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Erschienen in:
01.05.2018 | Original Article
Nomograms predicting survival of patients with unresectable or metastatic gastric cancer who receive combination cytotoxic chemotherapy as first-line treatment
Erschienen in: Gastric Cancer | Ausgabe 3/2018
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Background
Some clinicopathological variables are known to influence the survival of patients with advanced gastric cancer. A comprehensive model based on these factors is needed for prediction of an individual’s survival and appropriate patient counseling.
Methods
A nomogram for predicting 1-year survival in patients with advanced gastric cancer in the palliative chemotherapy setting was developed using clinicopathological data from 949 patients with unresectable or metastatic gastric cancer who had received first-line doublet cytotoxic chemotherapy from 2001 to 2006 at the National Cancer Center, Korea (Baseline Nomogram). For 836 patients whose initial response to chemotherapy is known, another nomogram (ChemoResponse-based Nomogram) was constructed using the response to chemotherapy as additional variable. Nomogram performance in terms of discrimination and calibration ability was evaluated using the C statistic and Hosmer–Lemeshow-type χ
2 statistics.
Results
Two different nomograms were developed and subjected to internal validation. The baseline nomogram incorporated 13 baseline clinicopathological variables, whereas the chemoresponse-based nomogram was composed of 11 variables including initial response to chemotherapy. Internal validation revealed good performance of the two nomograms in discrimination: C statistics = 0.656 (95% confidence interval, 0.628–0.673) for the baseline and 0.718 (95% confidence interval, 0.694–0.741) for the chemoresponse-based nomogram, which showed significantly better discrimination performance than the baseline nomogram (Z statistics = 3.74, p < 0.01).
Conclusion
This study suggests that individual 1-year survival probability of patients receiving first-line doublet cytotoxic chemotherapy for advanced gastric cancer can be reliably predicted by a nomogram-based method incorporating clinicopathological variables and initial response to chemotherapy.