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. Author manuscript; available in PMC: 2017 Jun 1.
Published in final edited form as: Cancer Prev Res (Phila). 2016 Mar 28;9(6):445–455. doi: 10.1158/1940-6207.CAPR-15-0200

Table 3.

Prediction models for oral cancer

Part A: Logistic Regression, all patients Odds Ratio (95%CI) P AUC Rescaled R2
Univariate models (150 cases / 150 controls)
    log2 solCD44 2.036 (1.552, 2.671) <.0001 0.681 0.137
    Protein 2.159 (1.288, 3.617) 0.003 0.590 0.042
Multivariable model 1(149 cases/148 controls)
    log2 solCD44 2.684 (1.797, 4.010) <.0001 0.763 0.276
    Protein 0.646 (0.301, 1.386) 0.262
Part B: Logistic Regression stratified by HPV status
HPV negative (48 cases / 150 controls)
Univariate
    Log2 solCD44 2.311 (1.561, 3.422) <.0001 0.689 0.146
    Protein 1.838 (0.888, 3.807) 0.101 0.562 0.020
Multivariable model2 (48 cases / 148 controls):
    log2 solCD44 4.017 (2.124, 7.597) <.0001 0.771 0.275
    Protein 0.179 (0.052, 0.620) 0.006
HPV positive (31 cases / 150 controls)
Univariate
    Log2 solCD44 2.001 (1.291, 3.102) 0.002 0.667 0.096
    Protein 1.882 (0.789, 4.492) 0.154 0.567 0.018
Multivariable model 3 (148 controls):
    log2 solCD44 3.079 (1.486, 6.378) 0.003 0.773 0.221
    Protein 0.384 (0.080, 1.833) 0.230
Part C: Logistic Regression Analysis of Risk Groups derived by Multivariate Recursive Partitioning Univariate Model4 of Risk Groups based on CD44 and protein levels
Risk Level
(n = case + control) 		SolCD44(ng/ml)
(level description)		 Protein
(mg/ml)		 Odds Ratio (95%CI) Prediction P AUC Rescaled
R2
Low
(102 = 29 + 73)		 <2.22
(low)		 <1.23
(low-medium)		 Reference Control 0.722 0.227
Medium
(116 = 54 + 62)		 ≥2.22 & <5.33
(medium)		 ≥0.558
(medium-high)		 2.192 (1.247, 3.854) Control 0.006
High
(5 = 4 + 1)		 <2.22
(low)		 ≥1.23
(high)		 10.069 (1.079, 93.93) Case 0.043
High
(20 = 16 + 4)		 ≥2.22 & <5.33
(medium)		 <0.558
(low)		 10.069 (3.103, 32.672) Case 0.0001
High
(57 = 47 + 10)		 ≥5.33
(high)		 -- 11.830 (5.279, 26.508) Case <.0001
Multivariable Model5 of Risk Groups based on CD44 and protein levels
Risk Level (n) SolCD44 Protein Odds Ratio (95%CI) Prediction P AUC Rescaled
R2
Low
(102)		 <2.22
(low)		 <1.23
(low-medium)		 Reference Control 0.790 0.325
Medium
(116)		 ≥2.22 & <5.33
(medium)		 ≥0.558
(medium-high)		 2.755 (1.483, 5.117) Control 0.001
High
(5)		 <2.22
(low)		 ≥1.23
(high)		 5.905 (0.591, 59.053) Case 0.131
High
(20)		 ≥2.22 & <5.33
(medium)		 <0.558
(low)		 11.860 (3.312, 42.472) Case <.0001
High
(57)		 ≥5.33
(high)		 -- 14.489 (5.973, 35.145) Case <.0001
SES High vs. low 0.577 (0.304, 1.094) 0.092
White Non-Hispanic vs Black at age <60 7.885 (2.372, 26.206)
White Hispanic vs Black at age <60 1.767 (0.636, 4.907)
White Non-Hispanic vs Black at age ≥60 0.799 (0.216, 2.956)
White Hispanic vs Black at age ≥60 0.382 (0.124, 1.175)
Age ≥60 vs <60 in Black 3.099 (0.838, 11.457)
Age ≥60 vs <60 in White Non-Hispanic 0.314 (0.111, 0.892)
Age ≥60 vs <60 in White Hispanic 0.669 (0.324, 1.383)
Alcohol Ever vs Never in Male 1.615 (0.713, 3.660)
Alcohol Ever vs Never in Female 0.202 (0.056, 0.726)
Male vs Female in alcohol=Never 0.216 (0.062, 0.757)
Male vs Female in alcohol=Ever 1.723 (0.695, 4.273)

AUC: area under the ROC curve. Rescaled R2: coefficient of determination measured the dispersion explained by model. Odds ratios: 1-unit increase for continuous variables log2 CD44, protein, and age, unless specified categories; race/ethnicity (WNH and Black vs. WH), gender (Male v. Female), smoking and alcohol (Ever v. Never), and SES (high vs. low).

1

Adjusted for age (p=0.132), race/ethnicity (p=0.004), age×race/ethnicity (p=0.006), gender (p=0.030), alcohol (p=0.032), gender×alcohol (p=0.020), smoking (p=0.527), and SES (p=0.042). Model “markers + covariates” (AUC=0.763) provided significantly better prediction than the reduced model excluding both markers (AUC=0.686) and only including potential risk factors (p=0.003), indicating that the markers aid prediction over and above prediction provided by knowledge of risk factors.

2

Adjusted for age (p=0.020), gender (p=0.009), age×gender (p=0.008), race/ethnicity (p=0.740), alcohol (p=0.183), smoking (p=0.487), and SES (p=0.047).

3

Adjusted for age (p=0.052), gender (p=0.104), age ×gender (p=0.096), race/ethnicity (p=0.298), alcohol (p=0.537), smoking (p=0.131), and SES (p=0.070).

4

AUC=0.722 for risk group model (based on CD44 and protein) is significantly different from AUC =0.681 for univariate model log2 solCD44 (p=0.025).

5

Logistic regression model included CD44-protein risk groups (5 categories, p<0.0001), age (≥60 vs. <60, p=0.090), gender (p=0.017), race/ethnicity (p=0.001), alcohol (p=0.014), SES (p=0.092), and interaction age×race/ethnicity (p=0.029) and gender×alcohol (p=0.007). Smoking (ever vs. never, p=0.700) and teeth removed (6 or more or all vs. 5 or less, p=0.485) were tested for inclusion into model (AUC=0.791); they were removed since their inclusion did not improve model fit.