Risk factors and predictive nomogram for non-curative resection in patients with early gastric cancer treated with endoscopic submucosal dissection: a retrospective cohort study.
코호트
1/5 보강
PICO 자동 추출 (휴리스틱, conf 3/4)
유사 논문P · Population 대상 환자/모집단
511 patients (535 EGC lesions) underwent ESD.
I · Intervention 중재 / 시술
gastric ESD at the First Affiliated Hospital of Ningbo University between 2016 and 2023
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[CONCLUSIONS] We developed nomograms to predict the risk of submucosal invasion and NCR prior to ESD. These predictive factors in addition to the existing ESD criteria can help provide the best treatment option for patients with EGC.
[INTRODUCTION] The objective of this study was to determine independent clinicopathological factors that can predict submucosal invasion and non-curative resection (NCR) outcomes after endoscopic subm
- p-value P < 0.05
APA
Guo L, Ding Y, et al. (2025). Risk factors and predictive nomogram for non-curative resection in patients with early gastric cancer treated with endoscopic submucosal dissection: a retrospective cohort study.. World journal of surgical oncology, 23(1), 213. https://doi.org/10.1186/s12957-025-03850-x
MLA
Guo L, et al.. "Risk factors and predictive nomogram for non-curative resection in patients with early gastric cancer treated with endoscopic submucosal dissection: a retrospective cohort study.." World journal of surgical oncology, vol. 23, no. 1, 2025, pp. 213.
PMID
40450359 ↗
Abstract 한글 요약
[INTRODUCTION] The objective of this study was to determine independent clinicopathological factors that can predict submucosal invasion and non-curative resection (NCR) outcomes after endoscopic submucosal dissection (ESD) in patients with early gastric cancer (EGC).
[METHODS] Data were collected from consecutive patients who underwent gastric ESD at the First Affiliated Hospital of Ningbo University between 2016 and 2023. A retrospective analysis was conducted using the chi-squared test and logistic regression analysis. Multiple logistic regression analysis was applied to investigate factors independently predicting both submucosal invasion and NCR. These factors were used to construct predictive nomograms.
[RESULTS] A total of 511 patients (535 EGC lesions) underwent ESD. Of these, 452 were curative (84.7%), and 83 (15.5%) were non-curative. Multivariate analysis revealed that location in the body and fundus or cardia of the stomach, larger tumor size (≥ 30 mm), and histological undifferentiated type were independent risk factors for submucosal invasion and deep submucosal invasion in patients with EGC (all P < 0.05). Multivariate analysis showed that tumor size of 20 ~ 29 mm, tumor size ≥ 30 mm, elevated lesions, depressed lesions, undifferentiated tumors and submucosal invasion were all independent predictors of NCR for EGCs (all P < 0.05). The area under the ROC curve (AUC) of the nomogram model for predicting submucosal invasion and non-curative resection was 0.821 (95% CI, 0.758 ~ 0.884) and 0.937 (95%CI, 0.889 ~ 0.985), respectively.
[CONCLUSIONS] We developed nomograms to predict the risk of submucosal invasion and NCR prior to ESD. These predictive factors in addition to the existing ESD criteria can help provide the best treatment option for patients with EGC.
[METHODS] Data were collected from consecutive patients who underwent gastric ESD at the First Affiliated Hospital of Ningbo University between 2016 and 2023. A retrospective analysis was conducted using the chi-squared test and logistic regression analysis. Multiple logistic regression analysis was applied to investigate factors independently predicting both submucosal invasion and NCR. These factors were used to construct predictive nomograms.
[RESULTS] A total of 511 patients (535 EGC lesions) underwent ESD. Of these, 452 were curative (84.7%), and 83 (15.5%) were non-curative. Multivariate analysis revealed that location in the body and fundus or cardia of the stomach, larger tumor size (≥ 30 mm), and histological undifferentiated type were independent risk factors for submucosal invasion and deep submucosal invasion in patients with EGC (all P < 0.05). Multivariate analysis showed that tumor size of 20 ~ 29 mm, tumor size ≥ 30 mm, elevated lesions, depressed lesions, undifferentiated tumors and submucosal invasion were all independent predictors of NCR for EGCs (all P < 0.05). The area under the ROC curve (AUC) of the nomogram model for predicting submucosal invasion and non-curative resection was 0.821 (95% CI, 0.758 ~ 0.884) and 0.937 (95%CI, 0.889 ~ 0.985), respectively.
[CONCLUSIONS] We developed nomograms to predict the risk of submucosal invasion and NCR prior to ESD. These predictive factors in addition to the existing ESD criteria can help provide the best treatment option for patients with EGC.
🏷️ 키워드 / MeSH 📖 같은 키워드 OA만
- Humans
- Stomach Neoplasms
- Retrospective Studies
- Nomograms
- Female
- Male
- Endoscopic Mucosal Resection
- Middle Aged
- Risk Factors
- Aged
- Neoplasm Invasiveness
- Prognosis
- Gastric Mucosa
- Follow-Up Studies
- Gastrectomy
- Adult
- Early gastric cancer (EGC)
- Endoscopic submucosal dissection (ESD)
- Non-curative resection (NCR)
- Predictive model
- Submucosal invasion
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