title: Reducing hypersensitivity reactions with HLA-B*5701 genotyping before abacavir prescription: clinically useful but is it cost-effective in Singapore?
abstract: OBJECTIVE
  Abacavir (ABC) is one of the more affordable antiretroviral drugs used for controlling HIV. Although with similar efficacy to current first-line drugs, its limited usage in Singapore can be attributed to its possible side effect of adverse hypersensitivity reactions (HSRs). HLA-B*5701 genotyping is a clinically relevant procedure for avoiding abacavir-induced HSRs. As patients who do not carry the risk allele are unlikely to develop HSRs, a simple rule can be developed to allow abacavir prescription for patients who are B*5701 negative. Here, we carry out a cost-effectiveness analysis of HLA-B*5701 genotyping before abacavir prescription in the context of the Singapore healthcare system, which caters predominantly to Han Chinese, Southeast-asian Malays, and South-asian Indians. In addition, we aim to identify the most cost-effective treatment regimen for HIV patients.
  
  
  METHODS
  A decision tree model was developed in TreeAge. The model considers medical treatment and genotyping costs, genotyping test characteristics, the prevalence of the risk allele, reduction in the quality of life, and increased expenditure due to side effects and other factors, evaluating independently over early-stage and late-stage HIV patients segmented by drug contraindications.
  
  
  RESULTS
  The study indicates that genotyping is not cost-effective for any ethnicity irrespective of the disease stage, except for Indian patients with early-stage HIV who are contraindicated to tenofovir.
  
  
  CONCLUSIONS
  Abacavir (as first-line) without genotyping is the cheapest and most cost-effective treatment for all ethnicities except for early-stage Indian HIV patients contraindicated to tenofovir. The HLA-B*5701 frequency, the mortality rate from abacavir-induced HSRs, and genotyping costs are among the major factors influencing the cost-effectiveness.
authors.affiliation: aNUS Graduate School for Integrative Science and Engineering bDepartment of Statistics and Applied Probability cDepartment of Medicine, Yong Loo Lin School of Medicine dLife Sciences Institute eSaw Swee Hock School of Public Health, National University of Singapore fInstitute of Infectious Disease and Epidemiology, Communicable Disease Centre, Tan Tock Seng Hospital gHealth Services and Systems Research Program hProgram for Emerging Infectious Diseases, Duke-NUS Graduate Medical School iHealth Sciences Authority jDivision of Infectious Diseases, University Medicine Cluster, National University Hospital kGenome Institute of Singapore, Agency for Science, Technology, and Research, Singapore, Singapore.
authors.forename: Ritika
authors.initials: R
authors.lastname: Kapoor
authors.forename: Rosario
authors.initials: R
authors.lastname: Martinez-Vega
authors.forename: Di
authors.initials: D
authors.lastname: Dong
authors.forename: Sharlene Yanying
authors.initials: SY
authors.lastname: Tan
authors.forename: Yee-Sin
authors.initials: YS
authors.lastname: Leo
authors.forename: Cheng-Chuan
authors.initials: CC
authors.lastname: Lee
authors.forename: Cynthia
authors.initials: C
authors.lastname: Sung
authors.forename: Oon-Tek
authors.initials: OT
authors.lastname: Ng
authors.forename: Sophia
authors.initials: S
authors.lastname: Archuleta
authors.forename: Yik-Ying
authors.initials: YY
authors.lastname: Teo
mesh_terms: D000328:Adult; D000368:Aged; D019380:Anti-HIV Agents / Q000191:economics* / Q000627:therapeutic use*; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D003663:Decision Trees; D015224:Dideoxynucleosides / Q000191:economics* / Q000627:therapeutic use*; D004342:Drug Hypersensitivity / Q000191:economics / Q000453:epidemiology / Q000235:genetics / Q000517:prevention & control*; D011307:Drug Prescriptions / Q000191:economics / Q000706:statistics & numerical data; D060005:Genotyping Techniques / Q000191:economics*; D015658:HIV Infections / Q000188:drug therapy / Q000191:economics / Q000453:epidemiology / Q000235:genetics; D015497:HIV-1; D015235:HLA-B Antigens / Q000235:genetics*; D017048:Health Care Costs; D006801:Humans; D008017:Life Expectancy; D008875:Middle Aged; D010818:Practice Patterns, Physicians' / Q000191:economics / Q000706:statistics & numerical data; D012846:Singapore / Q000453:epidemiology; D000099227:Abacavir
chemical_list: D019380:Anti-HIV Agents; D015224:Dideoxynucleosides; D015235:HLA-B Antigens; D000099227:Abacavir; C484830:HLA-B*57:01 antigen