ArticleAnnals of translational medicine2022
A novel prognostic model: which group of esophageal squamous cell carcinoma patients could benefit from adjuvant chemotherapy.
Article in Annals of translational medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed, 2 citations in OpenAlex.
- Optimal extent of lymphadenectomy improves prognosis and guides adjuvant chemotherapy in esophageal cancer: A propensity score-matched analysis.World journal of gastrointestinal surgery · 2024Article
- Dynamic alteration in SULmax predicts early pathological tumor response and short-term prognosis in non-small cell lung cancer treated with neoadjuvant immunochemotherapy.Frontiers in bioengineering and biotechnology · 2022Article
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: This study aimed to establish a reliable model for predicting the overall survival (OS) of esophageal squamous cell carcinoma (ESCC) patients and identifying the potential beneficiaries of adjuvant chemotherapy after esophagectomy. Methods: This retrospective study included 819 ESCC patients who underwent esophagectomy as the training cohort. We constructed a prognostic model named GTLN2. Both internal and external validation tests were performed. Potential beneficiaries were defined as ESCC patients who obtained a significantly longer OS after adjuvant chemotherapy. Propensity score matching (PSM) was utilized in the subgroup analysis to screen ESCC beneficiaries of adjuvant chemotherapy. Results: We enrolled a total of 819 cT1b-3 patients in the training cohort. Multiple prognostic factors were associated with adjuvant chemotherapy. Using uni-/multivariate analysis, histological grade (G), tumor invasion depth (T), regional lymph node metastasis (N), and the number of cleared lymph nodes (NCLNs) were identified as independent prognostic factors. Then, we developed the GTLN2 model based on these predictors and validated it using internal calculations [the 1-, 3- and 5-year area under the curves (AUCs) were 0.692, 0.685 and 0.680, respectively; P<0.001] and external cohorts (the 1-, 3-, and 5-year AUCs were 0.651, 0.619 and 0.650, respectively; P<0.001). ESCC patients were categorized into high- and low-risk groups based on their assigned risk scores. After 1:1 patient pairing was performed by PSM in the high-risk group, better OS was noted in patients receiving adjuvant chemotherapy (P=0.024). Conclusions: Differentiating high- and low-risk patient groups via a novel mathematical prediction model allows physicians to identify patients in need of adjuvant chemotherapy accurately.
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