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ORIGINAL ARTICLE

Immunohistochemical biomarkers and FDG uptake on PET/CT in head and neck squamous cell carcinoma

, , , , , , , , & show all
Pages 1408-1415 | Received 15 May 2015, Accepted 09 Jun 2015, Published online: 09 Aug 2015

Figures & data

Figure 1. IHC vs TSUVmax. Immunohistochemical stains versus TSUVmax. The proportion of positive cells have been binned in three groups, low expression (up to 1% positively stained cells) intermediate expression (> 1–33% positively stained cells) and high expression (> 33% positively stained cells) in order to have sufficient numbers in each stratum. p16 is scored dichotomously according to EORTCs p16 scoring guidelines [Citation18].

Figure 1. IHC vs TSUVmax. Immunohistochemical stains versus TSUVmax. The proportion of positive cells have been binned in three groups, low expression (up to 1% positively stained cells) intermediate expression (> 1–33% positively stained cells) and high expression (> 33% positively stained cells) in order to have sufficient numbers in each stratum. p16 is scored dichotomously according to EORTCs p16 scoring guidelines [Citation18].

Table I. Results of univariate and multivariate linear regression.

Figure 2. Proportion of p16 positive tumors. Logistic regression analysis of the probability of p16 positivity as a function of TSUVmax. Mean TSUVmax (with exact binomial confidence intervals) plotted for five 20 percentile groups based on TSUVmax. The knowledge of the TSUVmax of a tumor can be used to give a probability of the tumor being p16 positive. Logistic regression equation for p16: P = (exp(0.543+−0.108*TSUVmax))/(1 + exp(0.543+−0.108*TSUVmax)).

Figure 2. Proportion of p16 positive tumors. Logistic regression analysis of the probability of p16 positivity as a function of TSUVmax. Mean TSUVmax (with exact binomial confidence intervals) plotted for five 20 percentile groups based on TSUVmax. The knowledge of the TSUVmax of a tumor can be used to give a probability of the tumor being p16 positive. Logistic regression equation for p16: P = (exp(0.543+−0.108*TSUVmax))/(1 + exp(0.543+−0.108*TSUVmax)).

Figure 3. Proportion of Bcl-2 positive tumors. Logistic regression analysis of function with the probability of Bcl-2 positivity as a function of TSUVmax. Mean TSUVmax (with exact binomial confidence intervals) plotted for five 20 percentile groups based on TSUVmax. The knowledge of the TSUVmax of a tumor can be used to give a probability of the tumor being Bcl-2 positive. Logistic regression equation for Bcl-2: P = (exp(1.467+−0.103*TSUVmax))/(1 + exp(1.467+−0.103*TSUVmax)).

Figure 3. Proportion of Bcl-2 positive tumors. Logistic regression analysis of function with the probability of Bcl-2 positivity as a function of TSUVmax. Mean TSUVmax (with exact binomial confidence intervals) plotted for five 20 percentile groups based on TSUVmax. The knowledge of the TSUVmax of a tumor can be used to give a probability of the tumor being Bcl-2 positive. Logistic regression equation for Bcl-2: P = (exp(1.467+−0.103*TSUVmax))/(1 + exp(1.467+−0.103*TSUVmax)).
Supplemental material

ionc_a_1062539_sm6885.pdf

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