Analysis of Early Mortality of Chronic Lymphocytic Leukemia (CLL) Patients Treated in US Practices in the Connect CLL® Registry
Authors: Farber Charles M. , Mato Anthony , Nabhan Chadi , Kipps Thomas J. , Flowers Christopher , Kay Neil E. , Lamanna Nicole , Grinblatt David L. , Kozloff Mark , Weiss Mark , Sullivan Kristen , Flick E. Dawn , Kiselev Pavel , Bhushan Shriya , Swern Arlene S. , Sharman Jeff P. 
Published: October 2019

Introduction

The natural history of patients (pts) with CLL varies considerably. Some pts may have asymptomatic, indolent disease, while others may require therapy soon after diagnosis. Clinical staging systems cannot identify early-stage pts at risk for inferior survival. Genetic and molecular markers can provide additional information regarding prognosis and response prediction, however their utilization is limited in routine practice (Mato, ASCO 2015) and results can be conflicting. There is a need to identify characteristics of early-stage CLL pts at highest risk of early progression and/or death. Such characteristics, if readily available and reproducible, may identify such pts as candidates for early-intervention studies; particularly in the era of kinase inhibitor therapy. The Connect CLL registry is the largest prospective study describing real-world management of a diverse cohort of 1494 CLL pts. In this analysis, we evaluate key factors that are associated with early CLL-associated mortality in clinical practice.

Methods

Connect CLL is a multicenter, observational cohort study aimed at understanding patterns of CLL management without a study-specific intervention. Eligible pts were adults with a clinical diagnosis of CLL, enrolled between 2010-2014 at 179 community (n=1311), 17 academic (n=155), and 3 government (n=28) sites within ≤ 2 months of initiating either a first line of therapy (LOT1), or a second-line or subsequent LOT (LOT≥2). The goal of this analysis was to assess potential predictors of death occurring within 18 months following initiation of frontline therapy (LOT1). Because CLL usually presents as an indolent disease associated with a prolonged clinical course, we chose to define early mortality as any death occurring ≤ 18 months following enrollment. Univariate logistic regression was performed against potential predictor variables including several clinical characteristics and comorbid conditions, race, treatment (Tx) site, insurance type, geographic region, presence of prior malignancies, genetic prognostic factors (FISH and cytogenetics) at enrollment, cell surface markers (Zap70, CD38), reasons for Tx initiation and Tx choice for LOT1 (BR or FCR). IgVH mutation status and genetic mutations (P53, Notch1, etc.) were not included as these tests were not readily performed in community practice. Predictors that were found to be significant at the 0.15 significance level were included in the multivariable logistic regression using a stepwise variable selection process, to identify factors associated with early mortality.

Results

1344 pts completed 18 months of follow-up (n=1111) or died (n=233) within the first 18 months of study enrollment. Of these, 801 pts were enrolled in LOT1 (median time from diagnosis to LOT1 was 1.3 yrs; IQR, 0.1-3.7 yrs). 82 of 801 pts (10.2%) died within 18 months of LOT1 initiation; 41% of pts with available clinical information who died, were defined as early-stage (Rai stage 0-1). Of 26 potential predictors evaluated, 12 were associated with early mortality among LOT1 pts at the 0.15 significance level in univariate analyses including site, race, age>75, CD-38, del(17p), ECOG PS, CCI group, RAI stage, creatinine clearance, insurance status, reasons for Tx initiation, anemia and lymphocytosis. In multivariable logistic regression analyses we identified 4 independent predictors of mortality within 18 months of LOT1 initiation (Table): pt age, CD38 expression, baseline decreased hemoglobin (as a reason for Tx initiation), and race.

Conclusions

In CLL pts with Rai stage 0-1, we have identified 4 factors which are associated with increased risk of death within 18 months of initiation of frontline therapy. Interestingly, neither choice of FCR vs BR chemoimmunotherapy nor the presence of del(17p)/del(11q) were predictors of early mortality. Using these results, we are currently designing a model to predict early mortality in early-stage pts. Once validated, these results may provide a framework for trials targeting the "early stage, symptomatic" CLL pts for novel interventions.

Table. Multivariable Analysis: Predictors of Early Mortality Odds ratio estimate 95% CI P -value LOT1, n=781 Age ≥75 years, yes vs no 2.2 1.4-3.5 0.0012 CD38 expression, positive vs negative/not specified 1.8 1.1-2.9 0.0182 Anemia as reason for treatment, yes vs no 2.1 1.3-3.4 0.0040 Race, other vs Caucasian 1.9 1.0-3.8 0.0501

Disclosures

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