Highest Risk Quintile Research Articles

Abstract WMP88: Comparing Behavioral Principles in Mailed Messages to Activate Patients at High Risk for Stroke

Objectives: To compare the effect of behaviorally-tailored mailed messages on patient activation to reduce stroke risk. Methods: We used EHR data to construct Framingham Stroke Risk Scores (FSRS) in primary care patients in one VA and one non-VA urban healthcare system. Patients in the highest risk quintile were eligible. We recruited 15 subjects to develop four stroke risk messages: standard, incentive ($5 gift card), salience, and incentive plus salience. Patients were randomly assigned to receive one of the messages. All letters asked the patient to call a stroke prevention coordinator. Response to the messages (calling the prevention coordinator) was modeled separately in the two healthcare system cohorts using logistic regression. Results: From 6,695 eligibles, 1,759 Veterans (mean age 75.6, 99% male, 61% White, mean FSRS 18.6) and 2,084 non-Veterans (mean age 65.6, 36% male, 68% Black, mean FSRS 13.1) received a letter. Overall call response rate was 23% among Veterans and 13% among non-Veterans. Both cohorts were significantly more likely to respond to the incentive and to the incentive plus salience message compared to the standard message (Table). Older age (for Veterans) and Black race (for non-Veterans) were also significantly associated with response, but FSRS and medical comorbidity were not. Among 631 subjects calling the stroke prevention coordinator, 26% (100/390) of Veterans and 30% (73/241) of non-Veterans were unaware of their risk factors. Conclusions: A mailed letter including a small monetary incentive may be more effective than standard or salience-related messages in engaging high-risk patients with their health care system. Many patients are unaware of their stroke risk. Future analyses will examine the relationship between messages and primary care follow-up.

160: Predicting risk of blood transfusion during delivery

Postpartum hemorrhage requiring blood transfusion has nearly doubled from 2004 to 2012 in the United States. Our objective is to develop a model that will help predict the risk of blood transfusion using information available prior to delivery. Using the Consortium on Safe Labor data registry from NICHD, we included all women who had a delivery from 2002 to 2008. If they had more than one delivery in the time period studied, only the first delivery was included. Women with placental abruption or accreta were excluded as these are obvious risk factors. Pre-delivery variables that had associations with transfusion (with p<0.10) were included in a multivariable logistic regression model predicting transfusion. The model was then optimized using stepwise logistic regression. We validated the prediction model by using it in a separate sample of second deliveries from the same women. There were 156,833 deliveries for analysis in the model development sample, with 5479 deliveries (3.5%) requiring transfusion. In deliveries with transfusion, mothers were older, more often White, had lower BMI, and had a number of comorbidities. Transfusion was least likely to occur in university teaching hospitals. A variety of pre-delivery predictors were independently associated with transfusion risk (Table 1). Mothers in the lowest quintile of risk scores had 1.2% incidence of transfusion, while mothers in the highest risk quintile had incidence of 7.8% (p<.0001). The area under the curve or c statistic was 0.71 for the final prediction model. Hypothetical patient situations were created and the model was applied (Table 2). There were 15,967 second births that were used as a validation sample. The Pearson correlation for the parameter estimates between the original and the validation samples was 0.81, indicating strong validation of the model. Our model identified independent risk factors that can help predict risk of transfusion prior to delivery when obvious risk factors such as placenta accreta and abruption are not included. This model can assist health care professionals in counseling patients and preparing facilities/resources to reduce maternal morbidity.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

How Widespread and Predictable Is Stock Broker Misconduct?

We reconcile widely diverging recent estimates of broker misconduct. Qureshi and Sokobin [2015] reported that 1.3% of a sample of current and former brokers was associated with awards or settlements in excess of a threshold amount. Egan, Matvos, and Seru [2016] found that 7.8% of all current and former brokers have financial misconduct disclosures, including customer complaints, awards, and settlements. Applying Qureshi and Sokobin’s restrictive definition of potential misconduct to all brokers, we find that 2.3% of all current and former brokers have been associated with awards or settlements in excess of a threshold amount. Qureshi and Sokobin found that the top quintile of brokers sorted by estimated likelihood of being the subject of a customer complaint contains 55% of the brokers subsequently subject to complaints. We demonstrate that more sophisticated data mining techniques can sort brokers so that the highest risk quintile contains 75% of the brokers subsequently subject to customer complaints. We evaluate Qureshi and Sokobin’s claim that BrokerCheck provides helpful information to investors seeking to avoid bad brokers and answer the question posed by Egan, Matvos, and Seru: If BrokerCheck data can predict broker misconduct, why do investors not use those data to protect themselves? We find that BrokerCheck is nearly worthless in its current form but could easily be modified so that investors could protect themselves and market forces would substantially reduce broker misconduct.

