Transcript WHO training, Pretoria, SA Jens D. Lundgren, MD, DMSc Director, Copenhagen HIV Programme (044) Hvidovre University Hospital, 2650 Hvidovre, Denmark www.cphiv.dk; e-mail: [email protected].

WHO training, Pretoria, SA
Jens D. Lundgren, MD, DMSc
Director, Copenhagen HIV Programme (044)
Hvidovre University Hospital,
2650 Hvidovre, Denmark
www.cphiv.dk; e-mail: [email protected]
Copenhagen HIV
Programme
• Research unit at University of Copenhagen (located at
Hvidovre University Hospital)
• Coordinating centre for:
• Randomized controlled trials (RCT’s)
• COLATE, MaxCmin 1&2
• NIH-sponsored: ESPRIT, SILCAAT,
SMART
• Network: +300 clinics on 5 continents
• Cohort studies
• EuroSIDA (since 1994)
• Data collection of Adverse events of antiHIV drugs (D:A:D)
• Network: +200 clinics on 3 continents
Agenda for 3 sessions
• ADR from ART – examples
• The risk:benefit ratio of ART
• Methods to identify and understand AE’s in
addition to spontanous reporting
• Networking nationally and internationally
• Terminology
– ART=antiretroviral treatment
– ARV’s=antiretroviral’s (i.e. drug’s used as part of ART)
Global effort to collect ADRs
of ART
WHO course, Pretoria, SA
September 2004
Anti-HIV agents: 2004
Nucleo(t)side reverse Non-nucleoside
Protease
transcriptase
reverse
inhibitors (PI’s)
inhibitors (NRTI’s)
transcriptase
inhibitors (nNRTI’s)
Zidovudine (AZT)(’87) Nevirapin (´98)
Didanosine (ddI)(´91) Efavirenz (´99)
Zalcitabine (ddC)(’92) (TMC 125 (’05))
Lamivudine (3TC)(’96)
Stavudine (d4T) (’97)
Abacavir (1592)(´98)
Tenofovir (’02)
Fusion inhibitors: T-20 (’03)
Integrase inhibitors: ? (’03)
Ritonavir (´96)
Indinavir (´96)
Saquinavir (´96)
Nelfinavir (´97)
Lopinavir (’00)
Amprenavir (’01)
Fos-amp. (´03)
Italian
Cohort
I
Main reasons of discontinuation
of first HAART regimen within
1st year: ICONA
C O
N A
Naive
Antiretroviral
Toxicity
Failure
Non-adherence
Other
Continued
Monforte et al. AIDS 1999
Side effects of anti-HIV drugs
• Early onset
– Varies by drug: GI, renal, CNS, rash, liver
• Late onset
– peripheral neuropathy
– osteopenia
– liver toxicity
– altered fat distribution
– elevated lactic acid levels
– diabetes mellitus
– lipid changes in blood
– (cardiovascular disease)
(AZT-nonAZT) difference
(and 95% CI) of one-year
change in haemoglobin
Oz-1 (n=105)
Oz-2 (n=61)
START I & II (n=301)
BMS-148 (n=705)
BMS-152 (n=491)
Combined (n=1663)
-2
-1,5
-1
-0,5
0
0,5
Differences in Haemoglobin (g/dl) at 1 year
Moyle et al, 4th IWADRL, 2002
Abacavir hypersensitivity
reaction (HSR)
• Symptoms: Fever, rash, malaise
• Risk: From 1-8 (10) weeks from start. If HSR,
exposure is associated with immediate death
• Presence of HSR and HLA-B*5701 status
Mallal et al, Lancet 2002):
• B*5701 pos:
14/18 (78%)
• B*5701 neg:
4/167 (2%)
• Reduction of prevalence of HSR by denying
patients with HLA-B*5701, HLA-DR7, HLADQ3 abacavir:
• 9% to 2.5%
Proportion of subjects without a grade 3/4 AE
Time to initial grade 3 or 4 AE
Adverse events
1.00
Saquinavir/r
0.75
Indinavir/r
0.50
P = 0.0002 (log rank test)
0.25
0.00
0
4
12
24
36
48
Time (weeks)
MaxCmin1: Dragsted et al, JID, 2003
Retinoid syndrome
• Nails deformation, hair loss, dry lips or skin, itchy skin,
eczema or ulcers
• Assessment using a LDCD Study type questionnaire, i.e.
