scholarly journals SOURCE: Prediction Models for Overall Survival in Patients With Metastatic and Potentially Curable Esophageal and Gastric Cancer

2021 ◽  
Vol 19 (4) ◽  
pp. 403-410
Author(s):  
Héctor G. van den Boorn ◽  
Ameen Abu-Hanna ◽  
Nadia Haj Mohammad ◽  
Maarten C.C.M. Hulshof ◽  
Suzanne S. Gisbertz ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Proportional Hazards ◽  
Prediction Models ◽  
Metastatic Cancer ◽  
Cox Proportional Hazards ◽  
Future Research ◽  
Survival Prediction ◽  
Netherlands Cancer Registry ◽  
Treatment Type

Background: Personalized prediction of treatment outcomes can aid patients with cancer when deciding on treatment options. Existing prediction models for esophageal and gastric cancer, however, have mostly been developed for survival prediction after surgery (ie, when treatment has already been completed). Furthermore, prediction models for patients with metastatic cancer are scarce. The aim of this study was to develop prediction models of overall survival at diagnosis for patients with potentially curable and metastatic esophageal and gastric cancer (the SOURCE study). Methods: Data from 13,080 patients with esophageal or gastric cancer diagnosed in 2015 through 2018 were retrieved from the prospective Netherlands Cancer Registry. Four Cox proportional hazards regression models were created for patients with potentially curable and metastatic esophageal or gastric cancer. Predictors, including treatment type, were selected using the Akaike information criterion. The models were validated with temporal cross-validation on their C-index and calibration. Results: The validated model’s C-index was 0.78 for potentially curable gastric cancer and 0.80 for potentially curable esophageal cancer. For the metastatic models, the c-indices were 0.72 and 0.73 for esophageal and gastric cancer, respectively. The 95% confidence interval of the calibration intercepts and slopes contain the values 0 and 1, respectively. Conclusions: The SOURCE prediction models show fair to good c-indices and an overall good calibration. The models are the first in esophageal and gastric cancer to predict survival at diagnosis for a variety of treatments. Future research is needed to demonstrate their value for shared decision-making in clinical practice.

SOURCE: Prediction models for overall survival in patients with metastatic and potentially curable esophageal and gastric cancer.

2020 ◽  
Vol 38 (4_suppl) ◽  
pp. 301-301
Author(s):  
Héctor G. van den Boorn ◽  
Ameen Abu-Hanna ◽  
Nadia Haj Mohammad ◽  
Maarten C.C.M. Hulshof ◽  
Suzanne S. Gisbertz ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Decision Making ◽  
Overall Survival ◽  
Shared Decision Making ◽  
Prediction Models ◽  
Cox Regression ◽  
Future Research ◽  
Shared Decision ◽  
Netherlands Cancer Registry ◽  
Treatment Type

301 Background: Prediction models in cancer care can provide personalized prediction outcomes and can aid in shared decision making. Existing prediction models for esophageal and gastric cancer (EGC), however, are mostly aimed at predicting survival after a curative treatment has already been completed. The aim of this study is to develop prediction models, called SOURCE, to predict overall survival at diagnosis in potentially curable and metastatic EGC patients. Methods: The data from 12,756 EGC patients diagnosed between 2014-2017 were retrieved from the prospective Netherlands Cancer Registry. Four Cox regression models were created for potentially curable and metastatic cancers of the esophagus and stomach. Predictors, including treatment type, were selected using the Akaike Information Criterion. The models were validated with temporal cross-validation on their concordance-index (c-index) and calibration. Results: The validated model’s c-index is 0.76 for potentially curable cancer. For the metastatic models, the c-indices are 0.71 and 0.70 for esophageal and gastric cancer, respectively. The calibration intercepts and slopes lie in the 95% confidence interval of 0 and 1, respectively. The included model variables are given in Table. Conclusions: The SOURCE prediction models show fair c-indices and an overall good calibration. The models are the first in EGC to include treatment as a predictor. The models predict survival at diagnosis for a variety of treatments and therefore could have a high clinical applicability. Future research is needed to demonstrate the effect on shared decision making in clinical practice. [Table: see text]

scholarly journals Integrated Analysis of lncRNA-Associated ceRNA Network Identifies Two lncRNA Signatures as a Prognostic Biomarker in Gastric Cancer

