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Tubercolosi: le nuove sfide di una vecchia malattia
Andrea GoriDivision of Infectious Diseases,"San Gerardo" Hospital,University of Milano-BicoccaMonza (Milano)[email protected]
Lecco, 05 Novembre 2016
… una vecchia patologia emergente?
− 3 pandemie (HIV, Malaria e TB) 6 Milioni all’anno
− 1,6 Milioni per TB all’anno
− 5.000 morti per TB al giorno
− 5 epidemie di SARS al giorno
− 25 epidemie di avaria al giorno
− 50 epidemie di ebola al giorno
− 3 Titanic al giorno
− 15 Jambo Boing 747 al giorno
Casi di TBC nel quinquennio precedente (1988-1992)
0
5
10
15
20
25
30
35
40
1988 1989 1990 1991 1992
Casi TBC
1993 1994 1995 1996
Coinfezione HIV & TB
INFEZIONE DA HIV
TUBERCOLOSI
Casi di TB attesi e osservati, USA 1980-97
80 82 84 86 88 90 92 94 96
Impact of HIV on TB in Africa
Notified cases per 100,000 pop. 1980-2008
Percentage of global estimated HIV-positive TB cases
EMR
Cameroon
Thailand
Brazil
Democratic Republic of the Congo
China
Myanmar
EUR
Côte d'Ivoire
Malawi
United Republic of Tanzania
AMR
Zambia
WPR
Ethiopia
Mozambique
Kenya
Uganda
Zimbabwe
Nigeria
India
SEA
South Africa
AFR
1% 5% 10% 20% 50% 90% 0
100
200
300
400
500
600
700
1980 1984 1988 1992 1996 2000 2004 2008
Botswana
Côte d'Ivoire
DR Congo
Gabon
Guinea
Kenya
Malawi
Mozambique
South Africa
UR Tanzania
Zimbabwe
• 79% of all TB/HIV cases world-wide are in Africa• 50% of all TB/HIV cases world-wide in 9 African countries• 23% of the estimated 2 million HIV deaths due to TB
J Infect Dis 1997 Sep;176(3):637-42Nosocomial spread of human immunodeficiency virus-related multidrug-resistant tuberculosis in Buenos Aires, 1994-1995
Ann Ital Med Int 1998 Jul-Sep;13(3):139-45Mycobacterium tuberculosis drug resistance in patients with HIV and pulmonary tuberculosis infections in Rome: 1987-1996
MMWR 1990 Oct 12;39(40):718-22Nosocomial transmission of multidrug-resistant tuberculosis to health-care workers and HIV-infected patients in an urban hospital--Florida, 1988-1990
J Hosp Infect 2001 Feb;47(2):91-7Investigation and control of a large outbreak of multi-drug resistant tuberculosis at a central Lisbon hospital, 1995-1996
MMWR 1992 Jul 17;41(28):507-9Transmission of multidrug-resistant tuberculosis among immunocompromised persons in a correctional system--New York, 1991
Nosocomial MDR-TB outbreaks during the pre-HAART period
MMWR 1996 Apr 26;45(16):330-3Multidrug-resistant tuberculosis outbreak on an HIV ward--Madrid, Spain, 1991-1995
…how many drugs do we need?
