Post on 11-Jan-2016
Brainstorming with the Experts
Practical Approaches tothe Complex World of HCV
Supported by an educational grant from
Reducing the Health BurdenReducing the Health Burdenof HCV: Moving from Efficacy of HCV: Moving from Efficacy
to Effectivenessto Effectiveness
Hashem B. El-Serag, MD, MPHHashem B. El-Serag, MD, MPHProfessor of MedicineProfessor of Medicine
Department of GastroenterologyDepartment of GastroenterologyBaylor College of Medicine Baylor College of Medicine
and Michael E. DeBakey VA Medical Center and Michael E. DeBakey VA Medical CenterHouston, TexasHouston, Texas
National Institutes of Health. Hepatology. 2002;36(5 suppl 1):S3-20.
Hepatitis C Infection FactsHepatitis C Infection FactsUnited StatesUnited States
HCV is a leading cause of liver diseaseHCV is a leading cause of liver disease HCV accounts for an estimated 1/3 of HCV accounts for an estimated 1/3 of
hepatocellular carcinoma (HCC) cases hepatocellular carcinoma (HCC) cases HCV is the #1 reason for liver transplantHCV is the #1 reason for liver transplant Approximately 10,000 to 12,000 deaths Approximately 10,000 to 12,000 deaths
are attributed to HCV infection annuallyare attributed to HCV infection annually– Based on death certificates; likely Based on death certificates; likely
underestimatesunderestimates
Burden of HCV DiseaseBurden of HCV Disease
FrequencyFrequency– Prevalence (pool of existing cases)Prevalence (pool of existing cases)
– Incidence (occurrence of new cases)Incidence (occurrence of new cases)
Impact on Impact on – Longevity (premature death)Longevity (premature death)
– Morbidity (in- and outpatient care, quality of life)Morbidity (in- and outpatient care, quality of life)
– Finance (direct and indirect costs to society)Finance (direct and indirect costs to society)
US Prevalence of HCV InfectionNational Health and Nutrition Examination Survey
(NHANES), 1999–2002
Armstrong GL, et al. Ann Intern Med. 2006;144:705-714. Graphic courtesy of Dr. H.B. El-Serag.
0 1 2 3 4 5
Genotype
HCV RNA
Anti-HCV
Million
4.1
3.2
G2/3: 22%G1: 74%
0%
1%
2%
1960 1970 1980 1990 2000 2010 2020 2030
0
50
100
150
1960 1970 1980 1990 2000 2010 2020 2030
Infected 20+ years
Overall prevalence
Past and Future (Estimated) US IncidencePast and Future (Estimated) US Incidenceand Prevalence of HCV Infectionand Prevalence of HCV Infection
Graphic courtesy of Centers for Disease Control and Prevention.
Decline among IDUs
Overall incidence
Seropositive Seropositive withwith
no prior no prior testing (14%)testing (14%)Seropositive and Seropositive and
prior testing (86%)prior testing (86%)
4000 random sample 4000 random sample from 3.2 million veterans from 3.2 million veterans seen at 145 VA facilities seen at 145 VA facilities with research programswith research programs
HCV serology obtained HCV serology obtained on 1288/4000on 1288/4000
52/1288 anti-HCV+52/1288 anti-HCV+ 39/52 HCV RNA+39/52 HCV RNA+
Unaware of Unaware of diagnosis diagnosis
(46%)(46%)Aware of Aware of
diagnosis (54%)diagnosis (54%)
Estimated Chronic HCV Patient Status Estimated Chronic HCV Patient Status in the US Veteran Populationin the US Veteran Population
Dominitz JA, et al. Hepatology. 2005;41:88.
HCV InfectionHCV Infection
Chronic Hepatitis
Cirrhosis
HCC 1%1%
(1%–3%/y)(1%–3%/y)
100%100%
25 y25 y
90%90%(60%–95%/y)(60%–95%/y)
15%15%(10%–30%/y)(10%–30%/y)
HCV to HCC PyramidHCV to HCC Pyramid
Graphic courtesy of Dr. H.B. El-Serag.
-2 -1.5 -1 -0.5 0 0.5 1 1.5 2
All Other Cancers (Average)
LiverThyroid
Esophagus
Lung & Bronchus (Female)
Testis
Corpus & Uterus, NOS
Trends in US Cancer Mortality RatesTrends in US Cancer Mortality Rates
Annual Percent Change (1994–2003)NOS = not otherwise specified.National Cancer Institute. Seer Summary Figures and Tables. Available at: http://seer.cancer.gov/csr/1975_2003/results_merged/topic_graph_trends.pdf. Accessed on October 17, 2008.
Liver Cancer Has the Fastest Growing Liver Cancer Has the Fastest Growing Death Rate in the United StatesDeath Rate in the United States
0.990
0.995
1.000
0 2 4 6 8Years of Follow -Up
HCV and Non-Hodgkin’s LymphomaHCV and Non-Hodgkin’s Lymphomain US Veteransin US Veterans
n = 1369
HR 1.28 (95%CI 1.12–1.45)a
HCV+
HCV-
Giordano TP, et al. JAMA. 2007;297:2010-2017. Graphic courtesy of Dr. H.B. El-Serag.
aHazard ratios adjusted for gender, age, race, era of military service, and VA visits.
• Retrospective cohort studyRetrospective cohort study• 146,394 HCV+ and HCV+ and 572,293 HCV- • US veterans using VA data (1997–2004)US veterans using VA data (1997–2004)
HCV and Intrahepatic HCV and Intrahepatic Cholangiocarcinoma in US VeteransCholangiocarcinoma in US Veterans
With permission from El-Serag HB, et al. Hepatology. 2008. In press.
HCV PrevalenceHCV Prevalence HCC MortalityHCC Mortality
US1960sLowLow
HighHigh
LowLow
HighHigh
Japanese
1920s
European1940s
Association Between HCV Prevalence Association Between HCV Prevalence and HCC Mortalityand HCC Mortality
Schematic ofSchematic of 3 Worldwide Patterns3 Worldwide Patterns
Tanaka Y, et al. Gastroenterology. 2006;130:703-714.
Davis GL, et al. Liver Transpl. 2003;9:331-338.
