The clinical characteristics and survival
A total of 1109 patients were included in the primary cohort, and 6584 patients in the validation cohort. The age, sex, race, tumor location, T stage, N stage, TNM stage, tumor diameter, TI, mLN, mLNR, and the total LN were significantly different between the two cohorts (Table 1). In summary, the population in primary cohort were younger, had more male patients, was dominated by Asian patients, had more cancers located in the middle and upper third of stomach, had more patients in early stages, and had smaller tumor diameter compared to the validation cohort. Although the mLN was similar between the two cohorts, the mLNR was lower in the primary cohort due to the higher number of TLN. The 3-year and 5-year OS was significantly higher in the primary cohort than the validation cohort (all p<0.001) (Table 1) (Figure 1).
The univariate and multivariate analyses
The univariate analyses presented a significant correlation between the age, T stages, N stages, tumor diameter, TI, mLN, mLNR and the OS (all P<0.001). The multivariate analysis showed that the age, T stages, N stages and mLN were the independent prognostic factors for OS (Table 2).
The model selection
In the multivariate model, the “N3b” stage did not reached the statistical significance, and the hazard ratio (HR) was even lower than the “N3a” stage, which was inconsistent with the clinical impression obviously. The result might be explained by the limited number of “N3b” stage in the primary cohort (n=71, 6.4%). Besides, the case number of “T4b” was even lower (n=26, 2.3%), so we combined the stage “N3b” with “N3a” as “N3”, and the stage “T4b” with “T4a” as “T4” in the subsequent analyses (Table 1 and 2).
Apparently, the mLNR had a constant mathematical relationship with mLN and TLN, given the strong correlation between the two factors, the multivariate analysis might be biased by the collinearity between mLN and mLNR. On the other hand, since the TLN was documented to be the independent prognostic factor in multiple studies[4, 5], and was recommended to be above 30 for a favourable prognosis[6], we introduced the mLN and TLN in the model selection for clinical benefits.
Generally, the model was evaluated by its discriminative capability and the goodness of fit. The C-index and AIC was used as the assessment criteria for the two above features respectively. As the controlled model, the TNM stage model had a C-index of 0.717, and an AIC of 6662.988, which was inferior to other models. Interestingly, all other models had a same C-index of 0.744, however, the model (age + T stages + N stages + mLN + TLN) had the lowest AIC (6607.119), which implied a superiority in goodness of fit, in spite of the minor difference among the models (Table 3).
The nomogram development and external validation
The model containing age, T stages, N stages, mLN, and TLN was selected to develop the nomogram (Figure 2). The nomogram was used to predict the patient’s 3-year and 5-year OS by measuring all the variables on the “Points” scale and summing up all the scores, the projective point of the “Total points” on the “survival” scale could read the survival rate. The C-index of the nomogram was 0.744, which was close to the cutoff point of 0.75, and indicated a relatively good discriminative capability.
The calibration curves in the validation cohort demonstrated a good concordance with the nomogram-predicted survival either for 3-year or for 5-year (Figure 3). The C-index of the nomogram in validation cohort was 0.694 and 0.690 for 3-year and 5-year OS respectively. It was notable that, even there was a significant difference of survival rate between the primary cohort and the validation cohort, the nomogram still had a good accuracy in predicting survival in the range out of the primary cohort.