Abstract 137: Clinical Outcomes After Cardiac Stress Testing Among U.S. Patients Younger Than 65, 2006-2012

Background: Recent studies of national practice patterns suggest that there is inconsistency in the appropriateness of referrals for cardiac stress testing. However, little is known about the prevalence of relevant clinical outcomes such as coronary revascularization or acute myocardial infarction (AMI) after stress testing. Methods: Using administrative claims from a large national private insurer, we conducted an observational cohort study of patients aged 25-64 who underwent de novo stress testing from 2006-2012. We excluded patients with a prior diagnosis of coronary artery disease, heart failure, or stroke. We calculated rates of AMI and coronary angiography with or without revascularization in the year following stress testing. We estimated logistic regression models that included demographic characteristics (age, sex, and race) and relevant comorbidities (diabetes, hypertension, and dyslipidemia). Finally, we stratified the cohort into quintiles based on their risk of having an AMI or revascularization event in order to describe the characteristics of patients at lowest and highest risk. Results: We identified 564,313 patients (mean age 50, 49% women, 73% white) who underwent stress testing during the study period. Among these patients, 15% had diabetes, 37% had hypertension, and 42% had dyslipidemia. Within one year, 2.5% of the cohort underwent coronary revascularization or were hospitalized for AMI, and 2.7% underwent coronary angiography without revascularization. In the risk-stratified analysis, 0.5% of patients in the lowest risk quintile had an AMI or revascularization event, compared to 6.2% in the highest risk quintile (p&lt;.001). Compared to the highest risk quintile, patients in the lowest risk quintile were younger (mean age 40 versus 58 years; p&lt;.001), more likely to be female (85% versus 0%; p&lt;.001), more likely to be non-white (36% versus 16%; p&lt;.001), and less likely to have comorbidities (Table). Conclusion: The percentage of commercially insured U.S. patients who had an AMI or revascularization event within 1 year of stress testing was small. In the lowest risk quintile, the a priori prevalence of coronary disease risk factors was low, and the rates of subsequent AMI and revascularization was extremely low, raising questions about the value of stress testing in this subgroup.

SC18.05 UK Lung Screening Trial Cost Effectiveness and Current Planning Status of International Lung Cancer Screening Programs

The pilot UKLS lung cancer RCT screening trial recruited 4,000 individuals [1], using the LLPv2 risk model (5% risk over 5 years) [2]. The lessons learnt from the UKLS CT pilot screening trial are:•UKLS – A Population based trial – all IMD’s (socioeconomic groups) included [1].•Risk Stratification (LLPv2 5 % risk over 5 years) [2].•Volumetric assessment of CT detected nodules [3].•Care Pathway – Management pathway implemented [3].•Early Stage Disease (Stage 1 68%: Stage I&II 86%) [4].•High Proportion suitable for Surgery (83%) [4].•1.7% lung cancers identified at baseline scan [1].•Benign Resection rate – 10.3% (NLST 27%)[1].•Psychological impact – transient not significant [5, 6].•Cost effectiveness modelling within NICE parameters [1]. The cost effectiveness of the UKLS trial has been modelled and compared with that of the US National Lung Screening Trial (NLST), which has published an estimate of $81,000 per quality-adjusted life-year (QALY) as its mean incremental cost-effectiveness ratio (ICER) [7]. All UKLS cost estimates were based on 2011-12 NHS tariffs (Costs provided in $: £1=$1.5 on 30-11-15). Owing to the brief duration of the trial, observations relevant to economic evaluation were limited to cost-incurring events associated with screening and the initial management of screen-detected cancers. Expected outcomes of the cancers detected were simulated on the basis of both life tables and published survival data from other studies. The costs incurred from UKLS are those of baseline and repeat screens ($424,072), diagnostic workup ($113,478), and treatment ($449,243), which totaled $1,036794 (95% CI, $719,332 to $1,350,766). Recruitment costs ($15) per person for invitation and selection) were modelled from the UK colorectal screening program and we assumed a participation rate of 30% of those invited. The gross current costs of the program amounted to $1,133,217 (CI $817,887 to $1,450,610). Summary of findings: The ICER of screen-detection compared with symptomatic detection was estimated at $9495 per life-year gained. Using data from previous studies, we associated quality of life weights with the estimated survival gains, enabling us to report outcomes as QALYs. On this basis, the ICER equaled $12,709 per QALY gained (CI $ 8280 to $18966). The difference in cost effectiveness between NLST and UKLS as suggested by the estimated ICERs is more apparent than real. Most of the discrepancy can be explained by differences between settings in (i) local unit costs, (ii) intensity of resource use, (iii) number of screening rounds and (iv) disease prevalence in the target population. Thus, UKLS selected high-risk subjects only whereas NLST screened a general population, yet the latter reported an ICER as low as $32,000 for its highest-risk quintile. Expected QALY gains from screen-detection were similar in both trials. CT-Screening, cost-effectiveness, CT-implementation

Predicting 5-Year Risk of RRT in Stage 3 or 4 CKD: Development and External Validation.

