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PubMed2004

Clinical trial--derived risk model may not generalize to real-world patients with acute coronary syndrome.

BACKGROUND: Accurate risk stratification can guide clinical decision-making in the management of acute coronary syndromes (ACS). However, the applicability of risk models to the general ACS population remains unclear. The purpose of this study was to validate and compare a modified international clinical trial and a registry-based risk model in a contemporary, less selected ACS population. METHODS: In the prospective, observational Canadian ACS Registry, 4627 patients with ACS were enrolled from 51 centers. Baseline patient data were recorded on standardized case report forms. We evaluated risk models derived from the Platelet glycoprotein IIb/IIIa in Unstable angina: Receptor Suppression Using Integrilin Therapy (PURSUIT) and the Global Registry of Acute Cardiac Events (GRACE) predicting in-hospital death among patients with non-ST-elevation ACS. Model discrimination was measured by the c-statistic, and calibration was assessed graphically and by the Hosmer-Lemeshow goodness-of-fit test. RESULTS: In-hospital mortality rates were 2.4% overall and 1.5% among the patients with non-ST-elevation ACS (n = 2925; 63.2%) in our validation cohort. Both the in-hospital PURSUIT and GRACE risk models showed similar and good prognostic discrimination (c-statistics = 0.84 and 0.83, respectively; P = .69 for difference). The GRACE model also demonstrated good calibration (Hosmer-Lemeshow P = .40). In contrast, calibration in the PURSUIT model was poor (Hosmer-Lemeshow P < .001), with consistent overestimation of risks. CONCLUSIONS: Both the PURSUIT and GRACE models demonstrated good discrimination for in-hospital mortality rates in the Canadian ACS Registry. However, the GRACE risk model, derived from a less selected population, provided superior calibration in risk assessment across the spectrum of ACS. Our findings underscore the potential importance of risk model validation in the general ACS population rather than a clinical trial population to establish its generalizability before integration into clinical practice.

Adult↗

PubMed2004

Cardiac surgery risk modeling for mortality: a review of current practice and suggestions for improvement.

Risk models play a vital role in monitoring health care performances. Despite extensive research and widespread use of risk models in cardiac surgery, there are methodologic problems. We reviewed the methodology used for risk models for short-term mortality. The findings suggest that many risk models are developed in an ad hoc manner. Important aspects such as selection of risk factors, handling of missing values, and size of the data used for model development are not dealt with adequately. Methodologic details presented in publications are often sparse and unclear. Model development and validation processes are not always linked to the clinical aim of the model, which may affect their clinical validity. We make some suggestions in this review for improvement in methodology and reporting.

Cardiac Surgical Procedures↗

PubMed2005

Checking a semiparametric additive risk model.

McKeague and Sasieni [A partly parametric additive risk model. Biometrika 81 (1994) 501] propose a restriction of Aalen's additive risk model by the additional hypothesis that some of the covariates have time-independent influence on the intensity of the observed counting process. We introduce goodness-of-fit tests for this semiparametric Aalen model. The asymptotic distribution properties of the test statistics are derived by means of martingale techniques. The tests can be adjusted to detect particular alternatives. As one of the most important alternatives we consider Cox's proportional hazards model. We present simulation studies and an application to a real data set.

Computer Simulation↗

PubMed1988

Indirect corrections for confounding under multiplicative and additive risk models.

We define a multiplicative model and an additive model for the hazards associated jointly with exposure and with the presence of a confounder like smoking. Under the multiplicative model, the crude relative risk may be adjusted indirectly, by means of a factor proposed by Axelson [1978], and implicitly by Cornfield et al. [1959] and Schlesselman [1978]. We present corresponding indirect correction formulas under the additive risk model for the risk difference and for the excess relative risk. Conditions are established under which these corrections may be applied to age-adjusted rates from composite study populations. We demonstrate that indirect corrections may be no better than crude measures of risk if one assumes the wrong model for the joint action of the exposure and confounding factors. These results are illustrated on an example of occupational exposure to vermiculite. The limitations of the techniques are discussed.

