Amanda F Petrik, Eric S Johnson, Matthew Slaughter, Michael C Leo, Jamie Thompson, Rajasekhara R Mummadi, Ricardo Jimenez, Syed Akmal Hussain, Gloria Coronado
{"title":"The recalibration and redevelopment of a model to calculate patients' probability of completing a colonoscopy following an abnormal fecal test.","authors":"Amanda F Petrik, Eric S Johnson, Matthew Slaughter, Michael C Leo, Jamie Thompson, Rajasekhara R Mummadi, Ricardo Jimenez, Syed Akmal Hussain, Gloria Coronado","doi":"10.1177/09691413231195568","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Fecal immunochemical testing (FIT) is an effective screening tool for colorectal cancer. If an FIT is abnormal, a follow-up colonoscopy is necessary to remove polyps or find cancers. We sought to develop a usable risk prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test.</p><p><strong>Methods: </strong>We recalibrated and then redeveloped a prediction model in federally qualified health centers (FQHCs), using a retrospective cohort of patients aged 50-75 with an abnormal FIT test and clinical data. Logistic and Cox regressions were used to recalibrate and then redevelop the model.</p><p><strong>Results: </strong>The initial risk model used data from eight FQHCs (26 clinics) including 1723 patients. When we applied the model to a single large FQHC (34 clinics, 884 eligible patients), the model did not recalibrate successfully (c-statistic dropped more than 0.05, from 0.66 to 0.61). The model was redeveloped in the same FQHC in a cohort of 1401 patients with a c-statistic of 0.65.</p><p><strong>Conclusions: </strong>The original model developed in a group of FQHCs did not adequately recalibrate in the single large FQHC. Health system, patient characteristics or data differences may have led to the inability to recalibrate the model. However, the redeveloped model provides an adequate model for the single FQHC.</p>","PeriodicalId":51089,"journal":{"name":"Journal of Medical Screening","volume":" ","pages":"28-34"},"PeriodicalIF":2.6000,"publicationDate":"2024-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10909915/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Screening","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/09691413231195568","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2023/9/4 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PUBLIC, ENVIRONMENTAL & OCCUPATIONAL HEALTH","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: Fecal immunochemical testing (FIT) is an effective screening tool for colorectal cancer. If an FIT is abnormal, a follow-up colonoscopy is necessary to remove polyps or find cancers. We sought to develop a usable risk prediction model to identify patients unlikely to complete a colonoscopy following an abnormal FIT test.
Methods: We recalibrated and then redeveloped a prediction model in federally qualified health centers (FQHCs), using a retrospective cohort of patients aged 50-75 with an abnormal FIT test and clinical data. Logistic and Cox regressions were used to recalibrate and then redevelop the model.
Results: The initial risk model used data from eight FQHCs (26 clinics) including 1723 patients. When we applied the model to a single large FQHC (34 clinics, 884 eligible patients), the model did not recalibrate successfully (c-statistic dropped more than 0.05, from 0.66 to 0.61). The model was redeveloped in the same FQHC in a cohort of 1401 patients with a c-statistic of 0.65.
Conclusions: The original model developed in a group of FQHCs did not adequately recalibrate in the single large FQHC. Health system, patient characteristics or data differences may have led to the inability to recalibrate the model. However, the redeveloped model provides an adequate model for the single FQHC.
期刊介绍:
Journal of Medical Screening, a fully peer reviewed journal, is concerned with all aspects of medical screening, particularly the publication of research that advances screening theory and practice. The journal aims to increase awareness of the principles of screening (quantitative and statistical aspects), screening techniques and procedures and methodologies from all specialties. An essential subscription for physicians, clinicians and academics with an interest in screening, epidemiology and public health.