WHO training, Pretoria, SAJens D. Lundgren, MD, DMScDirector, Copenhagen HIV Programme (044)Hvidovre University Hospital,2650 Hvidovre, Denmarkwww.cphiv.dk; e-mail: jdl@cphiv.dk

Copenhagen HIV ProgrammeResearch unit at University of Copenhagen (located at Hvidovre University Hospital)Coordinating centre for:Randomized controlled trials (RCTs)COLATE, MaxCmin 1&2NIH-sponsored: ESPRIT, SILCAAT, SMARTNetwork: +300 clinics on 5 continentsCohort studiesEuroSIDA (since 1994)Data collection of Adverse events of anti-HIV drugs (D:A:D)Network: +200 clinics on 3 continents

Agenda for 3 sessionsADR from ART examples The risk:benefit ratio of ARTMethods to identify and understand AEs in addition to spontanous reportingNetworking nationally and internationally

TerminologyART=antiretroviral treatment ARVs=antiretrovirals (i.e. drugs used as part of ART)

Global effort to collect ADRs of ART WHO course, Pretoria, SASeptember 2004

Anti-HIV agents: 2004Fusion inhibitors: T-20 (03)Integrase inhibitors: ? (03)

Nucleo(t)side reverse transcriptase inhibitors (NRTIs)

Non-nucleoside reverse transcriptase inhibitors (nNRTIs)

Protease inhibitors (PIs)

Zidovudine (AZT)(87)

Didanosine (ddI)(91)

Zalcitabine (ddC)(92)

Lamivudine (3TC)(96)

Stavudine (d4T) (97)

Abacavir (1592)(98)

Tenofovir (02)

Nevirapin (98)

Efavirenz (99)

(TMC 125 (05))

Ritonavir (96)

Indinavir (96)

Saquinavir (96)

Nelfinavir (97)

Lopinavir (00)

Amprenavir (01)

Fos-amp. (03)

Main reasons of discontinuation of first HAART regimen within1st year: ICONAICONAItalianCohortNaiveAntiretroviralMonforte et al. AIDS 1999

Side effects of anti-HIV drugsEarly onsetVaries by drug: GI, renal, CNS, rash, liver Late onsetperipheral neuropathyosteopenialiver toxicityaltered fat distributionelevated lactic acid levelsdiabetes mellituslipid changes in blood(cardiovascular disease)

(AZT-nonAZT) difference (and 95% CI) of one-year change in haemoglobinMoyle et al, 4th IWADRL, 2002Differences in Haemoglobin (g/dl) at 1 yearOz-1 (n=105)Oz-2 (n=61)START I & II (n=301)BMS-148 (n=705)BMS-152 (n=491)Combined (n=1663)

Chart2

5.80.43930798990.4393079899

4.80.42023823960.4202382396

3.80.18523128660.1852312866

2.80.12971660580.1297166058

1.80.1508490630.150849063

0.50.08514580130.0851458013

Hb

Hmoglobin

NMeanSDtMSerrNMeanSDtMSerrNMeanSDtMSerr

OzCombo1AZT/3TC/IDVd4T/3TC/IDVd4T/ddI/IDV

Baseline Hb3513.792.033413.811.893613.731.35

Change Hb week 24 LOCF35-0.31.524-0.300.25340.861.14240.860.20360.971.1240.970.18

Change Hb week 52 LOCF3501.61520.000.273411.54521.000.26360.991.27520.990.21

OzCombo 2AZT/3TC/NVPd4T/3TC/NVPd4T/ddI/NVP

Baseline Hb2014.021.532114.51.082213.891.48

Change Hb week 24 LOCF19-0.261.1624-0.260.27200.541.27240.540.28220.570.9240.570.19

Change Hb week 52 LOCF200.021.09520.020.24200.581.24520.580.33220.681.14520.680.24

Start I & IIAZT/3TC/IDVd4T/3TC/IDVd4T/ddI/IDV

Baseline Hb20514.391.4610014.221.5710214.371.35

Change Hb week 24146-0.271.0824.5-0.270.09770.311.03240.310.12780.520.9723.50.520.11

Change Hb week 48115-0.211.3948.5-0.210.13580.440.9480.440.12590.361.0847.50.360.14

