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Table 2 Recommended content of statistical analysis plans for observational studies

From: DEBATE-statistical analysis plans for observational studies

Section/Item Index Description for observational studies
Section 1: Administrative information
 Title and study registration 1a Descriptive title that matches the protocol, with SAP either as a forerunner or subtitle, and study acronym
1b Study registration number
 SAP version 2 SAP version number with dates
 Protocol version 3 Reference to version of protocol being used
 SAP revisions 4a SAP revision history
4b Justification for each SAP revision
4c Timing of SAP revisions in relation to planned repetitive analyses
 Roles and responsibility 5 Names, affiliations, and roles of SAP contributors
 Signatures of: 6a Person writing the SAP
6b Senior statistician responsible
6c Chief investigator/clinical lead
Section 2: Introduction
 Background and rationale 7 Synopsis of study background and rationale including a brief description of research question and brief justification for undertaking the study
 Objectives 8 Description of specific objectives and hypotheses, including secondary objectives
Section 3: Study methods
 Study design 9 Brief description of study design including type of study (e.g. case-control, cross-sectional or cohort study)
 Power considerations 10 In case of an unspecified sample size, provide power calculations for (at least) the primary analysis or present a detectable difference with a specified power*
 Framework 11 Superiority, equivalence, or noninferiority hypothesis testing framework, including which comparisons will be presented on this basis
 Statistical interim analyses and stopping guidance 12a Information on repetitive analyses specifying what repetitive analyses will be carried out and listing of time points
12b Any planned adjustment of the significance level due to repetitive analyses
12c Details of guidelines for stopping the study early
 Timing of final analysis 13 Timing of final analysis, e.g., all outcomes analysed collectively or timing stratified by planned length of follow-up*
 Timing of outcome assessments 14 Time points at which the outcomes are measured including visit “windows”
Section 4: Statistical principles
 Confidence intervals and P-values 15 Level of statistical significance*
16 Description and rationale for any adjustment for multiplicity and, if so, detailing how the type 1 error is to be controlled*
17 Confidence interval to be reported
 Adherence and protocol deviations 18a Definition of protocol deviations for the trial
18b Description of which protocol deviations will be summarized
 Analysis populations 19 Definition of analysis populations, e.g., intention to treat, per protocol, complete case, safety
Section 5: Study Population
 Screening data 20 Reporting of screening data (if collected) to describe representativeness of study sample
 Eligibility 21 Summary of eligibility criteria
 Recruitment 22 Information to be included in the STROBE flow diagram*
 Withdrawal/follow-up 23a Level of withdrawal, e.g., dropouts after inclusion or refusal to be contacted for additional information
23b Timing of withdrawal/lost to follow-up data
23c Reasons and details of how withdrawal/lost to follow-up data will be presented
 Baseline patient characteristics 24a List of baseline characteristics to be summarized
24b Details of how baseline characteristics will be descriptively summarized
 Potential confounding covariates 25 A description of potential confounding covariates and how these will be dealt with*
Section 6: Analysis
 Outcome definitions   List and describe each primary and secondary outcome including details of:
26a Specification of outcomes and timings. If applicable include the order of importance of primary or key secondary end points (e.g., order in which they will be tested)
26b Specific measurement and units (e.g., glucose control, HbA1c [mmol/mol or %])
26c Any calculation or transformation used to derive the outcome (e.g., change from baseline, QoL score, time to event, logarithm, etc)
 Analysis methods 27a What analysis method will be used and how the treatment effects will be presented*
27b Any adjustment for covariates
27c Methods used for assumptions to be checked for statistical methods
27d Details of alternative methods to be used if distributional assumptions do not hold, e.g., normality, proportional hazards, etc
27e Any planned sensitivity analyses for each outcome where applicable*
27f Any planned subgroup analyses for each outcome including how subgroups are defined*
 Missing data 28 Reporting and assumptions/statistical methods to handle missing data (e.g., multiple imputation)*
 Additional analyses 29 Details of any additional statistical analyses required, e.g. complier-average causal effect analysis
 Harms 30 Only applies when intervention effects are studied. Sufficient detail on summarizing safety data, e.g. information on severity, expectedness, and associations; details of how adverse events are scored; how adverse event data will be analysed and the follow-up time.
 Statistical software 31 Details of statistical packages to be used to carry out analysis
 References 32a References to be provided for nonstandard statistical methods
32b Reference to Data Management Plan
32c Reference to the Study Master File and Statistical Master File
32d Reference to other standard operation procedures to be adhered to
  1. This table was adopted from and created with permission from Gamble et al. [7]. An asterisk (*) indicates that a more elaborate description is present in our manuscript