Magnesium Alloy Using Abrasive Waterjet Cutting

ZE41 is a magnesium alloy used in heat exchangers, condensers, reactors, and pressure vessels where good surface qualities are required. This current research focuses on the investigation of the striation angle (SA), surface roughness (SR), and striation zone (SZ) in ZE41, using abrasive waterjet cutting. Significant variables in the investigation were jet pressure, traverse speed, mass flow rate, and stand-off distance. In accordance with Taguchi’s L18 orthogonal array, the responses for each cut test were studied. In addition, the principal component-based grey incidence (PGI) technique successfully combined the strengths of the optimization tool to identify the ideal parameter condition. The confirmation results revealed that the PGI technique improved SR by 4.02%, SZ by 6.67%, and 1.48% in the SA