Browsing by Subject "RISK PREDICTION"

Sort by: Order: Results:

Now showing items 1-10 of 10
  • Lee, Jiwoo; Kiiskinen, Tuomo; Mars, Nina; Jukarainen, Sakari; Ingelsson, Erik; Neale, Benjamin; Ripatti, Samuli; Natarajan, Pradeep; Ganna, Andrea (2021)
    Background: Acute coronary syndrome (ACS) is a clinically significant presentation of coronary heart disease. Genetic information has been proposed to improve prediction beyond well-established clinical risk factors. While polygenic scores (PS) can capture an individual's genetic risk for ACS, its prediction performance may vary in the context of diverse correlated clinical conditions. Here, we aimed to test whether clinical conditions impact the association between PS and ACS. Methods: We explored the association between 405 clinical conditions diagnosed before baseline and 9080 incident cases of ACS in 387 832 individuals from the UK Biobank. Results were replicated in 6430 incident cases of ACS in 177 876 individuals from FinnGen. Results: We identified 80 conventional (eg, stable angina pectoris and type 2 diabetes) and unconventional (eg, diaphragmatic hernia and inguinal hernia) associations with ACS. The association between PS and ACS was consistent in individuals with and without most clinical conditions. However, a diagnosis of stable angina pectoris yielded a differential association between PS and ACS. PS was associated with a significantly reduced (interaction P=2.87x10(-8)) risk for ACS in individuals with stable angina pectoris (hazard ratio, 1.163 [95% CI, 1.082-1.251]) compared with individuals without stable angina pectoris (hazard ratio, 1.531 [95% CI, 1.497-1.565]). These findings were replicated in FinnGen (interaction P=1.38x10(-6)). Conclusions: In summary, while most clinical conditions did not impact utility of PS for prediction of ACS, we found that PS was substantially less predictive of ACS in individuals with prevalent stable coronary heart disease. PS may be more appropriate for prediction of ACS in asymptomatic individuals than symptomatic individuals with clinical suspicion for coronary heart disease.
  • IPPIC Collaborative Network; Snell, Kym I. E.; Allotey, John; Smuk, Melanie; Laivuori, Hannele; Heinonen, Seppo; Kajantie, Eero; Villa, Pia M. (2020)
    Background: Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. Methods: IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. Results: Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model's calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. Conclusions: The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice.
  • Weissbrod, Omer; Hormozdiari, Farhad; Benner, Christian; Cui, Ran; Ulirsch, Jacob; Gazal, Steven; Schoech, Armin P.; van de Geijn, Bryce; Reshef, Yakir; Marquez-Luna, Carla; O'Connor, Luke; Pirinen, Matti; Finucane, Hilary K.; Price, Alkes L. (2020)
    Fine-mapping aims to identify causal variants impacting complex traits. We propose PolyFun, a computationally scalable framework to improve fine-mapping accuracy by leveraging functional annotations across the entire genome-not just genome-wide-significant loci-to specify prior probabilities for fine-mapping methods such as SuSiE or FINEMAP. In simulations, PolyFun + SuSiE and PolyFun + FINEMAP were well calibrated and identified >20% more variants with a posterior causal probability >0.95 than identified in their nonfunctionally informed counterparts. In analyses of 49 UK Biobank traits (average n = 318,000), PolyFun + SuSiE identified 3,025 fine-mapped variant-trait pairs with posterior causal probability >0.95, a >32% improvement versus SuSiE. We used posterior mean per-SNP heritabilities from PolyFun + SuSiE to perform polygenic localization, constructing minimal sets of common SNPs causally explaining 50% of common SNP heritability; these sets ranged in size from 28 (hair color) to 3,400 (height) to 2 million (number of children). In conclusion, PolyFun prioritizes variants for functional follow-up and provides insights into complex trait architectures. PolyFun is a computationally scalable framework for functionally informed fine-mapping that makes full use of genome-wide data. It prioritizes more variants than previous methods when applied to 49 complex traits from UK Biobank.