AI454-147AZT/3TC/NFVd4T(tab)/ddI/NFV

Baseline Hb24613.901.5748113.781.75

Change Hb week 24 LOCF238-0.571.3924.5-0.570.094670.371.08240.370.05

Change Hb week 48 LOCF238-0.341.3948.5-0.340.094670.511.30480.510.06

AI454-148AZT/3TC/NFVd4T(EC)/ddI/NFV

Baseline Hb25014.161.7425513.941.76

Change Hb week 24 LOCF241-0.351.2424.5-0.350.082500.471.11240.470.07

Change Hb week 48 LOCF241-0.101.4048.5-0.100.092500.681.11480.680.07

AZT

nmeans.errwithinbetween

Six MonthsOz 135-0.300.25-10.5078.750.385.80.51p=0.2449

Oz 219-0.260.27-4.9425.350.404.80.55p=0.3395

Start I and II146-0.270.09-39.42170.292.653.80.18p=0.0030

AI454-148238-0.570.09-135.66458.826.492.80.18p

Abacavir hypersensitivity reaction (HSR)Symptoms: Fever, rash, malaiseRisk: From 1-8 (10) weeks from start. If HSR, exposure is associated with immediate deathPresence 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, HLA-DQ3 abacavir:9% to 2.5%

Time to initial grade 3 or 4 AEProportion of subjects without a grade 3/4 AEP = 0.0002 (log rank test)MaxCmin1: Dragsted et al, JID, 2003

Retinoid syndromeNails 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 symptomsAt Week 24 and 48Patients and physicians 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

242Randomized Treatment Gr

IDV/rtv SAQ/rtv (n=124) (n=120)p-valueCases (%) Non-cases (%)98 (40%)

144 (60%) 76 (61%) 23 (19%)

48 (39%) 97 (81%)< 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

Sheet:

BID

TID

Abnormal fat distributionLipoatrophy on armsLipoatrophy on legsIncreased abdominal fat (visceral)Mammae hypertrophy

Lipoatrophy in faceBuffalo hump Lipoatrophy in face

Lipoatrophy on armsLipoatrophy on legs

Both increased fasting and 2-hour insulin levels are evidence of insulin resistance in lipodystrophyP

Baseline Risks for CVD% of totalD:A:DAIDS 2003; 17(8): 1179-94

Lipid elevation and ART status at baseline in D:A:D% of all in stratumAIDS 2003; 17(8): 1179-94

% withelevatedtotalcholesterolBaselineCD4 countART statusat baselineCholesterol elevation, ART, CD4D:A:DAIDS 2003; 17(8): 1179-94

table 1

Geographical areaReferenceNumber of patientsAgeGenderTransmission categoryHIV stageART

CohortmedianIQR% female% homo%hetero% IVD% previous AIDSCD4 median (IQR)% nave

AHODAustralia66741(35-47)3.986.87.13.921.4500(324-680)7.1

ATHENANetherlands203743(37-50)14.067.619.14.331.3450(290-630)0.4

AquitaineFrance187239(35-46)24.740.926.722.023.6429(273-606)10.8

BASSSpain67438(35-43)24.832.625.239.332.8496(308-706)0.3

BrusselsBelgium110937(32-43)43.323.652.56.218.5435(273-622)23.2

CPCRAUSA146038(33-45)21.4nana16.024.5265(64-468)NA

EuroSIDAEurope and Israel411439(35-46)21.446.424.322.031.7358(220-520)3.1

HivBIVUSSweden96841(35-48)19.759.126.19.214.6480(320-660)13.6

ICONAItaly254036(33-40)31.520.036.938.613.0522(339-728)31.3

NiceFrance101938(34-43)29.926.432.830.322.0428(276-619)8.4

SCHSSwitzerland396139(34-45)29.635.833.826.624.8426(269-616)13.7

Total2042139(34-45)24.941.529.321.724.4420(260-614)11.6

table 2

Current ART at enrolment

NaveNo current ARTNRTINNRTIPIPI/NNRTITotal

n=1924 (11%)n=1721 (10%)n=2148 (12%)n=3419 (19%)n=7413 (42%)n=1227 (7%)n=17852

Age (median;IQR)37(33-42)39(35-45)40(35-47)39(35-46)41(36-49)41(36-49)39(34-45)

Gender (%female)32.429.629.823.020.616.524

AIDS (%)5.621.017.425.229.245.425

CD4-count (median;IQR)499(359-690)326(169-525)457(300-641)457(290-650)434(277-628)323(188-492)430(279-621)

log HIV RNA (median;range)3.9(4years

ARVPIC:

fucasesseincidenslower limitupper limit

0-1 years5321041.9219.515.823.3

1-2 years8772021.6223.019.926.2

2-3 years18784971.1926.524.128.8

3-4 years16475121.3731.128.433.8

>4years3741132.8430.224.635.8

ARVPIE:

