Assessment of Clinicopathological Characteristics and Development of an Individualized Prognostic Model for Patients With Hepatoid Adenocarcinoma of the Stomach

Ji, Lin; Wang, Zu‐Kai; Hong, Qingqi; Zhang, Peng; Zhang, Zizhen; He, Liang; Wang, Quan; Shang, Liang; Wang, Linjun; Sun, Yeqing; Li, Zhixiong; Liu, Jun-Jie; Ding, Fanghui; Lin, Ende; Fu, Yongan; Lin, Shuangming; Xie, Jian‐Wei; Li, Ping; Zheng, Chao-Hui; Huang, Chang‐Ming

doi:10.1001/jamanetworkopen.2021.28217

Cited by 18 publications

(18 citation statements)

References 40 publications

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“…Our novel nomogram has shown remarkable e ciency in predicting CSS among patients with HAC. A different nomogram produced with 315 patients who had primary HAS demonstrated that problematic node category 3, preoperative carcinoembryonic antigen (CEA) levels of 5 ng/mL or greater, and perineural invasion were independent risk factors for a worse survival outcome (Lin et al, 2021). However, this study did not nd any independent prognostic factors that are similar to our research.…”

Section: Discussioncontrasting

confidence: 62%

Development of a Prognostic Nomogram for Cancer-Specific Survival in Hepatoid Carcinoma: Insights from a Comprehensive SEER-Based Population Analysis

Wang#,

Zhou,

et al. 2024

Preprint

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Background Hepatoid adenocarcinoma (HAC) is a poorly differentiated extrahepatic tumor that can produce alpha-fetoprotein (AFP). The prognostic factors of HAC have not been fully stated in the literature. Therefore, we present a novel nomogram to predict the cancer-specific survival (CSS) of patients with HAC. Methods In total, 265 cases with HAC were extracted from the Surveillance, Epidemiology, and End Results (SEER) database from 2004–2015. A prognostic nomogram was produced using the discovered risk factors and a Cox proportional hazard regression model. The nomogram's predictive ability was assessed by utilizing the concordance index (c-index), calibration curve, and receiver operating characteristic (ROC). Results Multivariate Cox regression showed that metastasis at the liver, surgery, and chemotherapy were independently correlated with CSS. A nomogram was developed using these factors, with a c-index of 0.71 (95% CI 0.71–0.96). Furthermore, calibration curves demonstrated concordance between the predicted survival probability from the nomogram and the observed survival probability. The areas under the curve (AUC) for 1-year, 3-year, and 5-year survival were 0.80, 0.82, and 0.88, respectively. Conclusion Our study successfully formulated a prognostic nomogram that offers promising predictions for the 1-, 3-, and 5-year Cancer-Specific Survival (CSS) of patients with HAC. This nomogram holds potential for practical use in guiding treatment decisions and designing clinical trials.

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Section: Discussioncontrasting

confidence: 62%

Development of a Prognostic Nomogram for Cancer-Specific Survival in Hepatoid Carcinoma: Insights from a Comprehensive SEER-Based Population Analysis

Wang#,

Zhou,

et al. 2024

Preprint

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“…Nomogram is a comprehensive assessment tool that integrates multiple risk factors to predict outcomes. It has been demonstrated to possess superior prognostic prediction ability compared to traditional TNM staging in various types of tumors ( 28 - 30 ). Furthermore, nomograms have been successfully employed to predict the subset of patients who may derive benefits from specific therapies ( 31 , 32 ).…”

Section: Discussionmentioning

confidence: 99%

Risk factors and a prognostic model for patients with borderline resectable locally advanced T3–4N0–1 non-small cell lung cancer: a population-based study

