New molecular diagnostic tests for TB: Do patients benefit?

HSRC Roundtable02 June 2014

Pren NaidooRory Dunbar, Elizabeth Du Toit, Margaret van Niekerk,

Carl Lombard, Judy Caldwell, Nulda Beyers

Background Key TB Challenges

MDR-TB Estimated global cases (2012): 450,000 Global cases reported: 94,000 Poor availability of DST contributes to the low number

of cases diagnosed

Diagnosis of smear negative TB Smear microscopy has ~ 60% sensitivity (~40% in

HIV prevalent areas)

Early adoption of molecular diagnostics by DOH Xpert MTB/RIF introduced from 2011

Efficacy of Molecular Diagnostic Tests

Cochrane Review of studies where Xpert was used as an initial test replacing smear microscopy: MTB (15 studies)

Pooled sensitivity: 88% (95%CrI 83% - 92%) Pooled specificity: 98% (95%CrI 97% - 99%)

Rif R (11 studies) Pooled sensitivity: 94% (95% CrI 87% - 97%) Pooled specificity: 98% (95% CrI 97% - 99%)

Impact Assessment FrameworkLiverpool School of Tropical Medicine

1. EFFECTIVENESS • Are the desired outcomes achieved?

2. EQUITY • Who needs the intervention most? • Who benefits? Socio-economic; gender; age, patient groups eg

HIV+ etc

3. HEALTH SYSTEM • Human resource, infrastructure• Operating procedures, procurement• M&E implications

4. SCALE-UP • Costs and benefits of scale-up

5. HORIZON SCANNING • What other options are available or likely to become available?

• How do these compare?

From: Beyond accuracy: creating a comprehensive evidence base for TB diagnostic tools Mann G et al; Int J Tuberc Lung Dis 2010;14:1518-24.

TB Testing Algorithm

Universal Algorithm: Xpert MTB/RIF™ replaced smear

All presumptive TB cases 2 sputa submitted

Specimen 1 Specimen 2

Xpert Negative Culture if HIV+

Discard if HIV-/unknown

MTB+, Rif sensitive Smear

MTB+, Rif resistant Smear, culture, LPA and 2nd line DST

Smear if only 1 sputum sample submitted

Targeted Algorithm: Smear/Culture/DST (LPA)

Low MDR-risk 2 sputa for smears (3rd for culture if Sm-, HIV+)

High MDR-risk 2 sputa for smears, Culture, LPA DST

Are More TB Cases Diagnosed?

Total Presumptive TB Cases Tested by Sub-District

0

1000

2000

3000

4000

5000

Q4 '10 Q2 '11 Q4 '11 Q2 '12 Q2 '13

A

B

C

D

E

Targeted Universal

TB Yield by Sub-District (Pos Cases/Total Presumptive TB Cases)

0

5

10

15

20

25

30

Q4 '10 Q2 '11 Q4 '11 Q2 '12 Q2 '13

A

B

C

D

E

Targeted Universal

Are More TB Cases Diagnosed?

Total MDR-TB Cases by Sub-District

01020304050607080

Q4 '10 Q2 '11 Q4 '11 Q2 '12 Q2 '13

A

B

C

D

E

Targeted Universal

Total 188 Cases Total 196 Cases

Are More MDR-TB Cases Diagnosed?

Do Patients Commence TB Treatment Earlier?

Q2 2011

Group 1 and Group 2 – Smear/Culture

0.0

00

.20

0.4

00

.60

0.8

01

.00

Pro

port

ion

sta

rtin

g tr

eat

men

t

0 10 20 30 40 50 60 70 80 90Days until starting treatment

study_arm = Group 1 study_arm = Group 2

Kaplan-Meier failure estimates

Q4 2011

Group 1 - Xpert Group 2 – Smear/Culture0

.00

0.2

00

.40

0.6

00

.80

1.0

0P

ropo

rtio

n s

tart

ing

tre

atm

ent

0 10 20 30 40 50 60 70 80 90Days until starting treatment

study_arm = Group 1 study_arm = Group 2

Kaplan-Meier failure estimates

Q2 ‘11 Q4 ‘11

Group 1 Group 2 Group 1 Group 2

Median DS-TCT (95% CI) (days) 6 (6-7) 6 (6-7) 4 (4-5) 5 (4-5)

Targeted (n=360) Universal (n=120)

Median MDR-TB TCT

(95% CI) [IQR] (days)

43 (40-46)

[IQR: 30-64]

17 (13-22)

[IQR: 7-36]

Matched analysis Mean diff: 25 days (95% CI 17-32 days) p<0.001

Median Lab TAT

(95% CI) [IQR] (days)

25 (24 -27)

[IQR:19-35]

<1 (<1-2)

[IQR<1-17]

Matched analysis Mean diff: 20 days (95% CI 14-27 days) p<0.001

0.00

0.25

0.50

0.75

1.00

Pro

por

tion

sta

rtin

g tr

eatm

ent

0 50 100 150 200Days until starting treatment

Targeted

Universal

MDR Treatment Commencement Time

0.0

00

.20

0.4

00

.60

0.8

01

.00

Pro

port

ion

re

sult

ava

ilab

le

0 20 40 60 80 100 120 140 160Days until result available

TARGETED UNIVERSAL

Kaplan-Meier failure estimatesMDR-TB Treatment Commencement Time (TCT) Laboratory Turn Around Time (TAT)

Do Patients Commence MDR-TB Rx Earlier?