both worsening and improvement of symptoms
– At Week 24 and 48
– Patient’s and physician’s assessment of improvements
and worsening
• Cases defined at least moderate symptoms of retinoid
worsening at one or more sites
Retinoid status at Week 48
N
Randomized Treatment Gr
242
IDV/rtv
(n=124)
Cases (%)
98 (40%)
76 (61%)
23 (19%)
Non-cases
(%)
144 (60%)
48 (39%)
97 (81%)
p-value
SAQ/rtv
(n=120)
<
0.0001
The BEST Study: Treatment Arms
TID group. Continue with:
Indinavir 800 mg TID in combination with same 2 NRTIs
BID group. Switch to:
Indinavir 800 mg BID + Ritonavir 100 mg BID (liquid
formulation) in combination with same 2 NRTIs
Arnaiz et al, AIDS, 2003
Nephrolithiasis/haematuria: time to development
100
% p atien ts affected
90
80
70
60
B ID
50
T ID
40
30
20
10
0
0
1
2
3
4
5
6
7
8
9 10 11 12
M o n th s sin ce ran d o m izatio n
Abnormal fat distribution
Lipoatrophy in face
Lipoatrophy on arms
Lipoatrophy on legs
Both increased fasting and 2-hour
insulin levels are evidence of insulin
resistance in lipodystrophy
mIU/mL
90
80
70
60
50
40
30
20
10
0
P<0.05
Lipodystrophy
(n=71)
Control (n=213)
P<0.05
Fasting
Insulin
2-hour
Insulin
Hadigan et al, CID; 32:130
D:A:D
Baseline Risks for CVD
Family history of CHD
Previous CVD
Smoking
Hypertension
Obesity
Diabetes mellitus
Elevated total chol.
Elevated triglyc.
0
10
20
% of total
30
40
50
60
AIDS 2003; 17(8): 1179-94
Lipid elevation and ART status
at baseline in D:A:D
ART Naive
Elevated total cholesterol
No current ART
Elevated triglycerides
NRTI only
NRTI + NNRTI
NRTI + PI
NRTI + PI + NNRTI
0
10
20
% of all in stratum
30
40
50
60
AIDS 2003; 17(8): 1179-94
D:A:D
Cholesterol elevation, ART, CD4
60,0
50,0
% with
elevated
total
cholesterol
40,0
30,0
20,0
NRTI+PI+NNRTI
NRTI+PI
NRTI+NNRTI
10,0
NRTI
0,0
No ART
<100
Baseline
CD4 count
100200
Naïve
200300
300400
>400
ART status
at baseline
AIDS 2003; 17(8): 1179-94
Study 903
Mean (95%CI) Change from Baseline in
Triglycerides
Wk 48, p < 0.001
Change from Baseline (mg/dL)
110
100
– d4T+3TC+EFV
90
– TDF+3TC+EFV
80
70
74 mg/dL
60
50
40
30
20
10
0 mg/dL
0
-10
-20
BL 2
4
8
12
16
20
24
28
32
36
40
44
48
Week
Staszewski et al, XIV IAC, LBOr17
Metabolic and Physiognomic Changes in
HIV Patients Receiving Antiretroviral
Therapy
Lipid
abnormalities
Dysregulation
of glucose
metabolism
Fat
accumulation
Fat
atrophy
• 1 syndrome or several?
• 1 etiology or multifactorial?