Estimated Future HCV Disease Burden Estimated Future HCV Disease Burden 2000–20302000–2030
Assuming No CureAssuming No Cure Cirrhosis cases will almost double Cirrhosis cases will almost double
(472,103 to 879,747)(472,103 to 879,747) Decompensated cirrhosis cases will more Decompensated cirrhosis cases will more
than double (65,294 to 146,408)than double (65,294 to 146,408) HCC cases will almost double HCC cases will almost double
(7271 to 13,390)(7271 to 13,390) Liver-related deaths will more than triple Liver-related deaths will more than triple
(13,000/year to 39,875/year)(13,000/year to 39,875/year)
Efficacy and EffectivenessEfficacy and Effectiveness
Efficacy = Efficacy = utility of a medical treatment (drug or utility of a medical treatment (drug or device) evaluated under optimal conditionsdevice) evaluated under optimal conditions
Highly selected patient populationHighly selected patient population Best trained physiciansBest trained physicians Academic centers of excellenceAcademic centers of excellence
Effectiveness = Effectiveness = utility of a medical treatment in utility of a medical treatment in routine clinical settings, ie, real liferoutine clinical settings, ie, real life
Unselected patient populationUnselected patient population All physiciansAll physicians Private practicePrivate practice
Efficacy x Access x Correct Efficacy x Access x Correct Diagnosis x Recommendation Diagnosis x Recommendation
x Acceptance x Adherencex Acceptance x Adherence
With permission from El-Serag HB. Gastroenterology. 2007;132:8.
Treatment of HCVTreatment of HCV
Efficacy in Clinical Trials and Research
Centers
Effectiveness in Community Practice
Efficacy and EffectivenessEfficacy and EffectivenessA Demonstration of the Multiplicative A Demonstration of the Multiplicative
Effect of FactorsEffect of Factors
Efficacy of Rx Efficacy of Rx “X”“X”
60%60%
AccessAccess x 80%x 80%
Correct Correct diagnosisdiagnosis
x 85%x 85%
RecommendRecommend x 85%x 85%
AcceptanceAcceptance x 85%x 85%
AdherenceAdherence x 70%x 70%
Effectiveness of Effectiveness of Rx “X”Rx “X”
= 21%= 21%
El-Serag HB. Gastroenterology. 2007;132:8.
Efficacy of Rx Efficacy of Rx “X”“X”
80%80%
AccessAccess x 80%x 80%
Correct Correct diagnosisdiagnosis
x 85%x 85%
RecommendRecommend x 85%x 85%
AcceptanceAcceptance x 85%x 85%
AdherenceAdherence x 70%x 70%
Effectiveness of Effectiveness of Rx “Y”Rx “Y”
= 28%= 28%
Efficacy of Rx Efficacy of Rx “X”“X”
60%60%
AccessAccess x 90%x 90%
Correct Correct diagnosisdiagnosis
x 90%x 90%
RecommendRecommend x 90%x 90%
AcceptanceAcceptance x 90%x 90%
AdherenceAdherence x 80%x 80%
Effectiveness of Effectiveness of Rx “X” modifiedRx “X” modified
= 32%= 32%
Example 1: Rx “X”
Example 2: Rx “Y”
Example 3: Rx “X” Modified
ConclusionsConclusions
Burden of HCV is increasingBurden of HCV is increasing Although HCV incidence has declined,Although HCV incidence has declined,
the prevalence remains highthe prevalence remains high HCC incidence is increasingHCC incidence is increasing
– Lymphoma, cholangiocarcinomaLymphoma, cholangiocarcinoma
Treatment efficacy in clinical trials and Treatment efficacy in clinical trials and research settings is relatively high, but research settings is relatively high, but effectiveness in community practiceeffectiveness in community practiceis lowis low
Brainstorming with the Experts
Practical Approaches tothe Complex World of HCV
Supported by an educational grant from
Why Is Standard of CareWhy Is Standard of CareFalling Short?Falling Short?
Zobair M. Younossi, MD, MPHZobair M. Younossi, MD, MPHExecutive Director of Research, Inova Health SystemExecutive Director of Research, Inova Health System
Executive Director, Center for Liver Diseases, Executive Director, Center for Liver Diseases,Inova Fairfax HospitalInova Fairfax Hospital
Professor of Medicine, VCU-Inova CampusProfessor of Medicine, VCU-Inova CampusAffiliate Professor of Biomedical SciencesAffiliate Professor of Biomedical Sciences
George Mason UniversityGeorge Mason University Falls Church, Virginia Falls Church, Virginia
Possible Reasons for NonresponsePossible Reasons for Nonresponse
• Dose reductionDose reduction
• Active psychiatric issuesActive psychiatric issues
• Side effectsSide effects
• Patient’s beliefs & social supportPatient’s beliefs & social support
• Provider experienceProvider experience
Treatment FactorsTreatment Factors
Host FactorsHost Factors
Virus FactorsVirus Factors
• CirrhosisCirrhosis
• Poor responsiveness to treatmentPoor responsiveness to treatment
• Racial and ethnic differencesRacial and ethnic differences
• Variability in immune responsesVariability in immune responses
• Obesity and insulin resistanceObesity and insulin resistance
• GenotypeGenotype
• Viral loadViral load
• Sequence variabilitySequence variability
Younossi ZM, et al. J Hepatol. 2008;48:S285.
Can We Predict Nonresponse with Can We Predict Nonresponse with Gene Expression Profiling?Gene Expression Profiling?
68 HCV-infected patients (30 treatment-naive) 68 HCV-infected patients (30 treatment-naive) treated with PEG IFN treated with PEG IFN -2a or -2a or -2b plus RBV-2b plus RBV
Blood samples collected prior to treatment and on Blood samples collected prior to treatment and on days 1, 7, 28, and 56 posttreatmentdays 1, 7, 28, and 56 posttreatment
Virologic response data collectedVirologic response data collected From the peripheral blood cells, total RNA From the peripheral blood cells, total RNA
extracted, quantified, and used for 1-step RT-PCR extracted, quantified, and used for 1-step RT-PCR to profile 154 mRNAsto profile 154 mRNAs
Multiple regression and stepwise selection Multiple regression and stepwise selection performedperformed– Differences in gene expression assessed at different Differences in gene expression assessed at different
time points and predictive performance evaluatedtime points and predictive performance evaluated
Gene Expression Models Predicting SVRGene Expression Models Predicting SVRin Treatment-Naive HCV- Genotype 1 Patients in Treatment-Naive HCV- Genotype 1 Patients
Younossi ZM, et al. J Hepatol. 2008;48:S285.
