Prognosis of Young Survivors of Gastric Cancer in China and the U.S.: Determining Long-Term Outcomes Based on Conditional Survival

Sequential changes in conditional survival of patients undergoing curative gastrectomy for gastric cancer

BACKGROUND

Long-term data on the prognosis of patients who survived >5 years after gastrectomy for gastric cancer (GC) remain scarce. This study aimed to investigate sequential changes in conditional survival (CS) in patients with stage I-III GC who underwent R0 gastrectomy.

METHODS

Of 1129 patients with stage I to III GC who underwent R0 gastrectomy, the causes of death were assessed, and sequential changes in conditional overall survival (cOS), conditional disease-specific survival (cDSS), and conditional non-disease-specific survival (cNDSS) were calculated and compared. In a subgroup of 709 patients who survived >5 years, the associations between cOS, cDSS, cNDSS, and clinicopathologic factors were analyzed.

RESULTS

Over a median follow-up of 63 months, 203 patients (18.0%) died of GC, and 132 patients (11.7%) died of non-GC causes. The 5-year cDSS consistently increased over 10 years after gastrectomy for stage II and III GC. The cDSS and cNDSS intersected at 7 years after gastrectomy for stage II GC, whereas these measures crossed at 8 years after gastrectomy for stage III GC. In the 709 5-year survivors, multivariate analysis identified disease stage as being significantly associated with cOS and cDSS. Moreover, age ≥ 80 years, male sex, and preoperative comorbidities were associated with lower cNDSS.

CONCLUSION

Surveillance for GC relapse was crucial during the first 7 and 8 years after gastrectomy for stages II and III, respectively. Conversely, surveillance for second primary cancers and benign diseases became relatively more important 0, 7, and 8 years after gastrectomy for stages I, II, and III, respectively. In 5-year survivors, age ≥ 80 years, male sex, and preoperative comorbidities were associated with mortality unrelated to GC.

Prognostic factors for relapse-free 5-year survivors after gastrectomy for gastric cancer

BACKGROUND

Few studies have examined the prognosis of long-term survivors with gastric cancer (GC) after gastrectomy. This study aimed to identify the prognostic factors for 5-year recurrence-free survivors after gastrectomy for GC.

METHODS

A total of 721 patients with pathologic stage Ⅰ to Ⅲ GC who underwent gastrectomy between 2005 and 2018 and survived for 5 years without recurrence were enrolled. Conditional overall survival (cOS), conditional disease-specific survival (cDSS), and conditional non-disease-specific survival (cNDSS) of 5-year recurrence-free survivors were calculated. The association between cOS, cDSS, and cNDSS and clinicopathologic factors was evaluated using univariate and multivariate analyses.

RESULTS

The mean age of the patients was 70.5 ± 10.1 years, 68.5% of the patients were male, and 491, 128, and 102 had stage Ⅰ, Ⅱ, and Ⅲ GC, respectively. Of note, 17 patients relapsed, and 65 patients died (disease-specific, non-disease-specific, and unknown: 12, 45, and 6, respectively) during a median follow-up of 36 months. The 5-year cOS, cDSS, and cNDSS rates were 90.3%, 97.3%, and 93.3%, respectively. Multivariate analysis showed that age of ≥80 years and neutrophil-to-lymphocyte ratio (NLR) of ≥2.7 were significantly associated with poorer cOS. Stage Ⅲ GC was associated with decreased cDSS, and age of ≥80 years, NLR of ≥2.7, and mean corpuscular volume (MCV) of ≥93.4 fL were associated with lower cNDSS.

CONCLUSION

Age of ≥80 years, stage Ⅲ GC, NLR of ≥2.7, and MCV of ≥93.4 fL were unfavorable prognostic factors for 5-year recurrence-free survivors after gastrectomy for GC. Long-term surveillance after gastrectomy could be tailored based on these factors.