Cardiovascular disease as a
late - rather than early - onset side effect
• Proposed mechanism for anti-HIV therapy
induced increased risk is indirect
– altered glucose metabolism
– increase in cholesterol and triglycerid levels
– altered fat distribution
• Congitive dyslipidaemia - onset of clinical
symptoms: 8-10 years
• Emigration from low to high prevalence areas: 23 generations
• Treatment of dyslipidaemia: effect after 2-4 years
D:A:D
MIs per
1,000 PY
(95% CI)
8
MI by CART exposure
7
6
5
4
3
2
1
Test for trend
p<0.00001
0
Years on CART
No. MIs
No. PY
None
<1
1-2
2-3
3-4
>4
3
5,714
9
4,140
14
4,801
22
5,847
31
7,220
47
8,477
Total
126
36,199
N Engl J Med. 2003;349 (21)
D:A:D
Independent predictors of MI
Adjusted RR 1.26
(95% CI: 1.12-1.41)
CART per additional year
Age per additional 5 years
Male gender
Previous CVD
Ever smoking
0,1
0,5
1
5
Relative rate of myocardial infarction (95% CI)
Multivariable Poisson model, also adjusted for
family history, BMI, HIV transmission, cohort and race
10
Mitochondria
Cell
Mitochondrion
• Energy power-houses
• Have their own DNA
• Mitochondrial DNA is
replicated by a separate
enzyme to nuclear DNA
(DNA polymerase gamma)
ART naïve patients: Mean lactate values
at 48 weeks (Δ from BL)
1,2
mmol/L
1
† p=0.002
† p<0.001
*p=0.003
COM/ABC
COM/NFV
*p<0.001
d4T/3TC/NFV
0,8
*p=0.006
0,6
0,4
0,2
0
Lactate overall
Subgroup-male
Subgroup-female
-0,2
* p-value as compared to ABC/COM
† p-value as compared to COM/NFV
Kumar P, et al. 9th CROI 2002; Abs 33
Study 903
Venous lactate sub-study at week 48*
Mean (mmol/L)
TDF+3TC+EFV
(n=128)
d4T+3TC+EFV
(n=129)
1.2
1.9
p-value
< 0.0001
*Samples collected per AACTG Lactic Acidosis guidelines 6/00
Gallant et al, 42nd ICAAC, 2002
Risk of hyperlactatemia with different ART
combinations - logistic regression
Others
ZDV+EFV (no PI or ddI)
ZDV+PI (no ddI or EFV)
ZDV (no PI, ddI or EFV)
d4T &/or ddI + EFV + PI
d4T &/or ddI + EFV, no PI
d4T &/or ddI + PI, no EFV
d4T &/or ddI, no EFV or PI
0.1
1
10
100
Boubaker et al - Abstract 57, 7th CROI 2000
Lactic acidemia
Terminology
• lactic acidosis
venous lactate > 2 mmol/L
+ arterial ph <7.35 (rarely done)
lactic acidemia venous lactate > 2 mmol/L
• grade of lactate
acidosis symptoms
mortality
acidemia (mmol/L)
(%)
severe
>10
often
always
80
moderate 5 -10
rare
usual
0
mild
2-5
no
sometimes
0
Risk & treatment
2-9 per 1,000 PY
Stop ART – time to clinical recovery 1-3 weeks (risk of relapse higher if
restarting same drug combination)
Reversibility of symptomatic hyperlactatemia
– other NRTI’s or NRTI sparing ?
