Treatment Selection and Practice Patterns for the Management of High-Risk Chronic Lymphocytic Leukemia (CLL) in the US: An Analysis of the Impact of Risk Stratification on Treatment Selection from the Connect CLL® Registry
Authors: Mato Anthony , Nabhan Chadi , Flowers Christopher , Kay Neil E. , Kipps Thomas J. , Grinblatt David L. , Lamanna Nicole , Kozloff Mark , Sullivan Kristen , Flick E. Dawn , Kiselev Pavel , Bhushan Shriya , Swern Arlene S. , Sharman Jeff P. 
Published: October 2019

Abstract
Introduction: Results of several large clinical trials have demonstrated inferior outcomes when CLL patients (pts) with del(17p), or to a lesser extent del(11q), are treated with chemoimmunotherapy. Despite recent advances in targeted therapies, management of unfavorable-risk CLL pts remains challenging. The Connect CLL registry is the largest prospective study describing real-world management of a diverse cohort of CLL pts. Here we describe the management of genetically unfavorable-risk CLL pts enrolled in the Connect CLL Registry, and test associations between del(17p)/del(11q) mutations and treatment choice, timing of therapy, and outcomes.
Methods: Connect CLL is a longitudinal, multicenter, observational cohort study of 1,494 CLL pts enrolled between 2010-2014 at 179 community (n=1,311), 17 academic (n=155), and 3 government (n=28) sites within ≤ 2 months of initiating any line of therapy (LOT). For this study, pts were categorized into 3 risk-groups based on FISH or cytogenetic results at enrollment: unfavorable risk [either del(17p)/del(11q) positive]; favorable risk [absence of del(17p)/del(11q)]; and unknown risk (testing not performed). Analyses were stratified by LOT at enrollment (LOT1 vs LOT≥2). The risk of an EFS defining event was compared across risk-groups stratified by LOT, including only pts who had been followed for ≥ 2 years (yr) or those who had an EFS defining event (death, progression/relapse, transformation) within 2 yr, using multivariable (MV) logistic regression. Logistic regression analyses of 18 potential predictors were performed, and significant predictors (0.10 significance level) were then included in a MV logistic regression model to identify factors associated with inferior 2 yr EFS.
Results: Of 1,494 pts enrolled, 225 had unfavorable risk [del(17p), n = 94; del(11q), n = 131], 621 favorable risk, and 648 unknown risk. For pts enrolled at LOT1 (n = 889), 141 had unfavorable risk, 425 favorable risk, and 323 unknown risk. Baseline characteristics for unfavorable-risk pts in LOT1 included: median age 69 yr (62% age ≥ 65 yr); 91% White; 53% Rai stage ≥ 2; 86% community sites; 0.9 yr median time from dx to LOT1; 8% family history CLL. With the exception of age, unfavorable-risk pts treated at LOT1 with FCR (median age 63) and BR (median age 74) had similar demographic characteristics. Median time from dx to LOT1 was 1.0, 1.3, and 2.0 yr for unfavorable risk, favorable, and unknown-risk pts, respectively (P < 0.001 for comparison of the 3 risk-subgroups). Reasons for initiating treatment in unfavorable-risk pts were lymphadenopathy (42%), bone marrow failure (36%), and lymphocytosis (33%) (similar across the 3 risk-subgroups). The three most common therapies for unfavorable-risk pts in LOT1 were FCR (36%), BR (21%), and FR (6%). Favorable-risk (FCR 26%, BR 24%, and R 10%) and unknown-risk pts (FCR 22%, BR 18%, and R 17%) were treated similarly in LOT1. Median time from dx to LOT≥2 was 3.5 yr in unfavorable-risk pts (vs 4.1 yr in favorable and 4.6 yr in unknown risk pts; P = 0.04 for comparison of the 3 risk-groups). For unfavorable-risk pts in LOT≥2, BR (26%), R (11%), and FCR (10%) were most commonly prescribed. At any LOT, only 10% of unfavorable-risk pts participated in a clinical trial and 4% underwent allogeneic SCT. Overall, 33% (LOT1) and 68% (LOT≥2) of pts experienced an EFS defining event within 2 yrs. Pts with unfavorable risk (vs favorable risk) had significantly worse outcomes, with a higher-risk of death/progression/relapse/transformation within 2 yr (LOT1: 42% vs 29%, respectively, P = 0.008; and LOT≥2: 80% vs 61%, P = 0.004). Unfavorable-risk pts treated with either FCR or BR at LOT1 had similar risk of an EFS defining event (odds ratio [OR] 0.9, CI 0.6-1.5). Results from MV analyses of LOT1 pts identified unfavorable risk (OR 1.9; 95% CI 1.1-3.1; P = 0.0168) and age ≥ 75 years (OR 2.6; 95% CI 1.5-4.3; P = 0.007) as independent predictors of inferior EFS at 2 yr.
