Project title: Temporal trends in complete pathological response following neoadjuvant therapy for oesophageal adenocarcinoma.

Potential Supervisors:  Sally Lord

Project description: Neoadjuvant therapy (chemotherapy or chemoradiotherapy) followed by oesophagectomy is standard management for oesophageal adenocarcinoma. Rates of tumour complete pathological response (pCR) are expected to have increased over time, with recent clinical trials of neoadjuvant therapies reporting pCR of over 20%. Some patients with pCR may be able to safely forego surgery but this remains controversial and more information is required to select low-risk patients for non-operative treatment. As a first step for developing a larger research study on this topic, the student will conduct a systematic review of clinical trials and institution-based cohort studies of patients with oesophageal adenocarcinoma receiving neoadjuvant therapy to describe pCR rates and changes over time with newer treatment protocols.

Main research question: What is the frequency of pCR in patients with oesophageal adenocarcinoma treated with contemporary neoadjuvant therapies, and has it changed over time?

Research methodology: This will be a systematic review. The five main steps will be: formulating the research question; searching for relevant studies; screening studies; assessing study quality; extracting data; and summarizing and reporting results.

The summer scholar will gain experience in systematic reviews methods, appraising clinical trial data, and research reporting. They would be supported to submit the results of this project for a conference presentation. The results will be used to inform the development of a larger research project.

Project title: Predictors of and intervention for risk of bias in interventional studies at study design

Potential Supervisors:  Aidan Tan, Lene Seidler and Angela Webster

Project description: Publications in the field of medicine and health over the past decade have continued to grow rapidly in number. Despite the increase in articles, the quality of studies is often unsatisfactory.  Improving the quality of research has become an important goal, and reducing the risk of bias in research is an effective entry point. Bias refers to the discrepancy between the results of a study and the true situation. Quantifying the magnitude and direction of bias is difficult because the true results are usually not known. However, it is possible to determine whether a study has features that put it at ‘risk’ of bias, e.g. if it is not blinded, has high loss to follow-up or randomization is flawed.

As studies require a significant investment of human and financial resources, the ideal way to maximize study quality and avoid wasting resources is to reduce risk of bias at the design stage. Interventional studies (i.e., randomized controlled trials and non-randomized studies of interventions) have more rigorous and precise experimental designs and sources of bias are easier to analysis. To the best of our knowledge, there are no systematic reviews or guidelines on predicting or reducing risk of bias in interventional studies at study design. There is a need to understand the current state of research in this area, and work towards improving the quality of interventional studies and safeguarding the fidelity of their results.

Main research question: What are the predictors of and interventions for risk of bias in interventional studies at study design?

Research methodology: This will be a scoping review following the Joanna Briggs Institute methodology manual. It will involve five main steps: identifying the research question; searching for relevant studies; screening studies; extracting and graphing data; and summarizing and reporting results.

The successful applicant will gain an insight into the fields of meta-research, clinical epidemiology, evidence-based medicine, research methods and clinical trials. They will learn about critical appraisal of interventional studies, and the evaluation and integration of evidence. The summer scholar will improve their literature search and appraisal skills. We aim to submit the results of this project for publication. This would reward the summer scholar’s involvement with authorship in a peer-reviewed scientific journal.

Project title: Investigator adherence to data sharing

Potential Supervisors:  Aidan Tan, Lene Seidler and Angela Webster

Project description:

Billions of public funding are invested annually in clinical trials, $288 million in Australia alone. People put their trust in science by participating in clinical trials to advance health care. Yet, only about half of all studies publish their results in medical journals, and the ones that are published often do not report all their outcomes, or over emphasise benefits omitting less favourable findings. This means policy and clinical practice risks relying on biased evidence, and not all the evidence. One solution is to champion data sharing and re-use for subsequent projects and analyses. On-sharing trial data maximises the value of trial investment, by ensuring the data keeps on contributing to the evidence base beyond the end of the trial. One example is sharing of row-by-row individual participant data (IPD) of completed studies, to enable individual patient data meta-analysis. This can add tremendous value to trials, and is increasingly mandated by funders.

In the scientific community, in-principle support for data sharing is strong, however the in-practice commitment to sharing data is low.

However, despite scientific and ethical imperatives, the in-practice commitment to sharing data is low. The practice of data sharing is dictated by data sharing policies. Over the past few decades, a large number of data sharing policies have been developed by a wide range of stakeholders. These data sharing policies are defined by a variety of principles and describe a variety of approaches to addressing issues. However, they have been generally unsuccessful in closing the gap between the high level of in-principle support for data sharing and low level of in-practice willingness to actually do so.

This summer internship will investigate adherence to data sharing policies, to better understand the landscape of data sharing. Once completed, we hope this work will contribute to the development of an improved data sharing toolkit, to maximise the implementation of widespread data sharing. This will leverage maximum contribution and minimise research waste and strengthen the public acceptability of data sharing.

Main research question: To what extent do investigators adhere to the data sharing policies of relevant stakeholders across the health research life cycle?

As a research intern you will work with a team of expert supervisors. You will learn many useful and transferrable research skills including information management, study design and administration, critical appraisal, database management, data entry and cleaning, data analysis and synthesis and report drafting. The applicant will also develop skills in preparing a manuscript for publication in a peer-reviewed journal. The successful applicant who contributes well will be rewarded with co-authorship on any resulting conference presentations or journal publications. There may be opportunities to develop and extend this topic area into further projects suitable for Honours, MD projects or MPhil work. Preference will be given to applicants who explain their interest and personal objectives.

Project title: Improving the understanding of prospective meta-analyses - a next-generation evidence synthesis method to minimise research waste

Potential Supervisors:  James Sotiropoulos, Lene Seidler, Angela Webster, Kylie Hunter

Project description:

Prospective meta-analysis (PMA) is an exciting emerging evidence synthesis methodology where multiple studies are brought together prospectively (i.e., before the results of any of the studies are known to anyone) for meta-analysis. This approach has many advantages compared to standard retrospective meta-analysis. It minimizes bias in research and maximises the availability and value of research data - which in turn leads to improved health outcomes.

Prospective meta-analyses have provided answers to questions in the areas of how to treat people for COVID-19, prostate cancer treatments, and how to improve the survival of preterm infants.

Yet, since this is an emerging methodology, a deeper understanding of the landscape of studies using this methodology is required to further develop these methods and help more researchers to apply them.

This project seeks to identify and describe all prospective meta-analyses registered on PROSPERO (the international prospective register of systematic reviews). These findings will inform the development of refined methods recommendations for researchers conducting a PMA, with a view to make PMA a more accessible tool for the scientific community.

Main research question: What is the landscape of prospective meta-analyses registered on PROSPERO (the international prospective register of systematic reviews)?

As a research intern, you will work with a team of expert supervisors. You will learn many useful and transferrable research skills including information management, study design and administration, critical appraisal, database management, data entry and cleaning, data analysis and synthesis and report drafting. The applicant will also develop skills in preparing a manuscript for publication in a peer-reviewed journal. The successful applicant who contributes well will be rewarded with co-authorship on any resulting conference presentations or publications. There may be opportunities to develop and extend this topic area into further projects suitable for honours, MD projects, or MPhil work. Preference will be given to applicants who explain their interest and personal objectives.