EHA Library - The official digital education library of European Hematology Association (EHA)

CLINICAL EPIDEMIOLOGY OF CLL AND CYTOGENETIC ABNORMALITIES: ASSOCIATION OF UNIQUE EPIDEMIOLOGIC EXPOSURES WITH 17P OR 11Q DELETION IN NEWLY-DIAGNOSED CLL
Author(s): ,
James M Foran
Affiliations:
Division of Hematology & Medical Oncology,Mayo Clinic Cancer Center,Jacksonville,United States
,
Megan M O'Byrne
Affiliations:
Department of Health Sciences Research,Mayo Clinic,Rochester,United States
,
Asher A Chanan-Khan
Affiliations:
Division of Hematology & Medical Oncology,Mayo Clinic Cancer Center,Jacksonville,United States
,
Jose F Leis
Affiliations:
Division of Hematology & Medical Oncology,Mayo Clinic Cancer Center,Phoenix,United States
,
Neil E Kay
Affiliations:
Division of Hematology,Mayo Clinic,Rochester,United States
,
Daniel L Van Dyke
Affiliations:
Cytogenetics Laboratory,Mayo Clinic,Rochester,United States
,
James R Cerhan
Affiliations:
Department of Health Sciences Research,Mayo Clinic,Rochester,United States
,
Tait D Shanafelt
Affiliations:
Division of Hematology,Mayo Clinic,Rochester,United States
Susan L Slager
Affiliations:
Department of Health Sciences Research,Mayo Clinic,Rochester,United States
(Abstract release date: 05/19/16) EHA Library. Foran J. 06/09/16; 132603; E1054 Disclosure(s): No relevant disclosures
Dr. James M Foran
Dr. James M Foran
Contributions
Abstract
Abstract: E1054

Type: Eposter Presentation

Background
Clinical epidemiologic exposures associated with risk of developing CLL have been described in large case-control studies, including allergy, some autoimmune diseases, obesity, medical and family history, and some occupational exposures including rural/farm habitat. However, it is not known whether specific exposures are associated with a unique disease phenotype, and specifically whether risk factors for development of CLL are themselves associated with adverse cytogenetic profile by FISH, namely del(11q) and del(17p).

Aims
Primary Aim: To determine whether common clinical epidemiologic exposures associated with development of CLL are associated with a unique cytogenetic profile as determined by FISH at the time of diagnosis, and specifically which CLL risk factors are associated with adverse FISH profile [del(11q) and del(17p), either alone or in combination with other abnormalities]

Methods
We used cases from the Mayo Clinic Case-Control Study of Lymphoma, annotated with molecular markers from the Mayo Clinic CLL database to evaluate associations of medical history, lifestyle, family history, and farming history in a case-only study of the risk 17p or 11q deletion in CLL patients. Newly diagnosed CLL patients were enrolled between 2002 and 2012, and weight was patient-reported from 2 years prior to diagnosis. Unconditional logistic regression was used to estimate Odds Ratios (ORs) and 95% Confidence Intervals (CI) for risk adverse FISH profile (11q or 17p deletion). A significance level of 5% was used to determine statistical significance. 

Results
We included n=683 patients, of whom n=100 had 11q or 17p deletions. Results of the analysis are noted in the Table.We observed a significant association of rheumatoid arthritis with adverse FISH profile (11q or 17p deletion) at diagnosis (OR=2.49, 95% CI 1.06-5.86, p=0.037). In contrast, we observed a significant inverse relationship of any Allergy (Food, Plant, Animal, Insect, Dust, Mold) (OR=0.59, 95% CI 0.36-0.96, p=0.035) and of Atopy (OR 0.63, 95% CI 0.40-0.99, p=0.045) with adverse FISH profile. Other common exposures including obesity, smoking, and farm exposures were not associated with high risk FISH profile. Similarly, family history was also not associated with an adverse FISH profile, consistent with earlier reports.

