Haileyesus Getahun Stop TB Department WHO Intensified TB case finding among people living with HIV: what are the challenges of current strategies? 13 th.

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Presentation transcript:

Haileyesus Getahun Stop TB Department WHO Intensified TB case finding among people living with HIV: what are the challenges of current strategies? 13 th TB/HIV Core Group Meeting, April 17-18, 2008, New York, USA

Outline of presentation Global implementation of TB case finding Examples of country screening strategies Review of evidence on screening strategies Challenges Conclusions

The boundaries and names shown and the designations used on this map do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement.  WHO All rights reserved Countries with policy on intensified TB case finding among PLHIV, 2006 (N=109) No policy on ICF With policy on ICF Key

Countries reported TB screening among PLHIV, 2006 (N= 44) The boundaries and names shown and the designations used on this map do not imply the expression of any opinion whatsoever on the part of the World Health Organization concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Dotted lines on maps represent approximate border lines for which there may not yet be full agreement.  WHO All rights reserved No reported activity Countries reporting ICF Key * Brazil did not report for % of PLHIV are screened for TB globally South Africa and Russia report 68% of the screened PLHIV

Percentage of PLHIV screened for TB in countries with 80% of the global burden, 2006.

Proportion of PLHIV screened and diagnosed with TB in selected countries, % 8% 20% 31% 72%

Examples of TB screening tool from countries

National screening strategy: Rwanda 3-6 months

National screening strategy: Kenya Symptoms and signs Adults (any of) 1. Cough (of any duration)? 2. Blood stained sputum? 3. Night sweats >2 weeks 4. Fever ? 5. Weight loss? 6. Chest pain? 7. Breathlessness? 8. Fatigue? 9. History of previous TB treatment? 10. History of close contact with a person confirmed to have TB? 11. Swellings in the neck, armpits or elsewhere? 12: Diarrhea for more than two weeks? Symptom and signs Children (any of) 1. Cough: (of any duration)? 2. Blood stained sputum? 3. Night sweats >2 weeks 4. Fever? Of any duration? 5. Weight loss? 6. Chest pain? 7. Fast Breathing? 8. Fatigue? 9. History of previous TB treatment? 10. History of close contact with a person confirmed to have TB? 11. Swellings in the neck, armpits or elsewhere? 12: Diarrhea for more than 2 weeks? 13. Failure to thrive?

National screening strategy: India If any of the symptoms: Cough of 2wks and/or household contact with TB patient Hemoptysis Fever Excessive fatigue/night sweats/loss of apetite Pleuritic chest pain (increasing on cough/deep breathing) Swelling in the neck, arm pit, groin, abdomen, joints etc

National screening strategy: Tanzania Do you have the following? (one or more) 1.Cough for 2 or more wks? 2. Hemoptysis? 3.Fever for 2 or more wks? 4.Noticeable wt loss for new patients or a 3kg loss in a month? 5.Excessive sweating at night for 2 or more wks? Every month

National screening strategy: Malawi Any of the following Cough more than 3wks Weight loss Fever or night sweats Fatigue/tiredness Loss of appetite Lymph node enlargement

Observations from country practice Screening tools vary from country to country More and more non-specific constitutional symptoms and signs included in tools Children are not addressed Presence of nationally recommended screening tool does not always guarantee implementation

Review of the published evidence of TB screening strategies

Kimerling, et.al – Cambodia,2002 IJTLD 2002; 6:988–994 Population441 HIV+ in home-based care Gold stn.Single sputum culture # with TB41 (9%) with culture-confirmed TB CoughCough >3 weeks 65% sensitive, 33% specific AlgorithmAny 1 of: - cough>3 wks - hemoptysis - weight loss - fever - night sweats - weakness No information on role of CXR Sensitivity= 95% Specificity= 10%

Mohammed, et.al. – South Africa, 2004 IJTLD 2004: 8: Population129 HIV+ referred for IPT Gold stn.Definite = cx confirmed, probable = smear+, possible = clinical dx with response to treatment # with TB11 (9%) with TB (10 culture-confirmed) CoughCough >2 weeks 82% sensitive, 79% specific Algorithm2 or more of: - weight loss (>2.5%) - cough - night sweats - fever Adding CXR didn't improve performance Sensitivity= 100% Specificity= 88%

