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

PhUSELisbon, Portugal – 8-10 October 2007

From Local Laboratory toStandardisation and beyond:Applying a commonggrading system

Data Management Stream (DM01)

Angelo TinazziData Management and Programming UnitSENDO Tech S.r.l. – Milan (ITALY)co-authors

Irene Corradino, Enrica Paschetto, Sonia Colombini

Early Drug Development Early Drug Development In OncologyIn Oncology

2Tinazzi 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)

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


IOSI, Bellinzona,Cristiana Sessa

HQ-ActivitiesClinical development

Clinical OperationData Center RegulatoryMonitoring

Logistic

INT, Milano Luca Gianni

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

Core activitiesTrial design

Selected Screening & MoAClinical trials

PharmacokineticsPharmacodynamics

SENDO (Southern Europe New Drug Organisation) - Partner s


Previous Discuss at PhUSE about Lab Data Management

Szilagyi B, Binder C.Complex Laboratory Data Management, Strategiesand 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 clinicaldecision for patient’s care and to define the drugprofile….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 pressureessential 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 RangesNormal ranges, or reference ranges, are used to determine if a person’s value is “normal”. The ‘normal range’ for a givenconstituent 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 LabsLab 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 LabsLab 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 UnitCollected directly onto patient CRF


Laboratory CRF – Option 2

100 0 350 0120 0

120 109/L (100-350)


The SENDO Experience with 4 Trials

97Overall in SENDO Repository

1.4 (1-3)1114 (2-33)384 (ph II)

2.8 (1-5)3124 (2-61)203 (ph I)

2.7 (1-6)3327 (2-79)322 (ph I)

3.0 (1-7)4437 (2-90)341 (ph I)

Average Nr. of Local Labs Used by each patient (min-max)

Nr. of Different Local Labs Used

Nr. of samples collected (average nr by Patient, min-max)

Nr. of Patients

Study Nr

High heterogeneity inunit reported (the exampleis 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 obtainedfrom different labs can be summed, weighted and compared



�StandardisationEnsures 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 applyingconversion factors

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

Multiply 0.2558


�NormalisationThe application of a normalisation method to ensurehomogenization of results obtained from different locallabs


xx

ssxs LU

LULxLs

−−

−+= )(Reference/Standard Range

Local Labs RangeObserved Value

The standard reference can be taken from the literature or from a sample of normal ranges by taking the 10°and the 90°percentiles

Assume an observed value of 10 measured in the lab with normal range 5-25, ifour standard range has been determined to be 10-35…..

25.16525

1035)510(10 =

−−−+=s The normalised value

5-2912-3510-4515-4012-30

5101212152930354045

The statistical basis of Laboratory Normalization. Kar vanen J. DIA, Vol. 37, pp. 101-107; 2004


Applying a common grading system: the CTCAE

Ocular / VisualPain Pulmonary / Upper RespiratoryRenal / GenitourinarySecondary MalignancySexual / Reproductive FunctionSurgery / Intra-Operative InjurySyndromesVascular

Gastrointestinal Growth and DevelopmentHemorrhage / BleedingHepatobiliary / PancreasInfectionLymphaticMetabolic / LaboratoryMusculoskeletal / Soft TissueNeurology

Allergy / ImmunologyAuditor / EarBlood / Bone MarrowCardiac ArrhythmiaCoagulationConstitutional SymptomsDeathDermatology / SkinEndocrine

CTCAE Event Categories

� NCI Common Terminology Criteria for AdverseEvents – 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


Applying a common grading system: the CTCAE

Qualitative Definition (Arthritis)� a grade 1 is defined as “Mild pain with inflammation, erythem a, 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 (Pla telets Count)

<25,000/mm3<25.0 x 10^9 /L

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

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

<LLN – 75,000/mm3<LLN – 75.0 x 10 ^9 /L

Grade 4Grade 3Grade 2Grade 1


Example of Platelets Count from Local Lab to CTCAE Calculation

<25,000/mm3<25.0 x 10^9 /L

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

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

<LLN – 75,000/mm3<LLN – 75.0 x 10 ^9 /L

Grade 4Grade 3Grade 2Grade 1CTCAE Platelets Definition


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 whenare different from the expected/normal valuesby 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 mainindividual laboratory used may help

� Tools (i.e. SAS macro routines), are required tomanage and control the various steps of LocalLaboratory 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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