Immunotherapy Combined with Chemotherapy in the First-Line Treatment of Advanced Gastric Cancer: Systematic Review and Bayesian Network Meta-Analysis Based on Specific PD-L1 CPS

Objective: To compare the efficacy and safety of immunotherapy combined with chemotherapy as the first-line treatment for advanced gastric cancer. Data Sources: Phase III randomised controlled trials were searched from PubMed, Embase, Web of Science, Cochrane Library, and ClinicalTrials databases, and several international conference databases, from inception to 15 November 2024. Results: A total of eight eligible trials involved 7898 patients and eight treatments. The network meta-analysis showed that cadonilimab plus chemotherapy was the most superior treatment in improving overall survival (versus conventional chemotherapy, hazard ratio 0.62, 95% credible interval 0.50 to 0.78) and progression-free survival (0.53, 0.43 to 0.65), and consistency of results were observed in specific PD-L1 combined positive score groups. All immune checkpoint inhibitors combined with chemotherapy improved patient prognosis, but nivolumab plus chemotherapy may lead to an increase in grade 3 or higher adverse events (odds ratio 1.68, 95% credible interval 1.04 to 2.54), and the toxicity of cadonilimab plus chemotherapy was more likely to force patients to discontinue treatment. Conclusions: These results showed that cadonilimab plus chemotherapy had the best overall survival and progression-free survival benefits for advanced gastric cancer patients with HER-2 negative, and was preferentially recommended to patients with positive PD-L1 CPS.

Development and Validation of a Novel Conditional Survival Nomogram for Predicting Real-Time Prognosis in Patients With Breast Cancer Brain Metastasis

BACKGROUND

Breast cancer brain metastasis (BCBM) prognosis has not been evaluated dynamically, which may underestimate patient survival. This study aimed to perform a conditional survival (CS) analysis and develop and validate an individualized real-time prognostic monitoring model for survivors.

METHODS

The study included patients with BCBM from the Surveillance, Epidemiology, and End Results database (training group, n = 998) and our institution (validation group, n = 45) and updated patient overall survival (OS) over time using the CS method: CS(t2|t1)=OS(t1+t2)OS(t1). Multivariate Cox regression was used to identify prognostic factors for the nomogram, which estimated individualized OS. Furthermore, a novel CS-nomogram and its web version were further developed based on the CS formula.

RESULTS

CS analysis showed that the 5-year OS of BCBM survivors gradually improved from 13.5% estimated at diagnosis to 26.0%, 39.7%, 57.9%, and 77.6% (surviving 1-4 years, respectively). Cox regression identified age, marital status, estrogen receptor status, human epidermal growth factor receptor 2 (Her-2) status, histological grade, surgery, and chemotherapy as significant factors influencing OS (P < .05). We then constructed and deployed the CS-nomogram based on the CS formula and the nomogram to predict real-time prognosis dynamically (https://wh-wang.shinyapps.io/BCBM/). During performance evaluation, the model performed well in both the training and validation groups.

CONCLUSIONS

CS analysis showed a gradual improvement in prognosis over time for BCBM survivors. We developed and deployed on the web a novel real-time dynamic prognostic monitoring system, the CS-nomogram, which provided valuable survival data for clinical decision-making, patient counseling, and optimal allocation of healthcare resources.

Survival Outcomes for Adolescent and Young Adults With Cancer in Low- and Middle-Income Countries: A Systematic Review

PURPOSE

Patients with adolescent and young adult (AYA) cancer are recognized as a vulnerable subpopulation in high-income countries (HICs). Although survival gaps between HIC and low- and middle-income country (LMIC) children with cancer are well described, LMIC AYAs have been neglected. We conducted a systematic review to describe cancer outcomes among LMIC AYAs.

METHODS

We captured English language studies published from 2010 onward reporting LMIC AYA cancer survival outcomes. LMICs were defined according to World Bank 2019 classifications, whereas AYAs were defined as diagnosed between age 15 and 39 years. Cohorts were considered AYA if >75% of patients were AYA, the mean/median age and standard deviation were between 15 and 39 years, or the range was within 5 years of the AYA range (ie, 10-45 years). Cohort characteristics were abstracted, including country, cancer type, and cancer outcomes.

RESULTS

Of 6,207 studies identified by the search strategy, 658 underwent full-text review; 60 met inclusion criteria. No low-income countries were represented. Forty-four (73.3%) studies were conducted in upper-middle-income countries (UMICs) although these represented only 12 of 55 countries currently classified as UMICs. The most common cancers studied were acute lymphoblastic leukemia (n = 13 studies), breast cancer (n = 5), and osteosarcoma (n = 3). Five-year overall survival was highly variable, ranging from 39% to 63% for ALL, 60%-85% for breast cancer, and 47%-83% for osteosarcoma.

