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Abstract Funding Acknowledgements Type of funding sources: None. Aims. We tested the prognostic role of a risk score including bio-humoral evaluation, cardiopulmonary-echocardiographic stress (CPET-ESE) and lung ultrasound, in patients with heart failure (HF) with reduced and preserved ejection fraction (HFrEF and HFpEF), and subjects at risk of developing HF (American College of Cardiology/American Heart Association Stages A and B). Methods and results. We evaluated 318 subjects: 94 in Stages A-B, 194 in Stage C (85 HFpEF and 109 HFrEF), and 30 age and sex-matched controls (Stage 0). During a median follow-up of 18.5 months, we reported 40 urgent HF visits, 31 HF hospitalisations and 10 cardiovascular deaths. Cox proportional-hazards regression for predicting adverse events identified five independent predictors and each was assigned a number of points proportional to its regression coefficient: Δstress-rest B-lines >10 (3 points), peak oxygen consumption <16 mL/kg/min (2 points), minute ventilation/carbon dioxide production slope ≥36 (2 points), peak systolic pulmonary artery pressure ≥50 mmHg (1 point) and resting N-terminal pro-brain natriuretic peptide (NT-proBNP) >900 pg/mL (1 point). We defined three risk categories: low-risk (<3 points), intermediate-risk (3-6 points), and high-risk (>6 points). The event-free survival probability for these three groups were 93%, 52% and 20%, respectively. Hazard Ratio was 4.55 for each risk category upgrade (95% confidence interval [CI], 3.44-5.93). The area-under-curve for the scoring system to predict events was 0.92 (95% CI 0.88-0.96). Conclusion. A multiparametric risk score including indices of exercise-induced pulmonary congestion, markers of cardiopulmonary dysfunction and NT-proBNP identifies patients at increased risk for HF events across the HF spectrum. Table 1 Variable EPYC score EPYC score <3 (low risk) n = 217 EPYC score 3-6 (intermediate risk) n = 70 EPYC score >6 (high risk) n = 31 p-value (between risk categories) Event-free (n = 244) 0 (0 - 2) 210 (97) 32 (46) 2 (6) <0.0001 With events (n = 74) 6 (4 - 9) 7 (3) 38 (54) 29 (94) <0.0001 p-value (event-free vs with events) <0.0001 <0.0001 <0.0001 <0.0001 Stage 0-Controls (n = 30) 0 (0 - 1) 30 0 0 <0.0001 Stages A-B (n = 94) 1 (0 - 2) 85 (45) 6 (9) 3 (10) <0.0001 Stage C-HFpEF (n = 85) 3 (1 - 6)*† 46 (25) 29 (41) 10 (32) <0.0001 Stage C-HFrEF (n = 109) 4 (2 - 7)*† 56 (30) 35 (50) 18 (58) <0.0001 p-value (between HF Stages) <0.0001 <0.0001 <0.0001 <0.0001 Values are mean ± standard deviation, n (%), or median [25th quartile, 75th quartile]. * p < 0.01 vs Stage 0-Controls; † p < 0.01 vs Stages A-B. Abstract Figure 1

Abstract Aims Risk stratification of heart failure (HF) patients with preserved ejection fraction (HFpEF) can promote a more personalized treatment. We tested the prognostic value of a multi-parametric evaluation, including biomarkers, cardiopulmonary exercise testing-exercise stress echocardiography (CPET-ESE), and lung ultrasound, in HFpEF patients and subjects at risk of developing HF (HF Stages A and B). Background Risk stratification of heart failure (HF) patients with preserved ejection fraction (HFpEF) can promote a more personalized treatment. Design We tested the prognostic value of a multi-parametric evaluation, including biomarkers, cardiopulmonary exercise testing-exercise stress echocardiography (CPET-ESE), and lung ultrasound, in HFpEF patients and subjects at risk of developing HF (HF Stages A and B). Methods and results We performed a resting clinical/bio-humoural evaluation and a symptom-limited CPET-ESE in 274 patients (45 Stage A, 68 Stage B, and 161 Stage C-HFpEF) and 30 age- and sex-matched healthy controls. During