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Improving Cervical Precancer Surveillance: Validity of Claims-Based Prediction Models in ICD-9 and ICD-10 Eras

BACKGROUND: Human papillomavirus vaccine (HPV) impact on cervical precancer (cervical intraepithelial neoplasia grades 2+ [CIN2+]) is observable sooner than impact on cancer. Biopsy-confirmed CIN2+ is not included in most US cancer registries. Billing codes could provide surrogate metrics; however,...

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Autores principales: Shing, Jaimie Z, Griffin, Marie R, Nguyen, Linh D, Slaughter, James C, Mitchel, Edward F, Pemmaraju, Manideepthi, Rentuza, Alyssa B, Hull, Pamela C
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7853170/
https://www.ncbi.nlm.nih.gov/pubmed/33554035
http://dx.doi.org/10.1093/jncics/pkaa112
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author Shing, Jaimie Z
Griffin, Marie R
Nguyen, Linh D
Slaughter, James C
Mitchel, Edward F
Pemmaraju, Manideepthi
Rentuza, Alyssa B
Hull, Pamela C
author_facet Shing, Jaimie Z
Griffin, Marie R
Nguyen, Linh D
Slaughter, James C
Mitchel, Edward F
Pemmaraju, Manideepthi
Rentuza, Alyssa B
Hull, Pamela C
author_sort Shing, Jaimie Z
collection PubMed
description BACKGROUND: Human papillomavirus vaccine (HPV) impact on cervical precancer (cervical intraepithelial neoplasia grades 2+ [CIN2+]) is observable sooner than impact on cancer. Biopsy-confirmed CIN2+ is not included in most US cancer registries. Billing codes could provide surrogate metrics; however, the International Classification of Diseases, ninth (ICD-9) to tenth (ICD-10) transition disrupts trends. We built, validated, and compared claims-based models to identify CIN2+ events in both ICD eras. METHODS: A database of Davidson County (Nashville), Tennessee, pathology-confirmed CIN2+ from the HPV Vaccine Impact Monitoring Project (HPV-IMPACT) provided gold standard events. Using Tennessee Medicaid 2008-2017, cervical diagnostic procedures (N = 8549) among Davidson County women aged 18-39 years were randomly split into 60% training and 40% testing sets. Relevant diagnosis, procedure, and screening codes were used to build models from CIN2+ tissue diagnosis codes alone, least absolute shrinkage and selection operator (LASSO), and random forest. Model-classified index events were counted to estimate incident events. RESULTS: HPV-IMPACT identified 983 incident CIN2+ events. Models identified 1007 (LASSO), 1245 (CIN2+ tissue diagnosis codes alone), and 957 (random forest) incident events. LASSO performed well in ICD-9 and ICD-10 eras: 77.3% (95% confidence interval [CI] = 72.5% to 81.5%) vs 81.1% (95% CI = 71.5% to 88.6%) sensitivity, 93.0% (95% CI = 91.9% to 94.0%) vs 90.2% (95% CI = 87.2% to 92.7%) specificity, 61.3% (95% CI = 56.6% to 65.8%) vs 60.3% (95% CI = 51.0% to 69.1%) positive predictive value, 96.6% (95% CI = 95.8% to 97.3%) vs 96.3% (95% CI = 94.1% to 97.8%) negative predictive value, 91.0% (95% CI = 89.9% to 92.1%) vs 88.8% (95% CI = 85.9% to 91.2%) accuracy, and 85.1% (95% CI = 82.9% to 87.4%) vs 85.6% (95% CI = 81.4% to 89.9%) C-indices, respectively; performance did not statistically significantly differ between eras (95% confidence intervals all overlapped). CONCLUSIONS: Results confirmed model utility with good performance across both ICD eras for CIN2+ surveillance. Validated claims-based models may be used in future CIN2+ trend analyses to estimate HPV vaccine impact where population-based biopsies are unavailable.
