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. 2020 Aug;9(16):5708-5718.
doi: 10.1002/cam4.3225. Epub 2020 Jun 26.

Development and validation of a pretreatment nomogram to predict overall survival in gastric cancer

Etsuro Bando  1   2 , Xinge Ji  2 , Michael W Kattan  2 , Ho Seok Seo  3 , Kyo Young Song  3 , Cho-Hyun Park  3 , Maria Bencivenga  4 , Giovanni de Manzoni  4 , Masanori Terashima  1
Affiliations

Development and validation of a pretreatment nomogram to predict overall survival in gastric cancer

Etsuro Bando et al. Cancer Med. 2020 Aug.

Abstract

Background: Pretreatment clinical staging is essential to select therapy. However, there have been no published pretreatment gastric cancer nomograms constructed using pretreatment clinical prognostic factors, including in nonresection patients. We aimed to develop a new pretreatment gastric cancer nomogram for individualized prediction of overall survival (OS).

Methods: The nomogram was developed using data of 5231 Japanese gastric cancer patients, and it was created with a Cox regression model. Fifteen clinical variables, which were obtained at pretreatment, were collected and registered. Data of two independent cohorts of patients from Seoul St. Mary's Hospital (1001 patients), and the University of Verona (389 patients) formed the external validation cohorts. The model was validated internally and externally using measures of discrimination (Harrell's C-index), calibration, and decision curve analysis.

Results: The developed nomogram showed good discrimination, with a C-index of 0.855; that of the American Joint Committee on Cancer (AJCC) clinical stage was 0.819. In the external validation procedure, the C-indexes were 0.856 (AJCC, 0.795) in the Seoul St. Mary's cohort and 0.714 (AJCC, 0.648) in the University of Verona cohort. The nomogram performed well in the calibration and decision curve analyses when applied to both the internal and external validation cohorts. A stage-specific subset survival analysis of the three risk groups calculated using the nomogram also showed the superiority of nomogram-prediction when compared to AJCC.

Conclusion: This new pretreatment model accurately predicts OS in gastric cancer and can be used for patient counseling in clinical practice and stratification in clinical trials.

Keywords: clinical staging; gastric cancer; pretreatment nomogram; the American Joint Committee on Cancer.

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Conflict of interest statement

The authors made no disclosures.

Figures

FIGURE 1
FIGURE 1
Summary of treatment performed after diagnosis. Abbreviations: BSC, best supportive care; NAC, neoadjuvant chemotherapy
FIGURE 2
FIGURE 2
Kaplan‐Meier survival curves of overall survival by American Joint Committee on Cancer stage (AJCC) grouping in developing cohort, with numbers at risk
FIGURE 3
FIGURE 3
Pretreatment gastric cancer nomogram. This nomogram provides a method to calculate 1‐, 3‐, and 5‐y probability of survival. Add the scores for each covariate together and locate the total score on the total points axis. Draw a line straight down to the 1‐, 3‐, and 5‐y OS axes to obtain the probability. Abbreviations: CA19‐9, carbohydrate antigen 19‐9; CEA, carcinoembryonic antigen; cM, distant metastasis except metastasis in intra‐abdominal nonregional lymph node, liver metastasis, and peritoneal dissemination; ECOGPS, Eastern Cooperative Oncology Group performance status; Liver, liver metastasis; ln, natural logarithm; OS, overall survival; Peritoneum, peritoneal dissemination.
FIGURE 4
FIGURE 4
Discriminatory performance of the nomogram. Data are from the development cohort. A, Calibration plot of the overall survival nomogram. B, Decision curve to plot the net benefit achieved by making clinical decisions based on the final multivariable model prediction at 5 y, for overall survival. C, Distribution of nomogram predictions within each American Joint Committee on Cancer (AJCC) stage grouping, for overall survival
FIGURE 5
FIGURE 5
Kaplan‐Meier survival curves of the overall survival of patients stratified into three risk groups according to nomogram‐predicted 5‐y survival rate in the development cohort, with the numbers at risk. A, cStage I/ IIA, B, cStage IIB/III, and C, cStage IVA/IVB
See this image and copyright information in PMC

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