Liver FibrosisLiver FibrosisAre Non-invasive markers Are Non-invasive markers

sufficient?sufficient?

William Rosenberg

Prof of Hepatology

University of Southampton

CSO iQur Limited; Consultant to Bayer Healthcare

Why measure fibrosis?Why measure fibrosis?

• Assessment of disease– Diagnosis– Prognosis– Treatment decisions

• Monitoring disease– Natural history– Treatment effects– Drug development

Cross-sectional

Dynamic change over time

Liver BiopsyLiver BiopsyThe Reference Standard for The Reference Standard for

FibrosisFibrosis

Disadvantages of Liver BiopsyDisadvantages of Liver Biopsy

• Hazard to the patient

• Resource usage– Bed– Imaging– Staff– Processing

• Sampling Error

• Interpretation

Time

Liver biopsyLiver biopsy• Sampling error

– 1/50,000 of the liver– Fibrosis not evenly distributed

• Lt and Rt lobes difference 24% 1 Grade 30% 1 Stage • 20% error in scoring

Liver biopsy analysisLiver biopsy analysis• Size

– Biopsy size reproducibility Bedossa et al. 2004

• Histological scoring– Inter observer variation =0.9 – 0.49– Interpretation experience Bedossa et al. 2005

• Image analysis– Automation

• More fields• Greater reproducibility

Ideal markers of fibrosisIdeal markers of fibrosis

• Performed on a serum or urine sample• Test cheap and relatively easy• A continuous variable

– Allows distinction of small changes

• Correlates with fibrosis over full range– Accurate for all comparisons

• Provides clinically meaningful data– Prognostic information and treatment

response

Candidate ApproachCandidate Approach

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Candidate Biomarkers of FibrosisCandidate Biomarkers of Fibrosis

• Indirect: Indirect: Measures of liver functionMeasures of liver function– AST, ALT, GT, Apolipoprotein A1, bilirubin,

2-macroglobulin, haptoglobin, cholesterol– HOMA-IR– Platelets, PT

• Direct: Direct: ECM components and enzymesECM components and enzymes– HA, PIIINP, Collagen IV, Collagen VI, TIMP-1,

Laminin, YKL-40, Tenascin, Undulin, MMP-2

ELF MarkersELF MarkersRosenberg et al. Gastro Dec 2004Rosenberg et al. Gastro Dec 2004

Disease AUC Score Sensitivity Specificity PPV NPV

NAFLD 0.87 0.375 89% 96% 80% 98%

0.462 78% 98% 87% 96%

ALD 0.944 0.087 100.0% 16.7% 75.0% 100.0%

0.431 93.3% 100.0% 100.0% 85.7%

HCV 0.773 0.067 90% 31% 27.5% 92.3%

0.564 30% 99% 89.5% 83.3%

Detection of Scheuer Stage 0,1,2 versus 3,4

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IMBERT ROSSI POYNARD LEROY WAI LE CALVEZ FORNS THABUT SUD ELF

Correct Incorrect Inaccurate

Panel Performance Panel Performance Applying High and Low ThresholdsApplying High and Low Thresholds

NPV~95% PPV~90%NPV~95% PPV~90%

Fibrotest APRI Forns BayerHA

PIIINP

High, Mid and Low Cut-off SROCsHigh, Mid and Low Cut-off SROCs

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.4.6

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Detecting F3/4

Differentiating F2/3

Detecting F1/2

DOR 6.52 ( 1.69-25.23) Sens. 59.8 spec. 87.7

DOR 6.39 (1.89-21.65)Sens. 94.8 Spec. 35.8

DOR 8.14 (3.61-18.38)

Sens. 40.1 Spec. 95

Sufficient?Sufficient?

• Errors in liver biopsy– Expert opinion is flawed

• What matters?– Detecting Any fibrosis - F0,1 vs rest– Detecting Advanced fibrosis - F4,5,6

F 0,1 versus the restF 0,1 versus the rest

1.00.90.80.70.60.50.40.30.20.10.0

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Validation data ROC Curve

AUC=0.791 AUC=0.791 (95% CI: 0.720, 0.862)

p<0.001

Notts HCV CohortSee Parkes et al.

Poster 160 BSG 2006

F4, 5 and 6 versus the restF4, 5 and 6 versus the rest

1.00.90.80.70.60.50.40.30.20.10.0

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Validation data ROC Curve

AUC=0.860 AUC=0.860 (95% CI: 0.804, 0.916),

p<0.001

Notts HCV CohortSee Parkes et al.

Poster 160 BSG 2006

Case 1 DiagnosisCase 1 Diagnosis

• 35 year old Female G3 HCV for 10 years

• Normal LFTs and USS

Case 2 DiagnosisCase 2 Diagnosis

• 45 year Male G1 HCV

• 5 spiders, ? Palpable spleen

• Normal Bilirubin Albumin Platelets

• US normal

0.490.4

Excellent CVContinuous

Moderate CVCategorical

? ?

Will we ever know?Will we ever know??

PrognosisPrognosisELF Follow-upELF Follow-up

Dr Julie Parkes

MRC Clinician Scientist

Carol Gough

Preliminary data from Southampton and Newcastle

Clinical Follow up of ELF CohortClinical Follow up of ELF Cohort

• 224 patients

• 75% male

• Hep C 45% ALD 19% Fat 13%

• 62 F2-4

• 26 Liver related outcomes

Diagnosed F3,4 DS .102 Bx

Sensitivity 84.6 80.7

Specificity 27.3 31.8

PPV 28.9 25.0

NPV 97.3 96.4

Prediction of MortalityPrediction of Mortality

ConclusionConclusion

• ELF serum markers of liver fibrosis accurately predict liver related death over 5-8 years follow-up

• Performance is at least as good as histology

Case 3 PrognosisCase 3 Prognosis

• 35 year old man

• BMI=35 ALT=125

• Concerned about his future

Assessment Assessment ofof

Treatment ResponseTreatment Response

Drug treatment

Drug development

Treatment responseTreatment responsePoynard et al Hepatology 2003;38:481-492Poynard et al Hepatology 2003;38:481-492

• Not accurate for individual patients

• Changes in biomarkers correlate with changes in histology for cohorts

• Use in evaluating trials warrants further studies

Individual and Group DifferencesIndividual and Group Differences

NS

Significant difference

Cumulative evidence of difference

Biomarkers: continuous variable, change determined by biology,low cv, repeatable at high frequency

Case 4Case 4 Treatment Treatment

• 55 year old man with HCV

• Severe fibrosis 1 year pre-treatment

• Relapse after PEGIFN and RBV

• 6 months later

• Concerned about the future

Case 5 TreatmentCase 5 Treatment

• 53 year woman with BMI=33

• NIDDM and HTN

• ALT=68 -GT=125

• 3 months later

• BMI=28 ALT=72 on Pioglitazone

The FutureThe Future

• Better markers– Reverse biology

• Imaging

• Composite tests

Reverse BiologyReverse Biology

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ProteomicsProteomicsGlycomicsGlycomicsMetabonomicsMetabonomics

Other Tests for FibrosisOther Tests for Fibrosis

• Fibroelastogram– Ultrasound – Caution in obesity

• Micro bubbles– Performed with imaging– Invasive

• MRI– Additional information– Costly

Composite TestsComposite Tests

• Biopsy

+

• Non-invasive markers– Selective thresholds

+• Imaging

SummarySummary

• Liver biopsy– Hazardous, inaccurate

• Serum Markers– Safe, Accurate

• Are serum markers sufficient?– Correlate with histology– Predictive of long term outcome– Repeatable