fucasesseincidenslower limitupper limit

0-1 years229232.0910.05.914.1

1-2 years223272.3312.17.516.7

2-3 years217272.3912.47.717.1

3-4 years140203.1914.38.020.5

>4years

ARVPNC:

fucasesseincidenslower limitupper limit

0-1 years49198.9038.821.356.2

1-2 years111466.1141.429.553.4

2-3 years2461024.1141.533.449.5

3-4 years4682173.1546.440.252.5

>4years159805.6350.339.361.3

ARVPNP:

fucasesseincidenslower limitupper limit

0-1 years48106.5920.87.933.7

1-2 years142394.4027.518.836.1

2-3 years293722.9024.618.930.2

3-4 years3231043.1632.226.038.4

>4years152514.7033.624.342.8

ARVPNN:

fucasesseincidenslower limitupper limit

0-1 years5795.2615.85.526.10-1 years

1-2 years205443.2421.515.127.81-2 years

2-3 years5681412.0924.820.728.92-3 years

3-4 years7362051.9527.924.031.73-4 years

>4years196634.0532.124.240.1>4years

ARVPNE:

fucasesseincidenslower limitupper limit

0-1 years136203.2914.78.321.2

1-2 years190292.8315.39.720.8

2-3 years235312.3713.28.517.8

3-4 years176283.0115.910.021.8

>4years2946.9013.80.327.3

Ark1

TC>6.2 mmol/L

Time b. ART0-1 year1-2 years2-3 years3-4 years>4 yearsTime on ART0-1 year1-2 years2-3 years3-4 years>4 years

ARVNR:12.512.07.88.39.2ARVNR:8.114.58.28.98.7

ARVNNC:14.91819.822.2ARVNNC:14.91819.822.2

ARVNNE:4.27.18.3ARVNNE:4.49.1

ARVPIC:19.62326.531.130.2ARVPIC:19.62326.531.130.2

ARVPIE:11.913.310.212.512.9ARVPIE:1012.112.414.3

ARVPNC:38.841.441.546.450.3ARVPNC:38.841.441.546.450.3

ARVPNP:20.827.524.632.233.6ARVPNP:20.827.524.632.233.6

ARVPNN:15.821.524.827.932.1ARVPNN:15.821.524.827.932.1

ARVPNE:17.11712.716.310.5ARVPNE:14.715.313.215.9

Time on ART0-1 year1-2 years2-3 years3-4 years>4 years

ARVNR:8.114.58.28.98.7

ARVNNC:141620.619.2

ARVNNE:5.26.7

ARVPIC:13.621.324.427.733.3

ARVPIE:8.510.913.513.7

ARVPNC:38.841.441.546.450.3

ARVPNP:20.827.524.632.233.6

ARVPNN:15.821.524.827.932.1

ARVPNE:14.715.313.215.9

figur 3 (2)

8.1145.213.68.538.820.815.814.7

14.5166.721.310.941.427.521.515.3

8.220.62-3 years24.413.541.524.624.813.2

8.919.23-4 years27.713.746.432.227.915.9

8.7>4 years>4 years33.3>4 years50.333.632.1>4 years

Figure 3. Elevated total cholesterol (>6.2 mmol/L) according to duration of current and previous ART exposure. The ART groups are mutually exclusive (n (%): number of patients (% of DAD study population)) :ARVNR: Ever exposed to NRTI's only, n=1271 (7,1%), ARVNNC: Ever and currently exposed to NNRTI's (and NRTI's), n=1155 (6,5%), ARVNNE: Ever not currently exposed to NNRTI's, n=418 (2,3%), ARVPIC: Ever and currently exposed to PI's (and NRTI's), n=6295 (35,3%), ARVPIE: Ever not currently exposed to PI's, n=1225 (6,9%), ARVPNC: Ever and currently exposed to PI 's and NNRTI's (and NRTI's), n=1224 (6,9%), ARVPNP: Ever exposed to PI's and NNRTI's, currently PI's, n=1110 (6,2%),ARVPNN: Ever exposed to PI's and NNRTI's, currently NNRTI's, n=2258 (12,6%), ARVPNE: Ever exposed to PI's and NNRTI's, not currently receiving PI or NNRTI, n=955 (5,3%)

ARVNR:

ARVNNC:

ARVNNE:

ARVPIC:

ARVPIE:

ARVPNC:

ARVPNP:

ARVPNN:

ARVPNE:

Percentage with elevated TC

Elevated TC, cumulated time on ART

Diagram1

13.818.520.125.420.338.327.5

20.818.926.133.72444.733.5

17.824.42-3 years35.42951.637.7

25.635.33-4 years38.928.256.643.3

19>4 years>4 years47.1>4 years66>4 years

ARVNR:

