Impact of Preexisting Heart Failure on Treatment and Outcomes in Older Patients With Hodgkin Lymphoma.

Background: Older patients with Hodgkin lymphoma (HL) often have comorbid cardiovascular disease; however, the impact of pre-existing heart failure (HF) on the management and outcomes of HL is unknown. Objectives: The aim of this study was to assess the prevalence of pre-existing HF in older patients with HL and its impact on treatment and outcomes. Methods: Linked Surveillance, Epidemiology, and End Results (SEER) and Medicare data from 1999 to 2016 were used to identify patients 65 years and older with newly diagnosed HL. Pre-existing HF, comorbidities, and cancer treatment were ascertained from billing codes and cause-specific mortality from SEER. The associations between pre-existing HF and cancer treatment were estimated using multivariable logistic regression. Cause-specific Cox proportional hazards models adjusted for comorbidities and cancer treatment were used to estimate the association between pre-existing HF and cause-specific mortality. Results: Among 3,348 patients (mean age 76 ± 7 years, 48.6% women) with newly diagnosed HL, pre-existing HF was present in 437 (13.1%). Pre-existing HF was associated with a lower likelihood of using anthracycline-based chemotherapy regimens (OR: 0.42; 95% CI: 0.29-0.60) and a higher likelihood of lymphoma mortality (HR: 1.25; 95% CI: 1.06-1.46) and cardiovascular mortality (HR: 2.57; 95% CI: 1.96-3.36) in models adjusted for comorbidities. One-year lymphoma mortality cumulative incidence was 37.4% (95% CI: 35.5%-39.5%) with pre-existing HF and 26.3% (95% CI: 25.0%-27.6%) without pre-existing HF. The cardioprotective medications dexrazoxane and liposomal doxorubicin were used in only 4.2% of patients. Conclusions: Pre-existing HF in older patients with newly diagnosed HL is common and associated with higher 1-year mortality. Strategies are needed to improve lymphoma and cardiovascular outcomes in this high-risk population.

Association of Preexisting Heart Failure With Outcomes in Older Patients With Diffuse Large B-Cell Lymphoma.

Importance: Anthracycline-containing regimens are highly effective for diffuse large B-cell lymphoma (DLBCL); however, patients with preexisting heart failure (HF) may be less likely to receive anthracyclines and may be at higher risk of lymphoma mortality. Objective: To assess the prevalence of preexisting HF in older patients with DLBCL and its association with treatment patterns and outcomes. Design, Setting, and Participants: This longitudinal cohort study used data from the Surveillance, Epidemiology, and End Results (SEER)-Medicare registry from 1999 to 2016. The SEER registry is a system of population-based cancer registries, capturing more than 25% of the US population. Linkage to Medicare offers additional information from billing claims. This study included individuals 65 years and older with newly diagnosed DLBCL from 2000 to 2015 with Medicare Part A or B continuously in the year prior to lymphoma diagnosis. Data were analyzed from September 2020 to December 2022. Exposures: Preexisting HF in the year prior to DLBCL diagnosis ascertained from billing codes required one of the following: (1) 1 primary inpatient discharge diagnosis, (2) 2 outpatient diagnoses, (3) 3 secondary inpatient discharge diagnoses, (4) 3 emergency department diagnoses, or (5) 2 secondary inpatient discharge diagnoses plus 1 outpatient diagnosis. Main Outcomes and Measures: The primary outcome was anthracycline-based treatment. The secondary outcomes were (1) cardioprotective medications and (2) cause-specific mortality. The associations between preexisting HF and cancer treatment were estimated using multivariable logistic regression. The associations between preexisting HF and cause-specific mortality were evaluated using cause-specific Cox proportional hazards models with adjustment for comorbidities and cancer treatment. Results: Of 30 728 included patients with DLBCL, 15 474 (50.4%) were female, and the mean (SD) age was 77.8 (7.2) years. Preexisting HF at lymphoma diagnosis was present in 4266 patients (13.9%). Patients with preexisting HF were less likely to be treated with an anthracycline (odds ratio, 0.55; 95% CI, 0.49-0.61). Among patients with preexisting HF who received an anthracycline, dexrazoxane or liposomal doxorubicin were used in 78 of 1119 patients (7.0%). One-year lymphoma mortality was 41.8% (95% CI, 40.5-43.2) with preexisting HF and 29.6% (95% CI, 29.0%-30.1%) without preexisting HF. Preexisting HF was associated with higher lymphoma mortality in models adjusting for baseline and time-varying treatment factors (hazard ratio, 1.24; 95% CI, 1.18-1.31). Conclusions and Relevance: In this study, preexisting HF in patients with newly diagnosed DLBCL was common and was associated with lower use of anthracyclines and lower use of any chemotherapy. Trials are needed for this high-risk population.

