- Identify the study as developing and/or validating a multivariable prediction model, the target population, and the outcome to be predicted.
- Provide a summary of objectives, study design, setting, participants, sample size, predictors, outcome, statistical analysis, results, and conclusions.
- Background and objectives
- Explain the medical context (including whether diagnostic or prognostic) and rationale for developing or validating the multivariable prediction model, including references to existing models.
- Specify the objectives, including whether the study describes the development or validation of the model, or both.
- Source of data
- Describe the study design or source of data (e.g., randomized trial, cohort, or registry data), separately for the development and validation data sets, if applicable.
- Specify the key study dates, including start of accrual; end of accrual; and, if applicable, end of follow-up.
- Participants
- Specify key elements of the study setting (e.g., primary care, secondary care, general population) including number and location of centres.
- Describe eligibility criteria for participants.
- Give details of treatments received, if relevant.
- Outcome
- Clearly define the outcome that is predicted by the prediction model, including how and when assessed.
- Report any actions to blind assessment of the outcome to be predicted.
- Predictors
- Clearly define all predictors used in developing the multivariable prediction model, including how and when they were measured.
- Report any actions to blind assessment of predictors for the outcome and other predictors.
- Sample size
- Explain how the study size was arrived at.
- Missing data
- Describe how missing data were handled (e.g., complete-case analysis, single imputation, multiple imputation) with details of any imputation method.
- Statistical analysis methods
- Describe how predictors were handled in the analyses.
- Specify type of model, all model-building procedures (including any predictor selection), and method for internal validation.
- For validation, describe how the predictions were calculated.
- Specify all measures used to assess model performance and, if relevant, to compare multiple models.
- Describe any model updating (e.g., recalibration) arising from the validation, if done.
- Risk groups
- Provide details on how risk groups were created, if done.
- Development vs. validation
- For validation, identify any differences from the development data in setting, eligibility criteria, outcome, and predictors.
- Participants
- Describe the flow of participants through the study, including the number of participants with and without the outcome and, if applicable, a summary of the follow-up time. A diagram may be helpful.
- Describe the characteristics of the participants (basic demographics, clinical features, available predictors), including the number of participants with missing data for predictors and outcome.
- For validation, show a comparison with the development data of the distribution of important variables (demographics, predictors and outcome).
- Model development
- Specify the number of participants and outcome events in each analysis.
- If done, report the unadjusted association between each candidate predictor and outcome.
- Model specification
- Present the full prediction model to allow predictions for individuals (i.e., all regression coefficients, and model intercept or baseline survival at a given time point).
- Explain how to use the prediction model.
- Model performance
- Report performance measures (with CIs) for the prediction model.
- Model updating
- If done, report the results from any model updating (i.e., model specification, model performance).
- Limitations
- Discuss any limitations of the study (such as nonrepresentative sample, few events per predictor, missing data).
- Interpretation
- For validation, discuss the results with reference to performance in the development data, and any other validation data.
- Give an overall interpretation of the results, considering objectives, limitations, results from similar studies, and other relevant evidence.
- Implications
- Discuss the potential clinical use of the model and implications for future research.
- Supplementary information
- Provide information about the availability of supplementary resources, such as study protocol, Web calculator, and data sets.
- Funding
- Give the source of funding and the role of the funders for the present study.