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Cancer Sites
Established in 2000 by the National Cancer Institute (NCI), CISNET's projects comprise the following cancer sites: bladder, breast, cervical, colorectal, esophagus (funded through 2022), gastric, lung, multiple myeloma, prostate, and uterine.
CISNET invites inquiries from outside groups regarding collaborations on cancer control issues amenable to modeling (see Contact Us).
Models focus on the natural course of the disease and will address questions on its prevention, diagnosis, treatment, and surveillance.
Models focus on critical early detection and clinical management issues, and are being used to evaluate mortality outcomes, harms and costs of rapidly evolving cancer control paradigms.
Models focus on the natural history of human papillomavirus (HPV) and cervical carcinogenesis, the impact of HPV vaccination and screening, the comparative effectiveness of HPV vaccination and screening strategies, and approaches to improve cervical cancer outcomes.
Models focus on the natural history of the disease and the impact of interventions, including targeted screening and treatment, on mortality.
Models are being used to produce innovative changes to gastric cancer care with a focus on high-risk populations that bear the greatest gastric cancer burden.
Models focus on tobacco control in the US and other countries, lung cancer screening and early detection, targeted therapies and immunotherapies, and investigation of the synergistic impacts of those strategies.
Models focus on the natural history of the disease and the impact of novel strategies in preventing and treating multiple myeloma, with the goals of reducing its burden and improving outcomes.
Models focus on investigating risk-based screening and treatment strategies and approaches for improving outcomes.
Models are being used to inform strategies for reducing uterine cancer incidence and mortality by improving prevention, screening, and treatment.
Historical Sites
Models focus on evaluating the potential of new screening technologies, prevention methods, genomic and other biomarkers, and clinical prediction tools.