Epidemiologic Methods↗

PubMed2002

A process risk model for the shelf life of Atlantic salmon fillets.

The shelf life of Atlantic salmon (Salmo salar) portions produced for retail distribution is examined and the dominant aerobic spoilage organism is identified. Characterization of the harvesting and processing operations allow the development of a stochastic mathematical model, a process risk model (PRM), which predicts the range of the possible shelf life for the portions under normal retail and distribution. The considered risk is the failure to achieve the nominal 'use by' date. Bacterial counts from surface swabs, water, ice, and fish samples, collected over a period of 9 months, are fitted to distribution functions for use within the model. Comparisons are made between the distributions fitted to the observed bacterial levels and the predicted levels for the slurry water, initial surface contamination on the fish, and for the predicted and observed shelf life. Storage temperature of the packaged salmon portions has the greatest influence on shelf life, with contamination from contact surfaces and other sources being the next most important. The range of bacterial counts on the portions was between -0.6 and 5 log10 cfu/cm2. The model predicts bacterial counts in the slurry water to have an average value of 3.36 log10 cfu/ml, whereas the observed slurry water bacterial counts were 3.35 log10 cfu/ml. The predicted average initial bacterial contamination is 3.31 log10 cfu/cm2 on the fish surface and 3.23 log10 cfu/cm2 on the observed. The average predicted shelf life is 6.5 days, compared to an observed value of 6.2 days at 4 degrees C.

Animals↗

PubMed2004

Coronary artery bypass grafting: are risk models developed from on-pump surgery valid for off-pump surgery?

OBJECTIVE: This study was undertaken to test whether risk models developed from on-pump coronary artery bypass grafting are valid for assessing the risk for off-pump coronary artery bypass grafting. METHODS: From January 1997 through June 2002, a total of 12,845 patients underwent isolated coronary artery bypass grafting procedures in Providence Health System hospitals. Of these, 1782 operations (14%) were performed without cardiopulmonary bypass. An operative mortality risk model was derived from on-pump data with logistic regression. This model and two other external risk models developed from on-pump data were then applied to patients undergoing off-pump coronary artery bypass grafting to test the model adequacy. RESULTS: Good model discrimination and calibration were obtained from all three models. CONCLUSION: Operative mortality risk models developed from on-pump coronary artery bypass grafting can be used to assess the risk for off-pump coronary artery bypass grafting.

Aged↗

PubMed1996

Issues and concerns associated with different risk models for eating disorders.

OBJECTIVE: The present paper examines issues and concerns associated with different risk models in identifying individuals who may be vulnerable for eating disorders. METHOD: Studies were located by computerized search and the authors' knowledge of the literature. For the purposes of this paper, different risk models are grouped according to three types of sample selection criteria: exposure to environmental pressures toward thinness, parental psychopathology, and intraindividual characteristics. Intraindividual characteristics were subdivided into biological and behavior vulnerability markers, and within the behavior risk approach, symptom and nonsymptom risk models were further identified. RESULTS: Our literature review indicates that risk research on eating disorders is still in its formative years. More well-planned prospective risk studies are needed. CONCLUSIONS: Among these risk models, the nonsymptom risk approach, which defines risk on the basis of nonsymptom vulnerability markers, represents one of the more promising avenues for future risk research and deserves further exploration.

Anorexia Nervosa↗

PubMed2006

Psychometric evaluation of the Hendrich Fall Risk Model.

