Ateneo - UPO

The course is dedicated to clinical trial design and the main methodological choices that lead from the research question to the protocol definition.
The choice of study population, intervention, and comparator, endpoint definition, randomization, sample size, and main analysis strategies will be discussed. Superiority and non-inferiority studies, analysis populations, missing data, and issues related to the presence of endpoints or multiple comparisons will also be addressed.
Part of the course will be dedicated to early-stage trials, biomarker-based studies, and key innovative and adaptive designs. Finally, some examples of the use of real-world data and digital technologies in clinical research will be presented.

Friedman LM, Furberg CD, DeMets DL, Reboussin DM, Granger CB Fundamentals of Clinical Trials. Springer.
Piantadosi S. Clinical Trials: A Methodological Perspective. Wiley.
Scientific articles, examples of protocols and documents will also be used during the course methodological. International guidelines and standards will be used when necessary including ICH and CONSORT documents.

The course aims to provide the tools necessary to set up and critically evaluate the design of a clinical study. At the end of the course students will have to be able to start from an application for
research and define the main elements of a study: population, intervention, comparator, endpoint, randomization, sample size and analysis populations.
Some methodological aspects related to non-inferiority studies, biomarker-based trials, and adaptive and innovative designs will also be explored in depth, with attention to the implications of different choices on the validity and interpretation of the results.

Basic knowledge of clinical trials, major stages of clinical development, and randomized clinical trials is required.
Basic knowledge of biostatistics, particularly related to hypothesis testing, confidence intervals, and measures of effect, is also useful.

The lectures will alternate a theoretical part with the discussion of examples from published clinical studies and protocols.
Students will be involved in evaluating the different drawing choices and identifying the main methodological problems. Exercises on endpoints, randomization, sample size, and non-inferiority will be offered, as well as activities dedicated to reading and constructing simple study synopses.

Presentations, scientific articles, protocols used during lessons, and other supporting materials will be available on the course teaching platform (DIR).
Some articles or documents may be required to be read before the lessons dedicated to their discussion.

The examination will assess both knowledge of the main methodological aspects and the ability to apply them to the design of a clinical trial.
The test may include closed-ended and open-ended questions, short exercises, and the interpretation of parts of protocols or published studies.
In particular, the ability to choose an appropriate design, define the population, comparator, and endpoint, set up randomization, and understand the elements that influence sample size will be evaluated. The student will also have to be able to distinguish between studies of superiority, non-inferiority and equivalence, recognize the main populations of analysis and identify possible criticalities or sources of bias.
A brief exercise in designing or evaluating a study synopsis based on a clinical or translational problem may also be proposed.

1. From research question to study design
Definition of the research question, objectives and hypotheses. PICO. Exploratory and confirmatory studies. Efficacy and effectiveness. Internal and external validity. Choice of study design in relation to the research question.

2. Population, intervention, comparator and endpoint
Target population and study population. Inclusion and exclusion criteria. Choice of intervention and comparison group. Placebo, standard of care and active comparator. Primary, secondary and exploratory endpoints. Clinical, surrogate and composite endpoints. Patient-reported outcomes.

3. Randomization, masking, and control groups
Purpose of randomization. Simple, blocky, and layered randomization. Allocation concept. Blinded and open-label studies. Choice of control group.

4. Sample number
Main elements determining sample size: primary endpoint, effect size, variability, event frequency, type I error, power, and dropout. Difference between statistical significance and clinically relevant effect. Assessment of the intakes underlying the calculation of numerosity.

5. Superiority, non-inferiority and equivalence
Differences between studies of superiority, non-inferiority and equivalence. Non-inferiority margin and its interpretation. Use of confidence intervals. Choice of comparator. Role of intention-to-treat and per-protocol analyses.

6. Analysis populations, missing data and multiplicity
Intention-to-treat, modified intention-to-treat, per-protocol, and safety population. Protocol deviations, losses to follow-up, and missing data. Multiple endpoints and multiple comparisons. Analysis by subgroups. Prespecified and post-hoc analyses. Notes on the Statistical Analysis Plan.

7. Early-stage studies and biomarkers
Principles of early stage studies. Dose escalation, dose-limiting toxicity, dose expansion and proof-of-concept. Prognostic and predictive biomarkers. Enrichment and stratification. Introduction to basketball and umbrella trials.

8. Innovative and adaptive designs
Interim analysis and stopping rules. Principles of adaptive and group-sequential designs. Changing the sample size. Seamless designs. Master protocols and platform trials. Main methodological advantages and limitations.

9. Real-world data and digital technologies
Pragmatic trials and registry-based trials. Real-world data and real-world evidence. Use of external or historical controls. Confounding, selection bias, and data quality. Notes on digital endpoints, remote monitoring, and decentralized trials.

10. From study design to protocol
Construction of a simple study synopsis. Definition of objectives, population, intervention, comparator, endpoint, randomization, number, and populations of analysis. Overall evaluation of the design in terms of validity, clinical relevance and feasibility.

At the end of the course the student will be able to set up a study design starting from a clinical or translational research question and to motivate the main choices methodological.
It will be able to define population, intervention, comparator and endpoint, understand the principles of randomization and determination of sample size and distinguish between studies of superiority, non-inferiority and equivalence.
The student will also acquire the tools to critically assess populations of analyses, missing data, multiplicities and main sources of bias and to understand the essential characteristics of early-stage, biomarker-based and adaptive trials.
It will finally be able to read and critically evaluate a simple synopsis or study protocol.