Impact of Socioeconomic Factors on Prognosis and Clinical Management in Patients with Hepatocellular Carcinoma

Su, Bing-Bing; Zhou, Beifan; Bai, Dou‐Sheng; Qian, Jianjun; Zhang, Chi; Jin, Sheng‐Jie; Jiang, Guo‐Qing

doi:10.5152/tjg.2021.20617

Cited by 1 publication

(4 citation statements)

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“… 15 16 Although TNM stage has been recognised as a prognostic indicator of cancer, TNM only considers the extent of invasion of the primary tumour, lymph node metastatic status and distant spread. 17 Additionally, patients with IGA at the same stage may have a different prognosis and survival. 18 These results also imply that the TNM stage may be not optimal for clinical prognosis prediction.…”

Section: Discussionmentioning

confidence: 99%

“… 18 These results also imply that the TNM stage may be not optimal for clinical prognosis prediction. 17 Currently, surgery, systemic chemotherapy, radiotherapy and targeted therapy have been proven to have significant survival benefits for patients with gastric adenocarcinoma. 19 We also found that radiotherapy and gastrectomy can improve OS and CSS in patients with IGA in this study.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have shown that the prognosis of gastric adenocarcinoma was related to the TNM stage at the time of diagnosis 15 16. Although TNM stage has been recognised as a prognostic indicator of cancer, TNM only considers the extent of invasion of the primary tumour, lymph node metastatic status and distant spread 17. Additionally, patients with IGA at the same stage may have a different prognosis and survival 18.…”

Section: Discussionmentioning

confidence: 99%

“…Additionally, patients with IGA at the same stage may have a different prognosis and survival 18. These results also imply that the TNM stage may be not optimal for clinical prognosis prediction 17. Currently, surgery, systemic chemotherapy, radiotherapy and targeted therapy have been proven to have significant survival benefits for patients with gastric adenocarcinoma 19.…”

Section: Discussionmentioning

confidence: 99%

See 3 more Smart Citations

Prediction models for the survival in patients with intestinal-type gastric adenocarcinoma: a retrospective cohort study based on the SEER database

Hong¹,

Cheng²,

Gu³

et al. 2023

BMJ Open

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ObjectiveTo explore the influencing factors of survival in intestinal-type gastric adenocarcinoma (IGA) and set up prediction model for the prediction of survival of patients diagnosed with IGA.DesignA retrospective cohort study.Setting and participantsA total of 2232 patients with IGA who came from the Surveillance, Epidemiology, and End Results database.Primary and secondary outcome measuresPatients’ overall survival (OS) rate and cancer-specific survival (CSS) at the end of follow-up.ResultsOf the total population, 25.72% survived, 54.93% died of IGA and 19.35% died of other causes. The median survival time of patients was 25 months. The result showed that age, race, stage group, T stage, N stage, M stage, grade, tumour size, radiotherapy, number of lymph nodes removed and gastrectomy were independent prognostic factors of OS risk for patients with IGA; age, race, race, stage group, T stage, N stage, M stage, grade, radiotherapy and gastrectomy were associated with CSS risk for patients with IGA. In view of these prognostic factors, we developed two prediction models for predicting the OS and CSS risk for patients with IGA separately. For the developed OS-related prediction model, the C-index was 0.750 (95% CI: 0.740 to 0.760) in the training set, corresponding to 0.753 (95% CI: 0.736 to 0.770) in the testing set. Likewise, for the developed CSS-related prediction model, the C-index was 0.781 (95% CI: 0.770 to 0.793) in the training set, corresponding to 0.785 (95% CI: 0.766 to 0.803) in the testing set. The calibration curves of the training set and testing set revealed a good agreement between model predictions in the 1-year, 3-year and 5-year survival for patients with IGA and actual observations.ConclusionCombining demographic and clinicopathological features, two prediction models were developed to predict the risk of OS and CSS in patients with IGA, respectively. Both models have good predictive performance.

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Section: Discussionmentioning

confidence: 99%