National Survey of Drug -Resistant Tuberculosis in Chinaiom.nationalacademies.org/~/media/Files/Activity Files... ·  · 2014-11-22National Survey of Drug -Resistant Tuberculosis

National Survey of Drug-Resistant Tuberculosis in China

Dr. Yanlin Zhao National Centre for Tuberculosis Control and Prevention of

China CDC National TB Reference Laboratory , China CDC

BACKGROUND • China lists as 2nd among the 22 TB high-burden countries. • In 1979, 1984/1985, 1990, 2000, nationwide epidemiological

prevalence survey. • Prevalence survey in 2000 shows 18.6% of initial resistance

and 46.5% acquired resistance. • During 1996~2008, 13 province have taken part in drug-

resistance surveillance organized by WHO/IUATLD . Initial: 14.8%~42.1%; Acquired: 33.7%~66%

• Estimation of MDR-TB in China: 5.0%, 26%

Objectives

1. To interpret the epidemiological status of drug resistant tuberculosis in China

2. To analyze the risk factor for drug resistance occurrence among tuberculosis patients

3. To explore the predominant mycobacterium bacillus biological characteristics in China

4. To understand the micro-evolution of the prevalent strains in China.

Selection of the 70 sites

•70 clusters (sites) were selected according to new smear-positive cases reported by each province relative to the total number of cases nationwide in 2004 and 2005.

•All provinces should have at least one cluster.

1.70 clusters(counties) from all 31 provinces

2.51 smear positive new cases and 17 smear

positive retreatment cases with newly diagnosed

3. DST(proportion method) against 6 anti-TB

drugs

Method

5 1/29/2013

• Design and preparation

2 Pilots

Design and Preparation

Experience and lessons

Design and preparation

• Training objectives: all persons(about 700 persons) involved in this survey

• Training contents: Interaction method, role play and practice

Resource of reagents and disposables for the

laboratory

Anti-TB baseline survey lauching meeting ( 1st Apr. 2007)

Record files and register book

Logistics

• Monthly report • Newsletter • special email address • special fixed telephone • fixed people 24h response • established reporting and recording feedback machanism

Quality assurrance

• Leader group • Experts panel • Executive office • Standardization of definition • Standardization of methods • Standardization of the parameters of the equipment, reagents and disposals Standardization of the implementation period of the

time

Supervision Supervision for all clusters, Special supports to priority sites( 2 people from central level work in Tibet 3 weeks)

Strain files management

Strain logistic box special vehicle

Consent informs Questionaires

• Panel testing for all persons who are

responsible for DST • Panel testing from Hongkong Supernational

Reference Laboratory

Database of investigation

Data input double blinded input the data by Peking University and 100% recheck by NRL

DST work in NRL

•Lowenstein-Jensen (L-J) media and proportion method was used for DST.

•6 anti-Tb drugs were included: sonazied(INH), Rifampine(RFP),

Streptomycin(SM), Ethembutol(EMB), ofloxacin (Ofx); Kanamycin(Km)

Proficiency test for DST was done to NRL by Hong Kong Super-National reference laboratory .

10% of the isolates were randomly chosen to repeat DST , the outcome was eligible according to WHO’s guideline.

Species identification work in NRL

Selective L-J media method was used.

Case Enrollment & Culture Result

Category Anticipated# Actual Completeness Estimated∆ Culture +

New Patient 3570 3514 98.40% 3010 TB 3037

NTM 103

Treated Patient 1190 1086 91.30% 1010 TB 892

NTM 37

Total 4760 4600 96.6 4020 4069

# : considering 15% loss of samples due to failure to recover the culture or to growth of NTM. New patiens: 3010/0.85≈3570; Treated patients: 1010/0.85≈1190 ∆ : calculated under the estimation that drug resistance rate in new cases is 6% and 16% in previously treated cases, with a precision of ±1.2% / ±3.2% for CI 95% and a design effect of 2.

1. 3929 TB tested from 4069 cases

2.

3.

4. 120 thousand annually and 9 thousand cases among them are XDR patients.