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spelling pubmed-78531702021-02-04 Improving Cervical Precancer Surveillance: Validity of Claims-Based Prediction Models in ICD-9 and ICD-10 Eras Shing, Jaimie Z Griffin, Marie R Nguyen, Linh D Slaughter, James C Mitchel, Edward F Pemmaraju, Manideepthi Rentuza, Alyssa B Hull, Pamela C JNCI Cancer Spectr Article BACKGROUND: Human papillomavirus vaccine (HPV) impact on cervical precancer (cervical intraepithelial neoplasia grades 2+ [CIN2+]) is observable sooner than impact on cancer. Biopsy-confirmed CIN2+ is not included in most US cancer registries. Billing codes could provide surrogate metrics; however, the International Classification of Diseases, ninth (ICD-9) to tenth (ICD-10) transition disrupts trends. We built, validated, and compared claims-based models to identify CIN2+ events in both ICD eras. METHODS: A database of Davidson County (Nashville), Tennessee, pathology-confirmed CIN2+ from the HPV Vaccine Impact Monitoring Project (HPV-IMPACT) provided gold standard events. Using Tennessee Medicaid 2008-2017, cervical diagnostic procedures (N = 8549) among Davidson County women aged 18-39 years were randomly split into 60% training and 40% testing sets. Relevant diagnosis, procedure, and screening codes were used to build models from CIN2+ tissue diagnosis codes alone, least absolute shrinkage and selection operator (LASSO), and random forest. Model-classified index events were counted to estimate incident events. RESULTS: HPV-IMPACT identified 983 incident CIN2+ events. Models identified 1007 (LASSO), 1245 (CIN2+ tissue diagnosis codes alone), and 957 (random forest) incident events. LASSO performed well in ICD-9 and ICD-10 eras: 77.3% (95% confidence interval [CI] = 72.5% to 81.5%) vs 81.1% (95% CI = 71.5% to 88.6%) sensitivity, 93.0% (95% CI = 91.9% to 94.0%) vs 90.2% (95% CI = 87.2% to 92.7%) specificity, 61.3% (95% CI = 56.6% to 65.8%) vs 60.3% (95% CI = 51.0% to 69.1%) positive predictive value, 96.6% (95% CI = 95.8% to 97.3%) vs 96.3% (95% CI = 94.1% to 97.8%) negative predictive value, 91.0% (95% CI = 89.9% to 92.1%) vs 88.8% (95% CI = 85.9% to 91.2%) accuracy, and 85.1% (95% CI = 82.9% to 87.4%) vs 85.6% (95% CI = 81.4% to 89.9%) C-indices, respectively; performance did not statistically significantly differ between eras (95% confidence intervals all overlapped). CONCLUSIONS: Results confirmed model utility with good performance across both ICD eras for CIN2+ surveillance. Validated claims-based models may be used in future CIN2+ trend analyses to estimate HPV vaccine impact where population-based biopsies are unavailable. Oxford University Press 2020-12-30 /pmc/articles/PMC7853170/ /pubmed/33554035 http://dx.doi.org/10.1093/jncics/pkaa112 Text en © The Author(s) 2020. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Article
Shing, Jaimie Z
Griffin, Marie R
Nguyen, Linh D
Slaughter, James C
Mitchel, Edward F
Pemmaraju, Manideepthi
Rentuza, Alyssa B
Hull, Pamela C
Improving Cervical Precancer Surveillance: Validity of Claims-Based Prediction Models in ICD-9 and ICD-10 Eras
title Improving Cervical Precancer Surveillance: Validity of Claims-Based Prediction Models in ICD-9 and ICD-10 Eras
title_full Improving Cervical Precancer Surveillance: Validity of Claims-Based Prediction Models in ICD-9 and ICD-10 Eras
title_fullStr Improving Cervical Precancer Surveillance: Validity of Claims-Based Prediction Models in ICD-9 and ICD-10 Eras
title_full_unstemmed Improving Cervical Precancer Surveillance: Validity of Claims-Based Prediction Models in ICD-9 and ICD-10 Eras
title_short Improving Cervical Precancer Surveillance: Validity of Claims-Based Prediction Models in ICD-9 and ICD-10 Eras
title_sort improving cervical precancer surveillance: validity of claims-based prediction models in icd-9 and icd-10 eras
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7853170/
https://www.ncbi.nlm.nih.gov/pubmed/33554035
http://dx.doi.org/10.1093/jncics/pkaa112
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