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

ABSTRACT: BACKGROUND:Measurement error in time-to-event end points complicates interpretation of treatment effects in clinical trials. Non-differential measurement error is unlikely to produce large bias [1]. When error depends on treatment arm, bias is of greater concern. Blinded-independent central review (BICR) of all images from a trial is commonly undertaken to mitigate differential measurement-error bias that may be present in hazard ratios (HRs) based on local evaluations. Similar BICR and local evaluation HRs may provide reassurance about the treatment effect, but BICR adds considerable time and expense to trials. METHODS:We describe a BICR audit strategy [2] and apply it to five randomized controlled trials to evaluate its use and to provide practical guidelines. The strategy requires BICR on a subset of study subjects, rather than a complete-case BICR, and makes use of an auxiliary-variable estimator. RESULTS:When the effect size is relatively large, the method provides a substantial reduction in the size of the BICRs. In a trial with 722 participants and a HR of 0.48, an average audit of 28% of the data was needed and always confirmed the treatment effect as assessed by local evaluations. More moderate effect sizes and/or smaller trial sizes required larger proportions of audited images, ranging from 57% to 100% for HRs ranging from 0.55 to 0.77 and sample sizes between 209 and 737. LIMITATIONS:The method is developed for a simple random sample of study subjects. In studies with low event rates, more efficient estimation may result from sampling individuals with events at a higher rate. CONCLUSION:The proposed strategy can greatly decrease the costs and time associated with BICR, by reducing the number of images undergoing review. The savings will depend on the underlying treatment effect and trial size, with larger treatment effects and larger trials requiring smaller proportions of audited data.

SUBMITTER: Dodd LE

PROVIDER: S-EPMC7511980 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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

Dodd Lori E LE Korn Edward L EL Freidlin Boris B Gu Wenjuan W Abrams Jeffrey S JS Bushnell William D WD Canetta Renzo R Doroshow James H JH Gray Robert J RJ Sridhara Rajeshwari R

Clinical trials (London, England) 20130809 5

<h4>Background</h4>Measurement error in time-to-event end points complicates interpretation of treatment effects in clinical trials. Non-differential measurement error is unlikely to produce large bias [1]. When error depends on treatment arm, bias is of greater concern. Blinded-independent central review (BICR) of all images from a trial is commonly undertaken to mitigate differential measurement-error bias that may be present in hazard ratios (HRs) based on local evaluations. Similar BICR and ...[more]

PMID: 23935162

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Project description:Traditional methods of reporting adverse events in clinical trials are inadequate for modern cancer treatments with chronic administration. Conventional analysis and display of maximum grade adverse events do not capture toxicity profiles that evolve over time or longer lasting, lower grade toxic effects; we aimed to address this shortcoming in this study.We developed an analytic approach and standardised, comprehensive format, the Toxicity over Time (ToxT) approach, which combines graphs and adverse event tabular displays with multiple longitudinal statistical techniques into a readily applicable method to study toxic effects. Plots visualising summary statistics or individual patient data over discrete timepoints were combined with statistical methods including the following longitudinal techniques: repeated measures models that describe the changes in adverse events across all cycles of treatment; time-to-event analyses of first and worst grade toxicity; and area under the curve (AUC) analyses summarising adverse event profiles over the entire course of a study, including chronic low-grade events. We applied ToxT analysis to adverse event data from two completed North Central Cancer Treatment Group (NCCTG/Alliance) trials: N9741 (NCT00003594), in which different combinations of oxaliplatin, 5-fluorouracil, and irinotecan were investigated for metastatic colorectal cancer, and 979254, in which survivors of breast cancer were given venlafaxine or placebo for control of hot flashes.In trial NCCTG 979254 there was a higher incidence of late-occurring dry mouth in patients who were given venlafaxine than in those given placebo (week 1 [baseline]: 13% [six incidence in 48 patients, SD 5] vs 22% [11/49, SD 6]; p=0·20; week 5: 49% [24/49, 7] vs 2% [1/46, 2]; p<0·0001). In trial NCCTG N9741 there was an increased incidence of early nausea for patients given irinotecan plus oxaliplatin (IROX) compared with those given 5-fluorouracil plus oxaliplatin (FOLFOX; cycle 1 mean grade nausea 1·1 [SD 1·0] vs 0·6 [0·7]; p<0·0001). Event charts showed earlier occurrences of higher grades of diarrhoea for patients given IROX compared with those given FOLFOX, and the AUC analysis shows a higher magnitude of diarrhoea consistently over time throughout the study in patients given IROX versus those given FOLFOX (mean AUC 4·2 [SD 5·2] vs 2·9 [4·2]; p<0·0001).The ToxT analytical approach incorporates the dimension of time into adverse event assessment and offers a more comprehensive depiction of toxic effects than present methods. With new, continuously administered targeted agents, immunotherapy, and maintenance regimens, these improved longitudinal analyses are directly relevant to patients and are crucial in cancer clinical trials.National Cancer Institute of the National Institutes of Health and the Mayo Comprehensive Cancer Center.

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

Publications

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

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