A nomogram to predict overall survival and disease-free survival after curative resection of gastric adenocarcinoma

Liver metastasis from hepatoid adenocarcinoma of the stomach: a case report and literature review

Hepatoid adenocarcinoma of the stomach (HAS) represents a rare malignant neoplasm sharing morphological and immunophenotypic similarities with hepatocellular carcinoma (HCC). Pathological morphology serves as the cornerstone for diagnosis, often accompanied by elevated alpha-fetoprotein (AFP) levels, nonspecific clinical symptoms, and imaging features reminiscent of gastric adenocarcinoma (GA). Liver metastases from HAS can mimic the enhancement patterns of HCC, posing challenges in differentiation from high-risk HCC cases. Conversely, HAS typically exhibits poorer prognostic outcomes compared to HCC and GA. This report presents a case of HAS with liver metastasis alongside a comprehensive literature review covering its pathology, molecular mechanisms, clinical presentations, and treatment modalities. Special focus is given to imaging characteristics and the utilization of radiomics for early-stage detection. The integration of imaging findings with laboratory results aids in HAS diagnosis, while radiomics provides novel insights for precise discrimination. In conclusion, the identification of distinct imaging markers distinguishing HAS from HCC and GA shows promise in facilitating optimal treatment strategies and improving patient outcomes.

Development and validation of nomogram for predicting early recurrence after radical gastrectomy of gastric cancer

BACKGROUND

After radical surgery, early detection of recurrence and metastasis is a crucial factor in enhancing the prognosis and survival of patients with gastric cancer (GC). Therefore, assessing the risk of recurrence in gastric cancer patients and determining the timing for postoperative recurrence is crucial.

METHODS

The clinicopathological data of 521 patients with recurrent gastric cancer, who underwent radical gastrectomy at Zhejiang Cancer Hospital between January 2010 and January 2017, were retrospectively analyzed. These patients were randomly divided into two groups: a training group (n = 365) and a validation group (n = 156). In the training set, patients were further categorized into early recurrence (n = 263) and late recurrence (n = 102) groups based on a 2-year boundary. Comparative analyses of clinicopathological features and prognoses were conducted between these two groups. Subsequently, a nomogram for predicting early recurrence was developed and validated.

RESULTS

In this study, the developed nomogram incorporated age, serous infiltration, lymph node metastasis, recurrence mode, and the tumour marker CA19-9. In the training cohort, the area under the curve (AUC value) was 0.739 (95% CI, 0.682-0.798), with a corresponding C-index of 0.739. This nomogram was subsequently validated in an independent validation cohort, yielding an AUC of 0.743 (95% CI, 0.652-0.833) and a C-index of 0.743. Furthermore, independent risk factors for prognosis were identified, including age, absence of postoperative chemotherapy, early recurrence, lymph node metastasis, abdominal metastasis, and vascular cancer embolus.

CONCLUSION

Independent risk factors for gastric cancer recurrence following radical surgery were utilized to construct a nomogram for predicting early relapse. This nomogram effectively assesses the risk of recurrence, aids in treatment decision-making and follow-up planning in clinical settings, and demonstrated strong performance in the validation cohort.

Prognostic significance of metastatic lymph node ratio in gastric cancer: a Western-center analysis

BACKGROUND

Tumor-node-metastasis (TNM) staging is the central gastric cancer (GC) staging system, but it has some disadvantages. However, the lymph node ratio (LNR) can be used regardless of the type of lymphadenectomy and is considered an important prognostic factor. This study aimed to evaluate the relationship between LNR and survival in patients who underwent curative GC surgery.

METHODS

All patients who underwent radical gastric surgery between January 2014 and June 2022 were retrospectively evaluated. Clinicopathological features of tumors, TNM stage, and survival rates were analyzed. LNR was defined as the ratio between metastatic lymph nodes and total lymph nodes removed. The LNR groups were classified as follows: LNR0 = 0, 0.01 < LNR1 ≤ 0.1, 0.1 < LNR2 ≤ 0.25 and LNR3 > 0.25. Tumor characteristics and overall survival (OS) of the patients were compared between LNR groups.

RESULTS

After exclusion, 333 patients were analyzed. The mean age was 62 ± 14 years. According to the LNR classification, no difference was found between groups regarding age and sex. However, TNM stage III disease was significantly more common in LNR3 patients. Most patients (43.2%, n = 144) were in the LNR3 group. In terms of tumor characteristics (lymphatic, vascular, and perineural invasion), the LNR3 group had significantly poorer prognostic factors. The Cox regression model defined LNR3, TNM stage II-III disease, and advanced age as independent risk factors for survival. Patients with LNR3 demonstrated the lowest 5-year OS rate (35.7%) (estimated mean survival was 30 ± 1.9 months) compared to LNR 0-1-2.

CONCLUSION

Our study showed that a high LNR was significantly associated with poor OS in patients who underwent curative gastrectomy. LNR can be used as an independent prognostic predictor in GC patients.

Fatty Acid Binding Protein 5 (FABP5) Promotes Aggressiveness of Gastric Cancer Through Modulation of Tumor Immunity

PURPOSE

Gastric cancer (GC) is the second most lethal cancer globally and is associated with poor prognosis. Fatty acid-binding proteins (FABPs) can regulate biological properties of carcinoma cells. FABP5 is overexpressed in many types of cancers; however, the role and mechanisms of action of FABP5 in GC remain unclear. In this study, we aimed to evaluate the clinical and biological functions of FABP5 in GC.

MATERIALS AND METHODS

We assessed FABP5 expression using immunohistochemical analysis in 79 patients with GC and evaluated its biological functions following in vitro and in vivo ectopic expression. FABP5 targets relevant to GC progression were determined using RNA sequencing (RNA-seq).

RESULTS

Elevated FABP5 expression was closely associated with poor outcomes, and ectopic expression of FABP5 promoted proliferation, invasion, migration, and carcinogenicity of GC cells, thus suggesting its potential tumor-promoting role in GC. Additionally, RNA-seq analysis indicated that FABP5 activates immune-related pathways, including cytokine-cytokine receptor interaction pathways, interleukin-17 signaling, and tumor necrosis factor signaling, suggesting an important rationale for the possible development of therapies that combine FABP5-targeted drugs with immunotherapeutics.

CONCLUSIONS

These findings highlight the biological mechanisms and clinical implications of FABP5 in GC and suggest its potential as an adverse prognostic factor and/or therapeutic target.

Prognostic and Predictive Model of the Log Odds of the Negative Lymph Node/T Stage Ratio in Resectable Gastric Adenocarcinoma Patients

PURPOSE

There are few reports on disease-specific survival (DSS) prediction systems for resected gastric cancer (GC) patients. The aim of this study was to create a nomogram based on the log odds of the negative lymph node/T stage ratio (LONT) for individual risk prediction.

METHODS

We applied the Surveillance, Epidemiology, and End Results (SEER) Program database released in 2021 to screen GC patients from 2010 to 2015. Using a competitive risk model, we plotted the cumulative risk curve of variables for gastric cancer-specific death and death from other causes at each time point. According to the minimum BIC, we constructed and assessed a nomogram for the 12-month, 36-month, and 60-month cumulative mortality probabilities assessed by time-dependent ROC curves (time-AUCs), the C-index, Brier scores, decision curve analysis (DCA), and calibration curves.

RESULTS

A total of 3895 patients were ultimately included and randomly assigned to two sets: the training set (n = 2726, 70%) and the validation set (n = 1169, 30%). The LONT was a remarkable independent predictor of gastric cancer-specific death (high versus low: 0.705, 95% CI 0.524-0.95, p = 0.021). The variables selected based on the minimum BIC were as follows: location, AJCC, AJCC.T, AJCC.N, radiotherapy, LONT.cat, and chemotherapy. According to the time-AUC, C-index, Brier score, DCA, and calibration curves, the nomogram risk score had excellent survival prediction ability for DSS.

CONCLUSIONS

A low LONT was associated with a high cumulative incidence of DSS. A prognostic nomogram model based on the LONT could effectively predict DSS for resectable GC patients.

Hypergastrinemia and mortality in gastric adenocarcinoma: a population-based cohort study, the HUNT study

Purpose: Hypergastrinemia increases the risk of developing proximal gastric adenocarcinoma. However, it is unclear if hypergastrinemia affects the survival in patients with gastric adenocarcinoma. This study aimed to examine the hypothesis that hypergastrinemia is associated with increased risk of mortality in patients with gastric adenocarcinoma.Materials and methods: This prospective population-based cohort study based on the Trøndelag Health Study (HUNT) included 78,962 adult individuals (≥20 years). During the baseline assessment period (1995-2008) of these participants, serum samples were collected and frozen. All participants with a newly diagnosed gastric adenocarcinoma in the cohort in 1995-2015 were identified and their gastrin levels were measured in the pre-diagnostic serum samples. Gastrin levels were analysed in relation to all-cause mortality until year 2020 using multivariable Cox regression providing hazard ratios (HRs) with 95% confidence intervals (CIs), adjusted for sex, age, body mass index (BMI), tobacco smoking, tumour stage, completeness of surgical resection, and peri-operative chemotherapy.Results: Among 172 patients with gastric adenocarcinoma, 81 (47%) had hypergastrinemia (serum gastrin >60 pmol/L) and 91 (53%) had normal gastrin level. The tumour location was proximal in 83 patients (43%) and distal in 78 (41%). Hypergastrinemia was not associated with any increased risk of all-cause mortality in all patients (adjusted HR 0.8, 95% CI 0.5-1.1), or in sub-groups of patients with proximal tumour location (HR 0.9, 95% CI 0.4-2.2) or distal tumour location (HR 0.9, 95% CI 0.5-1.7).Conclusion: This population-based cohort study indicates that hypergastrinemia may not increase the risk of mortality in patients with gastric adenocarcinoma.

