Med Decis Making - Clarifying differences in natural history between models of screening: the case of colorectal cancer.

Tópicos

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Resumo

CKGROUND: Microsimulation 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.METHODS: The 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).RESULTS: Projected 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.CONCLUSIONS: The 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.

Resumo Limpo

ckground microsimul model import decis support tool screen howev complex make difficult understand limit realiz full potenti therefor import develop document clarifi structur assumpt author demonstr problem explor solut natur histori use independ develop colorect cancer screen modelsmethod author first project effect costeffect colonoscopi screen model crcspin simcrc miscan next provid convent present model includ inform structur paramet valu final report simul reduct clinic cancer incid follow onetim complet remov adenoma preclin cancer model call new measur maximum clinic incid reduct mclirresult project effect vari wide across model exampl estim mortal reduct colonoscopi screen everi year age year surveil adenoma patient rang given convent inform difficult explain differ larg differ structur make paramet valu incompar contrast mclir clear show impact model differ key featur natur histori dwell time preclin diseas dwell time vari year across model help explain differ project screen effectivenessconclus author propos new measur mclir summar implic predict screen effect differ natur histori assumpt includ mclir standard descript screen model improv transpar model

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