Journal article
Development of a claims-based algorithm to identify colorectal cancer recurrence
Annals of epidemiology, Vol.25(4), pp.297-300
04/2015
DOI: 10.1016/j.annepidem.2015.01.005
PMCID: PMC4369323
PMID: 25794767
Abstract
To examine the validity of claims data to identify colorectal cancer (CRC) recurrence and determine the extent to which misclassification of recurrence status affects estimates of its association with overall survival in a population-based administrative database.
We calculated the accuracy of claims data relative to medical records from one large tertiary hospital to identify CRC recurrence. We estimated the effect of misclassifying recurrence on survival by applying these findings to the linked Surveillance, Epidemiology, and End Results–Medicare data.
Of 174 eligible CRC patients identified through medical records, 32 (18.4%) had a recurrence. A claims-based algorithm of secondary malignancy codes yielded a sensitivity of 81% and specificity of 99% for identifying recurrence. Agreement between data sources was almost perfect (kappa: 0.86). In a model unadjusted for misclassification, CRC patients with recurrence were 3.04 times (95% confidence interval: 2.92–3.17) more likely to die of any cause than those without recurrence. In the corrected model, CRC patients with recurrence were 3.47 times (95% confidence interval: 3.06–4.14) more likely to die than those without recurrence.
Identifying recurrence in CRC patients using claims data is feasible with moderate sensitivity and high specificity. Future studies can use this algorithm with Surveillance, Epidemiology, and End Results–Medicare data to study treatment patterns and outcomes of CRC patients with recurrence.
•We examined the validity of a claims-based algorithm to identify CRC recurrence.•We determined the extent to which recurrence misclassification affects survival.•Secondary malignancy codes yielded moderate sensitivity and high specificity.•Identifying recurrence in CRC patients using claims data is feasible.•Addressing misclassification is important when using claims-based algorithms.
Details
- Title: Subtitle
- Development of a claims-based algorithm to identify colorectal cancer recurrence
- Creators
- Anjali D Deshpande - Division of General Medical Sciences, Department of Medicine, School of Medicine, Washington University in St. Louis, St. Louis, MOMario Schootman - Department of Epidemiology, College for Public Health and Social Justice, Saint Louis University, St. Louis, MOAllese Mayer - Department of Epidemiology, College for Public Health and Social Justice, Saint Louis University, St. Louis, MO
- Resource Type
- Journal article
- Publication Details
- Annals of epidemiology, Vol.25(4), pp.297-300
- DOI
- 10.1016/j.annepidem.2015.01.005
- PMID
- 25794767
- PMCID
- PMC4369323
- NLM abbreviation
- Ann Epidemiol
- ISSN
- 1047-2797
- eISSN
- 1873-2585
- Publisher
- Elsevier Inc
- Grant note
- CA91842; CA137750 / National Cancer Institute (http://dx.doi.org/10.13039/100000054)
- Language
- English
- Date published
- 04/2015
- Academic Unit
- Epidemiology
- Record Identifier
- 9983996086202771
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