Design of Trials, Meta-analyses and observational studies
Lead Research Organisation:
University College London
Department Name: UNLISTED
Abstract
The CTU-pioneered multi-arm, multi-stage trial design (MAMS), allows efficient evaluation of multiple treatments and the flexibility to drop inactive treatment arms and incorporate new ones. This has been demonstrated in our ongoing STAMPEDE trial in prostate cancer, which added a new arms since 2012. We also began to design a new CTU MAMS trial of novel tuberculosis regimens, and worked with other groups to develop potential MAMS trials in osteosarcoma, hepatobiliary cancer, melanoma, dermatology and multiple sclerosis. We also ran a workshop on MAMS methodology, leading to further requests for help to develop MAMS trials in other diseases. There are many new agents demanding assessment, and a need to evaluate biomarkers that effectively identify more responsive patient subgroups. Our FOCUS4 trial (funded 2012) in colorectal cancer represents a new approach to trial design, linking the evaluation of five novel treatments to the assessment of potentially predictive biomarkers in a multi-staged framework. It offers the flexibility to refine and introduce new biomarkers and/or new therapies, and introduces a new paradigm in oncology. Already, others are considering similar trials in pancreatic and upper gastrointestinal cancer.
Technical Summary
There is an urgent need for new methods for many clinical studies. In particular, we need more rapid, efficient and better evaluation of therapies. This is partly because of the increase in numbers of new therapeutic approaches demanding evaluation, and the staggering failure rate to show that the ‘new’ is better than the ‘old’. Also, phase III trials often require large numbers of patients, take a long time, and cost many millions of pounds. One of the principal ways to improve this situation is through better trial designs.
Motivated by, and directly relevant to, the real challenges of clinical research, and very commonly those faced directly in studies conducted by the MRC Clinical Trial Unit (CTU) we focus on multi-arm, multi-stage platform trials; designing phase II (and III trials) based on an enhanced decision process at the end of phase II; improving the design of stratified medicine trials and biomarker validation studies; designing trials in uncommon diseases and cluster randomised and stepped wedge trials. Also, we want to establish a flexible framework for time-to-event designs, be better able to account for non-proportional hazards, missing data, repeated measures and recurrent events in trial design and explore the possibility of re-randomising participants into trials. In addition, we are investigating sample size estimation for developing and validating prognostic models.
Motivated by, and directly relevant to, the real challenges of clinical research, and very commonly those faced directly in studies conducted by the MRC Clinical Trial Unit (CTU) we focus on multi-arm, multi-stage platform trials; designing phase II (and III trials) based on an enhanced decision process at the end of phase II; improving the design of stratified medicine trials and biomarker validation studies; designing trials in uncommon diseases and cluster randomised and stepped wedge trials. Also, we want to establish a flexible framework for time-to-event designs, be better able to account for non-proportional hazards, missing data, repeated measures and recurrent events in trial design and explore the possibility of re-randomising participants into trials. In addition, we are investigating sample size estimation for developing and validating prognostic models.
Organisations
- University College London (Lead Research Organisation)
- World Health Organization (WHO) (Collaboration)
- UNIVERSITY OF NOTTINGHAM (Collaboration)
- Lancaster University (Collaboration)
- University of Warwick (Collaboration)
- National Institute for Health Research (Collaboration)
- Association of the British Pharmaceutical Industry (Collaboration)
- UNIVERSITY OF CAMBRIDGE (Collaboration)
- AstraZeneca (Collaboration)
- QUEEN MARY UNIVERSITY OF LONDON (Collaboration)
- UNIVERSITY OF OXFORD (Collaboration)
- Alan Turing Institute (Collaboration)
- Amgen Inc (Collaboration)
- Birmingham Women's and Children's NHS Foundation Trust (Collaboration)
- London School of Hygiene and Tropical Medicine (LSHTM) (Collaboration)
- HEALTH DATA RESEARCH UK (Collaboration)
- UNIVERSITY OF LEEDS (Collaboration)
- Medical Research Council (MRC) (Collaboration)
- UNIVERSITY OF LIVERPOOL (Collaboration)
- Cytel (Collaboration)
- Monash University (Collaboration)
- KING'S COLLEGE LONDON (Collaboration)
Publications
Baio G
(2015)
Sample size calculation for a stepped wedge trial.
in Trials
Bartlett JW
(2020)
The Hazards of Period Specific and Weighted Hazard Ratios.
in Statistics in biopharmaceutical research
Bazo-Alvarez JC
(2021)
Cardiovascular outcomes of type 2 diabetic patients treated with DPP-4 inhibitors versus sulphonylureas as add-on to metformin in clinical practice.
in Scientific reports
Bazo-Alvarez JC
(2020)
Handling Missing Values in Interrupted Time Series Analysis of Longitudinal Individual-Level Data.
in Clinical epidemiology
Bazo-Alvarez JC
(2020)
Effects of long-term antipsychotics treatment on body weight: A population-based cohort study.
