Table 3 Assessing the prediction performance of the TNM stage, LncRNA classifier and nomogram in training set and validation set.

From: An integrated nomogram combining lncRNAs classifier and clinicopathologic factors to predict the recurrence of head and neck squamous cell carcinoma

Cohort

Model

Homogeneity monotonicity and discriminatory ability

Akaike information criterion (AIC)****

Likelihood ratio (LR) test*

Linear trend χ2 test**

C-index (95% CI)***

Training set

TNM stage

4.5

4.3

0.57 (0.52–0.59)

593

LncRNA classifier

32

30.5

0.67 (0.64–0.70)

561

Nomogram

58.1

62.7

0.76 (0.72–0.79)

541

Validation set

TNM stage

5.9

4.8

0.55 (0.52–0.58)

711

LncRNA

classifier

20.4

20.4

0.63 (0.61–0.65)

689

Nomogram

58.1

69.5

0.74 (0.71–0.76)

661

  1. Assessing the prognostic performance of the TNM stage, lncRNAs classifier and nomogram.
  2. *Higher homogeneity likelihood ratio indicates a smaller difference within the staging system, it means better homogeneity.
  3. **Higher discriminatory ability linear trend indicates a higher linear trend between staging system, it means better discriminatory ability and gradient monotonicity.
  4. ***A higher c-index means better discriminatory ability.
  5. ****Smaller AIC values indicate better optimistic prognostic stratification.
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