  • Khanshour, Anas M.; Kou, Ikuyo; Fan, Yanhui; Einarsdottir, Elisabet; Makki, Nadja; Kidane, Yared H.; Kere, Juha; Grauers, Anna; Johnson, Todd A.; Paria, Nandina; Patel, Chandreshkumar; Singhania, Richa; Kamiya, Nobuhiro; Takeda, Kazuki; Otomo, Nao; Watanabe, Kota; Luk, Keith D. K.; Cheung, Kenneth M. C.; Herring, John A.; Rios, Jonathan J.; Ahituv, Nadav; Gerdhem, Paul; Gurnett, Christina A.; Song, You-Qiang; Ikegawa, Shiro; Wise, Carol A. (2018)
    Adolescent idiopathic scoliosis (AIS) is the most common musculoskeletal disorder of childhood development. The genetic architecture of AIS is complex, and the great majority of risk factors are undiscovered. To identify new AIS susceptibility loci, we conducted the first genome-wide meta-analysis of AIS genome-wide association studies, including 7956 cases and 88 459 controls from 3 ancestral groups. Three novel loci that surpassed genome-wide significance were uncovered in intragenic regions of the CDH13 (P-value_rs4513093 = 1.7E-15), ABO (P-value_ rs687621 = 7.3E-10) and SOX6 (P-value_ rs1455114 = 2.98E-08) genes. Restricting the analysis to females improved the associations at multiple loci, most notably with variants within CDH13 despite the reduction in sample size. Genome-wide gene-functional enrichment analysis identified significant perturbation of pathways involving cartilage and connective tissue development. Expression of both SOX6 and CDH13 was detected in cartilage chondrocytes and chromatin immunoprecipitation sequencing experiments in that tissue revealed multiple HeK27ac-positive peaks overlapping associated loci. Our results further define the genetic architecture of AIS and highlight the importance of vertebral cartilage development in its pathogenesis.
  • CardShock Investigators; Jäntti, Toni; Tarvasmäki, Tuukka; Harjola, Veli-Pekka; Parissis, John; Javanainen, Tuija; Tolppanen, Heli; Jurkko, Raija; Hongisto, Mari; Kataja, Anu; Lassus, Johan; Jurkko, Raija; Jarvinen, Kristiina; Nieminen, Tuomo (2019)
    Introduction The prevalence of hypoalbuminemia, early changes of plasma albumin (P-Alb) levels, and their effects on mortality in cardiogenic shock are unknown. Materials and methods P-Alb was measured from serial blood samples in 178 patients from a prospective multinational study on cardiogenic shock. The association of hypoalbuminemia with clinical characteristics and course of hospital stay including treatment and procedures was assessed. The primary outcome was all-cause 90-day mortality. Results Hypoalbuminemia (P-Alb < 34g/L) was very frequent (75%) at baseline in patients with cardiogenic shock. Patients with hypoalbuminemia had higher mortality than patients with normal albumin levels (48% vs. 23%, p = 0.004). Odds ratio for death at 90 days was 2.4 [95% CI 1.5–4.1] per 10 g/L decrease in baseline P-Alb. The association with increased mortality remained independent in regression models adjusted for clinical risk scores developed for cardiogenic shock (CardShock score adjusted odds ratio 2.0 [95% CI 1.1–3.8], IABP-SHOCK II score adjusted odds ratio 2.5 [95%CI 1.2–5.0]) and variables associated with hypoalbuminemia at baseline (adjusted odds ratio 2.9 [95%CI 1.2–7.1]). In serial measurements, albumin levels decreased at a similar rate between 0h and 72h in both survivors and nonsurvivors (ΔP-Alb -4.6 g/L vs. 5.4 g/L, p = 0.5). While the decrease was higher for patients with normal P-Alb at baseline (p<0.001 compared to patients with hypoalbuminemia at baseline), the rate of albumin decrease was not associated with outcome. Conclusions Hypoalbuminemia was a frequent finding early in cardiogenic shock, and P-Alb levels decreased during hospital stay. Low P-Alb at baseline was associated with mortality independently of other previously described risk factors. Thus, plasma albumin measurement should be part of the initial evaluation in patients with cardiogenic shock. Trial registration NCT01374867 at
  • Moser, Andre; Reinikainen, Matti; Jakob, Stephan M.; Selander, Tuomas; Pettilä, Ville; Kiiski, Olli; Varpula, Tero; Raj, Rahul; Takala, Jukka (2022)
