Haileyesus GetahunStop TB Department

WHO

Intensified TB case finding among people living with HIV: what are the

challenges of current strategies?

13th 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 2006. 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 2006. All rights reserved

No reported activity

Countries reporting ICF

Key

* Brazil did not report for 2006

• 0.96% 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,

2006.1.83

0.00

0.77

0.00 0.00 0.05 0.00

1.07

0.00 0.00

0.31

0.00

0.78

0.96

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

1.80

2.00

Proportion of PLHIV screened and diagnosed with TB in selected

countries, 2006

0

20,000

40,000

60,000

80,000

100,000

120,000

South Africa Mozambique India Ethiopia Rwanda

PLHIV screened for TB

PLHIV with TB after screening

29%

8%20% 31% 72%

Examples of TB screening tool from countries

National screening strategy: Rwanda

3-6 months

National screening strategy: Kenya

Symptoms and signsAdults (any of)

1. Cough (of any duration)?2. Blood stained sputum?3. Night sweats >2 weeks4. 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 signsChildren (any of)

1. Cough: (of any duration)? 2. Blood stained sputum?3. Night sweats >2 weeks4. 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

Population

441 HIV+ in home-based care

Gold stn. Single sputum culture

# with TB

41 (9%) with culture-confirmed TB

Cough Cough >3 weeks 65% sensitive, 33% specific

Algorithm

Any 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: 8:792-795

Population

129 HIV+ referred for IPT

Gold stn. Definite = cx confirmed, probable = smear+, possible = clinical dx with response to treatment

# with TB

11 (9%) with TB (10 culture-confirmed)

Cough Cough >2 weeks 82% sensitive, 79% specific

Algorithm

2 or more of: - weight loss (>2.5%) - cough - night sweats - feverAdding CXR didn't improve performance

Sensitivity= 100%Specificity= 88%

Day, et. al. – South Africa, 2006IJTLD 2006: 10:523-529

Population 899 HIV-infected miners being evaluated for IPT

Gold Stn. Culture positive or clinical improvement

# with TB 44 (5%) patients met definition for TB, 35 culture +

Cough Cough >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

Population 496 HIV+ and HIV- at VCT centre (124 HIV+)

Gold Stn. Sputum culture

# with TB 29 (6%) with culture-confirmed TB

Cough Cough >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. – EthiopiaWorld Lung Health Conference 2007 Abstract S11

Setting Addis Ababa, Ethiopia – community hospital

Study pop.

438 newly diagnosed HIV+

Gold Stn. Concentrated sputum smear and culture

# with TB 32 (7%) with culture-confirmed TB

Cough Cough> 2 wks is 44% sensitive, 76% specific

Algorithm Cough or fever – 75% sensitivity, 57% specificityCXR 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 defin Culture positive

# with TB 66 (7%) with culture-confirmed TB

Cough Any (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 lossOther 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)

Algorithm Sensitivity Specificity

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

Algorithm CD4 < 250 CD4 >250

Sensitivity

Specificity

Sensitivity

Specificity

Day 97 31 70 39

Mohammed

92 51 48 67

Kimerling 92 35 67 54

Demissie 95 37 81 47

Pre-IPT 92 51 52 64

Cough/fever/wt. loss

97 27 81 37

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