CONCLUSION

Although three billion AYAs reside in LMICs, their cancer outcomes are neglected in the current literature. Existing data indicate variable survival, ranging from comparable with HIC outcomes to substantially inferior. These studies, however, represent only a limited number of LMICs and are biased toward UMICs. Systematic efforts to describe and improve LMIC AYA cancer outcomes are required.

Prognostic value of ground-glass opacity on computed tomography for patients with pathological stage IA3 lung adenocarcinoma: a multicenter retrospective cohort study

Background

Ground-glass opacity (GGO) on computed tomography (CT) has been suggested as a potential prognostic factor in lung adenocarcinoma (LUAD), but its significance in patients with pathological stage IA3 LUAD, particularly in relation to micropapillary (MIP) status, remains unclear. This study addresses the clinical need to stratify patients based on GGO and MIP status to optimize prognosis prediction and follow-up strategies.

Methods

A multicenter retrospective study was conducted on 411 patients with pathological stage IA3 LUAD, enrolled between July 2012 and July 2020. Patients were divided into two groups based on the presence of GGO. The association of GGO with recurrence-free survival (RFS) and cancer-specific survival (CSS) of patients with different MIP status was assessed, stratified by MIP status (MIP ≥5% was classified as positive, and MIP <5% as negative). A life-table analysis was used to calculate dynamic recurrence curves of subgroups formed by GGO and MIP and to establish a personalized follow-up strategy.

Results

The analysis indicated that GGO was associated with prolonged RFS (P<0.001) and CSS (P=0.006) in MIP-negative patients but not for MIP-positive patients. Time-dependent Cox multivariate analysis further showed that GGO was a favorable prognostic factor for RFS (P=0.03) and CSS (P=0.04) even at 2 years postoperatively. Based on GGO components and MIP status, patients were categorized into the four following subgroups: MIP(+)-GGO(+), MIP(+)-GGO(-), MIP(-)-GGO(+), and MIP(-)-GGO(-); the recommended number of follow-up visits for these four subgroups within 5 years were 3, 9, 3, and 11, respectively.

Conclusions

The GGO component demonstrated a beneficial prognostic effect primarily in MIP-negative patients with pathological stage IA3 LUAD, sustained for up to 2 years. The variation in recurrence risk across subgroups underscores the importance of personalized follow-up strategies based on GGO and MIP status to optimize patient monitoring and care.

Identification of Fatty Acid Metabolism-Related Subtypes in Gastric Cancer Aided by Machine Learning

INTRODUCTION

Gastric cancer, the fifth most common malignant tumor in the world, poses a serious threat to human health. However, the role of fatty acid metabolism (FAM) in gastric cancer remains incompletely understood. We aim to provide guidance for clinical decisions by utilizing public database of gastric adenocarcinoma to establish an FAM-related gene subtypes via machine learning algorithm.

METHODS

The intersection of FMGs from KEGG, Hallmark, and Reactome bioinformatics databases and the DEGs of the TCGA-STAD cohort was used to decompose the gene matrix related to establish FAM-related gene subtypes by NMF. Comparison of immune infiltrating differences between subtypes using ESTIMATE and Cibersort algorithms. The multifactor Cox regression to identify independent risk genes for patient prognosis based on the subtypes. A prognostic model including independent risk genes was built using random survival forest and Cox regression. IHC validation in gastric cancer and adjacent tissues confirmed the above gene expression level.

RESULTS

71 DEGs related to FMGs of STAD were identified, which was used to established the FAM-related gene subtypes, C1 and C2. The immune infiltrating analysis showed that most immune features of C2 were significantly upregulated compared to C1. The independent risk genes were CGβ8, UPK1B, and OR51G based on the subtypes. A gastric cancer prognostic model consisting of independent risk genes was constructed and patients were classified into high-risk and low-risk groups with survival differential analysis. Finally, IHC showed that CGβ8 and UPK1B expression were upregulated in gastric cancer, while OR51G2 did not detect differences in expression.