a median follow-up of 18.5 months, we reported 71 HF hospitalizations and 10 cardiovascular deaths. Cox proportional-hazards regression identified five independent predictors and each was assigned a number of points proportional to its regression coefficient: stress-rest ΔB-lines >10 (3 points), peak oxygen consumption <16 mL/kg/min (2 points), minute ventilation/carbon dioxide production slope ≥36 (2 points), peak systolic pulmonary artery pressure ≥50 mmHg (1 point) and resting N-terminal pro-brain natriuretic peptide (NT-proBNP) >900 pg/mL (1 point). The event-free survival probability for low risk (<3 points), intermediate risk (3–6 points), and high risk (>6 points) were 93%, 52%, and 20%, respectively. The area under the curve (AUC) for the scoring system to predict events was 0.92 (95% CI 0.88–0.96), with an accuracy significantly higher than the individual components of the score (all P < 0.01 vs. individual AUCs). Conclusion A weighted risk score including NT-proBNP, markers of cardiopulmonary dysfunction and indices of exercise-induced pulmonary congestion identifies HFpEF patients at increased risk for adverse events and Stage A and B subjects more likely to progress towards more advanced HF stages.

Abstract Background: Over the last two decades several phenotypic, molecular, and chromosomal markers have been identified that are significantly associated with the prognosis of CLL patients. Therefore, clinicians managing CLL patients would benefit from a simplified prognostic index. Methods: We analyzed prospectively collected data from 337 Binet A CLL patients enrolled in Italian the O-CLL1-GISL protocol with the aim of developing scores capable of predicting treatment free survival (TFS). Factors independently associated with TFS were included in the prognostic indexes. To account for differences in the magnitude of the association between the individual independent factors and TFS, we assigned a weighted risk score to each factor based on ranges of their corresponding hazard ratios (HRs) (i.e., 1 point for HR 1.1-1.9; 2 points for HR 2.0-2.9, etc.). The total risk score was then calculated by the sum of the ratings of each factor on individual basis. Risk groups were identified combining risk categories with a non-statistically different TFS. Results: We developed two scores based on weighted multivariable models: the first included clinical and laboratory parameters [clinical score (c-score)], while the second was based on biological markers [biological score (b-score)] (Table 1). The c-score allowed to predict the TFS of patients through the combination of Rai stage, b2-microglobulin and absolute lymphocyte count (ALC), while the b-score predicted TFS by IGHV mutational status and CD38 expression. The c-score showed a C-statistic of 0.72, while the b-score was 0.67, although cases stratified according to the b-score showed a more specific mRNA/microRNA profile. When the two scores were forced in a multivariate analysis, both showed an independent predictive value on TFS with a similar HR, demonstrating their complementarity. Thus, we attempted to integrate the two scores performing a further multivariate analysis in which all parameters, significantly associated with TFS at univariate analysis, were tested (Table 1). ALC, Rai stage, b2-microglobulin together with IGHV mutational status, resulted independently associated with TFS. We constructed a weighted score [comprehensive score (co-score)], including all the above 4 variables, which allowed the identification of 3 different risk groups with significantly different TFS (Figure 1). The C-statistic of the g-score was 0.75, showing a better concordance than the other two scores. Moreover, its validity was externally validated in