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Iterative Outlier Removal: A Method for Identifying Outliers in Laboratory Recalibration Studies.

TitleIterative Outlier Removal: A Method for Identifying Outliers in Laboratory Recalibration Studies.
Publication TypeJournal Article
Year of Publication2016
AuthorsParrinello CM, Grams ME, Sang Y, Couper DJ, Wruck LM, Li D, Eckfeldt JH, Selvin E
Secondary AuthorsCoresh JJ
JournalClin Chem
Volume62
Issue7
Pagination966-72
Date Published2016 07
ISSN1530-8561
KeywordsAtherosclerosis, Calibration, Clinical Laboratory Techniques, Data Interpretation, Statistical, Humans, Uric Acid
Abstract

BACKGROUND: Extreme values that arise for any reason, including those through nonlaboratory measurement procedure-related processes (inadequate mixing, evaporation, mislabeling), lead to outliers and inflate errors in recalibration studies. We present an approach termed iterative outlier removal (IOR) for identifying such outliers.

METHODS: We previously identified substantial laboratory drift in uric acid measurements in the Atherosclerosis Risk in Communities (ARIC) Study over time. Serum uric acid was originally measured in 1990-1992 on a Coulter DACOS instrument using an uricase-based measurement procedure. To recalibrate previous measured concentrations to a newer enzymatic colorimetric measurement procedure, uric acid was remeasured in 200 participants from stored plasma in 2011-2013 on a Beckman Olympus 480 autoanalyzer. To conduct IOR, we excluded data points >3 SDs from the mean difference. We continued this process using the resulting data until no outliers remained.

RESULTS: IOR detected more outliers and yielded greater precision in simulation. The original mean difference (SD) in uric acid was 1.25 (0.62) mg/dL. After 4 iterations, 9 outliers were excluded, and the mean difference (SD) was 1.23 (0.45) mg/dL. Conducting only one round of outlier removal (standard approach) would have excluded 4 outliers [mean difference (SD) = 1.22 (0.51) mg/dL]. Applying the recalibration (derived from Deming regression) from each approach to the original measurements, the prevalence of hyperuricemia (>7 mg/dL) was 28.5% before IOR and 8.5% after IOR.

CONCLUSIONS: IOR is a useful method for removal of extreme outliers irrelevant to recalibrating laboratory measurements, and identifies more extraneous outliers than the standard approach.

DOI10.1373/clinchem.2016.255216
Alternate JournalClin Chem
PubMed ID27197675
PubMed Central IDPMC4927349
Grant ListHHSN268201100012C / HL / NHLBI NIH HHS / United States
HHSN268201100009I / HL / NHLBI NIH HHS / United States
U01 HL096812 / HL / NHLBI NIH HHS / United States
HHSN268201100010C / HL / NHLBI NIH HHS / United States
HHSN268201100008C / HL / NHLBI NIH HHS / United States
HHSN268201100005G / HL / NHLBI NIH HHS / United States
U01 HL096917 / HL / NHLBI NIH HHS / United States
HHSN268201100008I / HL / NHLBI NIH HHS / United States
R01 DK089174 / DK / NIDDK NIH HHS / United States
HHSN268201100007C / HL / NHLBI NIH HHS / United States
HHSN268201100011I / HL / NHLBI NIH HHS / United States
HHSN268201100011C / HL / NHLBI NIH HHS / United States
U01 HL096902 / HL / NHLBI NIH HHS / United States
T32 HL007024 / HL / NHLBI NIH HHS / United States
HHSN268201100006C / HL / NHLBI NIH HHS / United States
HHSN268201100005I / HL / NHLBI NIH HHS / United States
K24 DK106414 / DK / NIDDK NIH HHS / United States
U01 HL096814 / HL / NHLBI NIH HHS / United States
HHSN268201100009C / HL / NHLBI NIH HHS / United States
HHSN268201100005C / HL / NHLBI NIH HHS / United States
U01 HL096899 / HL / NHLBI NIH HHS / United States
HHSN268201100007I / HL / NHLBI NIH HHS / United States
K08 DK092287 / DK / NIDDK NIH HHS / United States