Development and external validation of a nomogram for predicting the conditional probability of survival after D2 lymphadenectomy for gastric cancer: A multicentre study

Chen, Qi Yue; Zhong, Qing; Wang, Wei; Desiderio, Jacopo; Liu, Zhi Yu; Xie, Jian; Wang, Jia Bin; Lin, Jian; Lü, Jun; Cao, Long Long; Ma, Lin; Tu, Ru Hong; Li, Ping; Zheng, Chao; Zhou, Zhi Wei; Parisi, Amilcare; Changming, Huang

doi:10.1016/j.ejso.2019.04.003

Cited by 14 publications

(12 citation statements)

References 35 publications

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“…Several studies of prognostic nomograms have emphasized their potential advantages to patients and a reliable risk-based predictive tool that can be used widely in cancer-related research (38). Researchers have investigated a number of prognostic factors for GC, such as age, sex, tumor size, node status, depth of invasion, tumor site, Lauren type, histologic type, distant metastasis, and biological markers, with various prognostic models being established accordingly (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)37,(39)(40)(41)(42); however, none of these involved the value of clinical symptoms, HER2 status, and adjacent organ invasion. Additionally, only a few of these nomogram studies conducted validation in an external center, and some only focused on specific subgroups of patients (18); consequently, it remains elusive for the application of nomograms for a large population of GC patients.…”

Section: Discussionmentioning

confidence: 99%

“…Researchers have investigated a number of prognostic factors for GC, such as age, sex, tumor size, node status, depth of invasion, tumor site, Lauren type, histologic type, distant metastasis, and biological markers, with various prognostic models being established accordingly (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)37,(39)(40)(41)(42); however, none of these involved the value of clinical symptoms, HER2 status, and adjacent organ invasion. Additionally, only a few of these nomogram studies conducted validation in an external center, and some only focused on specific subgroups of patients (18); consequently, it remains elusive for the application of nomograms for a large population of GC patients. To address this, we established a model in this study that was validated externally, and it demonstrated its applicability for a wider range of populations with GC.…”

Section: Discussionmentioning

confidence: 99%

“…Thus far, the identification of prognosis for patients with GC has mainly depended on TNM staging, but owing to its inaccuracy and incompleteness, its prognostic value remains controversial. Therefore, the requirement for effective prognostic criteria has prompted researchers to explore new prognostic models for GC from multiple perspectives to help in the diagnosis of high-risk patients with poor prognoses (12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22). Identifying this proportion of patients would allow clinicians to adjust treatment strategies at an appropriate time, achieve effective intervention to control the progression of tumor, and extend patients' survival as far as possible.…”

Section: Introductionmentioning

confidence: 99%

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Development and external validation of a prognostic nomogram for patients with gastric cancer after radical gastrectomy

Yang

Chen

et al. 2021

Ann Transl Med

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Background: Gastric cancer (GC) is one of the most malignant diseases and threatens the health of individuals across the globe. Hitherto, the identification of prognosis risk stratification on GC has mainly depended on the TNM staging, but owing to its inaccuracy and incompleteness, the prognostic value it offers remains controversial in the current clinical setting. Thus, an effective prognostic model for GC after radical gastrectomy is still needed. Methods: Patients with pathologically confirmed GC who underwent radical gastrectomy from 2 different centers were retrospectively enrolled into a training and the validation cohort, respectively. The least absolute shrinkage and selection operator (LASSO) algorithm was applied to select variables among multiple factors, including clinical characteristics, pathological parameters, and surgery-and treatment-related indicators. The multivariate Cox regression method was used to establish the model to predict 1-, 2-, and 3-year survival. Both internal and external validations of the nomogram were then completed in terms of discrimination, calibration, and clinical utility. Finally, prognostic risk stratification of GC was conducted with X-tile software. Results: A total of 1,424 patients with GC were eligible in this study, including 1,010 in the training cohort and 414 in the validation cohort. Seven indicators were selected by LASSO to develop the nomogram, including the number of positive lymph nodes, tumor size, adjacent organ invasion, vascular invasion, the level of carbohydrate antigen 125 (CA 125), depth of invasion, and human epidermal growth factor receptor 2 (HER2) status. The nomogram demonstrated a robust predictive capacity with favorable accuracy, discrimination, and clinical utility both in the internal and external validations. Moreover, we divided the population into 3 risk groups of survival according to the cutoff points generated by X-tile, and in this way, the nomogram was further improved into a risk-stratified prognosis model. Conclusions: We have developed a prognostic risk stratification nomogram for GC patients after radical gastrectomy with 7 available indicators that may guide clinical practice and help facilitate tailored decisionmaking, thus avoiding overtreatment or undertreatment and improving communication between clinicians and patients.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Development and external validation of a prognostic nomogram for patients with gastric cancer after radical gastrectomy

Yang

Chen

et al. 2021

Ann Transl Med

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“…Clinical nomogram has gained a lot of attention for its more convenient and advanced prognosis ability [18]. It had already showed promising prognostic capability in different kinds of cancers including lung cancer [10,19], gastric cancer [20,21]], colorectal cancer [22], liver cancer [23], melanoma [24], etc. For resected NSCLC (stage I-IIIa) [19], a clinical nomogram built on sex, age, histology, sampled lymph nodes, T and N stage achieved higher C-index than that of the seventh edition American Joint Committee on Cancer TNM staging system for predicting OS (primary cohort, 0.71 v 0.68, respectively; P .01; validation cohort, 0.67 v 0.64, respectively; P .06).…”

