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Identifying monoclonal gammopathy of undetermined significance from electronic health records

BACKGROUND: Monoclonal gammopathy of undetermined significance (MGUS) precedes multiple myeloma (MM). Use of electronic health records may facilitate large‐scale epidemiologic research to elucidate risk factors for the progression of MGUS to MM or other lymphoid malignancies. AIMS: We evaluated the...

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Autores principales: Tanenbaum, Hilary C., Birmann, Brenda M., Bertrand, Kimberly A., Teras, Lauren R., Krishnan, Amrita Y., Pourhassan, Hoda, Goldsmith, Scott, Cannavale, Kimberly, Wang, Sophia S., Chao, Chun R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10026307/
https://www.ncbi.nlm.nih.gov/pubmed/36464325
http://dx.doi.org/10.1002/cnr2.1755
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author Tanenbaum, Hilary C.
Birmann, Brenda M.
Bertrand, Kimberly A.
Teras, Lauren R.
Krishnan, Amrita Y.
Pourhassan, Hoda
Goldsmith, Scott
Cannavale, Kimberly
Wang, Sophia S.
Chao, Chun R.
author_facet Tanenbaum, Hilary C.
Birmann, Brenda M.
Bertrand, Kimberly A.
Teras, Lauren R.
Krishnan, Amrita Y.
Pourhassan, Hoda
Goldsmith, Scott
Cannavale, Kimberly
Wang, Sophia S.
Chao, Chun R.
author_sort Tanenbaum, Hilary C.
collection PubMed
description BACKGROUND: Monoclonal gammopathy of undetermined significance (MGUS) precedes multiple myeloma (MM). Use of electronic health records may facilitate large‐scale epidemiologic research to elucidate risk factors for the progression of MGUS to MM or other lymphoid malignancies. AIMS: We evaluated the accuracy of an electronic health records‐based approach for identifying clinically diagnosed MGUS cases for inclusion in studies of patient outcomes/ progression risk. METHODS AND RESULTS: Data were retrieved from Kaiser Permanente Southern California's comprehensive electronic health records, which contain documentation of all outpatient and inpatient visits, laboratory tests, diagnosis codes and a cancer registry. We ascertained potential MGUS cases diagnosed between 2008 and 2014 using the presence of an MGUS ICD‐9 diagnosis code (273.1). We initially excluded those diagnosed with MM within 6 months after MGUS diagnosis, then subsequently those with any lymphoid malignancy diagnosis from 2007 to 2014. We reviewed medical charts for 100 randomly selected potential cases for evidence of a physician diagnosis of MGUS, which served as our gold standard for case confirmation. To assess sensitivity, we also investigated the presence of the ICD‐9 code in the records of 40 randomly selected and chart review‐confirmed MGUS cases among patients with a laboratory report of elevated circulating monoclonal (M‐) protein (a key test for MGUS diagnosis) and no subsequent lymphoid malignancy (as described above). The positive predictive value (PPV) for the ICD‐9 code was 98%. All MGUS cases confirmed by chart review also had confirmatory laboratory test results. Of the confirmed cases first identified via M‐protein test results, 88% also had the ICD‐9 diagnosis code. CONCLUSION: The diagnosis code‐based approach has excellent PPV and likely high sensitivity for detecting clinically diagnosed MGUS. The generalizability of this approach outside an integrated healthcare system warrants further evaluation.
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spelling pubmed-100263072023-03-21 Identifying monoclonal gammopathy of undetermined significance from electronic health records Tanenbaum, Hilary C. Birmann, Brenda M. Bertrand, Kimberly A. Teras, Lauren R. Krishnan, Amrita Y. Pourhassan, Hoda Goldsmith, Scott Cannavale, Kimberly Wang, Sophia S. Chao, Chun R. Cancer Rep (Hoboken) Original Articles BACKGROUND: Monoclonal gammopathy of undetermined significance (MGUS) precedes multiple myeloma (MM). Use of electronic health records may facilitate large‐scale epidemiologic research to elucidate risk factors for the progression of MGUS to MM or other lymphoid malignancies. AIMS: We evaluated the accuracy of an electronic health records‐based approach for identifying clinically diagnosed MGUS cases for inclusion in studies of patient outcomes/ progression risk. METHODS AND RESULTS: Data were retrieved from Kaiser Permanente Southern California's comprehensive electronic health records, which contain documentation of all outpatient and inpatient visits, laboratory tests, diagnosis codes and a cancer registry. We ascertained potential MGUS cases diagnosed between 2008 and 2014 using the presence of an MGUS ICD‐9 diagnosis code (273.1). We initially excluded those diagnosed with MM within 6 months after MGUS diagnosis, then subsequently those with any lymphoid malignancy diagnosis from 2007 to 2014. We reviewed medical charts for 100 randomly selected potential cases for evidence of a physician diagnosis of MGUS, which served as our gold standard for case confirmation. To assess sensitivity, we also investigated the presence of the ICD‐9 code in the records of 40 randomly selected and chart review‐confirmed MGUS cases among patients with a laboratory report of elevated circulating monoclonal (M‐) protein (a key test for MGUS diagnosis) and no subsequent lymphoid malignancy (as described above). The positive predictive value (PPV) for the ICD‐9 code was 98%. All MGUS cases confirmed by chart review also had confirmatory laboratory test results. Of the confirmed cases first identified via M‐protein test results, 88% also had the ICD‐9 diagnosis code. CONCLUSION: The diagnosis code‐based approach has excellent PPV and likely high sensitivity for detecting clinically diagnosed MGUS. The generalizability of this approach outside an integrated healthcare system warrants further evaluation. John Wiley and Sons Inc. 2022-12-04 /pmc/articles/PMC10026307/ /pubmed/36464325 http://dx.doi.org/10.1002/cnr2.1755 Text en © 2022 The Authors. Cancer Reports published by Wiley Periodicals LLC. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Tanenbaum, Hilary C.
Birmann, Brenda M.
Bertrand, Kimberly A.
Teras, Lauren R.
Krishnan, Amrita Y.
Pourhassan, Hoda
Goldsmith, Scott
Cannavale, Kimberly
Wang, Sophia S.
Chao, Chun R.
Identifying monoclonal gammopathy of undetermined significance from electronic health records
title Identifying monoclonal gammopathy of undetermined significance from electronic health records
title_full Identifying monoclonal gammopathy of undetermined significance from electronic health records
title_fullStr Identifying monoclonal gammopathy of undetermined significance from electronic health records
title_full_unstemmed Identifying monoclonal gammopathy of undetermined significance from electronic health records
title_short Identifying monoclonal gammopathy of undetermined significance from electronic health records
title_sort identifying monoclonal gammopathy of undetermined significance from electronic health records
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10026307/
https://www.ncbi.nlm.nih.gov/pubmed/36464325
http://dx.doi.org/10.1002/cnr2.1755
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