ARVNNC:

ARVNNE:

ARVPIC:

ARVPIE:

ARVPNC:

ARVPNE:

Diagram2

15.312.90-1 year27.831.90-1 year16.70-1 year31.3

21.214.51-2 years2324.125.823.112.538

2719.12-3 years22.530.3203515.742.2

21.43-4 years3-4 years26.226.826.238.425.434.1

31.9>4 years>4 years30.6>4 years26.641.230.238.5

ARVNR:

ARVNNC:

ARVNNE:

ARVPIC:

ARVPIE:

ARVPNC:

ARVPNP:

ARVPNN:

ARVPNE:

Diagram3

84.787.10-1 year72.268.10-1 year83.30-1 year68.7

78.885.51-2 years7775.974.276.987.562

7380.92-3 years77.569.7806584.357.8

78.63-4 years3-4 years73.873.273.861.674.665.9

68.1>4 years>4 years69.4>4 years73.458.869.861.5

ARVNR:

ARVNNC:

ARVNNE:

ARVPIC:

ARVPIE:

ARVPNC:

ARVPNP:

ARVPNN:

ARVPNE:

Ark1 (2)

Tri>2.3 mmol/L

Time on ART0-1 year1-2 years2-3 years3-4 years>4 years

ARVNR:13.820.817.825.619.0

ARVNNC:18.518.924.435.3

ARVNNE:20.126.1

ARVPIC:25.433.735.438.947.1

ARVPIE:20.3242928.2

ARVPNC:38.344.751.656.666

ARVPNP:19.630.144.755.755.1

ARVPNN:19.330.133.241.453.1

ARVPNE:27.533.537.743.3

HDL4 yearsTime on ART0-1 year1-2 years2-3 years3-4 years>4 years

ARVNR:15.321.22721.431.9ARVNR:84.778.87378.668.1

ARVNNC:12.914.519.1ARVNNC:87.185.580.9

ARVNNE:ARVNNE:

ARVPIC:27.82322.526.230.6ARVPIC:72.27777.573.869.4

ARVPIE:31.924.130.326.8ARVPIE:68.175.969.773.2

ARVPNC:25.82026.226.6ARVPNC:74.28073.873.4

ARVPNP:16.723.13538.441.2ARVPNP:83.376.96561.658.8

ARVPNN:12.515.725.430.2ARVPNN:87.584.374.669.8

ARVPNE:31.33842.234.138.5ARVPNE:68.76257.865.961.5

Diagram4

8.1145.213.68.538.820.815.814.7

14.5166.721.310.941.427.521.515.3

8.220.62-3 years24.413.541.524.624.813.2

8.93-4 years3-4 years27.713.746.432.227.915.9

8.7>4 years>4 years33.3>4 years50.333.632.1>4 years

NR

NNC

NNE

PIC

PIE

PNC

PNP

PNN

PNE

Diagram6

8.1145.213.68.538.820.815.814.7

14.5166.721.310.941.427.521.515.3

8.220.62-3 years24.413.541.524.624.813.2

8.93-4 years3-4 years27.713.746.432.227.915.9

8.7>4 years>4 years33.3>4 years50.333.632.1>4 years

NR

NNC

NNE

PIC

PIE

PNC

PNP

PNN

PNE

Diagram7

8.1145.213.68.538.814.7

14.5166.721.310.941.415.3

8.220.62-3 years24.413.541.513.2

8.93-4 years3-4 years27.713.746.415.9

8.7>4 years>4 years33.3>4 years50.3>4 years

Elevated Total Cholesterol and duration of ART

NR

NNC

NNE

PIC

PIE

PNC

PNE

Ark1 (3)

TC>6.2 mmol/L

Time b. ART0-1 year1-2 years2-3 years3-4 years>4 yearsTime on ART0-1 year1-2 years2-3 years3-4 years>4 years

ARVNR:12.512.07.88.39.2ARVNR:8.114.58.28.98.7

ARVNNC:14.91819.822.2ARVNNC:14.91819.822.2

ARVNNE:4.27.18.3ARVNNE:4.49.1

ARVPIC:19.62326.531.130.2ARVPIC:19.62326.531.130.2

ARVPIE:11.913.310.212.512.9ARVPIE:1012.112.414.3

ARVPNC:38.841.441.546.450.3ARVPNC:38.841.441.546.450.3

ARVPNP:20.827.524.632.233.6ARVPNP:20.827.524.632.233.6

ARVPNN:15.821.524.827.932.1ARVPNN:15.821.524.827.932.1

ARVPNE:17.11712.716.310.5ARVPNE:14.715.313.215.9

Time on ART0-1 year1-2 years2-3 years3-4 years>4 years

NR8.114.58.28.98.7

NNC141620.6

NNE5.26.7

PIC13.621.324.427.733.3

PIE8.510.913.513.7

PNC38.841.441.546.450.3

PNP20.827.524.632.233.6

PNN15.821.524.827.932.1

PNE14.715.313.215.9

figur 1 (2)