CONCLUSION

The study developed a machine learning-based gastric cancer prognosis risk model using FMGs. This model effectively stratifies patients according to their risk levels and provides valuable insights for clinical decision-making, enabling accurate evaluation of patient prognosis.

Application of Survival Quilts for prognosis prediction of gastrectomy patients based on the Surveillance, Epidemiology, and End Results database and China National Cancer Center Gastric Cancer database

Objective

Accurate prognosis prediction is critical for individualized-therapy making of gastric cancer patients. We aimed to develop and test 6-month, 1-, 2-, 3-, 5-, and 10-year overall survival (OS) and cancer-specific survival (CSS) prediction models for gastric cancer patients following gastrectomy.

Methods

We derived and tested Survival Quilts, a machine learning-based model, to develop 6-month, 1-, 2-, 3-, 5-, and 10-year OS and CSS prediction models. Gastrectomy patients in the development set (n = 20,583) and the internal validation set (n = 5,106) were recruited from the Surveillance, Epidemiology, and End Results (SEER) database, while those in the external validation set (n = 6,352) were recruited from the China National Cancer Center Gastric Cancer (NCCGC) database. Furthermore, we selected gastrectomy patients without neoadjuvant therapy as a subgroup to train and test the prognostic models in order to keep the accuracy of tumor-node-metastasis (TNM) stage. Prognostic performances of these OS and CSS models were assessed using the Concordance Index (C-index) and area under the curve (AUC) values.

Results

The machine learning model had a consistently high accuracy in predicting 6-month, 1-, 2-, 3-, 5-, and 10-year OS in the SEER development set (C-index = 0.861, 0.832, 0.789, 0.766, 0.740, and 0.709; AUC = 0.784, 0.828, 0.840, 0.849, 0.869, and 0.902, respectively), SEER validation set (C-index = 0.782, 0.739, 0.712, 0.698, 0.681, and 0.660; AUC = 0.751, 0.772, 0.767, 0.762, 0.766, and 0.787, respectively), and NCCGC set (C-index = 0.691, 0.756, 0.751, 0.737, 0.722, and 0.701; AUC = 0.769, 0.788, 0.790, 0.790, 0.787, and 0.788, respectively). The model was able to predict 6-month, 1-, 2-, 3-, 5-, and 10-year CSS in the SEER development set (C-index = 0.879, 0.858, 0.820, 0.802, 0.784, and 0.774; AUC = 0.756, 0.827, 0.852, 0.863, 0.874, and 0.884, respectively) and SEER validation set (C-index = 0.790, 0.763, 0.741, 0.729, 0.718, and 0.708; AUC = 0.706, 0.758, 0.767, 0.766, 0.766, and 0.764, respectively). In multivariate analysis, the high-risk group with risk score output by 5-year OS model was proved to be a strong survival predictor both in the SEER development set (hazard ratio [HR] = 14.59, 95% confidence interval [CI]: 1.872-2.774, P < 0.001), SEER validation set (HR = 2.28, 95% CI: 13.089-16.293, P < 0.001), and NCCGC set (HR = 1.98, 95% CI: 1.617-2.437, P < 0.001). We further explored the prognostic value of risk score resulted 5-year CSS model of gastrectomy patients, and found that high-risk group remained as an independent CSS factor in the SEER development set (HR = 12.81, 95% CI: 11.568-14.194, P < 0.001) and SEER validation set (HR = 1.61, 95% CI: 1.338-1.935, P < 0.001).

Conclusion

Survival Quilts could allow accurate prediction of 6-month, 1-, 2-, 3-, 5-, and 10-year OS and CSS in gastric cancer patients following gastrectomy.

The impact of the HER2-low status on conditional survival in patients with breast cancer

Introduction

With recent advances in breast cancer (BC) treatment, the disease-free survival (DFS) of patients is increasing and the risk factors for recurrence and metastasis are changing. However, a dynamic approach to assessing the risk of recurrent metastasis in BC is currently lacking. This study aimed to develop a dynamically changing prediction model for recurrent metastases based on conditional survival (CS) analysis.

Methods

Clinical and pathological data from patients with BC who underwent surgery at the Affiliated Hospital of Qingdao University between August 2011 and August 2022 were retrospectively analysed. The risk of recurrence and metastasis in patients with varying survival rates was calculated using CS analysis, and a risk prediction model was constructed.