Liu,

Lai,

Zhang

et al. 2023

Transl Cancer Res

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Background Non-small cell lung cancer (NSCLC) is a malignant disease with a significant morbidity rate. For patients diagnosed with borderline resectable locally advanced (T3–4 invasion and N0–1) NSCLC, the optimal treatment and prognosis are still under debate. This study aimed to develop a predictive nomogram that could assess the prognosis of these patients and optimize clinical decision-making. Methods Between 2010 to 2015, the survival, demographic and clinical characteristics of patients with borderline resectable locally advanced T3–4N0–1 NSCLC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Cox proportional hazard regression analyses were conducted to identify potential factors, which were further utilized to develop a dynamic nomogram for personalized prediction. Internal and external validation were conducted to verify the predictive accuracy of the nomogram. Results Totally, 5,054 eligible records were enrolled into the study cohort. The included patients were divided into a training cohort (n=3,538) and a validation cohort (n=1,516) in a 7:3 ratio. Nine independent prognostic factors (including age, gender, primary site, lymph node removal, differentiation grade, T stage, N stage, histology and adjuvant chemotherapy) were finally included into the nomogram. The developed nomogram exhibited favorable discriminative ability with the C-index =0.71. Moreover, the calibration curves demonstrated excellent agreement between predicted and observed outcomes in both the training and validation cohorts. Notably, subgroup analyses revealed that neoadjuvant chemotherapy was significantly associated with a better overall survival (OS) (P<0.05) in patients staged as T3–4N1. Conclusions In this study, we developed and validated a prognostic model to assist in clinical decision-making for patients with borderline resectable locally advanced T3–4N0–1 NSCLC. Our findings suggested that patients with T3–4N1 stage disease may derive significant benefits from neoadjuvant chemotherapy.

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“…Common clinical features in patients with TETs, such as age, GTF2I mutation, gender, Masaoka stage, and histologic type, were used to construct a nomogram using the R package “rms” and calibrate function. The time-dependent calibration curves from the R package “rms” were used to determine prediction accuracy of the nomogram [ 55 , 56 ].…”

Section: Methodsmentioning

confidence: 99%

Thymic epithelial tumors: examining the GTF2I mutation and developing a novel prognostic signature with LncRNA pairs to predict tumor recurrence

et al. 2022

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Background General transcription factor IIi (GTF2I) mutations are very common in thymic epithelial tumors (TETs) and are related to a more favorable prognosis in TET patients. However, limited research has been conducted on the role of GTF2I in the tumor immune microenvironment (TIME). Further, long non-coding RNAs (lncRNAs) have been associated with the survival of patients with TETs. Therefore, this study aimed to explore the relationship between GTF2I mutations and TIME and build a new potential signature for predicting tumor recurrence in the TETs. Research data was downloaded from The Cancer Genome Atlas database and the CIBERSORT algorithm was used to evaluate TIME differences between GTF2I mutant and wild-type TETs. Relevant differentially expressed lncRNAs based on differentially expressed immune-related genes were identified to establish lncRNA pairs. We constructed a signature using univariate and multivariate Cox regression analyses. Results GTF2I is the most commonly mutated gene in TETs, and is associated with an increased number of early-stage pathological types, as well as no history of myasthenia gravis or radiotherapy treatment. In the GTF2I wild-type group, immune score and immune cell infiltrations with M2 macrophages, activated mast cells, neutrophils, plasma, T helper follicular cells, and activated memory CD4 T cells were higher than the GTF2I mutant group. A risk model was built using five lncRNA pairs, and the 1-, 3-, and 5-year area under the curves were 0.782, 0.873, and 0.895, respectively. A higher risk score was related to more advanced histologic type. Conclusion We can define the GTF2I mutant-type TET as an immune stable type and the GTF2I wild-type as an immune stressed type. A signature based on lncRNA pairs was also constructed to effectively predict tumor recurrence.

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Assessment of Clinicopathological Characteristics and Development of an Individualized Prognostic Model for Patients With Hepatoid Adenocarcinoma of the Stomach

Cited by 18 publications

References 40 publications

Development of a Prognostic Nomogram for Cancer-Specific Survival in Hepatoid Carcinoma: Insights from a Comprehensive SEER-Based Population Analysis

Development of a Prognostic Nomogram for Cancer-Specific Survival in Hepatoid Carcinoma: Insights from a Comprehensive SEER-Based Population Analysis

Risk factors and a prognostic model for patients with borderline resectable locally advanced T3–4N0–1 non-small cell lung cancer: a population-based study

Thymic epithelial tumors: examining the GTF2I mutation and developing a novel prognostic signature with LncRNA pairs to predict tumor recurrence

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