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Shuyan Zhang ◽  
Shanshan Li ◽  
Jian-Lin Guo ◽  
Ningyi Li ◽  
Cai-Ning Zhang ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Cox Proportional Hazards ◽  
Integrated Analysis ◽  
Survival Prediction ◽  
Survival Prognosis ◽  
Cox Regression Analysis ◽  
Cerna Network

Background. Gastric cancer (GC) is a malignant tumour that originates in the gastric mucosal epithelium and is associated with high mortality rates worldwide. Long noncoding RNAs (lncRNAs) have been identified to play an important role in the development of various tumours, including GC. Yet, lncRNA biomarkers in a competing endogenous RNA network (ceRNA network) that are used to predict survival prognosis remain lacking. The aim of this study was to construct a ceRNA network and identify the lncRNA signature as prognostic factors for survival prediction. Methods. The lncRNAs with overall survival significance were used to construct the ceRNA network. Function enrichment, protein-protein interaction, and cluster analysis were performed for dysregulated mRNAs. Multivariate Cox proportional hazards regression was performed to screen the potential prognostic lncRNAs. RT-qPCR was used to measure the relative expression levels of lncRNAs in cell lines. CCK8 assay was used to assess the proliferation of GC cells transfected with sh-lncRNAs. Results. Differentially expressed genes were identified including 585 lncRNAs, 144 miRNAs, and 2794 mRNAs. The ceRNA network was constructed using 35 DElncRNAs associated with overall survival of GC patients. Functional analysis revealed that these dysregulated mRNAs were enriched in cancer-related pathways, including TGF-beta, Rap 1, calcium, and the cGMP-PKG signalling pathway. A multivariate Cox regression analysis and cumulative risk score suggested that two of those lncRNAs (LINC01644 and LINC01697) had significant prognostic value. Furthermore, the results indicate that LINC01644 and LINC01697 were upregulated in GC cells. Knockdown of LINC01644 or LINC01697 suppressed the proliferation of GC cells. Conclusions. The authors identified 2-lncRNA signature in ceRNA regulatory network as prognostic biomarkers for the prediction of GC patient survival and revealed that silencing LINC01644 or LINC01697 inhibited the proliferation of GC cells.

The role of ALBI and IGF-CTP score in refining prognostication of HCC.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. e16659-e16659
Author(s):  
Sunyoung S. Lee ◽  
Yehia I. Mohamed ◽  
Aliya Qayyum ◽  
Manal Hassan ◽  
Lianchun Xiao ◽  
...  
Keyword(s):  
Overall Survival ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Survival Prediction ◽  
Score System ◽  
Risk Of Death ◽  
U Statistics ◽  
Cox Proportional Hazards Models ◽  
Ctp Score

e16659 Background: Child-Turcotte-Pugh (CTP) score is widely used in the assessment of prognosis of HCC and CTP-A is the standard criterion for active therapy and clinical trials entry. Recently, ALBI and insulin-like growth factor-1 (IGF)-CTP scores have been reported to improve survival prediction over CTP score. However, comparative studies to compare both scores and to integrate IGF into Albi score are lacking. Methods: After institutional board approval, data and samples were prospectively collected. 299 HCC patients who had data to generate both IGF-CPG and Albi index were used. The ALBI index, and IGF score were calculated, Cox proportional hazards models were fitted to evaluation the association between overall survival (OS) and CTP, IGF-CTP, Albi and IGF, albumin, bilirubin. Harrell’s Concordance index (C-index) was calculated to evaluate the ability of the three score system to predict overall survival. And the U-statistics was used to compare the performance of prediction of OS between the score system. Results: OS association with CTP, IGF-CTP and Albi was performed (Table). IGF-CTP B was associated with a higher risk of death than A (HR = 1.6087, 95% CI: 1.2039, 2.1497, p = 0.0013), ALBI grade 2 was also associated with a higher risk of death than 1 (HR = 2.2817, 95% CI: 1.7255, 3.0172, p < 0.0001). IGF-1(analyzed as categorical variable) was independently associated with OS after adjusting for the effects of ALBI grade. Which showed IGF-1 ≤26 was significantly associated with poor OS, P = 0.001. Conclusions: Although ALBI grade and IGF-CTP score in this analysis had similar prognostic values in most cases, their benefits might be heterogenous in some specific conditions. We looked into corporation of IGF-1 into ALBI grade, IGF score with cutoff ≤26 which clearly refined OS prediction and better OS stratification of ALBI-grade.