    Objective: Prognostic models are key for benchmarking intensive care units (ICUs). They require up-to-date predictors and should report transportability properties for reliable predictions. We developed and validated an in-hospital mortality risk prediction model to facilitate benchmarking, quality assurance, and health economics evaluation. Study Design and Setting: We retrieved data from the database of an international (Finland, Estonia, Switzerland) multicenter ICU cohort study from 2015 to 2017. We used a hierarchical logistic regression model that included age, a modified Simplified Acute Physiology Score-II, admission type, premorbid functional status, and diagnosis as grouping variable. We used pooled and meta-analytic cross-validation approaches to assess temporal and geographical transportability. Results: We included 61,224 patients treated in the ICU (hospital mortality 10.6%). The developed prediction model had an area under the receiver operating characteristic curve 0.886, 95% confidence interval (CI) 0.882-0.890; a calibration slope 1.01, 95% CI (0.99-1.03); a mean calibration -0.004, 95% CI (-0.035 to 0.027). Although the model showed very good internal validity and geographic discrimination transportability, we found substantial heterogeneity of performance measures between ICUs (I-squared: 53.4-84.7%). Conclusion: A novel framework evaluating the performance of our prediction model provided key information to judge the validity of our model and its adaptation for future use. (c) 2021 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license ( http:// licenses/ by/ 4.0/ )
  • Epi25 Consortium; Leu, Costin; Stevelink, Remi; Palotie, Aarno; Daly, Mark J.; Lehesjoki, Anna-Elina (2019)
    Rare genetic variants can cause epilepsy, and genetic testing has been widely adopted for severe, paediatric-onset epilepsies. The phenotypic consequences of common genetic risk burden for epilepsies and their potential future clinical applications have not yet been determined. Using polygenic risk scores (PRS) from a European-ancestry genome-wide association study in generalized and focal epilepsy, we quantified common genetic burden in patients with generalized epilepsy (GE-PRS) or focal epilepsy (FE-PRS) from two independent non-Finnish European cohorts (Epi25 Consortium, n = 5705; Cleveland Clinic Epilepsy Center, n = 620; both compared to 20 435 controls). One Finnish-ancestry population isolate (Finnish-ancestry Epi25, n = 449; compared to 1559 controls), two European-ancestry biobanks (UK Biobank, n = 383 656; Vanderbilt biorepository, n = 49 494), and one Japanese-ancestry biobank (BioBank Japan, n = 168 680) were used for additional replications. Across 8386 patients with epilepsy and 622 212 population controls, we found and replicated significantly higher GE-PRS in patients with generalized epilepsy of European-ancestry compared to patients with focal epilepsy (Epi25: P = 1.64 x 10(-15); Cleveland: P = 2.85 x 10(-4); Finnish-ancestry Epi25: P = 1.80 x 10(-4)) or population controls (Epi25: P = 2.35 x 10(-70); Cleveland: P = 1.43 x 10(-7); Finnish-ancestry Epi25: P = 3.11 x 10(-4); UK Biobank and Vanderbilt biorepository meta-analysis: P = 7.99 x 10(-4)). FE-PRS were significantly higher in patients with focal epilepsy compared to controls in the non-Finnish, non-biobank cohorts (Epi25: P = 5.74 x 10(-19); Cleveland: P = 1.69 x 10(-6)). European ancestry-derived PRS did not predict generalized epilepsy or focal epilepsy in Japanese-ancestry individuals. Finally, we observed a significant 4.6-fold and a 4.5-fold enrichment of patients with generalized epilepsy compared to controls in the top 0.5% highest GE-PRS of the two non-Finnish European cohorts (Epi25: P = 2.60 x 10(-15); Cleveland: P = 1.39 x 10(-2)). We conclude that common variant risk associated with epilepsy is significantly enriched in multiple cohorts of patients with epilepsy compared to controls-in particular for generalized epilepsy. As sample sizes and PRS accuracy continue to increase with further common variant discovery, PRS could complement established clinical biomarkers and augment genetic testing for patient classification, comorbidity research, and potentially targeted treatment.