• Symptomatic hyperlactatemia in TARHELL
(d4T, n=16 to ZDV(4) or ABC (12)1
• At wk 48 (med.): -0.80 mmol/L
• Symptomatic hyperlactatemia at UCSD
(d4T to ZDV or ABA, n=12)2
•
•
•
•
At diagnosis: S-Lactate : 5.4 mM
1 relapse of symptomatic hyperlactatemia
2 discontinued due to unrelated reasons
9 remained asymptomatic after median 27 months –
S-lactate (med.) : 1.3 mM
1: Lonergan et al, 4th IWADRL, 2002. Abs 21
2: Lonergan et al, 42nd ICAAC, 2002. H-1080
Risk factors for femoral osteonecrosis (MRI):
% of HIV+ patients with osteonecrosis
Present
Absent
RR (95% CI)
Lipodystrophy
5%
4%
1.1 (0.4-2.9)
Low testosterone
12%
4%
3.2 (1.1-9.0)
Syst. corticosteroids
8%
2%
3.8 (1.3-11.0)
Lipid lowering agents 13%
3%
4.7 (1.8-11.9)
Testosterone
8%
2%
3.9 (1.3-11.6)
Weights lifting
7%
2%
3.3 (1.1-9.8)
Prevalence: 15/339 (4.4%) in HIV+; 0/118 (0%) in HIV- (age, sex matched);p=0.02
Miller et al, AIM, 2002
The balance when assessing
appropriate use of a treatment
intervention
Effect
GOOD
Toxicity
BAD
AIDS rate and 95% confidence intervals (per 100
PYFU)
9/
94
3/ 3/9
95 5
9/ 9/9
95 5
3/ 3/9
96 6
9/ -9/9
96 6
3/ 3/9
97 7
9/ 9/9
97 7
3/ 3/9
98 8
9/ 9/9
98 8
3/ 3/9
99 9
9/ 9/9
99 9
3/ 3/0
00 0
9/ -9/0
00 0
3/ 3/0
01 1
9/ 9/0
01 1
-3
/0
>= 2
3/
02
AIDS rates
EuroSIDA
1994
-2003
100
36
10
2.5
1
Mocroft et al, Lancet 2003
9/
94
3/ -3/9
95 5
9/ -9/9
95 5
3/ -3/9
96 6
9/ -9/9
96 6
3/ -3/9
97 7
9/ -9/9
97 7
3/ -3/9
98 8
9/ -9/9
98 8
3/ -3/9
99 9
9/ -9/9
99 9
3/ -3/0
00 0
9/ -9/0
00 0
3/ -3/0
01 1
9/ -9/0
01 1
-3
/
>= 02
3/
02
Median CD4 (/mm3) and
interquartile range
CD4 count during period (/mm3)
650
600
550
500
450
400
350
300
250
200
150
100
50
0
<=50
51-200
Calendar period
>200
80
60
40
% with CD4 in group
Changing population CD4
lymphocyte count in EuroSIDA
100
20
0
Mocroft et al, Lancet, 2003
Risk of clinical disease progression by CD4 cell
count at start of HAART
Rate 1.00
without
AIDS 0.95
or
death 0.90
>350
200-349
100-199
0.85
0.80
0-99
0.75
0
1
2
3
Years from starting HAART
Egger et al, ART Cohort Collaboration, Lancet, 2002
But –
this does NOT indicate
that ART works less well
in severely
immunocompromised
patients !!!
Predictive ability of pre-therapy CD4 cell
count on risk of disease progression in
ART-naive patients starting HAART
Rate (per 100 py)
Rate
%
10
100
8
80
6
60
4
40
2
20
0
0
<200
# events
# w/CD4 count
N=2742
% of events occurring at CD>200
267
237
200-350
> 350
Pre-therapy CD4 count (cells/µL)
44
29
32
23
SHCS, Frankfurt, EuroSIDA Phillips et al, JAMA, 2001
Relative hazard of viral load suppression <
500 c/mL within 32 weeks
2.0
1.5
1
0.67
0.5
>500
400499
300399
200299
100199
< 100
Baseline CD4 count (per cubic millimeter)
N=2742
SHCS, Frankfurt, EuroSIDA Phillips et al, JAMA, 2001
Percent with viral load > 500 c/mL –
baseline CD4 count
100
80
60
N.S.
40
CD4 count < 200
20
CD4 count 200 - 349
CD4 count > 350
0
0
24
48
72
96
120
144
Weeks from viral load < 500 copies per milliliter
N=2346
SHCS, Frankfurt, EuroSIDA Phillips et al, JAMA, 2001
Differential diagnosis of clinical events
developing in severely immunodeficient
patients recently started on ART
• Further complications from pre-therapy
impaired health status
• Still susceptible to opportunistic
infections also after initiation
• Immune reconstitution syndrome
• Adverse events
10
1
0,1
0,01
PC
P
TB
Ca
nd
Es
o
To
xo
M
AC
Cr
yp
t
CM
os
p
V
NH
L
*: 6.636 patients followed for 18.498 personyears
Ledergerber et al, BMJ 1999;319:23
KS
Hazard ratio (95% CI)
Swiss HIV Cohort(*): Relative risk of
different AIDS-defining events in 7/19976/1998 versus 1992-4
Systems complementary to
spontaneous reporting
Enthusiasm for an agent as a
function of time since first
introduced
Enthusiasm
”CURE” ”DOG”
REALISTIC
Time since initiation of phase I trials (years)
Textbook in Pharmacology, 1960’s
Enthusiasm for HAART as a function
of time since first introduced
Enthusiasm
1996
“?”
