RuleFit-Based Nomogram Using Inflammatory Indicators for Predicting Survival in Nasopharyngeal Carcinoma, a Bi-Center Study

Figures & data

Figure 1 Flowchart of the study procedures.

Table 1 Clinical Characteristics of Patients in the Primary and Validation Cohorts

Characteristics	Total	Primary	Validation	P-value
	(N=1706)	(N=1320)	(N=386)
Age (years)				<0.001*
Median (IQR)	46 (38–54)	45 (38–54)	47 (40–57)
Sex				0.385
Male	1261 (73.9%)	969 (73.4%)	292 (75.6%)
Female	445 (26.1%)	351 (26.6%)	94 (24.4%)
Histologic type				<0.001*
WHO type 1/2	63 (3.8%)	63 (4.8%)	0 (0.0%)
WHO type 3	1643 (96.2%)	1257 (95.2%)	386 (100.0%)
EBV DNA, 10^3 copies/mL				<0.001*
<1	806 (47.2%)	583 (44.2%)	223 (57.8%)
<10	493 (28.9%)	339 (25.7%)	154 (39.9%)
≥10	407 (23.9%)	398 (30.2%)	9 (2.3%)
T classification				0.204
T1	434 (25.4%)	331 (25.1%)	103 (26.7%)
T2	206 (12.1%)	153 (11.6%)	53 (13.7%)
T3	665 (39.0%)	532 (40.3%)	133 (34.5%)
T4	401 (23.5%)	304 (23.0%)	97 (25.1%)
N classification				0.064
N0	341 (20.0%)	278 (21.1%)	63 (16.3%)
N1	969 (56.8%)	752 (57.0%)	217 (56.2%)
N2	281 (16.5%)	205 (15.5%)	76 (19.7%)
N3	115 (6.7%)	85 (6.4%)	30 (7.8%)
Clinical stage				0.297
I	144 (8.4%)	115 (8.7%)	29 (7.5%)
II	377 (22.1%)	288 (21.8%)	89 (23.1%)
III	691 (40.5%)	547 (41.4%)	144 (37.3%)
IV	494 (29.0%)	370 (28.0%)	124 (32.1%)
Treatment				0.020*
RT alone	211 (12.4%)	155 (11.7%)	56 (14.5%)
CCRT	622 (36.5%)	504 (38.2%)	118 (30.6%)
IC + CCRT	872 (51.1%)	660 (50.0%)	212 (54.9%)

Notes: Data are presented as numbers with percentages or medians with interquartile ranges. Histologic type was based on basing on 2005 World Health Organization classification of tumors. T, N and clinical stage was based on the 8th American Joint Cancer Committee TNM staging system. *P-value <0.05, P values were calculated by Fisher’s exact test or chi-square test.

Abbreviations: IQR, interquartile range; WHO, World Health Organization; EBV, Epstein-Barr virus; RT, radiotherapy; CCRT, concurrent chemoradiotherapy; IC, induction chemotherapy.

Table 2 C-Index of Different Modules in the Primary and Validation Cohorts

Models	Primary Cohort		Validation Cohort
	C-Index	P-value	C-Index	P-value
OS:
Final model	0.769 (0.735~0.802)	Reference	0.752 (0.697~0.808)	Reference
RuleFit model	0.776 (0.742~0.810)	<0.001	0.734 (0.679~0.790)	0.124
AutoML model	0.963 (0.956~0.970)	<0.001	0.605 (0.542~0.668)	<0.001
Lin Quan’s model	0.746 (0.711~0.782)	<0.001	0.702 (0.642~0.762)	<0.001
Lasso model	0.754 (0.719~0.789)	0.041	0.686 (0.623~0.750)	<0.001
Clinical model	0.747 (0.711~0.782)	<0.001	0.715 (0.655~0.775)	<0.001
Base model	0.717 (0.682~0.753)	<0.001	0.688 (0.624~0.752)	<0.001
DMFS:
Final model	0.734 (0.698~0.770)	Reference	0.725 (0.666~0.784)	Reference
RuleFit model	0.741 (0.705~0.777)	0.015	0.703 (0.641~0.765)	0.169
AutoML model	0.827 (0.795~0.860)	<0.001	0.619 (0.549~0.69)	<0.001
Lin Quan’s model	0.715 (0.679~0.751)	0.021	0.697 (0.633~0.762)	0.145
Lasso model	0.716 (0.679~0.752)	0.002	0.689 (0.623~0.754)	0.010
Clinical model	0.713 (0.676~0.749)	0.001	0.695 (0.631~0.759)	0.008
Base model	0.687 (0.649~0.726)	<0.001	0.704 (0.639~0.770)	0.006
LRFS:
Final model	0.649 (0.599~0.700)	Reference	0.633 (0.543~0.724)	Reference
RuleFit model	0.647 (0.595~0.698)	0.178	0.622 (0.535~0.709)	0.865
AutoML model	0.733 (0.683~0.782)	<0.001	0.566 (0.475~0.658)	0.008
Lin Quan’s model	0.647 (0.598~0.696)	0.696	0.587 (0.495~0.678)	0.031
Lasso model	0.649 (0.599~0.698)	0.982	0.614 (0.529~0.700)	0.128
Clinical model	0.645 (0.596~0.694)	0.224	0.596 (0.507~0.686)	0.017
Base model	0.645 (0.596~0.694)	0.224	0.596 (0.507~0.686)	0.017
PFS:
Final model	0.691 (0.660~0.722)	Reference	0.701 (0.647~0.754)	Reference
RuleFit model	0.692 (0.661~0.723)	0.005	0.683 (0.629~0.737)	0.154
AutoML model	0.798 (0.770~0.826)	<0.001	0.587 (0.53~0.644)	<0.001
Lin Quan’s model	0.678 (0.647~0.709)	0.005	0.677 (0.622~0.733)	0.003
Lasso model	0.679 (0.648~0.710)	0.002	0.662 (0.605~0.719)	0.001
Clinical model	0.677 (0.646~0.708)	<0.001	0.674 (0.618~0.729)	0.001
Base model	0.665 (0.634~0.695)	<0.001	0.663 (0.606~0.720)	<0.001

Note: Clinical models were contributed by clinical predictors determined by univariate analysis (Table S2).

Abbreviations: OS, overall survival; DMFS, distant metastasis-free survival; LRFS, locoregional relapse-free survival; PFS, progression-free survival.

Figure 2 Nomogram of final model.

Abbreviations: OS, overall survival; EBV, Epstein-Barr virus.

Figure 3 Decision curve analysis of the 5-year overall survival predictions.

Notes: Horizontal and axis represent the mortality risk and net benefit, respectively. The curves of models are above on lines of extreme assumptions, indicating the net benefit.

Figure 4 Risk stratification in final model and AJCC stage.

Notes: AJCC stage I, II were thought low-risk and III, IV stage were high-risk. (A and D) groups represent patients with same high- or low-risk stratification in AJCC stage and final model. (B) group was predicted low risk by final model but high risk by AJCC, and C group was predicted high risk by final model but low risk by AJCC.

Abbreviations: OS, overall survival; AJCC, American Joint Cancer Committee.

Figure 5 A case of NPC patients using the network-based predictor for prognosis predicting.

Notes: Overall survival was set as the endpoint in app. Detailed instruction for replicated blood scores calculation was uploaded here to facilitate clinical and patient usage (https://github.com/trackse/bloodscore).

Abbreviations: OS, overall survival; EBV, Epstein-Barr virus.