Which MDR-TB Patients Benefit?0

.00

0.2

00

.40

0.6

00

.80

1.0

0P

ropo

rtio

n s

tart

ing

tre

atm

ent

0 20 40 60 80 100 120 140 160 180Days until starting treatment

TARGETED/hiv_status = negative TARGETED/hiv_status = positive

UNIVERSAL/hiv_status = negative UNIVERSAL/hiv_status = positive

Kaplan-Meier failure estimates

0.0

00

.20

0.4

00

.60

0.8

01

.00

Pro

port

ion

sta

rtin

g tr

eat

men

t

0 20 40 60 80 100 120 140 160 180Days until starting treatment

TARGETED/mdr_risk = low TARGETED/mdr_risk = high

UNIVERSAL/mdr_risk = low UNIVERSAL/mdr_risk = high

Kaplan-Meier failure estimates

p=0.056HIV+: HR 3.3 (95% CI 0.4 - 1.0)

No benefit by age, gender or HIV status

p = 0.037Low risk: HR 3.3 (95% CI:2.4-4.5)High risk: HR 2.0 (95% CI:1.4-2.8)

MDR-TB TCT by MDR-Risk ProfileMDR-TB TCT by HIV Status

TB Laboratory Costs per Algorithm (ZAR)For presumptive TB cases only

Total: R1,724,735 Total: R3,745,218

0

500 000

1 000 000

1 500 000

2 000 000

2 500 000

3 000 000

3 500 000

4 000 000

LPA R 292 522 R 93 723

Culture/auramine R 823 691 R 459 777

Direct microscopy R 608 523 R 178 723

Xpert R 3 012 995

Q2 2011 (Reflected as 2013) Q2 2013

Comparison of Median Patient Costs in the Targeted and Universal Algorithms

R 0

R 100

R 200

R 300

R 400

R 500

R 600

R 700

R 800

R 900

Targeted (n=89) R 33 R 0 R 120 R 231 R 777

Universal (n=64) R 15 R 0 R 45 R 131 R 373

Direct Transport

Costs

Direct Medical Costs

Transport time

Cost of Time in HCF

Total

Comparison of Median Patient Visits*

Median IQR Min-max P value

Targeted(n=89)

20 10-44 2-171 p<0.001

Universal(n=64)

7 4-23 2-184

*Calculated from first health care visit to any provider for current illness to MDR-TB treatment commencement

Patient’s Perspectives Many patients with previous TB identified their symptoms as attributable to TB

and went directly to the clinic for tests

“My mother said I must go to the clinic for a TB test. She was worried that I may have TB because my sister also had TB. I did not want to go, too scared that if I go for a TB tests they will also test me for HIV” (T2).

“But at all these times I was not sick it was just a cough, sweat at night and I felt that I was also losing weight nothing else, not a day I ever felt like I was sick” (T8).

“ I was having a terrible cough and I was sweating at night, but this did not ring an alarm for me, because I still thought this was just a fever and the change of season and that everything was going to be fine” (T3).

“…at the time when I started to feel sick I feel that I had to act a little bit strong not to let the family know how weak I really feel. I must not let them down. Although I could feel some pain I felt I must be a man to face this disease” (U7).

“I did not think it was serious, just thought it was a cough…Got cough meds at pharmacy… helped but coughed again…I went back again and again, got a different medication every time. I must have gone there 5 times...” (T12).

Patient’s Perspectives “I was at the day hospital for 24 hours in December and I waited for the doctor

but the doctor was busy and so they told me that I had infection in my lungs and they then gave me the drip and antibiotics…In the same month I didn’t feel so well so I went back to the same day hospital… and they gave me the same drip and antibiotics”.

“They don’t care about the patient. Once I was there and the nurses will just go on tea even if the very sick people are waiting on them. I told the nurse about a sick, old man and she said he must just wait.” T10

“After returning for my results and waiting for a long time, I was told that I needed to come back again after two days. After another two days I was told my results were not received due to a broken clinic fax machine. After this day I decided not to come back because I was waiting too long in the queue for my results and I was feeling better at this stage.”

“I was expecting long queues and sitting for ages before getting help. I am not sure what is the situations at the other clinics, but .. there was no queue and I got helped within 10 minutes…Staff in the TB room is very helpful and treats the patients with respect.” U9

Comments Summary Findings

No increase in yield for TB / MDR-TB cases 25-day reduction in MDR-TB TCT Substantial increase in laboratory costs Cost saving for MDR-TB patients Both patient and health system factors contribute to

delay

New technology on its own does not suffice Need to strengthen health systems and address

patient factors to optimise test benefits

Acknowledgements

Cape Town Health Directorate Western Cape Provincial Department of Health

National Health Laboratory Services

This research was supported by a United States Agency for International Development (USAID) Cooperative Agreement (TREAT TB – Agreement No. GHN-A-00-08-00004-00). The contents are the responsibility of the authors

and do not necessarily reflect the views of USAID.