AIMS: The aim of this paper is to report a psychometric evaluation of the Hendrich Fall Risk Model. BACKGROUND: Thoroughly developed and tested instruments for assessment of fall risk are needed to identify patients at risk of falling, to enable the implementation of preventative measures. METHOD: Data from 1977 patients/residents in 45 nursing homes and 7197 patients from 47 hospitals were evaluated in a cross-sectional survey. The internal consistency of the Hendrich Fall Risk Model was examined using the Kuder-Richardson Test. The dimensions of the model were revealed by exploratory factor analysis and the Care Dependency Scale was used to investigate construct validity. Using Spearman Rho the sum of weighted items was correlated with the sum of unweighted items to obtain information about the practicability of a weighted total score. The study was carried out in 2003. RESULTS: The internal consistency of the model was not high (alpha = 0.54). Additionally, factor analysis showed that the model had more than one dimension. The correlation between the fall risk model and Care Dependency Scale was quite high for hospital patients and the total group (Spearman Rho = -0.71 or -0.76 respectively, P < 0.01) and medium for nursing home residents (Spearman Rho = -0.51, P < 0.01). The total scores of the weighted and unweighted items correlated highly (Spearman Rho = 0.96, P < 0.01). CONCLUSIONS: The use of this risk model is not recommended for nursing homes. For hospitals, we advise the use of unweighted items.

Accidental Falls↗

PubMed2006

Establishment of risk model for pancreatic cancer in Chinese Han population.

AIM: To investigate risk factors for pancreatic cancer and establish a risk model for Han population. METHODS: This population-based case-control study was carried out from January 2002 to April 2004. One hundred and nineteen pancreatic cancer patients and 238 healthy people completed the questionnaire which was used for risk factor analysis. Logistic regression analysis was used to calculate odds ratio (ORs), 95% confidence intervals (Cls) and beta value, which were further used to establish the risk model. RESULTS: According to the study, people who have smoked more than 17 pack-years had a higher risk to develop pancreatic cancer compared to non-smokers or light smokers (not more than 17 pack-years) (OR 1.98; 95% CI 1.11-3.49, P = 0.017). More importantly, heavy smokers in men had increased risk for developing pancreatic cancer (OR 2.11; 95%CI 1.18-3.78, P = 0.012) than women. Heavy alcohol drinkers (>20 cup-years) had increased risk for pancreatic cancer (OR 3.68; 95%CI 1.60-8.44). Daily diet with high meat intake was also linked to pancreatic cancer. Moreover, 18.5% of the pancreatic cancer patients had diabetes mellitus compared to the control group of 5.8% (P = 0.0003). Typical symptoms of pancreatic cancer were anorexia, upper abdominal pain, bloating, jaundice and weight loss. Each risk factor was assigned a value to represent its importance associated with pancreatic cancer. Subsequently by adding all the points together, a risk scoring model was established with a value higher than 45 as being at risk to develop pancreatic cancer. CONCLUSION: Smoking, drinking, high meat diet and diabetes are major risk factors for pancreatic cancer. A risk model for pancreatic cancer in Chinese Han population has been established with an 88.9% sensitivity and a 97.6% specificity.

Adult↗

PubMed2005

Additive vs. logistic risk models for cardiac surgery mortality.

OBJECTIVE: Logistic regression is most often used to produce a cardiac operative risk model. But the logistic equation requires a computer to solve. Thus, simple additive models have been derived from logistic models by adding the odds ratios or modified coefficients. However, this simplification has no statistical justification, and the additive scores do not equal the original logistic probabilities. METHODS: The EuroSCORE risk model is a very successful and widely used cardiac surgery risk model and it comes in both an additive and a full logistic version. We applied the EuroSCORE model to the 28,337 cardiac surgeries in the Providence Health System Cardiovascular Study Group database. The discrimination of the models was assessed by the c index. The comparison of the mortality predictions of the logistic and the additive model are mostly descriptive and graphical. RESULTS: Theoretical considerations would predict that the additive model greatly underestimates the risk for the higher risk patients, and clinical data confirm this fact. For the 23,463 (83%) cases with complete data, the predicted mortality was 8.3% by the logistic model and 5.4% by the additive model. The discrimination (c index) of the additive (0.794) and logistic (0.791) models was equally good. A modified additive score is proposed (the mean of the logistic predicted mortality for each original additive score) which could be provided as a look-up table along with the scoring sheet. CONCLUSIONS: The additive EuroSCORE gives excellent discrimination, as good as the logistic risk model, but it greatly underestimates the risk of high-risk patients, compared to the logistic. The logistic equation should be used to predicate the mortality when possible. If this is not feasible, a modified additive score could be employed at the bedside. But the logistic should always be used for comparison of providers and for research publications.