Results

A total of 4244 patients were included in this study, with a median follow-up of 83.16 ± 31.59 months. Our findings suggested that the real-time DFS of patients increased over time, and the likelihood of DFS after surgery correlated with the number of years of prior survival. We explored different risk factors for recurrent metastasis in baseline patients, 3-year, and 5-year disease-free survivors, and found that low HER2 was a risk factor for subsequent recurrence in patients with 5-year DFS. Based on this, conditional nomograms were developed. The nomograms showed good predictive ability for recurrence and metastasis in patients with BC.

Conclusion

Our study showed that the longer patients with BC remained disease-free, the greater their chances of remaining disease-free again. Predictive models for recurrence and metastasis risk based on CS analysis can help improve the confidence of patients fighting cancer and help doctors personalise treatment and follow-up plans.

Clinicopathological characteristics and prognosis of adolescents and young adults with gastric cancer after gastrectomy: a propensity score matching analysis

Background

Gastric cancer (GC) among adolescents and young adults (AYAs, aged 15-39 years) has limited data on clinicopathological characteristics and prognosis. This study aimed to compare the clinicopathological characteristics, perioperative outcomes, and long-term outcomes of AYAs and older adults (OAs, aged > 39 years) with GC who underwent curative gastrectomy.

Methods

From January 1994 to June 2019, patients with GC undergoing curative gastrectomy were enrolled and divided into AYA group and OA group. The clinicopathological characteristics, treatment variables, perioperative outcomes and long-term outcomes were compared between the two groups, both before and after propensity score matching (PSM).

Results

AYAs had fewer comorbid conditions and were more likely to be females, have normal carcinoembryonic antigen (CEA) levels, poorly differentiated tumors with perineural invasion, and receive adjuvant chemotherapy. AYA patients had lower incidence of postoperative complications and shorter length of postoperative hospital stay than OA patients. No significant differences in postoperative 30-day or 90-day mortality were observed between AYAs and OAs, both before and after PSM. In the entire cohort, AYAs had similar median overall survival (OS) to OAs. However, in the PSM cohort, AYAs had significantly shorter median OS. Young age (15-39 years) was an independent risk factor for OS in GC patients following gastrectomy.

Conclusion

The clinicopathological characteristics were significantly different between AYA and OA patients with GC. AYA patients with GC had worse long-term prognosis than OA patients, and young age was an independent risk factor for OS in GC patients following gastrectomy.

Survival benefit of younger gastric cancer patients in China and the United States: A comparative study

BACKGROUND

The impact of racial and regional disparity on younger patients with gastric cancer (GC) remains unclear.

AIM

To investigate the clinicopathological characteristics, prognostic nomogram, and biological analysis of younger GC patients in China and the United States.

METHODS

From 2000 to 2018, GC patients aged less than 40 years were enrolled from the China National Cancer Center and the Surveillance Epidemiology and End Results database. Biological analysis was performed based on the Gene Expression Omnibus database. Survival analysis was conducted via Kaplan-Meier estimates and Cox proportional hazards models.

RESULTS

A total of 6098 younger GC patients were selected from 2000 to 2018, of which 1159 were enrolled in the China National Cancer Center, and 4939 were collected from the Surveillance Epidemiology and End Results database. Compared with the United States group, younger patients in China revealed better survival outcomes (P < 0.01). For race/ethnicity, younger Chinese cases also enjoyed a better prognosis than that in White and Black datasets (P < 0.01). After stratification by pathological Tumor-Node-Metastasis (pTNM) stage, a survival advantage was observed in China with pathological stage I, III, and IV (all P < 0.01), whereas younger GC patients with stage II showed no difference (P = 0.16). In multivariate analysis, predictors in China involved period of diagnosis, linitis plastica, and pTNM stage, while race, diagnostic period, sex, location, differentiation, linitis plastica, signet ring cell, pTNM stage, surgery, and chemotherapy were confirmed in the United States group. Prognostic nomograms for younger patients were established, with the area under the curve of 0.786 in the China group and of 0.842 in the United States group. Moreover, three gene expression profiles (GSE27342, GSE51105, and GSE38749) were enrolled in further biological analysis, and distinctive molecular characteristics were identified in younger GC patients among different regions.