Only a minority of patients with CKD progress to renal failure. Despite the potential benefits of risk stratification in the CKD population, risk prediction models are not routinely used. Our objective was to develop and externally validate a clinically useful and pragmatic prediction model for the 5-year risk of progression to RRT in stage 3 or 4 CKD. We used a retrospective cohort design. The development cohort consisted of 22,460 Kaiser Permanente Northwest members with stage 3 or 4 CKD (baseline 2002-2008). The validation cohort consisted of 16,553 Kaiser Permanente Colorado members with stage 3-4 CKD (baseline 2006-2008). The final model included eight predictors: age, sex, eGFR, hemoglobin, proteinuria/albuminuria, systolic BP, antihypertensive medication use, and diabetes and its complications. In the Northwest and Colorado cohorts, there were 737 and 360 events, and observed 5-year Kaplan-Meier risks of 4.72% (95% confidence interval [95% CI], 4.38 to 5.06) and 2.57% (95% CI, 2.30 to 2.83), respectively. Our prediction model performed extremely well in the development cohort, with a c-statistic of 0.96, an R2 of 79.7%, and good calibration. We had similarly good performance in the external validation cohort, with a c-statistic of 0.95, R2 of 81.2%, and good calibration. In the external validation cohort, the observed risk was slightly lower than the predicted risk in the highest-risk quintile. Using the top quintile of predicted risk as a cutpoint gave a sensitivity of 92.2%. We developed a pragmatic prediction model and risk score for predicting the 5-year RRT risk in stage 3 and 4 CKD. This model uses variables that are typically available in routine primary care settings, and can be used to help guide important decisions such as timing of referral to nephrology and fistula placement.

Arrival by ambulance explains variation in mortality by time of admission: retrospective study of admissions to hospital following emergency department attendance in England

BackgroundStudies finding higher mortality rates for patients admitted to hospital at weekends rely on routine administrative data to adjust for risk of death, but these data may not adequately capture...

Multistate Model to Predict Heart Failure Hospitalizations and All-Cause Mortality in Outpatients With Heart Failure With Reduced Ejection Fraction: Model Derivation and External Validation.

Outpatients with heart failure (HF) who are at high risk for HF hospitalization and death may benefit from early identification. We sought to develop and externally validate a model to predict both HF hospitalization and mortality that accounts for the semicompeting nature of the 2 outcomes and captures the risk associated with the transition from the stable outpatient state to the post-HF hospitalization state. A multistate model to predict HF hospitalization and all-cause mortality was derived using data (n=3834) from the HEAAL study (Heart Failure Endpoint evaluation of Angiotensin II Antagonist Losartan), a multinational randomized trial in symptomatic patients with reduced left ventricular ejection fraction. Twelve easily and reliably obtainable demographic and clinical predictors were prespecified for model inclusion. Model performance was assessed in the SCD-HeFT cohort (Sudden Cardiac Death in Heart Failure Trial; n=2521). At 1 year, the probability of being alive without HF hospitalization was 94% for a typical patient in the lowest risk quintile and 77% for a typical patient in the highest risk quintile and this variability in risk continued through 7 years of follow-up. The model c-index was 0.72 in the derivation cohort, 0.66 in the validation cohort, and 0.69 in the implantable cardiac defibrillator arm of the validation cohort. There was excellent calibration across quintiles of predicted risk. Our findings illustrate the advantages of a multistate modeling approach, providing estimates of HF hospitalization and death in the same model, comparison of predictors for the different outcomes and demonstrating the different trajectories of patients based on baseline characteristics and intermediary events. URL: http://www.clinicaltrials.gov. Unique identifiers: NCT00000609 and NCT00090259.

Abstract 3458: UK lung cancer screening trial (UKLS) cost effectiveness: similarities with the NLST high-risk quintiles