Time since initiation of phase I trials (years)
Toxicity - ways of detection
• Randomised trial:
• randomised phase
• open-label follow-up
• Passive surveillance
• Active survaillance:
• cohort studies
Why
Randomization?
• Conscious and unconscious bias eliminated
from treatment assignment
• Known and unknown confounders balanced
on average
Moderate treatment effects cannot be reliably
established in the presence of moderate bias.
Beta-carotene intake and cardiovascular mortality
Cohorts
Male health workers
Social insurance, men
Finland
Social insurance, women
Finland
Male chemical workers
Switzerland
Hyperlipidaemic men
USA
Nursing home residents
USA
Male smokers
Trials
USA
Skin cancer patients
Finland
USA
(Ex)-smokers, asbestos workers USA
Male physicians
USA
0.1
0.5 0.75
1
1.25 1.5 1.75
Relative risk (95% CI)
Egger et al. BMJ 1998
ONLY RANDOMISED TRIALS CAN RELIABLE
DEFINE THE RISK:BENEFIT RATIO OF ART IN A
GIVEN SETTING
BUT
IT IS NOT ALWAYS FEASIBLE TO DO THEM,
OR
THEY DO NOT ANSWER THE QUESTION !
Why are randomised trials not always
able to provide the answers we are
looking for ?
• Stopped when there is significant differences
• Ethically correct
• But, durability ? (ART has to continue for life)
• Use of laboratory endpoints (e.g. viral load)
minimises duration and size of trial
- result in rapid introduction of new drugs
• Snap-short of the entire duration of ART
• Not powered to detect differences in clinical meaningful
outcomes related to benefit and risk from ART
Pooled Analysis of
Immediate vs. Deferred AZT
Year of
Follow-up
0-
No. AIDS/Death
Events
209
1-
357
0.94
(0.76 - 1.16)
2-
440
1.05
(0.87 - 1.27)
3-
369
1.12
(0.91 - 1.38)
4-
307
0.98
(0.78 - 1.23)
5+
226
1.10
(0.84 - 1.43)
*Immediate vs. deferred AZT
Hazard Ratio*
0.52 (0.39 - 0.68)
PI-HAART versus dual NRTI
Therapy in Advanced Patients
Interval of
Follow-up
(months)
0-6
6 - 12
12 - 18
18 - 24
24 - 30
30 - 36
No. AIDS/
Death Events
167
141
137
94
86
54
Hazard Ratio*
Interval
Cum.
0.49
0.33
0.13
0.15
0.20
0.16
0.49
0.41
0.30
0.26
0.25
0.24
*PI regimen vs. nRTIs adjusted for baseline CD4+
Toxicity - use of randomised
trials
• BENEFITS
• Causal relationship
can be evaluated
• Methodology ADR
reporting welldeveloped
• PROBLEMS
• Size of population is
relatively small - rare events
• Patient population is selected
• Randomised trials usually
have a limited duration long-term toxicity
• Assessment of drug under
study - multiple combinations
Sample size to detect a doubling in the
incidence of existing toxicities
Two arm trial, 80% power, 5% significance
Total sample size required
5000
4000
3000
2000
1000
Pivotal
Phase 3
trial
0
5-10%
4-8%
3-6%
2-4%
1-2%
Difference in incidence rates between arms (%)
Hill et al, 4th IWADRL
Toxicity “missed” in randomised
trials
• Abnormal fat distribution
– 1995-97: Randomised trials evaluating efficacy/ toxicity
of ART. Lipodystrophy not identified
– Feb. ‘98: First report, Carr et al. – PI’s is responsible
– 2002: ACTG 384 substudy: NRTI’s responsible (PI’s
only play a minor role)
• Myocardial infarction
– 1998: Dyslipidaemia acknowledged
– 2002: Do not result in accelerated risk of myocardial
infarction
– 2003: Do result in myocardial infarction
Lipodystrophy
AIDS 1998, 12: F51-F58
Other options when RCT are not able
to provide the relevant answer
• Expert opinion – used in marked research
• Other sources of data:
– Case reports
– Passive surveillance
– Cohort studies
Relative importance: summary of
experience in last 8 years –
personal perspective
• Randomised controlled trials
• Early onset, frequent adverse events
• Cohort studies
• Complemented findings in RCT’s
• Rare early onset and late onset adverse events
• Spontanous reporting/passive surveillance
• Confusion
• Perscription studies
• None
• Case reports & expert opinion
• Confusion
”Cohort” – group of patients:
the number ain’t the only relevant
characteristic
•
•
•
•
•
Prospective or retrospective
Enrolment criteria
Which data are collected ?