scholarly journals SOURCE: A Registry-Based Prediction Model for Overall Survival in Patients with Metastatic Oesophageal or Gastric Cancer

Cancers ◽  
2019 ◽  
Vol 11 (2) ◽  
pp. 187 ◽  
Author(s):  
Héctor van den Boorn ◽  
Ameen Abu-Hanna ◽  
Emil ter Veer ◽  
Jessy van Kleef ◽  
Florian Lordick ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Decision Making ◽  
Overall Survival ◽  
Prediction Model ◽  
Prediction Models ◽  
Cox Regression ◽  
Added Value ◽  
Cancer Data ◽  
Netherlands Cancer Registry ◽  
Oesophagogastric Cancer

Prediction models are only sparsely available for metastatic oesophagogastric cancer. Because treatment in this setting is often preference-based, decision-making with the aid of a prediction model is wanted. The aim of this study is to construct a prediction model, called SOURCE, for the overall survival in patients with metastatic oesophagogastric cancer. Data from patients with metastatic oesophageal (n = 8010) or gastric (n = 4763) cancer diagnosed during 2005–2015 were retrieved from the nationwide Netherlands cancer registry. A multivariate Cox regression model was created to predict overall survival for various treatments. Predictor selection was performed via the Akaike Information Criterion and a Delphi consensus among experts in palliative oesophagogastric cancer. Validation was performed according to a temporal internal-external scheme. The predictive quality was assessed with the concordance-index (c-index) and calibration. The model c-indices showed consistent discriminative ability during validation: 0.71 for oesophageal cancer and 0.68 for gastric cancer. The calibration showed an average slope of 1.0 and intercept of 0.0 for both tumour locations, indicating a close agreement between predicted and observed survival. With a fair c-index and good calibration, SOURCE provides a solid foundation for further investigation in clinical practice to determine its added value in shared decision making.

Bevacizumab in Combination With Chemotherapy As First-Line Therapy in Advanced Gastric Cancer: A Biomarker Evaluation From the AVAGAST Randomized Phase III Trial

2012 ◽  
Vol 30 (17) ◽  
pp. 2119-2127 ◽  
Author(s):  
Eric Van Cutsem ◽  
Sanne de Haas ◽  
Yoon-Koo Kang ◽  
Atsushi Ohtsu ◽  
Niall C. Tebbutt ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Overall Survival ◽  
Advanced Gastric Cancer ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Locally Advanced ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Phase Iii ◽  
Neuropilin 1

Purpose The AVAGAST study showed that adding bevacizumab to chemotherapy in patients with advanced gastric cancer improves progression-free survival and tumor response rate but not overall survival. To examine the hypothesis that angiogenic markers may have predictive value for bevacizumab efficacy in gastric cancer, AVAGAST included a prospective, mandatory biomarker program. Patients and Methods Patients with previously untreated, locally advanced or metastatic gastric cancer were randomly assigned to bevacizumab (n = 387) or placebo (n = 387) in combination with chemotherapy. Blood and tumor tissue samples were collected at baseline. Prespecified biomarkers included plasma vascular endothelial growth factor-A (VEGF-A), protein expression of neuropilin-1, and VEGF receptors-1 and -2 (VEGFR-1 and VEGFR-2). Correlations between biomarkers and clinical outcomes were assessed by using a Cox proportional hazards model. Results Plasma was available from 712 patients (92%), and tumor samples were available from 727 patients (94%). Baseline plasma VEGF-A levels and tumor neuropilin-1 expression were identified as potential predictors of bevacizumab efficacy. Patients with high baseline plasma VEGF-A levels showed a trend toward improved overall survival (hazard ratio [HR], 0.72; 95% CI, 0.57 to 0.93) versus patients with low VEGF-A levels (HR, 1.01; 95% CI, 0.77 to 1.31; interaction P = .07). Patients with low baseline expression of neuropilin-1 also showed a trend toward improved overall survival (HR, 0.75; 95% CI, 0.59 to 0.97) versus patients with high neuropilin-1 expression (HR, 1.07; 95% CI, 0.81 to 1.40; interaction P = .06). For both biomarkers, subgroup analyses demonstrated significance only in patients from non-Asian regions. Conclusion Plasma VEGF-A and tumor neuropilin-1 are strong biomarker candidates for predicting clinical outcome in patients with advanced gastric cancer treated with bevacizumab.

