The Combined Performance of ADC, CSF CXC Chemokine Ligand 13, and CSF Interleukin 10 in the Diagnosis of Central Nervous System Lymphoma

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Fig 1.
An axial postgadolinium T1-weighted MR image (A) and a coregistered axial ADC map (B) demonstrate manual contouring of the contrast-enhancing CNSL on this section, which allows the measurement of ADCavg. This is performed on every section of the contrast-enhancing tumor.
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Fig 2.
Boxplots of ADCavg, CSF CXCL-13, and CSF IL-10. ADCavg is statistically significantly lower, and CSF CXCL-13 and IL-10 are statistically significantly higher in patients with CNSL (P < .001).
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Fig 3.
ROC curves of ADCavg (A), CXCL-13 (B), IL-10 (C), and ADCavg with CXCL-13 and IL-10 (D). All ROCs are statistically significant (P < .001). Diagnostic performance measured by AUC is statistically significantly superior in the multiple-variable model (D) compared with the single-variable models (A–C).

Table 2:

Variables for the CNSL and non-CNSL groups with P values^{^a}

Factor	Variable Means by Patient Group
Factor	CNSL (n = 43)	Non-CNSL (n = 44)	P Value
ADCavg	864.81	1071.65	<.001
95% CI	(832.50–897.13)	(981.23–1162.04)
CXCL-13	2960.49	72.54	<.001
95% CI	(1124.96–4796.01)	(9.02–136.05)
IL-10	557.48	5.93	<.001
95% CI	(167.49–947.47)	(3.42–8.43)

↵a The patients with CNSL had lower ADC values and higher CSF CXCL-13 and IL-10 values than those without CNSL.

Table 3:

Results of individual and multiple-variable ROCs for the diagnosis of CNSL^{^a}

Factor and P Value	ROC Results with Optimized Thresholds
Factor and P Value	AUC (95% CI)	Maximum Youden Index J	Threshold Sensitivity/Specificity	Threshold ± Likelihood Ratios	Threshold PPV/NPV
ADCavg (P < .001)	0.739 (0.634–0.827)	0.521 at ≤971	90.70/61.36	2.35/0.15	69.64/87.10
CXCL-13 (P < .001)	0.832 (0.737–0.904)	0.677 at <106.0	76.74/90.91	8.44/0.26	89.19/80.00
IL-10 (P < .001)	0.792 (0.692–0.872)	0.583 at >21.77	62.79/95.45	13.81/0.39	93.10/72.41
ADCavg, CXCL-13, IL-10 (P < .001)	0.928 (0.851–0.972)	0.723 at probability of >0.527	81.40/90.91	11.26/0.25	89.74/83.33

Note:—NPV indicates negative predictive value; PPV, positive predictive value.
↵a All ROC curves were statistically significant. Optimized thresholds were selected by using the maximum Youden Index J, the maximum vertical distance from the AUC = 0.5 null hypothesis line (sensitivity [1-specificity]). PPV and NPV should be interpreted with caution because they are highly dependent on the prevalence of the disease in the tested population, and as CSF testing becomes more common, this may not be reflective of our study population.

Table 4:

Sensitivities and corresponding threshold values from the ROC analysis for a set specificity of 95%^{^a}

Factor	Sensitivity at Set 95% Specificity (95% CI)	Threshold Value for 95% Specificity
ADCavg	0.00 (0.00–2.33)	≤598.2
CXCL-13	51.16 (18.60–79.07)	>262.82
IL-10	62.79 (48.84–79.07)	>20.65
ADCavg, CXCL-13, IL-10	72.09 (55.81–86.05)	Probability of >.616

↵a ADCavg alone was essentially unable to reach a specificity of 95% (the sensitivity at the calculated threshold is 0%); however, with the addition of the CSF variables in the combined model, we can reach a specificity of 95% with a sensitivity of 72.09%. The highest sensitivity at 95% specificity is reached in the multiple-variable model.