Survival Trends of Patients With Surgically Resected Gastric Cardia Cancer From 1988 to 2015: A Population-based Study in the United States. Am J Clin Oncol. 2019;42:581-587. [PMID: 31157623 DOI: 10.1097/coc.0000000000000558]

Neural network-based prognostic predictive tool for gastric cardiac cancer: the worldwide retrospective study

BACKGROUNDS

The incidence of gastric cardiac cancer (GCC) has obviously increased recently with poor prognosis. It's necessary to compare GCC prognosis with other gastric sites carcinoma and set up an effective prognostic model based on a neural network to predict the survival of GCC patients.

METHODS

In the population-based cohort study, we first enrolled the clinical features from the Surveillance, Epidemiology and End Results (SEER) data (n = 31,397) as well as the public Chinese data from different hospitals (n = 1049). Then according to the diagnostic time, the SEER data were then divided into two cohorts, the train cohort (patients were diagnosed as GCC in 2010-2014, n = 4414) and the test cohort (diagnosed in 2015, n = 957). Age, sex, pathology, tumor, node, and metastasis (TNM) stage, tumor size, surgery or not, radiotherapy or not, chemotherapy or not and history of malignancy were chosen as the predictive clinical features. The train cohort was utilized to conduct the neural network-based prognostic predictive model which validated by itself and the test cohort. Area under the receiver operating characteristics curve (AUC) was used to evaluate model performance.

RESULTS

The prognosis of GCC patients in SEER database was worse than that of non GCC (NGCC) patients, while it was not worse in the Chinese data. The total of 5371 patients were used to conduct the model, following inclusion and exclusion criteria. Neural network-based prognostic predictive model had a satisfactory performance for GCC overall survival (OS) prediction, which owned 0.7431 AUC in the train cohort (95% confidence intervals, CI, 0.7423-0.7439) and 0.7419 in the test cohort (95% CI, 0.7411-0.7428).

CONCLUSIONS

GCC patients indeed have different survival time compared with non GCC patients. And the neural network-based prognostic predictive tool developed in this study is a novel and promising software for the clinical outcome analysis of GCC patients.

Association between trends of mortality and incidence, survival and stage at diagnosis for six digestive and respiratory cancers in United States (2009-2013)

BACKGROUND

A decrease in cancer mortality has been reported in the USA, possibly due to decreased incidence, downstaging and improved survival. The aim of the present study is to estimate the contribution of these factors on the trend in cancer mortality.

METHODS

Data on incidence, mortality, stage at diagnosis, and overall and stage-specific survival for six common digestive and respiratory cancers (esophagus, stomach, colorectal, liver, pancreas and lung) during 2009-2013 in the USA from the surveillance, epidemiology and end results (SEER) program, was analyzed using generalized linear models separately among men and women.

RESULTS

Our study showed a decrease in mortality for esophageal (-0.09/100 000/year and -0.03/100 000/year), stomach (-0.11/100 000/year and -0.05/100 000/year), colorectal (-0.45/100 000/year and -0.29/100 000/year) and lung cancer (-1.89/100 000/year in men and -0.78/100 000/year in women) in men and women, respectively: for all of them, except lung cancer in women, there was a decrease in the incidence of comparable or greater magnitude; stage distribution and survival also contributed to the decrease in mortality for lung and colorectal cancer. Mortality from pancreatic cancer was stable: an increase in incidence was counterbalanced by an improvement in survival. Mortality from liver cancer increased, driven by an increase in mortality that was not offset by favorable trends in stage distribution and survival.

CONCLUSIONS

Trends in mortality were primarily affected by changes in incidence; an increase in the proportion of local stage at diagnosis and improved survival, although evident for some cancers, played a lesser role in mortality trends.

Changing trends of clinicopathologic features and survival duration after surgery for gastric cancer in Northeast China

BACKGROUND

Through analyzing the data from a single institution in Northeast China, this study revealed the possible clinicopathologic characteristics that influence the prognosis of patients with gastric cancer (GC).

AIM

To evaluate the changing trends of clinicopathologic features and survival duration after surgery in patients with GC in Northeast China, which is a high-prevalence area of GC.

METHODS

The study analyzed the difference in clinicopathologic features and survival duration after surgery of 5887 patients who were histologically diagnosed with GC at the Harbin Medical University Cancer Hospital. The study mainly analyzed the data in three periods, 2000 to 2004 (Phase 1), 2005 to 2009 (Phase 2), and 2010 to 2014 (Phase 3).