Abstract Introduction: The pilot UK lung cancer RCT screening trial recruited around 4,000 individuals, using the LLPv2 risk model (5% risk over 5 years). The cost effectiveness of the UKLS trial has been modelled and compared with that of the US National Lung Screening Trial (NLST), which has published an estimate of $81,000 per quality-adjusted life-year (QALY) as its mean incremental cost-effectiveness ratio (ICER). Methodology: All UKLS cost estimates were based on 2011-12 NHS tariffs (Costs provided in $: £1 = $1.5 on 30-11-15). Owing to the brief duration of the trial, observations relevant to economic evaluation were limited to cost-incurring events associated with screening and the initial management of screen-detected cancers. Expected outcomes of the cancers detected were simulated on the basis of both life tables and published survival data from other studies. The costs incurred from UKLS are those of baseline and repeat screens ($424,072), diagnostic workup ($113,478), and treatment ($449,243), which totalled $1,036794 (95% CI, $719,332 to $1,350,766). Recruitment costs ($15) per person for invitation and selection) were modelled from the UK colorectal screening programme and we assumed a participation rate of 30% of those invited. The gross current costs of the programme amounted to $1,133,217 (CI $817,887 to $1,450,610). Summary of findings: The ICER of screen-detection compared with symptomatic detection was estimated at $9495 per life-year gained. Using data from previous studies, we associated quality of life weights with the estimated survival gains, enabling us to report outcomes as QALYs. On this basis, the ICER equalled $12,709 per QALY gained (CI $ 8280 to $18966). The difference in cost effectiveness between NLST and UKLS as suggested by the estimated ICERs is more apparent than real. Most of the discrepancy can be explained by differences between settings in (i) local unit costs, (ii) intensity of resource use, (iii) number of screening rounds and (iv) disease prevalence in the target population. Thus, UKLS selected high-risk subjects only whereas NLST screened a general population, yet the latter reported an ICER as low as $32,000 for its highest-risk quintile. Expected QALY gains from screen-detection were similar in both trials. Conclusion: Other things remaining equal, ICERs will be higher in programmes where (i) unit costs of detection and management are higher, (ii) lower-risk subjects are invited to be screened, (iii) screens are repeated at frequent intervals. The convention for cost effectiveness acceptability in the UK is $30,000-45,000 per QALY gained, and we conclude that a lung cancer screening programme based on the UKLS protocol would be likely to offer acceptable value for money to the NHS. Citation Format: David Whynes, Stephen W. Duffy, David R. Baldwin, Anand Devaraj, John K. Field. UK lung cancer screening trial (UKLS) cost effectiveness: similarities with the NLST high-risk quintiles. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 3458.

How Widespread and Predictable is Stock Broker Misconduct?

In this paper we reconcile widely diverging recent estimates of broker misconduct. Qureshi and Sokobin report that 1.3% of current and past brokers are associated with awards or settlements in excess of a threshold amount. Egan, Matvos, and Seru find that 7.8% of current and former brokers have financial misconduct disclosures including customer complaints, awards, and settlements. Qureshi and Sokobin arrive at their low estimate by excluding 85% of all brokers, including those brokers most likely to have engaged in misconduct. Applying Qureshi and Sokobins restrictive definition of potential misconduct to all brokers, we find that misconduct is much more widespread.Qureshi and Sokobin find that the top quintile of brokers sorted by estimated likelihood of being subject of a customer complaint contains 55% of the brokers subsequently subject to complaints. We demonstrate that more sophisticated data mining techniques can sort brokers so that the highest risk quintile contains 75% of the brokers subsequently subject to complaints.We also evaluate Qureshi and Sokobin's claim that FINRA's BrokerCheck website provides helpful information to investors seeking to avoid bad brokers and answer the question posed by Egan, Matvos, and Seru: If BrokerCheck data can predict broker misconduct, why don't investors use that data to protect themselves? We find that BrokerCheck is worthless in its current hobbled form, but could easily be modified so that investors could protect themselves and market forces would substantially reduce broker misconduct.

Comparing LCZ696 With Enalapril According to Baseline Risk Using the MAGGIC and EMPHASIS-HF Risk Scores: An Analysis of Mortality and Morbidity in PARADIGM-HF

BackgroundAlthough most patients in the PARADIGM-HF (Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure) trial had mild symptoms, there is a poor correlation between reported functional limitation and prognosis in heart failure. ObjectivesThe aim of this study was to examine the spectrum of risk in PARADIGM-HF and the effect of LCZ696 across that spectrum. MethodsThis study analyzed rates of the primary composite outcome of cardiovascular death or heart failure hospitalization, its components, and all-cause mortality using the MAGGIC (Meta-Analysis Global Group in Chronic Heart Failure) and EMPHASIS-HF (Eplerenone in Mild Patients Hospitalization and Survival Study in Heart Failure) risk scores to categorize patients. The authors determined whether risk, on the basis of these scores, modified the treatment effect of LCZ696. ResultsThe complete MAGGIC risk score was available for 8,375 of the 8,399 patients in PARADIGM-HF. The median MAGGIC score was 20 (IQR: 16 to 24). An increase of 1 point was associated with a 6% increased risk for the primary endpoint (p < 0.001) and a 7% increased risk for cardiovascular death (p < 0.001). The benefit of LCZ696 over enalapril for the primary endpoint was similar across the spectrum of risk (p = 0.159). Treating 100 patients for 2 years with LCZ696 instead of enalapril led to 7 fewer patients in the highest quintile of risk experiencing primary outcomes, compared with 3 in the lowest quintile. Analyses using the EMPHASIS-HF risk score gave similar findings. ConclusionsAlthough most PARADIGM-HF patients had mild symptoms, many were at high risk for adverse outcomes and obtained a large absolute benefit from LCZ696, compared with enalapril, over a relatively short treatment period. LCZ696’s benefit was consistent across the spectrum of risk. (PARADIGM-HF trial [Prospective Comparison of ARNI With ACEI to Determine Impact on Global Mortality and Morbidity in Heart Failure]; NCT01035255)

