4 research outputs found
Chart for absolute 10-year risk of fatal cardiovascular disease based on the new model using cholesterol ratio.
<p>9,446 participants of the Swiss MONICA study conducted 1983–92, ages 25–74 years at baseline MONICA: MONItoring of trends and determinants in CArdiovascular disease, entire population with full follow-up HDL: High-density lipoprotein Each risk percentage is calculated using a combination of given risk factor values. E.g., a man aged 65, smoker, with a systolic blood pressure of 180 and a total cholesterol of 6 mmol/L has an absolute risk (within the next 10 years) of fatal CVD of 14%.</p
Chart for absolute 10-year risk of fatal cardiovascular disease based on the new model using total cholesterol.
<p>9,446 participants of the Swiss MONICA study conducted 1983–92, ages 25–74 years at baseline. MONICA: MONItoring of trends and determinants in CArdiovascular disease, entire population with full follow-up Each risk percentage is calculated using a combination of given risk factor values. E.g., a man aged 65, smoker, with a systolic blood pressure of 180 and a total cholesterol of 6 mmol/L has an absolute risk (within the next 10 years) of fatal CVD of 14%.</p
Parameters and coefficients of the three models.
*<p>“Low-risk” countries: Belgium (n = 10,641), Italy (n = 53,439), Spain (n = 4,701).</p><p>Figures in brackets are 95% confidence intervals, not given for the original SCORE model.</p><p>CVD: cardiovascular disease; CHD: coronary heart disease; non-CHD: non-coronary CVD.</p><p>Cholesterol ratio: Total-to-HDL(high-density lipoprotein)-cholesterol.</p
DataSheet1_Applying the estimand and target trial frameworks to external control analyses using observational data: a case study in the solid tumor setting.DOCX
Introduction: In causal inference, the correct formulation of the scientific question of interest is a crucial step. The purpose of this study was to apply causal inference principles to external control analysis using observational data and illustrate the process to define the estimand attributes.Methods: This study compared long-term survival outcomes of a pooled set of three previously reported randomized phase 3 trials studying patients with metastatic non-small cell lung cancer receiving front-line chemotherapy and similar patients treated with front-line chemotherapy as part of routine clinical care. Causal inference frameworks were applied to define the estimand aligned with the research question and select the estimator to estimate the estimand of interest.Results: The estimand attributes of the ideal trial were defined using the estimand framework. The target trial framework was used to address specific issues in defining the estimand attributes using observational data from a nationwide electronic health record-derived de-identified database. The two frameworks combined allow to clearly define the estimand and the aligned estimator while accounting for key baseline confounders, index date, and receipt of subsequent therapies. The hazard ratio estimate (point estimate with 95% confidence interval) comparing the randomized clinical trial pooled control arm with the external control was close to 1, which is indicative of similar survival between the two arms.Discussion: The proposed combined framework provides clarity on the causal contrast of interest and the estimator to adopt, and thus facilitates design and interpretation of the analyses.</p