Cardiac Surgical Procedures↗

PubMed2026

Risk Prognostication After Hypomethylating Agents Combined With Venetoclax in AML: The PRISM Risk Model.

PURPOSE: As risk stratification for patients with AML treated with lower-intensity venetoclax-based therapy remains suboptimal, we developed and validated a prognostic model integrating clinical, cytogenetic, and molecular features. METHODS: We assembled a multinational data set comprising 2,092 adults with newly diagnosed AML treated with hypomethylating agents plus venetoclax (HMA + VEN). One thousand nine hundred eighteen patients with complete data were randomly divided into training (70%) and internal validation (30%) cohorts. Two independent external validation cohorts were assembled (n = 500 and n = 222). Modeling overall survival (OS), Elastic Net regression was applied in 1,000 bootstrap samples from the training cohort to select variables for a Ridge regression, which generated a continuous Prognostic Risk Integration for Survival Modeling (PRISM) score and risk categories based on tertiles (PRISM-3: low, moderate, high). These PRISM indices were then computed for the validation cohorts and compared with the 4-gene classifier (based on mutations in FLT3-ITD, N/KRAS, and TP53). RESULTS: PRISM integrated 17 clinical and genomic variables and demonstrated a linear association with OS. PRISM-3 stratified survival consistently across all cohorts (median OS: 25.1-28.8 months for low risk, 12.5-14.7 months for moderate risk, and 5.8-6.7 months for high risk; P < .001). Compared with the 4-gene classifier, PRISM-3 reassigned approximately 40% of patients (and >50% of those with favorable risk) and demonstrated significantly better discrimination in validation cohorts (C-index 0.63-0.65 v 0.59-0.61; P < .05). CONCLUSION: PRISM is a validated prognostic model for patients with AML receiving HMA + VEN that improves survival risk stratification beyond current standard tools and supports individualized, risk-adapted clinical decision making. The model, the PRISM-AML Risk Calculator, is publicly available.

Humans↗

PubMed2006

Development of a contemporary bleeding risk model for elderly warfarin recipients.

BACKGROUND AND PURPOSE: Develop and validate a contemporary bleeding risk model to guide the clinical use of warfarin in the elderly atrial fibrillation (AF) population. METHODS: Chart-abstracted data from the National Registry of Atrial Fibrillation was combined with Medicare part A claims to identify major bleeding events requiring hospitalization. Using a split-sample technique, candidate variables that provided statistically stable relationships with major bleeding events were selected for model development. Three risk categories were created and validated. The new model was compared to existing bleeding risk models using c-statistics and Kaplan-Meier curves. RESULTS: Model development and validation was conducted on 26,345 AF patients who were > 65 years of age and had been discharged from the hospital while receiving warfarin therapy. The following eight variables were included in the final risk score model: age > or = 70 years; gender; remote bleeding; recent (ie, during index hospitalization) bleeding; alcohol/drug abuse; diabetes; anemia; and antiplatelet use. Bleeding rates were 0.9%, 2.0%, and 5.4%, respectively, for the groups with low, moderate, and high risk, compared to the bleeding rates for groups with moderate risk (1.5% and 1.0%) and high risk (1.8% and 2.5%) from other models. CONCLUSIONS: Using a nationally derived data set, we developed a model based on contemporary practice standards for determining major bleeding risk among AF patients receiving warfarin therapy. The larger sample size afforded the opportunity to incorporate additional risk factors. In addition, since the majority of our population was > 65 years of age, we had greater ability to stratify risk among the elderly.

Age Factors↗

PubMed2002

Effects of sirolimus on lipids in renal allograft recipients: an analysis using the Framingham risk model.

