Metabolic and inflammatory biomarker trajectories after a cancer diagnosis and the risk of cardiovascular diseases

Figures

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  Fig. 1. Study design and analytical approaches. CVD cardiovascular disease, TPR Total Population Register.

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  Fig. 2. Overall associations between any cancer diagnosis and the risk of cardiovascular disease and by age at cancer diagnosis. IRR, incidence rate ratio; CI, confidence intervals. *per 1000 person-years. **Adjusted for age and calendar period of follow-up, sex, year of birth, country of birth, income, education, and employment status at the first blood sampling, as well as diabetes and psychiatric disorders during follow-up. Incidence rate ratio together with 95% confidence intervals were calculated through Poisson regression models.

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  Fig. 3. Associations between any cancer diagnosis and the risk of cardiovascular disease by subtypes of cardiovascular disease. CVD, cardiovascular disease; IRR, incidence rate ratio; CI, confidence intervals. *per 1000 person-years. **Adjusted for age and calendar period of follow-up, sex, year of birth, country of birth, income, education, and employment status at the first blood sampling, as well as diabetes and psychiatric disorders during follow-up. Incidence rate ratio together with 95% confidence intervals were calculated through Poisson regression models.

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  Fig. 4. Associations between cancer and the risk cardiovascular disease by the subtypes of cancer. IRR, incidence rate ratio; CI, confidence intervals. *per 1000 person-years. **Adjusted for age and calendar period of follow-up, sex, year of birth, country of birth, income, education, and employment status at the first blood sampling, as well as diabetes and psychiatric disorders during follow-up. Incidence rate ratio together with 95% confidence intervals were calculated through Poisson regression models.

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  Fig. 5. Longitudinal biomarker trajectories among individuals with and without a history of cancer. TC, total cholesterol; HDL, high-density lipoprotein; LDL, low-density lipoprotein; TG, triglycerides; ApoA1, apolipoprotein A1; ApoB, apolipoprotein B; IgG, immunoglobulin G; CRP, C-reactive protein. Biomarker trajectories in relation to cancer were predicted and plotted by coefficients from the linear mixed effect models with a quadratic term of time for LDL, LDL/HDL ratio, leukocyte, and haptoglobin. Shaded areas represent 95% confidence intervals. Adjusted for propensity score, time since the index date, and interaction between cancer and time.

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  Fig. 6. Latent classes of longitudinal biomarker trajectories following a cancer diagnosis. Glucose [Class 1: stable at low levels, Class 2: started at high levels and increased]; TC [Class 1: started low with a U-shape pattern, Class 2: stable at high levels]; HDL [Class 1: started at low levels and increased, Class 2: started at high levels and decreased]; LDL [Class 1: started at high levels and decreased, Class 2: started at low levels and increased]; LDL/HDL ratio [Class 1: slight decrease followed by an increase, Class 2: slight increase followed by a decrease]; ApoA1 [Class 1: started at high levels and remained stable, Class 2: started low with an N-shape pattern]; ApoB [Class 1: started at low levels and decreased, Class 2: started at high levels and decreased]; ApoB/ApoA1 ratio [Class 1: started at low levels and decreased, Class 2: started at high levels and decreased]; albumin [Class 1–3: low-, moderate-, and high-stable levels]; CRP [Class 1: started at low levels, rapidly increased, then decreased, Class 2: started at high levels, slightly decreased, then increased]; uric acid [Class 1: started at low levels, remained stable, then increased, Class 2: started at high levels…