8.93.73.28.314.626.1

1.56.581820.741.1

59.38.622.223.644

610.39.120.928.146.3

5.411.710.725.329.650.1

Nave

No ART

NRTI

NRTI+NNRTI

NRTI+PI

NRTI+PI+NNRTI

Study 903Mean (95%CI) Change from Baseline in TriglyceridesWeek TDF+3TC+EFV d4T+3TC+EFVChange from Baseline (mg/dL) 1101009080706050403010200-10-20BL4044482428323612162048274 mg/dL0 mg/dLWk 48, p < 0.001Staszewski et al, XIV IAC, LBOr17

Metabolic and Physiognomic Changes in HIV Patients Receiving Antiretroviral Therapy1 syndrome or several?1 etiology or multifactorial?Fat atrophyFat accumulationLipidabnormalitiesDysregulation of glucose metabolism

Cardiovascular disease as a late - rather than early - onset side effect Proposed mechanism for anti-HIV therapy induced increased risk is indirect altered glucose metabolismincrease in cholesterol and triglycerid levelsaltered fat distributionCongitive dyslipidaemia - onset of clinical symptoms: 8-10 yearsEmigration from low to high prevalence areas: 2-3 generationsTreatment of dyslipidaemia: effect after 2-4 years

MI by CART exposureMIs per 1,000 PY (95% CI)No. MIsNo. PY3 9 14 22 31 47 5,714 4,140 4,801 5,847 7,220 8,477Years on CARTTotal

126

36,199Test for trendp

Independent predictors of MIRelative rate of myocardial infarction (95% CI)

Multivariable Poisson model, also adjusted for family history, BMI, HIV transmission, cohort and race0,5D:A:D

MitochondriaEnergy power-houses Have their own DNAMitochondrial DNA is replicated by a separate enzyme to nuclear DNA (DNA polymerase gamma)

MitochondrionCell

ART nave patients: Mean lactate values at 48 weeks ( from BL)mmol/L* p-value as compared to ABC/COM p-value as compared to COM/NFV*p

Study 903Venous lactate sub-study at week 48*Mean (mmol/L) 1.2 1.9 < 0.0001

*Samples collected per AACTG Lactic Acidosis guidelines 6/00 TDF+3TC+EFV d4T+3TC+EFV p-value (n=128) (n=129) Gallant et al, 42nd ICAAC, 2002

Risk of hyperlactatemia with different ART combinations - logistic regressiond4T &/or ddI, no EFV or PId4T &/or ddI + PI, no EFVd4T &/or ddI + EFV, no PId4T &/or ddI + EFV + PIZDV+PI (no ddI or EFV)ZDV+EFV (no PI or ddI)OthersZDV (no PI, ddI or EFV)Boubaker et al - Abstract 57, 7th CROI 2000

Lactic acidemialactic acidosisvenous lactate > 2 mmol/L+arterial ph 2 mmol/Lgrade oflactate acidosissymptoms mortalityacidemia(mmol/L) (%)severe>10 often always80 moderate5 -10 rare usual 0mild2 - 5 no sometimes 0TerminologyRisk & treatment2-9 per 1,000 PY Stop ART time to clinical recovery 1-3 weeks (risk of relapse higher ifrestarting same drug combination)

Reversibility of symptomatic hyperlactatemia other NRTIs or NRTI sparing ?Symptomatic hyperlactatemia in TARHELL (d4T, n=16 to ZDV(4) or ABC (12)1At wk 48 (med.): -0.80 mmol/L Symptomatic hyperlactatemia at UCSD (d4T to ZDV or ABA, n=12)2At diagnosis: S-Lactate : 5.4 mM1 relapse of symptomatic hyperlactatemia2 discontinued due to unrelated reasons9 remained asymptomatic after median 27 months S-lactate (med.) : 1.3 mM

1: Lonergan et al, 4th IWADRL, 2002. Abs 212: Lonergan et al, 42nd ICAAC, 2002. H-1080

Risk factors for femoral osteonecrosis (MRI): % of HIV+ patients with osteonecrosisPrevalence: 15/339 (4.4%) in HIV+; 0/118 (0%) in HIV- (age, sex matched);p=0.02Miller et al, AIM, 2002

