Using routine blood test results to predict the risk of death for emergency medical admissions to hospital: an external model validation study

YesBackground The Biochemistry and Haematology Outcome Model (BHOM) relies on the results from routine index blood tests to predict the patient risk of death. We aimed to externally validate the BHOM model. Method We considered all emergency adult medical patients who were discharged from Northern Lincolnshire and Goole (NLAG) hospital in 2014. We compared patient characteristics between NLAG (the validation sample) and the hospital where BHOM was developed. We evaluated the predictive performance, according to discriminative ability (with a concordance statistic, c), and calibration (agreement between observed and predicted risk). Result There were 29 834 emergency discharges of which 24 696 (83%) had complete data. In comparison with the development sample, the NLAG sample was similar in age, blood test results, but experienced a lower mortality (4.7% vs 8.7%). When applied to NLAG, the BHOM model had good discrimination (c-statistic 0.83 [95% CI 0.823 - 0.842]). Calibration was good overall, although the BHOM model overpredicted for lowest (<5%, observed = 229,predicted =286) and highest (≥50%, observed = 31, predicted = 49) risk groups, even after recalibrating for the differences in baseline risk of death. Conclusion Differences in patient case-mix profile and baseline risk of death need to be considered before the BHOM model can be used in another hospital. After re-calibrating for the baseline difference in risk the BHOM model had good discrimination but less adequate calibration

Predictive validity of the CriSTAL tool for short-term mortality in older people presenting at Emergency Departments: a prospective study

© 2018, The Author(s). Abstract: To determine the validity of the Australian clinical prediction tool Criteria for Screening and Triaging to Appropriate aLternative care (CRISTAL) based on objective clinical criteria to accurately identify risk of death within 3 months of admission among older patients. Methods: Prospective study of ≥ 65 year-olds presenting at emergency departments in five Australian (Aus) and four Danish (DK) hospitals. Logistic regression analysis was used to model factors for death prediction; Sensitivity, specificity, area under the ROC curve and calibration with bootstrapping techniques were used to describe predictive accuracy. Results: 2493 patients, with median age 78–80 years (DK–Aus). The deceased had significantly higher mean CriSTAL with Australian mean of 8.1 (95% CI 7.7–8.6 vs. 5.8 95% CI 5.6–5.9) and Danish mean 7.1 (95% CI 6.6–7.5 vs. 5.5 95% CI 5.4–5.6). The model with Fried Frailty score was optimal for the Australian cohort but prediction with the Clinical Frailty Scale (CFS) was also good (AUROC 0.825 and 0.81, respectively). Values for the Danish cohort were AUROC 0.764 with Fried and 0.794 using CFS. The most significant independent predictors of short-term death in both cohorts were advanced malignancy, frailty, male gender and advanced age. CriSTAL’s accuracy was only modest for in-hospital death prediction in either setting. Conclusions: The modified CriSTAL tool (with CFS instead of Fried’s frailty instrument) has good discriminant power to improve prognostic certainty of short-term mortality for ED physicians in both health systems. This shows promise in enhancing clinician’s confidence in initiating earlier end-of-life discussions

Understanding older patients' self-management abilities: functional loss, self-management, and well-being

Purpose: This study aimed to increase our understanding of self-management abilities and identify better self-managers among older individuals. Methods: Our cross-sectional research was based on a pilot study of older people who had recently been admitted to a hospital. In the pilot study, all patients (>65 years of age) who were admitted to the Vlietland hospital between June and October 2010 were asked to participate, which led to the inclusion of 456 older patients at baseline. A total of 296 patients (65% response rate) were interviewed in their homes 3 months after admission. Measures included social, cognitive, and physical functioning, self-management abilities, and well-being. We used descriptive, correlations, and multiple regression analyses. In addition, we evaluated the mediation effect of self-management abilities on well-being. Results: Social, cognitive, and physical functioning significantly correlated with self-management abilities and well-being (all p ≤ 0.001). After controlling for background characteristics, multiple regression analysis indicated that social, cognitive, and physical functioning still related to self-management abilities (β = 0.17-0.25; all p ≤ 0.001). Older people with low levels of social, cognitive, and physical functioning were worse self-managers than were those with higher levels of functioning. Conclusions: Self-management abilities mediate the relationship between social, cognitive, and physical functioning and well-being. Interventions to improve self-management abilities may help older people better deal with function losses as they age further

Mutation prediction models in Lynch syndrome: evaluation in a clinical genetic setting

