Optimizing prediction models for pancreatic fistula after pancreatectomy: Current status and future perspectives

Table 8 Postoperative pancreatic fistula prediction models after distal pancreatectomy

Ref.	Year	Country	Center	Design cohort	Study period	CR-POPF (%)	Variables3	AUC (95%CI)	Validation
Ecker et al[25]	2019	Multinational	Multi	2026	2001-2016	15.1	(1)(2)(6)(A)(G)(H)(e)	0.654 (0.620-0.688)
Guilbaud et al[79]	2021	France	Multi1	922	2017-2019	21.2	(a)(b)	0.762 (0.640-0.885)
Rollin et al[90]	2022	France	Single	103	2015-2019	32	(2)(8)(B)(c)	0.83 (0.75-0.92)
Nassour et al[91]	2022	USA	Nationwide	692	2014-2018	15.9	(1)(B)(D)(b)	0.731 (0.685-0.796)	Internal
							(1)(B)(b)(d)	0.791 (0.742-0.836)
Bonsdorff et al[89]	2022	Multinational	Multi	266	2013-2021	19.5	(3)(8)(F)	0.904 (0.855-0.949)	Internal-external
He et al[92]	2023	China	Single	115	2005-2020	33	(2)(6)(8)(E)	0.842 (0.762-0.921)
Pecorelli et al[26]	2023	Italy	Single	220	2016-2019	33.6	(2)(3)(4)(5)	0.651 (0.58-0.73)	Internal
							(2)(9)(10)(C)	0.725 (0.66-0.79)
							(5)(11)(C)	0.733 (0.64-0.80)
De Pastena et al[27]	2023	Multinational	Multi1	339	2014-2016	23	(7)(8)	0.731 (0.70-0.76)	Internal-external
							(2)(7)(8)(B)(E)	0.851 (0.80-0.90)	Internal

¹Indicates prospective studies, others are retrospective studies.

²Including patients underwent pancreaticoduodenectomy.

³From Table 2.

AUC: Area under the curve; CI: Confidence interval; CR-POPF: Clinically relevant postoperative pancreatic fistula.