The balance when assessing appropriate use of a treatment interventionEffectToxicityGOODBAD

AIDS ratesEuroSIDA 1994 -2003 362.5Mocroft et al, Lancet 2003

Changing population CD4 lymphocyte count in EuroSIDACD4 count during period (/mm3)Mocroft et al, Lancet, 2003

Risk of clinical disease progression by CD4 cell count at start of HAART Years from starting HAART01230.750.800.850.900.951.000-99100-199200-349>350Egger et al, ART Cohort Collaboration, Lancet, 2002RatewithoutAIDSordeath

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# events 267 44 32 # w/CD4 count 237 29 23Pre-therapy CD4 count (cells/L)Rate%SHCS, Frankfurt, EuroSIDA Phillips et al, JAMA, 2001N=2742

1.512.00.670.5>500 400- 300- 200- 100- < 100499 399 299 199Baseline CD4 count (per cubic millimeter)Relative hazard of viral load suppression < 500 c/mL within 32 weeksN=2742SHCS, Frankfurt, EuroSIDA Phillips et al, JAMA, 2001

Weeks from viral load < 500 copies per milliliter Percent with viral load > 500 c/mL baseline CD4 countCD4 count > 350 CD4 count 200 - 349 CD4 count < 200 N.S.N=2346SHCS, Frankfurt, EuroSIDA Phillips et al, JAMA, 2001

Differential diagnosis of clinical events developing in severely immunodeficient patients recently started on ARTFurther complications from pre-therapy impaired health statusStill susceptible to opportunistic infections also after initiationImmune reconstitution syndromeAdverse events

Swiss HIV Cohort(*): Relative risk of different AIDS-defining events in 7/1997-6/1998 versus 1992-4*: 6.636 patients followed for 18.498 person-yearsLedergerber et al, BMJ 1999;319:23

Systems complementary to spontaneous reporting

Enthusiasm for an agent as a function of time since first introducedEnthusiasmTime since initiation of phase I trials (years)CUREDOGREALISTICTextbook in Pharmacology, 1960s

Enthusiasm for HAART as a function of time since first introducedEnthusiasmTime since initiation of phase I trials (years)1996?

Toxicity - ways of detectionRandomised trial: randomised phaseopen-label follow-upPassive surveillanceActive 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.

0.10.50.7511.251.51.75Male health workersSocial insurance, menMale chemical workersHyperlipidaemic menNursing home residentsSocial insurance, womenMale physiciansMale smokers(Ex)-smokers, asbestos workersTrialsCohortsSkin cancer patientsUSAFinlandSwitzerlandUSAUSAFinlandFinlandUSAUSAUSARelative risk (95% CI)Egger et al. BMJ 1998Beta-carotene intake and cardiovascular mortality

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 differencesEthically correctBut, 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 drugsSnap-short of the entire duration of ARTNot powered to detect differences in clinical meaningful outcomes related to benefit and risk from ART

Pooled Analysis of Immediate vs. Deferred AZT0-2090.52(0.39 - 0.68)1-3570.94(0.76 - 1.16)2-4401.05(0.87 - 1.27)3-3691.12(0.91 - 1.38)4-3070.98(0.78 - 1.23)5+2261.10(0.84 - 1.43) No. AIDS/DeathEventsHazard Ratio*Year of Follow-up*Immediate vs. deferred AZT

PI-HAART versus dual NRTI Therapy in Advanced Patients0 - 61670.490.496 - 121410.330.4112 - 181370.130.3018 - 24940.150.2624 - 30860.200.2530 - 36540.160.24 No. AIDS/ Death EventsHazard Ratio*Interval of Follow-up (months) Interval Cum.*PI regimen vs. nRTIs adjusted for baseline CD4+

Toxicity - use of randomised trialsBENEFITSCausal relationship can be evaluatedMethodology ADR reporting well-developed PROBLEMSSize of population is relatively small - rare eventsPatient population is selectedRandomised trials usually have a limited duration - long-term toxicityAssessment of drug under study - multiple combinations

Pivotal Phase 3 trialHill et al, 4th IWADRL

Sample size to detect a doubling in the incidence of existing toxicitiesTwo arm trial, 80% power, 5% significance

Total sample size required

5-10%

4-8%

3-6%

2-4%

1-2%

Difference in incidence rates between arms (%)

Toxicity missed in randomised trials Abnormal fat distribution1995-97: Randomised trials evaluating efficacy/ toxicity of ART. Lipodystrophy not identifiedFeb. 98: First report, Carr et al. PIs is responsible2002: ACTG 384 substudy: NRTIs responsible (PIs only play a minor role)Myocardial infarction1998: Dyslipidaemia acknowledged2002: Do not result in accelerated risk of myocardial infarction2003: Do result in myocardial infarction

