Sample size calculation for clinical trials: the impact of clinician beliefs

被引:0
|
作者
P M Fayers
A Cuschieri
J Fielding
J Craven
B Uscinska
L S Freedman
机构
[1] MRC Clinical Trials Unit,Cancer Division
[2] Ninewells Hospital and Medical School,University Department of Surgery
[3] Queen Elizabeth Hospital,Department of Surgery
[4] Kingstown General Hospital,Department of Mathematics
[5] Statistics and Computer Science,undefined
[6] Bar Ilan University,undefined
来源
British Journal of Cancer | 2000年 / 82卷
关键词
sample size; prior beliefs; clinicians'; opinions; clinical trial;
D O I
暂无
中图分类号
学科分类号
摘要
The UK Medical Research Council (MRC) randomized trial of gastric surgery, ST01, compared conventional (D1) with radical (D2) surgery. Sample size estimation was based upon the consensus opinion of the surgical members of the design team, which suggested that a change in 5-year survival from 20% (D1) to 34% (D2) could be realistic and medically important. On the basis of these survival rates, the sample size for the trial was 400 patients. However, this trial was exceptional in the way that a survey of surgeons’ opinions was made at the start of the trial, in 1986, and again before results were analysed but after termination of the trial in 1994. At the initial survey, the three surgeons from the trial steering committee and 23 other surgeons experienced in treating gastric carcinoma were given detailed questionnaires. They were asked about the expected survival rate in the D1 group, anticipated difference in survival from D2 surgery, and what difference would be medically important and influence future treatment of patients. The consensus opinion of those surveyed was that there might be a survival improvement of 9.4%. In 1994, prior to closure of the trial, and before any survival information was disclosed, the survey was repeated with 21 of the original 26 surgeons. At this second survey, the opinion of the trial steering committee was that 9.5% difference was more realistic. This was in accord with the opinion of the larger group, which remained little changed since 1986. The baseline 5-year D1 survival was thought likely to be about 32%, which corresponded closely to the actual survival of recruited patients. Revised sample size calculations suggested that, on the basis of these more recent opinions, between 800 and 1200 patients would have been required. Both surveys assessed the level of treatment benefit that was deemed to be sufficient for causing surgeons to change their practice. This showed that the 13% difference in survival used as the study target was clinically relevant, but also indicated that many clinicians would remain unwilling to change their practice if the difference is only 9.5%. The experience of this carefully designed trial illustrates the problems of designing long-term, randomized trials. It raises interesting questions about the common practice of basing sample size estimates upon the beliefs of a trial design committee that may include a number of enthusiasts for the trial treatment. If their opinion of anticipated effect sizes drives the design of the trial, rather than the opinion of a larger community of experts that includes sceptics as well as enthusiasts, there is likely to be a serious miscalculation of sample size requirements. © 2000 Cancer Research Campaign
引用
收藏
页码:213 / 219
页数:6
相关论文
共 50 条
  • [41] Sample size calculation based on efficient unconditional tests for clinical trials with historical controls
    Shan, Guogen
    Moonie, Sheniz
    Shen, Jay
    JOURNAL OF BIOPHARMACEUTICAL STATISTICS, 2016, 26 (02) : 240 - 249
  • [42] Sample Size Calculation for Clinical Trials of Medical Decision Support Systems with Binary Outcome
    Rebrova, O. Yu.
    Gusev, A. V.
    SOVREMENNYE TEHNOLOGII V MEDICINE, 2022, 14 (03) : 6 - 13
  • [43] Inference and sample size calculation for clinical trials with incomplete observations of paired binary outcomes
    Zhang, Song
    Cao, Jing
    Ahn, Chul
    STATISTICS IN MEDICINE, 2017, 36 (04) : 581 - 591
  • [44] Underpowering in randomized trials reporting a sample size calculation
    Vickers, AJ
    JOURNAL OF CLINICAL EPIDEMIOLOGY, 2003, 56 (08) : 717 - 720
  • [45] Letter to the Editor: Sample Size Calculation in Bioequivalence Trials
    Peter Blood
    Journal of Pharmacokinetics and Pharmacodynamics, 2002, 29 : 95 - 97
  • [46] Demystifying sample-size calculation for clinical trials and comparative effectiveness research: the impact of low-event frequency in surgical clinical research
    Chang, David C.
    Yu, Peter T.
    Easterlin, Molly C.
    Talamini, Mark A.
    SURGICAL ENDOSCOPY AND OTHER INTERVENTIONAL TECHNIQUES, 2013, 27 (02): : 359 - 363
  • [47] Demystifying sample-size calculation for clinical trials and comparative effectiveness research: the impact of low-event frequency in surgical clinical research
    David C. Chang
    Peter T. Yu
    Molly C. Easterlin
    Mark A. Talamini
    Surgical Endoscopy, 2013, 27 : 359 - 363
  • [48] Introduction of a User-oriented Application for Biometrical Sample Size Calculation in Clinical and Epidemiological Trials
    Geis, Berit
    Tulka, Sabrina
    Knippschild, Stephanie
    Krummenauer, Frank
    KLINISCHE MONATSBLATTER FUR AUGENHEILKUNDE, 2021, 238 (02) : 179 - 185
  • [49] Sample size calculation for clinical trials with correlated count measurements based on the negative binomial distribution
    Li, Dateng
    Zhang, Song
    Cao, Jing
    STATISTICS IN MEDICINE, 2019, 38 (28) : 5413 - 5427