External Validation of the FREEDOM Score for Individualized Decision Making Between CABG and PCI.

BACKGROUND: Although randomized trials have established that coronary artery bypass grafting (CABG) is, on average, the most effective revascularization strategy compared with percutaneous coronary intervention (PCI) in patients with diabetes and multivessel disease (MVD), individual patients differ in many characteristics that can affect the benefits and harms of treatment. The FREEDOM (Future Revascularization Evaluation in Patients with Diabetes Mellitus) score was developed to predict different outcomes with CABG vs PCI on the basis of 8 patient characteristics and the smoking-treatment interaction. OBJECTIVES: This study aimed to assess the ability of the 5-year major adverse cardiovascular event (MACE) model to predict treatment benefit of CABG vs PCI in the SYNTAX (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery) and BEST (Bypass Surgery and Everolimus-Eluting Stent Implantation in the Treatment of Patients with Multivessel Coronary Artery Disease) trials. METHODS: This study identified 702 patients with diabetes and MVD to mirror the FREEDOM participants. Discrimination was assessed by C-index, and calibration was assessed by calibration plots in the PCI and CABG arms, respectively. The ability of the FREEDOM score to predict treatment benefit of CABG vs PCI was assessed. RESULTS: Overall, CABG was associated with a lower rate of 5-year MACE compared with PCI (12.4% vs 20.3%; log-rank P = 0.021) irrespective of a history of smoking (Pinteraction = 0.975). Both discrimination and calibration were helpful in the PCI arm (C-index: 0.69; slope: 0.96, intercept: -0.24), but moderate in the CABG arm (C-index: 0.61; slope: 0.61; intercept: -0.53). The FREEDOM score showed some heterogeneity of treatment benefit. CONCLUSIONS: The FREEDOM score could identify some heterogeneity of treatment benefit of CABG vs PCI for 5-year MACE. Until further prospective validations are performed, these results should be taken into consideration when using the FREEDOM score in patients with diabetes and MVD. (Synergy Between Percutaneous Coronary Intervention With Taxus and Cardiac Surgery [SYNTAX]; NCT00114972) (Bypass Surgery and Everolimus-Eluting Stent Implantation in the Treatment of Patients with Multivessel Coronary Artery Disease [BEST]; NCT00997828) (Future Revascularization Evaluation in Patients with Diabetes Mellitus [FREEDOM]; NCT00086450).

All-cause mortality as the primary endpoint for the GRAIL/National Health Service England multi-cancer screening trial.

A randomized trial of the GRAIL GalleriTM multi-cancer screening test is being planned for the National Health Service in England, and will have 140,000 healthy participants aged 50-79: 70,000 exposed to screening and 70,000 unexposed. The test reportedly detects 50 different cancers and is expected to reduce all-cancer mortality by approximately 25%. Given this effect size-and that cancer deaths constitute a large fraction of all deaths-the trial is sufficiently large to test the effect on all-cause mortality. Because most patients believe cancer screening "saves lives", the GRAIL/National Health Service collaboration could set the evaluation standard for multi-cancer screening.

External Validation of the SYNTAX Score II 2020.