Comparing Preoperative Targets to Failure-to-Rescue for Surgical Mortality Improvement

Failure-to-rescue (FTR or death after postoperative complication) is thought to explain surgical mortality excesses across hospitals, and FTR is an emerging performance measure and target for quality improvement. We compared the FTR population to preoperatively identifiable subpopulations for their potential to close the mortality gap between lowest- and highest-mortality hospitals. Patients undergoing small bowel resection, pancreatectomy, colorectal resection, open abdominal aortic aneurysm repair, lower extremity arterial bypass, and nephrectomy were identified in the 2007 to 2011 Nationwide Inpatient Sample. Lowest- and highest-mortality hospitals were defined using risk- and reliability-adjusted mortality quintiles. Five target subpopulations were established a priori: the FTR population, predicted high-mortality risk (predicted highest-risk quintile), emergency surgery, elderly (>75 years old), and diabetic patients. Across the lowest mortality quintile (n=282 hospitals, 56,893 patients) and highest-mortality quintile (282 hospitals, 45,784 patients), respectively, the size of target subpopulations varied only for the FTR population (20.2% vs 22.4%, p=0.002) but not for other subpopulations. Variation in mortality rates across lowest- and highest-mortality hospitals was greatest for the high-mortality risk (7.5% vs 20.2%, p<0.0001) and FTR subpopulations (7.8% vs 18.9%, p<0.0001). The FTR and high-risk populations had comparable sensitivity (81% and 75%) and positive predictive value (19% and 20%, respectively) for mortality. In Monte Carlo simulations, the mortality gap between the lowest- and highest-mortality hospitals was reduced by nearly 75% when targeting the FTR population or the high-risk population, 78% for the emergency surgery population, but less for elderly (51%) and diabetic (17%) populations. Preoperatively identifiable patients with high estimated mortality risk may be preferable to the FTR population as a target for surgical mortality reduction.

Cumulative effects of common genetic variants on risk of sudden cardiac death

BackgroundGenome-wide association studies and candidate-gene based approaches have identified multiple common variants associated with increased risk of sudden cardiac death (SCD). However, the independent contribution of these individual loci to disease risk is modest. ObjectiveTo investigate the cumulative effects of genetic variants previously associated with SCD risk. MethodsA total of 966 SCD cases from the Oregon-Sudden Unexpected Death Study and 1926 coronary artery disease controls from the Wellcome Trust Case–Control Consortium were investigated. We generated genetic risk scores (GRSs) for each trait composed of variants previously associated with SCD or with abnormalities in specific electrocardiographic traits such as QRS duration, QTc interval and heart rate. GRSs were calculated using a weighted approach based on the number of risk alleles weighted by the beta coefficients derived from the original studies. We also compared the highest and lowest quintiles for the GRS composed of SCD SNPs. ResultsIncreased cumulative risk was observed for a GRS composed of 14 SCD-SNPs (OR=1.17 [1.05–1.29], P=0.002). The risk for SCD was 1.5 fold greater in the highest risk quintile when compared to the lowest risk quintile (OR=1.46 [1.11–1.92]). We did not observe significant associations with SCD for SNPs that determine electrocardiographic traits. ConclusionsA modest but significant effect on SCD risk was identified for a GRS composed of 14 previously associated SCD SNPs. While next generation sequencing methodology will continue to identify additional novel variants, these findings represent proof of concept for the additive effects of gene variants on SCD risk.

Identification of patients with postoperative complications who are at risk for failure to rescue.