CONCLUSION

Except for younger cases with pTNM stage II, a survival advantage was observed in the China group with pathological stage I, III, and IV compared to the United States group, which might be partly due to differences in surgical approaches and the improvement of the cancer screening in China. The nomogram model provided an insightful and applicable tool to evaluate the prognosis of younger patients in China and the United States. Furthermore, biological analysis of younger patients was performed among different regions, which might partly explain the histopathological behavior and survival disparity in the subpopulations.

Prognostic nutritional index for predicting the clinical outcomes of patients with gastric cancer who received immune checkpoint inhibitors

OBJECTIVE

Although the application of immunotherapy in gastric cancer has achieved satisfactory clinical effects, many patients have no response. The aim of this retrospective study is to investigate the predictive ability of the prognostic nutrition index (PNI) to the prognosis of patients with gastric cancer who received immune checkpoint inhibitors (ICIs).

MATERIALS AND METHODS

Participants were 146 gastric cancer patients with ICIs (PD-1/PD-L1 inhibitors) or chemotherapy. All patients were divided into a low PNI group and a high PNI group based on the cut-off evaluated by the receiver operating characteristic (ROC) curve. We contrasted the difference in progression-free survival (PFS) and overall survival (OS) in two groups while calculating the prognosis factors for PFS and OS by univariate and multivariate analyses. Moreover, the nomogram based on the results of the multivariate analysis was constructed to estimate the 1- and 3-year survival probabilities.

RESULTS

There were 41 (28.1%) cases in the low PNI group and 105 (71.9%) cases in the high PNI group. The median survival time for PFS in the low PNI group and high PNI group was 12.30 months vs. 33.07 months, and 18.57 months vs. not reached in the two groups for OS. Patients in low PNI group were associated with shorter PFS and OS in all patients [Hazard ratio (HR) = 1.913, p = 0.013 and HR = 2.332, p = 0.001]. Additionally, in subgroup analysis, low PNI group cases also had poorer PFS and OS, especially in patients with ICIs. In addition, the multivariate analysis found that carbohydrate antigen 724 (CA724) and TNM stage were independent prognostic factors for PFS. At the same time, indirect bilirubin (IDBIL), CA724, PNI, and TNM stage were independent prognostic factors for OS.

CONCLUSION

Prognostic nutrition index was an accurate inflammatory and nutritional marker, which could predict the prognosis of patients with gastric cancer who received ICIs. PNI could be used as a biomarker for ICIs to identify patients with gastric cancer who might be sensitive to ICIs.

Comparison between Endoscopic Submucosal Dissection and Surgery in Patients with Early Gastric Cancer

Simple Summary

Conventional gastrectomy combined with regional lymph node dissection has been the standard treatment for early gastric cancer (EGC). This retrospective case–control study aimed to compare the clinical outcomes of endoscopic submucosal dissection (ESD) and surgical resection for EGC in China. After propensity score-matching, there were no significant differences between the two groups for OS, RFS, and DSS. Additionally, with similar R0 resection and recurrence rates, the ESD group showed less blood loss, fewer adverse events, lower hospital cost, and a shorter operative time and hospital duration than the surgery group. Therefore, ESD can be a first-line treatment of EGC in addition to surgery.

Abstract

Background: Endoscopic submucosal dissection (ESD) has become a preferred treatment option for early gastric cancer (EGC). This study aimed to compare the clinical outcomes of ESD and surgical resection for EGC. Methods: This was a retrospective case–control study. Patients with a diagnosis of EGC who underwent ESD or surgery in our hospital from 2011 to 2020 were enrolled. We compared the clinical characteristics and treatment outcomes of these two groups according to propensity score-matching. The primary outcome comparison was overall survival (OS). Secondary outcomes were disease-specific survival (DSS), recurrence-free survival (RFS), and treatment-related events. Results: In the matched cohort, the ESD group showed comparable OS, RFS, and DSS with the surgery group. Statistical differences were shown in blood loss and adverse events. Furthermore, the ESD group showed lower hospital cost, as well as a shorter operative time and hospital duration than the surgery group. The R0 resection and recurrence rates were similar between the two groups. In Cox regression analysis, age, tumor size, poor differentiation, and lymphovascular invasion were regarded as independent factors of OS. Conclusions: With sufficient safety and advantages, ESD can be a first-line treatment of EGC. Preoperative evaluation is vital to the appropriate treatment and prognosis.