RESULTS

Over time, the postoperative survival rate significantly increased from 2000 to 2014. In the past 15 years, compared with Phases 1 and 2, the tumor size was smaller in Phase 3 (P < 0.001), but the proportion of high-medium differentiated tumors increased (P < 0.001). The proportion of early GC gradually increased from 3.9% to 14.4% (P < 0.001). A surprising improvement was observed in the mean number of retrieved lymph nodes, ranging from 11.4 to 27.5 (P < 0.001). The overall 5-year survival rate increased from 24% in Phase 1 to 43.8% in Phase 3. Through multivariate analysis, it was found that age, tumor size, histologic type, tumor-node-metastasis stage, depth of invasion, lymph node metastasis, surgical approach, local infiltration, radical extent, number of retrieved lymph nodes, and age group were independent risk factors that influenced the prognosis of patients with GC.

CONCLUSION

The clinical features of GC in Northeast China changed during the observation period. The increasing detection of early GC and more standardized surgical treatment effectively prolonged lifetimes.

Prognostic significance of Borrmann type combined with vessel invasion status in advanced gastric cancer

BACKGROUND

Borrmann classification (types I-IV) for the detection of advanced gastric cancer has been accepted worldwide, and lymphatic and/or blood vessel invasion (LBVI) status is related to the poor prognosis after gastric cancer.

AIM

To evaluate the significance of Borrmann type combined with LBVI status in predicting the prognosis of advanced gastric cancer.

METHODS

We retrospectively studied the clinicopathological characteristics and long-term survival data of 2604 patients who were diagnosed with advanced gastric adenocarcinoma at Harbin Medical University Cancer Hospital from January 2009 to December 2013. Categorical variables were evaluated by the Pearson’s χ² test, the Kaplan-Meier method was used to identify differences in cumulative survival rates, and the Cox proportional hazards model was used for multivariate prognostic analysis.

RESULTS

A total of 2604 patients were included in this study. The presence of LVBI [LBVI (+)] and Borrmann type (P = 0.001), tumor location (P < 0.001), tumor size (P < 0.001), histological type (P < 0.001), tumor invasion depth (P < 0.001), number of metastatic lymph nodes (P < 0.001), and surgical method (P < 0.001) were significantly correlated with survival. When analyzing the combination of the Borrmann classification and LBVI status, we found that patients with Borrmann type III disease and LBVI (+) had a similar 5-year survival rate to those with Borrmann IV + LBVI (-) (16.4% vs 13.1%, P = 0.065) and those with Borrmann IV + LBVI (+) (16.4% vs 11.2%, P = 0.112). Subgroup analysis showed that the above results were true for any pT stage and any tumor location. Multivariate Cox regression analysis showed that Borrmann classification (P = 0.023), vascular infiltration (P < 0.001), tumor size (P = 0.012), pT stage (P < 0.001), pN stage (P < 0.001), and extent of radical surgery (P < 0.001) were independent prognostic factors for survival.

CONCLUSION

Since patients with Borrmann III disease and LBVI (+) have the same poor prognosis as those with Borrmann IV disease, more attention should be paid to patients with Borrmann III disease and LBVI (+) during diagnosis and treatment, regardless of the pT stage and tumor location, to obtain better survival results.

A clinical metabolomics-based biomarker signature as an approach for early diagnosis of gastric cardia adenocarcinoma

Gastric cardia adenocarcinoma (GCA) has a high mortality rate worldwide; however, current early diagnostic methods lack efficacy. Therefore, the aim of the present study was to identify potential biomarkers for the early diagnosis of GCA. Global metabolic profiles were obtained from plasma samples collected from 21 patients with GCA and 48 healthy controls using ultra-performance liquid chromatography/quadrupole-time-of-flight mass spectrometry. The orthogonal partial least squares discrimination analysis model was applied to distinguish patients with GCA from healthy controls and to identify potential biomarkers. Metabolic pathway analysis was performed using MetaboAnalyst (version 4.0) and revealed that ‘glycerophospholipid metabolism’, ‘linoleic acid metabolism’, ‘fatty acid biosynthesis’ and ‘primary bile acid biosynthesis’ were significantly associated with GCA. In addition, an early diagnostic model for GCA was established based on the relative levels of four key biomarkers, including phosphorylcholine, glycocholic acid, L-acetylcarnitine and arachidonic acid. The area under the receiver operating characteristic curve revealed that the diagnostic model had a sensitivity and specificity of 0.977 and 0.952, respectively. The present study demonstrated that metabolomics may aid the identification of the mechanisms underlying the pathogenesis of GCA. In addition, the proposed diagnostic method may serve as a promising approach for the early diagnosis of GCA.