Gastric Cancer

Background

Gastric cancer (GC), specifically gastric adenocarcinoma, is the fifth most common cancer and the third leading cause of cancer death globally. Additionally there is an alarming rise in early onset gastric cancer in the U.S. and hereditary types of gastric cancer are very difficult to screen for and are usually diagnosed at advanced stages, GC has a 5-year survival rate of ~30%.¹ In the U.S. Several factors are changing the landscape of GC prevention, including a better understanding of the disease natural history,^2-4 new evidence on prevention from prospective studies^5-9 and anticipated results from ongoing randomized controlled trials.^{10, 11} As early GC detection can improve survival by allowing for curative surgical or noninvasive endoscopic resection,¹² new targeted approaches to GC prevention have the potential to markedly improve population health and reduce GC mortality within the U.S.

Organization of the CISNET Gastric Group

Figure 1: The CISNET Gastric group is composed of three gastric cancer models: the Columbia University Gastric Cancer Simulation Model (GSiMo), the Harvard and Stanford University Gastric Cancer Model, and the Erasmus University Medical Center Microsimulation Screening Analysis Gastric Cancer Model (MISCAN-Gastric).

Common structures and inputs

All three models include detailed natural history components that have been calibrated to Surveillance, Epidemiology and End Results (SEER) GC incidence and include clinical components or realism that allows for analyses that evaluate and determine the clinical effectiveness of specific interventions for GC care.

Each model differs in its timeframe and cycles, with Harvard-GC using annual cycles, GSiMo employing monthly cycles, and MISCAN-GC utilizing continuous cycles. The starting population also varies, with Harvard-GC and MISCAN-GC beginning at birth, whereas GSiMo starts at age 18. The models simulate different racial and ethnic subgroups, with Harvard-GC covering a broader range, including Hispanic, Asian/Pacific Islander, and American Indian/Alaska Native populations, while the other two models focus on Non-Hispanic White and Black individuals.

In terms of natural history, all models account for gastric cancer histological subtypes, but Harvard-GC includes the most detailed categorization, including MALT lymphoma, GIST, and NET, whereas MISCAN-GC only considers intestinal-type adenocarcinoma. The models also incorporate different risk factors, with Harvard-GC including H. pylori, smoking, and residual factors, while the others primarily focus on H. pylori. The transition probabilities among health states vary, with Harvard-GC using constant probabilities with some age- and time-dependent elements, GSiMo incorporating age-specific monthly probabilities with relative risks based on H. pylori status, and MISCAN-GC modeling competing events with age-specific transition times.

Calibration relies on SEER data across all models, but Harvard-GC considers a wider range of subgroups, including race/ethnicity, nativity, and multiple histology types. Parameter calibration differs as well, with Harvard-GC using multiple parameter sets (50-100) and simulated annealing, GSiMo employing a single set with simulated annealing, and MISCAN-GC using a genetic algorithm. Regarding risk factor inputs, Harvard-GC utilizes demographic and NHANES data to model H. pylori and smoking prevalence, while the other models focus only on H. pylori prevalence. Competing mortality is incorporated differently, with Harvard-GC and GSiMo using demographic generators, while MISCAN-GC relies on observed data.

Impact

The overarching goal of these models is to drive transformative improvements in public health by addressing gastric cancer mortality and morbidity through a targeted, data-driven approach. By focusing on the highest risk patient groups, both in the U.S. and globally, these models aim to reduce the disproportionate burden of gastric cancer among those with numerous risk factors that bear the greatest burden of gastric cancer in the U.S. and the world. They will be instrumental in evaluating the cost-effectiveness of primary and secondary prevention strategies, such as H. pylori test-and-treat programs, smoking cessation initiatives, and endoscopic surveillance, which have the potential to significantly reduce incidence and mortality rates. Beyond the U.S., these models will be adapted and calibrated for global applications, guiding policymakers in implementing evidence-based cancer prevention strategies worldwide. Key public health outcomes include gastric cancer cases prevented, deaths averted, and gains in life years (LYs) and quality-adjusted life years (QALYs).