Machine Learning-Based Model for the Prognosis of Postoperative Gastric Cancer

Background

The use of machine learning (ML) in predicting disease prognosis has increased, and scientists have adopted different methods for cancer classification to optimize the early screening of cancer to determine its prognosis in advance. In this study, we aimed at improving the prediction accuracy of gastric cancer in postoperation patients by constructing a highly effective prognostic model.

Methods

The study used postoperative gastric cancer patient data from the SEER database. The LASSO regression method was used to construct a clinical prognostic model, and four machine learning methods (Boruta algorithm, neural network, support vector machine, and random forest) were used to screen and recombine the features to construct an ML prognostic model. Clinical information on 955 postoperative gastric cancer patients collected from the Affiliated Tumor Hospital of Harbin Medical University was used for external verification.

Results

Experimental results showed that the AUC values of 1, 3 and 5 years in the training set, validation set and external validation set of clinical prognosis model and ML prognosis model directly established by LASSO regression are all around 0.8.

Conclusion

Both models can accurately evaluate the prognosis of postoperative patients with gastric cancer, which may be helpful for accurate and personalized treatment of postoperative patients with gastric cancer.

Lymph node ratio-based the ypTNrM staging system for gastric cancer after neoadjuvant therapy: a large population-based study

PURPOSES

The lymph node ratio (LNR) has been considered a better prognostic factor than traditional N staging in patients with gastric cancer (GC), but its accuracy is unclear for those who receive neoadjuvant therapy (NAT). We aimed to compare the node ratio (Nr) staging with the ypN staging and to thereby develop a modified staging system incorporating Nr staging.

METHODS

A total of 1791 patients who underwent gastrectomy after NAT in the Surveillance, Epidemiology, and End Results database were retrospectively analyzed. ypTNrM staging was established based on the overall survival (OS).

RESULTS

The Nr staging was generated using 0.2 and 0.5 as the cutoff values of LNR and represented patients with more homogeneous OS compared with ypN staging. The 5-year OS rates for ypTNrM stages IA, IB, II, IIIA, and IIIB were 70.2%, 54.2%, 36.0%, 21.2%, and 6.6%, respectively, compared with 58.8%, 39.1%, and 21.6% for ypTNM stages I, II, and III, respectively. Compared with the ypTNM staging system, the ypTNrM staging system had a lower misclassification rate (3.0% vs. 50.9%) and better prognostic predictive power (C-index: 0.645 vs. 0.589, P < 0.001).

CONCLUSIONS

The ypTNrM staging system incorporating Nr staging may provide a more accurate assessment in the clinical decision-making process for GC after NAT.

Modified ypTNM Staging Classification for Gastric Cancer after Neoadjuvant Therapy: A Multi-Institutional Study

BACKGROUND

The benefits of neoadjuvant therapy for patients with locally advanced gastric cancer (GC) are increasingly recognized. The 8th edition of the American Joint Committee on Cancer (AJCC) Staging Manual first proposed ypTNM staging, but its accuracy is controversial. This study aims to develop a modified ypTNM staging.

PATIENTS AND METHODS

Clinicopathological data of 1,791 patients who underwent curative-intent gastrectomy after neoadjuvant therapy in the Surveillance, Epidemiology, and End Results database, as the development cohort, were retrospectively analyzed. Modified ypTNM staging was established based on overall survival (OS). We compared the prognostic performance of the AJCC 8th edition ypTNM staging and the modified staging for patients after neoadjuvant therapy.

RESULTS

In the development cohort, the 5-year OS for AJCC stages I, II, and III was 58.8%, 39.1%, and 21.6%, respectively, compared with 69.9%, 54.4%, 34.4%, 24.1%, and 13.6% for modified ypTNM stages IA, IB, II, IIIA, and IIIB. The modified staging had better discriminatory ability (C-index: 0.620 vs. 0.589, p < .001), predictive homogeneity (likelihood ratio chi-square: 140.71 vs. 218.66, p < .001), predictive accuracy (mean difference in Bayesian information criterion: 64.94; net reclassification index: 35.54%; integrated discrimination improvement index: 0.032; all p < .001), and model stability (time-dependent receiver operating characteristics curves) over AJCC. Decision curve analysis showed that the modified staging achieved a better net benefit than AJCC. In external validation (n = 266), the modified ypTNM staging had superior prognostic predictive power (all p < .05).