BACKGROUND: The SYNTAX score II 2020 (SSII-2020) was derived from cross correlation and externally validated in randomized trials to predict death and major adverse cardiac and cerebrovascular events (MACE) following percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG) in patients with 3-vessel disease (3VD) and/or left main coronary artery disease (LMCAD). OBJECTIVES: The authors aimed to investigate the SSII-2020's value in identifying the safest modality of revascularization in a non-randomized setting. METHODS: Five-year mortality and MACE were assessed in 7,362 patients with 3VD and/or LMCAD enrolled in a Japanese PCI/CABG registry. The discriminative abilities of the SSII-2020 were assessed using Harrell's C statistic. Agreement between observed and predicted event rates following PCI or CABG and treatment benefit (absolute risk difference [ARD]) for these outcomes were assessed by calibration plots. RESULTS: The SSII-2020 for 5-year mortality well predicted the prognosis after PCI and CABG (C-index = 0.72, intercept = -0.11, slope = 0.92). When patients were grouped according to the predicted 5-year mortality ARD, <4.5% (equipoise of PCI and CABG) and ≥4.5% (CABG better), the observed mortality rates after PCI and CABG were not significantly different in patients with lower predicted ARD (observed ARD: 2.1% [95% CI: -0.4% to 4.4%]), and the significant difference in survival in favor of CABG was observed in patients with higher predicted ARD (observed ARD: 9.7% [95% CI: 6.1%-13.3%]). For MACE, the SSII-2020 could not recommend a specific treatment with sufficient accuracy. CONCLUSIONS: The SSII-2020 for predicting 5-year death has the potential to support decision making on revascularization in patients with 3VD and/or LMCAD.

Redevelopment and validation of the SYNTAX score II to individualise decision making between percutaneous and surgical revascularisation in patients with complex coronary artery disease: secondary analysis of the multicentre randomised controlled SYNTAXES trial with external cohort validation.

BACKGROUND: Randomised controlled trials are considered the gold standard for testing the efficacy of novel therapeutic interventions, and typically report the average treatment effect as a summary result. As the result of treatment can vary between patients, basing treatment decisions for individual patients on the overall average treatment effect could be suboptimal. We aimed to develop an individualised decision making tool to select an optimal revascularisation strategy in patients with complex coronary artery disease. METHODS: The SYNTAX Extended Survival (SYNTAXES) study is an investigator-driven extension follow-up of a multicentre, randomised controlled trial done in 85 hospitals across 18 North American and European countries between March, 2005, and April, 2007. Patients with de-novo three-vessel and left main coronary artery disease were randomly assigned (1:1) to either the percutaneous coronary intervention (PCI) group or coronary artery bypass grafting (CABG) group. The SYNTAXES study ascertained 10-year all-cause deaths. We used Cox regression to develop a clinical prognostic index for predicting death over a 10-year period, which was combined, in a second stage, with assigned treatment (PCI or CABG) and two prespecified effect-modifiers, which were selected on the basis of previous evidence: disease type (three-vessel disease or left main coronary artery disease) and anatomical SYNTAX score. We used similar techniques to develop a model to predict the 5-year risk of major adverse cardiovascular events (defined as a composite of all-cause death, non-fatal stroke, or non-fatal myocardial infarction) in patients receiving PCI or CABG. We then assessed the ability of these models to predict the risk of death or a major adverse cardiovascular event, and their differences (ie, the estimated benefit of CABG versus PCI by calculating the absolute risk difference between the two strategies) by cross-validation with the SYNTAX trial (n=1800 participants) and external validation in the pooled population (n=3380 participants) of the FREEDOM, BEST, and PRECOMBAT trials. The concordance (C)-index was used to measure discriminative ability, and calibration plots were used to assess the degree of agreement between predictions and observations. FINDINGS: At cross-validation, the newly developed SYNTAX score II, termed SYNTAX score II 2020, showed a helpful discriminative ability in both treatment groups for predicting 10-year all-cause deaths (C-index=0·73 [95% CI 0·69-0·76] for PCI and 0·73 [0·69-0·76] for CABG) and 5-year major adverse cardiovascular events (C-index=0·65 [0·61-0·69] for PCI and C-index=0·71 [0·67-0·75] for CABG). At external validation, the SYNTAX score II 2020 showed helpful discrimination (C-index=0·67 [0·63-0·70] for PCI and C-index=0·62 [0·58-0·66] for CABG) and good calibration for predicting 5-year major adverse cardiovascular events. The estimated treatment benefit of CABG over PCI varied substantially among patients in the trial population, and the benefit predictions were well calibrated. INTERPRETATION: The SYNTAX score II 2020 for predicting 10-year deaths and 5-year major adverse cardiovascular events can help to identify individuals who will benefit from either CABG or PCI, thereby supporting heart teams, patients, and their families to select optimal revascularisation strategies. FUNDING: The German Heart Research Foundation and the Patient-Centered Outcomes Research Institute.