The Survival Relationship between Preoperative Inflammation Markers and Patients with Special Pathological Types of Gastric Cancer

BACKGROUND

The preoperative PLR is closely associated with prognosis of gastric cancer. This aims to research whether the PLR could predict overall survival (OS) of gastric cancer (GC) patients with SRC component.

METHODS

The data were collected from Harbin Medical University Cancer Hospital between January 2001 and December 2013 in China. The patients were diagnosed with GC by pathologic examination, which contained SRC component in pathological organization. PLR is obtained from peripheral blood markers (platelets/lymphocytes).

RESULTS

There is a difference in OS between high PLR group and low group, which is verified by Kaplan-Meier analysis and log-rank tests (P < 0.001). Moreover, multivariate analysis prove PLR was independent prognostic factor for GC (HR = 1.384, 95% (CI): 1.048-1.828; P = 0.022). The preoperative PLR in stage I + II (P = 0.033), stage III (P < 0.001), SRC component lower than 50% (P < 0.001), SRC component equal to or higher than 50% (P = 0.044), and R0 resection (P < 0.001) GC are still effective.

CONCLUSION

PLR is a simple, useful, and repeatable predictor of OS in gastric cancer of stages I-III with SRC component and may help clinicians identify patients with high risk and develop a more reasonable follow-up plan.

Extensive Dissection at No. 12 Station During D2 Lymphadenectomy Improves Survival for Advanced Lower-Third Gastric Cancer: A Retrospective Study From a Single Center in Southern China

BACKGROUND

D2 lymphadenectomy including No. 12a dissection has been accepted as a standard surgical management of advanced lower-third gastric cancer (GC). The necessity of extensive No. 12 nodes (No. 12a, 12b, and 12p) dissection remains controversial. This study aims to explore its impact on long-term survival for resectable GC.

METHODS

From 2009 to 2016, 353 advanced lower-third GC patients undergoing at least D2 lymphadenectomy during a radical surgery were included, with 179 patients receiving No. 12a, 12b, and 12p dissection as study group. A total of 174 patients with No. 12a dissection were employed as control group. Surgical and long-term outcomes including 90-day complications incidence, therapeutic value index (TVI), 3-year progression-free survival (PFS), and 5-year overall survival (OS) were compared between both groups.

RESULTS

No. 12 lymph node metastasis was observed in 20 (5.7%) patients, with 10 cases in each group (5.6% vs. 5.7%, p = 0.948). The metastatic rates at No. 12a, 12b, and 12p were 5.7%, 2.2%, and 1.7%, respectively. The incidence of 90-day complications was identical between both groups. Extensive No. 12 dissection was associated with increased TVI at No. 12 station (3.9 vs. 0.6), prolonged 3-year PFS rate (67.0% vs. 55.9%, p = 0.045) and 5-year OS rate (66.2% vs. 54.0%, p = 0.027). The further Cox-regression analysis showed that the 12abp dissection was an independent prognostic factor of improved survival (p = 0.026).

CONCLUSION

Adding No. 12b and 12p lymph nodes to D2 lymphadenectomy might be effective in surgical treatment of advanced lower-third GC and improve oncological outcomes compared with No. 12a-based D2 lymphadenectomy.

Dynamic Prediction of Survival after Curative Resection of Gastric Adenocarcinoma: A landmarking-based analysis

BACKGROUND

Accurate estimation of survival and recurrence are important to inform decisions regarding therapy and surveillance. We sought to design and validate a dynamic prognostic model for patients undergoing resection for gastric adenocarcinoma.

METHODS

Patients who underwent curative-intent surgery for gastric adenocarcinoma between 2000 and 2020 were identified using a multi-institutional database. Landmark analysis was used to create dynamic OS and DFS prediction models. Model performance was internally cross-validated via bootstrap resampling.

RESULTS

Among 895 patients, 507 (57.2%) patients underwent partial gastrectomy (n = 507, 57.2%) while 380 (42.8%) had total gastrectomy. Median tumor size was 40 mm (IQR: 25-65), most tumors were located in the antrum (n = 344, 39.5%) and infiltrated the subserosa (T3 tumors: n = 283, 31.9%) or serosa (T4 tumors: n = 253, 28.5%); lymph node metastasis occurred in 528 (59.1%) patients. Median OS and DFS were 17.5 (IQR: 7.5-42.8) and 14.3 months (IQR: 6.5-39.9), respectively. The impact of age, sex, preoperative comorbidities, tumor size and location, extent of lymphadenectomy and total number of lymph nodes examined, Lauren class, T and N category, postoperative complications, and tumor recurrence varied over time (all p < 0.05). An online tool to predict dynamic OS and DFS based on patient survival relative to time survived was developed and made available for clinical use. Discrimination ability of OS and DFS was excellent (C-index: 0.84 and 0.86, respectively) and calibration plots revealed good prediction.

CONCLUSIONS

An online dynamic prognostic tool was developed and validated to predict OS and DFS following resection of gastric adenocarcinoma. Landmark analysis to predict long-term outcomes based on follow-up time may be helpful to surgeons and patients.

Validation of a Nomogram to Predict Long Term Outcomes After Curative Surgery for Gastric Cancer in an Italian Cohort of Patients

AIM OF THE STUDY

Nomograms have been proposed to assess prognosis following curative surgery for gastric cancer. The objective of the current study was to evaluate the performance of the Gastric Cancer Collaborative Group nomograms developed in 2014 by Kim et al., using a cohort of patients from a 10-year single institution experience in gastric cancer management.

PATIENTS AND METHODS

We retrospectively reviewed patients who underwent curative-intent surgery for histologically confirmed gastric cancer at First Surgical Clinic of Padua University Hospital (Italy) from January 2010 to May 2020. Univariable and multivariable Cox proportional hazard models were employed to assess the effect of the variables of interest on mortality and recurrence. Multivariable analysis was performed by considering the variables included in the Gastric Cancer Collaborative Group nomograms in order to validate them. The performance of the nomograms was evaluated using Harrell's C-index and calibration plots.

RESULTS

Overall, 168 patients were included, with a median follow-up of 20.1 months. On multivariable analysis, tumor location, lymph node ratio, and pathological T stage were associated with recurrence; age, tumor location, lymph node ratio, and pT stage were associated with OS (overall survival). The nomograms had good discriminatory capability to classify both OS (C-index: 0.75) and DFS (disease-free survival) (C-index 0.72). The corrected C-Index for DFS based on the AJCC staging system revealed better prediction (C-Index 0.75), while the corrected C-Index for OS had worse discrimination ability compared with the current nomogram (C-Index 0.72).

CONCLUSIONS

The Gastric Cancer Collaborative Group nomograms demonstrated good performances in terms of prediction of both OS and DFS on external validation. The two nomograms are easy to apply, and variables included are widely available to most facilities.

A nomogram to predict overall survival and disease-free survival after curative-intent gastrectomy for gastric cancer

An individual prediction of DFS and OS may be useful after surgery for gastric cancer to inform patients and to guide the clinical management. Patients who underwent curative-intent resection for gastric cancer between January 2010 and May 2020 at a single Italian institution were identified. Variables associated with OS and DFS were recorded and analysed according to univariable and multivariable Cox models. Nomograms predicting OS and DFS were built according to variables resulting from multivariable Cox models. Discrimination ability was calculated using the Harrell's Concordance Index. Overall, 168 patients underwent curative-intent resection. Nomograms to predict OS were developed including age, tumor size, tumor location, T stage, N stage, M stage and post-operative complications, while nomogram to predict DFS includes Lauren classification, and lymph node ratio (LNR). On internal validation, both nomograms demonstrated a good discrimination with a Harrell's C-index of 0.77 for OS and 0.71 for DFS. The proposed nomogram to predict DFS and OS after curative-intent surgery for gastric cancer showed a good discrimination on internal validation, and may be useful to guide clinician decision-making, as well help identify patients with high-risk of recurrence or with a poor estimated survival.

Development of a Prognostic Nomogram and Nomogram Software Application Tool to Predict Overall Survival and Disease-Free Survival After Curative-Intent Gastrectomy for Gastric Cancer

BACKGROUND

We sought to derive and validate a prediction model of survival and recurrence among Western patients undergoing resection of gastric cancer.

METHODS

Patients who underwent curative-intent surgery for gastric cancer at seven US institutions and a major Italian center from 2000 to 2020 were included. Variables included in the multivariable Cox models were identified using an automated model selection procedure based on an algorithm. Best models were selected using the Bayesian information criterion (BIC). The performance of the models was internally cross-validated via the bootstrap resampling procedure. Discrimination was evaluated using the Harrell's Concordance Index and accuracy was evaluated using calibration plots. Nomograms were made available as online tools.

