Development of an Empirically Calibrated Model of Gastric Cancer in Two High-Risk Countries

Yeh, Jennifer M.; Kuntz, Karen M.; Ezzati, Majid; Hur, Chin; Kong, Chung Yin; Goldie, Sue J.

doi:10.1158/1055-9965.epi-07-2539

Cited by 26 publications

(33 citation statements)

References 29 publications

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“…This study contributes new information to the field of PDAC screening by introducing contemporary simulation methods that are being used to develop and analyze cancer policy models in other organ systems (33, 36, 49, 55–56). Our model is calibrated to National Cancer Institute SEER data, thereby leveraging high-quality data that are representative of the U.S. population to model pancreatic cancer.…”

Section: Discussionmentioning

confidence: 99%

Targeted Screening of Individuals at High Risk for Pancreatic Cancer: Results of a Simulation Model

Pandharipande¹,

Heberle

Dowling³

et al. 2015

Radiology

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Purpose To identify when, from the standpoint of relative risk, MRI-based pancreatic cancer screening may be effective in patients with a known or suspected genetic predisposition. Methods We developed a Markov model of pancreatic ductal adenocarcinoma (PDAC). The model was calibrated to National Cancer Institute Surveillance, Epidemiology and End Results registry data and informed by the published literature. A hypothetical screening strategy was evaluated in which all population individuals underwent one-time MRI screening at age 50. Screening outcomes for individuals with average PDAC risk (base case) were compared to those with increased risk, to assess for differential benefits in populations with a known or suspected genetic predisposition. Effects of varying key inputs, including MRI performance, surgical mortality, and screening age, were evaluated in sensitivity analysis. Results In the base case, screening resulted in a small number of cancer deaths averted (39/100,000 (men), 38/100,000 (women)) and a net decrease in life expectancy, driven by surgical deaths from false-positive results (-3 days (men), −4 days (women)). Life expectancy gains were achieved if individuals’ risk for PDAC exceeded 2.4× (men) or 2.7× (women) that of the general population. When relative risk increased further, for example to 30× that of the general population, averted cancer deaths and life expectancy gains increased substantially (1,219/100,000, 65 days (men) and 1,204/100,000, 71 days (women)). Results were additionally sensitive to MRI specificity and the surgical mortality rate. Conclusions Although PDAC screening with MRI for the entire population is not effective, individuals with even modestly increased risk may benefit.

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Section: Discussionmentioning

confidence: 99%

Targeted Screening of Individuals at High Risk for Pancreatic Cancer: Results of a Simulation Model

Pandharipande¹,

Heberle

Dowling³

et al. 2015

Radiology

Self Cite

View full text Add to dashboard Cite

show abstract

“…This study contributes new information to the field of PDAC screening by introducing contemporary simulation methods that are being used to develop and analyze cancer policy models in other organ systems (33,36,50,55,56). Our model is calibrated to National Cancer Institute Surveillance, Epidemiology, and End Results data, thereby leveraging high-quality data that are representative of the U.S. population to model pancreatic cancer.…”

Section: Discussionmentioning

confidence: 99%

Targeted Screening of Individuals at High Risk for Pancreatic Cancer: Results of a Simulation Model

Pandharipande¹,

Heberle²,

Dowling³

et al. 2016

Radiology

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Purpose:To identify when, from the standpoint of relative risk, magnetic resonance (MR) imaging-based screening may be effective in patients with a known or suspected genetic predisposition to pancreatic cancer. Materials and Methods:The authors developed a Markov model of pancreatic ductal adenocarcinoma (PDAC). The model was calibrated to National Cancer Institute Surveillance, Epidemiology, and End Results registry data and informed by the literature. A hypothetical screening strategy was evaluated in which all population individuals underwent one-time MR imaging screening at age 50 years. Screening outcomes for individuals with an average risk for PDAC ("base case") were compared with those for individuals at an increased risk to assess for differential benefits in populations with a known or suspected genetic predisposition. Effects of varying key inputs, including MR imaging performance, surgical mortality, and screening age, were evaluated with a sensitivity analysis. Results:In the base case, screening resulted in a small number of cancer deaths averted (39 of 100 000 men, 38 of 100 000 women) and a net decrease in life expectancy (23 days for men, 24 days for women), which was driven by unnecessary pancreatic surgeries associated with false-positive results. Life expectancy gains were achieved if an individual's risk for PDAC exceeded 2.4 (men) or 2.7 (women) times that of the general population. When relative risk increased further, for example to 30 times that of the general population, averted cancer deaths and life expectancy gains increased substantially (1219 of 100 000 men, life expectancy gain: 65 days; 1204 of 100 000 women, life expectancy gain: 71 days). In addition, results were sensitive to MR imaging specificity and the surgical mortality rate. Conclusion:Although PDAC screening with MR imaging for the entire population is not effective, individuals with even modestly increased risk may benefit.q RSNA, 2014

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“…The current analysis relied on visual assessment of trend, acceptance window (95% confidence interval of patient-level data), and percentage deviation from the mean, all of which are consistent with practical applications in the literature and can be implemented in settings with limited computing capacity and statistical support. 25,32,33,38,39 …”

Section: Discussionmentioning

confidence: 99%

Performance of a Mathematical Model to Forecast Lives Saved from HIV Treatment Expansion in Resource-Limited Settings

et al. 2014

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Background International guidelines recommend HIV treatment expansion in resource-limited settings, but funding availability is uncertain. We evaluated performance of a model that forecasts lives saved through continued HIV treatment expansion in Haiti. Methods We developed a computer-based, mathematical model of HIV disease and used incidence density analysis of patient-level Haitian data to derive model parameters for HIV disease progression. We assessed internal validity of model predictions and internally calibrated model inputs when model predictions did not fit the patient-level data. We then derived uncertain model inputs related to diagnosis and linkage to care, pre-treatment retention, and enrollment on HIV treatment through an external calibration process that selected input values by comparing model predictions to Haitian population-level data. Model performance was measured by fit to event-free survival (patient-level) and number receiving HIV treatment over time (population-level). Results For a cohort of newly HIV-infected individuals with no access to HIV treatment, the model predicts median AIDS-free survival of 9.0 years pre-calibration and 6.6 years post-calibration versus 5.8 years (95% CI 5.1, 7.0) from the patient-level data. After internal validation and calibration, 16 of 17 event-free survival measures (94%) had a mean percentage deviation between model predictions and the empiric data of <6%. After external calibration, the percentage deviation between model predictions and population-level data on the number on HIV treatment was <1% over time. Conclusions Validation and calibration resulted in a good-fitting model appropriate for health policy decision making. Using local data in a policy model-building process is feasible in resource-limited settings.

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Development of an Empirically Calibrated Model of Gastric Cancer in Two High-Risk Countries

Cited by 26 publications

References 29 publications

Targeted Screening of Individuals at High Risk for Pancreatic Cancer: Results of a Simulation Model

Targeted Screening of Individuals at High Risk for Pancreatic Cancer: Results of a Simulation Model

Targeted Screening of Individuals at High Risk for Pancreatic Cancer: Results of a Simulation Model

Performance of a Mathematical Model to Forecast Lives Saved from HIV Treatment Expansion in Resource-Limited Settings

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