Comprehensive Training Package on Active Tuberculosis Drug Safety Monitoring and Management (aDSM) 2023

Training package on active tuberculosis drug safety
monitoring and management (aDSM)
2023
 
 
 
3.3. Introduction to signal detection
 
Learning objectives
By the end of this presentation, the participant is expected to be able to:
 
1.
Describe the main aims and principles of signal
detectiona
 
2.
Describe the completion of safety profiles for new
TB drugs and regimens
 
One of the main reasons we collect aDSM data
 
Signal detection (1)
 
Reported information on a 
possible
 causal relationship between an AE
and a TB medicine
 
The relationship was 
previously unknown 
or incompletely documented
(e.g. 
a new aspect of a known association
)
 
Signal detection is based on analyses of multiple data points
 
Definition of signal
 
Reporting (1)
 
Signal detection is a continuous activity
Analysis for
completeness
consistency
timeliness
number and type of events per facility and nationwide
patterns over place and time
Related to the number of patients exposed
 
Reporting (2)
 
Construction of risk profile
Definite, probable and possible relationship
Communication to NTP and all DR-TB facilities
 
Signal detection would best be done over a large set of
observations
 
 
Data quality is reliable
 
Several reports show a credible and strong relationship between
event and drug
 
The event is of sufficient importance or interest :
to require regulatory action
to require advice to prescribers
for scientific /clinical purposes
 
Pointers for when to investigate
 
Usually >1 event with a similar, strong relationship to a medicine
(“certain” or “probable“).  Events coded as “possible” can be
used as supporting evidence
 
A cluster of unexpected deaths coded as “possible” forms an
exception to this general rule and will need to be taken seriously
 
Occasionally a single event (“certain” or “probable”) - notable
for its severity, seriousness or distinctiveness - can be regarded
as a signal
 
Features
 
Clinical assessment of individual events
Clinical review of collated events
Record linkage
Automated signal detection
 
Methods of signal identification
 
Drug-safety profile (1)
definition
 
Drug-safety profile:
A description of the benefits, risks and toxicity of a given TB drug
or regimen, specifying any known or likely safety concerns,
contraindications, cautions, preventive measures and other
features that the user should be aware of to protect the health of
a TB patient
 
Drug-safety
 profile (2)
adding new knowledge on benefits & harms
 
N
a
t
i
o
n
a
l
 
T
B
 
p
r
o
g
r
a
m
m
e
 
 
TB-MR treatment facility
Delivery of treatment
Management of adverse
reactions
Inform update of
treatment policy
and patient care
practice
(as per PMDT
guidance)
 
D
r
u
g
 
s
a
f
e
t
y
 
m
o
n
i
t
o
r
i
n
g
(aDSM Component)
Cohort-based follow-up of patients with
questionnaires to elicit symptoms; and
routine tests for TB drug safety
monitoring
 
 
Recording of all SAEs in a national
aDSM database (regularly transferred
into the global database)
Signal detection/causality assessment
by the NTP (if capacity is limited by
national pharmacovigilance system
(NPV))
Pharmaconvigilance
programme
Further analysis for signal
detection/causality assessment and
communication
New
evidence
Reporting as required by
local regulations
I
n
f
o
r
m
 
u
p
d
a
t
e
s
 
o
f
 
c
o
u
n
t
r
y
 
a
n
d
g
l
o
b
a
l
 
d
r
u
g
 
s
a
f
e
t
y
 
p
r
o
f
i
l
e
Support for signal
detection and
causality assessment
 
Creating new knowledge
 
Conclusions
 
Signal detection is an important process to improve
knowledge on the new TB medicines and complete the safety
profile of a new drug
When monitoring AEs it is important to look beyond adverse
reactions and biological pathways already linked to particular
drugs: previously unknown or rare associations may occur,
especially for newly released drugs
Reports of adverse events to the global aDSM database is
expected to improve the likelihood of picking up signals
Acknowledgements
The development of the aDSM training material was funded by TDR as part of the Access and Delivery Partnership (ADP)
with funding from the Government of Japan.
These training materials were put together in 2016 the WHO Task Force on aDSM
 with technical 
partners KNCV
Tuberculosis Foundation, Management Sciences for Health (SIAPS)
, MSF, WHO GTB, and TDR.
The materials were updated in 2022-23 by Mahamadou Bassirou Souleymane (TDR consultant) with Marie-Eve Raguenaud
(TDR), Branwen J Hennig (TDR), and Corinne Merle (TDR), and reviewed by Linh Nhat Nguyen (WHO/GTB), Medea Gegia
(WHO/GTB), and Fuad Mirzayev (WHO/GTB).
We thank all members of the WARN/CARN-TB working group on aDSM who contributed to the development of the aDSM
generic guidelines as well as the secretariat, particularly Dr Christ Houessinon
: 
Disadidi Ambrioso, Esse Marius, Adomou
Jamal Rouamba Ruffine, Haro Sougrimani, Koumbem Boureima, Nsanzerugeze Josélyne, Tollo Tollo Daniel Alphonse
Désiré, Mpaba Minkat Théophile Mistral, Julie Abessolo, Ursule IDOKO, Tijan Baldeh , Wandifa Samateh, Tida S Kinteh,
Alieu Wurie, Mardemn Yeasuen, Benjamin K. Quenneh, Cheick Oumar Bah, Kane El Hadj Malick, Aw Idriss, Mamoudou
Hama Rachida, Gagara I. M. Assiatou, Katambé Balkissa, Seiyabatou Elh Saidou, Liombo Anastasie, Lunganyu Junior,
Kitambala Sentime, Lula Yves , Habimana-Mucyo Yves, Migambi Patrick, dos Santos Brigite, Castro Vânia, Wadson Cruz,
Gueye Aminata, Mukeh Fahnbulleh, Bailor Samuel, Manjo Lamin, Saleh Mahareb Abdoulaye, Haroun Saleh Naima,
Mouhoudine Yerima, Kpelafia Silifa
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This training package focuses on signal detection in active tuberculosis drug safety monitoring. It covers the main aims and principles of signal detection, completion of safety profiles for new TB drugs and regimens, definition of signal, continuous reporting activities, construction of risk profiles, and pointers for investigation. Emphasis is placed on data quality, credibility of relationships between events and drugs, regulatory actions, and the importance of thorough observation in signal detection.