PPV = positive predictive value; NPV = negative predictive value; AUC = area under the curve;
HCV Genotype
Gene(s) in the Predictive
Model
ModelP-
value
Sensitivity %(95% CI)
Specificity %
(95% CI)
PPV %
NPV %
AUC
Pretreatment
Genotype 1
EP300, SOCS6 .00143285.7
(42.2–97.6)83.3
(51.6–97.4)75.0 90.9
0.881(0.651–0.980)
24 hours after initiation of treatment
Genotype 1
IL1B, ADAM9 .00908971.4
(29.3–95.5)81.8
(48.2–97.2)71.4 81.8
0.74(0.484–0.913)
7 days after initiation of treatment
Genotype 1
PRKRIR .009460100.0(58.9–100.0)
66.7(34.9–89.9)
63.6 100.00.786
(0.540–0.936)
This data suggests that SVR depends on the successful engagement of host-
specific response by IFN-based therapy
Immunity, Race, and NonresponseImmunity, Race, and Nonresponse HCV-infected African Americans (AA) have lower HCV-infected African Americans (AA) have lower
sustained virologic response (SVR) compared with sustained virologic response (SVR) compared with HCV-infected HCV-infected Caucasian American (CA): 28% vs. 52%28% vs. 52%11
Could lower SVR be related to differences in immune Could lower SVR be related to differences in immune response?response?– 187 Caucasian American (CA) and 187 African American (AA)
infected with HCV genotype 1 from Virahep-C study Virahep-C study
– Type 1 helper (Th1) response to HCV core protein and Type 1 helper (Th1) response to HCV core protein and combined HCV antigens were lower in AA compared with CAcombined HCV antigens were lower in AA compared with CA
– This difference in immunity remained significant after adjusting for gender, serum alanine aminotransferase, histologic severity and viral load22
– This suggests that AA may have weaker This suggests that AA may have weaker HCV-specific immunityHCV-specific immunity
1. Conjeevaram HS, et al. Gastroenterology. 2006;131:470-477 2. Rosen HR, et al. Hepatology. 2007;46:350-358
Obesity, Diabetes, Steatosis, and Nonresponse
DDiisseeaasse e
PPrrooggrreessssiioonn
Impact on progression
RReessppoonnsse e
tto o
TThheerraappyy
+
SVR
SVR
Impact on the efficacy of treatment
HCV graphic courtesy of David Brunelli, MD. http://www.med-ars.it/virus.htm.
0%
10%
20%
30%
40%
50%
60%
70%
0%
10%
20%
30%
40%
50%
60%
70%
Graphic courtesy of Dr. Zobair M. Younossi.
Author, Year Evidencea N SVR (%) Association with SVR
Kumar D, 20021 II-2 62 G1 (32), G3 (65)
For G3, SVR steatosis
Poynard T, 20032 II-2 1428 56 SVR with steatosis
Bressler B, 20033 II-2 253 42 SVR with BMI >30 kg/m2, G1, and cirrhosis
Sanyal A, 20034 II-2 110 NA Response in fatty liver disease
Thomopoulos K, 20055
II-2 116 52 SVR with steatosis, GGT, and G1/4
D’Souza R, 20056 II-1 59 56 SVR with Insulin resistance, fasting insulin, and Asian ethnicity
Harrison S, 20057 II-2 315 40 SVR with steatosis and steatohepatitis
Romero-Gomez M, 20058
II-2 159 53 SVR with insulin resistance, fibrosis, and GI
Camma C, 20069 II-2 291 NA SVR with steatosis, fibrosis, and age >50 y
Jian Wu Y, 200610 II-1 98 57 SVR with insulin resistance and fasting insulin
Tarantino G, 200611 II-2 80 NA SVR with waist circumference
Conjeeveram HS, 200712
II-1 399 NA SVR with insulin resistance
Westin J, 200713 II-1 272 G3: 89; nonG3: 56
SVR with steatosis in nonG3 only
Insulin Resistance, Obesity, Steatosis, and Nonresponse
Graphic courtesy of Dr. Zobair M. Younossi.aAASLD strength-of-evidence scale. Strader DB, et al. Hepatology. 2004;39:1147-1171.
Insulin Resistance and NonresponseInsulin Resistance and NonresponseGenotype 1 Patients Treated with PEG IFN + RBV for 48 weeksa
aTreatment: PEG IFN -2a 180 g/wk or PEG IFN -2b 1.5 g/kg/wk + RBV 800–1200/d.HOMA = Homeostasis Model of Assessment; an index of insulin resistance calculated as fasting insulin (mIU/L) x fasting glucose (mmol/L) 22.5.Romero-Gomez M, et al. Gastroenterology. 2005;128:636-641.
20%
40%
61%
0
10
20
30
40
50
60
70
HOMA <2 HOMA 2–4 HOMA >4
SVR (%)
n = 43 n = 45 n = 25
Patients with chronic hepatitis C treated with IFNPatients with chronic hepatitis C treated with IFNor IFN/RBV for 24 weeks (N = 89)or IFN/RBV for 24 weeks (N = 89)11
– Insulin resistance and beta cell function were measured by Insulin resistance and beta cell function were measured by HOMA-IR and HOMA-%B, respectivelyHOMA-IR and HOMA-%B, respectively
– SVR was associated with improvement of insulin resistance and SVR was associated with improvement of insulin resistance and beta cell function beta cell function
Non-genotype 3 patients (N=96) re-treated with PEG-Non-genotype 3 patients (N=96) re-treated with PEG-IFN+RBV for 24 weeks (HALT-C)IFN+RBV for 24 weeks (HALT-C)22
– Insulin resistance was measured by HOMA-IR Insulin resistance was measured by HOMA-IR – After 20 weeks of treatment, HOMA-IR declined in responders After 20 weeks of treatment, HOMA-IR declined in responders
(HCV RNA negative) as compared to partial responders ((HCV RNA negative) as compared to partial responders (>> 1 log 1 log decline but positive) or null responders (< 1 log decline)decline but positive) or null responders (< 1 log decline)
Change in HOMA-IR from baseline: -2.68 vs. -0.72 vs. +0.1, p=0.017Change in HOMA-IR from baseline: -2.68 vs. -0.72 vs. +0.1, p=0.017
1. Kawaguchi T, et al. Am J Gastroenterol. 2007;102:570-576.2. Delgado-Borrego A, et al. Hepatology 2008; 48 (no.3) Supplement: 271 (Abstract)
Impact of SVR on Insulin ResistanceImpact of SVR on Insulin Resistance
• IR seems to be associated with low SVR• Achieving SVR may improve IR• What are the mechanisms?