RESULTS

Overall, 895 patients met inclusion criteria. Age (hazard ratio [HR] 1.47, 95% confidence interval [CI] 1.17-1.84), presence of preoperative comorbidities (HR 1.66, 95% CI 1.14-2.41), lymph node ratio (LNR; HR 1.72, 95% CI 1.42-2.01), and lymphovascular invasion (HR 1.81, 95% CI 1.33-2.45) were associated with overall survival (OS; all p < 0.01), whereas tumor location (HR 1.93, 95% CI 1.23-3.02), T category (Tis-T1 vs. T3: HR 0.31, 95% CI 0.14-0.66), LNR (HR 1.82, 95% CI 1.45-2.28), and lymphovascular invasion (HR 1.49; 95% CI 1.01-2.22) were associated with disease-free survival (DFS; all p < 0.05) The models demonstrated good discrimination on internal validation relative to OS (C-index 0.70) and DFS (C-index 0.74).

CONCLUSIONS

A web-based nomograms to predict OS and DFS among gastric cancer patients following resection demonstrated good accuracy and discrimination and good performance on internal validation.

Dual-region radiomics signature: Integrating primary tumor and lymph node computed tomography features improves survival prediction in esophageal squamous cell cancer

BACKGROUND

Preoperative prognostic biomarkers to guide individualized therapy are still in demand in esophageal squamous cell cancer (ESCC). Some studies reported that radiomic analysis based on CT images has been successfully performed to predict individual survival in EC. The aim of this study was to assess whether combining radiomics features from primary tumor and regional lymph nodes predicts overall survival (OS) better than using single-region features only, and to investigate the incremental value of the dual-region radiomics signature.

METHODS

In this retrospective study, three radiomics signatures were built from preoperative enhanced CT in a training cohort (n = 200) using LASSO Cox model. Associations between each signature and survival was assessed on a validation cohort (n = 107). Prediction accuracy for the three signatures was compared. By constructing a clinical nomogram and a radiomics-clinical nomogram, incremental prognostic value of the radiomics signature over clinicopathological factors in OS prediction was assessed in terms of discrimination, calibration, reclassification and clinical usefulness.

RESULTS

The dual-region radiomic signature was an independent factor, significantly associated with OS (HR: 1.869, 95% CI: 1.347, 2.592, P = 1.82e-04), which achieved better OS (C-index: 0.611) prediction either than the single-region signature (C-index:0.594-0.604). The resulted dual-region radiomics-clinical nomogram achieved the best discriminative ability in OS prediction (C-index:0.700). Compared with the clinical nomogram, the radiomics-clinical nomogram improved the calibration and classification accuracy for OS prediction with a total net reclassification improvement (NRI) of 26.9% (P=0.008) and integrated discrimination improvement (IDI) of 6.8% (P<0.001).

CONCLUSION

The dual-region radiomic signature is an independent prognostic marker and outperforms single-region signature in OS for ESCC patients. Integrating the dual-region radiomics signature and clinicopathological factors improves OS prediction.

A novel nomogram based on cardia invasion and chemotherapy to predict postoperative overall survival of gastric cancer patients

Background

We aimed to establish and externally validate a nomogram to predict the 3- and 5-year overall survival (OS) of gastric cancer (GC) patients after surgical resection.

Methods

A total of 6543 patients diagnosed with primary GC during 2004–2016 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. We grouped patients diagnosed during 2004–2012 into a training set (n = 4528) and those diagnosed during 2013–2016 into an external validation set (n = 2015). A nomogram was constructed after univariate and multivariate analysis. Performance was evaluated by Harrell’s C-index, area under the receiver operating characteristic curve (AUC), decision curve analysis (DCA), and calibration plot.

Results

The multivariate analysis identified age, race, location, tumor size, T stage, N stage, M stage, and chemotherapy as independent prognostic factors. In multivariate analysis, the hazard ratio (HR) of non-cardia invasion was 0.762 (P < 0.001) and that of chemotherapy was 0.556 (P < 0.001). Our nomogram was found to exhibit excellent discrimination: in the training set, Harrell’s C-index was superior to that of the 8th American Joint Committee on Cancer (AJCC) TNM classification (0.736 vs 0.699, P < 0.001); the C-index was also better in the validation set (0.748 vs 0.707, P < 0.001). The AUCs for 3- and 5-year OS were 0.806 and 0.815 in the training set and 0.775 and 0.783 in the validation set, respectively. The DCA and calibration plot of the model also shows good performance.

Conclusions

We established a well-designed nomogram to accurately predict the OS of primary GC patients after surgical resection. We also further confirmed the prognostic value of cardia invasion and chemotherapy in predicting the survival rate of GC patients.

Establishment of the Radiologic Tumor Invasion Index Based on Radiomics Splenic Features and Clinical Factors to Predict Serous Invasion of Gastric Cancer

Background

Currently, there are shortcomings in diagnosing gastric cancer with or without serous invasion, making it difficult for patients to receive appropriate treatment. Therefore, we aimed to develop a radiomic nomogram for preoperative identification of serosal invasion.

Methods

We selected 315 patients with gastric cancer, confirmed by pathology, and randomly divided them into two groups: the training group (189 patients) and the verification group (126 patients). We obtained patient splenic imaging data for the training group. A p-value of <0.05 was considered significant for features that were selected for lasso regression. Eight features were chosen to construct a serous invasion prediction model. Patients were divided into high- and low-risk groups according to the radiologic tumor invasion risk score. Subsequently, univariate and multivariate regression analyses were performed with other invasion-related factors to establish a visual combined prediction model.

Results

The diagnostic accuracy of the radiologic tumor invasion score was consistent in the training and verification groups (p<0.001 and p=0.009, respectively). Univariate and multivariate analyses of invasion risk factors revealed that the radiologic tumor invasion index (p=0.002), preoperative hemoglobin <100 (p=0.042), and the platelet and lymphocyte ratio <92.8 (p=0.031) were independent risk factors for serosal invasion in the training cohort. The prediction model based on the three indexes accurately predicted the serosal invasion risk with an area under the curve of 0.884 in the training cohort and 0.837 in the testing cohort.

Conclusions

Radiological tumor invasion index based on splenic imaging combined with other factors accurately predicts serosal invasion of gastric cancer, increases diagnostic precision for the most effective treatment, and is time-efficient.

Multi-Institutional Development and External Validation of a Nomogram for Prediction of Extrahepatic Recurrence After Curative-Intent Resection for Hepatocellular Carcinoma

BACKGROUNDS

Extrahepatic recurrence of hepatocellular carcinoma (HCC) after surgical resection is associated with unfavorable prognosis. The objectives of the current study were to identify the risk factors and develop a nomogram for the prediction of extrahepatic recurrence after initial curative surgery.

METHODS

A total of 635 patients who underwent curative-intent resection for HCC between 2000 and 2017 were identified from an international multi-institutional database. The clinicopathological characteristics, risk factors, and long-term survival of patients with extrahepatic recurrence were analyzed. A nomogram for the prediction of extrahepatic recurrence was established and validated in 144 patients from an external cohort.

RESULTS

Among the 635 patients in the derivative cohort, 283 (44.6%) experienced recurrence. Among patients who recurred, 80 (28.3%) patients had extrahepatic ± intrahepatic recurrence, whereas 203 (71.7%) had intrahepatic recurrence only. Extrahepatic recurrence was associated with more advanced initial tumor characteristics, early recurrence, and worse prognosis versus non-extrahepatic recurrence. A nomogram for the prediction of extrahepatic recurrence was developed using the β-coefficients from the identified risk factors, including neutrophil-to-lymphocyte ratio, multiple lesions, tumor size, and microvascular invasion. The nomogram demonstrated good ability to predict extrahepatic recurrence (c-index: training cohort 0.786; validation cohort: 0.845). The calibration plots demonstrated good agreement between estimated and observed extrahepatic recurrence (p = 0.658).

CONCLUSIONS

An externally validated nomogram was developed with good accuracy to predict extrahepatic recurrence following curative-intent resection of HCC. This nomogram may help identify patients at high risk of extrahepatic recurrence and guide surveillance protocols as well as adjuvant treatments.

The log odds of negative lymph nodes/T stage: a new prognostic and predictive tool for resected gastric cancer patients

Purpose

When only the TNM classification is used to predict survival in gastric cancer (GC) patients, the impact of the degree of lymphadenectomy on the prognosis is neglected. This study aimed to establish a more effective nomogram based on the log odds of negative lymph nodes/T stage ratio (LONT) to predict survival in surgically treated GC patients.

Methods

The data of resected GC patients were extracted from the Surveillance, Epidemiology, and End Results Program (SEER) database. Univariate and multivariate Cox regression analyses were used to identify the significant prognostic factors. The prognostic performance was assessed using a calibration plot, concordance index (C-index), and area under the (time-dependent receiver operating characteristic) curve (AUC) to compare the predicted survival probability based on the nomogram score groups.

Results

The results showed LONT as an independent prognostic factor for cancer-specific survival (CSS) and overall survival (OS), independent of clinicopathological factors. After removing potential redundancy, only LONT, T stage, N stage, location and age were used in the final nomogram model. The model had a higher C-index (0.736 ± 0.012) and AUC (0.798) than the TNM staging system (0.685 ± 0.012 and 0.744). The nomogram score could predict a significant survival difference between any two adjacent groups in terms of CSS and OS.