LipodystrophyAIDS 1998, 12: F51-F58

Other options when RCT are not able to provide the relevant answerExpert opinion used in marked researchOther sources of data: Case reportsPassive surveillance Cohort studies

Relative importance: summary of experience in last 8 years personal perspectiveRandomised controlled trialsEarly onset, frequent adverse eventsCohort studiesComplemented findings in RCTsRare early onset and late onset adverse eventsSpontanous reporting/passive surveillanceConfusionPerscription studiesNoneCase reports & expert opinionConfusion

Cohort group of patients:the number aint the only relevant characteristicProspective or retrospectiveEnrolment criteriaWhich data are collected ? How are data collected ?Which quality control measures are utilizedPower to detect the outcome being investigated

EuroSIDA - data collectionConsecutive patientsNew cohorts added every 2 year - refreshmentRoutine outpatient clinic appointmentAge > 16 (cohort I-III: CD4 < 500/mm3)Every 6 months (June, December)Data collection formformat adjustableData checkAt site: check of computerised data (preprinted)At coordinating centre: data entry queriessite visits

EuroSIDA Cohorts I-V72 hospitals in 24 European countries + Israel and ArgentinaCohort VI started in November 2003 (additional 1,300 patients)

Surveillance of emerging adverse events outside of RCTRare early and all late-onset adverse eventsIdentificationCase description of phenomenonBiological plausibilityCohort studies Requires open-ended questionsNot feasible in larger cohort studies

Quality versus quantityVolume of questions/work requiredQualityof data

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 eventsStudy a priori identified signalsAlthough methods exist to use large cohorts to identify signals not suspected previously (discussed later) Assess association with drug classes or individual drugsQuantify risk in subgroups of patients

Inclusion: selectionExternal validity extrapolationActive recruitment versus extraction from databases developed for other reasonsConsecutive versus non-consecutiveRetrospective 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 nave cohortComplete assessment of riskDrug experienced cohortAEs may be missed (if they occurs prior to time when patient enters cohort)Cohort still on drug can tolerate the drugBiological 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 dataIncidence of potential toxicityTime from initiation of therapy or follow-upInitiatedtherapyNot Initiatedtherapy

Incidence of adverse eventPerson-year of follow-up# Events

If adverse event is late onsetIf incidence is calculatedOn versus of drug % of patients on drug followed prior to biologically plausible onset of adverse eventTime intervals since starting drugDefine time lag Ability to detect adverse event Time lag versus total exposure time per patient

Event:what is possible and how collectAscertainment (within a population, who developed the AE and who did not) Case definitionObjectively documentedReliable picked up in the patient record notes Quality control source documentation Collected prospectively or retrospectivelyProspectively: allows for training and proper work-up awareness high Retrospective: awareness variableSource verificationCompeting risksHIV-related (e.g. chest pain)Co-morbidities, eg CVD (next slide)

PowerRisk 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/analysisStipulate 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 followedBackground risk low: unusual high rate, but requires many patientsBackground risk high: signal may be missed An independent effect associated with drugsRequires the collection of all important risk factors for the co-morbidity

Lost-to-follow-upShould be low !Is health situation (for the parameter evaluated) for those lost better or poorer than for those remaining ?Emigration versus transferral to hospiceOrganisation of health system:Single - centralised PluralPrivate insurance organisationsGovernment supported programs Ability to follow patients switching program

Principal for working: think outside and work within the boxEinsteins definition of insanity: repeating the same experimentover and over, and expecting different results

Critical criteria for a successful observational studyQuality of data (garbage in = garbage out)Limit the volume of data to be collected to critical important itemsDescribe what you want to achieve prior to launchAllow 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 staffOn-site training of staff Dynamic & ongoing dialogue between clinicians and epidemiological and statistical functions to ensureTimely extract of clinical relevant informationOptimise engagement by entire study team

Prognosis without HAART3-year probability of AIDS in 1604 men enrolled in the Multicenter AIDS Cohort Study (MACS) 1984-1985 Viral load >60,00020 - 60,000 6 - 20,000 1 - 5,000

Effect of Absolute vs. delta-viral load from Setpoint on current CD4-Slope in 628 Patients On-Treatment with Stable Viral LoadPLATO study group, Ledergerber et al, Lancet, 2004

Clinical symptoms of mitochondrial toxicityPolyneuropathy Myopathy Steatosis Lactic acidosis Pancreatitis Vomiting Pancytopenias Renal proximal tubular dysfunction

