Date post: | 02-Jan-2016 |
Category: |
Documents |
Upload: | peter-houston |
View: | 215 times |
Download: | 1 times |
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.