Cancer Reports (Mar 2023)

Identifying monoclonal gammopathy of undetermined significance from electronic health records

  • Hilary C. Tanenbaum,
  • Brenda M. Birmann,
  • Kimberly A. Bertrand,
  • Lauren R. Teras,
  • Amrita Y. Krishnan,
  • Hoda Pourhassan,
  • Scott Goldsmith,
  • Kimberly Cannavale,
  • Sophia S. Wang,
  • Chun R. Chao

DOI
https://doi.org/10.1002/cnr2.1755
Journal volume & issue
Vol. 6, no. 3
pp. n/a – n/a

Abstract

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Abstract 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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