PICO, PICOTS, PICOTT Framework for Clinical Questions as a Way to Design Clinical Trials

The PICO process (or framework) is a mnemonic used in evidence-based medicine to frame and answer a clinical question. The PICO framework is also used to develop literature search strategies, for instance in systematic reviews. The PICO acronym stands for:
        P – Patient, Problem or Population
        I – Intervention
       C – Comparison, control or comparator
       O – Outcome(s) (eg. pain, fatigue, nausea, infections, death)

The PICO framework can also be used in designing and planning a clinical trial. In doing so, people  suggest adding T and S to form PICOTS or PICOTT:
        T - Timing, duration or date of publication (eg. measured at 1-month of follow-up)
        S - Study type (eg. randomized controlled trial), sometimes S can be used to stand for Setting or 

              Sample Size

In a book by Matchar DB. Introduction to the Methods Guide for Medical Test Reviews, the PICO and PICOTS frameworks were discussed:

When well built, clinical questions usually have four components:
P: The patient situation, population, or problem of interest.
I: The main intervention, defined very broadly, including an exposure, a diagnostic test, a prognostic factor, a treatment, a patient perception and so forth.
C: A comparison intervention or exposure (also defined very broadly), if relevant.
O: The clinical outcome(s) of interest, including a time horizon, if relevant.

In addition to the standard PICO components, the broader PICOTS framework is extremely useful and important for defining key clinical questions and assessing whether a given study is applicable or not. T refers to Timing and S refers to Setting or Study Design.
T: Timing, i.e. the time it takes to demonstrate an outcome OR the period in which patients are observed.
S: Setting (e.g. ambulatory settings including primary, specialty care and inpatient settings), or sometimes Study Design (such as a randomized controlled trial). 

The PICOTS framework is also discussed in a book by Samson and Schoelles "Chapter 2: Medical Tests Guidance (2) Developing the Topic and Structuring Systematic Reviews of Medical Tests: Utility of PICOTS, Analytic Frameworks, Decision Trees, and Other Frameworks"

The content below is from FDA's website "Using the PICOTS Framework to Strengthen Evidence Gathered in Clinical Trials—Guidance from the AHRQ’s Evidence-based Practice Centers Program"

P: Patient population

Define the patient population that will be studied in the trial and consider how it compares to the general affected population. Consider patient baseline sociodemographic (e.g., age, race, socioeconomic status) and clinical characteristics (e.g., severity of condition, comorbidities) that may contribute to differences in treatment outcomes or treatment preferences. Define the selection criteria and consider how patients in the study may be diagnosed or treated differently in usual clinical care. Consider biases that may be introduced by the selection of patients or attrition of patients.

I: Intervention

Define the intervention, including all of its components. Consider contextual factors, such as prior, concurrent, posttreatments, or specialized training of the provider, which may affect the safety and/or effectiveness of the intervention.

C: Comparator

Define whether there is a placebo or active control comparator. Consider blinding. For placebo-controlled studies, consider the risk and benefit of using sham comparators. An active comparator should be relevant to current practice. If the comparator is “usual care,” define the components of the “usual care” clearly. Do not select an active comparator that has known poor effectiveness in specific subgroup populations.

O: Outcome

Define the safety and effectiveness outcomes that matter to patients and which predict long-term successful results. If surrogate outcomes, such as biochemical or physiological measures, are used, they should be clinically relevant. Consider the validity and reliability of outcome measures, including composite measures. Define the planned outcome measures and analyses in the protocol. Pre-specify subgroup analyses. Report all findings as defined in the protocol. Note any post hoc analyses.

T: Timing

Define the duration of treatment and the follow-up schedule that matter to patients. Consider both long- and short-term outcomes.

S: Setting

Define the setting (primary, specialty, inpatient, nursing homes, or other long-term care setting) where the study is implemented and the relevance of the study setting to real world use.

In summary, trials that provide high strength of evidence:

• Study patients who are likely to be offered the intervention in everyday practice.
• Examine clinical strategies and complexities that are more likely to be replicated in practice.
• Measure the most relevant set of benefits and harms.
• Have low risk of bias.
• Have adequate power to address subgroups.
• Directly compare interventions.
• Include all important intended and unintended effects including adherence and tolerability.

In Duke's website for Evidence-Based Practice, the PICOTT framework was defined as the following:

PATIENT OR PROBLEMHow would you describe a group of patients similar to yours? What are the most important characteristics of the patient?INTERVENTION, EXPOSURE, PROGNOSTIC FACTORWhat main intervention are you considering? What do you want to do with this patient?COMPARISONWhat is the main alternative being considered, if any?OUTCOMEWhat are you trying to accomplish, measure, improve or affect?Type of QuestionTherapy / Diagnosis / Harm / Prognosis / PreventionType of StudySystematic review / RCT / cohort study / case control

The other day, Dr. Sheng Lou from Duke University reviewed the clinical trial design for Remdesivir in treating Coronavirus infection and he used the PICOTS framework. There are two ongoing pivotal studies in China: one for mild/moderate patients and one for severe patients.