Prior Stroke in PFO Patients Is Associated With Both PFO-Related and -Unrelated Factors.

Background and Purpose: To identify factors associated with prior stroke at presentation in patients with cryptogenic stroke (CS) and patent foramen ovale (PFO). Methods: We studied cross-sectional data from the International PFO Consortium Study (NCT00859885). Patients with first-ever stroke and those with prior stroke at baseline were analyzed for an association with PFO-related (right-to-left shunt at rest, atrial septal aneurysm, deep venous thrombosis, pulmonary embolism, and Valsalva maneuver) and PFO-unrelated factors (age, gender, BMI, hypertension, diabetes mellitus, hypercholesterolemia, smoking, migraine, coronary artery disease, aortic plaque). A multivariable analysis was used to adjust effect estimation for confounding, e.g., owing to the age-dependent definition of study groups in this cross-sectional study design. Results: We identified 635 patients with first-ever and 53 patients with prior stroke. Age, BMI, hypertension, diabetes mellitus, hypercholesterolemia, coronary artery disease, and right-to-left shunt (RLS) at rest were significantly associated with prior stroke. Using a pre-specified multivariable logistic regression model, age (Odds Ratio 1.06), BMI (OR 1.06), hypercholesterolemia (OR 1.90) and RLS at rest (OR 1.88) were strongly associated with prior stroke.Based on these factors, we developed a nomogram to illustrate the strength of the relation of individual factors to prior stroke. Conclusion: In patients with CS and PFO, the likelihood of prior stroke is associated with both, PFO-related and PFO-unrelated factors.

Developing a cancer-specific trigger tool to identify treatment-related adverse events using administrative data.

BACKGROUND: As there are few validated tools to identify treatment-related adverse events across cancer care settings, we sought to develop oncology-specific "triggers" to flag potential adverse events among cancer patients using claims data. METHODS: 322 887 adult patients undergoing an initial course of cancer-directed therapy for breast, colorectal, lung, or prostate cancer from 2008 to 2014 were drawn from a large commercial claims database. We defined 16 oncology-specific triggers using diagnosis and procedure codes. To distinguish treatment-related complications from comorbidities, we required a logical and temporal relationship between a treatment and the associated trigger. We tabulated the prevalence of triggers by cancer type and metastatic status during 1-year of follow-up, and examined cancer trigger risk factors. RESULTS: Cancer-specific trigger events affected 19% of patients over the initial treatment year. The trigger burden varied by disease and metastatic status, from 6% of patients with nonmetastatic prostate cancer to 41% and 50% of those with metastatic colorectal and lung cancers, respectively. The most prevalent triggers were abnormal serum bicarbonate, blood transfusion, non-contrast chest CT scan following radiation therapy, and hypoxemia. Among patients with metastatic disease, 10% had one trigger event and 29% had two or more. Triggers were more common among older patients, women, non-whites, patients with low family incomes, and those without a college education. CONCLUSIONS: Oncology-specific triggers offer a promising method for identifying potential patient safety events among patients across cancer care settings.

Clinical Prediction Models for Valvular Heart Disease.

