From Local Laboratory to Standardisation and beyond Applying a common grading system

PhUSE
Lisbon, Portugal – 8-10 October 2007

From Local Laboratory to
Standardisation and beyond:
Applying a commong
Early Drug Development
In Oncology grading system

Data Management Stream (DM01)

Angelo Tinazzi
Data Management and Programming Unit
SENDO Tech S.r.l. – Milan (ITALY)
co-authors
Irene Corradino, Enrica Paschetto, Sonia Colombini

SENDO (Southern Europe New Drug Organisation)

Non profit Academic Research Organisation (ARO)
Early Drug Development in Oncology
Coordinating a Network of oncology-hospitals
5 phase I (2 in Italy, 3 in Switzerland)
~ 30 phase II (Italy, Switzerland, Spain)
Pre-clinical Laboratory (PK, PD)
Head Quarter based in Milan
Clinical Development
Clinical Operations
Data-Management
Biostatistics
Medical Writing

Tinazzi A Corradino I Paschetto E Colombini S: From Local Laboratory to Standardisation and
beyond: Applying a common grading system PhUSE 2007, DM01 (Lisbon, Portugal – 8-10 October 2007) 2

SENDO (Southern Europe New Drug Organisation) - Partners

HQ-Activities
Clinical development
Clinical Operation
Data Center
Regulatory
INT, Milano
Monitoring
IOSI, Bellinzona, Luca Gianni
Logistic
Cristiana Sessa
Core activities
Trial design
Selected Screening & MoA
Clinical trials
Pharmacokinetics
Pharmacodynamics

and also ....
CHUV Lausanne, KSSG S Gallen,
Istituto Mario Negri Milano


Previous Discuss at PhUSE about Lab Data Management

Szilagyi B, Binder C.
Complex Laboratory Data Management, Strategies
and Tools for a Way out of the Maze.
PhUSE 2005; DM05


Laboratory Data
Use of Laboratory Tests in Clinical Trials
For safety
Activity
Categories
Pharmacodynamic
Pharmacokynetic
Microbiology
Immunology
Cytology
Pharmacogenomic
They are also used to make immediate clinical
decision for patient’s care and to define the drug
profile….focus on
Haematology
Chemistry
Urinalysis


Laboratory Data Characteristics

Qualitative vs Quantitative vs Semi-Quantitative
Quantitative
Most chemistry/hematology
They are expressed in a specific unit
They refere to a range (minimum-maximum)
Semi-Quantitative (i.e. trace)
Qualitative (i.e. +/-)
Clinical Interpretation
Not clinically significant
Clinically Significant (Adverse Event)


Focus on hematology data
White Blood Count (WBC)
Hemoglobin
Neutrophils
Monocytes
Basophils
Eosinophils
Band
Lymphocytes
Platelets
Red Blood Cells
Hematocrit
Hemoglobin
Coagulation tests (i.e. PTT, PT)


Focus on chemistry data
Electrolytes
Sodium
Potassium
Chloride
Bicarbonate
Carbon Dioxide

They maintain body fluid and blood pressure
essential for the function of most body systems


Focus on chemistry data
Enzymes
Aspartate Aminotransferase (AST/SGOT)
Alanine Aminotransferase (ALT/SGPT)
Gamma Glutamyl Transferase (γGT)
Alkaline Phosphatase
Troponin I
Creatine Phosphokinase (CPK)
Lactate Dehydrogenase (LDH)

They help diagnose liver and heart diseases


Focus on urinalysis data
Protein
Cells
Hormone

They tests the health of organ and body process


Normal Ranges
Normal ranges, or reference ranges, are used to determine if a
person’s value is “normal”. The ‘normal range’ for a given
constituent of clinical interest is considered to be the
concentrations of the constituent which are found in the body
fluid or excretions of a group of clinically normal persons.
by gender
by age
fasting / non-fasting
analysis method / kit used by laboratory may change over
time, and so the normal ranges


Local Laboratory vs Central Laboratories

Central Labs
Lab samples are analysed (and taken) in the same lab center
Standard methods (and machine calibration)
Unique normal ranges for each sample
Electronic data transfer (no data-transcription errors)
Local Labs
Lab samples are analysed (and taken) in different lab centers
Sample can be taken anywhere / anytime
Multiple normal ranges, so different methods applied
No transport issue, but data need to re-keyed


Local laboratory data-management


Laboratory CRF – Option 1

Normal Ranges and Unit
Collected directly onto patient CRF


Laboratory CRF – Option 2

120 0 100 0 350 0

120 109/L (100-350)


The SENDO Experience with 4 Trials
Study Nr Nr. of Nr. of samples Nr. of Average Nr. of
Patients collected Different Local Labs Used
(average nr by Local by each
Patient, min-max) Labs Used patient (min-max)
1 (ph I) 34 37 (2-90) 44 3.0 (1-7)
2 (ph I) 32 27 (2-79) 33 2.7 (1-6)
3 (ph I) 20 24 (2-61) 31 2.8 (1-5)
4 (ph II) 38 14 (2-33) 11 1.4 (1-3)
Overall in 97
SENDO
Repository