Conclusion

High LONT is associated with improved survival of gastric cancer patients, independent of other clinicopathological factors. The prognostic nomogram model based on LONT could effectively predict CSS and OS for resectable GC patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00432-021-03654-y.

Development and Validation of a Nomogram for Preoperative Prediction of Localization of Neonatal Gastrointestinal Perforation

Background: Information regarding the localization of gastrointestinal perforation is crucial for the following surgical procedure. This study was to determine the key indicators and develop a prediction model for the localization in neonates with gastrointestinal perforation. Methods: A nomogram to predict the location of neonatal gastrointestinal perforation was developed using a cohort of patients who underwent surgery between July 2009 and May 2021. Baseline variables were analyzed using logistics regression and nomogram developed using significant predictors. The predictive performance of the nomogram was assessed by the concordance index (C-index), calibration curve, and area under the receiver operating characteristic (ROC) curve (AUC). The nomogram was further validated in an integrated external cohort. Results: We investigated the data of 201 patients, of which 65 (32.3%) were confirmed with upper gastrointestinal perforation by surgery. Multivariate logistic regression analysis identified the following as independent predictors: preterm [OR: 5.014 (1.492-18.922)], time of onset [OR: 0.705 (0.582-0.829)], preoperative hemoglobin [OR:1.017 (1.001-1.033)], bloody stool: No [OR: 4.860 (1.270-23.588)], shock [OR: 5.790 (1.683-22.455)] and sepsis: No [OR 3.044 (1.124-8.581)]. Furthermore, the nomogram was effective in predicting the perforation site, with an AUC of 0.876 [95% confidence interval (CI): 0.830-0.923]. Internal validation showed that the average AUC was 0.861. Additionally, the model achieved satisfactory discrimination (AUC, 0.900; 95% CI, 0.826-0.974) and calibration (Hosmer-Lemeshow test, P = 0.4802) in external validation. Conclusions: The nomogram based on the six factors revealed good discrimination and calibration, suggesting good clinical utility. The nomogram could help surgeons predict the location of gastrointestinal perforation before surgery to make a surgical plan.

Preoperative computed tomography-guided disease-free survival prediction in gastric cancer: a multicenter radiomics study

PURPOSE

Preoperative and noninvasive prognosis evaluation remains challenging for gastric cancer. Novel preoperative prognostic biomarkers should be investigated. This study aimed to develop multidetector-row computed tomography (MDCT)-guided prognostic models to direct follow-up strategy and improve prognosis.

METHODS

A retrospective dataset of 353 gastric cancer patients were enrolled from two centers and allocated to three cohorts: training cohort (n = 166), internal validation cohort (n = 83), and external validation cohort (n = 104). Quantitative radiomic features were extracted from MDCT images. The least absolute shrinkage and selection operator penalized Cox regression was adopted to construct a radiomic signature. A radiomic nomogram was established by integrating the radiomic signature and significant clinical risk factors. We also built a preoperative tumor-node-metastasis staging model for comparison. All models were evaluated considering the abilities of risk stratification, discrimination, calibration, and clinical use.

RESULTS

In the two validation cohorts, the established four-feature radiomic signature showed robust risk stratification power (P = 0.0260 and 0.0003, log-rank test). The radiomic nomogram incorporated radiomic signature, extramural vessel invasion, clinical T stage, and clinical N stage, outperforming all the other models (concordance index = 0.720 and 0.727) with good calibration and decision benefits. Also, the 2-yr disease-free survival (DFS) prediction was most effective (time-dependent area under curve = 0.771 and 0.765). Moreover, subgroup analysis indicated that the radiomic signature was more sensitive in risk stratifying patients with advanced clinical T/N stage.

CONCLUSIONS

The proposed MDCT-guided radiomic signature was verified as a prognostic factor for gastric cancer. The radiomic nomogram was a noninvasive auxiliary model for preoperative individualized DFS prediction, holding potential in promoting treatment strategy and clinical prognosis.

Development and validation of an artificial neural network prognostic model after gastrectomy for gastric carcinoma: An international multicenter cohort study

BACKGROUND

Recently, artificial neural network (ANN) methods have also been adopted to deal with the complex multidimensional nonlinear relationship between clinicopathologic variables and survival for patients with gastric cancer. Using a multinational cohort, this study aimed to develop and validate an ANN-based survival prediction model for patients with gastric cancer.

METHODS

Patients with gastric cancer who underwent gastrectomy in a Chinese center, a Japanese center, and recorded in the Surveillance, Epidemiology, and End Results database, respectively, were included in this study. Multilayer perceptron neural network was used to develop the prediction model. Time-dependent receiver operating characteristic (ROC) curves, area under the curves (AUCs), and decision curve analysis (DCA) were used to compare the ANN model with previous prediction models.

RESULTS

An ANN model with nine input nodes, nine hidden nodes, and two output nodes was constructed. These three cohort's data showed that the AUC of the model was 0.795, 0.836, and 0.850 for 5-year survival prediction, respectively. In the calibration curve analysis, the ANN-predicted survival had a high consistency with the actual survival. Comparison of the DCA and time-dependent ROC between the ANN model and previous prediction models showed that the ANN model had good and stable prediction capability compared to the previous models in all cohorts.

CONCLUSIONS

The ANN model has significantly better discriminative capability and allows an individualized survival prediction. This model has good versatility in Eastern and Western data and has high clinical application value.

A Novel Diagnostic Nomogram for Noninvasive Evaluating Liver Fibrosis in Patients with Chronic Hepatitis B Virus Infection

Objective

To establish a novel nomogram for diagnosing liver fibrosis in patients with chronic hepatitis B virus (HBV) infection and verify the diagnostic performance of the established nomogram.

Methods

Patients with chronic HBV infection who met the inclusion and exclusion criteria were enrolled in this retrospective study; 70% and 30% of patients were randomly assigned to training dataset and validation dataset, respectively. The risk factors for liver fibrosis were screened using the univariate and multivariate logistic regression analyses. Based on the results, a nomogram was established and verified.

Results

508 patients with chronic HBV infection were included in this study (n = 355 for training dataset and n = 153 for validation dataset). The logistic regression analysis showed that liver stiffness measurement (LSM), platelet (PLT) count, and prothrombin time (PT) were independent risk factors for liver fibrosis (P < 0.01), which were used to establish the nomogram. The consistency index (C-index) of the nomogram established for diagnosing liver fibrosis was 0.875. The calibration line and the ideal line were consistent, which indicated that diagnosis of liver fibrosis by the established model was accurate. The values of area under the receiver operator characteristic (ROC) curve (AUROC) for diagnosing liver fibrosis by the nomogram were 0.857 and 0.862 in the training dataset and validation dataset, respectively, which were noticeably higher than those in the well-known serological models, including the aspartate aminotransferase- (AST-) to-platelet ratio index (APRI) scoring model, fibrosis-4 (FIB-4) scoring model, APAG model (including age, PT, albumin, and γ-glutamyl transferase), and S-index model (all P < 0.05).

Conclusion

LSM, PT, and PLT were found as independent risk factors for liver fibrosis. The established nomogram exhibited an excellent diagnostic performance, and it can more visually and individually evaluate the probability of liver fibrosis in patients with chronic HBV infection.

Fatty Acid Oxidation Controls CD8+ Tissue-Resident Memory T-cell Survival in Gastric Adenocarcinoma

The success of checkpoint inhibitors in cancer treatment is associated with the infiltration of tissue-resident memory T (Trm) cells. In this study, we found that about 30% of tumor-infiltrating lymphocytes (TIL) in the tumor microenvironment of gastric adenocarcinoma were CD69⁺CD103⁺ Trm cells. Trm cells were low in patients with metastasis, and the presence of Trm cells was associated with better prognosis in patients with gastric adenocarcinoma. Trm cells expressed high PD-1, TIGIT, and CD39 and represented tumor-reactive TILs. Instead of utilizing glucose, Trm cells relied on fatty acid oxidation for cell survival. Deprivation of fatty acid resulted in Trm cell death. In a tumor cell-T-cell coculture system, gastric adenocarcinoma cells outcompeted Trm cells for lipid uptake and induced Trm cell death. Targeting PD-L1 decreased fatty acid binding protein (Fabp) 4 and Fabp5 expression in tumor cells of gastric adenocarcinoma. In contrast, the blockade of PD-L1 increased Fabp4/5 expression in Trm cells, promoting lipid uptake by Trm cells and resulting in better survival of Trm cells in vitro and in vivo. PD-L1 blockade unleashed Trm cells specifically in the patient-derived xenograft (PDX) mice. PDX mice that did not respond to PD-L1 blockade had less Trm cells than responders. Together, these data demonstrated that Trm cells represent a subset of TILs in the antitumor immune response and that metabolic reprogramming could be a promising way to prolong the longevity of Trm cells and enhance antitumor immunity in gastric adenocarcinoma.

A SEER population analysis of stage IB resected gastric cancer: who can benefit from adjuvant therapy?

Objective: The benefit of adjuvant therapy (AT) remains controversial in stage IB gastric cancer (GC). This study aimed to offer a reference for the rational indications of AT.Methods: We retrospectively included 1216 stage IB GC who experienced curative surgery from the SEER database between 2004 and 2015. These patients were allocated into two groups: Group AT and Group surgery alone (Group SA). We established a nomogram to predict OS and then divided whole cohort into low-risk and high-risk groups based on the OS predicted by the nomogram.Results: Six variables, which were significantly related with OS of entire patients after matched, were incorporated in the nomogram. These variables were age, examined lymph nodes, tumor site, marital, family income and stage IB. The C-index of the model was 0.637 and the calibration curve showed that the anticipated values were in accordance with the actual values. The decision curve demonstrated that the optimal clinical impact was achieved when the threshold possibility was 0-56%. Then, the entire cohort was separated into low-risk (≤159 points) as well as high-risk (>159 points) groups based on the projected 5-year OS of recursive partitioning analysis. Group SA revealed a significantly poorer OS than Group AT for high-risk patients (p < .001); on the other hand, there was a comparable OS for low-risk patients (p = .361).Conclusions: We have developed an effective, intuitional and applied prognostic tool to clinical decision-making. For stage IB GC after surgical resection, AT was only recommended for high-risk patients. However, AT may be dispensable for low-risk patients.

Nomogram for predicting the survival of gastric adenocarcinoma patients who receive surgery and chemotherapy

Background

Surgery is the only way to cure gastric adenocarcinoma (GAC), and chemotherapy is the basic adjuvant management for GAC. A significant prognostic nomogram for predicting the respective disease-specific survival (DSS) rates of GAC patients who receive surgery and chemotherapy has not been established.

Objective

We were planning to establish a survival nomogram model for GAC patients who receive surgery and chemotherapy.

Methods

We identified 5764 GAC patients who had received surgery and chemotherapy from the record of Surveillance, Epidemiology, and End Results (SEER) database. About 70% (n = 4034) of the chosen GAC patients were randomly assigned to the training set, and the rest of the included ones (n = 1729) were assigned to the external validation set. A prognostic nomogram was constructed by the training set and the predictive accuracy of it was validated by the validation set.

Results

Based on the outcome of a multivariate analysis of candidate factors, a nomogram was developed that encompassed age at diagnosis, number of regional lymph nodes examined after surgery, number of positive regional lymph nodes, sex, race, grade, derived AJCC stage, summary stage, and radiotherapy status. The C-index (Harrell’s concordance index) of the nomogram model was some larger than that of the traditional seventh AJCC staging system (0.707 vs 0.661). Calibration plots of the constructed nomogram displayed that the probability of DSS commendably accord with the survival rate. Integrated discrimination improvement (IDI) revealed obvious increase and categorical net reclassification improvement (NRI) showed visible enhancement. IDI for 3-, 5- and 10- year DSS were 0.058, 0.059 and 0.058, respectively (P > 0.05), and NRI for 3-, 5- and 10- year DSS were 0.380 (95% CI = 0.316–0.470), 0.407 (95% CI = 0.350–0.505), and 0.413 (95% CI = 0.336–0.519), respectively. Decision curve analysis (DCA) proved that the constructed nomogram was preferable to the AJCC staging system.

Conclusion

The constructed nomogram supplies more credible DSS predictions for GAC patients who receive surgery and chemotherapy in the general population. According to validation, the new nomogram will be beneficial in facilitating individualized survival predictions and useful when performing clinical decision-making for GAC patients who receive surgery and chemotherapy.

Development and validation of a nomogram for predicting overall survival of node-negative ampullary carcinoma

BACKGROUND

The accuracy of the current staging system for predicting the overall survival (OS) of patients with ampullary carcinoma (AC) is still unsatisfactory, especially in node-negative (N0) patients. We aimed at establishing a nomogram to accurately predict OS in N0 AC.

METHODS

This study enrolled 697 N0 AC patients from the Surveillance, Epidemiology, and End Results database (design cohort [DC], n = 697) and the First Affiliated Hospital of Sun Yat-sen University (validation cohort [VC], n = 112), who underwent surgical resection. The nomogram was established by using prognostic factors determined by univariate and multivariate regression analyses.

RESULTS

The nomogram for OS was developed by using four independent prognostic factors, including age, grade, T stage, and a number of examined lymph nodes. The C-index of a nomogram for OS in DC and VC was 0.665 and 0.731, respectively. Calibration curves showed good consistency of the nomogram. The nomogram had a better accuracy in predicting OS compared with conventional staging system (P < .05). On the basis of nomogram-predicted scores, the patients were stratified into groups with different risk. The OS of low-risk patients was significantly longer than high-risk ones (P ≤ .010).

CONCLUSIONS

The nomogram could be used to predict the OS of N0 AC. It could help guide further treatment in clinical practice.

Prognostic nomogram based on log odds of positive lymph nodes for gastric carcinoma patients after surgical resection

Aim: To build a prognostic nomogram based on log odds of positive lymph nodes for patients with gastric carcinoma (GC) after resection, and to compare the predictive performance with the American Joint Committee on Cancer (AJCC) staging system and lymph node ratio (LNR). Methods: Multivariate analyses were performed to identify the independent variables for cancer-specific survival (CSS). A nomogram was constructed based on independent clinicopathological factors. Results: The C-indices for predicting CSS were 0.674 in development cohort and 0.647 in validation cohort, which were higher than that of the AJCC staging system and LNR. Conclusion: The nomogram was more accurate than the AJCC staging system and LNR for predicting CSS in patients undergoing resection for GC.

Construction of a nomogram for the prediction of prognosis in patients with resectable gastric cancer undergoing fewer than sixteen lymph node biopsies

Background

Lymph node metastases evaluation is important for assessing gastric cancer prognosis. In patients not undergoing adequate lymph node biopsy, lymph node stage migration occurs with the use of the existing staging system. This study established a prediction model to improve prognostication in patients undergoing fewer than 16 lymph nodes biopsy.

Patients and methods

In total, 3036 eligible patients from the Surveillance, Epidemiology, and End Results Program database were evaluated. They were randomized into development and validation sets in a 1:1 ratio (n=1520 and 1516, respectively). To avoid model overfitting and loss of important factors, prognostic factors related to overall survival (OS) were screened according to the Akaike information criterion. The nomogram was assessed using discrimination and consistency tests in the development and validation sets; the concordance index (C-index), calibration curves, and receiver operating characteristic (ROC) curves were also evaluated. Comparison with the 7th American Joint Committee on Cancer (AJCC) staging system was based on Kaplan–Meier curves, ROC, risk stratification, and decision curve analysis (DCA).

Results

Age, race, degree of differentiation, invasion depth, chemotherapy, radiotherapy, and lymph node ratio were independent prognostic factors in OS. C-indices of the development and validation sets were 0.759 (95% CI: 0.741–0.777) and 0.742 (95% CI: 0.713–0.771), respectively; calibration curves were approximately 45° diagonal, indicating good predictive ability of the nomogram. In contrast to the 7th AJCC staging system, the Kaplan–Meier curves and risk stratification of the nomogram had better discrimination ability, the ROC curves of the nomogram achieved more predictive accuracy, and the DCA indicated that the nomogram conferred higher net benefit.

Conclusion

Our constructed nomogram predicts the prognosis of patients with resectable gastric cancer undergoing biopsy of fewer than 16 lymph nodes more precisely and has better clinical applicability than the 7th AJCC staging system.

Perioperative risk calculator for distal gastrectomy predicts overall survival in patients with gastric cancer

BACKGROUND

Although some predictive factors of long-term survival after a distal gastrectomy for gastric cancer have been reported, only few studies have predicted long-term outcomes based on preoperative parameters. We aimed to evaluate the reliability of perioperative risk calculator for predicting overall survival (OS) after distal gastrectomy in patients with gastric cancer.

METHODS

Overall, 337 patients (225 males, 112 females) who had undergone a distal gastrectomy for gastric cancer at the Keio University Hospital, Tokyo, Japan, between January 2009 and December 2013 were enrolled in this study. We investigated the reliability of a risk calculator for the prediction of OS.

RESULTS

In multivariate analysis, the risk models for operative mortality and 30-day mortality were identified as predictors of death. Time-dependent receiver operating characteristics (ROC) curve analysis indicated that the estimated area under the curve (AUC) value of the risk model for operative mortality was > 0.870 during the first postoperative 3 years. We set optimal cutoff values of the risk model operative mortality for OS using the Cutoff Finder online tool. The cutoff values of 4.117% were significant risk factors of death. Similar results were observed in the external validation set.

CONCLUSIONS

We elucidated the associations among risk calculator values and OS rates of patients with gastric cancer. Time-dependent ROC curve analysis suggested that the AUC value of the risk model for operative mortality was high, indicating that this risk calculator would be useful for not only short-term outcomes, but also long-term outcomes.

Prognostic and Predictive Factors for the Curative Treatment of Esophageal and Gastric Cancer in Randomized Controlled Trials: A Systematic Review and Meta-Analysis

BACKGROUND

An overview of promising prognostic variables and predictive subgroups concerning the curative treatment of esophageal and gastric cancer from randomized controlled trials (RCTs) is lacking. Therefore, we conducted a systematic review and meta-analysis.