Background While many clinical prediction models (CPMs) exist to guide valvular heart disease treatment decisions, the relative performance of these CPMs is largely unknown. We systematically describe the CPMs available for patients with valvular heart disease with specific attention to performance in external validations. Methods and Results A systematic review identified 49 CPMs for patients with valvular heart disease treated with surgery (n=34), percutaneous interventions (n=12), or no intervention (n=3). There were 204 external validations of these CPMs. Only 35 (71%) CPMs have been externally validated. Sixty-five percent (n=133) of the external validations were performed on distantly related populations. There was substantial heterogeneity in model performance and a median percentage change in discrimination of -27.1% (interquartile range, -49.4%--5.7%). Nearly two-thirds of validations (n=129) demonstrate at least a 10% relative decline in discrimination. Discriminatory performance of EuroSCORE II and Society of Thoracic Surgeons (2009) models (accounting for 73% of external validations) varied widely: EuroSCORE II validation c-statistic range 0.50 to 0.95; Society of Thoracic Surgeons (2009) Models validation c-statistic range 0.50 to 0.86. These models performed well when tested on related populations (median related validation c-statistics: EuroSCORE II, 0.82 [0.76, 0.85]; Society of Thoracic Surgeons [2009], 0.72 [0.67, 0.79]). There remain few (n=9) external validations of transcatheter aortic valve replacement CPMs. Conclusions Many CPMs for patients with valvular heart disease have never been externally validated and isolated external validations appear insufficient to assess the trustworthiness of predictions. For surgical valve interventions, there are existing predictive models that perform reasonably well on related populations. For transcatheter aortic valve replacement (CPMs additional external validations are needed to broadly understand the trustworthiness of predictions.

Models with interactions overestimated heterogeneity of treatment effects and were prone to treatment mistargeting.

OBJECTIVES: We aimed to compare the performance of different regression modeling approaches for the prediction of heterogeneous treatment effects. STUDY DESIGN AND SETTING: We simulated trial samples (n = 3,600; 80% power for a treatment odds ratio of 0.8) from a superpopulation (N = 1,000,000) with 12 binary risk predictors, both without and with six true treatment interactions. We assessed predictions of treatment benefit for four regression models: a "risk model" (with a constant effect of treatment assignment) and three "effect models" (including interactions of risk predictors with treatment assignment). Three novel performance measures were evaluated: calibration for benefit (i.e., observed vs. predicted risk difference in treated vs. untreated), discrimination for benefit, and prediction error for benefit. RESULTS: The risk modeling approach was well-calibrated for benefit, whereas effect models were consistently overfit, even with doubled sample sizes. Penalized regression reduced miscalibration of the effect models considerably. In terms of discrimination and prediction error, the risk modeling approach was superior in the absence of true treatment effect interactions, whereas penalized regression was optimal in the presence of true treatment interactions. CONCLUSION: A risk modeling approach yields models consistently well calibrated for benefit. Effect modeling may improve discrimination for benefit in the presence of true interactions but is prone to overfitting. Hence, effect models-including only plausible interactions-should be fitted using penalized regression.

Personalized Decision Making in Early Stage Breast Cancer: Applying Clinical Prediction Models for Anthracycline Cardiotoxicity and Breast Cancer Mortality Demonstrates Substantial Heterogeneity of Benefit-Harm Trade-off.

BACKGROUND: Anthracycline agents can cause cardiotoxicity. We used multivariable risk prediction models to identify a subset of patients with breast cancer at high risk of cardiotoxicity, for whom the harms of anthracycline chemotherapy may balance or exceed the benefits. PATIENTS AND METHODS: A clinical prediction model for anthracycline cardiotoxicity was created in 967 patients with human epidermal growth factor receptor-negative breast cancer treated with doxorubicin in the ECOG-ACRIN study E5103. Cardiotoxicity was defined as left ventricular ejection fraction (LVEF) decline of ≥ 10% to < 50% and/or a centrally adjudicated clinical heart failure diagnosis. Patient-specific incremental absolute benefit of anthracyclines (compared with non-anthracycline taxane chemotherapy) was estimated using the PREDICT model to assess breast cancer mortality risk. RESULTS: Of the 967 women who initiated therapy, 51 (5.3%) developed cardiotoxicity (12 with clinical heart failure). In a multivariate model, increasing age (odds ratio [OR], 1.04; 95% confidence interval [CI], 1.01-1.08), higher body mass index (OR, 1.06; 95% CI, 1.02-1.10), and lower baseline LVEF (OR, 0.93; 95% CI, 0.89-0.98) at baseline were significantly associated with cardiotoxicity. The concordance statistic of the risk model was 0.70 (95% CI, 0.63-0.77). In patients with low anticipated treatment benefit (n = 176) from the addition of anthracycline (< 2% absolute risk difference of breast cancer mortality at 10 years), 16 (9%) of 176 had a > 10% risk of cardiotoxicity and 61 (35%) of 176 had a 5% to 10% risk of cardiotoxicity at 1 year. CONCLUSION: Older age, higher body mass index, and lower baseline LVEF were associated with increased risk of cardiotoxicity. We identified a subgroup with low predicted absolute benefit of anthracyclines but with high predicted risk of cardiotoxicity. Additional studies are needed incorporating long-term cardiac outcomes and cardiotoxicity model external validation prior to implementation in routine clinical practice.