A minority of patients who experience postoperative complications die (failure to rescue). Understanding the preoperative factors that lead to failure to rescue helps surgeons predict and avoid operative mortality. To provide a mechanism for identifying a high-risk group of patients with postoperative complications who are at a substantially increased risk for failure to rescue. Observational study evaluating failure to rescue in patients entered into the American College of Surgeons National Surgical Quality Improvement Program database. The large sample of surgical patients included in this study underwent a wide range of operations during a 5-year period in more than 200 acute care hospitals. We examined and identified patients at high risk for failure to rescue using propensity stratification. We also developed a risk-scoring system that allowed preoperative identification of patients at the highest risk for failure to rescue. Risk-scoring system that predicts failure to rescue. Of the 1,956,002 database patients, there were 207,236 patients who developed serious postoperative complications. Deaths occurred in 21,731 patients with serious complications (10.5% failure to rescue). Stratification of patients into quintiles, according to their propensity for developing serious complications, found that 90% of operative deaths occurred in the highest-risk quintile, usually within a week of developing the initial complication. A risk-scoring system for failure to rescue, based on regression-derived variable odds ratios, predicted patients in the highest-risk quintile with good predictive accuracy. Only 31.8% of failure-to-rescue patients had a single postoperative complication. Perioperative deaths increased exponentially as the number of complications per patient increased. Patients with complications who had surgical residents involved in their care had reduced rates of failure to rescue compared with patients without resident involvement. Twenty percent of high-risk patients account for 90% of failure to rescue (Pareto principle). More than two-thirds of patients with failure to rescue have multiple complications. On average, a few days elapse before death following a complication. A risk-scoring system based on preoperative variables predicts patients in the highest-risk category of failure to rescue with good accuracy. In high-risk patients who develop complications, our results suggest that early intervention, preferably in a high-level intensive care facility with a surgical training program, offers the best chance to reduce failure-to-rescue rates.

Ischemic electrocardiographic abnormalities and prognosis in decompensated heart failure.

Identification of coronary ischemia may enable targeted diagnostic and therapeutic strategies for acute heart failure. We determined the risk of 30-day mortality associated with ischemic ECG abnormalities in patients with acute heart failure. Among 8772 patients (53.4% women, median 78 years [Q1, Q3: 68,84]) presenting with acute heart failure to 86 hospital emergency departments in Ontario, Canada, Q-waves, T-wave inversion, or ST-depression were present in 51.8% of subjects. However, presence of ST-depression was the only finding associated with 30-day mortality with adjusted odds ratio 1.24 (95% confidence interval [CI], 1.02-1.50). Using continuous net reclassification improvement, addition of ST-depression to the Emergency Heart failure Mortality Risk Grade model reclassified 16.9% of patients overall, and 29.3% of those with a history of ischemic heart disease (both P<0.001). By adding ST-depression to the model, the Emergency Heart failure Mortality Risk Grade was extended to predict 30-day death with high discrimination (c-statistic 0.801), with 0.57% mortality rate in the lowest risk decile. Adjusted odds ratios for 30-day mortality were 2.81 (95% CI, 1.48-5.31; P=0.002) in quintile 2, 7.41 (95% CI, 4.13-13.30; P<0.001) in quintile 3, and 14.47 (95% CI, 8.20-25.54; P<0.001) in quintile 4 compared with the lowest risk quintile. When the highest risk quintile was subdivided into 2 equally sized risk strata (deciles 9 and 10), the adjusted odds ratios for 30-day mortality were 27.20 (95% CI, 15.33-48.27; P<0.001) in decile 9 and 58.96 (95% CI, 33.54-103.65; P<0.001) in highest risk decile 10. Presence of ST-depression on the ECG reclassified risk of 30-day mortality in patients with acute heart failure, identifying both high- and low-risk subsets.

External validation of the Garvan nomograms for predicting absolute fracture risk: the Tromsø study.

BackgroundAbsolute risk estimation is a preferred approach for assessing fracture risk and treatment decision making. This study aimed to evaluate and validate the predictive performance of the Garvan Fracture Risk Calculator in a Norwegian cohort.MethodsThe analysis included 1637 women and 1355 aged 60+ years from the Tromsø study. All incident fragility fractures between 2001 and 2009 were registered. The predicted probabilities of non-vertebral osteoporotic and hip fractures were determined using models with and without BMD. The discrimination and calibration of the models were assessed. Reclassification analysis was used to compare the models performance.ResultsThe incidence of osteoporotic and hip fracture was 31.5 and 8.6 per 1000 population in women, respectively; in men the corresponding incidence was 12.2 and 5.1. The predicted 5-year and 10-year probability of fractures was consistently higher in the fracture group than the non-fracture group for all models. The 10-year predicted probabilities of hip fracture in those with fracture was 2.8 (women) to 3.1 times (men) higher than those without fracture. There was a close agreement between predicted and observed risk in both sexes and up to the fifth quintile. Among those in the highest quintile of risk, the models over-estimated the risk of fracture. Models with BMD performed better than models with body weight in correct classification of risk in individuals with and without fracture. The overall net decrease in reclassification of the model with weight compared to the model with BMD was 10.6% (p = 0.008) in women and 17.2% (p = 0.001) in men for osteoporotic fractures, and 13.3% (p = 0.07) in women and 17.5% (p = 0.09) in men for hip fracture.ConclusionsThe Garvan Fracture Risk Calculator is valid and clinically useful in identifying individuals at high risk of fracture. The models with BMD performed better than those with body weight in fracture risk prediction.

