Dataset Information

Development of an Algorithm to Distinguish Smoldering Versus Symptomatic Multiple Myeloma in Claims-Based Data Sets.

ABSTRACT: 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.

SUBMITTER: Fiala MA

PROVIDER: S-EPMC6289182 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Development of an Algorithm to Distinguish Smoldering Versus Symptomatic Multiple Myeloma in Claims-Based Data Sets.

Fiala Mark A MA Dukeman James J Tuchman Sascha A SA Keller Matt M Vij Ravi R Wildes Tanya M TM

JCO clinical cancer informatics 20171221

<h4>Purpose</h4>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 Modificati ...[more]

PMID: 30547156

Similar Datasets

Project description:PurposeWhether patients with smoldering multiple myeloma (SMM) needed to receive early interventional treatment remains controversial. Herein, we conducted a meta-analysis comparing the efficacy and safety of early treatment over deferred treatment for patients with SMM.MethodsMEDLINE and Cochrane Library were searched to May 2014 for randomized controlled trials (RCTs) that assessed the effect of early treatment over deferred treatment. Primary outcome measure was mortality, and secondary outcome measures were progression, response rate, and adverse events.ResultsOverall, 5 trials including 449 patients were identified. There was a markedly reduced risk of disease progression with early treatment (Odds Ratio [OR] = 0.13, 95% confidence interval [CI] = 0.07 to 0.24). There were no significant differences in mortality and response rate (OR = 0.85, 95% CI = 0.45 to 1.60, and OR = 0.63, 95% CI = 0.32 to 1.23, respectively). More patients in the early treatment arm experienced gastrointestinal toxicities (OR = 10.02, 95%CI = 4.32 to 23.23), constipation (OR = 8.58, 95%CI = 3.20 to 23.00) and fatigue or asthenia (OR = 2.72, 95%CI = 1.30 to 5.67). No significant differences were seen with the development of acute leukemia (OR = 2.80, 95%CI = 0.42 to 18.81), hematologic cancer (OR = 2.07, 95%CI = 0.43 to 10.01), second primary tumors (OR = 3.45, 95%CI = 0.81 to 14.68), nor vertebral compression (OR = 0.18, 95%CI = 0.02 to 1.59).ConclusionsEarly treatment delayed disease progression but increased the risk of gastrointestinal toxicities, constipation and fatigue or asthenia. The differences on vertebral compression, acute leukemia, hematological cancer and second primary tumors were not statistically significant. Based on the current evidence, early treatment didn't significantly affect mortality and response rate. However, further much larger trials were needed to provide more evidence.

Dataset Information

Development of an Algorithm to Distinguish Smoldering Versus Symptomatic Multiple Myeloma in Claims-Based Data Sets.

Publications

Development of an Algorithm to Distinguish Smoldering Versus Symptomatic Multiple Myeloma in Claims-Based Data Sets.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets