Differences in risk profile associated with varicose veins and chronic venous insufficiency - results from the Bonn Vein Study 1.

Background: The aim of this publication is to demonstrate similarities and differences in the association of risk factors with the prevalence of different manifestations of chronic venous disease (CVD), like varicose veins (VV), venous oedema (C3) and severe chronic venous insufficiency (CVI) in the population-based cross-sectional Bonn Vein Study 1 (BVS). Patients and methods: In the BVS 1 between 13.11.2000 and 15.3.2002, 3.072 participants, 1350 men and 1722 women, from a simple random sample of the general population of the city of Bonn and two rural townships aged 18-79 years were included. The overall response proportion was 59%. All participants answered a standardized questionnaire including information about socio-economic data, lifestyle, physical activity, medical history, and quality of life. Venous investigations were performed clinically and by a standardized duplex examination by trained investigators. The CEAP classification in the version of 1996 was used to classify the findings. Logistic regression models were performed for the association of possible risk factors with VV, venous edema (C3) and severe CVI (C4-C6). The predictive risk (PR) describes the association of the diseases and the possible influencing factors. Results: VV, venous oedema (C3) and severe CVI (C4-C6) have common risk factors like higher age, number of pregnancies, family history of VV and overweight or obesity. Female gender is significantly associated with VV and C3 but not with severe CVI (C4-C6). High blood pressure and urban living are only associated with C3 and C4-C6 disease whereas prolonged sitting is associated with C3 and lower social class with C4-C6 exclusively. Discussion: In many epidemiological studies risk factors were associated with chronic venous disorders in general. Our data show that VV, venous edema and severe CVI may have different risk profiles. Venous edema is more often associated with arterial hypertension and sedentary lifestyle whereas lower social class seems to be a risk factor for severe CVI including venous ulcers. Conclusions: The differences in the association of risk factors to VV, venous edema and severe CVI should be considered if prevention and treatment of chronic venous diseases are planned. As examples, compression stockings could be proposed in sitting profession to prevent oedema, VV patients with risk factors like obesity might benefit from early treatment for VV and obesity. More longitudinal evaluation of risk factors is necessary to evaluate the true risk profile of CVD.

One-year follow-up healthcare costs of patients diagnosed with skin cancer in Germany: a claims data analysis.

BACKGROUND: Routine skin cancer screening (SCS) is covered by the German statutory health insurance (SHI) since 2008. The objective of this study was to compare direct healthcare costs between patients in whom skin cancer was detected by routine SCS and patients in whom skin cancer was not detected by routine SCS. METHODS: A retrospective observational study of administrative claims data from a large German SHI was performed. Patients with a diagnosis of malignant melanoma (MM) or non-melanoma skin cancer (NMSC) diagnosed in 2014 or 2015 were included. Costs were obtained for one year before and one year after diagnosis and analyzed in a difference-in-differences approach using regression models. Frequency matching was applied and risk adjustment was performed. Additional analyses were conducted, separately for specific age groups, excluding persons who died during the observation period and without taking costs for screening into consideration. RESULTS: A total of 131,801 patients were included, of whom 13,633 (10.3%) had a diagnosis of MM and 118,168 (89.7%) had a diagnosis of NMSC. The description of total costs (without risk adjustment) shows lower mean total costs among patients whose skin cancer was detected via routine SCS compared to patients in whom skin cancer was not detected by routine SCS (MM: €5,326 (95% confidence interval (CI) €5,073; €5,579) vs. €9,038 (95% CI €8,629; €9,448); NMSC: €4,660 (95% CI €4,573; €4,745) vs. €5,890 (95% CI €5,813; €5,967)). Results of the regression analysis show cost savings of 18.8% (95% CI -23.1; -8.4) through routine SCS for patients with a diagnosis of MM. These cost savings in MM patients were more pronounced in patients younger than 65 years of age. For patients with a diagnosis of NMSC, the analysis yields a non-substantial increase in costs (2.5% (95% CI -0.1; 5.2)). CONCLUSION: Cost savings were detected for persons with an MM diagnosed by routine SCS. However, the study could not detect lower costs due to routine SCS in the large fraction of persons with a diagnosis of NMSC. These results offer important insights into the cost structure of the routine SCS and provide opportunities for refinements.

Skin Cancer Screening and Medical Treatment Intensity in Patients with Malignant Melanoma and Non-Melanocytic Skin Cancer.

BACKGROUND: This cohort study concerns the effect of skin cancer screening (SCS) on medical treatment intensity in patients with skin cancer. METHODS: Routine data from persons aged 35 to 99 who were insured by the AOK health insurance company were used to identify persons who received a diagnosis of malignant melanoma or a non-melanocytic skin cancer in 2014 or 2015, either through skin cancer screening or without screening. These persons were included in cohort studies. The routine data contained no information on tumor stages or grading. Tumor-associated rates of hospital admission, contact with physicians in outpatient practice, and intensity of surgical treatment were determined; rate ratios (RR) and their 95% confidence intervals (CI) were estimated. RESULTS: The cohort studies included 13 633 patients with melanoma (6480 with SCS and 7153 without) and 118 168 patients with non-melanocytic skin cancer (43 308 with screening and 74 860 without). Patients whose melanomas had been detected by screening had a lower medical treatment intensity than unscreened patients (intensity of tumor-associated surgical treatment (RR = 0.79, 95% CI [0.74; 0.85]), hospital contact rate (RR = 0.44, 95% CI: [0.38; 0.50]), contact with physicians in outpatient practice (RR = 0.79, 95% CI: [0.73; 0.85]). Among patients with non-melanocytic skin cancer, the screened patients displayed a lower hospital contact rate (RR = 0.52, 95% CI: [0.49; 0.56]), a higher contact rate in the outpatient sector (RR = 1.11, 95% CI: [1.08; 1.13]), and no difference in surgical treatment intensity (RR = 0.98, 95% CI: [0.96; 1.00]). CONCLUSION: SCS is associated with lower medical treatment intensity in the first 12 months after diagnosis in patients with melanoma. Among patients with non-melanocytic skin cancer, those who had been screened had lower hospital contact rates, but there was no observed lowering of other rates reflecting treatment intensity.

The impossibility of mortality evaluation of skin cancer screening in Germany based on health insurance data: a case-control study.

BACKGROUND: The aim of this paper was to perform a mortality evaluation of skin cancer screening (SCS) in Germany using General Local Health Insurance Fund (AOK) data. METHODS: AOK-insured men and women aged 35-99 years who died of cutaneous malignant melanoma in 2015-2016 were identified. Controls were AOK-insured people who survived to the end of each case's year of death. For each case, 10 controls were matched. The SCS history of each individual was reconstructed using the billing codes 01745 and 01746. RESULTS: In total, 1037 melanoma deaths and 10,370 controls were included. Cumulative SCS prevalence increased among controls over calendar years, as expected (males and females, 2009: 13.5% and 12.5%; 2015: 52.1% and 55.1%). In contrast, among cases, cumulative SCS prevalence was already high in 2009 and did not show a monotonic increase over the years of diagnosis. Of the 1037 melanoma deaths, 224 (21.6%) had at least one SCS settled in the 12 months after diagnosis. DISCUSSION: A mortality evaluation with health insurance data alone is not possible because SCS billing codes are not only used for real SCS but also for occasion-related diagnostic work-up of abnormal skin findings. A mortality evaluation with health insurance data requires an individual linking with data of the screening physician and the cancer registries.