scholarly journals Survival rates and prognostic factors in right- and left-sided colon cancer stage I–IV: an unselected retrospective single-center trial

2021 ◽  
Author(s):  
Claudius E. Degro ◽  
Richard Strozynski ◽  
Florian N. Loch ◽  
Christian Schineis ◽  
Fiona Speichinger ◽  
...  
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Blood Level ◽  
Proportional Hazards ◽  
Survival Rates ◽  
Cox Proportional Hazards ◽  
Stage I ◽  
Cancer Stage ◽  
Single Center ◽  
Significant Difference

Abstract Purpose Colorectal cancer revealed over the last decades a remarkable shift with an increasing proportion of a right- compared to a left-sided tumor location. In the current study, we aimed to disclose clinicopathological differences between right- and left-sided colon cancer (rCC and lCC) with respect to mortality and outcome predictors. Methods In total, 417 patients with colon cancer stage I–IV were analyzed in the present retrospective single-center study. Survival rates were assessed using the Kaplan–Meier method and uni/multivariate analyses were performed with a Cox proportional hazards regression model. Results Our study showed no significant difference of the overall survival between rCC and lCC stage I–IV (p = 0.354). Multivariate analysis revealed in the rCC cohort the worst outcome for ASA (American Society of Anesthesiologists) score IV patients (hazard ratio [HR]: 16.0; CI 95%: 2.1–123.5), CEA (carcinoembryonic antigen) blood level > 100 µg/l (HR: 3.3; CI 95%: 1.2–9.0), increased lymph node ratio of 0.6–1.0 (HR: 5.3; CI 95%: 1.7–16.1), and grade 4 tumors (G4) (HR: 120.6; CI 95%: 6.7–2179.6) whereas in the lCC population, ASA score IV (HR: 8.9; CI 95%: 0.9–91.9), CEA blood level 20.1–100 µg/l (HR: 5.4; CI 95%: 2.4–12.4), conversion to laparotomy (HR: 14.1; CI 95%: 4.0–49.0), and severe surgical complications (Clavien-Dindo III–IV) (HR: 2.9; CI 95%: 1.5–5.5) were identified as predictors of a diminished overall survival. Conclusion Laterality disclosed no significant effect on the overall prognosis of colon cancer patients. However, group differences and distinct survival predictors could be identified in rCC and lCC patients.

scholarly journals Association of chemotherapy with survival in stage II colon cancer patients who received radical surgery: a retrospective cohort study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Zhihao Lv ◽  
Yuqi Liang ◽  
Huaxi Liu ◽  
Delong Mo
Keyword(s):  
Colon Cancer ◽  
Overall Survival ◽  
Cancer Patients ◽  
Prediction Models ◽  
Radical Surgery ◽  
Survival Rates ◽  
Stage Ii ◽  
Survival Prediction ◽  
Stage Ii Colon Cancer ◽  
Overall Survival Rates

