Literature DB >> 18927094

Early reporting for cancer screening trials.

Stuart G Baker1, Barnett S Kramer, Philip C Prorok.   

Abstract

OBJECTIVE: Many cancer screening trials involve a screening programme of one or more screenings with follow-up after the last screening. Usually a maximum follow-up time is selected in advance. However, during the follow-up period there is an opportunity to report the results of the trial sooner than planned. Early reporting of results from a randomized screening trial is important because obtaining a valid result sooner translates into health benefits reaching the general population sooner. The health benefits are reduction in cancer deaths if screening is found to be beneficial and more screening is recommended, or avoidance of unnecessary biopsies, work-ups and morbidity if screening is not found to be beneficial and the rate of screening drops.
METHODS: Our proposed method for deciding if results from a cancer screening trial should be reported earlier in the follow-up period is based on considerations involving postscreening noise. Postscreening noise (sometimes called dilution) refers to cancer deaths in the follow-up period that could not have been prevented by screening: (1) cancer deaths in the screened group that occurred after the last screening in subjects whose cancers were not detected during the screening program and (2) cancer deaths in the control group that occurred after the time of the last screening and whose cancers would not have been detected during the screening programme had they been randomized to screening (the number of which is unobserved). Because postscreening noise increases with follow-up after the last screening, we propose early reporting at the time during the follow-up period when postscreening noise first starts to overwhelm the estimated effect of screening as measured by a z-statistic. This leads to a confidence interval, adjusted for postscreening noise, that would not change substantially with additional follow-up. Details of the early reporting rule were refined by simulation, which also accounts for multiple looks.
RESULTS: For the re-analysis of the Health Insurance Plan trial for breast cancer screening and the Mayo Lung Project for lung cancer screening, estimates and confidence intervals for the effect of screening on cancer mortality were similar on early reporting and later.
CONCLUSION: The proposed early reporting rule for a cancer screening trial with post-screening follow-up is a promising method for making results from the trial available sooner, which translates into health benefits (reduction in cancer deaths or avoidance of unnecessary morbidity) reaching the population sooner.

Entities:  

Mesh:

Year:  2008        PMID: 18927094      PMCID: PMC2586667          DOI: 10.1258/jms.2008.007058

Source DB:  PubMed          Journal:  J Med Screen        ISSN: 0969-1413            Impact factor:   2.136


  7 in total

1.  Simple maximum likelihood estimates of efficacy in randomized trials and before-and-after studies, with implications for meta-analysis.

Authors:  Stuart G Baker; Barnett S Kramer
Journal:  Stat Methods Med Res       Date:  2005-08       Impact factor: 3.021

2.  Adjusting for non-compliance and contamination in randomized clinical trials.

Authors:  J Cuzick; R Edwards; N Segnan
Journal:  Stat Med       Date:  1997-05-15       Impact factor: 2.373

Review 3.  Dangers of using "optimal" cutpoints in the evaluation of prognostic factors.

Authors:  D G Altman; B Lausen; W Sauerbrei; M Schumacher
Journal:  J Natl Cancer Inst       Date:  1994-06-01       Impact factor: 13.506

4.  The paired availability design: a proposal for evaluating epidural analgesia during labor.

Authors:  S G Baker; K S Lindeman
Journal:  Stat Med       Date:  1994-11-15       Impact factor: 2.373

5.  Lung cancer mortality in the Mayo Lung Project: impact of extended follow-up.

Authors:  P M Marcus; E J Bergstralh; R M Fagerstrom; D E Williams; R Fontana; W F Taylor; P C Prorok
Journal:  J Natl Cancer Inst       Date:  2000-08-16       Impact factor: 13.506

6.  Randomized trials, generalizability, and meta-analysis: graphical insights for binary outcomes.

Authors:  Stuart G Baker; Barnett S Kramer
Journal:  BMC Med Res Methodol       Date:  2003-06-16       Impact factor: 4.615

7.  Statistical issues in randomized trials of cancer screening.

Authors:  Stuart G Baker; Barnett S Kramer; Philip C Prorok
Journal:  BMC Med Res Methodol       Date:  2002-09-19       Impact factor: 4.615

  7 in total
  4 in total

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Journal:  Eur J Epidemiol       Date:  2017-12-05       Impact factor: 8.082

2.  Cancer screening trials: nuts and bolts.

Authors:  Philip C Prorok; Pamela M Marcus
Journal:  Semin Oncol       Date:  2010-06       Impact factor: 4.929

3.  Improving the biomarker pipeline to develop and evaluate cancer screening tests.

Authors:  Stuart G Baker
Journal:  J Natl Cancer Inst       Date:  2009-07-02       Impact factor: 13.506

4.  Limitations in the Effect of Screening on Breast Cancer Mortality.

Authors:  Anna-Belle Beau; Per Kragh Andersen; Ilse Vejborg; Elsebeth Lynge
Journal:  J Clin Oncol       Date:  2018-09-04       Impact factor: 44.544

  4 in total

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