Validity of an Automated Algorithm to Identify Cirrhosis Using Electronic Health Records in Patients with Primary Biliary Cholangitis

被引:5
|
作者
Lu, Mei [1 ]
Bowlus, Christopher L. [2 ]
Lindor, Keith [3 ]
Rodriguez-Watson, Carla, V [4 ,5 ]
Romanelli, Robert J. [6 ]
Haller, Irina, V [7 ]
Anderson, Heather [8 ]
VanWormer, Jeffrey J. [9 ]
Boscarino, Joseph A. [10 ]
Schmidt, Mark A. [11 ]
Daida, Yihe G. [12 ]
Sahota, Amandeep [13 ]
Vincent, Jennifer [14 ]
Li, Jia [1 ]
Trudeau, Sheri [1 ]
Rupp, Loralee B. [15 ]
Gordon, Stuart C. [16 ,17 ]
机构
[1] Henry Ford Hlth Syst, Dept Publ Hlth Sci, 3E One Ford Pl, Detroit, MI 48202 USA
[2] Univ Calif Davis, Sch Med, Sacramento, CA 95817 USA
[3] Arizona State Univ, Coll Hlth Solut, Phoenix, AZ USA
[4] Kaiser Permanente Midatlantic Res Inst, Ctr Hlth Res, Rockville, MD USA
[5] Reagan Udall Fdn FDA, Washington, DC USA
[6] Palo Alto Med Fdn, Res Inst, Palo Alto, CA 94301 USA
[7] Essentia Hlth, Essentia Inst Rural Hlth, Duluth, MN USA
[8] Univ Colorado, Skaggs Sch Pharm & Pharmaceut Sci, Anschutz Med Campus, Aurora, CO USA
[9] Marshfield Clin Res Fdn, Marshfield, WI USA
[10] Geisinger Med Clin, Dept Populat Hlth Sci, Danville, PA USA
[11] Kaiser Permanente Northwest, Ctr Hlth Res, Portland, OR USA
[12] Kaiser Permanente Hawaii, Ctr Integrated Hlth Care Res, Honolulu, HI USA
[13] Kaiser Permanente Southern Calif, Dept Res & Evaluat, Los Angeles, CA USA
[14] Baylor Scott & White Res Inst, Temple, TX USA
[15] Henry Ford Hlth Syst, Ctr Hlth Policy & Hlth Serv Res, Detroit, MI USA
[16] Henry Ford Hlth Syst, Div Gastroenterol & Hepatol, Detroit, MI 48202 USA
[17] Wayne State Univ, Sch Med, Detroit, MI USA
来源
CLINICAL EPIDEMIOLOGY | 2020年 / 12卷
关键词
primary biliary cirrhosis; cholangitis; race/gender/ethnicity; gender; ethnicity; decompensated cirrhosis; ursodeoxycholic acid; UCDA;
D O I
10.2147/CLEP.S262558
中图分类号
R1 [预防医学、卫生学];
学科分类号
1004 ; 120402 ;
摘要
Background: Biopsy remains the gold standard for determining fibrosis stage in patients with primary biliary cholangitis (PBC), but it is unavailable for most patients. We used data from the 11 US health systems in the FibrOtic Liver Disease Consortium to explore a combination of biochemical markers and electronic health record (EHR)-based diagnosis/procedure codes (DPCs) to identify the presence of cirrhosis in PBC patients. Methods: Histological fibrosis staging data were obtained from liver biopsies. Variables considered for the model included demographics (age, gender, race, ethnicity), total bilirubin, alkaline phosphatase, albumin, aspartate aminotransferase (AST) to platelet ratio index (APRI), Fibrosis 4 (FIB4) index, AST to alanine aminotransferase (ALT) ratio, and >100 DPCs associated with cirrhosis/decompensated cirrhosis, categorized into ten clusters. Using least absolute shrinkage and selection operator regression (LASSO), we derived and validated cutoffs for identifying cirrhosis. Results: Among 4328 PBC patients, 1350 (32%) had biopsy data; 121 (9%) were staged F4 (cirrhosis). DPC clusters (including codes related to cirrhosis and hepatocellular carcinoma diagnoses/procedures), Hispanic ethnicity, ALP, AST/ALT ratio, and total bilirubin were retained in the final model (AUROC=0.86 and 0.83 on learning and testing data, respectively); this model with two cutoffs divided patients into three categories (no cirrhosis, indeterminate, and cirrhosis) with specificities of 81.8% (for no cirrhosis) and 80.3% (for cirrhosis). A model excluding DPCs retained ALP, AST/ALT ratio, total bilirubin, Hispanic ethnicity, and gender (AUROC=0.81 and 0.78 on learning and testing data, respectively). Conclusion: An algorithm using laboratory results and DPCs can categorize a majority of PBC patients as cirrhotic or noncirrhotic with high accuracy (with a small remaining group of patients' cirrhosis status indeterminate). In the absence of biopsy data, this EHR-based model can be used to identify cirrhosis in cohorts of PBC patients for research and/or clinical follow-up.
引用
收藏
页码:1261 / 1267
页数:7
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