1) Personalizzazione ed ottimizzazione dei percorsi diagnostic i - Mirella Fraquelli

2) Gli studi prognostici : metodologia e interpretazione - Gennaro D’Amico

3) Dimensione dell’effetto terapeutico: Eterogeneit à, confondimento e interazione neitrial clinici - Calogero Cammà

4) Eterogeneità e meta-analisi - Fabio Tinè

5) Valutazioni di costo-efficacia : la cassetta degli attrezzi - Americo CicchettiDiscussione

JAMA 2013

Personalized medicine “refers to the tailoring of medical t reatment to the individual

characteristics of each patient. It does not literally mean the creation of drugs or

medical devices that are unique to a patient, but

rather the ability to classify individuals into subpopulations that differ in their

susceptibility to a particular disease or their response to a specific treatment.

Personalized medicine

JAMA 2013

Although the increasing attention directed to personalize d medicine has

largely focused on the interaction of an individual’s genom e with specific

treatments, any individual characteristics that affect treatment outc omes may

be relevant to clinical decision making.

Personalized medicine

A R Feinstein, J Clin Epidemiol 1998

.Taxonomic subgroups were an important, basic intellectualactivity in medical science. In clinical medicine, the taxonomyof pathophysiology has been an essential component of thereasoning and judgment used in good clinical practice.

During the past two decades, however, pathophysiology hasbecome increasingly ignored in medical research andeducation.

Personalized medicine

• What may be true for a group of people of mean

age 50 is unlikely to be true for an individual 50-year

old. (Morgenstern 1982)

• La stima media PER UN GRUPPO può non essere

valida per il singolo paziente.

Ecological bias

Anything that is good science can’t be bad statistics. Thepotential tragedy now is that what may seem to be goodstatistics will be bad science.

Jerome Cornfield

Personalized medicine

Personalizzazione ed ottimizzazione dei

percorsi diagnostici

Mirella Fraquelli

Fondazione IRCCS Cà Granda Ospedale Maggiore, Policlinico – Milano

Monotematica AISF 2013

“Personalizzazione della Cura in Epatologia”

Pisa, 17 - 19 Ottobre 2013

Dr. Mirella Fraquelli

Fondazione IRCCS Cà Granda Ospedale Maggiore, Policlinico – MI

Il sottoscritto dichiara di non aver avuto negli ultimi 12 mesi conflitto d’interesse in relazione a questa presentazione

e

che la presentazione non contiene discussionedi farmaci in studio o ad uso off-label

The clinical decision process

n Diagnosis, prognosis and treatment are part of a same

sequential process with the goal of progressively reducing the

uncertainty about a patient’s true state and take the best

clinical decisions

n Physicians should apply the ‘summary’ results obtained from

the available evidences to individual patients

Analytical

approaches

The clinical reasoning: the dual process theory

Unconscious intuitive

approaches

Spectrum

Automatic,

biased process

Inferential

mode of

discursive

thinking

System 1 System 2

Pagliaro, Bobbio , Colli. La diagnosi in Medicina, Milano, Raffaello Cortina Editore, 2011

Characteristics Non analytical Analytical

Diagnostic criteria

Cognitive type

Frequence of use

Rapidity

Similarity between

patients

Heuristic, intuitive

Very frequent

Fast

Large amount of

knowledge

Hypotetic-deductive

Iterative

Less frequent

Slow

Area of application

Errors

Common diseases

Initial tests «typical»

Overconfidence

Rare disease

Initial tests atypical

Overload

Overinvestigation

Pagliaro, Bobbio , Colli. La diagnosi in Medicina, Milano, Raffaello Cortina Editore, 2011

Female, 45 yrs

Weight loss : 10 kg during last 3 months

Asthenia

Tremor and palpitation

What is the diagnosis?

System 1- Non-analytical reasoning: e.g. perceptive recognition

Female, 45 yrs

Weight loss : 10 kg during last 3 months

Asthenia

Tremor and palpitation

What is the diagnosis?

����Tyreotoxicosis

System 1- Non-analytical reasoning: e.g. perceptive recognition

System 2 : Analytical reasoning

Initial level of probability of a diagnostic hypothesis

(Epidemiology, medical history, physical examination, laboratory etc.)

PRE-TEST PROBABILITY

INDEX TEST RESULT

Variation of the level of probability

POST-TEST PROBABILITY

Level of certainty necessary for a therapeutic decision

- +

System 2 : Analytical reasoning

The acceptable level of UNCERTAINTY depends on the

penalty for being wrong.

For my single patient

it will be better to be treated if false positive or

not treated if false negative?

Non-analytic vs analytic reasoning

The case of acute cholecystitis

Abdominal pain characteristics, fever and Murphy sign:

LR+ 30

n The clinical judge is simple and rapid (Gestalt) when facing with a

typical case

n Combinations of certain symptoms, signs, and laboratory results likely

have more useful LRs, and inform the diagnostic impressions of

experienced clinicians more than predictive rules

Trowbridge J AMA 2003; 298:80-86

simple

chaotic

complex

1

1Level of uncertainty

Lev

el o

f d

isa

grr

em

en

t

0

Diagnosis-

treatment

strategies

guidelines

RCT

Stacey RD. Strategic management and organizational dynamics. London: Pitmann Publishing, 1996.

