Purpose: The distinction of patients with symptomatic multiple myeloma (MM) from those with smoldering MM poses a challenge for researchers who use administrative databases. Historically, researchers either have included all patients or used treatment receipt as the distinguishing factor; both methods have drawbacks. We present an algorithm for distinguishing between symptomatic and smoldering MM using ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) codes for the classic defining events of symptomatic MM commonly referred to as the CRAB criteria (hypercalcemia, renal impairment, anemia, and bone lesions). Patients and Methods: SEER-Medicare-linked data from 4,187 patients with MM diagnosed between 2007 and 2011 were used for this analysis. Results: Eighty-four percent had ICD-9-CM codes consistent with CRAB criteria, whereas only 57% received treatment. Overall survival of patients with symptomatic MM defined as receipt of treatment was 32.3 months versus 26.6 months for the overall population and 22.9 months for patients with symptomatic MM defined by CRAB criteria. Conceptually, removal of patients with smoldering MM should result in a reduction in overall survival; however, the cohort of patients who received treatment tended to be younger and healthier than the overall population, which could have skewed the results. Conclusion: The algorithm we present resulted in a larger and more representative sample than classification by treatment status and reduced potential bias that could result from including all patients with smoldering MM in the analysis. Although this study was performed using the SEER-Medicare database, the methodology was broad enough that the algorithm could be extended to additional claims-based data sets with relative ease.
Purpose: The distinction of patients with symptomatic multiple myeloma (MM) from those with smoldering MM poses a challenge for researchers who use administrative databases. Historically, researchers either have included all patients or used treatment receipt as the distinguishing factor; both methods have drawbacks. We present an algorithm for distinguishing between symptomatic and smoldering MM using ICD-9-CM (International Classification of Diseases, Ninth Revision, Clinical Modification) codes for the classic defining events of symptomatic MM commonly referred to as the CRAB criteria (hypercalcemia, renal impairment, anemia, and bone lesions). Patients and Methods: SEER-Medicare-linked data from 4,187 patients with MM diagnosed between 2007 and 2011 were used for this analysis. Results: Eighty-four percent had ICD-9-CM codes consistent with CRAB criteria, whereas only 57% received treatment. Overall survival of patients with symptomatic MM defined as receipt of treatment was 32.3 months versus 26.6 months for the overall population and 22.9 months for patients with symptomatic MM defined by CRAB criteria. Conceptually, removal of patients with smoldering MM should result in a reduction in overall survival; however, the cohort of patients who received treatment tended to be younger and healthier than the overall population, which could have skewed the results. Conclusion: The algorithm we present resulted in a larger and more representative sample than classification by treatment status and reduced potential bias that could result from including all patients with smoldering MM in the analysis. Although this study was performed using the SEER-Medicare database, the methodology was broad enough that the algorithm could be extended to additional claims-based data sets with relative ease.
Authors: S Vincent Rajkumar; Meletios A Dimopoulos; Antonio Palumbo; Joan Blade; Giampaolo Merlini; María-Victoria Mateos; Shaji Kumar; Jens Hillengass; Efstathios Kastritis; Paul Richardson; Ola Landgren; Bruno Paiva; Angela Dispenzieri; Brendan Weiss; Xavier LeLeu; Sonja Zweegman; Sagar Lonial; Laura Rosinol; Elena Zamagni; Sundar Jagannath; Orhan Sezer; Sigurdur Y Kristinsson; Jo Caers; Saad Z Usmani; Juan José Lahuerta; Hans Erik Johnsen; Meral Beksac; Michele Cavo; Hartmut Goldschmidt; Evangelos Terpos; Robert A Kyle; Kenneth C Anderson; Brian G M Durie; Jesus F San Miguel Journal: Lancet Oncol Date: 2014-10-26 Impact factor: 41.316
Authors: Robert A Kyle; Ellen D Remstein; Terry M Therneau; Angela Dispenzieri; Paul J Kurtin; Janice M Hodnefield; Dirk R Larson; Matthew F Plevak; Diane F Jelinek; Rafael Fonseca; Lee Joseph Melton; S Vincent Rajkumar Journal: N Engl J Med Date: 2007-06-21 Impact factor: 91.245
Authors: Eberechukwu Onukwugha; Candice Yong; Arif Hussain; Brian Seal; C Daniel Mullins Journal: BMC Med Res Methodol Date: 2014-01-02 Impact factor: 4.615
Authors: A Ravindran; A C Bartley; S J Holton; W I Gonsalves; P Kapoor; M A Siddiqui; S K Hashmi; A L Marshall; A A Ashrani; A Dispenzieri; R A Kyle; S V Rajkumar; R S Go Journal: Blood Cancer J Date: 2016-10-21 Impact factor: 11.037