Determine TB prevalence and incidence, select trial sites and choose target populations for TB vaccines

Suzanne Verver, epidemiologist

3 rd Global Forum on TB vaccines, 26 March 2013, Cape Town

Outline

• • • Choose target populations Epi studies to determine TB prevalence and incidence Select trial sites: hotspots

Target groups

• • • • • • • • • Infants Easy to access Include vaccine in EPI Slow effect on epidemic Adults Highest incidence The older the more stable More difficult to access and follow-up High risk groups: HIV infected, urban population • • • • • Adolescents 12-18 Mix pre- and post-infection (South Africa 50%) Easy to access; the younger the easier to follow up but the lower the incidence Probably need to be included for licensure

WHO TB impact working group mtg 2010 background paper no 9 by Ana Bierenbach

WHO TB Impact working group mtg 2010 background paper no 9 by Ana Bierenbach

Objectives of epidemiological studies to prepare for vaccine trials

• • To assess TB prevalence (adolescents) & incidence To assess proportion MTB infected • To assess comorbidities (Malaria, HIV) & mortality (verbal autopsy) and strategies to reduce these • To assess recruitment and cohort retention strategies • To assess yield of different case finding strategies and diagnostic algorithms • To assess current coverage of BCG & EPI • To build capacity for vaccine trials

• • • •

Assess TB incidence and prevalence: Cohort studies (see poster 43)

Adolescent cohort studies and neonatal cohort studies South Africa (SATVI): compare active and passive case finding strategies – ACS (n=6363) ; NCS (n = 4786) – Moyo Int J Tuberc Lung Dis 2012; Mahomed PlosOne 2013 India, Kenya and Uganda: – NCS (n~2500-2900); ACS (n~5000) – publications ongoing Excellent studies but took > 5 years to get results

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Alternative designs

Infants: – Shorter cross sectional study among infants 0-3 yr to assess period prevalence (CHC Cambodia and CISM Mozambique): challenges to assign prevalent and incident cases HIV infected adults: – Retrospective paper based cohort study to estimate TB incidence among HIV infected adults: link TB and HIV records and compare to district data (Aurum, South Africa): challenges to link records – Combined retrospective and prospective estimate of TB incidence among HIV infected persons: South Africa (Aurum) and Tanzania (Ifakara in Bagamoyo): analysis ongoing – Estimates change with IPT and ART use

No quick way to get accurate incidence estimates

• • • •

Lessons from neonatal cohort studies for trials

• • • • • Number of culture positive cases small -> adapted endpoints (Moyo 2012) Active case finding finds more cases, and they are equally severe as in passive group -> decided to use active follow-up in future trials (Moyo 2012) High mortality needs mortality reduction strategies (Nabongo submitted) High concordance TST and quantiferon, but low sensitivity for TB disease > both tests needed (Moyo 2011) Large proportion of participants was suspects and needed admission in ward; -> more efficient ways? (Moyo 2012) Importance of testing mother and infant for HIV (in prep) Relevance of surveillance of TB treatment registers (Moyo 2012) Enrollment strategies (Moyo 2012) Relevance of harmonization of CXR reading (Wajja in prep)

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Lessons from adolescent studies for trials

Proportion LTBI differed by site: in South Africa 50% (Mahomed 2011).

Adolescents with positive TST and/or Quantiferon have higher TB incidence than those with no infection at baseline (Mahomed 2011). Quantiferon converters have 9x higher risk to develop TB (Machingaidze 2012).

Relevance of surveillance site specific: in SA half the cases detected through regular health system but not in Uganda (Mahomed 2013) Differences between specific schools (Mahomed 2013) Ruler and calliper comparable for TST (Geldenhuys 2010) Low proportion smear-positive: early case finding leads to less severe cases (Waako submitted) TB among adolescents not HIV related; probably due to high transmission (Mahomed 2013, Nduba submitted, Waako submitted) High proportion non-tuberculous mycobacteria (Asiimwe 2013) Usefulness of early morning sample (Ssengooba 2013)

• • • • • • •

Learn lessons during preparatory epi studies rather than during trials*?

• Cheaper since no investigational product, less ethical requirements, less intensive follow-up for adverse events, less screen failures Do not want to make errors in trials Capacity building In infants no quick and easy way to obtain incidence; and highest in third year Adaptive designs also need some estimates Lessons applicable to several groups (eg adolescents/adults) Epi studies can identify high risk groups (smokers, urban slums) Epi studies can collect samples for biomarkers

Lessons from trials see Tameris 2012

Challenge of epi studies

• • • Define scientific objectives: – – – add on studies, biomarkers link with questions of national TB control programmes Takes more time Need to analyse data in detail to predict numbers for more strict exclusion criteria in trial

Develop trial sites

• • • • • • HIV/malaria vaccine trial sites TB epidemiology: calculate expected number of TB suspects, LTBI and TB cases by type. Clinical: CV ward, tuberculin skin testing, gastric washing, induced sputum, harmonize chest x-ray reading of non severe cases Laboratory: TB culture capacity for large number of samples with low proportion positive ; sample handling TB treatment start and follow-up for outcome Collaborate with TB control programme Community knowledge, attitudes and practice • • TB diagnostic/drug trial sites TB epidemiology: calculate expected number of TB suspects, LTBI and TB cases by type. Clinical; depends on target group • Lab: expand capacity • • Follow-up of large cohort by routine screening Community knowledge, attitude and practice & work with community in general

TB hotspots – HIV negative adults

• • • •

Find geographical hotspots within countries

Use NTP data by district/subdistrict Calculate TB incidence among HIV uninfected = A*(1-B)/C*(1-D) A = number of TB cases notified B = proportion of TB cases co-infected with HIV C = population D = proportion of the population HIV infected Limitations: differences in age, sex, underdiagnosing & underreporting of TB and HIV, mortality, population estimates Literature review on TB incidence among HIV negative persons (Mitchell et al in preparation): • Very little information: IPT trials, active case finding/screening studies, prevalence surveys Use modelling

TB incidence in trial differs from notified incidence

• • • •

Expect a decrease due to:

Strict selection criteria Exclusion of high risk groups Exclusion of prevalent cases: wash out effect Early case finding & preventive therapy • •

Expect an increase due to:

Under notification: assess by inventory studies Under diagnosis Notified cases may not cover the age category or geographical area where the trial takes place

• • • • • • Study to quantify the level of under-reporting of diagnosed cases of TB to national surveillance systems.

Compare the number of cases recorded in public and private health facilities with the records of cases notified To estimate TB incidence using capture–recapture methods.

Need 3 fairly independent data sources Use record linkage Simpler: – assess initial defaulters – Assess cases lost from hospital referrals – Collaborate private sector

Under diagnosis: develop hotspots

Improve current case finding of health system

• • • • by: Improving diagnostics establishing contact tracing Following up all suspects and make sure they do not get lost in system Needs collaboration with TB control programmes and private sector

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Acknowledgements

KNCV: Ellen Mitchell Sites: • • SATVI/UCT South Africa KEMRI/CDC, Kisumu Kenya • IDI/Makerere Uganda & TB team Iganga/Mayuge • • CISM Mozambique Aurum South Africa • Ifakara Institute Tanzania Partners/funders: • • • GSK biologicals, Belgium Aeras, USA EDCTP • • ITM Belgium Karolinska Institute, Sweden More info: [email protected]

; www.kncvtbc.org