Method - Design

方法-设计

• 批准号: MC_UU_00004/09
• 负责人: Ian White
• 金额: $ 275.23万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Intramural
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=MC_UU_00004%2F09
• 关键词: Method; Design

Randomised trials are the best way to find out what treatments work, but they can be slow and expensive. We are inventing new and efficient ways to design randomised trials that can give clear answers, often answering multiple questions within the same trial. This work is supported by detailed statistical modelling to show how to analyse the new designs while strictly controlling the risk of wrongly concluding that a treatment is effective when in truth it isn’t. The new designs are implemented in our own trials, and this helps us to refine the designs and demonstrate their value for other trials.Our novel designs are for 1. trials to evaluate whether it is safe to shorten the duration of treatment or use a treatment with fewer side effects;2. trials to evaluate multiple treatments, where we can drop treatments that are found to be ineffective, adopt the use of treatments that are found to be effective, and start evaluating new promising treatments;3. trials that work even when the benefit of treatment is short-term or delayed; 4. trials where groups of patients are randomised rather than individual patients; 5. trials specifically designed to evaluate treatments tailored to specific types of patient; and6. trials comparing a number of treatments, where some patients cannot receive some of the treatments.The results of our work are that treatments can be evaluated faster, more effectively and more cost-effectively.

随机试验是发现治疗有效的最佳方法，但它们可能缓慢而昂贵。我们正在发明新的有效方法来设计随机试验，这些试验可以给出明确的答案，通常在同一试验中回答多个问题。这项工作得到了详细的统计建模的支持，以展示如何分析新的设计，同时严格控制错误地得出治疗有效的结论的风险，而实际上它不是。新的设计在我们自己的试验中实施，这有助于我们改进设计，并证明其对其他试验的价值。评估缩短治疗时间或使用副作用较少的治疗是否安全的试验;2.评估多种治疗方法的试验，我们可以放弃发现无效的治疗方法，采用发现有效的治疗方法，并开始评估新的有希望的治疗方法;3.即使在治疗的益处是短期或延迟的情况下也有效的试验; 4.随机分组患者而非单个患者的试验; 5.专门设计用于评估针对特定类型患者的治疗的试验;以及6.我们的工作成果是可以更快、更有效、更经济地评估治疗方法。

项目成果

Multi-arm Multi-stage (MAMS) Platform Randomized Clinical Trials

多臂多阶段（MAMS）平台随机临床试验

• 发表时间: 2022
• 作者: Choodari-Oskooei B

Starting a conversation about estimands with public partners involved in clinical trials: a co-developed tool.

• DOI: 10.1186/s13063-023-07469-9
• 发表时间: 2023-07-06
• 期刊: Trials
• 影响因子: 2.5

Evaluating how clear the questions being investigated in randomised trials are: systematic review of estimands.

• DOI: 10.1136/bmj-2022-070146
• 发表时间: 2022-08-23
• 期刊: BMJ-BRITISH MEDICAL JOURNAL
• 影响因子: 105.7
• 作者: Cro, Suzie;Kahan, Brennan C.;Rehal, Sunita;Ster, Anca Chis;Carpenter, James R.;White, Ian R.;Cornelius, Victoria
• 通讯作者: Cornelius, Victoria

Predicting prognosis for adults with depression using individual symptom data: a comparison of modelling approaches.

使用个体症状数据预测抑郁症的成年人的预后：建模方法的比较。

• DOI: 10.1017/s0033291721001616
• 发表时间: 2023-01
• 期刊: PSYCHOLOGICAL MEDICINE
• 影响因子: 6.9
• 作者: Buckman, J. E. J.;Cohen, Z. D.;O'Driscoll, C.;Fried, E., I;Saunders, R.;Ambler, G.;DeRubeis, R. J.;Gilbody, S.;Hollon, S. D.;Kendrick, T.;Watkins, E.;Eley, T. C.;Peel, A. J.;Rayner, C.;Kessler, D.;Wiles, N.;Lewis, G.;Pilling, S.
• 通讯作者: Pilling, S.

Facilities for optimizing and designing multiarm multistage (MAMS) randomized controlled trials with binary outcomes

• DOI: 10.1177/1536867x231196295
• 发表时间: 2023-09-01
• 期刊: STATA JOURNAL
• 影响因子: 4.8
• 作者: Choodari-Oskooei，Babak;Bratton，Daniel J.;Parmar，Mahesh K. B.
• 通讯作者: Parmar，Mahesh K. B.