Trial design picker

Every trial design in the glossary as a card: when to use it, a trial in Nuclide that used it, and the risk that most often undoes it. Below the cards is a plain-English list that starts from the question you want answered and names the design that answers it, then the statistics you will meet when the result comes out and the lifecycle every trial passes through.

1 designs6 familiesAll trial terms All endpoint terms Trials in plain words Failure museum

Comparative designs1 Single-arm and externally controlled designs0 Master protocols0 Adaptive designs0 Dose-finding designs0 Pragmatic, cluster and real-world designs0 Which design fits my question Reading the result Lifecycle

Comparative designs

1 designs

Two or more arms, assigned by chance. The only designs that can prove a treatment causes a benefit.

Crossover in trials

When patients in a trial's control arm are allowed to switch to the experimental drug after their cancer progresses. It is fair to patients but blurs the survival comparison, because the control group has now had the drug too.

When to use it: Control patients will be offered the experimental drug at progression, for ethical or practical reasons.
Main risk: Dilutes the survival comparison; a real benefit can vanish, and its absence can be excused.
Worked example: PSMAforePositiveMost control patients crossed over to the radioligand, blurring overall survival.

Trials Estimands and intercurrent events Lutetium-177

Single-arm and externally controlled designs

0 designs

Everyone gets the new treatment. Fast and small, and unable on their own to show anyone lives longer.

Master protocols

0 designs

One infrastructure, many questions: one drug across indications, many drugs within a cancer, or arms that come and go for years.

Adaptive designs

0 designs

Rules fixed in advance let the trial change as data come in: merge phases, resize, drop arms, tilt randomisation.

Dose-finding designs

0 designs

How a first-in-human trial climbs to a useful dose, and why the highest tolerable dose is no longer the goal.

Pragmatic, cluster and real-world designs

0 designs

Testing treatments where and how they will actually be used, from a single patient to whole districts.

Which design fits my question

Start from the question, not the design. Each answer links to the term that explains the trade-offs.

1.
Is the new treatment better than what we do now?
A randomised controlled trial, blinded if the outcome involves judgement.
2.
Can we give less (shorter, fewer fractions, no chemotherapy) without losing much?
A non-inferiority trial with a justified margin, analysed both intention-to-treat and per protocol.
3.
Does this drug work in a rare mutation that appears across many indications?
A basket trial, with response rate per basket and a confirmatory commitment.
4.
Which of many targeted drugs helps which molecular subgroup of one cancer?
An umbrella trial with a shared screening panel and matched sub-studies.
5.
Will there be new candidate treatments in this disease for years to come?
A platform trial with a shared control arm and pre-specified rules for adding and dropping arms.
6.
Does the marker predict benefit, or just prognosis?
A biomarker-stratified design that randomises within marker-positive and marker-negative groups and tests the interaction.
7.
What dose should go into the pivotal trial?
Model-based dose escalation followed by a randomised comparison of two or more doses.
8.
Should treatment change depending on early response or residual disease?
A SMART design that re-randomises at the decision point and compares whole strategies.
9.
Does the intervention work in ordinary clinics and ordinary patients?
A pragmatic trial with broad eligibility, usual care as comparator and a hard outcome.
10.
Is the intervention delivered to a community or a whole clinic?
A cluster-randomised trial, or a stepped-wedge design if every site will adopt it eventually.
11.
Can we randomise at all?
If not, a single-arm trial with an external control, and honesty about what it cannot show.
12.
Which treatment works for this one patient's symptom?
An N-of-1 trial, if the treatment acts and wears off quickly.

Reading the result

The statistics a trial report throws at you, each with a worked example from the corpus. The evidence table puts every hazard ratio in Nuclide on one axis and Trials in plain words turns results into people out of 100.

Estimands and intercurrent events

The lifecycle every trial passes through

Protocol, ethics review, registration, enrolment, monitoring, readout, publication, label. The regulatory timeline dates the last step for every product in Nuclide and the catalyst calendar lists the readouts still to come.