Targeted Incentive Programs For Lung Cancer Screening Can Improve Population Health And Economic Efficiency.

Because an intervention's clinical benefit depends on who receives it, a key to improving the efficiency of lung cancer screening with low-dose computed tomography (LDCT) is to incentivize its use among the current or former smokers who are most likely to benefit from it. Despite its clinical advantages and cost-effectiveness, only 3.9 percent of the eligible population underwent LDCT screening in 2015. Using individual lung cancer mortality risk, we developed a policy simulation model to explore the potential impact of implementing risk-targeted incentive programs, compared to either implementing untargeted incentive programs or doing nothing. We found that compared to the status quo, an untargeted incentive program that increased overall LDCT screening from 3,900 (baseline) to 10,000 per 100,000 eligible people would save 12,300 life-years and accrue a net monetary benefit (NMB) of $771 million over a lifetime horizon. Increasing screening by the same amount but targeting higher-risk people would yield an additional 2,470-6,600 life-years and an additional $210-$560 million NMB, depending on the extent of the risk-targeting. Risk-targeted incentive programs could include provider-level bonuses, health plan premium subsidies, and smoking cessation programs to maximize their impact. As clinical medicine becomes more personalized, targeting and incentivizing higher-risk people will help enhance population health and economic efficiency.

Risk-Targeted Lung Cancer Screening: A Cost-Effectiveness Analysis.

Background: Targeting low-dose computed tomography (LDCT) for lung cancer screening to persons at highest risk for lung cancer mortality has been suggested to improve screening efficiency. Objective: To quantify the value of risk-targeted selection for lung cancer screening compared with National Lung Screening Trial (NLST) eligibility criteria. Design: Cost-effectiveness analysis using a multistate prediction model. Data Sources: NLST. Target Population: Current and former smokers eligible for lung cancer screening. Time Horizon: Lifetime. Perspective: Health care sector. Intervention: Risk-targeted versus NLST-based screening. Outcome Measures: Incremental 7-year mortality, life expectancy, quality-adjusted life-years (QALYs), costs, and cost-effectiveness of screening with LDCT versus chest radiography at each decile of lung cancer mortality risk. Results of Base-Case Analysis: Participants at greater risk for lung cancer mortality were older and had more comorbid conditions and higher screening-related costs. The incremental lung cancer mortality benefits during the first 7 years ranged from 1.2 to 9.5 lung cancer deaths prevented per 10 000 person-years for the lowest to highest risk deciles, respectively (extreme decile ratio, 7.9). The gradient of benefits across risk groups, however, was attenuated in terms of life-years (extreme decile ratio, 3.6) and QALYs (extreme decile ratio, 2.4). The incremental cost-effectiveness ratios (ICERs) were similar across risk deciles ($75 000 per QALY in the lowest risk decile to $53 000 per QALY in the highest risk decile). Payers willing to pay $100 000 per QALY would pay for LDCT screening for all decile groups. Results of Sensitivity Analysis: Alternative assumptions did not substantially alter our findings. Limitation: Our model did not account for all correlated differences between lung cancer mortality risk and quality of life. Conclusions: Although risk targeting may improve screening efficiency in terms of early lung cancer mortality per person screened, the gains in efficiency are attenuated and modest in terms of life-years, QALYs, and cost-effectiveness. Primary Funding Source: National Institutes of Health (U01NS086294).

