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Gastric Cancer with Radiographically Occult Metastatic Disease: Biology, Challenges, and Diagnostic Approaches.

ABSTRACT: Gastric adenocarcinoma is an aggressive cancer that demonstrates heterogeneous biology depending on patient ethnicity, tumor location, tumor type, and genetic profile. It remains the third leading cause of cancer deaths worldwide and was estimated to result in 782,000 deaths in 2018. Challenges exist in accurately assessing the disease burden, as available radiological staging often underestimates metastatic disease. This diagnostic handicap, along with the poor understanding of the heterogeneous biology of gastric cancer, has hindered the development of effective therapeutic solutions and thus halted improvement in patient outcomes over the last few decades. The management of occult peritoneal disease is complicated, as most patients are understaged by standard imaging studies and therefore thought to have local diseases. In this article, we systematically review recent literature on the limitations that are associated with standard radiographic staging, discuss recent molecular biology advances to better identify and diagnose occult peritoneal disease, and propose possible management strategies to approach this complicated clinical problem.

SUBMITTER: Sanjeevaiah A

PROVIDER: S-EPMC7139817 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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Gastric Cancer with Radiographically Occult Metastatic Disease: Biology, Challenges, and Diagnostic Approaches.

Sanjeevaiah Aravind A Park Haeseong H Fangman Benjamin B Porembka Matthew M

Cancers 20200305 3

Gastric adenocarcinoma is an aggressive cancer that demonstrates heterogeneous biology depending on patient ethnicity, tumor location, tumor type, and genetic profile. It remains the third leading cause of cancer deaths worldwide and was estimated to result in 782,000 deaths in 2018. Challenges exist in accurately assessing the disease burden, as available radiological staging often underestimates metastatic disease. This diagnostic handicap, along with the poor understanding of the heterogeneou ...[more]

PMID: 32150838

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Project description:BackgroundFecal occult blood test (FOBT)-based screening for colorectal cancer (CRC) reduces mortality, with earlier stage at diagnosis a prominent feature. Other characteristics of FOBT screen-detected cancers and any implications for clinical management have not been well explored.MethodsWe examined a multisite clinical registry to compare the characteristics and outcomes of FOBT screen-detected CRC via the Australian National Bowel Cancer Screening Program (NBCSP), which is offered biennially to individuals aged 50-74 years, and age-matched non-screen-detected CRC in the same registry. All statistical tests were 2-sided. Odds ratios (ORs) were calculated using the Baptista-Pike method, and hazard ratios via the log-rank method.ResultsOf 7153 registry patients diagnosed June 1, 2006, to June 30, 2020, 4142 (57.9%) were aged between 50 and 74 years. Excluding 406 patients with non-NBCSP screen-detected cancers and 35 patients with unknown method of detection, 473 (12.8%) were screen detected via the NBCSP, and 3228 (87.2%) were non-screen detected. Screen-detected patients were younger (mean age = 62.4 vs 64.2 years; P < .001) and more medically fit (OR for ASA score 1-2 = 1.91, 95% confidence interval [CI] = 1.51 to 2.41; P < .001). Pathologic characteristics within each stage favored the screen-detected patients. Stage III screen-detected colon cancers were more likely to receive adjuvant therapy (OR = 3.58, 95% CI = 1.52 to 8.36; P = .002). Screen-detected patients had superior relapse-free (hazard ratio = 0.41, 95% CI = 0.29 to 0.60; P < .001) and overall survival (hazard ratio = 0.22, 95% CI = 0.15 to 0.35; P < .001), which was maintained in matched stage comparisons and multivariable analysis.ConclusionsBeyond stage at diagnosis, multiple other factors associated with a favorable outcome are observed in FOBT screen-detected CRC. Given the substantial stage-by-stage differences in survival outcomes, if independently confirmed, individualized adjuvant therapy and surveillance strategies could be warranted for FOBT screen-detected cancers.

Project description:ImportanceOccult peritoneal metastasis frequently occurs in patients with advanced gastric cancer and is poorly diagnosed with currently available tools. Because the presence of peritoneal metastasis precludes the possibility of curative surgery, there is an unmet need for a noninvasive approach to reliably identify patients with occult peritoneal metastasis.ObjectiveTo assess the use of a deep learning model for predicting occult peritoneal metastasis based on preoperative computed tomography images.Design, setting, and participantsIn this multicenter, retrospective cohort study, a deep convolutional neural network, the Peritoneal Metastasis Network (PMetNet), was trained to predict occult peritoneal metastasis based on preoperative computed tomography images. Data from a cohort of 1225 patients with gastric cancer who underwent surgery at Sun Yat-sen University Cancer Center (Guangzhou, China) were used for training purposes. To externally validate the model, data were collected from 2 independent cohorts comprising a total of 753 patients with gastric cancer who underwent surgery at Nanfang Hospital (Guangzhou, China) or the Third Affiliated Hospital of Southern Medical University (Guangzhou, China). The status of peritoneal metastasis for all patients was confirmed by pathological examination of pleural specimens obtained during surgery. Detailed clinicopathological data were collected for each patient. Data analysis was performed between September 1, 2019, and January 31, 2020.Main outcomes and measuresThe area under the receiver operating characteristic curve (AUC) and decision curve were analyzed to evaluate performance in predicting occult peritoneal metastasis.ResultsA total of 1978 patients (mean [SD] age, 56.0 [12.2] years; 1350 [68.3%] male) were included in the study. The PMetNet model achieved an AUC of 0.946 (95% CI, 0.927-0.965), with a sensitivity of 75.4% and a specificity of 92.9% in external validation cohort 1. In external validation cohort 2, the AUC was 0.920 (95% CI, 0.848-0.992), with a sensitivity of 87.5% and a specificity of 98.2%. The discrimination performance of PMetNet was substantially higher than conventional clinicopathological factors (AUC range, 0.51-0.63). In multivariable logistic regression analysis, PMetNet was an independent predictor of occult peritoneal metastasis.Conclusions and relevanceThe findings of this cohort study suggest that the PMetNet model can serve as a reliable noninvasive tool for early identification of patients with clinically occult peritoneal metastasis, which will inform individualized preoperative treatment decision-making and may avoid unnecessary surgery and complications. These results warrant further validation in prospective studies.

Dataset Information

Gastric Cancer with Radiographically Occult Metastatic Disease: Biology, Challenges, and Diagnostic Approaches.

Publications

Gastric Cancer with Radiographically Occult Metastatic Disease: Biology, Challenges, and Diagnostic Approaches.

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