METHODS

PubMed, EMBASE, CENTRAL, and ASCO/ESMO conferences were searched up to March 2019 for RCTs on the curative treatment of esophageal or gastric cancer with data on prognostic and/or predictive factors for overall survival. Prognostic factors were deemed potentially clinically relevant according to the following criteria; (1) statistically significant (p < 0.05) in a multivariate analysis, (2) reported in at least 250 patients, and (3) p < 0.05, in ≥ 33% of the total number of patients in RCTs reporting this factor. Predictive factors were potentially clinically-relevant if (1) the p-value for interaction between subgroups was <0.20 and (2) the hazard ratio in one of the subgroups was significant (p < 0.05).

RESULTS

For gastric cancer, 39 RCTs were identified (n = 13,530 patients) and, for esophageal cancer, 33 RCTs were identified (n = 8618 patients). In total, we identified 23 potentially clinically relevant prognostic factors for gastric cancer and 16 for esophageal cancer. There were 15 potentially clinically relevant predictive factors for gastric cancer and 10 for esophageal cancer.

CONCLUSION

The identified prognostic and predictive factors can be included and analyzed in future RCTs and be of guidance for nomograms. Further validation should be performed in large patient cohorts.

Genome-wide identification of a novel miRNA-based signature to predict recurrence in patients with gastric cancer

The current tumor node metastasis (TNM) staging system is inadequate for identifying high-risk gastric cancer (GC) patients. Using a systematic and comprehensive-biomarker discovery and validation approach, we attempted to build a microRNA (miRNA)-recurrence classifier (MRC) to improve the prognostic prediction of GC. We identified 312 differentially expressed miRNAs in 446 GC tissues compared to 45 normal controls by analyzing high-throughput data from The Cancer Genome Atlas (TCGA). Using a Cox regression model, we developed an 11-miRNA signature that could successfully discriminate high-risk patients in the training set (n = 372; P < 0.0001). Quantitative real-time polymerase chain reaction-based validation in an independent clinical cohort (n = 88) of formalin-fixed paraffin-embedded clinical GC samples showed that MRC-derived high-risk patients succumb to significantly poor recurrence-free survival in GC patients (P < 0.0001). Cox and stratification analysis indicated that the prognostic value of this signature was independent of clinicopathological risk factors. Time-dependent receiver operating characteristic (ROC) analysis revealed that the area under the curve of this signature was significantly larger than that of TNM stage in the TCGA (0.733 vs. 0.589 at 3 years, P = 0.004; 0.802 vs. 0.635 at 5 years, P = 0.005) and validation cohort (0.835 vs. 0.689 at 3 years, P = 0.003). A nomogram was constructed for clinical use, which integrated both MRC and clinical-related variables (depth of invasion, lymph node status and distance metastasis) and did well in the calibration plots. In conclusion, this novel miRNA-based signature is superior to currently used clinicopathological features for identifying high-risk GC patients. It can be readily translated into clinical practice with formalin-fixed paraffin-embedded specimens for specific decision-making applications.

Nomograms to Predict the Individual Survival of Patients with Solitary Hepatocellular Carcinoma after Hepatectomy

Background/Aims

Solitary hepatocellular carcinoma (HCC) is a subgroup of HCCs. We aimed to establish nomograms for predicting the survival of solitary HCC patients after hepatectomy.

Methods

A total of 538 solitary HCC patients were randomly classified into training and validation sets. A Cox model was used to identify predictors of overall survival (OS) in the training set. A nomogram was generated based on these predictors and was validated using the validation set.

Results

Tumor size, microvascular invasion, and major vascular invasion were significantly associated with OS in the training set. Nomograms were developed based on these predictors in the multivariate analysis. The C-index was 0.75 for the OS nomogram and 0.72 for the recurrence-free survival nomogram. Compared to the index of conventional staging systems for predicting survival (0.71 for Barcelona Clinic Liver Cancer, 0.66 for the seventh American Joint Committee on Cancer, 0.68 for Cancer of the Liver Italian Program, and 0.70 for Hong Kong Liver Cancer), the index of the OS nomogram was significantly higher. Moreover, the calibration curve fitted well between the predicted and observed survival rate. Similarly, in the validation set, the nomogram discrimination was superior to those of the four staging systems (p<0.001).

Conclusions

The nomograms demonstrated good discrimination performance in predicting 3- and 5-year survival rates for solitary HCCs after hepatectomy.

Comparison of East and West Survival Nomograms in Turkish Gastric Cancer Patients Who Underwent Radical Surgery

BACKGROUND AND AIM:

The clinicopathological demonstrations of gastric cancer vary widely between Eastern and Western countries. Turkey is situated in Europe and Middle East which acts as a bridge between east and west. We aimed to validate the two popular nomograms of east and west origin by means of patients who underwent curative surgery for gastric cancer in our country.

MATERIAL AND METHODS:

Of the 202 patients diagnosed with gastric cancer between the years 2006 and 2013, 145 of these patients whose data were sufficient were included in the study. For all patients, demographic, laboratory, operative, and pathologic findings were documented. For each patient, prognostic factors were incorporated into the nomograms for estimating 5-year survival probability.

RESULTS:

For a Turkish cohort, the western nomogram showed a better discriminative capacity (AUC = 0.721, 95% confidence interval 0.637-0.806) and was better calibrated (the Hosmer-Lemeshow goodness-of-fit test p = 0.323), as compared to the eastern nomogram with AUC = 0.615, 95% confidence interval 0.522-0.708, and p = 0.077, respectively.

CONCLUSION:

Western nomogram was found to be more effective than eastern nomogram in prediction of estimating 5-year survival probability in patients with resectable gastric cancer in Turkish population.

Prediction models for patients with esophageal or gastric cancer: A systematic review and meta-analysis

Background

Clinical prediction models are increasingly used to predict outcomes such as survival in cancer patients. The aim of this study was threefold. First, to perform a systematic review to identify available clinical prediction models for patients with esophageal and/or gastric cancer. Second, to evaluate sources of bias in the included studies. Third, to investigate the predictive performance of the prediction models using meta-analysis.

Methods

MEDLINE, EMBASE, PsycINFO, CINAHL, and The Cochrane Library were searched for publications from the year 2000 onwards. Studies describing models predicting survival, adverse events and/or health-related quality of life (HRQoL) for esophageal or gastric cancer patients were included. Potential sources of bias were assessed and a meta-analysis, pooled per prediction model, was performed on the discriminative abilities (c-indices).

Results

A total of 61 studies were included (45 development and 16 validation studies), describing 47 prediction models. Most models predicted survival after a curative resection. Nearly 75% of the studies exhibited bias in at least 3 areas and model calibration was rarely reported. The meta-analysis showed that the averaged c-index of the models is fair (0.75) and ranges from 0.65 to 0.85.

Conclusion

Most available prediction models only focus on survival after a curative resection, which is only relevant to a limited patient population. Few models predicted adverse events after resection, and none focused on patient’s HRQoL, despite its relevance. Generally, the quality of reporting is poor and external model validation is limited. We conclude that there is a need for prediction models that better meet patients’ information needs, and provide information on both the benefits and harms of the various treatment options in terms of survival, adverse events and HRQoL.

Nomogram based on systemic inflammatory response markers predicting the survival of patients with resectable gastric cancer after D2 gastrectomy

This study aimed to construct a nomogram to predict survival of patients with resectable gastric cancer (RGC) based on both clinicopathology characteristics and systemic inflammatory response markers (SIRMs). Of 3,452 RGC patients after D2 gastrectomy at the Sun Yat-sen University Cancer Center, 1058 patients who met the inclusion criterion were analyzed. The patients operated on from January 1, 2005 to December 31, 2009 were assigned to the training set (817 patients) to establish a nomogram, and the rest (241 patients) were selected as validation set. Based on the training set, seven independent risk factors were selected in the nomogram. The calibration curves for probability of 1-year, 3-year and 5-year overall survival (OS) showed satisfactory accordance between nomogram prediction and actual observation. When the metastatic lymph node stage (mLNS) is replaced by metastasis lymph node ratio (mLNR) in validation set, the C-index in predicting OS rise from 0.77 to 0.79, higher than that of 7th American Joint Committee on Cancer 7th (AJCC) staging system (0.70; p<0.001). In conclusions, the proposed nomogram which including mLNR and routine detected SIRMs resulted in optimal survival prediction for RGC patients after D2 gastrectomy.

Prognostic value of preoperative serum lactate dehydrogenase levels for resectable gastric cancer and prognostic nomograms

The present study aimed to evaluate the prognostic significance of preoperative serum lactate dehydrogenase (SLDH) levels for resected gastric cancer and construct prognostic nomograms for risk prediction. The study cohort consisted of 619 patients with D2-resected gastric cancer. The relationship of SLDH levels with clinicopathological features and clinical outcomes was evaluated. Prognostic nomograms were created using identified prognosticators to predict 3-year overall survival (OS) and 3-year disease-free survival (DFS), and bootstrap validation was performed. High SLDH levels were correlated with old age but not depth of invasion or lymph node metastasis. When assessed as a continuous variable, high SLDH levels were independently associated with poor OS and DFS. Internal validation of the developed nomograms revealed good predictive accuracy (bootstrap-corrected concordance indices: 0.77 and 0.75, respectively for prediction of OS and DFS). The preoperative SLDH levels, an identified unfavorable prognosticator, were incorporated into nomograms along with other clinicopathological features to refine the prediction of clinical outcomes for patients with D2-resected gastric cancer.