a series of 297 newly diagnosed Binet A CLL patients from the Mayo Clinic, USA. Conclusions: Using this multistep process and external validation, we developed a score with high discriminatory power and predictive significance on the individual patient level. Table 1. Univariate and multivariate Cox proportional Hazards Models Variable Univariate analysis Multivariate analysis Clinical model Biological model Comprehensive model HR (95% CI) P HR (95% CI) P score HR (95% CI) P score HR (95% CI) P score Age (years) <60/>60 1.12 (0.73-1.74) 0.59 - - - - - - - - - Sex Male/Female 0.93 (0.6-1.44) 0.93 - - - - - - - - - Rai stage 0/I-II 2.30 (1.47-3.50) <0.0001 2.13 (1.24-3.03) 0.004 0/2 - - - 1.76 (1.11-2.78) 0.015 0/1 ALC (109/L) <10/>10 3.43 (1.99-5.92) <0.0001 2.91 (1.85-5.20) <0.0001 0/2 - - - 2.70 (1.54-4.72) 0.001 0/2 b-2 microglobulin normal/elevated 3.04 (1.96-4.70) <0.0001 2.78 (1.79-4.30) <0.0001 0/2 - - - 2.65 (1.66-4.21) <0.0001 0/2 LDH normal/elevated 1.25 (0.57-2.71) 0.57 - - - - - - - - - CD38 negative/positive 3.22 (2.06-5.02) <0.0001 - - - 2.11 (1.15-3.16) 0.02 0/2 1.40 (0.80-2.42) 0.24 - ZAP-70 negative/positive 2.34 (1.51-3.61) <0.0001 - - - 1.21 (0.70-2.16) 0.485 - 1.0 (0.98-1.01) 0.72 - IGHV mutated/unmutated 3.57 (2.32-5.50) <0.0001 - - - 2.10 (1.12-3.90) 0.019 0/2 2.39 (1.27-4.50) 0.007 0/2 FISH risk low+int/high 2.93 (1.46-5.90) 0.002 - - - 1.65 (0.76-3.34) 0.216 - 1.80 (0.84-3.88) 0.13 - Abbreviations: ALC: absolute lymphocyte count; CI: confidential interval; HR: hazard ratio. Figure 1. TFS according to comprehensive progression risk score. Figure 1. TFS according to comprehensive progression risk score. Disclosures Shanafelt: Cephalon: Research Funding; Glaxo-Smith-Kline: Research Funding; Genentech: Research Funding; Hospira: Research Funding; Celgene: Research Funding; Jannsen: Research Funding; Polyphenon E International: Research Funding; Pharmacyclics: Research Funding. Kay:Genentech: Research Funding; Celgene Corporation: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Membership on an entity's Board of Directors or advisory committees, Research Funding; Hospira: Research Funding; Tolero Pharma: Research Funding; Pharmacyclics: Research Funding.

The chronic lymphocytic leukemia International Prognostic Index (CLL‐IPI) combines 5 parameters (age, clinical stage, TP53 status [normal vs. del(17p) and/or TP53 mutation], IGHV mutational status, serum β2‐microglobulin) to predict survival and time‐to‐first‐treatment (TTFT) in CLL patients. We performed an observational study in 337 prospectively collected, Binet stage A patients to validate the ability of the CLL‐IPI to predict TTFT in an independent cohort of early stage CLL patients. The CLL‐IPI score stratified Binet stage A patients into three subgroups with different outcome. Since the CLL‐IPI was originally developed to predict survival, we next investigated the optimal cut‐off score to predict TTFT in Binet stage A patients. Recursive partitioning analysis identified three subsets with scores of 0 (n = 139), 1 (n = 90), and ≥ 2(n = 108). The probability of remaining free from therapy 5 years after diagnosis was 85%, 67% and 46% in these three categories (P < 0.0001.; C‐statistic:c = 0.72; 95% CI:0.58‐0.81). This optimized CLL‐IPI scoring for TTFT was subsequently validated in an independent cohort of Binet A patients from the Mayo Clinic (n = 525). The ability of either original or optimized CLL‐IPI to predict TTFT was equivalent to other prognostic models specifically designed for this endpoint (2011 MDACC score and O‐CLL1 score). Although originally developed to predict suvival, the CLL‐IPI is useful for predicting TTFT in early stage CLL patients. Am. J. Hematol. 91:1090–1095, 2016. © 2016 Wiley Periodicals, Inc.