• Host-related• Virus-related
Mechanism—Host-related Metabolic Conditions Contributing to Nonresponse
LOWER
SVR
IR
Pro-inflammatory
adipocytokines
Lower interferon bioavailablity
+
Increase adipose tissue +
Biologicresponse
to IFN-
+ +
Oxidativestress
Graphic courtesy of Dr. Zobair M. Younossi.
Proteasomal degradation
of IRS-1(Insulin receptor
substrate 1)
STAT-1(Signal transducer
& activator of transcription-1)
Promotes
ImpairedIFN
signaling
Impairedinsulin
signaling
SOCS-3(Suppressor of
cytokine signalling-3)
Negative regulator
Up-regulatesexpression
LowerSVR
LowerSVR
Mechanism—Virus-Related Metabolic Conditions Contributing to Nonresponse
Graphic courtesy of Dr. Zobair M. Younossi.HCV graphic courtesy of David Brunelli, MD. http://www.med-ars.it/virus.htm
ConclusionsConclusions
Nonresponse may be related to virus-, host-, or Nonresponse may be related to virus-, host-, or treatment-related factorstreatment-related factors– Virus—genotypes, viral loadVirus—genotypes, viral load– Host—early gene expression, immunity, metabolic Host—early gene expression, immunity, metabolic
conditionsconditions– Treatment—adherence to full regimen, Treatment—adherence to full regimen,
side-effect managementside-effect management Although some of these factors are fixed, others Although some of these factors are fixed, others
can be modified, potentially improving responsecan be modified, potentially improving response These strategies to improve response must be These strategies to improve response must be
tested in well designed clinical trialstested in well designed clinical trials
Brainstorming with the Experts
Practical Approaches tothe Complex World of HCV
Supported by an educational grant from
Challenges Posed by Nonresponders and Relapsers
Fred Poordad, MDChief, Hepatology and Liver Transplantation
Associate Professor of MedicineComprehensive Transplant Center
Cedars-Sinai Medical CenterLos Angeles, California
Re-treatmentRe-treatment
Should We Ever Re-treat a PEG IFN/RBV Should We Ever Re-treat a PEG IFN/RBV Nonresponder or Relapser?Nonresponder or Relapser?
EPIC-3 DIRECT
What Did We Learn from These Trials?
EPIC-3 = Evaluation of Peg-Intron in Control of Hepatitis C Cirrhosis.REPEAT = Retreatment with Pegasys in Patients Not Responding to Peg-Intron Therapy.DIRECT = Daily-Dose Consensus Interferon and Ribavirin: Efficacy of Combined Therapy.
REPEAT
EPIC-3 Study DesignEPIC-3 Study Design2293 HCV-infected patients 2293 HCV-infected patients with advanced fibrosis whowith advanced fibrosis whofailed prior (PEG)IFN/RBVfailed prior (PEG)IFN/RBV
PEG IFN PEG IFN -2b 1.5 µg/kg/wk + RBV 800–1400 mg/d-2b 1.5 µg/kg/wk + RBV 800–1400 mg/d
HBV RNA at 12 wk
Continue Continue treatment through treatment through
wk 48wk 48
Follow-up Follow-up through wk 72through wk 72
Metavir fibrosis stage
PEG IFN PEG IFN -2b -2b 0.5 µg/kg/wk 0.5 µg/kg/wk vs control for vs control for
up to 3 y up to 3 y
PEG IFN PEG IFN -2b -2b 0.5 µg/kg/wk 0.5 µg/kg/wk vs control for vs control for
up to 5 yup to 5 y
PosPos NegNeg
F2–3F2–3 F4F4
Poynard T, et al. J Hepatol. 2008;48:S369.
SVR in Nonresponders by Prior SVR in Nonresponders by Prior Treatment and Genotype/Fibrosis ScoreTreatment and Genotype/Fibrosis Score
68
16
18
18
5640
8
3938
18
6
4
4
4
0 20 40 60 80
G2/3 F2
G2/3 F3
G2/3 F4
G1 F2
G1 F3
G1 F4
Overall
SVR
Prior PEGIFN/RBV (n = 476)
Prior IFN/RBV (n = 903)
SVR = sustained virologic response.Poynard T, et al. J Hepatol. 2008;48:S369.
76
28
42
43
51
32
21
18
26
59
67
62
61
32
0 20 40 60 80
G2/3 F2
G2/3 F3
G2/3 F4
G1 F2
G1 F3
G1 F4
Overall
SVR
Prior PEGIFN/RBV (n = 344)
Prior IFN/RBV (n = 300)
Poynard T, et al. J Hepatol. 2008;48:S369.
SVR in Relapsers by Prior Treatment SVR in Relapsers by Prior Treatment and Genotype/Fibrosis Scoreand Genotype/Fibrosis Score
Association of SVR withAssociation of SVR withHCV RNA at Week 12HCV RNA at Week 12
Nonresponders and RelapsersNonresponders and Relapsers
12
56
00
20
40
60
Pat
ien
ts w
ith
SV
R (
%)
HCV RNAHCV RNA
UndetectableUndetectable(n = 823)(n = 823)
Positive; Positive; ≥2-log decrease≥2-log decrease
(n = 188)(n = 188)
Positive; Positive; <2-log decrease<2-log decrease
(n = 66)(n = 66)
Poynard T, et al. J Hepatol. 2008;48:S369.
Follow-up
Wk 0Wk 0
Jensen DM, et al. Hepatology. 2007;46:291A.
REPEAT Study DesignREPEAT Study Design
Wk 48Wk 48Wk 24Wk 24 Wk 72Wk 72 Wk 96Wk 96
Follow-up
Follow-up
Follow-up
AA
BB
CC
DD
RBV 1000–1200 mg/d
RBV 1000–1200 mg/d
RBV 1000–1200 mg/d
RBV 1000–1200 mg/d
Wk 12Wk 12
PEG IFN -2a 180 µg/wk
PEG IFN -2a 180 µg/wk
PEG IFN -2a 180 µg/wk
PEG IFN -2a 180 µg/wk
360 µg/wk
360 µg/wk
No
nre
spo
nd
ers
to p
revi
ou
s N
on
resp
on
der
s to
pre
vio
us
PE
G I
FN
P
EG
IF
N
-2a/
RB
V (
N =
942
)-2
a/R
BV
(N
= 9
42)
SVR with PEG IFN SVR with PEG IFN -2a/RBV Re-treatment-2a/RBV Re-treatment+/- Higher-dose Induction, +/- Longer Duration+/- Higher-dose Induction, +/- Longer Duration
Jensen DM, et al. Hepatology. 2007;46:291A. ITT analysisITT analysis
aaAll arms 91% genotype 1.All arms 91% genotype 1.