Abstract Background It remains controversial whether patients with Stage II colon cancer would benefit from chemotherapy after radical surgery. This study aims to assess the real effectiveness of chemotherapy in patients with stage II colon cancer undergoing radical surgery and to construct survival prediction models to predict the survival benefits of chemotherapy. Methods Data for stage II colon cancer patients with radical surgery were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Propensity score matching (1:1) was performed according to receive or not receive chemotherapy. Competitive risk regression models were used to assess colon cancer cause-specific death (CSD) and non-colon cancer cause-specific death (NCSD). Survival prediction nomograms were constructed to predict overall survival (OS) and colon cancer cause-specific survival (CSS). The predictive abilities of the constructed models were evaluated by the concordance indexes (C-indexes) and calibration curves. Results A total of 25,110 patients were identified, 21.7% received chemotherapy, and 78.3% were without chemotherapy. A total of 10,916 patients were extracted after propensity score matching. The estimated 3-year overall survival rates of chemotherapy were 0.7% higher than non- chemotherapy. The estimated 5-year and 10-year overall survival rates of non-chemotherapy were 1.3 and 2.1% higher than chemotherapy, respectively. Survival prediction models showed good discrimination (the C-indexes between 0.582 and 0.757) and excellent calibration. Conclusions Chemotherapy improves the short-term (43 months) survival benefit of stage II colon cancer patients who received radical surgery. Survival prediction models can be used to predict OS and CSS of patients receiving chemotherapy as well as OS and CSS of patients not receiving chemotherapy and to make individualized treatment recommendations for stage II colon cancer patients who received radical surgery.

Longer duration of symptoms at the time of presentation is not associated with worse survival in primary bone sarcoma

2018 ◽  
Vol 100-B (5) ◽  
pp. 652-661 ◽  
Author(s):  
J. M. Lawrenz ◽  
J. F. Styron ◽  
M. Parry ◽  
R. J. Grimer ◽  
N. W. Mesko
Keyword(s):  
Overall Survival ◽  
Proportional Hazards ◽  
Bone Sarcoma ◽  
Axial Skeleton ◽  
Cox Proportional Hazards ◽  
Low Grade ◽  
Duration Of Symptoms ◽  
Negative Effect ◽  
Primary Bone Sarcoma ◽  
Primary Bone

Aims The primary aim of this study was to determine the effect of the duration of symptoms (DOS) prior to diagnosis on the overall survival in patients with a primary bone sarcoma. Patients and Methods In a retrospective analysis of a sarcoma database at a single institution between 1990 and 2014, we identified 1446 patients with non-metastatic and 346 with metastatic bone sarcoma. Low-grade types of tumour were excluded. Our data included the demographics of the patients, the characteristics of the tumour, and the survival outcome of patients. Cox proportional hazards analysis and Kaplan–Meier survival analysis were performed, and the survivorship of the non-metastatic and metastatic cohorts were compared. Results In the non-metastatic cohort, a longer DOS was associated with a slightly more favourable survival (hazard ratio (HR) 0.996, 95% confidence interval (CI) 0.994 to 0.998, p < 0.001). In all types of tumour, there was no difference in survival between patients with a DOS of greater than four months and those with a DOS of less than four months (p = 0.566). There was no correlation between the year of diagnosis and survival (p = 0.741). A diagnosis of chondrosarcoma (HR 0.636, 95% CI 0.474 to 0.854, p = 0.003) had the strongest positive effect on survival, while location in the axial skeleton (HR 1.76, 95% CI 1.36 to 2.29, p < 0.001) had the strongest negative effect on survival. Larger size of tumour (HR 1.05, 95% CI 1.03 to 1.06, p < 0.001) and increased age of the patient (HR 1.02, 95% CI 1.01 to 1.03, p < 0.001) had a slightly negative effect on survival. Metastatic and non-metastatic cohorts had similar median DOS (16 weeks, p = 0.277), although the median survival (15.5 months vs 41 months) and rates of survival at one year (69% vs 89%) and five years (20% vs 59%) were significantly shorter in the metastatic cohort. Conclusion A longer DOS prior to diagnosis is not associated with a poorer overall survival in patients with a primary bone sarcoma. Location in the axial skeleton remains the strongest predictor of a worse prognosis. This may be helpful in counselling patients referred for evaluation on a delayed basis. Cite this article: Bone Joint J 2018;100-B:652–61.