This report describes the effects of sirolimus on plasma lipids, and uses the Framingham risk model to assess the clinical importance of these effects. Lipid data from two large controlled studies of 1295 renal transplant patients were analyzed retrospectively. Sirolimus 2 mg/day and 5 mg/day were compared with placebo or azathioprine, and administered concomitantly with steroids and cyclosporine over 12 months. Hypercholesterolemia and hypertriglyceridemia occurred in all treatment groups and were maximal at 2-3 months. The sirolimus groups evidenced higher lipid levels than the controls, but the elevations diminished over time. At 1 year, the patients given sirolimus 2 mg/day had a mean cholesterol level 17 mg/dL greater and a mean triglyceride level 59 mg/dL greater than the controls. Among the patients given sirolimus 5 mg/day, mean cholesterol was 30 mg/dL greater and mean triglycerides were 103 mg/dL greater than the controls. Treatment with statins and fibrates was effective in reducing cholesterol and triglyceride levels, respectively, in the sirolimus-treated patients. The Framingham risk model predicted that the 17 mg/dL elevation in cholesterol would increase the incidence of coronary heart disease (CHD) by 1.5 new cases per 1000 persons per year and CHD death by 0.7 events per 1000 persons per year. Lipid elevations observed in the sirolimus-treated patients were manageable, improved over time, and responded to lipid-lowering therapy. Based on the Framingham risk model, the CHD risks associated with these cholesterol elevations are small compared with the baseline risks of the transplant population.

Cholesterol↗

PubMed2002

Assessing the accuracy of three viral risk models in predicting the outcome of implementing HIV and HCV NAT donor screening in Australia and the implications for future HBV NAT.

BACKGROUND: Risk modeling is now the most practical method of estimating the residual risk of viral transmission in developed countries. One method of assessing the accuracy of a risk model is to measure the observed against the predicted outcome after implementing a new screening method. The primary objective of this paper is to assess the accuracy of three published models in predicting the impact of implementing HIV and HCV NAT in Australia. STUDY DESIGN AND METHODS: Viral screening data on Australian donors for 2000 and 2001 were retrospectively analyzed. The data were applied to the three models to estimate the risk of transmission and predicted NAT yield for HIV, HCV, and HBV. RESULTS: The median risk estimates for the three models were 1 in 3,415,000 for HIV NAT, 1 in 911,000 for HCV NAT, and 1 in 483,000 for HBsAg. The predicted NAT yield for the three models ranged from 0.17 to 0.30 per million donations for HIV, 1.20 to 5.55 for HCV, and 0.47 to 1.01 for HBV. The observed NAT yield was not significantly different from the expected yield with any of the three models for either HIV or HCV. CONCLUSIONS: First, the residual risk in Australian donors is small in comparison with other transfusion complications and comparable to or lower than the risk in US and European nonremunerated donors. Second, mathematical risk modeling has sufficient precision to be used as a predictive tool for risk-benefit assessments of novel screening procedures. Finally, in relation to the case for implementing HBV NAT and/or anti-HBc in Australia, we conclude that at present, there is inadequate information about our donor population to perform an evidence-based risk-benefit analysis.

Adult↗

PubMed1998

1995 coronary artery bypass risk model: The Society of Thoracic Surgeons Adult Cardiac National Database.

BACKGROUND: The Society of Thoracic Surgeons (STS) Adult Cardiac National Database has recently completed the development of the 1995 risk model to be used to estimate the risk of operative death for isolated coronary artery bypass graft (CABG) procedures. This article describes the detailed methodology used, as well as a new Expert Advisory Panel review mechanism that was initiated by The Society. METHODS: Placing emphasis on clinical relevance, data quality, data completeness, and univariate analyses, a logistic regression analysis was used to develop the 1995 CABG-only risk model. The STS National Office invited an Expert Advisory Panel (composed of nationally recognized, independent biostatisticians) to review the modeling process used. RESULTS: The 1995 CABG-only model details are reported. Standard performance measures indicated the model had high predictive power and an acceptable level of calibration. The Expert Advisory Panel reviewed the 1995 CABG model and concluded that the current modeling techniques were adequate. Suggestions for future model development and reporting were proposed by the Panel. CONCLUSIONS: The most current STS risk model of CABG operative mortality is a reliable and statistically valid tool. Its development and performance have been critically examined and approved by an independent panel of experts.

Coronary Artery Bypass↗

PubMed2002

A risk model for the prediction of recurrent falls in community-dwelling elderly: a prospective cohort study.