The proposed 'concordance-statistic for benefit' provided a useful metric when modeling heterogeneous treatment effects.

OBJECTIVES: Clinical prediction models that support treatment decisions are usually evaluated for their ability to predict the risk of an outcome rather than treatment benefit-the difference between outcome risk with vs. without therapy. We aimed to define performance metrics for a model's ability to predict treatment benefit. STUDY DESIGN AND SETTING: We analyzed data of the Synergy between Percutaneous Coronary Intervention with Taxus and Cardiac Surgery (SYNTAX) trial and of three recombinant tissue plasminogen activator trials. We assessed alternative prediction models with a conventional risk concordance-statistic (c-statistic) and a novel c-statistic for benefit. We defined observed treatment benefit by the outcomes in pairs of patients matched on predicted benefit but discordant for treatment assignment. The 'c-for-benefit' represents the probability that from two randomly chosen matched patient pairs with unequal observed benefit, the pair with greater observed benefit also has a higher predicted benefit. RESULTS: Compared to a model without treatment interactions, the SYNTAX score II had improved ability to discriminate treatment benefit (c-for-benefit 0.590 vs. 0.552), despite having similar risk discrimination (c-statistic 0.725 vs. 0.719). However, for the simplified stroke-thrombolytic predictive instrument (TPI) vs. the original stroke-TPI, the c-for-benefit (0.584 vs. 0.578) was similar. CONCLUSION: The proposed methodology has the potential to measure a model's ability to predict treatment benefit not captured with conventional performance metrics.

Survival Analyses and Prognosis of Plasma-Cell Myeloma and Plasmacytoma-Like Posttransplantation Lymphoproliferative Disorders.

BACKGROUND: Multiple myeloma/plasmacytoma-like posttransplantation lymphoproliferative disorder (PTLD-MM) is a rare complication of solid organ transplantation. Case series have shown variable outcomes, and survival data in the modern era are lacking. PATIENTS AND METHODS: A cohort of 212 PTLD-MM patients was identified in the Scientific Registry of Transplant Recipients between 1999 and 2011. Overall survival (OS) was estimated by the Kaplan-Meier method, and the effects of treatment and patient characteristics on OS were evaluated by Cox proportional hazards models. OS in 185 PTLD-MM patients was compared to 4048 matched controls with multiple myeloma (SEER-MM) derived from Surveillance, Epidemiology, and End Results (SEER) data. RESULTS: Men comprised 71% of patients; extramedullary disease was noted in 58%. Novel therapeutic agents were used in 19% of patients (more commonly during 2007-2011 vs. 1999-2006; P = .01), reduced immunosuppression in 55%, and chemotherapy in 32%. Median OS was 2.4 years and improved in the later time period (adjusted hazard ratio [aHR], 0.64, P = .05). Advanced age, creatinine > 2 g/dL, white race, and use of OKT3 were associated with inferior OS in multivariable analysis. OS of PTLD-MM patients is significantly inferior to SEER-MM patients (aHR, 1.6, P < .001). Improvements in OS over time differed between PTLD-MM and SEER-MM. Median OS of patients diagnosed from 2000 to 2005 was shorter for PTLD-MM than SEER-MM patients (18 vs. 47 months, P < .001). There was no difference among those diagnosed from 2006 to 2010 (44 months vs. median not reached, P = .5; interaction P = .08). CONCLUSION: Age at diagnosis, elevated creatinine, white race, and OKT3 were associated with inferior survival in patients with PTLD-MM. Survival of PTLD-MM is inferior to SEER-MM, although significant improvements in survival have been documented.

Development and Validation of a Predictive Model for Short- and Medium-Term Hospital Readmission Following Heart Valve Surgery.

