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. 2013 Mar;15(2):196–209. doi: 10.1016/j.jmoldx.2012.09.006

Table 4.

Cox proportional hazards analyses testing the count of CNV as a predictive variable for TTT

Independent segments (n=14)
Independent CLL-specific segments (n=3)
HR 95% CI P variable P overall model (Likelihood ratio test) HR 95% CI P variable P overall model (Likelihood ratio test)
Count of CNV as a continuous variable 2.1 1.7–2.7 6.1 × 10−12 2.1 × 10−12 1.5 1.2–1.9 0.0005 0.0006

Count of CNV as a categorical variable 5.9 × 10−13 0.0023
 1 CNV 1.9 0.9–4.2 0.0907 1.6 1.1–2.2 0.0131
 2 CNV 3.6 1.6–7.9 0.0014 2.2 1.3–3.7 0.0022
 3 CNV 9.5 4.2–21.7 9.1 × 10−8 NA NA NA

Count of CNV as a continuous variable compared to unfavorable cytogenetics 2.3 × -10−11 1.1 × 10−12 0.0014 2.6x10−5
 Count of CNV 2.1 1.67–2.59 6.7 × 10−11 1.5 1.2–1.9 0.0010
 Del11q22 and/or del17p13 1.6 1.04–2.40 0.0323 1.9 1.2–2.8 0.0032

Count of CNV as a categorical variable compared to known prognostic variables 1.7 × 10−7 5.4 × 10−14 0.0709 1.3 × 10−6
 1 CNV 1.8 0.8–3.9 0.1478 1.3 0.9–1.9 0.1424
 2 CNV 2.9 1.3–6.6 0.0103 1.8 1.1–3.0 0.0262
 ≥3 CNV 7.5 3.1–17.8 5.8 × 10−6 NA NA NA
 Unmutated IGHV status 1.9 1.3–2.7 0.0013 2.2 1.5–3.2 2.0 × 10−5
 Del11q22 and/or dell7p13 1.2 0.8–1.8 0.3899 1.5 1.0–2.2 0.0820
 Lambda light chain use 1.1 0.78–1.6 0.5507 1.4 1.0–2.0 0.0526

CI, confidence interval; HR, hazard ratio; n, number of patients; NA, not applicable; p, p-value.

P-values for the significance of addition of the CNV count to clinical variables was tested using an analysis of deviance and is based on the chi- square statistic.