The object of this article was to determine the predictive value of risk factors for recurrent falls and the construction of a fall risk model as a contribution to a mobility assessment for the identification of community-dwelling elderly at risk for recurrent falling in general practice. The design was a prospective cohort study (n = 311). There were four primary health care centers. A sample stratified on previous falls, age, and gender of community-dwelling elderly persons aged 70 years or over (n = 311) was taken from the respondents to a mail questionnaire (n = 1660). They were visited at home to assess physical and mental health, balance and gait, mobility and strength. A 36-week follow-up with telephone calls every 6 weeks was conducted. Falls and fall injuries were measured. During follow-up 197 falls were reported by 33% of the participants: one fall by 17% and two or more falls by 16%. Injury due to a fall was reported by 45% of the fallers: 2% hip fractures, 4% other fractures, and 39% minor injuries. A fall risk model for the prediction of recurrent falls with an area under the curve (AUC) of 0.79, based on logistic regression analysis, showed that the main determinants for recurrent falls were: an abnormal postural sway (OR 3.9; 95% Cl 1.3-12.1), two or more falls in the previous year (OR 3.1; 95% Cl 1.5-6.7), low scores for hand grip strength (OR 3.1; 95% Cl 1.5-6.6), and a depressive state of mind (OR 2.2; 95% CI 1.1-4.5). To facilitate the use of the model for clinical practice, the model was converted to a "desk model" with three risk categories: low risk (0-1 predictor), moderate risk (two predictors), and high risk (> or =3 predictors). A fall risk model converted to a "desk model," consisting of the predictors postural sway, fall history, hand dynamometry, and depression, provides added value in the identification of community-dwelling elderly at risk for recurrent falling and facilitates the prediction of recurrent falls.

Accidental Falls↗

PubMed2000

Risk models in genetic epidemiology.

Advances in the identification and treatment of genetically transmitted diseases have lead to an increased need for reliable estimates of genetic susceptibility risk. These estimates are used in clinic settings to identify individuals at increased risk of being a carrier of a disease susceptibility allele as well as to define the probability of developing a particular disease given one is a carrier. Accurate assessment of these probabilities is extremely important given the implications for medical decision making including the identification of patients who might benefit from genetic counselling or from entry into clinical trials. A wide range of risk models has been proposed including those that utilize logistic regression, Cox proportional hazards regression, log-incidence models, and Bayesian modelling. The specific data used to create the various risk models varies by disease and may include molecular, epidemiologic, and clinical information although, in general, family history remains the primary variable of interest, particularly for those diseases for which a susceptibility allele(s) has yet to be identified. When permitted by sample size, researchers also attempt to measure the effect of any gene-environment interaction. In this paper we give an overview of the various definitions of risk as well as several of the more frequently used methods of risk estimation in genetic epidemiology at present. In addition, the means by which different methods are able to provide a measure of error or uncertainty associated with a given risk estimate will be discussed. Applications to risk modelling for breast cancer are given the disease for which risk assessment has probably been most extensively defined.

Breast Neoplasms↗

PubMed1999

The 1996 coronary artery bypass risk model: the Society of Thoracic Surgeons Adult Cardiac National Database.

BACKGROUND: The Society of Thoracic Surgeons Adult Cardiac National Database has recently completed the update for the 1996 risk model to be used to estimate the risk of operative death for isolated coronary artery bypass graft (CABG) procedures. METHODS: We placed emphasis on clinical relevance, data quality, data completeness, and univariate analyses. A logistic regression approach was used to develop the 1996 CABG-only risk model. RESULTS: Odds ratios for the factors with highest risk are multiple reoperations (OR = 4.3), emergent salvage status (OR = 3.7), and first reoperation (OR = 2.7). Standard performance measures indicated the model had high predictive power and an acceptable level of calibration after adjustment for a large sample size effect. CONCLUSION: The most current STS risk model of CABG operative mortality is a reliable and statistically valid tool. The 1996 CABG-only model has been approved for use by The Society of Thoracic Surgeons.

Adult↗