Results

22 1/29/2013

Percentage of MDR-TB

New case 5.71%

Retreated case 25.64%

Total 8.32%

Percentage of XDR-TB

New case 0.47%

Retreated case 2.06%

Total 0.68%

National prevalence of drug-resistant TB: China (2007)

New cases (N = 3037)

Previously treated cases (N =892)

n (%) 95% CI n (%) 95% CI

Susceptible to all 4 first line drugs† 2009 (65.8) 62.4-69.1 417 (45.5) 40.6-50.4

Resistance to INH or RMP (not both) 338 (11.2) 8.4-14.2 141 (16.1) 8.9-24.7

Multidrug resistance (MDR) 175 (5.7) 4.5-7.0 226 (25.6) 21.5-29.8

Any resistance to OFX or KM 131 (4.2) 3.1-5.3 95 (11.4) 8.2-14.7

OFX resistance 88 (2.7) 1.8-3.6 76 (8.7) 6.1-11.2.3

KM resistance 59 (2.0) 1.4-2.6 33 (4.8) 2.5-7.2

MDR + resistance to OFX or KM 58 (1.8) 0.95-2.64 73 (8.5) 6.4-10.6

Extensively drug resistance 15 (0.47) 0.15-0.79 14 (2.1) 0.58-3.5

Zhao et al, NEJM, 2012

January 29, 2013 © 2011 Bill & Melinda Gates Foundation | 24

Previously treated MDRTB cases: last treatment completion and the location of last treatment

Zhao et al, NEJM, 2012

Risk factors for drug-resistant TB among previously treated cases

January 29, 2013 © 2011 Bill & Melinda Gates Foundation | 25

Drug-resistant TB

(non-MDR)*

Multidrug-

resistant TB†

Women 1.7 (1.1-2.7) 2.2 (1.4-3.5)

Age >60 years 0.79 (0.53-1.2) 0.42 (0.27-0.68)

Lived in area with DOTS implementation after 2000 1.4 (0.96-2.0) 1.7 (1.2-2.6)

No. of prior TB treatment episodes and medical facility

providing last TB treatment

One prior treatment and other medical facilities 1.0 (Ref) 1.0 (Ref)

One prior treatment and TB hospital 1.6 (0.70-3.5) 1.5 (0.62-3.4)

≥2 prior treatments and other medical facilities 1.5 (0.93-2.3) 3.3 (2.1-5.2)

≥2 prior treatments and TB hospital 4.0 (1.2-14) 13 (3.9-46)

Zhao et al, NEJM, 2012

Preventing MDRTB: new tools + system change

• Reduce sub-optimal treatment in CDC and hospital system by using treatment regimens based on resistance testing

• Make sure patients starting treatment in hospitals are followed up after discharge till they complete treatment; build linkage between hospital system and CDC system

• Improve treatment provided by TB hospitals: appropriate drug regimens, improved infection control, better follow-up after discharge

• Improve community case-management of patients on treatment (perhaps using adherence technology)

January 29, 2013 © 2011 Bill & Melinda Gates Foundation | 26

Patients evaluated for TB

No MDR

Routine treatment (1st-line drugs)

MDR

CDC system Specialized hospital

Patients evaluated for TB

No MDR M/XDR

M/XDR treatment (2nd-line drugs)

Effective case management in community

Building hospital-CDC collaboration to prevent and treat M/XDR TB

DOTS Program

(in CDC)

Diagnosis • Smear microscopy

Empiric treatment • Standardized regimen

using 1st-line drugs Community case-management

• Self or family members

Innovative

Program (CDC & hospital)

Molecular diagnosis • Rapid dx of TB • Rapid dx of MDR-TB

Treatment based on testing for resistance

• 2nd-line drugs for MDR • 1st-line FDC drugs for

non-MDR Technology-supported case-management

• Use of mobile phone & med monitor

Hospital-CDC collaboration

Quality-assured drugs

Financing model for MDRTB

Incentive model for HCW’s

Risk factors for drug-resistant TB among new cases

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Drug-resistant TB

(non-MDR)*

Multidrug-

resistant TB†

Women 0.90 (0.74-1.1) 1.5 (1.0-2.1)

Age >60 years 0.88 (0.71-1.1) --- ---

Occupation as non-farmer 1.2 (0.95-1.4) 1.4 (0.97-2.0)

Lived in area with DOTS implementation after 2000 0.85 (0.71-1.0) --- ---

History of treatment with TB drugs and prior TB diagnosis

No treatment (with or without a prior TB diagnosis) 1.0 (Ref) 1.0 (Ref)

Treatment of <1 month and a prior TB diagnosis 1.6 (1.1-2.1) 1.2 (0.65-2.4)

Treatment of any duration and no prior TB diagnosis 1.2 (0.86-1.5) 2.4 (1.5-3.8)