in Journal of psychopharmacology (Oxford, England)
Bazo-Alvarez JC
(2021)
Current Practices in Missing Data Handling for Interrupted Time Series Studies Performed on Individual-Level Data: A Scoping Review in Health Research.
in Clinical epidemiology
Blake HA
(2020)
Propensity scores using missingness pattern information: a practical guide.
in Statistics in medicine
Blenkinsop A
(2019)
Multiarm, multistage randomized controlled trials with stopping boundaries for efficacy and lack of benefit: An update to nstage
in The Stata Journal: Promoting communications on statistics and Stata
Description | MRC HTMR Network award- Adaptive Design Outreach officer |
Amount | £136,000 (GBP) |
Organisation | Medical Research Council (MRC) |
Sector | Public |
Country | United Kingdom |
Start | 03/2014 |
End | 02/2016 |
Title | PRACTical trial design |
Description | The PRACTical trial design is a new trial design for a clinical setting where several treatments are available with little evidence to choose between them, but many or all patients in the target population have characteristics that make some of the treatments unsuitable. The motivating example is in carbapenem-resistant infections, where antibiotic therapy needs to be personalised based on antimicrobial susceptibility testing and tolerance of toxicity. Traditional two-arm trials, recruiting only patients eligible for both treatments, only address part of the question and recruit poorly, while a multi-arm trial where patients must be eligible for all arms would have even greater recruitment challenges. Trials are urgently needed to answer clinical questions such as whether high-dose carbapenem might overcome resistance, whether older, potentially toxic drugs are more effective in combination with other drugs, and whether newer drugs could be beneficial. Similar issues arise in other diseases, such as TB. Our proposal is to draw up a "personal randomisation list" for each patient, consisting of all the treatments that are potentially suitable, and to randomise the patient between these treatments. Designing a trial in this way should help to overcome recruitment problems. If all patients with the same personal randomisation list are considered as a separate sub-trial, then the idea is akin to network meta-analysis. The idea is to pool information across sub-trials and thus gain efficiency compared to separately analysing each sub-trial. Put differently, we obtain both direct evidence (head-to-head comparisons) and indirect evidence (comparing via a third treatment) about treatment effects. We then combine them, bearing in mind that using direct evidence alone may suffer a large loss of efficiency and may yield incoherent treatment recommendations, while indirect evidence may be of lower validity. |
Type Of Material | Improvements to research infrastructure |
Year Produced | 2021 |
Provided To Others? | Yes |
Impact | A trial is in set-up, NeoSEP1, using this design. NeoSEP1 explores best antibiotic treatment for newborn babies who are in hospital with severe sepsis (https://www.isrctn.com/ISRCTN48721236). A second trial is being developed using this design to compare anti-venoms for snake bites. |
URL | https://www.sciencedirect.com/science/article/pii/S147330992030791X?dgcid=author |
Title | Additional file 1 of Planning a method for covariate adjustment in individually randomised trials: a practical guide |
Description | Additional file 1 Stata code to generate Fig. 1. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Planning_a_method_for_cova... |
Title | Additional file 1 of Planning a method for covariate adjustment in individually randomised trials: a practical guide |
Description | Additional file 1 Stata code to generate Fig. 1. |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_1_of_Planning_a_method_for_cova... |
Title | Additional file 2 of Planning a method for covariate adjustment in individually randomised trials: a practical guide |
Description | Additional file 2 Stata code for the analysis of the GetTested trial (Assumes the data file journal.pmed.1002479.s001.xls has been downloaded from https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002479#sec020 ). |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Planning_a_method_for_cova... |
Title | Additional file 2 of Planning a method for covariate adjustment in individually randomised trials: a practical guide |
Description | Additional file 2 Stata code for the analysis of the GetTested trial (Assumes the data file journal.pmed.1002479.s001.xls has been downloaded from https://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002479#sec020 ). |
Type Of Material | Database/Collection of data |
Year Produced | 2022 |
Provided To Others? | Yes |
URL | https://springernature.figshare.com/articles/dataset/Additional_file_2_of_Planning_a_method_for_cova... |
Title | sj-txt-3-smm-10.1177_09622802211007522 - Supplemental material for Estimation of required sample size for external validation of risk models for binary outcomes |
Description | Supplemental material, sj-txt-3-smm-10.1177_09622802211007522 for Estimation of required sample size for external validation of risk models for binary outcomes by Menelaos Pavlou, Chen Qu, Rumana Z Omar, Shaun R Seaman, Ewout W Steyerberg, Ian R White and Gareth Ambler in Statistical Methods in Medical Research |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://sage.figshare.com/articles/dataset/sj-txt-3-smm-10_1177_09622802211007522_-_Supplemental_mat... |
Title | sj-txt-3-smm-10.1177_09622802211007522 - Supplemental material for Estimation of required sample size for external validation of risk models for binary outcomes |
Description | Supplemental material, sj-txt-3-smm-10.1177_09622802211007522 for Estimation of required sample size for external validation of risk models for binary outcomes by Menelaos Pavlou, Chen Qu, Rumana Z Omar, Shaun R Seaman, Ewout W Steyerberg, Ian R White and Gareth Ambler in Statistical Methods in Medical Research |