Background/aims: The identification of Lynch syndrome is hampered by the absence of specific diagnostic features and underutilization of genetic testing. Prediction models have therefore been developed, but they have not been validated for a clinical genetic setting. The aim of the present study was to evaluate the usefulness of currently available prediction models. METHODS: We collected data of 321 index probands who were referred to the department of Clinical Genetics of the Erasmus Medical Center because of a family history of colorectal cancer. These data were used as input for five previously published models. External validity was assessed by discriminative ability (AUC: area under the receiver operating characteristic curve) and calibration. For further insight, predicted probabilities were categorized with cut-offs of 5%, 10%, 20% and 40%. Furthermore, costs of different testing strategies were related to the number of extra detected mutation carriers. RESULTS: Of the 321 index probands, 66 harboured a germline mutation. All models discriminated well between high risk and low risk index probands (AUC: 0.82-0.84). Calibration was well for the Premm1,2 and Edinburgh model, but poor for the other models. Cut-offs could be found for the prediction models where costs could be saved while missing only few mutations. CONCLUSIONS: The Edinburgh and Premm1,2 model were the models with the best performance for an intermediate to high-risk setting. These models may well be of use in clinical practice to select patients for further testing of mismatch repair gene mutations

Cost effectiveness of breast cancer screening and prevention: a systematic review with a focus on risk-adapted strategies

OBJECTIVES: Benefit and cost effectiveness of breast cancer screening are still matters of controversy. Risk-adapted strategies are proposed to improve its benefit-harm and cost–benefit relations. Our objective was to perform a systematic review on economic breast cancer models evaluating primary and secondary prevention strategies in the European health care setting, with specific focus on model results, model characteristics, and risk-adapted strategies. METHODS: Literature databases were systematically searched for economic breast cancer models evaluating the cost effectiveness of breast cancer screening and prevention strategies in the European health care context. Characteristics, methodological details and results of the identified studies are reported in evidence tables. Economic model outputs are standardized to achieve comparable cost-effectiveness ratios. RESULTS: Thirty-two economic evaluations of breast cancer screening and seven evaluations of primary breast cancer prevention were included. Five screening studies and none of the prevention studies considered risk-adapted strategies. Studies differed in methodologic features. Only about half of the screening studies modeled overdiagnosis-related harms, most often indirectly and without reporting their magnitude. All models predict gains in life expectancy and/or quality-adjusted life expectancy at acceptable costs. However, risk-adapted screening was shown to be more effective and efficient than conventional screening. CONCLUSIONS: Economic models suggest that breast cancer screening and prevention are cost effective in the European setting. All screening models predict gains in life expectancy, which has not yet been confirmed by trials. European models evaluating risk-adapted screening strategies are rare, but suggest that risk-adapted screening is more effective and efficient than conventional screening

A risk prediction model for the assessment and triage of women with hypertensive disorders of pregnancy in low-resourced settings: the miniPIERS (Pre-eclampsia Integrated Estimate of RiSk) multi-country prospective cohort study.

BACKGROUND: Pre-eclampsia/eclampsia are leading causes of maternal mortality and morbidity, particularly in low- and middle- income countries (LMICs). We developed the miniPIERS risk prediction model to provide a simple, evidence-based tool to identify pregnant women in LMICs at increased risk of death or major hypertensive-related complications. METHODS AND FINDINGS: From 1 July 2008 to 31 March 2012, in five LMICs, data were collected prospectively on 2,081 women with any hypertensive disorder of pregnancy admitted to a participating centre. Candidate predictors collected within 24 hours of admission were entered into a step-wise backward elimination logistic regression model to predict a composite adverse maternal outcome within 48 hours of admission. Model internal validation was accomplished by bootstrapping and external validation was completed using data from 1,300 women in the Pre-eclampsia Integrated Estimate of RiSk (fullPIERS) dataset. Predictive performance was assessed for calibration, discrimination, and stratification capacity. The final miniPIERS model included: parity (nulliparous versus multiparous); gestational age on admission; headache/visual disturbances; chest pain/dyspnoea; vaginal bleeding with abdominal pain; systolic blood pressure; and dipstick proteinuria. The miniPIERS model was well-calibrated and had an area under the receiver operating characteristic curve (AUC ROC) of 0.768 (95% CI 0.735-0.801) with an average optimism of 0.037. External validation AUC ROC was 0.713 (95% CI 0.658-0.768). A predicted probability ≥25% to define a positive test classified women with 85.5% accuracy. Limitations of this study include the composite outcome and the broad inclusion criteria of any hypertensive disorder of pregnancy. This broad approach was used to optimize model generalizability. CONCLUSIONS: The miniPIERS model shows reasonable ability to identify women at increased risk of adverse maternal outcomes associated with the hypertensive disorders of pregnancy. It could be used in LMICs to identify women who would benefit most from interventions such as magnesium sulphate, antihypertensives, or transportation to a higher level of care