TB Bacteria: Classification/Definitions
XDR-TB: definitions
XDR (3/06/06) -MDR TB + resistance to > 3/6 of major classes of 2nd-line drugs
-Need >four 2nd-line drugs for RX
XDR (since 10/06) –MDR TB + resistance to at least Fq & any injectable 2° -line (amikacin, kanamycin, capreomycin)
-Treatment outcomes (Latvia) ~ 60% vs <30%
CDC 2006
XDR
MDR1
MDR2
Mortality analysis: HIV+ vs HIV- patients
AIDS 1998,12:1095-1102 and CID 2002, 34
0%
20%
40%
60%
80%
100%
T0 10 weeks 20 weeks 30 weeks 40 weeks 50 weeks
HIV+ MDR-TB Milan1996
HIV+ Milan 2002
HIV- Atlanta 1994
HIV- Atlanta 1997
Emergence of MDR (XDR)-TB outbreaks(Lombardia, 1993-1998)
MDR M. tb Outbreak
Genotype: Type 20
Hospitals involved: 5
N° cases: 28
MDR M. tb Outbreak
Genotype: Type 65
Hospitals involved: 6
N° cases: 29
'94
'94
'94
'95
'96
'95
'92
MDR M. tb Outbreak
Genotype: Type 1
Hospitals involved: 11
N° cases: 157
MDR M. tb Outbreak
Genotype: Type 23
Hospitals involved: 2
N° cases: 17
MDR M. tb Outbreak
Genotype: Type 580
Hospitals involved: 3
N° cases: 28
Incidence of XDR tubercolosis in HIV+ patients (Milano, 1988-2006)
HAART
PRE-HAART
POST-HAART
HIV infection could be successfully treated
Incidence of XDR tubercolosis in HIV+ patients (Milano, 1988-2006)
HAART
0
10
20
30
40
50
60
70
80
tot
HIV
immigrati
MDR
pa
zie
nti
Impatto della trasmissione di TB tra pazienti
HIV+ e la popolazione generale
Impatto della trasmissione di TB tra pazienti
HIV+ e la popolazione generale
0
10
20
30
40
50
60
70
80
tot
HIV
immigrati
MDRpa
zie
nti
0
3
6
9
12
15
18
21
1994 1995 1996 1997 1998 1999 2000 2001
pa
zie
nti
0
5
10
15
20
25
30
35
40
1994 1995 1996 1997 1998 1999 2000 2001
pa
zie
nti
0
4
8
12
16
20
24
28
32
1994 1995 1996 1997 1998 1999 2000 2001
pa
zie
nti
TB in pazienti italiani e immigrati: (Milano, 1990-2001)
0%
20%
40%
60%
80%
100%
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001
Pazienti italiani Pazienti immigrati
Rapporto Italiani/Immigrati (Milano 1989-2005)
0%
20%
40%
60%
80%
100%
1989 1991 1993 1995 1997 1999 2001 2003 2005
Italiani
Immigrati
Variabilità dei dati nelle diverse realtà geografiche
Non esiste una “omogeneicità dei flussi migratori nelle diverse realtà geografiche
Roma: prevalenza di Polacchi
Brescia: prevalenza di Senegalesi
Bologna: prevalenza di Pachistani
Veneto? Campania?
Modificazione della trasmissione di TB in relazione alle diverse etnie
0
50
100
150
200
250
300
altro
Est Europa
Brasile
Perù
Cina
SudEst Asia
India
Est Africa
West Africa
Nord-Africa
Un altro modo di vedere la terra…
XDR TB in KwaZulu-Natal South Africa
Spread of MDR e XDR-TB in HIV+
Franzetti et al. CID, 1999 e Gandhi et al, Lancet 2006
Milano 1992-1996(Franzetti et al.)
SudAfrica 2005(Gandhi et al.)