BACKGROUND: Although models exist for predicting hospital readmission after coronary artery bypass surgery, no such models exist for predicting readmission after heart valve surgery (HVS). METHODS AND RESULTS: Using a geographically and structurally diverse sample of US hospitals (Premier Inpatient Database, January 2007-June 2011), we examined patient, hospital, and clinical factors predictive of short- and medium-term hospital readmission post-HVS. We set aside 20% of hospitals for model validation. A generalized estimating equation model accounted for clustering within hospitals. At 219 hospitals, we identified 38 532 patients (67 years, 56% male, 62% aortic valve surgery) who underwent HVS. A total of 3125 (7.8%) and 4943 (12.8%) patients were readmitted to the index hospital within 1 and 3 months, respectively. Our 3-month model predicted readmission rates between 3% and 61% with fair discrimination (C-statistic, 0.67) and good calibration (predicted vs observed differences in validation cohort averaged 1.9% across all deciles of predicted readmission risk). Results were similar for our 1-month model and our simplified 3-month model (suitable for clinical use), which used the 5 strongest predictors of readmission: transfused units of packed Red blood cells, presence of End-stage renal disease, type of Valve surgery, Emergency hospital admission, and hospital Length of stay (REVEaL). CONCLUSIONS: We described and validated key factors that predict short- and medium-term hospital readmission post-HVS. These models should enable clinicians to identify individuals with HVS who are at increased risk for hospital readmission and are most likely to benefit from improved postdischarge care and follow-up.

Myocardial Infarction, Stroke, and Mortality in cART-Treated HIV Patients on Statins.

Despite combination antiretroviral therapy (cART), people living with HIV (PLWH) continue to have more systemic inflammation and metabolic disturbances than the general population. These risk factors for atherosclerosis and organ dysfunction may be ameliorated by statins. We retrospectively analyzed 438 cART treated PLWH from the Nutrition For Healthy Living (NFHL) cohort to determine the association between statins and myocardial infarction (MI), stroke, and all-cause mortality as a composite. We used Cox proportional hazards regression as our main analysis. The average age was 44 years, 32% were women, and 67 of the 438 subjects used statins. There was no association between statins and our composite endpoint in two separate models [1.26 (0.57-2.79) in statin history model and 0.93 (0.65-1.32) per year in statin duration model]. The composite outcome was significantly associated with CD4 count, age, and smoking status in both models. CD4 count remained significant even after exclusion of mortality from the composite (HR=0.88, p=0.02). Confounding control via propensity scoring and multiple imputations did not change the results. Statins did not have an effect on MI, stroke, and mortality. Interestingly, CD4 count appears to be an important predictor of these outcomes, even after exclusion of death from the composite.

Baseline characteristics predict risk of progression and response to combined medical therapy for benign prostatic hyperplasia (BPH).

OBJECTIVE: To better risk stratify patients, using baseline characteristics, to help optimise decision-making for men with moderate-to-severe lower urinary tract symptoms (LUTS) secondary to benign prostatic hyperplasia (BPH) through a secondary analysis of the Medical Therapy of Prostatic Symptoms (MTOPS) trial. PATIENTS AND METHODS: After review of the literature, we identified potential baseline risk factors for BPH progression. Using bivariate tests in a secondary analysis of MTOPS data, we determined which variables retained prognostic significance. We then used these factors in Cox proportional hazard modelling to: i) more comprehensively risk stratify the study population based on pre-treatment parameters and ii) to determine which risk strata stood to benefit most from medical intervention. RESULTS: In all, 3047 men were followed in MTOPS for a mean of 4.5 years. We found varying risks of progression across quartiles. Baseline BPH Impact Index score, post-void residual urine volume, serum prostate-specific antigen (PSA) level, age, American Urological Association Symptom Index score, and maximum urinary flow rate were found to significantly correlate with overall BPH progression in multivariable analysis. CONCLUSIONS: Using baseline factors permits estimation of individual patient risk for clinical progression and the benefits of medical therapy. A novel clinical decision tool based on these analyses will allow clinicians to weigh patient-specific benefits against possible risks of adverse effects for a given patient.