eMS | Pros | | | | Algorithms for central reading. Categorical score leads to easier algorithms for adjudication. Widely used over past 5 years.
|
Cons | Final score defined by worst lesion. Lacks precision for global burden of severity and extent of lesions. Lack of face validity Endoscopic features only post hoc defined. Limited spectrum at lower and higher spectrum of activity.
| | | Limited interobserver agreement. Inconsistencies between readers if insufficient washing of the mucosa. Data on impact of reader paradigms on eMS-based endpoints is missing.
|
UCEIS | Pros | | | | |
Cons | | Lack of ability to highlight segmental healing. Limited use in clinical trials. Development not focused at responsiveness.
| | Agreement and adjudication more complex for more granular scores as compared with categorical scores. Modest agreement on some lesions (eg, bleeding).
|
Rutgeerts | Pros | | | | |
Cons | | | Developed for end-to-end anastomoses, never validated for side-to-side anastomoses. Limited interobserver agreement.
| |
CDEIS | Pros | | | | |
Cons | Complexity. Exact weight of each variable to be better clarified. Unvalidated thresholds for remission and response. The definition of remission does not exclude the presence of ulcers.
| | | |
SES-CD | Pros | Developed and validated in order to precisely report disease activity. Possibility to easily exclude a given variable. Segmental and ulcer subscores can be calculated.
| | | Widely used in trials. Excellent inter-rater variability. Different reader algorithms available (fix or sliding scale for adjudication, paired reading …).
|
Cons | | | | Agreement and adjudication more complex for more granular scores as compared with categorical scores. No adjustment for missing segments due to sum score. Not developed for postoperative anatomy.
|