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- Chen, Qiao Sen, et al.
(författare)
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A machine learning based approach to identify carotid subclinical atherosclerosis endotypes
- 2023
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Ingår i: Cardiovascular Research. - : OXFORD UNIV PRESS. - 0008-6363 .- 1755-3245. ; 119:16, s. 2594-2606
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Tidskriftsartikel (refereegranskat)abstract
- Aims To define endotypes of carotid subclinical atherosclerosis. Methods and results We integrated demographic, clinical, and molecular data (n = 124) with ultrasonographic carotid measurements from study participants in the IMPROVE cohort (n = 3340). We applied a neural network algorithm and hierarchical clustering to identify carotid atherosclerosis endotypes. A measure of carotid subclinical atherosclerosis, the c-IMTmean-max, was used to extract atherosclerosis-related features and SHapley Additive exPlanations (SHAP) to reveal endotypes. The association of endotypes with carotid ultrasonographic measurements at baseline, after 30 months, and with the 3-year atherosclerotic cardiovascular disease (ASCVD) risk was estimated by linear (& beta;, SE) and Cox [hazard ratio (HR), 95% confidence interval (CI)] regression models. Crude estimates were adjusted by common cardiovascular risk factors, and baseline ultrasonographic measures. Improvement in ASCVD risk prediction was evaluated by C-statistic and by net reclassification improvement with reference to SCORE2, c-IMTmean-max, and presence of carotid plaques. An ensemble stacking model was used to predict endotypes in an independent validation cohort, the PIVUS (n = 1061). We identified four endotypes able to differentiate carotid atherosclerosis risk profiles from mild (endotype 1) to severe (endotype 4). SHAP identified endotype-shared variables (age, biological sex, and systolic blood pressure) and endotype-specific biomarkers. In the IMPROVE, as compared to endotype 1, endotype 4 associated with the thickest c-IMT at baseline (& beta;, SE) 0.36 (0.014), the highest number of plaques 1.65 (0.075), the fastest c-IMT progression 0.06 (0.013), and the highest ASCVD risk (HR, 95% CI) (1.95, 1.18-3.23). Baseline and progression measures of carotid subclinical atherosclerosis and ASCVD risk were associated with the predicted endotypes in the PIVUS. Endotypes consistently improved measures of ASCVD risk discrimination and reclassification in both study populations. Conclusions We report four replicable subclinical carotid atherosclerosis-endotypes associated with progression of atherosclerosis and ASCVD risk in two independent populations. Our approach based on endotypes can be applied for precision medicine in ASCVD prevention.
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| 2. |
- Crombag, Marie-Rose B S, et al.
(författare)
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Exposure to Docetaxel in the Elderly Patient Population : a Population Pharmacokinetic Study.
- 2019
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Ingår i: Pharmaceutical research. - : Springer Science and Business Media LLC. - 0724-8741 .- 1573-904X. ; 36:12, s. 181-
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Docetaxel is commonly used in elderly patients, who are frequently diagnosed with prostate cancer. Although previous studies revealed no clinically relevant impact of older age on docetaxel pharmacokinetics (PK), this may be masked by indication. Metastatic castration-resistant prostate cancer (mCRPC) patients were reported to have approximately two-times lower systemic exposure compared to patients with other solid tumors. This study assessed the impact of older age on docetaxel PK, also considering the effect of indication on docetaxel PK.METHODS: Prospectively collected docetaxel PK data from patients aged ≥70 was pooled with PK data from an earlier published multicenter study. A 3-compartment population PK model, including multiple covariates, was used to describe docetaxel plasma concentration-time data. We added the effect of prostate cancer (mCRPC and metastatic hormone-sensitive prostate cancer (mHSPC)) on clearance to this model. Hereafter, we evaluated the additional impact of older age on docetaxel clearance, using a significance threshold of p < 0.005.RESULTS: Docetaxel plasma concentration-time data from 157 patients were analyzed. Median age in the total cohort was 67 years (range 31-87), with 49% of the total cohort aged ≥70. The impact of age on docetaxel clearance was statistically significant (p < 0.005). For a typical patient, a 10-year and 20-year increase of age led to a reduction in clearance of 17% and 34%, respectively.CONCLUSION: In this cohort study, age significantly and independently affected docetaxel clearance, showing lower docetaxel clearance in elderly patients. In our cohort, mCRPC and mHSPC patients both had higher clearance than patients with other solid tumors.
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| 3. |
- Severson, Tesa, et al.
(författare)
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Androgen receptor reprogramming demarcates prognostic, context-dependent gene sets in primary and metastatic prostate cancer
- 2022
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Ingår i: Clinical Epigenetics. - : Springer Science and Business Media LLC. - 1868-7075 .- 1868-7083. ; 14:1
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Tidskriftsartikel (refereegranskat)abstract
- The androgen receptor (AR) is a prostate master transcription factor. It binds to genetic enhancers, where it regulates gene activity and plays a fundamental role in prostate pathophysiology. Previous work has demonstrated that AR-DNA binding is systematically and consistently reprogrammed during prostate tumorigenesis and disease progression. We charted these reprogrammed AR sites and identified genes proximal to them. We were able to devise gene lists based on AR status within specific histological contexts: normal prostate epithelium, primary prostate tumor, and metastatic prostate cancer. We evaluated expression of the genes in these gene sets in subjects from two distinct clinical cohorts—men treated with surgery for localized prostate cancer and men with metastatic prostate cancer. Among men with localized prostate cancer, expression of genes proximal to AR sites lost in the transition from normal prostate to prostate tumor was associated with clinical outcome. Among men with metastatic disease, expression of genes proximal to AR sites gained in metastatic tumors was associated with clinical outcome. These results are consistent with the notion that AR is fundamental to both maintaining differentiation in normal prostate tissue and driving de-differentiation in advanced prostate cancer. More broadly, the study demonstrates the power of incorporating context-dependent epigenetic data into genetic analyses.
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