Cold Agglutinin Disease (CAD)Can have SERIOUS consequences

Patients are consistently at risk for dangerous events1

CAD is associated with a significantly elevated thromboembolic threat1

In the largest retrospective claims-database study of patients with CAD (n=814) vs a matched cohort (n=7960),* there was a

55% increased risk of thromboembolic events

  • 31% experienced a TE vs 20% in the comparison cohort (P<0.0001)

Patients with CAD are at a significant increased risk vs the comparison cohort for1:

Stroke
23% vs 14%
(P<0.0001)

MI
7% vs 4%
(P=0.002)

DVT
5% vs 2%
(P=0.003)

PE
5% vs 2%
(P<0.0001)

Severe anemia may not be the only predictor of risk—markers of hemolysis may be signs of thromboembolic risk

In patients who had a TE and available laboratory results1:

had evidence of
active hemolysis
had severe anemia
(defined as hemoglobin
≤8 g/L)

Study limitations

  • Analyses were conducted using claims-based data, and the codes used may be subject to coding errors
  • The Optum database only covers commercially insured patients
  • Incidence of all TEs may be underestimated due to inability to account for multiple TEs occurring within each type
  • Identifying patients with CAD by linkage of claims data with electronic health records in the Optum database allowed for a more precise identification using clinical notes in comparison to using claims data alone, as the ICD-9 code for CAD also includes warm AIHAs

*Patients were matched 1:10 on sex, ethnicity, region, follow-up, age, and entry date.

Elevated bilirubin and LDH.


CAD is associated with increased mortality2-4

In a retrospective claims-database study of US patients with CAD (n=651) vs a matched cohort (n=3255), there was a

Significant increase in mortality seen as early as year 1 after diagnosis2

Survival probability in patients with CAD compared with matched CONTROLS WITHOUT CAD

  • This study assessed mortality in CAD and measured survival using the Kaplan-Meier method
  • Patients were retrospectively identified from Optum’s de-identified longitudinal EMR repository (Optum-Humedica) between January 2007 and September 2018 (study period)
  • The case and control cohorts were matched by age, sex, race, region, index year, and follow-up period using 1:5 nearest neighbor matching

Study limitations

  • Analyses were conducted using claims-based data, and the codes used may be subject to coding errors
  • The Optum database only covers commercially insured patients
  • Identifying patients with CAD by linkage of claims data with electronic health records in the Optum database allowed for a more precise identification using clinical notes in comparison to using claims data alone, as the ICD-9 code for CAD also includes warm AIHAs

In a population-based study comparing patients with CAD (n=72) vs a matched general population cohort (n=720), there was a

Significantly decreased survival probability in Danish patients with CAD3

Survival probability in patients with CAD compared with a matched general population cohort

  • This study assessed mortality in CAD and measured survival using the Kaplan-Meier method3
  • Patients were identified in the Danish National Patient Registry, Civil Registration System, and National Health Service Prescription Database from 1999 to 20133
  • Each patient was matched 1:10 based on age, sex, region, and adjusted based on Charlson Comorbidity Index (CCI) score, including cancer and other conditions3,4

Study limitations

  • Medical histories of patients with diagnosis codes specific for CAD and their comparisons were abstracted from the Danish National Patient Registry, and current vital status was ascertained from the Civil Registration System. Information abstracted from the medical registry, including demographic and clinical variables, was used to characterize the study cohorts
  • In patients with >1 TE coded, only the first TE was used for analysis to avoid overcounting
  • Analyses for mortality and TEs were adjusted for comorbidities using CCI score. Multivariate models were built using Cox regression analyses to remove any potential confounding effects of CCI on the relationship between CAD and risk of TEs or mortality

Sponsored by Bioverativ Therapeutics Inc., a Sanofi company.

ADDITIONAL STUDIES ARE NEEDED TO FURTHER UNDERSTAND THE RISKS ASSOCIATED WITH CAD

Icon of blood representing CAD symptom of hemolytic anemia

The complement
pathway plays a
critical role in CAD

Icon of checklist

Understand criteria
to diagnose CAD
in patients

AIHA=autoimmune hemolytic anemia; CAD=Cold Agglutinin Disease; DVT=deep vein thrombosis; ICD=International Classification of Diseases; LDH=lactate dehydrogenase; MI=myocardial infarction; PE=pulmonary embolism; TE=thromboembolic event.
References: 1. Broome CM, Cunningham JM, Mullins M, et al. Incidence of thromboembolic events is increased in a retrospective analysis of a large cold agglutinin disease (CAD) cohort. Poster presented at: 59th Annual Meeting and Exposition of the American Society of Hematology Conference (ASH); December 9-12, 2017; Atlanta, GA. Abstract 928. 2. Hill QA, Punekar R, Arian JM, Broome CM, Su J. Mortality among patients with cold agglutinin disease in the United States: an electronic health record (EHR)-based analysis. Blood. 2019;134(suppl 1):4790. doi:10.1182/blood-2019-122140 3. Bylsma LC, Gulbech Ording A, Rosenthal A, et al. Occurrence, thromboembolic risk, and mortality in Danish patients with cold agglutinin disease. Blood Adv. 2019;3(20):2980-2985. 4. Quan H, Li B, Couris CM, et al. Updating and validating the Charlson Comorbidity Index and score for risk adjustment in hospital discharge abstracts using data from 6 countries. Am J Epidemiol. 2011;173(6):676-682.