Type Of Material | Database/Collection of data |
Year Produced | 2021 |
Provided To Others? | Yes |
URL | https://sage.figshare.com/articles/dataset/sj-txt-3-smm-10_1177_09622802211007522_-_Supplemental_mat... |
Description | Adaptive Designs Working Group |
Organisation | Medical Research Council (MRC) |
Department | Network of Hubs for Trials Methodology Research (HTMR) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | The HTMR Network supported the Adaptive Designs Working Group (WG) to regularly meet and exchange ideas. This involves members of the methodology community and Hub members. |
Collaborator Contribution | Scope: The Adaptive Designs Working Group collaborates to increase uptake of methods, to improve knowledge and to link with key stakeholders such as regulators and industry in this important area for improving the speed and efficiency of trials. Future objectives: The Network plays a vital role in increasing the implementation of adaptive design methodology, with the main barriers to implementation already identified as a lack of software and a lack of expertise. The future plans for this group include continued annual meetings, strengthening the engagement with industry and the development of collaborative inter-Hub visits to develop novel adaptive designs. The group is focusing its efforts on preparing tutorial papers for applied journals and mainstream medical journals; presentations and lectures to increase uptake of methods among stakeholders; and the development of computer software to help researchers to undertake trials with adaptive designs. |
Impact | Adaptive designs meet regularly and host an annual meeting on their research. There is an adaptive design outreach officer - paid for by the Network- who is undertaking regular visits to CTUs and is working on new research methodologies. To date (2016 Feb) 7 CTUs have been visited, and they have collaborated with one group on developing a trial application |
Start Year | 2010 |
Description | Alan Turing Institute and AI - Data Study Group |
Organisation | Alan Turing Institute |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | We have described the problems in monitoring of clinical trial data. Phase III clinical trials are typically multicentre (50-200 sites) and recruit several hundred patients (300-10000). ICH GCP E6(R2) say "Clinical trialists monitor trial data in order to protect the rights and well-being of participants, to ensure that the trial data are accurate, complete, and verifiable, and to confirm that the trial is being run in compliance with the currently approved protocol, with the principles of good clinical practice (GCP), and with the relevant regulatory requirements". This monitoring can take 25% of the CTU trial budget. With risk based monitoring, we consider the risks to the patients and the trial and devise the monitoring to reduce or mitigate these risks. It may be more efficient to use AI (or ML) to look at the full dataset and find what data areas and sites we need to target, rather than use our ideas of risk and solution. We are supplying data sets, information about monitoring and on-hand expertise to allow an exploration of the use of AI. |
Collaborator Contribution | ATI will provide funding for project work for the week. Scientists of the Alan Turing Institute will use AI including ML on our clinical trial data to find out what data areas and sites we need to approach to improve the clinical trial data. We will have monitoring experts from the clinical trials unit on hand to give any explanations required and check the process is on track. |
Impact | The data study group was run in November and December 2021, allowing a group of volunteers to work intensively on the monitoring problem. A report is currently being written. |
Start Year | 2021 |
Description | Alan Turing Institute and AI - Data Study Group |
Organisation | Health Data Research UK |
Country | United Kingdom |
Sector | Private |
PI Contribution | We have described the problems in monitoring of clinical trial data. Phase III clinical trials are typically multicentre (50-200 sites) and recruit several hundred patients (300-10000). ICH GCP E6(R2) say "Clinical trialists monitor trial data in order to protect the rights and well-being of participants, to ensure that the trial data are accurate, complete, and verifiable, and to confirm that the trial is being run in compliance with the currently approved protocol, with the principles of good clinical practice (GCP), and with the relevant regulatory requirements". This monitoring can take 25% of the CTU trial budget. With risk based monitoring, we consider the risks to the patients and the trial and devise the monitoring to reduce or mitigate these risks. It may be more efficient to use AI (or ML) to look at the full dataset and find what data areas and sites we need to target, rather than use our ideas of risk and solution. We are supplying data sets, information about monitoring and on-hand expertise to allow an exploration of the use of AI. |
Collaborator Contribution | ATI will provide funding for project work for the week. Scientists of the Alan Turing Institute will use AI including ML on our clinical trial data to find out what data areas and sites we need to approach to improve the clinical trial data. We will have monitoring experts from the clinical trials unit on hand to give any explanations required and check the process is on track. |
Impact | The data study group was run in November and December 2021, allowing a group of volunteers to work intensively on the monitoring problem. A report is currently being written. |
Start Year | 2021 |
Description | B1- Big Idea- Adaptive Design Outreach officer |