Section: Discussionmentioning

confidence: 99%

Prognostic Nomogram to Predict the Overall Survival of Patients with “driver-gene-negative” Lung Adenocarcinoma (LUAD) and Its’ Biological Basis Deciphering

Zhu

Yang

Shan

et al. 2021

Preprint

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Objectives: Assessing the prognosis of patients with “driver-gene-negative” lung adenocarcinoma (LUAD patients negative for EGFR, KRAS, BRAF, HER2, MET, ALK, RET and ROS1 were identified as “driver-gene-negative”) is of significant clinical importance. We aimed to devise a prognostic nomogram for this LUAD subgroup and to define its biological basis.Materials and methods: Prognostic nomogram were established based on a retrospective study of 294 patients with surgical resected “driver-gene-negative” LUAD at The First Affiliated Hospital of Sun Yat-sen University between September 2003 and June 2015. The concordance index (C-index) and calibration curve were used to determine its predictive accuracy and discriminatory capacity. Patients were classified into low- and high-risk subgroups according to nomogram scores. To define the biological basis, we carried out gene set enrichment analysis in an independent dataset of 49 “driver-gene-negative” LUAD patients.Results: The nomogram built on the independent factors including CTC, age and stage achieved C-index of 0.785 [95% confidence interval (CI) 0.753-0.817] for predicting OS of “driver-gene-negative” LUAD. The calibration curves for OS probabilities showed a good agreement between the nomogram prediction and actual observation. High-risk patients had shorter OS [hazard ratio (HR) = 7.43, 95% CI 5.20-10.42, p<0.0001]. The genetic analysis suggested the biological basis for the role of the predictive model may be due to changes in cell proliferation, metabolism and neurological disease, indicating a relationship between increased proliferative potential and preferential poor prognosis.Conclusions: The prognostic nomogram showed promising prediction efficacy and is expected to predict the prognosis of “driver-gene-negative” LUAD. The easy-to-use nomogram and the enriched pathways can help clinical decision-making, guide follow-up planning, and develop new therapeutic targets.

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“…The most important issue is ensuring proper oncological surgery by performing an adequate lymphadenectomy with minimally invasive approaches. Researchers still regard nodal clearance as an important factor in uencing long-term survival [6][7][8][9][10][11][12][13]. In randomized trials [3], laparoscopy demonstrated the removal of at least 15 lymph nodes, as required by international guidelines [14]; however, a signi cant difference in favor of open surgery resulted in the total number of lymph nodes harvested.…”

Section: Introductionmentioning

confidence: 99%

Prospective, observational, multicenter study on minimally invasive gastrectomy for gastric cancer: robotic, laparoscopic and open surgery compared on operative and follow-up outcomes - IMIGASTRIC II study protocol: IMIGASTRIC II

Desiderio

Norero

et al. 2019

Journal of Gastric Surgery

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Background: Several meta-analyses have tried to defi ne the role of minimally invasive approaches. However, further evidence to get a wider spread of these methods is necessary. Current studies describe minimally invasive surgery as a possible alternative to open surgery but deserving further clarifi cation. However, despite the increasing interest, the difficulty of planning prospective studies of adequate size accounts for the low level of evidence, which is mostly based on retrospective experiences. A multi-institutional prospective study allows the collection of an impressive amount of data to investigate various aspects of minimally invasive procedures with the opportunity of developing several subgroup analyses. A prospective data collection with high methodological quality on minimally invasive and open gastrectomies can clarify the role of diff erent procedures with the aim to develop specifi c guidelines. Methods and analysis: a multi-institutional prospective database will be established including information on surgical, clinical and oncological features of patients treated for gastric cancer with robotic, laparoscopic or open approaches and subsequent follow-up. The study has been shared by the members of the International study group on Minimally Invasive surgery for GASTRIc Cancer (IMIGASTRIC) The database is designed to be an international electronic submission system and a HIPPA protected real time data repository from high volume gastric cancer centers. Ethics: This study is conducted in compliance with ethical principles originating from the Helsinki Declaration, within the guidelines of Good Clinical Practice and relevant laws/regulations. Trial registration number: NCT02751086

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Development and external validation of a nomogram for predicting the conditional probability of survival after D2 lymphadenectomy for gastric cancer: A multicentre study

Cited by 14 publications

References 35 publications

Development and external validation of a prognostic nomogram for patients with gastric cancer after radical gastrectomy

Development and external validation of a prognostic nomogram for patients with gastric cancer after radical gastrectomy

Prognostic Nomogram to Predict the Overall Survival of Patients with “driver-gene-negative” Lung Adenocarcinoma (LUAD) and Its’ Biological Basis Deciphering

Prospective, observational, multicenter study on minimally invasive gastrectomy for gastric cancer: robotic, laparoscopic and open surgery compared on operative and follow-up outcomes - IMIGASTRIC II study protocol: IMIGASTRIC II

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