Prediction Model for 30-Day Hospital Readmissions Among Patients Discharged Receiving Outpatient Parenteral Antibiotic Therapy

Factors associated with readmission for patients prescribed outpatient parenteral antibiotic therapy (OPAT) at hospital discharge have not been definitively identified. The study aim was to develop a model of 30-day readmissions for OPAT patients. A database comprising 782 OPAT patients treated between 2009 and 2011 at a single academic center was created. Variables collected included patient demographics, comorbidities, infections, and antibiotic classes. Final model discrimination was assessed using the c-statistic, and calibration was examined graphically. Mean patient age was 58 years (range, 18-95 years), 43% were women, and the most common diagnoses were bacteremia (24%), osteomyelitis (20%), and pyelonephritis (13%). The unplanned 30-day readmission rate was 26%. The leading indications for readmission were non-infection related (30%), worsening infection (29%), and new infection (19%). The final regression model consisted of age (odds ratio [OR], 1.09 per decade; 95% confidence interval [CI], 0.99-1.21), aminoglycoside use (OR, 2.33; 95% CI, 1.17-4.57), resistant organisms (OR, 1.57; 95% CI, 1.03-2.36), and number of prior hospital discharges without intravenous antibiotics in the past 12 months (OR, 1.20 per prior admission; 95% CI, 1.09-1.32). The c-statistic was 0.61 and the highest-risk quintile of patients had almost a 3-fold higher rate of readmission compared to the lowest. Patients prescribed OPAT are at risk for readmission. A subgroup of patients at especially high risk can be identified using easily obtainable clinical characteristics at the time of hospital discharge. More intensive interventions to prevent OPAT readmissions should be targeted and tested with those at highest risk.

THU0010 A Weighted Genetic Risk Score Using 46 Loci to Predict Rheumatoid Arthritis Risk

BackgroundRecent advances in the identification of loci associated with susceptibility to complex disease have led to methods being developed that incorporate this information into genetic screening models to identify individuals...

519 SPARC (SURVIVAL PREDICTION AFTER RADICAL CYSTECTOMY): A MULTIFACTORIAL OUTCOME PREDICTION MODEL FOR PATIENTS UNDERGOING RADICAL CYSTECTOMY FOR BLADDER CANCER

INTRODUCTION AND OBJECTIVES: While multiple independent clinicopathologic variables associated with outcome following radical cystectomy (RC) for bladder cancer (BC) have been identified, limited prediction tools exist to facilitate an individualized risk assessment based on the relative weight of these various features. Herein, we developed an outcome prediction model based on clinical and pathologic characteristics found to be significantly associated with death from BC after RC. METHODS: We evaluated 1829 patients who underwent RC without neoadjuvant therapy at our institution between 1980–2008. Of these, 1,751 with non-metastatic, non-small cell histology were identified. Univariate analysis evaluating variables associated with BC specific mortality was conducted. A multivariate model was obtained using a stepwise selection process from variables significant at the 0.05 level. A scoring system based on the -coefficients of this model was created, assigning 1 point for each parameter estimate value of 0.20. RESULTS: Median follow-up after RC was 10.7 years (interquartile range 7.7, 15.7), during which time 652 patients experienced death due to BC. On multivariate analysis (Table), race, Charlson comorbidity index, ECOG status, current smoking status, preoperative hydronephrosis, pathologic stage, multifocality, lymphovascular invasion, and concurrent CIS were significantly associated with BC death. Cumulative scores from these variables were used to stratify patients into quintiles according to risk score of BC death as 4, 5-8, 9-12, 13-16, and 17. 5-year cancer specific survival (CSS) from the lowest to highest risk quintile was 95%, 82%, 58%, 35%, and 17%, respectively (p 0.0001). The c-index for this model was 0.76. CONCLUSIONS: We present a model for individualizing estimation of CSS following radical cystectomy. Pending external validation, these data may be used for patient counseling, specifically with regard to recommendations for adjuvant therapy and surveillance frequency, as well as in clinical trial development.

236 RISK STRATIFICATION OF PATIENTS WITH EXTRACAPSULAR EXTENSION (PT3AN0) AT RADICAL PROSTATECTOMY: IDENTIFYING OPTIMAL CANDIDATES FOR ADJUVANT THERAPY