Organisation | Lancaster University |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Network funding provided for this post |
Collaborator Contribution | This proposal is for an "Adaptive Design Outreach Officer" who would be associated with the Adaptive Designs Working Group (ADWG). The key aim would be to raise awareness and use of adaptive designs across a broad range of diseases and across the development and assessment spectrum. Adaptive methods in this context are defined in its broadest sense end will include Bayesian adaptive dose-finding and group-sequential methods, multi-arm trials, lack-of-benefit stopping rules and sample size reassessment methods. The main activity of the outreach officer would be to proactively engage with applied health researchers to discuss the merits and relative drawbacks of the currently available adaptive designs. In particular, the outreach officer would: 1. Develop training material on current adaptive designs 2. Visit each of the UKCRC registered Clinical Trials Units1 to present about the potential of adaptive designs 3. Facilitate the uptake and implementation of adaptive designs 4. Support the writing of tutorial papers on adaptive designs |
Impact | ongoing |
Start Year | 2014 |
Description | B1- Big Idea- Adaptive Design Outreach officer |
Organisation | Medical Research Council (MRC) |
Department | MRC Clinical Trials Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Network funding provided for this post |
Collaborator Contribution | This proposal is for an "Adaptive Design Outreach Officer" who would be associated with the Adaptive Designs Working Group (ADWG). The key aim would be to raise awareness and use of adaptive designs across a broad range of diseases and across the development and assessment spectrum. Adaptive methods in this context are defined in its broadest sense end will include Bayesian adaptive dose-finding and group-sequential methods, multi-arm trials, lack-of-benefit stopping rules and sample size reassessment methods. The main activity of the outreach officer would be to proactively engage with applied health researchers to discuss the merits and relative drawbacks of the currently available adaptive designs. In particular, the outreach officer would: 1. Develop training material on current adaptive designs 2. Visit each of the UKCRC registered Clinical Trials Units1 to present about the potential of adaptive designs 3. Facilitate the uptake and implementation of adaptive designs 4. Support the writing of tutorial papers on adaptive designs |
Impact | ongoing |
Start Year | 2014 |
Description | B1- Big Idea- Adaptive Design Outreach officer |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Network funding provided for this post |
Collaborator Contribution | This proposal is for an "Adaptive Design Outreach Officer" who would be associated with the Adaptive Designs Working Group (ADWG). The key aim would be to raise awareness and use of adaptive designs across a broad range of diseases and across the development and assessment spectrum. Adaptive methods in this context are defined in its broadest sense end will include Bayesian adaptive dose-finding and group-sequential methods, multi-arm trials, lack-of-benefit stopping rules and sample size reassessment methods. The main activity of the outreach officer would be to proactively engage with applied health researchers to discuss the merits and relative drawbacks of the currently available adaptive designs. In particular, the outreach officer would: 1. Develop training material on current adaptive designs 2. Visit each of the UKCRC registered Clinical Trials Units1 to present about the potential of adaptive designs 3. Facilitate the uptake and implementation of adaptive designs 4. Support the writing of tutorial papers on adaptive designs |
Impact | ongoing |
Start Year | 2014 |
Description | Clinical trials in small populations: methodological challenges and solutions (N68) |
Organisation | Lancaster University |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Co-applicants and part of the organising committee for a national 2-day workshop |
Collaborator Contribution | Co-applicants and part of the organising committee for a national 2-day workshop |
Impact | A two-day meeting bringing together methodologists, applied statisticians, patient representatives and regulators to disseminate state-of-the-art methods and set priorities for methodological research in trials in small populations |
Start Year | 2015 |
Description | Clinical trials in small populations: methodological challenges and solutions (N68) |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Co-applicants and part of the organising committee for a national 2-day workshop |
Collaborator Contribution | Co-applicants and part of the organising committee for a national 2-day workshop |
Impact | A two-day meeting bringing together methodologists, applied statisticians, patient representatives and regulators to disseminate state-of-the-art methods and set priorities for methodological research in trials in small populations |
Start Year | 2015 |
Description | Clinical trials in small populations: methodological challenges and solutions (N68) |
Organisation | University of Liverpool |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Co-applicants and part of the organising committee for a national 2-day workshop |
Collaborator Contribution | Co-applicants and part of the organising committee for a national 2-day workshop |
Impact | A two-day meeting bringing together methodologists, applied statisticians, patient representatives and regulators to disseminate state-of-the-art methods and set priorities for methodological research in trials in small populations |
Start Year | 2015 |
Description | Clinical trials in small populations: methodological challenges and solutions (N68) |
