Literature DB >> 21210772

An audit strategy for progression-free survival.

Lori E Dodd1, Edward L Korn, Boris Freidlin, Robert Gray, Suman Bhattacharya.   

Abstract

In randomized clinical trials, the use of potentially subjective endpoints has led to frequent use of blinded independent central review (BICR) and event adjudication committees to reduce possible bias in treatment effect estimators based on local evaluations (LE). In oncology trials, progression-free survival (PFS) is one such endpoint. PFS requires image interpretation to determine whether a patient's cancer has progressed, and BICR has been advocated to reduce the potential for endpoints to be biased by knowledge of treatment assignment. There is current debate, however, about the value of such reviews with time-to-event outcomes such as PFS. We propose a BICR audit strategy as an alternative to a complete-case BICR to provide assurance of the presence of a treatment effect. We develop an auxiliary-variable estimator of the log-hazard ratio that is more efficient than simply using the audited (i.e., sampled) BICR data for estimation. Our estimator incorporates information from the LE on all the cases and the audited BICR cases, and is an asymptotically unbiased estimator of the log-hazard ratio from BICR. The estimator offers considerable efficiency gains that improve as the correlation between LE and BICR increases. A two-stage auditing strategy is also proposed and evaluated through simulation studies. The method is applied retrospectively to a large oncology trial that had a complete-case BICR, showing the potential for efficiency improvements.
© 2011, The International Biometric Society No claim to original US Federal works.

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Year:  2011        PMID: 21210772      PMCID: PMC3160504          DOI: 10.1111/j.1541-0420.2010.01539.x

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  6 in total

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2.  Survival analysis using auxiliary variables via non-parametric multiple imputation.

Authors:  Chiu-Hsieh Hsu; Jeremy M G Taylor; Susan Murray; Daniel Commenges
Journal:  Stat Med       Date:  2006-10-30       Impact factor: 2.373

Review 3.  Blinded independent central review of progression-free survival in phase III clinical trials: important design element or unnecessary expense?

Authors:  Lori E Dodd; Edward L Korn; Boris Freidlin; C Carl Jaffe; Lawrence V Rubinstein; Janet Dancey; Margaret M Mooney
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4.  Paclitaxel plus bevacizumab versus paclitaxel alone for metastatic breast cancer.

Authors:  Kathy Miller; Molin Wang; Julie Gralow; Maura Dickler; Melody Cobleigh; Edith A Perez; Tamara Shenkier; David Cella; Nancy E Davidson
Journal:  N Engl J Med       Date:  2007-12-27       Impact factor: 91.245

5.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).

Authors:  E A Eisenhauer; P Therasse; J Bogaerts; L H Schwartz; D Sargent; R Ford; J Dancey; S Arbuck; S Gwyther; M Mooney; L Rubinstein; L Shankar; L Dodd; R Kaplan; D Lacombe; J Verweij
Journal:  Eur J Cancer       Date:  2009-01       Impact factor: 9.162

6.  Independent review of E2100: a phase III trial of bevacizumab plus paclitaxel versus paclitaxel in women with metastatic breast cancer.

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  6 in total
  7 in total

1.  Assessing temporal agreement between central and local progression-free survival times.

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Journal:  Stat Med       Date:  2014-11-13       Impact factor: 2.373

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Authors:  Ajay K Gopal; Barbara Pro; Joseph M Connors; Anas Younes; Andreas Engert; Andrei R Shustov; Xuedong Chi; Emily K Larsen; Dana A Kennedy; Eric L Sievers
Journal:  Clin Trials       Date:  2016-05-05       Impact factor: 2.486

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Authors:  George D Demetri; Margaret von Mehren; Robin L Jones; Martee L Hensley; Scott M Schuetze; Arthur Staddon; Mohammed Milhem; Anthony Elias; Kristen Ganjoo; Hussein Tawbi; Brian A Van Tine; Alexander Spira; Andrew Dean; Nushmia Z Khokhar; Youn Choi Park; Roland E Knoblauch; Trilok V Parekh; Robert G Maki; Shreyaskumar R Patel
Journal:  J Clin Oncol       Date:  2015-09-14       Impact factor: 44.544

4.  Errors in multiple variables in human immunodeficiency virus (HIV) cohort and electronic health record data: statistical challenges and opportunities.

Authors:  Bryan E Shepherd; Pamela A Shaw
Journal:  Stat Commun Infect Dis       Date:  2020-10-07

5.  Use of administrative data to increase the practicality of clinical trials: Insights from the Women's Health Initiative.

Authors:  Garnet L Anderson; Carolyn J Burns; Joseph Larsen; Pamela A Shaw
Journal:  Clin Trials       Date:  2016-06-30       Impact factor: 2.486

6.  An audit strategy for time-to-event outcomes measured with error: application to five randomized controlled trials in oncology.

Authors:  Lori E Dodd; Edward L Korn; Boris Freidlin; Wenjuan Gu; Jeffrey S Abrams; William D Bushnell; Renzo Canetta; James H Doroshow; Robert J Gray; Rajeshwari Sridhara
Journal:  Clin Trials       Date:  2013-08-09       Impact factor: 2.486

7.  Parameter estimation in Cox models with missing failure indicators and the OPPERA study.

Authors:  Naomi C Brownstein; Jianwen Cai; Gary D Slade; Eric Bair
Journal:  Stat Med       Date:  2015-08-04       Impact factor: 2.373

  7 in total

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