How can I transfer the results obtained from diagnostic

studies to my single patient ?

Internal validityExternal validity

Internal validity

Correct study design

Ideal experimental conditions

Data homogeneity

Reduced heterogeneity

Data precision and

repeatability

External validity

Clinically relevant context

No center selection

No patients selection

Co-morbidity

Data transferability

Diagnostic test accuracy studies

• Critical appraisal of available diagnostic literature by assessing:

- methodological quality (INTERNAL VALIDITY)

- transferability (EXTERNAL VALIDITY)

- reporting (correct expression of diagnostic estimates)

(QUADAS 2, STARD INITIATIVE)

• Match the characteristic of my patient to that of those reported in

the literature as measures of accuracy may vary across patient

groups

Factors affecting the transferability of data derived from

diagnostic studies to a single patient

Practical example: transient elastography (TE, fibroscan)

A non-invasive technique conceived to assess

hepatic fibrosis by measuring liver stiffness.

Factors affecting the transferability of data derived from

diagnostic studies to a single patient

INTERNAL VALIDITY

n Assess existing pathways and formulate the proposed role for the IT

n Assess the index test intrinsic properties (repeatability, indeterminate

results, cut off) and Operator/s performances and variability

n Choose the correct study design

n Consider the reference standard properties

Roles of index test (’new’)

Bossuyt et al. BMJ 2006

Consecutive patients with

suspected chronic liver disease

Transient

elastography

positive negative

Liver Biopsy

TE role: replacement

TE - Intrinsic properties and operator’s characterisitcs

Applicability : failure 2.4 - 5% (related to ascites, reduced intercostal space)

inconsistent results 8-18% (mainly related BMI >28 kg/m2 )

Reproducibility: intra- extra-observer variability ICC 0.97-0.98

Normal values: mean (+SD) 4.8-5.4 (+1.5-6.9) kPa

median 4.1 (females ) 4.6 (males)

95th 7.4 (females) 7.8 (males)

Increased if steatosis, increased BMI, metabolic syndrome

Correct study design: architecture of diagnostic research

Phase 0

Intrinsic TE properties (reliability, reproducibility)

Phase 2Consecutive HCV patients with a wide spectrum of hepatic

fibrosis , all undergoing both TE (IndexTest) and liver biopsy(Ref Standard)

Phase 3

To assess if TE tested patients fare better than comparable patients tested

by a LB or not tested (efficacy)

Phase 4 Benefits and harms of the TE-treatment strategy into clinical practice (effectiveness & safety )

Phase 1TE values in healthy volunteers, blood

donors, and the general populationFactors influencing TE values

(sex, age, BMI)

Colli, Fraquelli et al. Hepatology 2013, accepted

“Relevant” spectrum of

patientsTE

Liver biopsy

Liver biopsy

TP

FP

FN

TN_

Basic design of diagnostic accuracy studies: Prospective, blinded cross

classification of test and reference standard in a clinical relevant setting

Study design

Diagnostic Case Control Study

Test parameter

Healthy

volunteers

%

Very sick

individuals

Test

threshold

Spectrum effects: evaluation of two very different

populations

the healthiest the sickest

SPECTRUM BIAS

Diagnostic Cross sectional Study

Test parameter

Patients without

disease

%

Patients with

disease

Test

threshold

Spectrum effects: evaluation of representative

populations

SPECTRUM VARIATION

Factors affecting the transferability of data derived from

diagnostic studies to a single patient

EXTERNAL VALIDITY

n Patients spectrum (disease prevalence, center or patient

selection)

n Patients characteristics (sex, age, BMI , etc)

n Co-morbidity

Severity of the disease

co-morbidities

Severity of the diseaseco-morbidities

Severity of the disease

co-morbidities

• Sensitivity and specificity (LR+ & LR -) are intrinsic properties of a

diagnostic test assumed to be independent from context.

Actually they may change according to different settings (primary

care vs referral center) and these changes are not predictable.

• Variation in disease prevalence and test accuracy between studies

should prompt the readers to detect important differences in

study population or study design affecting accuracy

Effect of prevalence on diagnostic estimates

Pos Aagreement

BCases detected only by

the Index Test

Neg CCases detected only by

the Reference Standard

Dagreement

TE

LIVER BIOPSY

Pos Neg

Index Test more

specific

Index Test

more

sensitive

Glasziou Ann Intern Med 2008; 149:816

Disagreements between Reference Standard and Index Test

Methodological and reporting quality:

the correct expression of diagnostic estimates

Degos et al, J Hepatol 2010Friedrich-Rust et al. Gastroenterology 2008

AUROC:

0.84 (0.82-0.86)

AUROC

Diagnostic accuracy: ROC curves and thresholds

0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

1-Specificity

Sen

sitiv

ity

0

0,2

0,4

0,6

0,8

1

0 0,2 0,4 0,6 0,8 1

1-Specificity

Sen

sitiv

ity

Cut offvariation

AUROC: quantitative measure of the diagnostic accuracy from 0.5 to 1

Good if > 0.80 (but look at confidence intervals !!!)