How are data collected ?
Which quality control measures are
utilized
• Power to detect the outcome being
investigated
EuroSIDA - data collection
• Consecutive patients
• New cohorts added every 2 year - refreshment
• Routine outpatient clinic appointment
• Age > 16 (cohort I-III: CD4 < 500/mm3)
• Every 6 months (June, December)
• Data collection form
– format adjustable
• Data check
– At site: check of computerised data (preprinted)
– At coordinating centre:
• data entry
• queries
• site visits
EuroSIDA Cohorts I-V
EuroSIDA
n = 9802
Cohort I
n = 3116
May 1994
Cohort II
n = 1365
1996
Cohort III Cohort IV Cohort V
n = 2839 n = 1225 n = 1257
1997
1999
2001
72 hospitals in 24 European countries + Israel and Argentina
Cohort VI started in November 2003 (additional 1,300 patients)
Surveillance of emerging adverse
events outside of RCT
• Rare early and all late-onset
adverse events
• Identification
– Case description of phenomenon
– Biological plausibility
– Cohort studies
• Requires open-ended questions
• Not feasible in larger cohort studies
Quality versus quantity
Quality
of
data
Volume of questions/
work required
In cohort studies it is not
important to collect all sorts of
information
BUT
rather focus on collecting the
information required for the need
of the cohort
and
ENSURE THAT THE QUALITY OF
THE DATA IS GOOD
(garbage in=garbage out)
Role of large prospective cohort
studies for emerging adverse
events
• Study a priori identified signals
• Although methods exist to use large cohorts to identify
signals not suspected previously (discussed later)
• Assess association with drug classes or
individual drugs
• Quantify risk in subgroups of patients
Inclusion: selection
• External validity – extrapolation
• Active recruitment versus extraction
from databases developed for other
reasons
• Consecutive versus non-consecutive
• Retrospective studies !
• Study of trends over time – the addition
of new patients
Risk of AE as function of
time since starting the drug:
More on selection bias !!
• Enrolment:
• Drug naïve cohort
• Complete assessment of risk
• Drug experienced cohort
• AE’s may be missed (if they occurs prior to time
when patient enters cohort)
• Cohort still on drug can tolerate the drug
• Biological mechanism of how AE may develop
may assist in making rational assessment of
whether a cohort is suitable to assess risk of a
certain AE
Identification of a potential toxicity with
a late onset using cohort data
Incidence of potential toxicity
Initiated
therapy
Not
Initiated
therapy
Time from initiation of therapy or follow-up
Incidence of adverse event
# Events
Person-year of follow-up
If adverse event is late
onset
• If incidence is calculated
• On versus of drug
• % of patients on drug followed prior to
biologically plausible onset of adverse
event
• Time intervals since starting drug
• Define time lag
• Ability to detect adverse event
Time lag versus total exposure time
per patient
Event:
what is possible and how collect
• Ascertainment (within a population, who developed the AE
and who did not)
• Case definition
• Objectively documented
• Reliable picked up in the patient record notes
• Quality control – source documentation
• Collected prospectively or retrospectively
• Prospectively: allows for training and proper
work-up – awareness high
• Retrospective: awareness variable
• Source verification
• Competing risks
• HIV-related (e.g. chest pain)
• Co-morbidities, eg CVD (next slide)
Power
• Risk of type I error (study detect a
difference that is not there in reality)
• Risk of type II error (study did not detect
a difference that is there in reality)
• Formulate hypothesis prior to launch
study/analysis
• Stipulate what difference is acceptable
to be missed
Co-morbidities as adverse events:
noise or true problem ?