You have accessJournal of UrologyProstate Cancer: Epidemiology & Natural History (I)1 Apr 2013236 RISK STRATIFICATION OF PATIENTS WITH EXTRACAPSULAR EXTENSION (PT3AN0) AT RADICAL PROSTATECTOMY: IDENTIFYING OPTIMAL CANDIDATES FOR ADJUVANT THERAPY Manuel S. Eisenberg, R. Jeffrey Karnes, Dharam Kaushik, Laureano Rangel, Eric Bergstralh, and Stephen A. Boorjian Manuel S. EisenbergManuel S. Eisenberg Rochester, MN More articles by this author , R. Jeffrey KarnesR. Jeffrey Karnes Rochester, MN More articles by this author , Dharam KaushikDharam Kaushik Rochester, MN More articles by this author , Laureano RangelLaureano Rangel Rochester, MN More articles by this author , Eric BergstralhEric Bergstralh Rochester, MN More articles by this author , and Stephen A. BoorjianStephen A. Boorjian Rochester, MN More articles by this author View All Author Informationhttps://doi.org/10.1016/j.juro.2013.02.1616AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookTwitterLinked InEmail INTRODUCTION AND OBJECTIVES Several prospective randomized trials have demonstrated a benefit to adjuvant radiation (ART) after radical prostatectomy (RP) for patients found to have pathologically locally-advanced tumors. However, these studies have included heterogeneous cohorts of men, and thus ART in all such cases may represent overtreatment in a significant subset. Herein, we evaluated the long-term survival of patients with pT3aN0 disease at RP without adjuvant therapy, and determined predictors of disease recurrence in these men. METHODS We evaluated 17,862 patients who underwent RP at Mayo Clinic between 1987−2011. Of these, 1548 with pT3aN0 disease who did not receive neoadjuvant or adjuvant therapy were identified. Biochemical recurrence (BCR)-free survival was estimated using the Kaplan Meier method. Cox proportional hazards regression analysis was used to assess the association of clinicopathologic features with BCR. Variables which were significantly associated with BCR in the Cox model (Table) went through a stepwise selection process. A weighted score was generated for each parameter, and cumulative weighted scores were used to stratify patients according to BCR risk. RESULTS Median follow−up after RP was 11.6 years (interquartile range (IQR) 5.9,16.6), during which time 449 patients experienced BCR and 553 died, including 76 who died of prostate cancer. On multivariate analysis, preoperative PSA (HR 1.3; 95% CI 1.1,1.5; p=0.0003), clinical tumor stage (HR 1.2; 95% CI 1.1,1.3; p=0.001), pathologic Gleason score (HR 1.8; 95% CI 1.6,2.1; p<0.0001), surgical margin status (HR 1.6; 95% CI 1.3,1.9; p<0.0001), and a detectable first postoperative PSA (HR 2.2; 95% CI 1.7,2.8; p<0.0001) were significantly associated with BCR. Cumulative weighted scores from these variables were used to stratify patients into quintiles according to BCR risk. 15-year BCR-free survival from lowest to highest risk quintile was 69%, 58%, 45%, 32%, and 24%, respectively (p<0.0001). C-index for this model was 0.69. CONCLUSIONS We present a model for individualizing estimation of BCR in men with pT3aN0 disease at RP. These data may be used for patient counseling, specifically with regard to risk stratification when discussing utilization of secondary therapies. Parameter Hazard Ratio p value Relative Weight Value Natural log preoperative PSA 1.3 0.0003 0.26 Per lab value Clinical Stage 1.2 0.0010 0.18 T1a/b = 0, T1c=1, T2a = 2, T2b = 3, T3/4 = 4 Pathologic Gleason sum 1.8 < 0.0001 0.61 2-6=6, 7=7, 8-10=8 Surgical Margins Status 1.6 < 0.0001 0.46 negative = 0, positive = 1 First Postoperative PSA 2.2 < 0.0001 0.77 < 0.15=0, ≥0.15=1 Biochemical Recurrence-Free Survival Quintile (Total Score)⁎ No. pts 5 year BCR free 10 year BCR free 15 year BCR free I (< 4.75) 215 90% (167) 79% (119) 69% (61) II (4.75 - 5.03) 215 85% (132) 66% (73) 58% (36) III (5.04 - 5.30) 213 75% (112) 53% (53) 45% (22) IV (5.31 - 5.75) 215 64% (105) 43% (49) 32% (21) V (≥5.76) 214 49% (82) 30% (38) 24% (15) Numbers in parentheses are number at risk unless otherwise indicated. ⁎ Group score calculated by the following equation: 0.26454*ln(preoperative PSA) + 0.18183*Clinical stage + 0.61439* Pathological Gleason + 0.46328* Positive surgical margin + 0.77047*Detectable PSA. © 2013 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 189Issue 4SApril 2013Page: e97 Advertisement Copyright & Permissions© 2013 by American Urological Association Education and Research, Inc.MetricsAuthor Information Manuel S. Eisenberg Rochester, MN More articles by this author R. Jeffrey Karnes Rochester, MN More articles by this author Dharam Kaushik Rochester, MN More articles by this author Laureano Rangel Rochester, MN More articles by this author Eric Bergstralh Rochester, MN More articles by this author Stephen A. Boorjian Rochester, MN More articles by this author Expand All Advertisement Advertisement PDF downloadLoading ...