References

1. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin. 2012;62(1):10-29. Epub 2012/01/13. doi: 10.3322/caac.20138. PubMed PMID: 22237781.
2. Kumar S, Metz DC, Ellenberg S, Kaplan DE, Goldberg DS. Risk Factors and Incidence of Gastric Cancer After Detection of Helicobacter pylori Infection: A Large Cohort Study. Gastroenterology. 2020;158(3):527-36 e7. Epub 2019/10/28. doi: 10.1053/j.gastro.2019.10.019. PubMed PMID: 31654635; PMCID: PMC7010558.
3. Li D, Bautista MC, Jiang SF, Daryani P, Brackett M, Armstrong MA, Hung YY, Postlethwaite D, Ladabaum U. Risks and Predictors of Gastric Adenocarcinoma in Patients with Gastric Intestinal Metaplasia and Dysplasia: A Population-Based Study. Am J Gastroenterol. 2016;111(8):1104-13. Epub 2016/05/18. doi: 10.1038/ajg.2016.188. PubMed PMID: 27185078.
4. Sonnenberg A, Genta RM. Changes in the Gastric Mucosa With Aging. Clin Gastroenterol Hepatol. 2015;13(13):2276-81. Epub 2015/03/01. doi: 10.1016/j.cgh.2015.02.020. PubMed PMID: 25724703.
5. Piazuelo MB, Bravo LE, Mera RM, Camargo MC, Bravo JC, Delgado AG, Washington MK, Rosero A, Garcia LS, Realpe JL, Cifuentes SP, Morgan DR, Peek RM, Jr., Correa P, Wilson KT. The Colombian chemoprevention trial. Twenty-year follow-up of a cohort of patients with gastric precancerous lesions. Gastroenterology. 2020. Epub 2020/11/22. doi: 10.1053/j.gastro.2020.11.017. PubMed PMID: 33220252.
6. Choi IJ, Kook MC, Kim YI, Cho SJ, Lee JY, Kim CG, Park B, Nam BH. Helicobacter pylori Therapy for the Prevention of Metachronous Gastric Cancer. N Engl J Med. 2018;378(12):1085-95. Epub 2018/03/22. doi: 10.1056/NEJMoa1708423. PubMed PMID: 29562147.
7. Choi IJ, Kim CG, Lee JY, Kim YI, Kook MC, Park B, Joo J. Family History of Gastric Cancer and Helicobacter pylori Treatment. N Engl J Med. 2020;382(5):427-36. Epub 2020/01/30. doi: 10.1056/NEJMoa1909666. PubMed PMID: 31995688.
8. Li WQ, Ma JL, Zhang L, Brown LM, Li JY, Shen L, Pan KF, Liu WD, Hu Y, Han ZX, Crystal-Mansour S, Pee D, Blot WJ, Fraumeni JF, Jr., You WC, Gail MH. Effects of Helicobacter pylori treatment on gastric cancer incidence and mortality in subgroups. J Natl Cancer Inst. 2014;106(7):dju116. Epub 2014/06/14. doi: 10.1093/jnci/dju116. PubMed PMID: 24925350; PMCID: 4067110.
9. Ma JL, Zhang L, Brown LM, Li JY, Shen L, Pan KF, Liu WD, Hu Y, Han ZX, Crystal-Mansour S, Pee D, Blot WJ, Fraumeni JF, Jr., You WC, Gail MH. Fifteen-year effects of Helicobacter pylori, garlic, and vitamin treatments on gastric cancer incidence and mortality. J Natl Cancer Inst. 2012;104(6):488-92. Epub 2012/01/25. doi: 10.1093/jnci/djs003. PubMed PMID: 22271764; PMCID: PMC3309129.
10. Park J, Nam B-H, Herrero R, Choi I. Effect of Helicobacter pylori Eradication on Gastric Cancer Prevention in Korea: A Randomized Controlled Clinical Trial. In: Matsui S, Crowley J, editors. Frontiers of Biostatistical Methods and Applications in Clinical Oncology 2017.
11. Pan KF, Zhang L, Gerhard M, Ma JL, Liu WD, Ulm K, Wang JX, Zhang L, Zhang Y, Bajbouj M, Zhang LF, Li M, Vieth M, Liu RY, Quante M, Wang LH, Suchanek S, Zhou T, Guan WX, Schmid R, Classen M, You WC. A large randomised controlled intervention trial to prevent gastric cancer by eradication of Helicobacter pylori in Linqu County, China: baseline results and factors affecting the eradication. Gut. 2016;65(1):9-18. Epub 2015/05/20. doi: 10.1136/gutjnl-2015-309197. PubMed PMID: 25986943.
12. Choi KS, Jun JK, Suh M, Park B, Noh DK, Song SH, Jung KW, Lee HY, Choi IJ, Park EC. Effect of endoscopy screening on stage at gastric cancer diagnosis: results of the National Cancer Screening Programme in Korea. British journal of cancer. 2015;112(3):608-12. Epub 2014/12/09. doi: 10.1038/bjc.2014.608. PubMed PMID: 25490528./li>