scholarly journals Eps15 Homology Domain-Containing Protein 3 Hypermethylation as a Prognostic and Predictive Marker for Colorectal Cancer

Biomedicines ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 453
Author(s):  
Yu-Han Wang ◽  
Shih-Ching Chang ◽  
Muhamad Ansar ◽  
Chin-Sheng Hung ◽  
Ruo-Kai Lin
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Mrna Expression ◽  
Proportional Hazards ◽  
Uterine Cancer ◽  
Colonic Polyps ◽  
Predictive Marker ◽  
Cox Proportional Hazards ◽  
The Cancer Genome Atlas ◽  
Eps15 Homology Domain

Colorectal cancer (CRC) arises from chromosomal instability, resulting from aberrant hypermethylation in tumor suppressor genes. This study identified hypermethylated genes in CRC and investigated how they affect clinical outcomes. Methylation levels of specific genes were analyzed from The Cancer Genome Atlas dataset and 20 breast cancer, 16 esophageal cancer, 33 lung cancer, 15 uterine cancer, 504 CRC, and 9 colon polyp tissues and 102 CRC plasma samples from a Taiwanese cohort. In the Asian cohort, Eps15 homology domain-containing protein 3 (EHD3) had twofold higher methylation in 44.4% of patients with colonic polyps, 37.3% of plasma from CRC patients, and 72.6% of CRC tissues, which was connected to vascular invasion and high microsatellite instability. Furthermore, EHD3 hypermethylation was detected in other gastrointestinal cancers. In the Asian CRC cohort, low EHD3 mRNA expression was found in 45.1% of patients and was connected to lymph node metastasis. Multivariate Cox proportional-hazards survival analysis revealed that hypermethylation in women and low mRNA expression were associated with overall survival. In the Western CRC cohort, EHD3 hypermethylation was also connected to overall survival and lower chemotherapy and antimetabolite response rates. In conclusion, EHD3 hypermethylation contributes to the development of CRC in both Asian and Western populations.

scholarly journals A novel nomogram to predict the overall survival in esthesinoeroblastoma

2020 ◽  
Author(s):  
Lijie Jiang ◽  
Tengjiao Lin ◽  
Yu Zhang ◽  
Wenxiang Gao ◽  
Jie Deng ◽  
...  
Keyword(s):  
Overall Survival ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Validation Cohort ◽  
Risk Groups ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Cancer Center ◽  
P Value ◽  
Training Cohort

Abstract Background Increasing evidence indicates that the pathology and the modified Kadish system have some influence on the prognosis of esthesioneuroblastoma (ENB). However, an accurate system to combine pathology with a modified Kadish system has not been established. Methods This study aimed to set up and evaluate a model to predict overall survival (OS) accurately in ENB, including clinical characteristics, treatment and pathological variables. We screened the information of patients with ENB between January 1, 1976, and December 30, 2016 from the National Cancer Institute Surveillance, Epidemiology, and End Results (SEER) program as a training cohort. The validation cohort consisted of patients with ENB at Sun Yat-sen University Cancer Center and The First Affiliated Hospital of Sun Yat-sen University in the same period, and 87 patients were identified. The Pearson’s chi-squared test was used to assess significance of clinicopathological and demographic characteristics. We used the Cox proportional hazards model to examine univariate and multivariate analyses. The model coefficients were used to calculate the Hazard ratios (HR) with 95% confidence intervals (CI). Prognostic factors with a p- value < 0.05 in multivariate analysis were included in the nomogram. The concordance index (c-index) and calibration curve were used to evaluate the predictive power of the nomogram. Results The c-index of training cohort and validation cohort are 0.737 (95% CI, 0.709 to 0.765) and 0.791 (95% CI, 0.767 to 0.815) respectively. The calibration curves revealed a good agreement between the nomogram prediction and actual observation regarding the probability of 3-year and 5-year survival. We used a nomogram to calculate the 3-year and 5-year growth probability and stratified patients into three risk groups. Conclusions The nomogram provided the risk group information and identified mortality risk and can serve as a reference for designing a reasonable follow-up plan.

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