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ARCHERY: a prospective observational study of artificial intelligence-based radiotherapy treatment planning for cervical, head and neck and prostate cancer - study protocol

Por: Aggarwal · A. · Court · L. E. · Hoskin · P. · Jacques · I. · Kroiss · M. · Laskar · S. · Lievens · Y. · Mallick · I. · Abdul Malik · R. · Miles · E. · Mohamad · I. · Murphy · C. · Nankivell · M. · Parkes · J. · Parmar · M. · Roach · C. · Simonds · H. · Torode · J. · Vanderstraeten · B. · Lan
Introduction

Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%–40% of patients in low-income and middle-income countries (LMICs) have access to it. A shortfall in specialised workforce has been identified as the most significant barrier to expanding radiotherapy capacity. Artificial intelligence (AI)-based software has been developed to automate both the delineation of anatomical target structures and the definition of the position, size and shape of the radiation beams. Proposed advantages include improved treatment accuracy, as well as a reduction in the time (from weeks to minutes) and human resources needed to deliver radiotherapy.

Methods

ARCHERY is a non-randomised prospective study to evaluate the quality and economic impact of AI-based automated radiotherapy treatment planning for cervical, head and neck, and prostate cancers, which are endemic in LMICs, and for which radiotherapy is the primary curative treatment modality. The sample size of 990 patients (330 for each cancer type) has been calculated based on an estimated 95% treatment plan acceptability rate. Time and cost savings will be analysed as secondary outcome measures using the time-driven activity-based costing model. The 48-month study will take place in six public sector cancer hospitals in India (n=2), Jordan (n=1), Malaysia (n=1) and South Africa (n=2) to support implementation of the software in LMICs.

Ethics and dissemination

The study has received ethical approval from University College London (UCL) and each of the six study sites. If the study objectives are met, the AI-based software will be offered as a not-for-profit web service to public sector state hospitals in LMICs to support expansion of high quality radiotherapy capacity, improving access to and affordability of this key modality of cancer cure and control. Public and policy engagement plans will involve patients as key partners.

Exploring The Transgender Individual's Experience With Healthcare Interactions: A Phenomenological Study

Abstract

Purpose

The purpose of the study was to provide a transgender narrative on healthcare interactions to increase visibility and awareness of transgender-identified issues in accessing care. This study aimed to: (a) examine how transgender individuals perceive and experience interactions with trained healthcare professionals, such as nurses, physicians, and mental health professionals, (b) identify common issues related to transgender individuals' barriers to care, and (c) identify how these barriers affect a transgender individual's ability to access health care.

Design

A phenomenological approach was used.

Methods

The nine transgender-identified participants received a demographic questionnaire followed by a virtual semi-structured interview. Thematic analysis was used to analyze the interview data.

Findings

The themes that emerged from the data were (a) challenges with accessing health care, (b) inconsistent healthcare information, and (c) disenfranchised versus empowered experiences.

Conclusion

The results of this study not only provided an opportunity for the transgender participants to share their experiences, but also provides educational information for healthcare providers to improve their future interactions with transgender patients.

Clinical relevance

Identifying the transgender patient with the correct name and pronoun, providing a welcoming and open healthcare environment, and knowing where to locate transgender health resources will improve the transgender patient's healthcare experience.

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