High heterogeneity in
unit reported (the example
is for Platelets count only)


Quality Control
Missing data (unit, range, interpretation)
Hand writing legibility
Unit and value incosistencies

Normal Range Validity
Outliers detection


Statistical Analysis Process

Main Analysis
Univariate (mean, std, min, max, etc)
Shift Tables / Change From Baseline (absolute, %, log)
Correlations
Time to Event (i.e. Time to lowest observation, or time to nadir)
Worst toxic effect observed

Data must be ‘manipulated’ so that results obtained
from different labs can be summed, weighted and
compared


Standardisation
Ensures that all laboratory values are expressed in the
same unit (Système International d’Unités - SI)

It consists in the adoption of a standard unit by applying
conversion factors

Multiply 0.2558

Potassium 13.7 mg/dL SI unit is mmol/L 3.5 mmol/L


Normalisation 5-29
12-35
The application of a normalisation method to ensure 10-45
homogenization of results obtained from different local 15-40
labs 12-30
U s − Ls Reference/Standard Range
s = Ls + ( x − L x ) 5
U x − Lx Local Labs Range 10
Observed Value 12
12
The standard reference can be taken from the literature or from a sample of
15
normal ranges by taking the 10°and the 90°percentiles 29
30
Assume an observed value of 10 measured in the lab with normal range 5-25, if
35
our standard range has been determined to be 10-35…..
40
35 − 10 45
s = 10 + (10 − 5) = 16.25 The normalised value
−5
25 Normalization. Karvanen J. DIA, Vol. 37, pp. 101-107; 2004
The statistical basis of Laboratory

Applying a common grading system: the CTCAE
NCI Common Terminology Criteria for Adverse
Events – CTCAE (v3.0)
A standard in oncology for classifying Adverse Events
Severity
A Grading system ranging from ‘0’ (no toxic effect) to ‘4’
(severe toxic effect), with the addition of ‘5’ (death)
An event has unique representation
Events are organised in categories
Link with MedDRA Term
CTCAE Event Categories
Allergy / Immunology Gastrointestinal Ocular / Visual
Auditor / Ear Growth and Development Pain
Blood / Bone Marrow Hemorrhage / Bleeding Pulmonary / Upper Respiratory
Cardiac Arrhythmia Hepatobiliary / Pancreas Renal / Genitourinary
Coagulation Infection Secondary Malignancy
Constitutional Symptoms Lymphatic Sexual / Reproductive Function
Death Metabolic / Laboratory Surgery / Intra-Operative Injury
Dermatology / Skin Musculoskeletal / Soft Tissue Syndromes
Endocrine Neurology Vascular


Applying a common grading system: the CTCAE

Qualitative Definition (Arthritis)
a grade 1 is defined as “Mild pain with inflammation, erythema, or
joint swelling, but not interfering with function”
a grade 4, is defined as “Disabling”

Quantitative Definition (Diarrhea)
a grade 1, is defined as “Increase of <4 stools per day over baseline;
mild increase in ostomy output compared to baseline”
a grade 4, is defined….

Quantitative Definition based on Lab Data Results (Platelets Count)
Grade 1 Grade 2 Grade 3 Grade 4
<LLN – 75,000/mm3 <75,000 – 50,000/mm3 <50,000 – 25,000/mm3 <25,000/mm3
<LLN – 75.0 x 10^9 /L <75.0 – 50.0 x 10^9 /L <50.0 – 25.0 x 10^9 /L <25.0 x 10^9 /L


Example of Platelets Count from Local Lab to CTCAE Calculation

CTCAE Platelets Definition
Grade 1 Grade 2 Grade 3 Grade 4

<LLN – 75,000/mm3 <75,000 – 50,000/mm3 <50,000 – 25,000/mm3 <25,000/mm3
<LLN – 75.0 x 10^9 /L <75.0 – 50.0 x 10^9 /L <50.0 – 25.0 x 10^9 /L <25.0 x 10^9 /L


Quality Control – Additional tips in identifying Invalid Values

For each parameter, sort the converted SI
value in ascending order
Review the lowest and highest values when
are different from the expected/normal values
by a factor of 10,100,1000
Look for jumps in values
Look for values that are substantially above or
below typical normal ranges values
Review grade 3-4 CTCAE


Conclusions – 1

In many studies, laboratory data represent
50-80% of the data to be collected
Central laboratory are not always applicable,
however electronical data-transfer from main
individual laboratory used may help
Tools (i.e. SAS macro routines), are required to
manage and control the various steps of Local
Laboratory Data collection and analysis
Specialist in laboratory data-management


Conclusions – 2

Estabilish a central data-repository of local labs
How small are the differences / abnormalities
that need to be defined?
Choice between a more or less sophisticated
method of harmonization of laboratory results (e.g.
Normalization vs SI Standardization)
CDISC LAB Team


Questions


From Local Laboratory to Standardisation and beyond Applying a common grading system

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