Table 1.

CRESCENDO (Creating a Clinical Prediction Model to predict Surgical Success in Endometriosis) data sets and their planned use during analysis^a.

Analysis step and primary models: treatment success in women with confirmed diagnosis		Secondary models: treatment success in women with suspected endometriosis
Model development
	Random 90% of BSGEb data set	MEDALc data set
Model performance
	Remaining 10% of BSGE data set	Bootstrapped samples of MEDAL data set or another appropriate method
External validation
	MEDAL data set	Laparoscopic uterosacral nerve ablation (control arm only)

^aDatabases containing pre-, intra-, and postoperative information of women with deep endometriosis (British Society of Gynaecological Endoscopy) or absent or superficial endometriosis (magnetic resonance imaging to establish diagnosis against laparoscopy or laparoscopic uterosacral nerve ablation).

^bBSGE: British Society of Gynaecological Endoscopy.

^cMEDAL: magnetic resonance imaging to establish diagnosis against laparoscopy.