Brinkman, AIDS 1998; 12:1735-44

Peripheral neuropathyPotential causes:HIVNRTIs (especially the d-drugs)Diabetes mellitusOther internal medicine type diseasesPathophysiology of NRTI-induced:Depletion of neural branchesCourse of events for NRTI-induced:Initial symptoms: tingling/odd sensation/numbness in toes+palm of the foot (sign: decreased sensibility)Always bilateralTypical involvement: incl angle regionPotentially reversible especially soon after debut

Use of large cohort studies to identify signalsIndicators of emerging not previously recognised - toxicityTreatment limiting toxicity causes of Mortality causes of Identify risk factors for indicatorsIf 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)

Death ratesEuroSIDA 1994 -2003 Update: Mocroft et al, Lancet 2003

Why are causes of death important ?ART aims to prevent death but cant be expected to prevent deaths unrelated to HIV

Separate ART failure from background noiseClinical endpoint RCTs of interventions/strategies to inhibit HIV replication and/or improve immune functionObservational studies predictors of response to such interventionsSurveillance system to identify emerging HIV and ART-related deathsTemporal changes in patternRisk factors of specific causes

REQUIEM

REcommendation for Quality Uniform Interpretation & Evaluation of Mortality in HIVPanel with global representation of most ongoing cohort studiesCommon CRFUniform procedure for coding causesPublicly release end of 2004 on www.cphiv.dk

Toxicity - use of cohort studiesBENEFITSLarge size Unselected patientsLong-term follow-upPrevalence, incidence and risk factors of specified potential toxicities evaluated PROBLEMSDetection of associations, not causal relationship - hypothesis generatingQuality of data inversily correlated with volume of data collected

Networking nationally and internationally

What issues will arise when implementing ART in a regionToxicityReal (likelihood of not previously identified versus well established events)Believed but not realContinued morbidity&mortality after starting ARTQuestions on risk:benefit ratioPatient communityPhysicians not fully up to date Request from policy makers to document Resistance

Ongoing active surviellance from cohort studySource of information on risk:benefit ratioSource for continued eduation/trainingthere is nothing like data that makes an impactLack of data = confusionQuality controlBenchmarkingIdentification of specially interesting cases and risk hereofAdditional investigations

Initiatives required to address these issuesPassivesurveillanceActive surveillanceRandomisedcontrolledtrials

Initiatives required to address these issuesPassivesurveillanceActive surveillanceRandomisedcontrolledtrials

Combining cohortsQuality of data collectionUniformity of data to be collectedprospective versus retrospective; quality versus quantityMerging databases

Examples of ongoing cohorts Multicenter: EuroSIDA - 20 European countries Swiss HIV Cohort Study - SwitzerlandFrench HIV Hospital Database FranceATHENA The NetherlandsICONA - ItalyCPCRA observation database - USAUnicenter:Clinic cohorts: Royal Free, Sydney, Frankfurt, Baltimore, St Stephens, Perth, Cologne, etcMerger 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 forprotocol developmentdata extraction and exchange

HIV Collaboration Data Exchange Protocol ( HICDEP )Provide harmonised formats for data-exchange between cohortsIncorporating knowledge from DAD, EuroSIDA, CASCADE, PLATO, ART-CC, SHCSCovers 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.pdfKjr & Ledergerber, Antiviral Therapy, 2004

Structure overview of HICDEP+ Visit info+ Overlap

Many researchers investigating HIV-related metabolic disorders agree that this syndrome most likely has a multifactorial etiologyFour distinct sets of issues have been noted: dyslipidemias, glucose dysregulation, fat depletion, and fat accumulationThis figure presents the incidence of mortality, and 95% confidence intervals, per 100 patient years of follow-up. As previously published, the mortality during 9/94-3/95 was high at over 20 per 100 person-years of follow-up. There was a rapid decline during 1996 and 1997, to a rate of 3.3 per 100 PYFU during March-September 1997. Thereafter, the rates have remained at around3 per 100 person-years of follow-up.

The decrease over time was highly statistically significant. Further, there was no evidence of any change in mortality rates after March 1997, p = 0.37Let us first look at the subgroup of 628 patients with available VL setpoint.VL and delta-VL are each stratified into 4 groups for which we calculated the mean CD4 slope. The 95% confidence intervals are from robust regression and take into account that we have multiple observations per patient.There is a significant association between increasing absolute VL and decreasing CD4-slopes, and between increasing delta-VL and increasing CD4 slopes. If the absolute VL remains below 4 log or delta VL is at or above 2 logs, CD4 slopes remain positive.