72-wk induction arm (n = 317) 72-wk induction arm (n = 317)
48-wk induction arm (n = 156)48-wk induction arm (n = 156)
Treatment ArmTreatment Armaa
16161414
77 99
00
1010
2020
3030
4040
AA BB CC
SV
R (
%)
SV
R (
%)
DD
72-wk standard arm (n = 156)72-wk standard arm (n = 156)
48-wk standard arm (n = 313)48-wk standard arm (n = 313)
DIRECT Study—Consensus IFN DIRECT Study—Consensus IFN in PEG IFN/RBV Failuresin PEG IFN/RBV Failures
PEG IFN PEG IFN -2a or -2a or -2b + RBV-2b + RBV
<2-log decline HCV RNA<2-log decline HCV RNA HCV RNA positiveHCV RNA positive
12 wk12 wkaa 24 wk24 wk
Consensus IFN Consensus IFN 9 µg QD + RBV9 µg QD + RBVbb
48 wk (n = 170)48 wk (n = 170)
Consensus IFN Consensus IFN 15 µg QD + RBV15 µg QD + RBVbb
48 wk (n = 170)48 wk (n = 170)
No treatmentNo treatment24 wk (n = 170)24 wk (n = 170)
May be eligible for May be eligible for roll overroll over
Randomization (N = 510)
DIRECT Trial. Available at: http://www.directtrial.com/. Accessed on October 17, 2008.
aaPatients with <2-log drop in HCV RNA between week 12 and 24. bRBV 1000–1200 mg/d.
No
nre
spo
nd
ers
No
nre
spo
nd
ers
SVR with Consensus IFN Re-treatmentSVR with Consensus IFN Re-treatmentDIRECT Trial (N = 343)DIRECT Trial (N = 343)
OverallOverall
<2-log drop<2-log dropaa
55 66
00
1010
2020
3030
4040
OverallOverall
Consensus IFN 9 µg QD + RBVConsensus IFN 9 µg QD + RBV
SV
R (
%)
SV
R (
%)
4466
00
F0–F3F0–F3bb F4F4bb
1010 1111
OverallOverall
2200
F0–F3F0–F3bb F4F4bb
2929
Consensus IFN 15 µg QD + RBVConsensus IFN 15 µg QD + RBV
>2-log drop>2-log dropaa
OverallOverall
<2-log drop<2-log dropaa
>2-log drop>2-log dropaa
aHCV RNA response to previous therapy.bFibrosis score within 3 years of study entry.
Bacon B, et al. Hepatology. 2007;46:311A. ITT analysisITT analysis
Maintenance TherapyMaintenance Therapy
Does PEG IFN Prevent Histologic Does PEG IFN Prevent Histologic and Clinical Progression?and Clinical Progression?
HALT-C COPILOT
What Did We Learn from These Trials?
HALT-C = Hepatitis C Antiviral Long-term Treatment against Cirrhosis.COPILOT = Colchicine vs Peg-Intron Long-Term.
HALT-C Trial DesignHALT-C Trial Design
Re-treatment (“Lead-In”) Re-treatment (“Lead-In”) PhasePhase
Maintenance PhaseMaintenance Phase
11451145HCV-HCV-infected infected patients patients with with advanced advanced fibrosis fibrosis whowhofailed failed IFN-based IFN-based therapytherapy
PEG IFN PEG IFN -2a 180 -2a 180
µg/wk + RBV µg/wk + RBV 1000–1200 1000–1200
mg/d for 24–mg/d for 24–48 wk48 wk
Nonresponse at wk 24
(n = 662)
Relapse/breakthrough during or after
48 wk(n = 151)
PEG IFN PEG IFN -2a 90 -2a 90 µg/wkµg/wk
(n = 517)(n = 517)
Discontinue Discontinue treatmenttreatment(n = 533)(n = 533)
Ran
do
miz
atio
n
Express(n = 237)
Pro
gre
ssio
n o
f L
iver
Dis
ease
The HALT-C Trial. Available at: The HALT-C Trial. Available at: http://www.haltctrial.org/overview.html. Accessed on September 30, 2008.
3.5
y
4.64.6
13.213.2
3.23.2
31.931.9
6.6*6.6*
14.3*14.3*
2.8*2.8*
28.2*28.2*
00
1010
2020
3030
4040
DeathDeath DecompensationDecompensation HCCHCC
No treatment (n = 533)No treatment (n = 533)
PEG IFN PEG IFN -2a 90 µg/wk (n = 517)†-2a 90 µg/wk (n = 517)†
*P = NS †17% d/c at 1 y and 30% d/c at 3.5 y
Di Bisceglie AM, et al. Hepatology. 2007;46:290A.
Effect of Long-term PEG IFN Effect of Long-term PEG IFN HALT-C Data at 3.5 YearsHALT-C Data at 3.5 Years
% P
atie
nts
%
Pat
ien
ts
IncreaseIncreasein Fibrosisin Fibrosis
COPILOT Study DesignCOPILOT Study Design
Baseline Baseline
LB = liver biopsy; US = ultrasound.
Afdhal NH, et al. J Hepatol. 2008;48:S4.
24 Weeks24 Weeks12 Weeks12 Weeks 2 Years2 Years 4 Years4 Years
PEG IFN -2b 0.5 µg/kg/wk (n = 286)
Colchicine 0.6 mg BID (n = 269)
LB, US,LB, US,endoscopyendoscopy
Clinical Clinical evaluationevaluation
USUS Endoscopy, Endoscopy, LBLB
Endoscopy, Endoscopy, LBLB
IFN/RBV orPEG IFN/RBV
Nonresponders with Ishak stage 3–6
21.2
16.718.5
12.6
0
5
10
15
20
25
ITT PP
Clinical Endpoint (%)
PEG IFN PEG IFN -2b 0.5 µg/kg/wk (n = 286)-2b 0.5 µg/kg/wk (n = 286)
Colchicine 0.6 mg BID (n = 269)Colchicine 0.6 mg BID (n = 269)
Impact of Long-Term Colchicine vs PEG Impact of Long-Term Colchicine vs PEG IFN on Liver Disease ProgressionIFN on Liver Disease Progression
COPILOT Final Results
Afdhal NH, et al. J Hepatol. 2008;48:S4.ITT = intention-to-treat analysis; PP = per-protocol analysis.
