Machine Learning for the Prediction of Lymph Nodes Micrometastasis in Patients with Non-Small Cell Lung Cancer: A Comparative Analysis of Two Practical Prediction Models for Gross Target Volume Delineation

Figures & data

Table 1 Patients’ Demographics and Clinicopathological Characteristics

Variables	No. (%)
	(N=1524)
Age,year
Mean	46.8
SD	12.1
Sex
Male	1014 (66.5%)
Female	510 (33.5%)
Smoking
Yes	983 (64.5%)
No	541 (35.5%)
Site
Central type	633 (41.5%)
Peripheral type	891 (58.5%)
BMI,kg/m^2
>27	407 (26.7%)
≤27	1117 (73.3%)
Differentiation
Poorly differentiation	180 (11.8%)
Moderately differentiation	839 (55.1%)
Highly differentiation	505 (33.1%)
Pathology
Squamous carcinoma	946 (62.1%)
Adenocarcinoma	539 (35.4%)
Others	39 (2.6%)
SUVmax
≤8	1175 (77.1%)
>8	349 (22.9%)
T stage
T1	278 (18.2%)
T2	1121 (73.6%)
T3	87 (5.7%)
T4	38 (2.5%)
Tumor Diameter,cm
>3	481 (31.6%)
≤3	1043 (68.4%)
Vascular invasion
Yes	876 (57.5%)
No	648 (42.5%)
Pulmonary membrane invasion
Yes	433 (28.4%)
No	1091 (71.6%)
Clustered lymph nodes
Yes	893 (58.6%)
No	631 (41.4%)
Maximum short diameter of lymph nodes
>0.6	255 (16.7%)
≤0.6	1269 (83.3%)
KRAS mutation
Yes	176 (11.5%)
No	1348 (88.5%)
EGFR mutation
Yes	420 (27.6%)
No	1104 (72.4%)

Abbreviations: SD, Standard deviation; BMI, Body mass index; SUVmax, Maximum standard uptake value; T stage, tumor node metastasis classification (AJCC7th); AJCC, American Joint Committee on Cancer.

Figure 1 Correlation matrix of candidate features. Values in this matrix demonstrated the correlation coefficient of each corresponding variable.

Notes: Different colors represented the strength of correlation, in which dark blue and red indicated strong positive and negative relationships, respectively.

Abbreviations: Differentiation, degree of tumor differentiation; Pathology, Squamous cell, adenocarcinoma, or other types; SUVmax, Maximum standard uptake value; Site, Tumor site; BMI, Body Mass Index; Diameter, Tumor diameter; Vascular, Vascular invasion; Pulmonary, Pulmonary membrane invasion; Cluster, Clustered lymph nodes; Lymph, Maximum short diameter of the lymph node; T stage, tumor node metastasis classification (AJCC7th); AJCC, American Joint Committee on Cancer.

Figure 2 Random forest model. (A) The candidate factors associated with micrometastasis of lymph nodes were ordered according to the mean decreased Gini index. (B) Relationship of dynamic changes between the prediction error and the number of decision trees. (C) Performance of the prediction model with increasing numbers of features in the tenfold cross-validation.

Table 2 The Predictive Performances of Different Models Associated with Micrometastasis of Lymph Nodes

GL Model	Multivariate Analysis		Discrimination
	OR(95% CI)	P-value	Brier	R^2	C-Index	AIC
Model1
Sex (Male vs Female)	0.94 (0.87–1.02)	<0.01
Age*,y	1.11 (0.99–1.24)	0.11
Diameter,cm (≤3cm vs>3)	1.11 (0.99–1.24)	0.06
Vascular invasion (Yes vs No)	0.31 (0.24–0.39)	<0.01
Differentiation (Moderate vs High)	0.97 (0.85–1.10)	<0.01	0.05	0.06	0.681	328.60
(Poorly vs High)	1.55 (1.39–1.73)	<0.01
Pulmonary membrane invasion (Yes vs No)	2.67 (1.95–3.67)	<0.01
EGFR (Positive vs Negative)	1.01 (0.89–1.16)	0.83
SUVmax (≤8.0 vs>8.0)	2.59 (2.25–2.98)	<0.01
Model2
Vascular invasion (Yes vs No)	0.31 (0.25–0.40)	<0.01
Differentiation (Moderate vs High)	0.97 (0.85–1.10)	<0.01
(Poorly vs High)	1.54 (1.39–1.72)	<0.01
Tumor site (Central vs Peripheral)	2.69 (1.96–3.69)	<0.01	0.05	0.06	0.686	327.50
EGFR (Positive vs Negative)	1.07 (0.94–1.22)	0.30
SUVmax (≤8.0 vs>8.0)	2.49 (2.18–2.84)	<0.01
Model3
Differentiation (Moderate vs High)	0.92 (0.96–0.99)	<0.01
(Poorly vs High)	0.31 (0.24–0.39)	0.03
Vascular invasion (Yes vs No)	0.97 (0.85–1.10)	<0.01
Pulmonary membrane invasion (Yes vs No)	1.55 (1.39–1.72)	<0.01	0.04	0.07	0.685	330.60
SUVmax (≤8.0 vs>8.0)	2.68 (1.96–3.68)	<0.01
Diameter, cm (≤3cm vs >3)	2.62 (2.28–3.02)	<0.01

Note: *Continuous variable.

Abbreviations: AIC, Akaike information criterion; GL model, generalized linear model; OR, odds ratio; 95% CI, 95% confidence level; SUVmax, Maximum standard uptake value.

Figure 3 Validation and comparison of the predictive model. The training set (A) and testing set (B) associated with micrometastasis of lymph nodes were measured via the RF model. The comparison of the ROC curve of the RF model (C) and GL model (D).

Abbreviations: ROC, Receiver operating characteristic; AUC, The area under the curve.