• Adverse event/background risk ratio !
– Characteristics of the cohort followed
• Background risk low: “unusual high rate”, but
requires many patients
• Background risk high: signal may be missed
• An ”independent” effect associated
with drugs
• Requires the collection of all important risk factors
for the co-morbidity
Lost-to-follow-up
• Should be low !
• Is health situation (for the parameter
evaluated) for those lost better or poorer
than for those remaining ?
• Emigration versus transferral to hospice
• Organisation of health system:
– Single - centralised
– Plural
• Private insurance organisations
• Government supported programs
• Ability to follow patients switching program
Principal for working: think outside
and work within the box
Einstein’s definition of insanity: repeating the same experiment
over and over, and expecting different results
Critical criteria for a successful
observational study
• Quality of data (garbage in = garbage out)
• Limit the volume of data to be collected to critical
important items
• Describe what you want to achieve prior to launch
• Allow for flexibility while is ongoing
• Standardized case record form (with the flexibility of
additional items in the future)
• Reciprocal quality control: Data already in the
database should be available for review clinical site
staff
• On-site training of staff
• Dynamic & ongoing dialogue between clinicians and
epidemiological and statistical functions to ensure
• Timely extract of clinical relevant information
• Optimise engagement by entire study team
Prognosis without HAART
85.5%
Probability of AIDS within 3
years
100%
64.4%
80%
60%
40%
40.1%
40.1%
42.9%
32.6%
32.6%
16.1%
8.1%
16.1%
8.1%
20%
2.0%
8.1%
9.5%
3.2%
2.0%
14 - 41K
3 - 14K
0%
> 110K
41 - 110K
3.7%
2.0%
0.0%
< 3K
< 200
201 - 350
351 - 500
501 - 750
> 750
CD4 count
HIV-1
RNA concentration
Viral load
>60,000
20 - 60,000 6 -(copies/ml)
20,000 1 - 5,000 <1000
3-year probability of AIDS in 1604 men enrolled in the Multicenter
AIDS Cohort Study (MACS) 1984-1985
Mellors JW, et al. Ann Int Med 1997
Effect of Absolute vs. delta-viral load from
Setpoint on current CD4-Slope in 628 Patients
On-Treatment with Stable Viral Load
Mean(95%CI) CD4-slope
[cells/mL*yr]
Patients:
88
Observations: 177
177
410
308
705
394 284
1304 687
376
1005
188
441
159
427
150
100
50
0
-50
<2.5
3
[log10
4
>4.5 <0.5
1
2
>2.5
delta-VL from setpoint
VL
[log10 copies/mL]
copies/mL]
PLATO study group, Ledergerber et al, Lancet, 2004
Clinical symptoms of
mitochondrial toxicity
Polyneuropathy
Myopathy
Steatosis
Lactic acidosis
Pancreatitis
Vomiting
Pancytopenias
Renal proximal tubular dysfunction
Brinkman, AIDS 1998; 12:1735-44
Peripheral neuropathy
• Potential causes:
• HIV
• NRTI’s (especially the d-drugs)
• Diabetes mellitus
• Other internal medicine type diseases
• Pathophysiology of NRTI-induced:
• Depletion of neural branches
• Course of events for NRTI-induced:
• Initial symptoms: tingling/odd sensation/numbness
in toe’s+palm of the foot (sign: decreased
sensibility)
• Always bilateral
• Typical involvement: incl angle region
• Potentially reversible – especially soon after debut
Use of large cohort studies
to identify signals
• Indicators of emerging – not previously recognised toxicity
• Treatment limiting toxicity – causes of
• Mortality – causes of
• Identify risk factors for indicators
• If risk is excessively high in subgroup (or compared to
data from other sources)
• Investigation of cases that have already occurred
(retrospective investigation)
• Plan more details collection of data (prospectively)
9/
94
3/ 3/9
95 5
9/ 9/9
95 5
3/ 3/9
96 6
9/ 9/9
96 6
3/ 3/9
97 7
9/ 9/9
97 7
3/ 3/9
98 8
9/ 9/9
98 8
3/ 3/9
99 9
9/ 9/9
99 9
3/ 3/0
00 0
9/ 9/0
00 0
3/ 3/0
01 1
9/ 9/0
01 1
-3
/0
>= 2
3/
02
Death rate and 95% confidence
intervals
(per 100 PYFU)
Death rates
EuroSIDA 1994 -2003
All deaths
0,1
HIV-related deaths
Non-HIV deaths
100
10
1
Calendar period
Update: Mocroft et al, Lancet 2003
Why are causes of death
important ?