Validation of an assessment tool: Estimation of Postoperative Overall Survival for Gastric Cancer

BACKGROUND

Benchmarking of long-term surgical outcomes has rarely been attempted. We previously devised a prediction model for assessing the outcome of late survival after surgery, termed the Estimation of Postoperative Overall Survival for Gastric Cancer (EPOS-GC). This study was undertaken to validate EPOS-GC in an external data set.

METHODS

A retrospective cohort study was conducted in 11 cancer care hospitals in Japan, analyzing a consecutive series of patients who underwent elective gastric cancer resection between April 2007 and March 2009. EPOS-GC consists of three tumor-related variables and three physiological variables. The primary endpoint was postoperative overall survival. The observed-to-expected (O/E) ratio of 5-year survival rates was defined as a metric of quality of care. The sample size for O/E was determined as 42.

RESULTS

We included 2045 patients for analysis. The median (95% confidence interval) follow-up time was 5.1 (1.2-6.8) years for censored patients. Although EPOS-GC demonstrated a good discriminative power (Harrell's C-index, 95% confidence interval: 0.80, 0.79-0.83), the calibration plot revealed that EPOS-GC underestimated 5-year survival rates in the high-risk group. Therefore, we recalibrated the model with Cox's regression analysis. The recalibrated EPOS-GC showed a good calibration, preserving the high discriminative power (C-index, 95% confidence interval: 0.80, 0.78-0.82). The O/E among hospitals according to the recalibrated EPOS-GC ranged between 0.87 and 1.27. The O/E correlated with hospital volumes (Spearman's correlation = 0.76, n = 11, p = .006).

CONCLUSION

EPOS-GC with recalibration can convey risk-adjusted quality assurance regarding late survival following gastric cancer resection.

Lymph node staging systems in patients with gastric cancer treated with D2 resection plus adjuvant chemotherapy

Background: The optimal nodal staging scheme for gastric cancer remains unsettled. We compared the prognostic performances of the metastatic lymph node, lymph node ratio, and log odds of metastatic lymph nodes based on nomograms among 801 patients with D2-resected gastric cancer treated with adjuvant chemotherapy.

Methods: When assessed as a continuous covariate, each nodal staging variable was incorporated into a prognostic nomogram with other significant prognosticators to predict the 5-year overall survival. The discriminatory abilities of the nomograms were compared using the concordance index. Patients were divided into subgroups using each nomogram, and the prognostic homogeneity of the nomograms was assessed using the Kaplan-Meier method with log-rank tests.

Results: The discriminatory abilities of the three nomograms were comparable (P > 0.05 for all pairwise comparisons). However, for patients within each lymph node ratio subgroup, overall survival was homogenous when stratified by subgroups of the other two staging schemes, while it differed significantly among the different lymph node ratio subgroups for patients within some of the other two staging subgroups.

Conclusion: The lymph node ratio-based staging scheme performs the best for the prediction of survival in patients with locally advanced gastric cancer treated with D2 resection followed by adjuvant chemotherapy.

A nomogram to predict prognosis for gastric cancer with peritoneal dissemination

Objective

To identify independent prognostic factors to be included in a nomogram to predict the prognosis of gastric cancer patients with peritoneal dissemination.

Methods

This is a retrospective study on 684 patients with a histological diagnosis of gastric cancer with peritoneal dissemination from the Sun Yat-sen University Cancer Center as the development set, and 62 gastric cancer patients from the Sixth Affiliated Hospital of Sun Yat-sen University as the validation group. Chi-square test and Cox regression analysis were used to compare the clinicopathological variables and the prognosis of gastric cancer patients with peritoneal dissemination. The Harrell’s concordance index (C-index) and calibration curve were determined for comparisons of predictive ability of the nomogram.

Results

Univariate and multivariate analyses showed that serum carcinoembryonic antigen (CEA) level (P=0.032), ascites grading (P=0.008), presence of extraperitoneal metastasis (P<0.001), seeding status (P=0.016) and performance status (P=0.009) were independent prognostic factors for gastric cancer patients with peritoneal dissemination in the development set. The nomogram model was constructed using these five factors. Internal validation showed that the C-index of the model was 0.641. For the external validation, the C-index of this model was 0.709.

Conclusions

We developed and validated a nomogram to predict the prognosis for gastric cancer patients with peritoneal dissemination. This nomogram may play an important clinical role in guiding palliative therapy for these types of patients, although it may need more data for optimization.

Western Validation of a Novel Gastric Cancer Prognosis Prediction Model in US Gastric Cancer Patients

BACKGROUND

A novel prediction model for accurate determination of 5-year overall survival of gastric cancer patients was developed by an international collaborative group (G6+). This prediction model was created using a single institution's database of 11,851 Korean patients and included readily available and clinically relevant factors. Already validated using external East Asian cohorts, its applicability in the American population was yet to be determined.

STUDY DESIGN

Using the Surveillance, Epidemiology, and End Results (SEER) dataset, 2014 release, all patients diagnosed with gastric adenocarcinoma who underwent surgical resection between 2002 and 2012, were selected. Characteristics for analysis included: age, sex, depth of tumor invasion, number of positive lymph nodes, total lymph nodes retrieved, presence of distant metastasis, extent of resection, and histology. Concordance index (C-statistic) was assessed using the novel prediction model and compared with the prognostic index, the seventh edition of the TNM staging system.

RESULTS

Of the 26,019 gastric cancer patients identified from the SEER database, 15,483 had complete datasets. Validation of the novel prediction tool revealed a C-statistic of 0.762 (95% CI 0.754 to 0.769) compared with the seventh TNM staging model, C-statistic 0.683 (95% CI 0.677 to 0.689), (p < 0.001).

CONCLUSIONS

Our study validates a novel prediction model for gastric cancer in the American patient population. Its superior prediction of the 5-year survival of gastric cancer patients in a large Western cohort strongly supports its global applicability. Importantly, this model allows for accurate prognosis for an increasing number of gastric cancer patients worldwide, including those who received inadequate lymphadenectomy or underwent a noncurative resection.

Development and Validation of a Nomogram to Predict the Benefit of Adjuvant Radiotherapy for Patients with Resected Gastric Cancer

Background: The US guidelines for gastric cancer (GC) recommend adjuvant radiotherapy (ART) combined with 5-fluorouracil as a standard treatment for patients with resected locally advanced GC. However, patient selection criteria for optimizing the use of adjuvant therapies are lacking. In this study, we developed and validated a nomogram to predict the individualized overall survival (OS) benefit of ART among patients with resected ≥stage IB GC. Patients and Methods: The 2002-2006 Surveillance, Epidemiology, and End Results (SEER) data of 5,206 patients with resected GC were used as a training set for the development of a nomogram. The 2007-2008 SEER data of 1,986 patients with resected GC were used as validation data. Results: In the multivariate analysis weighted by inverse propensity score, the efficacy of ART varied by the ratio of positive to examined nodes (Pinteraction <0.01). The magnitude of this difference was included in the nomogram with associated prognosticators to predict the 3- and 5-year OS with and without ART. The nomogram showed significant prognostic superiority to the 8th TNM staging in the training set (Concordance index, 0.68 versus 0.65; P<0.01) and the validation set (Concordance index, 0.68 versus 0.64; P<0.01). Moreover, the calibration was accurate, and the actual efficacy of ART was positively correlated with the nomogram-estimated survival benefit from ART (Pinteraction <0.01 and Pinteraction =0.02 in the training set and the validation set, respectively). Conclusion: The nomogram can aid individualized clinical decision making by estimating the 3- and 5-year OS and potential benefits of ART among patients with resected GC.

A Nomogram for Predicting Overall Survival of Gastric Cancer Patients with Insufficient Lymph Nodes Examined

Insufficient number of examined lymph nodes (eLNs) was considered to increase significantly the risk of stage migration in gastric cancer patients. The aim of our study is to establish a nomogram predicting the overall survival (OS) for patients with an insufficient number of eLNs. A total of 872 gastric cancer patients with extended lymphadenectomies were assigned randomly (2:1) to the development cohort and the validation cohort. The nomogram was established based on the Cox regression model using the development cohort. The concordance index (C-index) was used to evaluate the discriminative ability. We also compared our model with two other staging systems. Using multivariate analysis, age, sex, tumor location, depth of invasion, macroscopic type, lymphovascular invasion, the number of eLNs, and metastatic lymph nodes were selected and incorporated into the nomogram. The C-index of the nomogram was 0.742 and 0.743 in development and validation cohorts, respectively, which were significantly superior to the C-indices (range 0.705-0.712, all P < 0.001) of American Joint Committee on Cancer (AJCC) seventh edition and lymph node ratio staging systems in both cohorts. We established a nomogram which could predict accurately OS for gastric cancer patients with insufficient number of eLNs.

Validation of two prognostic models for recurrence and survival after radical gastrectomy for gastric cancer

BACKGROUND

Prognostic models from Korea and Italy have been developed that predict overall survival and cancer recurrence respectively after radical gastrectomy for gastric cancer. The aim of this study was to validate the two models in independent patient cohorts, and to evaluate which factors may explain differences in prognosis between Korean and Italian patients with gastric cancer.

METHODS

Patients who underwent radical gastrectomy for gastric cancer between January 2000 and December 2004 at Seoul National University Hospital and at eight centres in Italy were included. Discrimination of the models was tested with receiver operating characteristic (ROC) curves and calculation of area under the curve (AUC). Calibration was evaluated by plotting actual survival probability against predicted survival probability for the Korean nomogram, and actual against predicted risk of recurrence for the Italian score.