Organisation | University of Warwick |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Co-applicants and part of the organising committee for a national 2-day workshop |
Collaborator Contribution | Co-applicants and part of the organising committee for a national 2-day workshop |
Impact | A two-day meeting bringing together methodologists, applied statisticians, patient representatives and regulators to disseminate state-of-the-art methods and set priorities for methodological research in trials in small populations |
Start Year | 2015 |
Description | Clustering and covariates in the design and analysis of RCTs |
Organisation | Queen Mary University of London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Initiator of collaboration; provide expertise and intellectual input |
Collaborator Contribution | Leadership of the project |
Impact | A number of publications have resulted from this collaboration, for example PMID: 23825027, 24749914, 24755011, 24456267. More are forthcoming. |
Start Year | 2010 |
Description | Collaboration with Cytel, manufacturers of East software |
Organisation | Cytel |
Country | United Kingdom |
Sector | Private |
PI Contribution | We have formed a collaboration with Cytel, manufacturers of East software for designing adaptive trials, with the aim of getting our novel MAMS methods implemented in East and conversely using East to validate our software. Based on our experience with Stampede and other MAMS trials, we provide advice on how to develop a suitable user interface in East, as well as implementing our methods both analytically and via simulation. |
Collaborator Contribution | Based on our input and advice, Cytel will develop prototypes for us to try them out and gives us feed-back so that we know what does or does not work. |
Impact | This is multi-disciplinary collaboration which includes both the development of statistical methodology as well as implementing those in East. |
Start Year | 2019 |
Description | Collaboration with WHO on complex adaptive trial designs |
Organisation | World Health Organization (WHO) |
Country | Global |
Sector | Public |
PI Contribution | We designed mlti-arm multi-stage (MAMS) selection trial in postpartum haemorrhage. It is planned to be conducted in middlle and low income countries in Africa and South East Asia. |
Collaborator Contribution | WHO will conduct the trial with the technical/statistical support of the MRC CTU. |
Impact | Conference presentation, and a (working) design article. |
Start Year | 2020 |
Description | Collaborative research with MRC BSU |
Organisation | University of Cambridge |
Department | MRC Biostatistics Unit |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Joint collaborative research in design and analysis of clinical trials |
Collaborator Contribution | Joint collaborative research in design and analysis of clinical trials |
Impact | Several papers including PUBMED id: 19153970; 19452569; 21225900 |
Description | Jane Walker - University of Oxford |
Organisation | University of Oxford |
Department | Department of Psychiatry |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Contribute to the design, conduct and analysis of a pragmatic multicentre randomised controlled trial to compare the effectiveness and cost-effectiveness of Proactive Liaison Psychiatry with usual care. |
Collaborator Contribution | Lead on the design, conduct and analysis of a pragmatic multicentre randomised controlled trial to compare the effectiveness and cost-effectiveness of Proactive Liaison Psychiatry with usual care. |
Impact | Trial is ongoing |
Start Year | 2016 |
Description | MAMS design for erosive lichen planus |
Organisation | University of Nottingham |
Department | Centre of Evidence Based Dermatology |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Group keen to develop a methodologically efficient design to assess new treatments for women with vulval erosive lichen planus, a rare but debilitating condition. We have worked to help develop study designs, including updates to the multi-arm multi-stage approach, which will be covered in a PhD (Dan B). Eventually calculated that a multi-stage approach could not be used with the particular outcome measures required for the condition. Funding was successfully obtained for the trial which will be run from Nottingham CTU. MRC CTU's Scientific Strategy Group chose not to proceed with this. The unit has developed the first draft of the Statistical Analysis Plan and will engage in an advisory capacity. One member of the unit will serve on the IDMC. |
Collaborator Contribution | Treatment of patients, design and discussion and leadership of research. |
Impact | Grant applications submitted to NIHR and RfPB. Lead researcher has successfully won an NIHR fellowship during this time to contribute further to the research. |
Start Year | 2012 |
Description | Making decisions at the end of a Phase 2 clinical trial |
Organisation | Amgen Inc |
Country | United States |
Sector | Private |
PI Contribution | Methodological development of an approach to the decision as to whether to proceed to a phase three trial at the end of phase two that synthesizes the available data. An exploration as to how this can also be used to design trials at phase two and three. |
Collaborator Contribution | Methodological development and simulation work as part of a PhD research project |
Impact | 2 research papers published and a further paper has been submitted; has had implications for how trial design decisions are made within Amgen |
Start Year | 2012 |
Description | Methodology Research Collaboration with industry |
Organisation | AstraZeneca |
Country | United Kingdom |
Sector | Private |
PI Contribution | Commitment to developing research activity in to design, conduct or analysis methodology in areas of mutual interest. Detailed discussions ongoing |
Collaborator Contribution | Commitment to developing research activity in to design, conduct or analysis methodology in areas of mutual interest. Detailed discussions ongoing |