Group Event-Free Survival— PEG IFN vs Colchicine
(P-value, logrank)
All .311
With portal hypertension .057
Without portal hypertension .345
ITT AnalysisITT Analysis
Group Event-Free Survival— PEG IFN vs Colchicine
(P-value, logrank)
All .146
With portal hypertension .038
Without portal hypertension .656
On-Drug AnalysisOn-Drug Analysis
Afdhal NH, et al. J Hepatol. 2008;48:S4.
COPILOT—Event-Free SurvivalCOPILOT—Event-Free SurvivalColchicine vs PEG IFN
Individualizing Therapy for Individualizing Therapy for Nonresponders and RelapsersNonresponders and Relapsers
Maintenance therapy has no significant beneficial effectsMaintenance therapy has no significant beneficial effects
Nonresponders or relapsers to prior
IFN +/- RBV
Consider re-treatment with PEG IFN/RBV
Nonresponders to prior PEG IFN/RBV
Do not re-treat with PEG IFN/RBV
Consider consensus IFN for nonresponders with >2-log
decline and no cirrhosis
Relapsers to prior PEG IFN/RBV
Consider re-treatment with PEG IFN/RBV
ConclusionsConclusions
Response to re-treatment regimens Response to re-treatment regimens depends on initial responsedepends on initial response
Majority of patients do not warrant Majority of patients do not warrant re-treatment with current regimensre-treatment with current regimens
Future regimens with small molecules Future regimens with small molecules need to be further studied in these need to be further studied in these patient populations patient populations
Brainstorming with the Experts
Practical Approaches tothe Complex World of HCV
Supported by an educational grant from
Can We Do Better?Role of Emerging
STAT-C Drugs
Ira M. Jacobson, MDVincent Astor Professor of Clinical Medicine
Chief, Division of Gastroenterology and HepatologyMedical Director of the Center for the
Study of Hepatitis CWeill Cornell Medical College
New York, New York
Emerging Anti-HCV TherapiesEmerging Anti-HCV Therapies
Genome Sequence-Based
RNA interference
EnzymeInhibitors
Protease
Polymerase
Other
IFN and RBV modifications• Albumin IFN, omega IFN• Taribavirin (viramidine)
Immune approaches• Therapeutic vaccines• Toll-like receptor agonists• Yeast expressing HCV Ag
Targeting cellular factors• Cyclophilin antagonists• Nitazoxanide
STAT-CSTAT-C
Other EnzymeInhibitors
Ribozymes
Antisenseoligonucleotides
Graphic courtesy of Dr. I. M. Jacobson.Ag = antigen; IFN = interferon; RBV = ribavirin.
Increased SVR Resistance
Side effectsDecreased duration
Key Themes at the Dawn of a New EraKey Themes at the Dawn of a New Era
Graphic courtesy of Dr. I. M. Jacobson.
PROVE1: Telaprevir Phase IIPROVE1: Telaprevir Phase IIU.S., Genotype 1, Treatment NaiveU.S., Genotype 1, Treatment Naive
240 48 72Weeks 12 6036
Peg-IFN + RBV Follow-upTVR +
Peg-IFN + RBV T12/PR24
(n=79)
TVR + Peg-IFN + RBV Peg-IFN + RBV Follow-up
T12/PR48(n=79)
Follow-upPR48 (control)
(n=75)Peg-IFN + RBV Placebo +
Peg-IFN + RBV
Follow-upT12/PR12
(n=17)TVR +
Peg-IFN + RBV
McHutchison J et al, J Hepatol. 2008;48:S4.
Peg-IFN = Peg-IFN alfa-2a 180 ug/wkRBV = Ribavirin 1000-1200mg/dayTVR = Telaprevir 750mg q8h
PROVE 2 Study PROVE 2 Study European Phase 2: G1, NaïveEuropean Phase 2: G1, Naïve
Interim AnalysisInterim Analysis
Arm A
Arm B
Arm C
Arm D
Weeks
12 24 48
TVR+PEG+RBVTVR+PEG+RBV
TVR+PEGTVR+PEG
TVR+PEG+RBVTVR+PEG+RBV
PEG IFN alfa-2a 180 ug + RBV 1000-1200 mgPEG IFN alfa-2a 180 ug + RBV 1000-1200 mg
0
PEG+RBV
36
Dusheiko G et al, J Hepatol. 2008;48:S26.
N=82
N=81
N=82
N=78
PROVE2: SVR Rates PROVE2: SVR Rates
0
20
40
60
80
Control T/P/R24 T/P/R12 T/P12
48
68*
36
% HCV RNAneg 62**
Higher relapse ratewith 12 vs 24 weeks
Impaired response, more breakthrough
and more relapse w/out RBV
*p=0.01 vs control**p=0.08 vs control
(SVR-12)
Dusheiko G et al, J Hepatol. 2008;48:S26.
Boceprevir: SPRINT-1 Study Boceprevir: SPRINT-1 Study Inernational, Genotype 1, Treatment NaiveInernational, Genotype 1, Treatment Naive
PEG 1.5 µg/kg + RBV 800-1400 mg + boceprevir 800 mg TID for 48 weeksPEG 1.5 µg/kg + RBV 800-1400 mg + boceprevir 800 mg TID for 48 weeks
PEG 1.5 µg/kg + RBV 800-1400 mg + boceprevir 800 mg TID for 28 weeksPEG 1.5 µg/kg + RBV 800-1400 mg + boceprevir 800 mg TID for 28 weeks
No Lead-inNo Lead-in Dosing Strategy Dosing Strategy
PEG 1.5 µg/kg + RBV 400-1000 mg + boceprevir 800 mg TID for 48 weeksPEG 1.5 µg/kg + RBV 400-1000 mg + boceprevir 800 mg TID for 48 weeks
Low dose Low dose RBVRBV
Dosing Strategy Dosing Strategy
PEG 1.5 µg/kg +RBV 800-1400 mg for 48 weeks
PEG 1.5 µg/kg +RBV 800-1400 mg for 48 weeksControlControl
PEG 1.5 µg/kg + RBV 800-1400 mg + boceprevir 800 mgTID for 24 weeks
PEG 1.5 µg/kg + RBV 800-1400 mg + boceprevir 800 mgTID for 24 weeks
PEG 1.5 µg/kg + RBV 800-1400 mg + boceprevir 800 mg TID for 44 weeksPEG 1.5 µg/kg + RBV 800-1400 mg + boceprevir 800 mg TID for 44 weeks
PEG-2b + PEG-2b + RBV 800-1400 mg RBV 800-1400 mg
x 4 weeksx 4 weeks
PEG-2b + PEG-2b + RBV 800-1400 mg RBV 800-1400 mg
x 4 weeksx 4 weeks
PEG-2b + PEG-2b + RBV 800-1400 mg RBV 800-1400 mg
x 4 weeksx 4 weeks
PEG-2b + PEG-2b + RBV 800-1400 mg RBV 800-1400 mg
x 4 weeksx 4 weeksLead-inLead-in
Dosing Strategy Dosing Strategy
Follow-up Follow-up x 44 weeksx 44 weeksFollow-up Follow-up x 44 weeksx 44 weeks
Follow-up Follow-up x 24 weeksx 24 weeksFollow-up Follow-up x 24 weeksx 24 weeks
Follow-up Follow-up x 24 weeksx 24 weeksFollow-up Follow-up x 24 weeksx 24 weeks
Follow-up Follow-up x 24 weeksx 24 weeksFollow-up Follow-up x 24 weeksx 24 weeks
Follow-up Follow-up x 24 weeksx 24 weeksFollow-up Follow-up x 24 weeksx 24 weeks
Follow-up Follow-up x 44 weeksx 44 weeksFollow-up Follow-up x 44 weeksx 44 weeks
Kwo et al., EASL 2008, p. 372; Oral Presentation; Kwo P, et al, Hepatology. 2008;48:1027A.