Pts with XDR-TB 90 53
Pts with a previous hospital admission
70% 67%
Prevalence of XDR-TB 43%
(among TB in HIV+ve pts)
39%(among overall TB pts)
Median CD4 cell count 12 43
Median survival time 94 days 16 days
Mortality (at 1 year) 93% 98%
Clustered strains by genotyping analysis
88% 85%
Factors contributing to the spread of XDR tuberculosis in the Milan
Overcrowded infectious disease wards inadequate compliance with infection control procedures
Poor adherence to treatment
Prolonged hospitalisation favouring exposure between patients
Delays in diagnosis
Obtainment of drug susceptibility test results
HAART unavailability
Adherence to basic administrative and source-control
measures
cough-inducing procedures in TB suspects
protocol for early diagnosis
placement of patients in single rooms
negative pressure rooms was made available for patient isolation
Control measurements implementation
… It is therefore arguable that final eradication of the outbreak was favoured by the use of HAART
s
i
v
e
R
e
s
i
s
t
a
n
c
e
t
o
S
e
c
o
n
d
-
L
i
n
s
i
v
e
R
e
s
i
s
t
a
n
c
e
t
o
S
e
c
o
n
d
-
L
i
n
XDR a worldwide issue
Patients XDR infected (Uzbekistan)
13 top settings with highest % of MDR-TB among new cases, 2001-2010
16.5
19.2
19.3
19.4
20.0
22.3
23.8
27.3
28.3
15.4
14.8
16.0
16.1
0 5 10 15 20 25 30
Tashkent, Uzbekistan (2005)
Estonia (2008)
Donetsk Oblast, Ukraine (2006)
Mary El Republic, Russian Federation (2008)
Dushanbe city and Rudaki district, Tajikistan (2009)
Belgorod Oblast, Russian Federation (2008)
Kaliningrad Oblast, Russian Federation (2008)
Republic of Moldova (2006)
Ivanovo Oblast, Russian Federation (2008)
Baku city, Azerbaijan (2007)
Arkhangelsk Oblast, Russian Federation (2008)
Pskov Oblast, Russian Federation (2008)
Murmansk Oblast, Russian Federation (2008)
35.3Minsk, Belarus (2010)Preliminary results
Efficacy of TB control measurements
“The Case of Peru”
Pu
lmo
nary T
B c
ases/
10
0,0
00
World Health Organization
50
100
150
200
250
1975 1980 1985 1990 1995 2000 2005
Case finding
Treatment success 86% globally
Global WHO Regions
8584
86 86
83
80
75
80
85
90
2003 2004 2005 2006 2007 2008
Tre
atm
en
t su
ccess r
ate
(%
)
Progress in most regions, but Europe lagging behind
65
70
75
80
85
90
95
2003 2004 2005 2006 2007 2008
W. Pacific
SE Asia
EMR
Africa
93
88
80
Americas
77
66
Europe
La strada per arrivare ai farmaci può essere un percorso ad ostacoli
Inaccessibilità dei servizi
Disinformazione
Stigma
Ineguaglianze
Costi economici della diagnosi
Liste di attesa
Impreparazione
Mancato coordinamento
Inefficace coinvolgimento del settore privato
Risorse insufficienti
Obiettivi dello studio
− Stimare il ritardo diagnostico e terapeutico nei pazienti con tubercolosi in Italia
− Descrivere le modalità di accesso alle cure e le eventuali occasioni mancate di diagnosi
− Identificare i fattori epidemiologici, sociali e clinici associati al ritardo
Materiali e metodi
• Studio multicentrico prospettico osservazionale sul territorio nazionale:
– Clinica di Malattie Infettive, H “San Gerardo” di Monza
– Clinica di Malattie Infettive, H “Luigi Sacco” di Milano
– Istituto “Villa Marelli” di Milano
– Clinica di Malattie Infettive, Spedali Civili di Brescia
– Clinica di Malattie Infettive, H “San Martino” di Genova
– Clinica di Malattie Infettive, Policlinico Gemelli di Roma
– UO Pneumotisiologia dell’ Ospedale Fallacara, Bari
Definizione di ritardato accesso alla terapia
RITARDO
DIAGNOSTICO
RITARDOTERAPIA
Tempo intercorso fra l’insorgenza dei sintomi e la diagnosi di micobatteriosi
polmonare
Tempo intercorso fra la diagnosi di micobatteriosi polmonare e
l’avvio del trattamento specifico
Definizione di ritardato accesso alla terapia
Tempo intercorso fra l’insorgenza dei sintomi e il I contatto con un sanitario
Tempo intercorso fra la diagnosi e l’avvio del trattamento
specifico
RITARDO
STRUTTURA
Tempo intercorso fra il I contatto e la diagnosi di micobatteriosi
polmonare
RITARDO
PAZIENTE
RITARDOTERAPIA
Ritardo diagnostico
Ritardo
(settimane) Totale Per sede Provenienza
Mediana(IQR)
PolmonareNon
polmonareItaliano Non italiano
Ritardo diagnostico
Ritardo paziente
Ritardo struttura
7.5 (3-18.5)
1 (0-5)
4 (0-13)
5 (2-10)*
0.5 (0-4.5)
1.5 (0-5.5)§
19 (7-33)*
1 (0-5)
17 (7-22)§
6 (3-22)
0 (0-3)
5 (1-12)
7.5 (3-18)
1 (0-7)
3 (0-13)
Ritardo terapia 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-0) 0 (0-0)
* Wilcoxon P= <0,001; § Wilcoxon P= <0,001;
Percorso diagnostico
• 3/30 (10%) sospetto diagnostico
immediato
• Nei restanti casi, mediamente 4,4
valutazioni prima della diagnosi.
