ABSTRACT
OBJECTIVES: In UK laboratories, the diagnostic algorithm for chronic hepatitis C (HCV) infection commonly requires two serological assays to confirm anti-HCV-antibody positivity in a serum sample followed by HCV RNA detection in a second whole-blood sample (two-step testing algorithm). A single-step algorithm (both anti-HCV antibodies and RNA tested on an initial serum specimen) has been advocated to reduce attrition rates from the care pathway. STUDY DESIGN: To investigate the feasibility, clinical impact and relative costs of switching from a two-step to single-step testing algorithm in the laboratory, a pilot study on unselected primary care requests was undertaken. METHODS: All primary care patients tested for HCV infection from December 2013 to April 2016 were included. The single-step testing algorithm was introduced in March 2015. Before this, the two-step algorithm was used. Patients were followed up until August 2016. RESULTS: RNA quantitation in plasma was within one log of serum values for 21 paired samples. Although all patients in the single-step algorithm received an RNA test, only 70% completed the two-step testing algorithm; differences in referral rates to specialist care was due to 30% of HCV antibody-positive patients in the two-step algorithm not having follow-up whole-blood sampling for HCV RNA testing. Costs per new diagnosis and new diagnosis referred to specialist care were lower in single-step testing by £94.32 and £144.25, respectively. CONCLUSION: This study provides further evidence that a single-step testing algorithm, as recommended in the UK Standards for Microbiology Investigation, works in practice and should be the standard of care for screening for chronic HCV.
Subject(s)
Hepatitis C/diagnosis , Mass Screening/economics , Mass Screening/methods , Primary Health Care , Algorithms , Costs and Cost Analysis , Feasibility Studies , Hepacivirus/immunology , Hepacivirus/isolation & purification , Hepatitis C Antibodies/blood , Humans , Outcome Assessment, Health Care , Pilot Projects , RNA, Viral/blood , Referral and Consultation/statistics & numerical data , United KingdomABSTRACT
SETTING: Birmingham, United Kingdom, 2010-2014. OBJECTIVE: To investigate predictors for clustering of tuberculosis (TB) cases and cluster size and to evaluate the impact of cluster investigation using social network data. DESIGN: Retrospective observational cohort study. Prioritised cases linked using 24-locus mycobacterial interspersed repetitive units-variable number of tandem repeats (MIRU-VNTR) were interviewed using a social network approach to find epidemiological links. RESULTS: Of 2055 TB cases notified, 56% could be typed. Clustering was associated with younger age, UK birth, Black Caribbean ethnicity, social risk factors, pulmonary TB and negative human immunodeficiency virus status. Only UK birth and presence of more than one social risk factor were associated with larger cluster size, while drug resistance was associated with smaller cluster size. Social network data from 139/431 clustered cases found new epidemiological links in 11/19 clusters with ⩾5 members (undirected median network density 0.09, interquartile range 0.05-0.4). Ninety-eight additional contacts were assessed, with one case of active TB and 24 with latent tuberculous infection diagnosed. CONCLUSION: A social network approach increased knowledge of likely transmission events, but few additional TB cases were diagnosed. Obtaining social network data for all typed and untyped TB cases may improve contact tracing and reduce unexpected transmission detected from molecular data.
Subject(s)
Latent Tuberculosis/epidemiology , Social Environment , Tuberculosis, Pulmonary/epidemiology , Tuberculosis/epidemiology , Adult , Bacterial Typing Techniques , Cluster Analysis , Female , Humans , Latent Tuberculosis/diagnosis , Male , Middle Aged , Mycobacterium tuberculosis/classification , Mycobacterium tuberculosis/isolation & purification , Retrospective Studies , Risk Factors , Tuberculosis/diagnosis , Tuberculosis, Pulmonary/diagnosis , United Kingdom/epidemiologyABSTRACT
BACKGROUND: There have been few studies on risk factors and treatment outcomes of isoniazid (H)-resistant tuberculosis (TB), and optimal treatment regimens are debated. AIM: : To identify risk factors for H-resistant TB, describe treatment regimens and compare these to national guidelines and describe short-term outcomes of H-resistant TB in Birmingham, UK. DESIGN: Retrospective case series. METHODS: Cases of H-resistant tuberculosis in Birmingham between January 1999 and December 2010 (n = 89) were compared with drug-susceptible cases (n = 2497). Treatment regimens and outcomes at 12 months from diagnosis were evaluated by case note review. RESULTS: No independent predictors for H-resistant TB were found. For 76/89 (85%) patients with full treatment details available, median treatment duration was 11 months (interquartile range 9-12 months). Only 27/72 (38%) patients with H-monoresistance were treated in line with national guidelines. A further 14/72 (19%) were treated according to other recognized guidelines. Overall treatment success was 75/89 (84%). Treatment failure occurred in 6/89 (7%) patients, all developed multi-drug resistance. Poor adherence was documented in these patients and use of a non-standard regimen in one patient was not thought to have contributed to treatment failure. CONCLUSIONS: No discriminating risk factors for early detection of H-resistant TB were found. Treatment regimens in clinical practice were highly varied. H-resistance can drive MDR-TB when there is evidence or suspicion of poor adherence. A low threshold for enhanced case management with directly observed therapy is warranted in this group.
