ArticleCancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology2021
Updated Methodology for Projecting U.S.- and State-Level Cancer Counts for the Current Calendar Year: Part I: Spatio-temporal Modeling for Cancer Incidence.
Article in Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
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Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Evaluation and forecasting methods to estimate number of patients with non-Hodgkin lymphoma: a systematic literature review.Population health metrics · 2025Pooled it
- Spatiotemporal Modeling Approach to Mapping Geographic and Temporal Variation in Cancer Incidence Rates for US Counties.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2026Article
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- Exercise-induced βBrain, behavior, and immunity · 2025Article
- Nomogram for predicting the development of pneumonia after colorectal cancer surgery.Scientific reports · 2025Article
- Forecasting cancer incidence and prevalence using age-period-cohort and survivorship models: a practical, flexible, and interpretable framework.Frontiers in oncology · 2025Article
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- Exploring the Potential Role of Phytopharmaceuticals in Alleviating Toxicities of Chemotherapeutic Agents.Current protein & peptide science · 2024Review
- Invited Commentary: Predicting Incidence Rates of Rare Cancers-Adding Epidemiologic and Spatial Contexts.American journal of epidemiology · 2022Article
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- Colorectal cancer statistics, 2026.CA: a cancer journal for cliniciansObservational
- Prostate cancer statistics, 2025.CA: a cancer journal for cliniciansArticle
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- Cancer statistics for African American and Black people, 2025.CA: a cancer journal for cliniciansArticle
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Abstract
backgroundThe American Cancer Society (ACS) and the NCI collaborate every 5-8 years to update the methods for estimating numbers of new cancer cases and deaths in the current year in the United States and in every state and the District of Columbia. In this article, we reevaluate the statistical method for estimating unavailable historical incident cases which are needed for projecting the current year counts.
methodsWe compared the current county-level model developed in 2012 (M0) with three new models, including a state-level mixed effect model (M1) and two state-level hierarchical Bayes models with varying random effects (M2 and M3). We used 1996-2014 incidence data for 16 sex-specific cancer sites to fit the models. An average absolute relative deviation (AARD) comparing the observed with the model-specific predicted counts was calculated for each site. Models were also cross-validated for six selected sex-specific cancer sites.
resultsFor the cross-validation, the AARD ranged from 2.8% to 33.0% for M0, 3.3% to 31.1% for M1, 6.6% to 30.5% for M2, and 10.4% to 393.2% for M3. M1 encountered the least technical issues in terms of model convergence and running time.
conclusionsThe state-level mixed effect model (M1) was overall superior in accuracy and computational efficiency and will be the new model for the ACS current year projection project. IMPACT: In addition to predicting the unavailable state-level historical incidence counts for cancer surveillance, the updated algorithms have broad applicability for disease mapping and other activities of public health planning, advocacy, and research.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.