SPRINT-1—SVR-12 RatesSPRINT-1—SVR-12 RatesPEG IFN PEG IFN -2b + RBV-2b + RBV +/-+/- BoceprevirBoceprevir
0
20
40
60
80
100
SV
R (
%) 56 55
7466
PEG IFN -2b/RBV lead-in
No PEG IFN/RBV lead-in
SVR = sustained virologic response.Kwo P, et al, Hepatology. 2008;48:1027A. Graphic courtesy of Dr. I. M. Jacobson.
38
(SVR-12)(SVR-12)28 wk28 wk 48 wk48 wk
Control (PEG IFN/RBV)
48 wk48 wk(SVR-12)(SVR-12)
(58/
103)
(59/
107)
(76/
103)
(68/
103)
(39/
104)
STAT-C Agents STAT-C Agents in Nonrespondersin Nonresponders
“Functional Monotherapy”“Functional Monotherapy”Or Something More?Or Something More?
Virologic ResponseVirologic Response in PEG-Interferon + Ribavirin Non-Responders in PEG-Interferon + Ribavirin Non-Responders
(ITT, N=357)(ITT, N=357)Initial treatment armInitial treatment arm EOT EOT SVR SVR
Control Lead-in with PEG-IFN Control Lead-in with PEG-IFN αα-2b-2b + ribavirin + ribavirin
•PCR negativePCR negative →→ PEG-IFN PEG-IFN αα-2b-2b + ribavirin + ribavirin 8% (4/49)8% (4/49) 2% (1/49)2% (1/49)
•PCR positivePCR positive →→ P PEG-IFN EG-IFN αα-2b-2b + ribavirin + boceprevir + ribavirin + boceprevir 400 mg400 mg
32% 32% (14/44)*(14/44)* 7% (3/44)7% (3/44)
PEG-IFN PEG-IFN αα-2b-2b + boceprevir 100 mg + boceprevir 100 mg 6% (3/48)*6% (3/48)* 2% (1/48)2% (1/48)
PEG-IFN PEG-IFN αα-2b-2b + boceprevir 200 mg + boceprevir 200 mg 16% 16% (8/49)*(8/49)* 12% (6/49)12% (6/49)
PEG-IFN PEG-IFN αα-2b-2b + ribavirin + boceprevir 400 mg + ribavirin + boceprevir 400 mg 20% 20% (10/49)*(10/49)* 14% (7/49)14% (7/49)
PEG-IFN PEG-IFN αα-2b-2b + boceprevir 400 mg + boceprevir 400 mg 13% 13% (13/97)*(13/97)* 5% (5/97)5% (5/97)
PEG-IFN PEG-IFN αα-2b-2b + boceprevir 800 mg + boceprevir 800 mg 21% 21% (14/65)*(14/65)* 4% (3/65)4% (3/65)
Assay: TaqMan PCR assay LLD < 125 IU/ml (N/ITT)= number of subjects/Intent to Treat ( n=357 subjects)Assay: TaqMan PCR assay LLD < 125 IU/ml (N/ITT)= number of subjects/Intent to Treat ( n=357 subjects)*143 subjects rolled over PegInterferon + ribavirin + boceprevir 800 mg TID *143 subjects rolled over PegInterferon + ribavirin + boceprevir 800 mg TID
PROVE3: Prior Treatment FailuresPROVE3: Prior Treatment Failures
240 48 72Weeks 12 6036
(P) Peg-IFN = pegylated interferon alfa-2a 180 µg/wk; (R) RBV = ribavirin 1,000 or 1,200 mg/day;(T) TVR = telaprevir 750 mg q8h
Interim analysis
Peg-IFN + RBV
Follow-upT12/PR24TVR +
Peg-IFN + RBV
SVR
Follow-upPR48
(control) Peg-IFN + RBV Placebo +
Peg-IFN + RBV
SVR
Follow-upSVR
TVR + Peg-IFNT24/P24 (no RBV)
T24/PR48 Follow-upSVR
Peg-IFN + RBV TVR +
Peg-IFN + RBV
McHutchison JG, et al. 59th AASLD. October 31-November 4, 2008. Abstract 269.
PROVE3: Interim Results in Prior PROVE3: Interim Results in Prior NonrespondersNonresponders
PR48PR48
N=68N=68
T12/PR24T12/PR24
N=66N=66
T24/PR48T24/PR48
N=64N=64
T24/P24T24/P24
N=62N=62
Wk 4Wk 4 0% 50% 34% 32%
Wk 12Wk 12 3% 71% 55% 37%
EOTEOT NA 65% NA 34%
SVR-12SVR-12 NA 41% NA 11%
McHutchison JG, et al. 59th AASLD. October 31-November 4, 2008. Abstract 269.
PROVE3: Interim Results in PriorPROVE3: Interim Results in PriorRelapsersRelapsers
PR48PR48
N=42N=42
T12/PR24T12/PR24
N=40N=40
T24/PR48T24/PR48
N=41N=41
T24/P24T24/P24
N=39N=39
Wk 4Wk 4 0% 80% 71% 72%
Wk 12Wk 12 17% 88% 78% 78%
EOTEOT NA 83% NA 69%
SVR-12SVR-12 NA 72% NA 36%
McHutchison JG, et al. 59th AASLD. October 31-November 4, 2008. Abstract 269.