RESULTS

Some 2867 and 940 patients from Korea and Italy respectively were included. The Korean nomogram achieved good discrimination in the Italian cohort (AUC 0·80, 95 per cent c.i. 0·77 to 0·83), and the Italian model performed well in the Korean cohort (AUC 0·87, 0·85 to 0·89). The Korean nomogram also achieved good calibration, but this was not seen for the Italian model. Multivariable analyses confirmed that Italian ethnicity was an independent risk factor for cancer recurrence (odds ratio (OR) 1·72, 1·31 to 2·25; P < 0·001), but not for overall survival (OR 1·20, 0·95 to 1·53; P = 0·130).

CONCLUSION

Both prognostic models performed fairly well in independent patient cohorts. Differences in recurrence rates of gastric cancer may be partially explained by ethnicity.

Validation of a nomogram for selecting patients for chemotherapy after D2 gastrectomy for cancer

BACKGROUND

According to some guidelines for the management of gastric cancer, adjuvant chemotherapy is recommended for patients with pT3-4 or node-positive disease. The aim of this study was to define low- and high-risk groups in terms of survival, and to predict the benefit of adjuvant fluoropyrimidine plus oxaliplatin (F-OX) chemotherapy.

METHODS

Patients with pT3-4 or node-positive gastric cancer after gastrectomy with D2 lymphadenectomy between 2000 and 2013 were included. The performance of a previously published nomogram was assessed by discrimination and calibration. Patients were stratified into risk groups on the basis of the nomogram-predicted overall survival probability. The efficacy of F-OX within each risk subgroup was assessed using the log rank test and Cox regression analysis weighted by inverse propensity score.

RESULTS

Some 1464 patients were included. The nomogram showed better discrimination than the seventh AJCC staging classification (concordance index 0·72 versus 0·68 respectively; P = 0·008) and accurate calibration. F-OX was not associated with improved survival in patients in the low-risk group, whereas it reduced the risk of death by over 20 per cent in the intermediate- and high-risk groups (P = 0·036 and P < 0·001 respectively) (P for interaction = 0·014).

CONCLUSION

A nomogram can aid in individualized decision-making regarding the administration of F-OX after gastrectomy for cancer.

Comparison of prognostic nomograms based on different nodal staging systems in patients with resected gastric cancer

Purpose: Previous studies addressing the optimal nodal staging system in patients with resected gastric cancer have shown inconsistent results, and the optimal system for development of prognostic nomograms remains unclear. In this study, we compared prognostic nomograms based on the metastatic lymph node (MLN) count, lymph node ratio (LNR), and log odds of metastatic lymph nodes (LODDS) to predict the 5-year overall survival in patients with resected gastric cancer.

Methods: We analysed 15,320 patients with resected gastric cancer in the Surveillance, Epidemiology, and End Results (SEER) database between 1988 and 2010. Missing data were handled using multiple imputation. When assessed as a continuous covariate with restricted cubic splines, each MLN, LNR, and LODDS variable was incorporated into a nomogram with other significant prognosticators to predict the 5-year overall survival. A two-centre Chinese dataset (1,595 cases) was used as external validation data.

Results: The discriminatory abilities of the MLN-, LNR-, and LODDS-based nomograms were comparable (concordance indices: 0.744, 0.741, and 0.744, respectively, in the SEER set, P > 0.152 for all pairwise comparisons; 0.715, 0.712, and 0.713, respectively, in the Chinese set, P > 0.445 for all pairwise comparisons). The discriminatory abilities of the three nomograms were all superior to the American Joint Committee on Cancer (AJCC) TNM classification (concordance indices: 0.713, P < 0.001 for all in the SEER set; and 0.693, P < 0.001 for all in the Chinese set). The discriminatory abilities of the nomograms were comparable regardless of the number of nodes examined. Moreover, decision curve analyses indicated similar net benefits of using the nomograms.

Conclusion: MLN-, LNR-, and LODDS should be considered equally in the development of multivariate prognostic models and nomograms to refine the prediction of survival among patients with resected gastric cancer.

Equipping the 8th Edition American Joint Committee on Cancer Staging for Gastric Cancer with the 15-Node Minimum: a Population-Based Study Using Recursive Partitioning Analysis

BAKCGROUND

The recently proposed 8th American Joint Committee on Cancer (AJCC) staging for gastric cancer (GC) did not include the evaluated lymph node (ELN) count as a prognostic indicator. In this study, we performed recursive partitioning analysis (RPA) to objectively combine the 15-ELN threshold and 8th AJCC stage to refine the staging for GC.

METHODS

We analyzed 19,018 patients with non-metastatic GC from the Surveillance, Epidemiology, and End Results database. The dataset was randomly divided into training and validation sets.

RESULTS

For each 8th AJCC stage, survival was significantly better for patients with ≥15 ELNs versus those with <15 ELNs (P < 0.001 for all). RPA divided non-metastatic GC into seven stages: RPA-IA (8th AJCC IA with ≥15 ELNs), RPA-IB (IA with <15 ELNs and IB/IIA with ≥15 ELNs), RPA-IIA (IB with <15 ELNs and IIB with ≥15 ELNs), RPA-IIB (IIA with <15 ELNs and IIIA with ≥15 ELNs), RPA-IIIA (IIB with <15 ELNs), RPA-IIIB (IIIA with <15 ELNs and IIIB ≥15 ELNs), and RPA-IIIC (IIIB with <15 ELNs and IIIC). The corresponding 5-year survival rates were 84.1, 70.3, 52.8, 41.4, 32.9, 21.7, and 10.2%, respectively (P < 0.001 for all pairwise comparisons). The RPA staging outperformed the 8th AJCC staging in terms of discrimination and homogeneity among the SEER training and validation sets, as well as an independent Chinese cohort.

CONCLUSION

By equipping the 8th AJCC stage with the 15-ELN threshold, the proposed RPA staging is superior to the 8th AJCC staging without overcomplicating.

Nomogram for 5-year relapse-free survival of a patient with advanced gastric cancer after surgery

BACKGROUND

Prognoses vary substantially among patients with advanced gastric cancer following curative surgery. The aim of the current study was to develop and verify the validity of a novel nomogram that predicts the probability of 5-year relapse-free survival (RFS) in patients who underwent curative resection for stage II/III gastric cancer.

MATERIALS AND METHODS

A nomogram to predict 5-year RFS following surgical resection of gastric cancer was constructed based on the data of patients who underwent surgery for primary gastric carcinoma at three institutions in Japan in January 2001-December 2006. Multivariate analysis using a Cox proportional hazards regression model was performed, and the nomogram's predictive accuracy (discrimination) and the agreement between observed outcomes and predictions (calibration) were evaluated by internal validation.

RESULTS

Multivariate analyses revealed that age at operation, depth of tumor, tumor location, lymph node classification, and presence of combined resection were significant prognostic factors for RFS. In the internal validation, discrimination of the developed nomogram for 5-year RFS was superior to that of the American Joint Committee on Cancer TNM classification (concordance indices of 0.80 versus 0.67; P < 0.001). Moreover, calibration appeared to be accurate. Based on these results, we have created free software to more easily predict 5-year RFS.

CONCLUSION

We developed and validated a nomogram to predict 5-year RFS after curative surgery for stage II/III gastric cancer. This tool will be useful for the assessing a patient's individual recurrence risk when considering additional therapy in clinical practice.

Preoperative neutrophil-to-lymphocyte ratio plus platelet-to-lymphocyte ratio in predicting survival for patients with stage I-II gastric cancer

Background

The preoperative neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) are associated with poor prognosis of gastric cancer. We aimed to determine whether the combination of NLR and PLR (NLR–PLR) could better predict survival of patients after curative resection for stage I–II gastric cancer.

Methods

We collected data from the medical records of patients with stage I–II gastric cancer undergoing curative resection between December 2000 and November 2012 at the Sun Yat-sen Cancer Center. The preoperative NLR–PLR was calculated as follows: patients with both elevated NLR (≥2.1) and PLR (≥120) were given a score of 2, and patients with only one or neither were given a score of 1 or 0, respectively.

Results

Kaplan–Meier analysis and log-rank tests revealed significant differences in overall survival (OS) among patients with NLR–PLR scores of 0, 1 and 2 (P < 0.001). Multivariate analysis showed that OS was independently associated with the NLR–PLR score [hazard ratio (HR) = 1.51, 95% confidence interval (CI) 1.02–2.24, P = 0.039] and TNM stage (HR = 1.36, 95% CI 1.01–1.83, P = 0.041). However, other systemic inflammation-based prognostic scores, including the modified Glasgow prognostic score, the prognostic nutritional index, and the combination of platelet count and NLR, were not. In TNM stage-stratified analysis, the prognostic significance of NLR–PLR was maintained in patients with stage I (P < 0.001) and stage II cancers (P = 0.022). In addition, the area under the receiver operating characteristic curve for the NLR–PLR score was higher than those of other systemic inflammation-based prognostic scores (P = 0.001).

Conclusion

The preoperative NLR-PLR score is a useful predictor of postoperative survival in the patients with stage I–II gastric cancer and may help identify high-risk patients for rational therapy and timely follow-up.