The value of source data verification in a cancer clinical trial.

<h4>Background</h4>Source data verification (SDV) is a resource intensive method of quality assurance frequently used in clinical trials. There is no empirical evidence to suggest that SDV would impact on comparative treatment effect results from a clinical trial.<h4>Methods</h4...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Catrin Tudur Smith, Deborah D Stocken, Janet Dunn, Trevor Cox, Paula Ghaneh, David Cunningham, John P Neoptolemos
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2012
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b5e22a0909df4b099fd2051e3034cc62
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:b5e22a0909df4b099fd2051e3034cc62
record_format	dspace
spelling	oai:doaj.org-article:b5e22a0909df4b099fd2051e3034cc622021-11-18T08:05:17ZThe value of source data verification in a cancer clinical trial.1932-620310.1371/journal.pone.0051623https://doaj.org/article/b5e22a0909df4b099fd2051e3034cc622012-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/23251597/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Source data verification (SDV) is a resource intensive method of quality assurance frequently used in clinical trials. There is no empirical evidence to suggest that SDV would impact on comparative treatment effect results from a clinical trial.<h4>Methods</h4>Data discrepancies and comparative treatment effects obtained following 100% SDV were compared to those based on data without SDV. Overall survival (OS) and Progression-free survival (PFS) were compared using Kaplan-Meier curves, log-rank tests and Cox models. Tumour response classifications and comparative treatment Odds Ratios (ORs) for the outcome objective response rate, and number of Serious Adverse Events (SAEs) were compared. OS estimates based on SDV data were compared against estimates obtained from centrally monitored data.<h4>Findings</h4>Data discrepancies were identified between different monitoring procedures for the majority of variables examined, with some variation in discrepancy rates. There were no systematic patterns to discrepancies and their impact was negligible on OS, the primary outcome of the trial (HR (95% CI): 1.18(0.99 to 1.41), p = 0.064 with 100% SDV; 1.18(0.99 to 1.42), p = 0.068 without SDV; 1.18(0.99 to 1.40), p = 0.073 with central monitoring). Results were similar for PFS. More extreme discrepancies were found for the subjective outcome overall objective response (OR (95% CI): 1.67(1.04 to 2.68), p = 0.03 with 100% SDV; 2.45(1.49 to 4.04), p = 0.0003 without any SDV) which was mostly due to differing CT scans.<h4>Interpretation</h4>Quality assurance methods used in clinical trials should be informed by empirical evidence. In this empirical comparison, SDV was expensive and identified random errors that made little impact on results and clinical conclusions of the trial. Central monitoring using an external data source was a more efficient approach for the primary outcome of OS. For the subjective outcome objective response, an independent blinded review committee and tracking system to monitor missing scan data could be more efficient than SDV.Catrin Tudur SmithDeborah D StockenJanet DunnTrevor CoxPaula GhanehDavid CunninghamJohn P NeoptolemosPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 7, Iss 12, p e51623 (2012)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Catrin Tudur Smith Deborah D Stocken Janet Dunn Trevor Cox Paula Ghaneh David Cunningham John P Neoptolemos The value of source data verification in a cancer clinical trial.
description	<h4>Background</h4>Source data verification (SDV) is a resource intensive method of quality assurance frequently used in clinical trials. There is no empirical evidence to suggest that SDV would impact on comparative treatment effect results from a clinical trial.<h4>Methods</h4>Data discrepancies and comparative treatment effects obtained following 100% SDV were compared to those based on data without SDV. Overall survival (OS) and Progression-free survival (PFS) were compared using Kaplan-Meier curves, log-rank tests and Cox models. Tumour response classifications and comparative treatment Odds Ratios (ORs) for the outcome objective response rate, and number of Serious Adverse Events (SAEs) were compared. OS estimates based on SDV data were compared against estimates obtained from centrally monitored data.<h4>Findings</h4>Data discrepancies were identified between different monitoring procedures for the majority of variables examined, with some variation in discrepancy rates. There were no systematic patterns to discrepancies and their impact was negligible on OS, the primary outcome of the trial (HR (95% CI): 1.18(0.99 to 1.41), p = 0.064 with 100% SDV; 1.18(0.99 to 1.42), p = 0.068 without SDV; 1.18(0.99 to 1.40), p = 0.073 with central monitoring). Results were similar for PFS. More extreme discrepancies were found for the subjective outcome overall objective response (OR (95% CI): 1.67(1.04 to 2.68), p = 0.03 with 100% SDV; 2.45(1.49 to 4.04), p = 0.0003 without any SDV) which was mostly due to differing CT scans.<h4>Interpretation</h4>Quality assurance methods used in clinical trials should be informed by empirical evidence. In this empirical comparison, SDV was expensive and identified random errors that made little impact on results and clinical conclusions of the trial. Central monitoring using an external data source was a more efficient approach for the primary outcome of OS. For the subjective outcome objective response, an independent blinded review committee and tracking system to monitor missing scan data could be more efficient than SDV.
format	article
author	Catrin Tudur Smith Deborah D Stocken Janet Dunn Trevor Cox Paula Ghaneh David Cunningham John P Neoptolemos
author_facet	Catrin Tudur Smith Deborah D Stocken Janet Dunn Trevor Cox Paula Ghaneh David Cunningham John P Neoptolemos
author_sort	Catrin Tudur Smith
title	The value of source data verification in a cancer clinical trial.
title_short	The value of source data verification in a cancer clinical trial.
title_full	The value of source data verification in a cancer clinical trial.
title_fullStr	The value of source data verification in a cancer clinical trial.
title_full_unstemmed	The value of source data verification in a cancer clinical trial.
title_sort	value of source data verification in a cancer clinical trial.
publisher	Public Library of Science (PLoS)
publishDate	2012
url	https://doaj.org/article/b5e22a0909df4b099fd2051e3034cc62
work_keys_str_mv	AT catrintudursmith thevalueofsourcedataverificationinacancerclinicaltrial AT deborahdstocken thevalueofsourcedataverificationinacancerclinicaltrial AT janetdunn thevalueofsourcedataverificationinacancerclinicaltrial AT trevorcox thevalueofsourcedataverificationinacancerclinicaltrial AT paulaghaneh thevalueofsourcedataverificationinacancerclinicaltrial AT davidcunningham thevalueofsourcedataverificationinacancerclinicaltrial AT johnpneoptolemos thevalueofsourcedataverificationinacancerclinicaltrial AT catrintudursmith valueofsourcedataverificationinacancerclinicaltrial AT deborahdstocken valueofsourcedataverificationinacancerclinicaltrial AT janetdunn valueofsourcedataverificationinacancerclinicaltrial AT trevorcox valueofsourcedataverificationinacancerclinicaltrial AT paulaghaneh valueofsourcedataverificationinacancerclinicaltrial AT davidcunningham valueofsourcedataverificationinacancerclinicaltrial AT johnpneoptolemos valueofsourcedataverificationinacancerclinicaltrial
_version_	1718422252691652608

The value of source data verification in a cancer clinical trial.

Ejemplares similares