Establishment and application of three predictive models of anastomotic leakage after rectal cancer sphincter-preserving surgery

Table 1 Single factor analysis of anastomotic leakage, n (%)

Patient characteristics	AL (n = 51)	No AL (n = 446)	t/χ²	P value
Sex			6.921	0.009
Male	33 (64.71)	244 (54.71)
Female	18 (35.29)	202 (45.29)
Age, year (mean ± SD)	60.98 ± 10.83	59.27 ± 10.76	1.073	0.284
BMI, kg/m² (mean ± SD)	22.30 ± 2.91	21.45 ± 3.06	1.896	0.058
Diabetes mellitus			14.164	< 0.001
No	21 (41.18)	302 (67.71)
Yes	30 (58.82)	144 (32.29)
Hypertension			0.232	0.630
No	16 (31.37)	155 (34.75)
Yes	35 (68.63)	291 (65.25)
Smoking history			6.970	0.008
No	14 (27.45)	209 (46.86)
Yes	37 (72.55)	237 (53.14)
Neoadjuvant treatment			7.973	0.005
No	16 (31.37)	233 (52.24)
Yes	35 (68.63)	213 (47.76)
Hb, g/L (mean ± SD)	135.60 ± 10.46	136.75 ± 10.41	0.746	0.456
Alb, g/L (mean ± SD)	33.23 ± 6.59	37.13 ± 7.25	3.664	< 0.001
Tumor size, cm (mean ± SD)	4.73 ± 1.22	3.42 ± 1.26	7.009	< 0.001
Tumor location, cm (mean ± SD)	4.32 ± 1.28	6.13 ± 1.30	9.378	< 0.001
TNM stage			0.010	0.995
I	32 (62.75)	281 (63.00)
II	12 (23.53)	106 (23.77)
III	7 (13.72)	59 (13.23)
ASA score			0.289	0.866
I	34 (66.67)	282 (63.23)
II	12 (23.53)	111 (24.89)
III	5 (9.80)	53 (11.88)
Surgical approach			1.676	0.195
Open	13 (25.49)	154 (34.53)
Laparoscopic	38 (74.51)	292 (65.47)
Operation time, min (mean ± SD)	182.19 ± 6.25	181.87 ± 5.79	0.378	0.705
Blood loss, mL (mean ± SD)	230.45 ± 17.62	232.74 ± 20.58	0.761	0.447

AL: Anastomotic leakage; Alb: Albumin; ASA: American Society of Anesthesiologists; BMI: Body mass index; Hb: Hemoglobin; TNM: Tumor-node-metastasis.

Table 2 Assignment of each factor

Factor	Assignment
Sex	Female = 0, male = 1
Diabetes mellitus	No = 0, yes = 1
Smoking history	No = 0, yes = 1
Neoadjuvant treatment	No = 0, yes = 1
Albumin level	Enter the original value
Tumor size	Enter the original value
Tumor location	Enter the original value

Table 3 Analysis of influencing factors of anastomotic leakage

Factor	β	SE	Wald χ²	P value	OR (95%CI)
Sex	1.271	0.429	8.778	0.003	3.656 (1.538-8.264)
Diabetes mellitus	1.735	0.427	16.504	< 0.001	5.669 (2.455-13.092)
Smoking history	1.758	0.967	3.309	0.069	5.801 (0.873-38.572)
Neoadjuvant treatment	-0.947	0.940	1.015	0.314	0.388 (0.062-2.448)
Albumin level	-0.108	0.030	12.627	< 0.001	0.898 (0.846-0.953)
Tumor size	0.957	0.177	29.204	< 0.001	2.604 (1.840-3.684)
Tumor location	-1.300	0.212	37.699	< 0.001	0.272 (0.180-0.413)

CI: Confidence interval; OR: Odds ratio.

Table 4 Prediction efficiency of the three model training sets

Model	Sensitivity	Specificity	Accuracy	Recall	Precision	AUC (95%CI)
Nomogram	0.745	0.966	0.936	0.987	0.946	0.922 (0.883-0.961)
Decision tree	0.833	0.862	0.951	0.994	0.955	0.919 (0.863-0.975)
Random forest	1.000	1.000	0.951	0.994	0.955	1.000 (1.000-1.000)

AUC: Area under the receiver operating characteristic curve; CI: Confidence interval.

Table 5 Prediction efficiency of the three model validation sets

Model	Sensitivity	Specificity	Accuracy	Recall	Precision	AUC (95%CI)
Nomogram	0.867	0.909	0.927	1.000	0.921	0.950 (0.908-0.992)
Decision tree	0.836	0.864	0.951	0.994	0.955	0.882 (0.797-0.968)
Random forest	0.984	0.727	0.893	1.000	0.889	0.934 (0.883-0.985)

AUC: Area under the receiver operating characteristic curve; CI: Confidence interval.