Impact | None yet |
Start Year | 2014 |
Description | NIHR & MRC Trials Methodology Research Parternship Executive Group |
Organisation | Association of the British Pharmaceutical Industry |
Country | United Kingdom |
Sector | Charity/Non Profit |
PI Contribution | Intellectual input and plans for further collaboration on future projects Member of Executive Group (Coordinated from University of Liverpool) Co-chair of Health Informatics Working Group (Co-chaired from University of Leeds) Co-chair of Statistical Analysis Working Group (Co-chaired from Kings College London) |
Collaborator Contribution | 25 partner organisations around UK (not all listed at this stage) Intellectual input and plans for further collaboration on future projects |
Impact | (None yet) |
Start Year | 2019 |
Description | NIHR & MRC Trials Methodology Research Parternship Executive Group |
Organisation | King's College London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input and plans for further collaboration on future projects Member of Executive Group (Coordinated from University of Liverpool) Co-chair of Health Informatics Working Group (Co-chaired from University of Leeds) Co-chair of Statistical Analysis Working Group (Co-chaired from Kings College London) |
Collaborator Contribution | 25 partner organisations around UK (not all listed at this stage) Intellectual input and plans for further collaboration on future projects |
Impact | (None yet) |
Start Year | 2019 |
Description | NIHR & MRC Trials Methodology Research Parternship Executive Group |
Organisation | Medical Research Council (MRC) |
Country | United Kingdom |
Sector | Public |
PI Contribution | Intellectual input and plans for further collaboration on future projects Member of Executive Group (Coordinated from University of Liverpool) Co-chair of Health Informatics Working Group (Co-chaired from University of Leeds) Co-chair of Statistical Analysis Working Group (Co-chaired from Kings College London) |
Collaborator Contribution | 25 partner organisations around UK (not all listed at this stage) Intellectual input and plans for further collaboration on future projects |
Impact | (None yet) |
Start Year | 2019 |
Description | NIHR & MRC Trials Methodology Research Parternship Executive Group |
Organisation | National Institute for Health Research |
Country | United Kingdom |
Sector | Public |
PI Contribution | Intellectual input and plans for further collaboration on future projects Member of Executive Group (Coordinated from University of Liverpool) Co-chair of Health Informatics Working Group (Co-chaired from University of Leeds) Co-chair of Statistical Analysis Working Group (Co-chaired from Kings College London) |
Collaborator Contribution | 25 partner organisations around UK (not all listed at this stage) Intellectual input and plans for further collaboration on future projects |
Impact | (None yet) |
Start Year | 2019 |
Description | NIHR & MRC Trials Methodology Research Parternship Executive Group |
Organisation | University of Leeds |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input and plans for further collaboration on future projects Member of Executive Group (Coordinated from University of Liverpool) Co-chair of Health Informatics Working Group (Co-chaired from University of Leeds) Co-chair of Statistical Analysis Working Group (Co-chaired from Kings College London) |
Collaborator Contribution | 25 partner organisations around UK (not all listed at this stage) Intellectual input and plans for further collaboration on future projects |
Impact | (None yet) |
Start Year | 2019 |
Description | NIHR & MRC Trials Methodology Research Parternship Executive Group |
Organisation | University of Liverpool |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input and plans for further collaboration on future projects Member of Executive Group (Coordinated from University of Liverpool) Co-chair of Health Informatics Working Group (Co-chaired from University of Leeds) Co-chair of Statistical Analysis Working Group (Co-chaired from Kings College London) |
Collaborator Contribution | 25 partner organisations around UK (not all listed at this stage) Intellectual input and plans for further collaboration on future projects |
Impact | (None yet) |
Start Year | 2019 |
Description | NIHR & MRC Trials Methodology Research Parternship Executive Group |
Organisation | University of Oxford |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input and plans for further collaboration on future projects Member of Executive Group (Coordinated from University of Liverpool) Co-chair of Health Informatics Working Group (Co-chaired from University of Leeds) Co-chair of Statistical Analysis Working Group (Co-chaired from Kings College London) |
Collaborator Contribution | 25 partner organisations around UK (not all listed at this stage) Intellectual input and plans for further collaboration on future projects |
Impact | (None yet) |
Start Year | 2019 |
Description | Novel clinical trial design in a surgical setting (ROSSINI II) |
Organisation | Birmingham Women's and Children's NHS Foundation Trust |
Country | United Kingdom |
Sector | Public |
PI Contribution | Key role in the trial design and sample size calculation. Developed a proposal for the design of the trial, using novel multi-arm multi-stage design, with binary outcome (total: eight arms). |
Collaborator Contribution | Responsible for submitting the funding application and running the clinical trial |
Impact | None yet. |
Start Year | 2014 |
Description | Re-randomisation of patients to a clinical trial |
Organisation | Monash University |
Country | Australia |
Sector | Academic/University |
PI Contribution | Intellectual input to original design and resulting paper; currently working on follow up projects to demonstrate strengths and weaknesses and to understand practicalities of the design |
