Sir and the management of cancer trial data
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SIR and the Management of Cancer Trial Data. Kate Motohashi Gray Cancer Institute, Northwood, UK. Introduction. BCON Trial Coordinator/ Data Manager since May 2001 Biology background with no experience of databases!. Topics of Discussion. Background to the trial The database

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SIR and the Management of Cancer Trial Data

Kate Motohashi

Gray Cancer Institute, Northwood, UK


Introduction

  • BCON Trial Coordinator/ Data Manager since May 2001

  • Biology background with no experience of databases!


Topics of Discussion

  • Background to the trial

  • The database

  • Retrieval of data

  • Restructuring of the database

  • Some questions


A MULTICENTRE RANDOMISED PHASE III TRIAL OF RADIOTHERAPY WITH CARBOGEN AND NICOTINAMIDE IN THE TREATMENT OF LOCALLY ADVANCED BLADDER CANCERTRIALPI: Prof Peter HoskinTRIAL STATISTICIAN Prof Søren BentzenFunded by the Cancer Research UK


BCON

  • Bladder cancer 

  • Carbon dioxide 2%

  • Oxygen 98%

  • Nicotinamide


Bladder Cancer

  • ~ 4% of all cancers in UK

  • UK incidence 2000: 11 080 (with just over two-thirds men)

  • Peak incidence in 7th decade

  • History of smoking/ exposure to chemicals


Treatment of bladder cancer

  • Surgery

    1.Transurethral resection (TUR)

    2.Total cystectomy

  • Chemotherapy

  • Radiotherapy


Overall 5 year survival after RT

  • T2, T3 &T4 (muscle invasive): 5-40%


Reasons for RT failure

  • Intrinsic cell radio-resistance

  • Tumour repopulation during RT

  • Resistant cells due to HYPOXIA

    HYPOXIA: the reduction of the O2

    supply to tissue below physiological levels

    - O2 is crucial for RT success


Aim of BCON Trial

  • To address the problem of hypoxia by addition of the hypoxia modifying agents, carbogen and nicotinamide


  • CARBOGEN: 02 (98%) and C02 (2%)

    Oxygenation of the tumour is increased when cabogen is breathed

  • NICOTINAMIDE: amide of vitamin B3

    Improves perfusion by reducing closure of blood vessels


Phase II study at MVH

  • 30 patients received carbogen alone

  • 32 patients received CON

    When compared to historical data significant gains were observed in

  • Local tumour control

  • Disease-free survival

  • Overall survival


BCON Trial

  • Control arm

    RT alone

  • Experimental arm

    RT plus CON


Endpoints of BCON Trial

  • Tumour response at 6 months

  • Local-failure free survival*

  • Overall disease specific survival

  • Treatment related morbidity*

  • Quality of Life*

    * Requiring ability to store records at different time-points


Target Accrual (to detect 15% improvement in local control)

  • 330 patients over 4 years

  • Recruitment started Nov 2000


Why SIR?

  • Good at handling clinical data where patients have multiple visits

  • Compatibility with SPSS

SIR 2000 or SIR 2002?

Old Forms

  • Developed with colour, ‘if’ clauses, width definitions etc

  • Allow double data entry


Design of database

  • Case orientated – patient number

  • Schema modelled on Case Report

    Forms

  • Multiple records for morbidity data,

    cystoscopy results and QoL


Example of Weeks 1 to 12 symptom recording


Record types


Retrieval of data

  • Accrual status

  • Dumping to SPSS

  • Follow-up status

  • CRF compliance

  • Reimbursement status

  • Data verification/ error-checking

  • Compliance to Nicotinamide


Participating centres


RecruitmentCumulative accrual


CRF status (Dec 2003)


Old cystoscopy gradings

  • 0 no tumour

  • 1 > 50% reduction

  • 2 < 50% reduction

  • 3 progression

  • 4 recurrence after complete remission

  • 5 new superficial cancer


New cystoscopy gradings

  • 0 no tumour

  • 1 superficial

  • 2 muscle invasive


Cystoscopy results in database


1. Missing Values

  • Up to three values can be specified which are missing values for the variable. Missing values are excluded from statistical procedures and functions.

    BCON Database Missing Values

  • BLANK = not available (ever)

  • ‘9’/ ‘99’/ ‘999’ etc = not available (yet)


RETRIEVAL

.PROCESS CASES ALL

. PROCESS REC NEWCYST

. GET VARS TUMSTATE

. IFTHEN (EXISTS (TUMSTATE) EQ 0) WRITE PATNO

. ENDIF

. END PROCESS REC

.END PROCESS CASE

END RETRIEVAL

This retrieves field with missing value but doesn’t distinguish between different categories of missing values


2. Wild card searches

  • Using search mode in forms and % for unknown characters

  • E.g. ‘F%W%’

  • Can it be done with PQL?


3. Editing Log

  • Journalling – logs changes to the database

  • Is it possible to create a log where person editing data is prompted to give a reason for the change?


Acknowledgements

  • Prof Søren Bentzen

  • Prof Peter Hoskin

  • Dr Francesca Buffa

  • Trial centre contacts


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