Anne Fia Grann

Aarhus University Hospital, Århus, Central Jutland, Denmark

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Publications (4)5.08 Total impact

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    ABSTRACT: Background:Comorbid conditions may play an important role in the prognosis of melanoma patients but have received little attention.Methods:Using data from Danish registries, we identified patients diagnosed with melanoma from 1987 to 2009. We estimated the prevalence of comorbidity and calculated mortality rate ratios and interaction risks between melanoma and comorbidity. For every melanoma patient, 10 individuals were selected for comparison. Individuals in the comparison cohort were matched to their corresponding melanoma patients on age, gender, and exact prevalent comorbidities.Results:We included 23 476 patients, 81% of whom had no comorbidity. Higher prevalence of comorbidity was associated with more advanced cancer stage. The standardised mortality rate increased with increasing level of comorbidity in both cohorts and was consistently higher among melanoma patients. Melanoma and comorbidity interacted to increase the mortality rate. The highest proportional excess was seen in melanoma patients with comorbidity score 3, in whom interaction accounted for 77 deaths per 1000 person-years (40% of the total rate). We stratified by cancer stage and found that the interaction was markedly concentrated in patients with distant metastases.Conclusion:Interaction between melanoma and comorbidity was primarily concentrated in patients with distant metastases, which raises the possibility that comorbidity is associated with delay of melanoma diagnosis, advanced cancer stage, and less aggressive melanoma treatment.British Journal of Cancer advance online publication, 16 May 2013; doi:10.1038/bjc.2013.246 www.bjcancer.com.
    British Journal of Cancer 05/2013; · 5.08 Impact Factor
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    ABSTRACT: The purpose of this study was to investigate the completeness of TNM (Tumor, Node, Metastasis) staging of melanoma in the Danish Cancer Registry (DCR). We identified 8762 patients with a first primary diagnosis of melanoma from the DCR between 2004 and 2009. We obtained information on level of comorbidity, defined according to the Charlson Comorbidity Index, through the Danish National Patient Register. We computed the completeness of TNM staging overall and by each stage component. Analyses were stratified by gender, age, year of diagnosis, and level of comorbidity. We designed an algorithm that categorized melanoma stage as localized, regional, distant, or unknown. Owing to knowledge on clinical coding practice, we allowed for categorization of tumors with certain missing stage components. The overall completeness of the TNM staging was 78.4% (95% confidence interval [CI] 77.5-79.3). Completeness varied little by gender and year of diagnosis. However, completeness decreased from 83.5% (95% CI 81.7-85.3) in patients aged 0-39 years to 68.7% (95% CI 65.7-71.6%) in patients 80 years or older, and from 80.3% (95% CI 79.4-81.3) among patients with a low level of comorbidity to 67.4% (95% CI 63.1-71.4) among patients with a high level of comorbidity. Using the algorithm, 87.3% of cases could be assigned to one of the defined stage categories. The overall completeness of the TNM registration for melanoma was fairly high but varied with age and level of comorbidity. Thus, data on TNM stage should be used with caution in epidemiological and other research.
    Clinical Epidemiology 01/2012; 4:5-10.
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    ABSTRACT: This paper provides an introduction to the clinical laboratory information system (LABKA) research database in Northern and Central Denmark. The database contains millions of stored laboratory test results for patients living in the two Danish regions, encompassing 1.8 million residents, or one-third of the country's population. More than 1700 different types of blood test analyses are available. Therefore, the LABKA research database represents an incredible source for studies involving blood test analyses. By record linkage of different Danish registries with the LABKA research database, it is possible to examine a large number of biomarkers as predictors of disease risk and prognosis and as markers of disease severity, and to evaluate medical treatments regarding effectiveness and possible side effects. Large epidemiological studies using routinely stored blood test results for individual patients can be performed because it is possible to link the laboratory data to high-quality individual clinical patient data in Denmark.
    Clinical Epidemiology 01/2011; 3:133-8.
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    ABSTRACT: To examine time trends of survival and mortality of ovarian cancer in the central and northern Denmark regions during the period 1998-2009. We conducted a cohort study including women recorded with a first-time diagnosis of ovarian cancer in the Danish National Registry of Patients (DNRP) between 1998 and 2009. Patients were followed for survival through the Danish Civil Registration System. We determined survival stratified by age, and used Cox proportional hazard regression analyses to obtain mortality rate ratios (MRRs) to assess changes over time. We found no improvement in overall ovarian cancer survival between 1998 and 2009. One-year survival was 71% in 1998-2000 and 68% in 2007-2009. Three-year survival declined from 48% in 1998-2000 to 46% in 2007-2009 (predicted), and 5-year survival declined from 40% in 1998-2000 to 37% in 2007-2009 (predicted). Compared with the period 1998-2000, the age-adjusted 1-year MRR was 1.05 (95% confidence interval CI: 0.86-1.28) for the period 2007-2009, and the predicted age-adjusted 3- and 5-year MRRs were 0.96 (95% CI: 0.83-1.12) and 0.99 (95% CI: 0.86-1.14), respectively. Results are not adjusted for tumor stage as this information was not available. We also observed a decline in the annual number of incident ovarian cancer patients during the study period, most pronounced in the youngest age group. The survival of ovarian cancer patients did not improve during the study period. This lack of improvement contrasts with the national cancer strategies implemented during this last decade, focusing on improving the survival of ovarian cancer patients.
    Clinical Epidemiology 01/2011; 3 Suppl 1:59-64.