Day, et. al. – South Africa, 2006 IJTLD 2006: 10: Population899 HIV-infected miners being evaluated for IPT Gold Stn.Culture positive or clinical improvement # with TB44 (5%) patients met definition for TB, 35 culture + CoughCough >3 weeks 14% sensitive, 88% specific Algorithm Any 1 of - night sweats - new or worsening cough - weight loss >5% - abnormal CXR. Combination of - night sweats - cough - reported weight loss CXR increased the sensitivity of the screening Sensitivity= 91% Specificity= 59% Sensitivity= 59% Specificity= 76%

Chheng, et.al. – Cambodia,2008 IJTLD 2008: 12: S54-S62 Population496 HIV+ and HIV- at VCT centre (124 HIV+) Gold Stn.Sputum culture # with TB29 (6%) with culture-confirmed TB CoughCough >3 weeks 55% sensitive, 59% specific Algorithm Any 1 of: - hemoptysis - fever - weight loss - loss of appetite - night sweats Complex of: - fever - hemoptysis - weight loss BMI <18.5: Sensitivity 70%, specificity 61% No CXR was performed Sensitivity= 100% Specificity= 19% Sensitivity= 100% Specificity= 20%

Demissie, et.al. – Ethiopia World Lung Health Conference 2007 Abstract S11 SettingAddis Ababa, Ethiopia – community hospital Study pop.438 newly diagnosed HIV+ Gold Stn.Concentrated sputum smear and culture # with TB32 (7%) with culture-confirmed TB CoughCough> 2 wks is 44% sensitive, 76% specific AlgorithmCough or fever – 75% sensitivity, 57% specificity CXR improved sensitivity to 91% (at a cost of specificity)

Cain, et.al.Thailand, Cambodia, 2008 World Lung Health Conference 2007 Abstract S11 Study Pop.951 newly diagnosed or newly presenting HIV + TB definCulture positive # with TB66 (7%) with culture-confirmed TB CoughAny (71% sensitivity, 56% specificity) More than 2 wks (29% sensitive, 85% specific) More than 3 wks (24% sensitive, 91% specific) Algorithm Any 1 of: - cough - fever - weight loss Other symptoms: Loss of appetite, weight loss, difficulty breathing, fatigue, fever, shaking chills, night sweat, chest pain, abdominal pain,nausea / vomiting Sensitivity= 91% Specificity= 33%

Recalculation on the published algorithms using Thailand and Cambodia data (Courteousy of Cain & Varma, 2008) AlgorithmSensitivitySpecificity Day (cough, NS, wt. loss)86 (59*)34 (76) Mohammed (any 2 of: cough, NS, fever, wt. loss >2.5%) 74 (100)61 (88) Kimerling (any 1 of cough >3 wks, hemoptysis, wt. loss, fever, NS, weakness) 82 (100)45 (10) Chheng (hemoptysis, wt. loss, fever) 82 (100)47 (20) Demissie (cough or fever)89 (75)43 (57) * In Blue are original figures

AlgorithmCD4 < 250CD4 >250 SensitivitySpecificitySensitivitySpecificity Day Mohammed Kimerling Demissie Pre-IPT Cough/fever /wt. loss Recalculation of published algorithms using Thailand and Cambodia data (Courteousy of Cain & Varma,2008)

Observations from available evidence Findings are generally inconsistent Chronic cough more than 2 or 3 wks alone looks insensitive predictor of TB in PLHIV Role of CXR is not clear and inconsistent

Challenges: "Sub-clinical" TB in PLHIV Lucas et al. AIDS 1991 (Cote D’Ivoire) Mtei et al. Clin Infect Dis 2004 (Tanzania) Day et al. Int J Tuberc Lung Dis 2006 (S. Africa) Wood et al. AJRCCM 2007 (S. Africa) Corbett et al. PLoS Med 2007 (Zimbabwe)

Challenge: implementation issues Standardised screening tool needed but is there enough evidence to develop an optimal one? Screening tool that can rule out active TB disease is needed and how best to link it with IPT? Who administers the standard tool and where? How often should it be administered? Monitoring and evaluation- how should it be recorded and reported?

Conclusions TB screening among PLHIV is poorly implemented and requires urgent action Standardised screening tool is needed but there is no complete evidence to develop one Massive research efforts to develop the best and feasible screening tool are urgently needed Interim tool through meta-analysis of existing data need to be explored through collaboration "TB dipstick test"- simple and rapid tool is crucial