Collaborator Contribution | Intellectual input to original design and resulting paper; currently working on follow up projects to demonstrate strengths and weaknesses and to understand practicalities of the design. |
Impact | Several invited seminars (Leeds, Leicester, LSHTM), conference papers, one published paper. |
Start Year | 2014 |
Description | Re-randomisation of patients to a clinical trial |
Organisation | Queen Mary University of London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual input to original design and resulting paper; currently working on follow up projects to demonstrate strengths and weaknesses and to understand practicalities of the design |
Collaborator Contribution | Intellectual input to original design and resulting paper; currently working on follow up projects to demonstrate strengths and weaknesses and to understand practicalities of the design. |
Impact | Several invited seminars (Leeds, Leicester, LSHTM), conference papers, one published paper. |
Start Year | 2014 |
Description | Sample size calculations for cluster randomised trials |
Organisation | Queen Mary University of London |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Review of how sample size calculations are made and reported in cluster randomised trials, critical review of the published sample formulae with practical guidance. Further work will include development of guidance for calculating sample size for trials with an ordinal outcome |
Collaborator Contribution | Joint supervision of PhD student |
Impact | Two research papers have been published and a presentation has been made at a conference. One further article is in development |
Start Year | 2011 |
Description | Stepped wedge trial design |
Organisation | London School of Hygiene and Tropical Medicine (LSHTM) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | Intellectual contribution to all activities, lead authorship on one of 6 publications |
Collaborator Contribution | Intellectual contributions |
Impact | Special issue of Trials (6 articles), workshop to present the findings. Further collaboration with other parts of UCL as well as with LSHTM. Work is already being cited. |
Start Year | 2014 |
Description | Stratified Medicine WG |
Organisation | Medical Research Council (MRC) |
Department | Network of Hubs for Trials Methodology Research (HTMR) |
Country | United Kingdom |
Sector | Academic/University |
PI Contribution | The HTMR Network supports the Stratified Medicine Working Group (WG) to regularly meet and exchange ideas. This involves members of the methodology community and Hub members. |
Collaborator Contribution | Scope- Stratified Medicine is about tailoring treatments to specific patients, helping to ensure the highest chance of benefit and minimising the potential for harm or unnecessary treatment The Stratified Medicine Working Group collaborates to look at novel designs for biomarker-stratified trials, and to bring the stratified medicine approach into a wider range of disease areas, complementing work already done in the widely studied examples of cancer and heart disease. Future Objectives- The Working Group is preparing a guidance paper to help people reading a stratified medicine research paper, and has started to explore means for delivering advice to applicants to the MRC Research Panel on Stratified Medicine. Members of the Working Group are also planning to develop prognostic models that help in the prediction of harms and benefits following the use of thrombolysis to treat stroke, drawing on individual participant data meta-analysis of clinical trials. |
Impact | ongoing collaborations. |
Start Year | 2012 |
Title | A combined test for a generalized treatment effect in clinical trials with a time-to-event outcome |
Description | Performs a combined test for a generalized treatment effect in clinical trials with a time-to-event outcome |
Type Of Technology | Software |
Year Produced | 2017 |
Impact | None yet - just released |
Title | R package for the design of Non-inferiority and durations trials |
Description | Gives utility functions to help the design and analysis of non-inferiority trials. These include functions for sample size calculations on various scales and for testing for non-inferiority. |
Type Of Technology | Webtool/Application |
Year Produced | 2020 |
Open Source License? | Yes |
Impact | None yet - just released |
Title | nstage |
Description | nstage is a Stata add-on to aid the design of a multi-arm multi-stage (MAMS) trial by recommending the duration of each trial stage and decision procedures at the end of each stage. It was updated in 2016 to calculate the familywise type 1 error rate and in 2019 to allow early stopping for efficacy. |
Type Of Technology | Software |
Year Produced | 2016 |
Impact | Used in the design of a number of MAMS trials including STAMPEDE, FOCUS4, and RAMPART. |
URL | https://ideas.repec.org/c/boc/bocode/s457931.html |
Description | An Interview with Professor Andrew Nunn |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Other audiences |
Results and Impact | Andrew Nunn joined the MRC's Tuberculosis & Chest Diseases Unit as a statistician in 1966. During the next 20 years he was directly involved in the design, conduct and analysis of the programme of trials conducted under the leadership of Professors Wallace Fox and Denny Mitchison in East Africa, Hong Kong and Singapore which led to the worldwide adoption of short course chemotherapy for tuberculosis. Following the closure of that unit he joined the MRC's Uganda AIDS Programme which researched the dynamics of the HIV epidemic in a rural African environment. On his return to the UK he became head of the Division Without Portfolio within the newly formed MRC Clinical Trials Unit with responsibility for developing trials in neglected areas. Andrew is Co-Chief Investigator of STREAM, the first randomised controlled-trial of a treatment regimen for multi-drug resistant TB. In the context of treatment guidelines based on 'very low quality' evidence, Andrew designed STREAM to generate gold-standard evidence on the safety and efficacy of the promising 9-month short-course regimen previously evaluated only in observational studies. The trial has subsequently been adapted to test a bedaquiline-containing oral regimen. |