• ART aims to prevent death but can’t be
expected to prevent deaths unrelated to HIV
• Separate ART failure from ”background noise”
• Clinical endpoint RCT’s of interventions/strategies to inhibit HIV
replication and/or improve immune function
• Observational studies – predictors of response to such
interventions
• Surveillance system to identify emerging HIV and
ART-related deaths
• Temporal changes in pattern
• Risk factors of specific causes
REQUIEM
• REcommendation
for Quality Uniform Interpretation &
Evaluation of Mortality in HIV’
• Panel with global representation of most
ongoing cohort studies
• Common CRF
• Uniform procedure for coding causes
• Publicly release – end of 2004 on www.cphiv.dk
Toxicity - use of cohort studies
•
•
•
•
•
BENEFITS
Large size
Unselected patients
Long-term follow-up
Prevalence,
incidence and risk
factors of specified
potential toxicities
evaluated
• PROBLEMS
• Detection of
associations, not
causal relationship hypothesis
generating
• Quality of data
inversily correlated
with volume of data
collected
Networking nationally and
internationally
What issues will arise when
implementing ART in a region
• Toxicity
• Real (likelihood of not previously identified versus well
established events)
• Believed but not real
• Continued morbidity&mortality after starting
ART
• Questions on risk:benefit ratio
• Patient community
• Physicians – not fully up to date
• Request from policy makers to document
• Resistance
Ongoing active surviellance
from cohort study
• Source of information on risk:benefit ratio
• Source for continued eduation/training
• there is nothing like data that makes an
impact
• Lack of data = confusion
• Quality control
• Benchmarking
• Identification of specially interesting cases and risk
hereof
• Additional investigations
Initiatives required to
address these issues
Active
surveillance
Passive
surveillance
Randomised
controlled
trials
Initiatives required to
address these issues
Passive
surveillance
Active
surveillance
Randomised
controlled
trials
Combining cohorts
• Quality of data collection
• Uniformity of data to be collected
• prospective versus retrospective;
• quality versus quantity
• Merging databases
Examples of ongoing cohorts
• Multicenter:
– EuroSIDA - 20 European countries
– Swiss HIV Cohort Study - Switzerland
– French HIV Hospital Database – France
– ATHENA – The Netherlands
– ICONA - Italy
– CPCRA observation database - USA
• Unicenter:
– Clinic cohorts: Royal Free, Sydney, Frankfurt, Baltimore, St
Stephens, Perth, Cologne, etc
• Merger of cohorts:
– Data collection of Adverse effects of anti-HIV Drugs (D:A:D)
Need for a standard on HIV
databases?
• Cohort collaborations have proven very successful in
addressing issues that individual cohorts lack the power to
answer
• Many more collaborations can be expected in the future
• Proprietary formats cause unnecessary additional
workload for
• protocol development
• data extraction and exchange
HIV Collaboration Data Exchange
Protocol ( HICDEP )
• Provide harmonised formats for data-exchange
between cohorts
– Incorporating knowledge from DAD, EuroSIDA, CASCADE, PLATO, ARTCC, SHCS
– Covers data from demographics to resistance data
• Give guidance on possible data structure and formats
for new cohorts
• Protocol, sample database and list of codes is
available electronically at:
CHIP – Copenhagen HIV Programme
http://www.cphiv.dk/HICDEP.pdf
Kjær & Ledergerber, Antiviral Therapy, 2004
Structure overview of HICDEP
Basic info
Lab + BP
Medication
Diseases/AE
Resistance
+ Visit info
+ Overlap