  • CardShock Study Investigators; GREAT-Network; Tolppanen, Heli; Javanainen, Tuija; Nieminen, Tuomo; Harjola, Veli-Pekka; Jurkko, Raija; Lassus, Johan (2018)
    Changes in QRS duration and pattern are regarded to reflect severe ischemia in acute coronary syndromes (ACS), and ventricular conduction blocks (VCBs) are recognized high-risk markers in both ACS and acute heart failure. Our aim was to evaluate the prevalence, temporal evolution, association with clinical and angiographic parameters, and impact on mortality of VCBs in ACS-related cardiogenic shock (CS). Data of 199 patients with ACS-related CS from a prospective multinational cohort were evaluated with electrocardiogram data from baseline and day 3. VCBs including left or right bundle branch block, right bundle branch block and hemiblock, isolated hemiblocks, and unspecified intraventricular conduction delay were assessed. Fifty percent of patients had a VCB at baseline; these patients were older, had poorer left ventricular function and had more often left main disease compared with those without VCB. One-year mortality was over 2-fold in patients with VCB compared with those without VCB (68% vs 32%, p
  • Okser, Sebastian; Pahikkala, Tapio; Airola, Antti; Salakoski, Tapio; Ripatti, Samuli; Aittokallio, Tero (2014)
  • Takala, Jukka; Moser, Andre; Raj, Rahul; Pettilä, Ville; Irincheeva, Irina; Selander, Tuomas; Kiiski, Olli; Varpula, Tero; Reinikainen, Matti; Jakob, Stephan M. (2022)
    Purpose Intensive care patients have increased risk of death and their care is expensive. We investigated whether risk-adjusted mortality and resources used to achieve survivors change over time and if their variation is associated with variables related to intensive care unit (ICU) organization and structure. Methods Data of 207,131 patients treated in 2008-2017 in 21 ICUs in Finland, Estonia and Switzerland were extracted from a benchmarking database. Resource use was measured using ICU length of stay, daily Therapeutic Intervention Scoring System Scores (TISS) and purchasing power parity-adjusted direct costs (2015-2017; 17 ICUs). The ratio of observed to severity-adjusted expected resource use (standardized resource use ratio; SRUR) was calculated. The number of expected survivors and the ratio of observed to expected mortality (standardized mortality ratio; SMR) was based on a mortality prediction model covering 2015-2017. Fourteen a priori variables reflecting structure and organization were used as explanatory variables for SRURs in multivariable models. Results SMR decreased over time, whereas SRUR remained unchanged, except for decreased TISS-based SRUR. Direct costs of one ICU day, TISS score and ICU admission varied between ICUs 2.5-5-fold. Differences between individual ICUs in both SRUR and SMR were up to > 3-fold, and their evolution was highly variable, without clear association between SRUR and SMR. High patient turnover was consistently associated with low SRUR but not with SMR. Conclusion The wide and independent variation in both SMR and SRUR suggests that they should be used together to compare the performance of different ICUs or an individual ICU over time.