Year(s) Of Engagement Activity | 2018 |
URL | https://soundcloud.com/user-110325996-105034477/andrew-nunn-talks-medical-statistics-tb-and-algerian... |
Description | An Interview with Professor Jayne Tierney. |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Jayne Tierney has been a Research Scientist at the Unit since it was formed in 1999, and prior to that, in the Cancer Trials Office in Cambridge. For more than 20 years, she has been responsible for designing and conducting systematic reviews and meta-analyses to rigorously re-evaluate the effectiveness of therapies; projects that have influenced practice guidelines and the treatment of patients worldwide. Today we discuss Jayne's career in depth, improving systematic reviews, and how to stand out as an individual when the work you do is mostly collaborative. |
Year(s) Of Engagement Activity | 2018 |
URL | https://soundcloud.com/user-110325996-105034477/jayne-tierney-talks-systematic-reviews-impact-and-fi... |
Description | An interview with Patrick Royston for the first podcast in a series 'MRCCTU: The Ideas Behind the Trials' |
Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Public/other audiences |
Results and Impact | Professor Patrick Royston was awarded the Stata Journal Editors' Prize 2016, for his significant contributions to Stata and the Stata community over the last 25 years, and for three papers he published in the Stata Journal during the previous two years. Today, Patrick will officially receive his award at 2017 London Stata Users Group meeting in London. To commemorate this occasion, we have interviewed Patrick for the first podcast in our new series 'MRCCTU: The Ideas Behind the Trials'. The interview explores Patrick's career in more depth, and provides an insight into his work with Stata, including fractional polynomials, and survival analysis "beyond the Cox model". There is also some excellent advice for younger statisticians just starting out in the field. Click the link below to listen to the podcast. |
Year(s) Of Engagement Activity | 2017 |
URL | https://soundcloud.com/user-110325996-105034477/patrick-royston-receives-the-stata-journal-editors-p... |
Description | EU-PEARL workshop on non-concurrent controls |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | International workshop on the controversial area of using on patients in a platform protocol not randomised concurrently to the trial. M Parmar and M Sydes contributed presentations and panel discussions. |
Year(s) Of Engagement Activity | 2022 |
URL | https://www.youtube.com/watch?v=nYl-lHtVwxA&ab_channel=EU-PEARL |
Description | IW speak at TB prevention trials workshop 15-17/9/2021 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Invited speaker at WHO Technical Consultation: Innovative clinical trial designs for the evaluation of new TB preventive treatment |
Year(s) Of Engagement Activity | 2021 |
Description | Marie Curie workshop |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | 40 people from a range of backgrounds attended a workshop "Missing Data in Palliative Care Studies" at which Ian White spoke. This led to a draft document for use by the Marie Curie charity and others. |
Year(s) Of Engagement Activity | 2017 |
Description | Member of trial steering committee, POSNOC trial |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | Yes |
Geographic Reach | National |
Primary Audience | Professional Practitioners |
Results and Impact | Appointed member of trial steering committee, POSNOC trial (2014-2024): POSNOC - A randomised trial of armpit (axilla) treatment for women with early stage breast cancer. The POSNOC trial will provide evidence relevant to patients and to the NHS. The protocol has been designed to integrate into current NHS practice. The hypothesis of the POSNOC trial is that low axillary tumour burden patients (clinically and ultrasound negative) with macrometastases in 1 or 2 SNs, receiving systemic therapy, would have non-inferior outcomes whether they are randomised to adjuvant therapy alone or adjuvant therapy plusaxillary treatment (ANC or ART) |
Year(s) Of Engagement Activity | 2014,2015,2016,2017,2018,2019,2020,2021 |
URL | http://www.nets.nihr.ac.uk/__data/assets/pdf_file/0004/111469/PRO-12-35-17.pdf |
Description | Poster presented at CRUK Early Detection of Cancer Conference |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Poster presented at CRUK Early Detection of Cancer Conference, October 2022 Title: Characterising Cancer-specific Methylation Changes During Leukaemia - Development to Guide Improved Early Detection |
Year(s) Of Engagement Activity | 2022 |
Description | Training Research Ethics Committees on the issues in platform protocols |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation by M Sydes on Education and training: platform protocols and RECs at EFPIA meeting on Complex Clinical Trials. Aimed at people who sit or or engage with Research Ethics Committees. |
Year(s) Of Engagement Activity | 2021 |
URL | https://www.efpia.eu/media/636521/day-2-s2-bo6-master-v2.pdf |
Description | UCL health methods software showcase |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | Local |
Primary Audience | Professional Practitioners |
Results and Impact | Online workshop for all UCL staff writing software for statistics-related applicatins in health |
Year(s) Of Engagement Activity | 2021 |