CONCLUSION

We have developed and validated a modified ypTNM staging through multicenter data that is superior to the AJCC 8th edition ypTNM staging, allowing more accurate assessment of the prognosis of patients with GC after neoadjuvant therapy.

IMPLICATIONS FOR PRACTICE

The 8th edition of the American Joint Committee on Cancer (AJCC) Staging Manual first proposed ypTNM staging, but its accuracy is controversial. Based on multi-institutional data, this study developed a modified ypTNM staging, which is superior to the AJCC 8th edition ypTNM staging, allowing more accurate assessment of the prognosis of patients with gastric cancer after neoadjuvant therapy.

Redefining Conditional Overall and Disease-Free Survival After Curative Resection for Intrahepatic Cholangiocarcinoma: a Multi-institutional, International Study of 1221 patients

OBJECTIVES

To assess conditional survival (CS) according to recurrence status, as well as conditional disease-free survival (cDFS) among patients with intrahepatic cholangiocarcinoma (ICC).

METHODS

CS and cDFS were evaluated among ICC patients who underwent curative-intent resection for ICC by using a multi-institutional database. Five-year CS (CS5) at "x" years was calculated separately for patients who did and did not experience recurrence. The cDFS3 at "x" years was defined as the chance to be disease-free for an additional 3 years after not having experienced a recurrence for "x" years postoperatively.

RESULTS

Among 1221 patients, median OS was 36.8 months. While estimated actuarial OS decreased over time, CS5 increased as patients survived over longer periods of time and reached 93.9% at 4 years among 139 patients who did not experience a recurrence. Among the 725 (59.4%) patients who did experience a tumor recurrence, CS5 decreased to 17.7% the first postoperative year; however, CS5 subsequently increased to 79.7% for 81 patients who had survived 4 years after surgery. While actuarial DFS decreased from 54.6% at 1 year to 28.2% at 5 years, estimated cDFS3 following liver resection increased over time. Of note, patients with known risk factors for recurrence had even more marked improvements in cDFS3 over subsequent years versus patients without risk factors for recurrence.

CONCLUSION

CS and cDFS changed over time according to the presence of disease-specific risk factors, as well as the presence of recurrence.

Conditional survival and recurrence of remnant gastric cancer after surgical resection: A multi-institutional study

The present study was designed to evaluate the dynamic survival and recurrence of remnant gastric cancer (RGC) after radical resection and to provide a reference for the development of personalized follow-up strategies. A total of 298 patients were analyzed for their 3-year conditional overall survival (COS3), 3-year conditional disease-specific survival (CDSS3), corresponding recurrence and pattern changes, and associated risk factors. The 5-year overall survival (OS) and the 5-year disease-specific survival (DSS) of the entire cohort were 41.2% and 45.8%, respectively. The COS3 and CDDS3 of RGC patients who survived for 5 years were 84.0% and 89.8%, respectively. The conditional survival in patients with unfavorable prognostic characteristics showed greater growth over time than in those with favorable prognostic characteristics (eg, COS3, ≥T3: 46.4%-83.0%, Δ36.6% vs ≤T2: 82.4%-85.7%, Δ3.3%; P < 0.001). Most recurrences (93.5%) occurred in the first 3 years after surgery. The American Joint Committee on Cancer (AJCC) stage was the only factor that affected recurrence. Time-dependent Cox regression showed that for both OS and DSS, after 4 years of survival, the common prognostic factors that were initially judged lost their ability to predict survival (P > 0.05). Time-dependent logistic regression analysis showed that the AJCC stage independently affected recurrence within 2 years after surgery (P < 0.05). A postoperative follow-up model was developed for RGC patients. In conclusion, patients with RGC usually have a high likelihood of death or recurrence within 3 years after radical surgery. We developed a postoperative follow-up model for RGC patients of different stages, which may affect the design of future clinical trials.