• 14/31 (45%) sospetto diagnostico
immediato
• Nei restanti casi, mediamente 2,7
valutazioni prima della diagnosi.
• 12/20 (60%) sospetto diagnostico
immediato
• Nei restanti casi, mediamente 2,5
valutazioni prima della diagnosi.
Fattori associati al ritardo diagnostico
− A differenza di altre casistiche, in Italia il ritardo diagnostico sembrerebbe essere principalmente sostenuto dal ritardo di struttura
− I pazienti che si rivolgono a strutture ospedaliere emedici specialistici hanno minor ritardo diagnostico
− differente gravità dei sintomi iniziali?
− precoce avvio verso esami specialistici?
TB care and
control
Development agenda
Research sensu lato
Health systems
and policies Free services, labs, quality
drugs, regulated private care,
better M&E
New tools
Operational research
Transfer of technology4444
Innovative Actions Needed in 4 Areas
Early & increased case detection: new
tools
Scale-up TB/HIV and MDR-TB
interventions
M&E and impact measurement
Engage all care providers
Active screening among at-risk
populations
Socio-economic factors:
living conditions, food
insecurity, awareness, risk
behaviour, access to care
MDR-TB, Multi drug resistant TB
M&E, Monitoring and evaluation
Innovative action needed in 4 spheres
Dal Mondo alla “Nostra” Africa
Acknowledgements
Clinical managementAntonio MuscatelloSilvia CostarelliLuca BisiAnna CappellettiSergio ForestiGiuseppe LapadulaSebastiano LeoneMarco MigliorinoAlessandro PerrettiFrancesca SabbatiniAlessandro SoriaAlberto DolaraMarianna RossiNicola SquillaceAlessandra Bandera
Data retrieval and analysisDavide MangioniSilvia Limonta
Statistical analysis (IRCCS Mario Negri)Liliane Chatenaud
Study coordinatorsValeria PastoreElena Cappelletti
Samples managementIlaria Beretta
Study nursesMarzia FiorinoPatrizia Acquaviva
Division of Onco-Haemathology, “San Gerardo” Hospital, University Milano-BicoccaMonza, ItalyLuisa VergaFausto RossiniPietro PioltelliEnrico Pogliani
Division of Division of Pathology, “San Gerardo” Hospital, University Milan-BicoccaMonza, ItalyAmbrogio BrennaSerena CuttinGiorgio Catoretti
Division of Microbiology and Virology Laboratories, “San Gerardo” Hospital, Monza, ItalySergio MalandrinAnnalisa Cavallero
Department of Surgery, “San Gerardo” Hospital, Monza, ItalyMarco PoleseVittorio Giardini
Haemathology and Transfusion Center, “San Gerardo” Hospital, Monza, ItalyPaolo PerseghinArianna Incontri
Institute of Clinical Infectious Diseases Catholic University of Sacred Heart, Rome, ItalySimona DigiambenedettoAndrea De LucaRoberto Cauda
Chair of Immunology,University of Milan, Milan, ItalyDaria TrabattoniMarina SaresellaMara BiasinMario (Mago) Clerici
Division of Infectious Diseases, “L. Sacco” Hospital, Milan, Italy,Stefania PiconiPaolo BonfantiGiuliano Rizzardini