PROVE3: Interim Results in PriorPROVE3: Interim Results in PriorBreakthroughsBreakthroughs
PR48PR48
N=3N=3
T12/PR24T12/PR24
N=9N=9
T24/PR48T24/PR48
N=8N=8
T24/P24T24/P24
N=10N=10
Wk 4Wk 4 0% 44% 75% 30%
Wk 12Wk 12 0% 44% 75% 50%
EOTEOT NA 44% NA 30%
SVR-12SVR-12 NA 44% NA 20%
McHutchison JG, et al. 59th AASLD. October 31-November 4, 2008. Abstract 269.
Telaprevir “Rollover” StudyTelaprevir “Rollover” Study
Open label telaprevirOpen label telaprevir Treatment failures in control arms of the three PROVE Treatment failures in control arms of the three PROVE
trialstrials Prior response patterns well characterizedPrior response patterns well characterized Telaprevir + PEG IFN 2a + RBV 12 weeks, then 12 or 36 Telaprevir + PEG IFN 2a + RBV 12 weeks, then 12 or 36
weeks of additional therapyweeks of additional therapy Stopping rules: Stopping rules:
– HCV RNA > 100 IU/ml at week 4HCV RNA > 100 IU/ml at week 4
– HCV RNA > 25 IU/ml at week 12HCV RNA > 25 IU/ml at week 12
Shiffman ML, et al. 59th AASLD, October 31-November 4, 2008. Abstract 1852; Shiffman ML, et al. J Hepatol. 2008;4:1135A.
Telaprevir “Rollover” StudyTelaprevir “Rollover” Study
0
20
40
60
80
100
Week 4 Week 12 Week 24
Null
Partial
Relapse4040
85859191
6161
90909494
4343
8282
7171
48 33 23 46 29 18 42 22 7
Shiffman ML, et al. 59th AASLD, October 31-November 4, 2008. Abstract 1852; Shiffman ML, et al. J Hepatol. 2008;4:1135A.
HC
V R
NA
<10
IU/m
l(%
)
Nucleoside Polymerase Inhibitor R7128Nucleoside Polymerase Inhibitor R7128 + PEG IFN + PEG IFN -2a + RBV-2a + RBV
28-Day Data in G1 Patients28-Day Data in G1 Patients11
0
20
40
60
80
100
10
30
85
1. Lalezari J, et al. J Hepatol. 2008;48:S29. 2. Gane EJ, et al. 59th AASLD. October 31–November 4, 2008. Abstract LB10. Graphic courtesy of Dr. I. M. Jacobson.
% P
CR
Neg
ativ
e
PEG IFN/RBV(n = 10)
PEG IFN +RBV +R7128
500 mg BID(n = 20)
PEG IFN/RBV + R7128
1500 mg BID(n = 20)
Ongoing studies in G2,3 as well as G1; RVR 90% in
G2,3 treatment failures2
Nitazoxanide in Genotype-4–Infected Nitazoxanide in Genotype-4–Infected Patients (Egypt)Patients (Egypt)
0
20
40
60
80
100
RVR ETR SVR
PEG IFN +RBV
NTZ + PEG IFN
NTZ + PEG IFN +RBV
Rossignol JF, et al. 59th AASLD. October 31-November 4, 2008. Abstract 1848. Graphic courtesy of Dr. I. M. Jacobson.
N = 96 treatment-naive patientsN = 96 treatment-naive patients
Control group PEG IFN + RBV (48 wk)Control group PEG IFN + RBV (48 wk)
Lead-in with 12 wk of nitazoxanideLead-in with 12 wk of nitazoxanide
–36 wk of additional therapy of PEG IFN or PEG IFN + RBV36 wk of additional therapy of PEG IFN or PEG IFN + RBV
7979
6161
5050
3838
54546464
75757171
8282
RVR = rapid virologic response; ETR = end-of-treatment response; SVR = sustained virologic response.
Drug 1 Drug 2Enhanced
Suppression
Resistance Studies
Decreased Emergence of de Novo Resistance
Suppression of Pre-existing
Resistant Variants
Boceprevir1 Valopicitabine Yes Yes Yes
Boceprevir2 HCV-796 Yes Yes Yes
ITMN-1913 R1479 Yes NA Yes
NM1074 ACH-806 Yes NA NA
Telaprevir4 ACH-806 Yes NA NA
Telaprevir5 R1479 NA Yes NA
Valopicitabine6 Various NA NA Yes
1. Ralston R, et al. J. Hepatol. 2007;46:S298. 2. Howe AY, et al. J. Hepatol. 2007;46:S165. 3. Seiwert SD, et al. J. Hepatol. 2007;46:S167. 4. Huang M, et al. J. Hepatol. 2007;46:S8. 5. McCowen M, et al. 14th International Symposium on Hepatitis C Virus and Related Viruses. September 9-13, 2007. Abstract P-265. 6. Bichko V, et al. J. Hepatol. 2007;46:S163.
The PromiseThe Promise of Combination Therapy of Combination TherapyIn Vitro Combinations StudiedIn Vitro Combinations Studied
The Goal of Future Combination RegimensThe Goal of Future Combination Regimens
•Different drugs may contribute variably to each of these goals•Not all components have to be STAT-C agents
Drug A Drug B Drug C
Profound suppression of broad range of
viral variants,including pre-existing
Prevention of emergent resistance
(pre-existing or de novo)
+ +
How Should the Prospect of Novel How Should the Prospect of Novel Treatments Factor into Your Decision-Treatments Factor into Your Decision-
Making?Making? Treatment-naive G1Treatment-naive G1
– Stage 0–1: watch and wait is acceptable in many patentsStage 0–1: watch and wait is acceptable in many patents– Stage 3–4: should treat nowStage 3–4: should treat now– Stage 2: proactivity with flexibilityStage 2: proactivity with flexibility
Where in stage 2 is patient?Where in stage 2 is patient? Mindset of patient; age of patient; duration of infectionMindset of patient; age of patient; duration of infection ContraindicationsContraindications
Treatment-naive G2,3Treatment-naive G2,3– Need good reason not to treatNeed good reason not to treat
NonrespondersNonresponders– Watch and wait appropriate for mostWatch and wait appropriate for most
RelapsersRelapsers– Consider longer course of retreatment, especially if advanced Consider longer course of retreatment, especially if advanced
fibrosisfibrosisYour local (or not so local) clinical investigator is happy to hear from you!Your local (or not so local) clinical investigator is happy to hear from you!