An electronic health record-based tool could improve accuracy and eliminate bias in provider estimation of the risk of death from other causes among men with nonmetastatic cancer.
To recalibrate and validate the Veterans Aging Cohort Study Charlson Comorbidity Index (VACS-CCI) to predict non-prostate cancer mortality (non-PCM) and to compare it with a tool predicting prostate cancer mortality (PCM).
An observational cohort of men with biopsy-confirmed nonmetastatic prostate cancer, enrolled from 2001 to 2018 in the national US Veterans Health Administration (VA), was divided by the year of diagnosis into the development (2001-2006 and 2008-2018) and validation (2007) sets.
Mortality (all cause, non-PCM, and PCM) was evaluated. Accuracy was assessed using calibration curves and C statistic in the development, validation, and combined sets; overall; and by age (<65 and 65+ yr), race (White and Black), Hispanic ethnicity, and treatment groups.
Among 107 370 individuals, we observed 24 977 deaths (86% non-PCM). The median age was 65 yr, 4947 were Black, and 5010 were Hispanic. Compared with CCI and age alone (C statistic 0.67, 95% confidence interval [CI] 0.67-0.68), VACS-CCI demonstrated improved validated discrimination (C statistic 0.75, 95% CI 0.74-0.75 for non-PCM). The prostate cancer mortality tool also discriminated well in validation (C statistic 0.81, 95% CI 0.78-0.83). Both were well calibrated overall and within subgroups. Owing to missing data, 18 009/125 379 (14%) were excluded, and VACS-CCI should be validated outside the VA prior to outside application.
VACS-CCI is ready for implementation within the VA. Electronic health record-assisted calculation is feasible, improves accuracy over age and CCI alone, and could mitigate inaccuracy and bias in provider estimation.
Veterans Aging Cohort Study Charlson Comorbidity Index is ready for application within the Veterans Health Administration. Electronic health record-assisted calculation is feasible, improves accuracy over age and Charlson Comorbidity Index alone, and might help mitigate inaccuracy and bias in provider estimation of the risk of non-prostate cancer mortality.
European urology oncology. 2024 Jan 02 [Epub ahead of print]
Amy C Justice, Janet P Tate, Frank Howland, J Michael Gaziano, Michael J Kelley, Benjamin McMahon, Christopher Haiman, Roxanne Wadia, Ravi Madduri, Ioana Danciu, John T Leppert, Michael S Leapman, David Thurtle, Vincent J Gnanapragasam
VA Connecticut Healthcare, West Haven, CT, USA; Pain Research, Informatics, Multimorbidities, Education (PRIME) Center, VA Connecticut Healthcare System, West Haven, CT, USA; Department of Medicine, Yale School of Medicine, New Haven, CT, USA; School of Public Health, Yale University, New Haven, CT, USA. Electronic address: ., VA Connecticut Healthcare, West Haven, CT, USA; Department of Medicine, Yale School of Medicine, New Haven, CT, USA., Wabash College Economics Department, Crawfordsville, IN, USA., VA Boston Healthcare, Boston, MA, USA., Durham VA Health Care System, Durham, NC, USA; Cancer Institute and Department of Medicine, Duke University, Durham, NC, USA., Los Alamos National Laboratory, Los Alamos, NM, USA., Center for Genetic Epidemiology, USC Keck School of Medicine, University of Southern California, Los Angeles, CA, USA., Department of Anatomic Pathology and Lab Medicine, Yale School of Medicine, New Haven, CT, USA., Data Science Learning Division, Argonne Research Library, Lemont, IL, USA., Oak Ridge National Laboratory, Oak Ridge, TN, USA; Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, USA., Department of Urology, Stanford University, Stanford, CA, USA; VA Palo Alto Health Care System, Palo Alto, CA, USA., VA Connecticut Healthcare, West Haven, CT, USA; Department of Urology, Yale School of Medicine, New Haven, CT, USA., University of Cambridge, Cambridge, UK.
PubMed http://www.ncbi.nlm.nih.gov/pubmed/38171965