Youden index: maximum joint sensitivity and specificity

Cut off to rule out

Cut off to rule in

TE performance in diagnosing cirrhosis in HCV

Author, yr Etiology Disease

prev (%)

Patient

#

Cut-off,

kPa

Sens

(%)

Spec

(%)

-LR +LR AUROC

Ziol, 2005 HCV 19 251 14.6 86 96 0.14 23.0 0.87

Castera, 2005 HCV 25 183 12.5 87 91 0.14 9.7 0.95

Ganne-Carrié 2006 Mixed 15 775 14.6 79 95 0.11 15.8 0.95

Coco, 2007HCV-HBV 20 159 14.0 78 98 0.22 39 0.96

Fraquelli, 2007 Mixed 18 200 12.0 91 89 0.10 8.2 0.90

Arena, 2008 HCV 19 150 14.8 94 92 0.07 11.3 0.98

Lupşor, 2008 HCV 21 324 11.8 87 91 0.14 9.4 0.94

Zarski, 2012 HCV 15 382 12.9 77 90 0.25 7.7 0.93

Incertezza

DIAGNOSI

Probabilità Pre-Test

Risultato del Test LR+ & LR-

Probabilità Post-Test

Pre-test

ODDS

Post-test

ODDS

Bayesian approach

Some practical examples….

1. Male, 60 yr, HCV positive, HCV RNA 1.298.000, genotype

1b, non-responder dual tx, Potus 100 gr ETOH/die, BMI 31

(PRE-TEST PROB. ≈ 50%)

2. Male 50 yrs, HCV positive, HCV RNA 1.234.565, genotype

1b, naive, no potus, BMI 26

(PRE-TEST PROB. ≈ 25%)

3. Female, 25 yr, HCV positive, HCV RNA 652489

genotype 2, naive, no potus, BMI 21

(PRE-TEST PROB. <10%)

Study Exclusion criteria Sex

(males, %)

Age BMI Comorbidities/

cofactors

Lupsor et al.

(tertiary

center)

-Pregnancy

-HCC

- HBV or HIV

coinfection

- Ascites

35 48±10 26±4 NR

Arena et al.

(tertiary

center)

- BMI> 30

- Previous or current

ETOH abuse

-HBV or HIV

coinfection

-Hepatic

decompensation, HCC

61 50±12 23±2.8 NR

Ziol et al.

(secondary

centers)

- Ascites 62 47±13 24±3 NR

Castera et al

(tertiary

center)

- HBV or HIV

coinfection

- uninterpretable LB

examination

- HCC

57 51±12 25±4 NR

LR+ 9.4

LR- 0.14

25 50 75 100

25

5

0

75

1

00

Test Information

Pre-test

probability

Po

sr-t

est

pro

ba

bili

ty

TE in diagnosing F=4

cut off 11.8

Ex. 1

Lupsor et al. J Gastr Liver Dis 2008

LR+ 11.3

LR- 0.07

25 50 75 100

25

5

0

75

1

00

Test Information

Pre-test

probability

Po

sr-t

est

pro

ba

bili

ty

TE in diagnosing F=4

cut off 14.8

Ex. 2

Arena et al . Gastro 2008

LR+ 9.4

LR- 0.10

25 50 75 100

25

5

0

75

1

00

Test Information

Pre-test

probability

Po

sr-t

est

pro

ba

bili

ty

TE in diagnosing F=4

cut off 11.8

Ex. 3

Lupsor et al. J Gastr Liver Dis 2008

LR+ 9.4

LR- 0.10

25 50 75 100

25

5

0

75

1

00

Test Information

Pre-test

probability

Po

sr-t

est

pro

ba

bili

ty

TE in diagnosing F=4

cut off 11.8

Ex. 3

Lupsor et al. J Gastr Liver Dis 2008

Gender ?

Age ???

Prevalence ?

What is important to patients…

• ...always different to what is important to doctors….

• Physicians seem not always be able to interpret the preferences

of their patients

• Patients and their families should be encouraged to participate

more actively to the decision regarding diagnostic and

therapeutic choices

Mutiple Sclerosis

Rothwell et al. BMJ 1997; 314: 1580–83.

n Well trained and experienced physicians rarely used the analytic

approach especially for common, simple and iterative problems

n On the contrary, complex, unusual problems are more efficiently

approached with the analytic approach or by combining the two

processes

n A critical appraisal of the existing scientific evidence is essential to

transfer the results of diagnostic studies to individual patients

n Patients should be properly informed by physicians and their

preferences should always be taken into account to take the best

clinical decisions

Conclusions