  • Tuberculosis
  • Drug Safety Monitoring
  • Signal Detection
  • TB Drugs
  • Risk Profiles

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  1. Training package on active tuberculosis drug safety monitoring and management (aDSM) 2023

  2. 3.3. Introduction to signal detection

  3. Learning objectives By the end of this presentation, the participant is expected to be able to: 1. Describe the main aims and principles of signal detectiona 2. Describe the completion of safety profiles for new TB drugs and regimens

  4. Signal detection (1) One of the main reasons we collect aDSM data

  5. Definition of signal Reported information on a possible causal relationship between an AE and a TB medicine The relationship was previously unknown or incompletely documented (e.g. a new aspect of a known association) Signal detection is based on analyses of multiple data points

  6. Reporting (1) Signal detection is a continuous activity Analysis for completeness consistency timeliness number and type of events per facility and nationwide patterns over place and time Related to the number of patients exposed

  7. Reporting (2) Construction of risk profile Definite, probable and possible relationship Communication to NTP and all DR-TB facilities Signal detection would best be done over a large set of observations

  8. Pointers for when to investigate Data quality is reliable Several reports show a credible and strong relationship between event and drug The event is of sufficient importance or interest : to require regulatory action to require advice to prescribers for scientific /clinical purposes

  9. Features Usually >1 event with a similar, strong relationship to a medicine ( certain or probable ). Events coded as possible can be used as supporting evidence A cluster of unexpected deaths coded as possible forms an exception to this general rule and will need to be taken seriously Occasionally a single event ( certain or probable ) - notable for its severity, seriousness or distinctiveness - can be regarded as a signal

  10. Methods of signal identification Clinical assessment of individual events Clinical review of collated events Record linkage Automated signal detection

  11. Drug-safety profile (1) definition Drug-safety profile: A description of the benefits, risks and toxicity of a given TB drug or regimen, specifying any known or likely safety concerns, contraindications, cautions, preventive measures and other features that the user should be aware of to protect the health of a TB patient

  12. Drug-safety profile (2) adding new knowledge on benefits & harms

  13. Creating new knowledge National TB programme Pharmaconvigilance programme Drug safety monitoring (aDSM Component) Further analysis for signal detection/causality assessment and communication TB-MR treatment facility Cohort-based follow-up of patients with questionnaires to elicit symptoms; and routine tests for TB drug safety monitoring Delivery of treatment Management of adverse reactions Reporting as required by local regulations Recording of all SAEs in a national aDSM database (regularly transferred into the global database) Signal detection/causality assessment by the NTP (if capacity is limited by national pharmacovigilance system (NPV)) Support for signal detection and causality assessment Inform updates of country and global drug safety profile Inform update of treatment policy and patient care practice (as per PMDT guidance) New evidence

  14. Conclusions Signal detection is an important process to improve knowledge on the new TB medicines and complete the safety profile of a new drug When monitoring AEs it is important to look beyond adverse reactions and biological pathways already linked to particular drugs: previously unknown or rare associations may occur, especially for newly released drugs Reports of adverse events to the global aDSM database is expected to improve the likelihood of picking up signals

  15. Acknowledgements The development of the aDSM training material was funded by TDR as part of the Access and Delivery Partnership (ADP) with funding from the Government of Japan. These training materials were put together in 2016 the WHO Task Force on aDSM with technical partners KNCV Tuberculosis Foundation, Management Sciences for Health (SIAPS), MSF, WHO GTB, and TDR. The materials were updated in 2022-23 by Mahamadou Bassirou Souleymane (TDR consultant) with Marie-Eve Raguenaud (TDR), Branwen J Hennig (TDR), and Corinne Merle (TDR), and reviewed by Linh Nhat Nguyen (WHO/GTB), Medea Gegia (WHO/GTB), and Fuad Mirzayev (WHO/GTB). We thank all members of the WARN/CARN-TB working group on aDSM who contributed to the development of the aDSM generic guidelines as well as the secretariat, particularly Dr Christ Houessinon: Disadidi Ambrioso, Esse Marius, Adomou Jamal Rouamba Ruffine, Haro Sougrimani, Koumbem Boureima, Nsanzerugeze Jos lyne, Tollo Tollo Daniel Alphonse D sir , Mpaba Minkat Th ophile Mistral, Julie Abessolo, Ursule IDOKO, Tijan Baldeh , Wandifa Samateh, Tida S Kinteh, Alieu Wurie, Mardemn Yeasuen, Benjamin K. Quenneh, Cheick Oumar Bah, Kane El Hadj Malick, Aw Idriss, Mamoudou Hama Rachida, Gagara I. M. Assiatou, Katamb Balkissa, Seiyabatou ElhSaidou, Liombo Anastasie, Lunganyu Junior, Kitambala Sentime, Lula Yves , Habimana-Mucyo Yves, Migambi Patrick, dos Santos Brigite, Castro V nia, Wadson Cruz, Gueye Aminata, Mukeh Fahnbulleh, Bailor Samuel, Manjo Lamin, Saleh Mahareb Abdoulaye, Haroun Saleh Naima, Mouhoudine Yerima, Kpelafia Silifa

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