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28.01.2020 | Original Article | Ausgabe 12/2020

Digestive Diseases and Sciences 12/2020

Development and Validation of Prognostic Nomograms for Patients with Primary Gastrointestinal Non-Hodgkin Lymphomas

Zeitschrift:
Digestive Diseases and Sciences > Ausgabe 12/2020
Autoren:
Bo Sun, Yang Xia, Yuqian Guo, Chiyi He, Wei Wang
Wichtige Hinweise

Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1007/​s10620-020-06078-9) contains supplementary material, which is available to authorized users.

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Abstract

Background and Aims

The objective of this study was to construct and authenticate nomograms to project overall survival (OS) and cancer-specific survival (CSS) in primary gastrointestinal non-Hodgkin lymphomas (PGINHL).

Methods

Suitable patients were chosen from the Surveillance, Epidemiology and End Results database and Wannan Medical College Yijishan Hospital. The Cox regression model was used to acquire independent predictive factors to develop nomograms for projecting OS and CSS. The performance of the nomograms was validated using the Harrell’s concordance index (C-index), calibration curves, and decision curve analysis (DCA) and was compared with that of the AJCC 7th staging system. Survival curves were obtained using the Kaplan–Meier method, while the log-rank test was used to compare the difference among the groups.

Results

The C-index of the nomograms for OS and CSS was 0.735 (95% CI = 0.719–0.751) and 0.761 (95% CI = 0.739–0.783), respectively, signifying substantial predictive accuracy. These outcomes were reproducible when the nomograms were used for the internal and external validation cohorts. Moreover, assessments of the C-index, AUC, and DCA between the nomogram results and the AJCC 7th staging system showed that the former was better for evaluation and was more clinically useful.

Conclusions

We constructed the nomogram which could predict 1-, 3-, and 5-year OS and CSS of patients with PGINHL. Our nomogram showed good performance, suggesting that it can be used as an efficacious instrument for predictive assessment of patients with PGINHL.

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