Prognostic impact of examined lymph-node count for patients with esophageal cancer: development and validation prediction model.

Tytuł:: Prognostic impact of examined lymph-node count for patients with esophageal cancer: development and validation prediction model.
Autorzy:: Yuan S; Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, People's Republic of China.
Wei C; Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, People's Republic of China.
Wang M; Department of Radiotherapy, The First Affiliated Hospital of Xinxiang Medical University, Xinxiang, Henan, People's Republic of China.
Deng W; Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, People's Republic of China.
Zhang C; Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, People's Republic of China.
Li N; Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, People's Republic of China. .
Luo S; Department of Internal Medicine, The Affiliated Cancer Hospital of Zhengzhou University, Henan Cancer Hospital, No. 127 Dongming Road, Zhengzhou, 450008, Henan, People's Republic of China. .
Źródło:: Scientific reports [Sci Rep] 2023 Jan 10; Vol. 13 (1), pp. 476. Date of Electronic Publication: 2023 Jan 10.
Typ publikacji:: Journal Article; Research Support, Non-U.S. Gov't
Język:: English
Imprint Name(s):: Original Publication: London : Nature Publishing Group, copyright 2011-
MeSH Terms:: Lymph Nodes*/pathology
Esophageal Neoplasms*/diagnosis
Esophageal Neoplasms*/surgery
Esophageal Neoplasms*/pathology
Humans ; Prognosis ; Neoplasm Staging ; Regression Analysis
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Entry Date(s):: Date Created: 20230110 Date Completed: 20230112 Latest Revision: 20230227
Update Code:: 20240105
PubMed Central ID:: PMC9831985
DOI:: 10.1038/s41598-022-27150-6
PMID:: 36627338
: Czasopismo naukowe

Pełny tekst

Esophageal cancer (EC) is a malignant tumor with high mortality. We aimed to find the optimal examined lymph node (ELN) count threshold and develop a model to predict survival of patients after radical esophagectomy. Two cohorts were analyzed: the training cohort which included 734 EC patients from the Chinese registry and the external testing cohort which included 3208 EC patients from the Surveillance, Epidemiology, and End Results (SEER) registry. Cox proportional hazards regression analysis was used to determine the prognostic value of ELNs. The cut-off point of the ELNs count was determined using R-statistical software. The prediction model was developed using random survival forest (RSF) algorithm. Higher ELNs count was significantly associated with better survival in both cohorts (training cohort: HR = 0.98, CI = 0.97-0.99, P < 0.01; testing cohort: HR = 0.98, CI = 0.98-0.99, P < 0.01) and the cut-off point was 18 (training cohort: P < 0.01; testing cohort: P < 0.01). We developed the RSF model with high prediction accuracy (AUC: training cohort: 87.5; testing cohort: 79.3) and low Brier Score (training cohort: 0.122; testing cohort: 0.152). The ELNs count beyond 18 is associated with better overall survival. The RSF model has preferable clinical capability in terms of individual prognosis assessment in patients after radical esophagectomy.
(© 2023. The Author(s).)

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