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SIR and the Management of Cancer Trial Data

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

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  1. SIR and the Management of Cancer Trial Data Kate Motohashi Gray Cancer Institute, Northwood, UK

  2. Introduction • BCON Trial Coordinator/ Data Manager since May 2001 • Biology background with no experience of databases!

  3. Topics of Discussion • Background to the trial • The database • Retrieval of data • Restructuring of the database • Some questions

  4. 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

  5. BCON • Bladder cancer  • Carbon dioxide 2% • Oxygen 98% • Nicotinamide

  6. 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

  7. Treatment of bladder cancer • Surgery 1.Transurethral resection (TUR) 2.Total cystectomy • Chemotherapy • Radiotherapy

  8. Overall 5 year survival after RT • T2, T3 &T4 (muscle invasive): 5-40%

  9. 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

  10. Aim of BCON Trial • To address the problem of hypoxia by addition of the hypoxia modifying agents, carbogen and nicotinamide

  11. 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

  12. 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

  13. BCON Trial • Control arm RT alone • Experimental arm RT plus CON

  14. 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

  15. Target Accrual (to detect 15% improvement in local control) • 330 patients over 4 years • Recruitment started Nov 2000

  16. 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

  17. Design of database • Case orientated – patient number • Schema modelled on Case Report Forms • Multiple records for morbidity data, cystoscopy results and QoL

  18. Example of Weeks 1 to 12 symptom recording

  19. Record types

  20. Retrieval of data • Accrual status • Dumping to SPSS • Follow-up status • CRF compliance • Reimbursement status • Data verification/ error-checking • Compliance to Nicotinamide

  21. Participating centres

  22. RecruitmentCumulative accrual

  23. CRF status (Dec 2003)

  24. Old cystoscopy gradings • 0 no tumour • 1 > 50% reduction • 2 < 50% reduction • 3 progression • 4 recurrence after complete remission • 5 new superficial cancer

  25. New cystoscopy gradings • 0 no tumour • 1 superficial • 2 muscle invasive

  26. Cystoscopy results in database

  27. 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)

  28. 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

  29. 2. Wild card searches • Using search mode in forms and % for unknown characters • E.g. ‘F%W%’ • Can it be done with PQL?

  30. 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?

  31. Acknowledgements • Prof Søren Bentzen • Prof Peter Hoskin • Dr Francesca Buffa • Trial centre contacts

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