ArticleMedical decision making : an international journal of the Society for Medical Decision Making
Clarifying differences in natural history between models of screening: the case of colorectal cancer.
Article in Medical decision making : an international journal of the Society for Medical Decision Making. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 2 of them syntheses that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
26 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Benefits of colorectal cancer screening using fecal immunochemical testing with varying positivity thresholds by age and sex.Journal of the National Cancer Institute · 2025Pooled it
- Economic evaluations of colorectal cancer screening: A systematic review and quality assessment.Clinics (Sao Paulo, Brazil) · 2023Pooled it
- Lung cancer detectability by test, histology, stage, and gender: estimates from the NLST and the PLCO trials.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2015Trial
- Emulator-Based Bayesian Calibration of the CISNET Colorectal Cancer Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- The Impact of Model Assumptions on Personalized Lung Cancer Screening Recommendations.Medical decision making : an international journal of the Society for Medical Decision Making · 2024Article
- Revisiting the standard blueprint for biomarker development to address emerging cancer early detection technologies.Journal of the National Cancer Institute · 2024Review
- Emulator-based Bayesian calibration of the CISNET colorectal cancer models.medRxiv : the preprint server for health sciences · 2024Article
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- Comparison of Simulated Outcomes Between Stool- and Blood-Based Colorectal Cancer Screening Tests.Population health management · 2023Article
- Shopping for New Cancer Screening Tests.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2023Article
- A progressive three-state model to estimate time to cancer: a likelihood-based approach.BMC medical research methodology · 2022Article
- Microsimulation Model for Prevention and Intervention of Coloretal Cancer in China (MIMIC-CRC): Development, Calibration, Validation, and Application.Frontiers in oncology · 2022Article
- Cost-effectiveness of prophylactic hysterectomy in first-degree female relatives with Lynch syndrome of patients diagnosed with colorectal cancer in the United States: a microsimulation study.Cancer medicine · 2021Article
- Impact of Knowledge and Risk Perceptions on Older Adults' Intention for Surveillance Colonoscopy.Journal of clinical gastroenterology · 2021Article
- The Impact of Different Screening Model Structures on Cervical Cancer Incidence and Mortality Predictions: The Maximum Clinical Incidence Reduction (MCLIR) Methodology.Medical decision making : an international journal of the Society for Medical Decision Making · 2020Article
- Article
- Comparing CISNET Breast Cancer Models Using the Maximum Clinical Incidence Reduction Methodology.Medical decision making : an international journal of the Society for Medical Decision Making · 2018Article
- Effect of Time to Diagnostic Testing for Breast, Cervical, and Colorectal Cancer Screening Abnormalities on Screening Efficacy: A Modeling Study.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2018Article
- CMOST: an open-source framework for the microsimulation of colorectal cancer screening strategies.BMC medical informatics and decision making · 2017Article
- Validation of Models Used to Inform Colorectal Cancer Screening Guidelines: Accuracy and Implications.Medical decision making : an international journal of the Society for Medical Decision Making · 2016Article
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10 authors.
Funding
Abstract
backgroundMicrosimulation models are important decision support tools for screening. However, their complexity makes them difficult to understand and limits realization of their full potential. Therefore, it is important to develop documentation that clarifies their structure and assumptions. The authors demonstrate this problem and explore a solution for natural history using 3 independently developed colorectal cancer screening models.
methodsThe authors first project effectiveness and cost-effectiveness of colonoscopy screening for the 3 models (CRC-SPIN, SimCRC, and MISCAN). Next, they provide a conventional presentation of each model, including information on structure and parameter values. Finally, they report the simulated reduction in clinical cancer incidence following a one-time complete removal of adenomas and preclinical cancers for each model. They call this new measure the maximum clinical incidence reduction (MCLIR).
resultsProjected effectiveness varies widely across models. For example, estimated mortality reduction for colonoscopy screening every 10 years from age 50 to 80 years, with surveillance in adenoma patients, ranges from 65% to 92%. Given only conventional information, it is difficult to explain these differences, largely because differences in structure make parameter values incomparable. In contrast, the MCLIR clearly shows the impact of model differences on the key feature of natural history, the dwell time of preclinical disease. Dwell times vary from 8 to 25 years across models and help explain differences in projected screening effectiveness.
conclusionsThe authors propose a new measure, the MCLIR, which summarizes the implications for predicted screening effectiveness of differences in natural history assumptions. Including the MCLIR in the standard description of a screening model would improve the transparency of these models.
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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.