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Implementing HLA-B*58:01 testing prior to allopurinol initiation in Malaysian primary care setting: A qualitative study from doctors’ and patients’ perspective

by Wei Leik Ng, Norita Hussein, Chirk Jenn Ng, Nadeem Qureshi, Yew Kong Lee, Zhenli Kwan, Boon Pin Kee, Sue-Mian Then, Tun Firzara Abdul Malik, Fatimah Zahrah Mohd Zaidan, Siti Umi Fairuz Azmi

Introduction

Allopurinol, the first-line treatment for chronic gout, is a common causative drug for severe cutaneous adverse reactions (SCAR). HLA-B*58:01 allele was strongly associated with allopurinol-induced SCAR in Asian countries such as Taiwan, Japan, Thailand and Malaysia. HLA-B*58:01 screening before allopurinol initiation is conditionally recommended in the Southeast-Asian population, but the uptake of this screening is slow in primary care settings, including Malaysia. This study aimed to explore the views and experiences of primary care doctors and patients with gout on implementing HLA-B*58:01 testing in Malaysia as part of a more extensive study exploring the feasibility of implementing it routinely.

Methods

This qualitative study used in-depth interviews and focus group discussions to obtain information from patients with gout under follow-up in primary care and doctors who cared for them. Patients and doctors shared their gout management experiences and views on implementing HLA-B*58:01 screening in primary care. Data were coded and analysed using thematic analysis.

Results

18 patients and 18 doctors from three different healthcare settings (university hospital, public health clinics, private general practitioner clinics) participated. The acceptability to HLA-B*58:01 screening was good among the doctors and patients. We discovered inadequate disclosure of severe side effects of allopurinol by doctors due to concerns about medication refusal by patients, which could potentially be improved by introducing HLA-B*58:01 testing. Barriers to implementation included out-of-pocket costs for patients, the cost-effectiveness of this implementation, lack of established alternative treatment pathway besides allopurinol, counselling burden and concern about genetic data security. Our participants preferred targeted screening for high-risk populations instead of universal screening.

Conclusion

Implementing HLA-B*58:01 testing in primary care is potentially feasible if a cost-effective, targeted screening policy on high-risk groups can be developed. A clear treatment pathway for patients who test positive should be made available.

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.

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