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Table 5 Characteristics of the studies used to inform the developed prognostic model

From: Development, validation and clinical usefulness of a prognostic model for relapse in relapsing-remitting multiple sclerosis

Study

Design

Sample size (EPV)

Outcome

Missing data

Discrimination

Presentation of the model

Model

Calibration

Validation

PHeld et al. [9]

Placebo arms of clinical trials

Multicentre

n = 821

(NA)

Relapse rate

Complete case analysis

Discrimination: c-statistic NA for continuous outcome

Calibration: absent.

Internal validation: split-sample

Table

Prognostic model

Kalincik et al. [35]

Cohort study

n = 8513

Treatment response for relapse frequency

Mentioned: Values of the principal components can be estimated even for patients with incomplete data

Accuracy and internal validity reported (moderate for relapse rate at 2 years)

Internal validation:

in a separate, non-overlapping MSBase cohort. External validation:

2945 patients from the Swedish Multiple Sclerosis Registry

Table of principal components

Prediction model

Liquori et al. [10]

Cohort (R)

Single centre

n = 127

(NA)

Relapse rate

Complete case analysis

Overall performance reported R2

Calibration: absent

Validation: absent

NA

Prognostic model

Pellegrini et al. [34]

RCT

n = 2099

Treatment response to annualized relapse rate

Complete case analysis

Performance measure of area under the AD(c) curve shown in the graph

Calibration absent

Internal validation:

Splitting of the training dataset into two subsets (50%/50%)

External validation:

Independent RCT

Table

Prediction model

Signori et al. [36]

All published randomized clinical trials in RRMS reporting a subgroup analysis

Six trials 6693 RRMS patients

Treatment response to annualized relapse rate

Not relevant

Not relevant

Not relevant

Subgroups responsive to treatments

Sormani et al. [7]

Placebo arm of RCT

Multicentre

n = 539

(insufficient data reported)

Number of relapses at 9 months

Complete case analysis

Discrimination: absent

Calibration: absent

Internal validation: absent

Mathematical formula

Prognostic model

Stühler et al. [33]

Real-world data

n = 25000

Treatment response to number of relapses

Complete case analysis

Discrimination:

c-statistic (0.65)

Calibration:

Calibration plot

Internal validation:

1)10-fold cross-validation, 2)leave-one-site-out cross-validation, and 3)excluding test set

Table

Prediction model