What are the key components of a prospective study research protocol format?

Prospective Study Research Protocol Format

A prospective study protocol must include a clearly defined research question using frameworks like PICO (population, intervention, comparator, outcome), prospective registration before data collection begins, and pre-specified objectives, eligibility criteria, sample size calculations, data collection methods, and statistical analysis plans to ensure methodological rigor and minimize bias. 1, 2

Essential Protocol Components

Research Question and Rationale

• Define the research objective as either descriptive or analytical, specifying what gaps in current evidence the study will address 2
• Use the PICO framework to structure your hypothesis: specify the target patient population, intervention (or exposure) and comparator, outcome definition, and relevant time frame for outcome development 1
• Provide justification for undertaking the study, including a summary of relevant published and unpublished studies examining benefits and harms 1
• Explain the choice of comparators and why a prospective design is the appropriate approach 1, 2

Study Design Specification

• Clearly identify and describe the study design (e.g., prospective cohort, randomized controlled trial, parallel group, crossover) and framework (e.g., superiority, equivalence, noninferiority) 1, 2
• Specify the allocation ratio for controlled trials and describe the type of trial being conducted 1
• Document the study setting including geographic locations, types of facilities (e.g., community clinic, academic hospital), and list of study sites 1

Participant Selection and Recruitment

• Detail eligibility criteria with specific inclusion and exclusion criteria for participants, and if applicable, for study centers and individuals performing interventions 1, 2
• Describe recruitment strategies to allow assessment of potential selection biases in the target sample 2
• Plan for consecutive enrollment beginning at study onset to avoid selection bias 2
• Calculate and specify sample size requirements with supporting clinical and statistical assumptions, including power calculations and strategies for achieving adequate enrollment 1, 2

Variables and Measurements

• Provide a complete list of core variables grouped as baseline characteristics, exposures, and outcomes 2
• Describe each variable in detail including:
  • Specific measurement variables (e.g., systolic blood pressure, HbA1c levels) 1
  • Analysis metrics (e.g., change from baseline, final value, time to event) 1
  • Method of aggregation (e.g., median, proportion) 1
  • Timing of collection and methods of assessment 2
  • Clinical relevance of chosen efficacy and harm outcomes 1

Intervention Details (for controlled trials)

• Describe interventions for each group with sufficient detail to allow replication, including how and when they will be administered 1
• Specify criteria for discontinuing or modifying allocated interventions (e.g., dose changes in response to adverse events) 1
• Outline strategies to improve adherence and procedures for monitoring adherence (e.g., drug tablet return, laboratory tests) 1
• List relevant concomitant care that is permitted or prohibited during the trial 1

Outcomes and Endpoints

• Pre-specify primary and secondary endpoints before analysis is conducted to avoid exploitation of type I error through selective reporting 1
• Define outcomes prospectively with clear specification of measurement timing and methods 1
• Provide evidence of the analytic plan developed before actual analysis, including a priori selection of primary versus secondary outcome measures 1
• Plan subgroup analyses prospectively by factors known to affect test performance or treatment effects (e.g., disease severity, time since symptom onset) 1

Statistical Analysis Plan

• Summarize the main aspects of the statistical analysis plan, including:
  • Pre-planned strategies to identify and mitigate main sources of bias 2
  • Methods for handling missing data 2
  • Planned statistical tests and significance levels 1
  • For meta-analyses: rationale for weighing scheme (fixed vs. random effects) and methods for dose-response analysis 1

Study Timeline

• Create a time schedule of enrollment, interventions (including run-ins and washouts), assessments, and visits for participants 1
• Include a schematic diagram showing the study flow and timing of all procedures 1
• Record timing details for each participant including time from exposure, time since symptom onset, and timing between index test and reference standard 1

Administrative Elements

• Provide a descriptive title identifying the study design, population, interventions, and trial acronym if applicable 1
• Include protocol version with date and version identifier 1
• List funding sources and types of financial, material, and other support 1
• Define roles and responsibilities including:
  • Names, affiliations, and roles of protocol contributors 1
  • Name and contact information for trial sponsor 1
  • Role of sponsor and funders in study design, data management, analysis, interpretation, and publication decisions 1
  • Composition and responsibilities of coordinating center, steering committee, data management team, and other oversight groups 1

Registration and Ethical Approval

• Prospectively register the protocol in an appropriate clinical trial registry (e.g., ClinicalTrials.gov, WHO primary registries) before study initiation 1, 2
• Obtain ethical approval from appropriate institutional review boards or ethics committees 2
• Include the trial registration number to facilitate identification in the registry 1

Critical Pitfalls to Avoid

Protocol Development Errors

• Avoid ill-defined research questions that fail to specify comparator exposures, as this leads to inappropriate study inclusion and substantial heterogeneity 1
• Do not introduce vague protocol criteria that create unnecessary subjectivity during screening and data extraction 1
• Never underestimate subject matter expertise required to formulate research hypotheses and translate them into protocols 1
• Avoid combining incompatible study designs (e.g., observational cohorts with randomized trials) without clear justification, as this can lead to misleading findings 1

Timing and Specification Issues

• Ensure index test and reference standard are conducted as close in time as possible, ideally using the same sample or paired samples 1
• Use the same follow-up period for all individuals when the reference standard includes clinical follow-up or repeat testing 1
• Specify all protocol elements prospectively to prevent post-hoc modifications that introduce bias 1

Quality Standards

• Adhere to reporting guidelines such as PRISMA-P for systematic reviews, SPIRIT for clinical trials, or ARRIVE for animal research 1, 2
• Recognize that protocol quality is arguably one of the major determinants of overall study quality and bias 1
• Understand that prospective registration provides evidence that objectives, procedures, and outcomes were defined prospectively and allows transparent reporting of modifications 1

Protocol as Foundation for Publication

The protocol serves as the roadmap for the entire study and, when written rigorously, forms the first half of the final manuscript—simply requiring conversion from future to past tense 3. This approach ensures that the study will be carried out successfully and is essential for all health research 4.