Clinic of Infectious Diseases, “San Paolo” Hospital, University of MilanMilan, ItalyGiulia Marchetti Camilla TincatiAntonella d’Arminio Monforte
Back up Slides
Molecular epidemiology of tuberculosis spreading in European metropolitan
areas
Andrea GoriDivision of Infectious Diseases,"San Gerardo" Hospital,University of Milano-BicoccaMonza [email protected]
Individual patients/strains in the DB
5823 records
8 cities
2009-2012 (Jun)
TB PAN-NET: Work Package 1
- A.O. San Gerardo, Monza
- Fondazione Centro S. Raffaele,
Università Vita Salute, Milano
- Queen Mary and Westfield College,
University of London
- Forschungszentrum , Borstel,
Leibeniz-Zentrum fur Medizin
Biowissenschaften
- Swedish Institute for
Infectious Diseases Control
- Institut Pasteur, Lille
- Scientific Institute of Public
Health, Institute Pasteur
- Tartu University Hospital
- State Agency of Tuberculosis
and Lung Diseases
- Institute of Biotecnology
- National Tuberculosis and
Infectious Diseases HospitalGori A, et al. 2015
Individual patients/strains in the DB
Gori A, et al. 2015
6823 patients
Overall drug susceptibility
− 465 MDR (9%)− 183 mono INH-R− 96 mono RIF-R− 403 other R patterns
Gori A, et al. 2015
Risk factors distribution
Vilnius Tartu Brussels Milan
Alcohol abuse 41.2% 46.5% 3.7% 1.6%
Homeless 7.6% 7.3% 3.8% 4.1%
Drug abuse 1.3% 6.7% 1.1% 0.2%
Recent detention 2.3% 14.8% 1.9% 0.6%
HIV AbPositiveNegativeUnknown
1.3%61.4%37.3%
11.4%84.2%4.4%
6.6%61.3%32.1%
3%49.6%47.4%
Prevalence of different resistant patterns
Resistance pattern
Vilnius Tartu Hamburg Brussels Stockholm London
Susceptible 144 (48.6) 464 (56.0) 336 (89.8) 554 (80.1) 333 (84.1) 1242 (86.7)
INH resistance 47 (15.9) 54 (6.5) 17 (4.5) 35 (5.1) 49 (12.4) 62 (4.3)
RIF resistance 0 5 (0.6) 0 4 (0.6) 0 69 (4.8)
DIF resistance 21 (7.1) 41 (4.9) 18 (4.8) 71 (10.3) 1 (0.3) 24 (1.7)
MDR 84 (28.4) 265 (32.0) 3 (0.8) 28 (4.0) 13 (3.3) 36 (4.5)
Total 296 829 374 692 396 1433
− 6671 (97.4%) antibiograms
Gori A, et al. 2015
Prevalence of different resistant patterns
Resistance pattern
Vilnius Tartu Hamburg Brussels Stockholm London
Susceptible 144 (48.6) 464 (56.0) 336 (89.8) 554 (80.1) 333 (84.1) 1242 (86.7)
INH resistance 47 (15.9) 54 (6.5) 17 (4.5) 35 (5.1) 49 (12.4) 62 (4.3)
RIF resistance 0 5 (0.6) 0 4 (0.6) 0 69 (4.8)
DIF resistance 21 (7.1) 41 (4.9) 18 (4.8) 71 (10.3) 1 (0.3) 24 (1.7)
MDR 84 (28.4) 265 (32.0) 3 (0.8) 28 (4.0) 13 (3.3) 36 (4.5)
Total 296 829 374 692 396 1433
− 6671 (97.4%) antibiograms
Gori A, et al. 2015
MDR-TB in the TB PAN-NET database
Epidemiological characteristics of MDR-TB
n % 95% CI
Foreignborn 61 16.2 12.8-20.2
Lived in healthcare facilities 12 3.2 1.8-5.5
Homeless 35 9.3 6.8-12.6
Have been in detention 49 13.0 10.0-16.8
Alcohol abuser 182 48.3 43.3-53.3
Drug abuser 21 5.6 3.7-8.4
HIV Positive 38 10.1 7.4-13.5