Predicting Parkinson disease in the community using a nonmotor risk score

At present, there are no validated methods to identify persons who are at increased risk for Parkinson Disease (PD) from the general population. We investigated the clinical usefulness of a recently proposed non-motor risk score for PD (the PREDICT-PD risk score) in the population-based Rotterdam Study. At baseline (1990), we constructed a weighted risk score based on 10 early nonmotor features and risk factors in 6492 persons free of parkinsonism and dementia. We followed these persons for up to 20 years (median 16.1 years) for the onset of PD until 2011. We studied the association between the PREDICT-PD risk score and incident PD using competing risk regression models with adjustment for age and sex. In addition, we assessed whether the PREDICT-PD risk score improved discrimination (C-statistics) and risk classification (net reclassification improvement) of incident PD beyond age and sex. During follow-up, 110 persons were diagnosed with incident PD. The PREDICT-PD risk score was associated with incident PD (hazard ratio [HR] = 1.30; 95 % confidence interval [1.06; 1.59]) and yielded a small, non-significant improvement in overall discrimination (ΔC-statistic = 0.018[−0.005; 0.041]) and risk classification (net reclassification improvement = 0.172[−0.017; 0.360]) of incident PD. In conclusion, the PREDICT-PD risk score only slightly improves long-term prediction of PD in the community

On the combination of omics data for prediction of binary outcomes

Enrichment of predictive models with new biomolecular markers is an important task in high-dimensional omic applications. Increasingly, clinical studies include several sets of such omics markers available for each patient, measuring different levels of biological variation. As a result, one of the main challenges in predictive research is the integration of different sources of omic biomarkers for the prediction of health traits. We review several approaches for the combination of omic markers in the context of binary outcome prediction, all based on double cross-validation and regularized regression models. We evaluate their performance in terms of calibration and discrimination and we compare their performance with respect to single-omic source predictions. We illustrate the methods through the analysis of two real datasets. On the one hand, we consider the combination of two fractions of proteomic mass spectrometry for the calibration of a diagnostic rule for the detection of early-stage breast cancer. On the other hand, we consider transcriptomics and metabolomics as predictors of obesity using data from the Dietary, Lifestyle, and Genetic determinants of Obesity and Metabolic syndrome (DILGOM) study, a population-based cohort, from Finland

Personalized Prediction of Lifetime Benefits with Statin Therapy for Asymptomatic Individuals: A Modeling Study

Background: Physicians need to inform asymptomatic individuals about personalized outcomes of statin therapy for primary prevention of cardiovascular disease (CVD). However, current prediction models focus on short-term outcomes and ignore the competing risk of death due to other causes. We aimed to predict the potential lifetime benefits with statin therapy, taking into account competing risks. Methods and Findings: A microsimulation model based on 5-y follow-up data from the Rotterdam Study, a population-based cohort of individuals aged 55 y and older living in the Ommoord district of Rotterdam, the Netherlands, was used to estimate lifetime outcomes with and without statin therapy. The model was validated in-sample using 10-y follow-up data. We used baseline variables and model output to construct (1) a web-based calculator for gains in total and CVD-free life expectancy and (2) color charts for comparing these gains to the Systematic Coronary Risk Evaluation (SCORE) charts. In 2,428 participants (mean age 67.7 y, 35.5% men), statin therapy increased total life expectancy by 0.3 y (SD 0.2) and CVD-free life expectancy by 0.7 y (SD 0.4). Age, sex, smoking, blood pressure, hypertension, lipids, diabetes, glucose, body mass index, waist-to-hip ratio, and creatinine were included in the calculator. Gains in total and CVD-free life expectancy increased with blood pressure, unfavorable lipid levels, and body mass index after multivariable adjustment. Gains decreased considerably with advancing age, while SCORE 10-y CVD mortality risk increased with age. Twenty-five percent of participants with a low SCORE risk achieved equal or larger gains in CVD-free life expectancy than the median gain in participants with a high SCORE risk. Conclusions: We developed tools to predict personalized increases in total and CVD-free life expectancy with statin therapy. The predicted gains we found are small. If the underlying model is validated in an independent cohort, the tools may be useful in discussing with patients their individual outcomes with statin therapy. Please see later in the article for the Editors' Summar