Zhao et al, NEJM, 2012

Preventing drug-resistant TB among new cases

• Who are the patients with no prior diagnosis of TB but given TB drugs? – Likely suspected to have TB and started on TB

drugs – Did not receive a diagnosis of TB because proper

diagnosis not made – Took TB drugs long enough, but improperly,

such that MDRTB developed – Mostly treated in hospital system

• Importance of performing proper diagnosis of TB

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Implications for new drug R&D • Important to “turn off the tap” of DR-TB

– Current factors causing DR-TB will lead to rapid “loss” of any new drug to resistance

• Urgency in light of new TB drugs becoming available – TMC-207, OPC67683, linozelid

– Need to improve system, adopt new diagnostics, and use new drugs in a rational manner in order to prevent DR-TB

• Level of quinolone resistance has implications for development and use of new

January 29, 2013 © 2011 Bill & Melinda Gates Foundation | 31

Questions continues…

What’s the population structure of the prevalent TB strains in China?

What advantages do they have to become the prevalent strains?

How do the prevalent strains interact with hosts and environment?

4000 TB Strains

Drug resistance pattern

Drug resistant related mutations

Spoligotyping

24 loci MIRU-VNTR plus

IS6110 RFLP

BJ/non-BJ strains Virulence & Pathogenicity

Whole Genome Sequencing SNPs

Distribution map of different spoligotypes

Phenotypic drug resistance profiles and epidemiologic data of 11 Chinese M. tuberculosis isolates

Isolates Virulence First-line drug resistancea

Second-line drug resistanceb

Type Gender Age, years Genotype

16543-1 1 INH, RIF MDR Male 86 Beijing

04243-1 2 EMB Susceptible Male 17 Beijing

05112-1 3 INH, STR, EMB, RIF MDR Female 16 Beijing

05112-4 3 INH, STR, EMB, RIF MDR Female 16 Beijing

02166-2 4 INH, STR Susceptible Female 75 Beijing

05120-2 5 INH, STR Susceptible Male 34 Beijing

16559-3 6 STR OFX Susceptible Male 63 Beijing

01105-1 7 Susceptible Male 77 Beijing

01008-4 8 STR Susceptible Male 61 Non-beijing

05116-4 9 INH, RIF MDR Female 59 Non-beijing

31211-1 10 INH Susceptible Female 18 Non-beijing

03328-3 11 INH Susceptible Male 69 Non-beijing

H37Rv 12 Susceptible Non-beijing

Table 2. Shared mutations in the high virulent strains Locus Id Nn-synonymous Mtation Fund Anotation

04243-1a 05112-1b 05112-4c 02166-2d 05120-2e 16559-3f Rv0336 Y376C Y376C Y376C 13E12 repeat family protein

Rv0515 Y376C Y376C Y376C 13E12 repeat family protein

Rv0775 R86Q R86Q R86Q R86Q hypothetical protein Rv0775

Rv1152 G105A G105A G105A G105A transcriptional regulatory protein

Rv1295 G237S G237S G237S G237S threonine synthase

Rv1588c A63T A63T A63T A63T REP13E12 repeat-containing protein

Rv1934c N102S N102S N102S N102S acyl-CoA dehydrogenase FADE17

Rv2124c Y1098D Y1098D Y1098D Y1098D 5-methyltetrahydrofolate--homocystein methyltransferase

Rv2769c A136V A136V A136V A136V PE family protein

Rv3774 G124D G124D G124D G124D enoyl-CoA hydratase

Rv2543 A138V,A139T

A138V,A139T

A138V,A139T

A138V,A139T

A138V,A139T

A138V,A139T

lipoprotein LppA

• Position of the 871 non-synonymous SNPs by excluding common SNPs in Beijing genotype and non-Beijing genotype, respectively, Positions are Relative to the M. tuberculosis H37Rv Genome Sequence (From inner to outer: 01008-4, 02166-2, 03232-3, 03328-3, 04243-1, 05112-1, 05112-4, 05116-4, 05120-2, 16559-3, 31211-1, green indicates susceptible strains, cyan indicates MDR strains)

Visible TB distribution model

大气监测数据可视化

4 dimension distribution by Genotypes

分枝杆菌迁徙可视化效果图

Acknowledgement

people who made efforts and contribution to the survey

Disease Prevention and Control Center of China (CDC)

Beijing Tuberculosis and Thoracic Tumor Institute

Peking Union Medical College of China

Beijing University of China

31 provincial TB dispensary and 70 clusters

[email protected] 010-58900777

Thank you for your attention!