Conclusions: Although similar treatment approaches were used among the 3 risk-subgroups, pts with unfavorable-risk CLL had inferior outcomes at LOT1 and LOT≥2. These results, from a real-world setting, validate the findings for unfavorable risk pts from large clinical trials. These data underscore the importance of performing genetic risk stratification on all CLL pts, and support consideration of clinical trials and/or B cell receptor targeted agents for unfavorable risk CLL pts when treatment is considered.

Disclosures
Mato: Janssen: Consultancy; AbbVie: Consultancy, Research Funding; Genentech: Consultancy; Pronai Pharmaceuticals: Research Funding; Celgene Corporation: Consultancy, Research Funding; Pharmacyclics: Consultancy, Research Funding; Gilead: Consultancy, Research Funding; TG Therapeutics: Research Funding. Nabhan:Celgene Corporation: Honoraria, Research Funding. Flowers:Celegene: Other: Unpaid consultant, Research Funding; Celegene: Other: Unpaid consultant, Research Funding; Spectrum: Research Funding; Infinity Pharmaceuticals: Research Funding; OptumRx: Consultancy; Onyx Pharmaceuticals: Research Funding; Janssen: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Onyx Pharmaceuticals: Research Funding; Pharmacyclics: Research Funding; Gilead Sciences: Research Funding; Genentech: Research Funding; Acerta: Research Funding; Genentech: Research Funding; Janssen: Research Funding; Millennium/Takeda: Research Funding; Infinity Pharmaceuticals: Research Funding; Spectrum: Research Funding; Millennium/Takeda: Research Funding; Pharmacyclics: Research Funding; OptumRx: Consultancy; Gilead Sciences: Research Funding; AbbVie: Research Funding; Seattle Genetics: Consultancy; Acerta: Research Funding. Kay:Pharmacyclics: Research Funding; Genentech: Research Funding; Tolero Pharma: 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. Kipps:Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor; Pharmacyclics Abbvie Celgene Genentech Astra Zeneca Gilead Sciences: Other: Advisor. Grinblatt:Celgene Corporation: Consultancy, Honoraria, Speakers Bureau. Lamanna:Genentech-Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Infinity: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene Corporation: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Kozloff:Genentech: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Roche: Consultancy, Speakers Bureau; AbbVie: Consultancy. Sullivan:Celgene Corporation: Employment, Equity Ownership. Flick:Celgene Corporation: Employment, Equity Ownership. Kiselev:Celgene Corporation: Consultancy. Bhushan:Celgene Corporation: Employment, Equity Ownership. Swern:Celgene Corporation: Employment, Equity Ownership. Sharman:Gilead: Consultancy, Honoraria, Research Funding, Speakers Bureau; Calistoga: Honoraria; Roche: Research Funding; TG Therapeutics, Inc.: Research Funding; Celgene Corporation: Consultancy, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Janssen: Research Funding.