Search

Kasper Bruun Kristensen,1 Lars Christian Lund,1 Peter Bjødstrup Jensen,1 Anne Broe,1 Emelie Rotbain,2 Per Damkier,1,3,4 Anton Pottegård,1 Jacob Harbo Andersen,1 Mikkel Højlund,1,5 Morten Olesen,1 Lotte Rasmussen,1 Morten Rix Hansen,1,3,4 Martin Thomsen Ernst,1 Rikke Wesselhoeft,1,6 Daniel Pilsgaard Henriksen,3 Mette Reilev,1 Mette Bliddal,1,7 Jesper Hallas1 1Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, Odense, Denmark; 2Department of Hematology, Odense University Hospital, Odense, Denmark; 3Department of Clinical Pharmacology, Odense University Hospital, Odense, Denmark; 4Department of Clinical Research, University of Southern Denmark, Odense, Denmark; 5Department of Psychiatry Aabenraa, Mental Health Services in the Region of Southern Denmark, Aabenraa, Denmark; 6Child and Adolescent Psychiatry Odense, Mental Health Services in the Region of Southern Denmark, Odense, Denmark; 7Research Unit OPEN, Department of Clinical Research, University of Southern Denmark, Odense, DenmarkCorrespondence: Jesper Hallas, Clinical Pharmacology, Pharmacy and Environmental Medicine, Department of Public Health, University of Southern Denmark, J.B. Winsløws Vej 19, 2, Odense, 5000, Denmark, Tel +4565503010, Email jhallas@health.sdu.dkPurpose: To develop the Nordic Multimorbidity Index (NMI), a multimorbidity measure specifically suited to the Nordic health and administrative registry data based on current diagnosis, treatment, and coding practices.Methods: The NMI was developed to predict 5-year mortality in a population-based cohort of randomly sampled Danish residents aged ≥ 40 years (n = 425,087) followed from 2013 to 2018. Included predictors were selected from hospital diagnoses and filled drug prescriptions based on a combination of subject matter knowledge and a data-driven approach using backwards elimination. The performance of the NMI was assessed in a temporal validation cohort of Danish residents followed from 2007 to 2012 and in six cohorts of new users of selected drugs. The discriminative performance of the NMI, Charlson Comorbidity Index (CCI) and the Elixhauser Comorbidity Index (ECI) was assessed using the c-statistic from logistic regression models with 5-year mortality as dependent variable and the multimorbidity index score, age, and sex as independent variables.Results: The NMI included 50 predictors. In the temporal validation cohort, the c-statistic of the NMI (0.887, 95% CI 0.883– 0.890) exceeded that of the CCI (0.871, 95% CI 0.868– 0.874) and ECI (0.866, 95% CI 0.863– 0.870). In all new user cohorts, the NMI outperformed the other indices with c-statistics ranging from 0.781 (95% CI 0.779– 0.784) to 0.838 (95% CI 0.834– 0.842).Conclusion: The NMI predicted 5-year mortality in a general Danish population and six cohorts of new users of selected drugs and was superior to the CCI and ECI. The NMI could be preferred over these indices to quantify the level of multimorbidity for, eg, descriptive purposes or confounding control. The NMI should be validated in other patient populations and other Nordic countries.Keywords: multimorbidity, comorbidity, pharmacoepidemiology, prognosis, risk score

Emelie C Rotbain,1– 5 Klaus Rostgaard,3,5 Michael A Andersen,2,3 Caspar Da Cunha-Bang,2 Carsten U Niemann,2 Henrik Frederiksen,1,4,6 Henrik Hjalgrim2,3,5,7 1Department of Hematology, Odense University Hospital, Odense, Denmark; 2Department of Hematology, Rigshospitalet, Denmark; 3Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark; 4Department of Clinical Research, University of Southern Denmark, Odense, Denmark; 5Danish Cancer Society Research Center, Hematology Research Group, Copenhagen, Denmark; 6Academy of Geriatric Cancer Research (AGECARE), Odense University Hospital, Odense, Denmark; 7Department of Clinical Medicine, Copenhagen University, Copenhagen, DenmarkCorrespondence: Emelie C RotbainDepartment of Hematology, Odense University Hospital, Kløvervænget 6, Odense, DK-5000, DenmarkTel +45 5369 0201Email erot0006@regionh.dkPurpose: Age-related comorbidity is highly prevalent in chronic lymphocytic leukemia (CLL). The purpose of this study was to provide information on current patterns of healthcare utilization in CLL.Patients and Methods: We used data from Danish nation-wide registers to study healthcare utilization the year before and the year after CLL diagnosis and in relation to first-line treatment. Patients diagnosed with CLL between 1997 and 2018 were included and stratified on number of comorbidities, presence of specific comorbidities, and fitness status, respectively. Healthcare utilization was studied in terms of hospital admissions, in-hospital bed days, out-patient visits, emergency room visits, and prescription drugs. Odds ratios with 95% confidence intervals were calculated using multivariable logistic regression analyses adjusting for age, sex, and calendar year.Results: The study comprised 9170 patients with CLL with a median age of 71 years, of whom 35% had ≥ 1 comorbidity. Healthcare utilization increased markedly upon CLL diagnosis both in patients with and without comorbidities. During the year after CLL diagnosis, 39% were hospitalized, 16% visited an emergency room, 88% visited an out-patient clinic, and 93% received prescription drugs. Both individual comorbidities and the total number of comorbidities were associated with increased healthcare utilization of all types, except for contacts to hematological departments.Conclusion: Our results suggest that CLL diagnosis may unveil incipient diseases and aggravate comorbidities and thereby have considerably wider health implications than those directly related to CLL. These findings may be used by clinicians and decisions makers to guide planning of multidisciplinary care for cancer patients.Keywords: chronic lymphocytic leukemia, hematology, epidemiology, real-world data

Purpose: Our aim was to assess the validity of the ICD-10 code for splenomegaly in the Danish National Registry of Patients (DNRP), as well as to investigate which underlying diseases explained the observed splenomegaly., Background: Splenomegaly is a common finding in patients referred to an internal medical department and can be caused by a large spectrum of diseases, including haematological diseases and liver cirrhosis. However, some patients remain without a causal diagnosis, despite extensive medical work-up., Patients and Methods: We identified 129 patients through the DNRP, that had been given the ICD-10 splenomegaly diagnosis code in 1994-2013 at Odense University Hospital, Denmark, excluding patients with prior splenomegaly, malignant haematological neoplasia or liver cirrhosis. Medical records were reviewed for validity of the splenomegaly diagnosis, diagnostic work-up, and the underlying disease was determined. The positive predictive value (PPV) with 95% confidence interval (CI) was calculated for the splenomegaly diagnosis code. Patients with idiopathic splenomegaly in on-going follow-up were also invited to be investigated for Gaucher disease., Results: The overall PPV was 92% (95% CI: 85, 96). Haematological diseases were the underlying causal diagnosis in 39%; hepatic diseases in 18%, infectious disease in 10% and other diseases in 8%. 25% of patients with splenomegaly remained without a causal diagnosis. Lymphoma was the most common haematological causal diagnosis and liver cirrhosis the most common hepatic causal diagnosis. None of the investigated patients with idiopathic splenomegaly had Gaucher disease., Conclusion: Our findings show that the splenomegaly diagnosis in the DNRP is valid and can be used in registry-based studies. However, because of suspected significant under-coding, it should be considered if supplementary data sources should be used in addition, in order to attain a more representative population. Haematological diseases were the most common cause, however in a large fraction of patients no causal diagnosis was found.