Conclusion
Some clinical epidemiologic risk factors (allergy, atopy and rheumatoid arthritis) associated with the development of CLL are themselves significantly associated with specific disease-related cytogenetic abnormalities as determined by FISH profile at diagnosis. This suggests that some CLL risk factors may be associated with a unique clinical and genetic phenotype, which may influence disease biology and prognosis after diagnosis. Specific exposures that appear to mediate disease risk through alternate pathways of immune stimulation (i.e. allergy and atopy vs. rheumatoid arthritis) are associated with a significantly different cytogenetic risk profile at diagnosis, suggesting that they likely have unique mechanisms of leukemogenesis. Further studies are ongoing to determine the impact of CLL epidemiologic risk factors on clinical outcome in association with other clinical and biological prognostic factors at diagnosis.



Session topic: E-poster

Keyword(s): Chronic lymphocytic leukemia, Epidemiology, FISH
Abstract: E1054

Type: Eposter Presentation

Background
Clinical epidemiologic exposures associated with risk of developing CLL have been described in large case-control studies, including allergy, some autoimmune diseases, obesity, medical and family history, and some occupational exposures including rural/farm habitat. However, it is not known whether specific exposures are associated with a unique disease phenotype, and specifically whether risk factors for development of CLL are themselves associated with adverse cytogenetic profile by FISH, namely del(11q) and del(17p).

Aims
Primary Aim: To determine whether common clinical epidemiologic exposures associated with development of CLL are associated with a unique cytogenetic profile as determined by FISH at the time of diagnosis, and specifically which CLL risk factors are associated with adverse FISH profile [del(11q) and del(17p), either alone or in combination with other abnormalities]

Methods
We used cases from the Mayo Clinic Case-Control Study of Lymphoma, annotated with molecular markers from the Mayo Clinic CLL database to evaluate associations of medical history, lifestyle, family history, and farming history in a case-only study of the risk 17p or 11q deletion in CLL patients. Newly diagnosed CLL patients were enrolled between 2002 and 2012, and weight was patient-reported from 2 years prior to diagnosis. Unconditional logistic regression was used to estimate Odds Ratios (ORs) and 95% Confidence Intervals (CI) for risk adverse FISH profile (11q or 17p deletion). A significance level of 5% was used to determine statistical significance. 

Results
We included n=683 patients, of whom n=100 had 11q or 17p deletions. Results of the analysis are noted in the Table.We observed a significant association of rheumatoid arthritis with adverse FISH profile (11q or 17p deletion) at diagnosis (OR=2.49, 95% CI 1.06-5.86, p=0.037). In contrast, we observed a significant inverse relationship of any Allergy (Food, Plant, Animal, Insect, Dust, Mold) (OR=0.59, 95% CI 0.36-0.96, p=0.035) and of Atopy (OR 0.63, 95% CI 0.40-0.99, p=0.045) with adverse FISH profile. Other common exposures including obesity, smoking, and farm exposures were not associated with high risk FISH profile. Similarly, family history was also not associated with an adverse FISH profile, consistent with earlier reports.

Conclusion
Some clinical epidemiologic risk factors (allergy, atopy and rheumatoid arthritis) associated with the development of CLL are themselves significantly associated with specific disease-related cytogenetic abnormalities as determined by FISH profile at diagnosis. This suggests that some CLL risk factors may be associated with a unique clinical and genetic phenotype, which may influence disease biology and prognosis after diagnosis. Specific exposures that appear to mediate disease risk through alternate pathways of immune stimulation (i.e. allergy and atopy vs. rheumatoid arthritis) are associated with a significantly different cytogenetic risk profile at diagnosis, suggesting that they likely have unique mechanisms of leukemogenesis. Further studies are ongoing to determine the impact of CLL epidemiologic risk factors on clinical outcome in association with other clinical and biological prognostic factors at diagnosis.



Session topic: E-poster

Keyword(s): Chronic lymphocytic leukemia, Epidemiology, FISH

By clicking “Accept Terms & all Cookies” or by continuing to browse, you agree to the storing of third-party cookies on your device to enhance your user experience and agree to the user terms and conditions of this learning management system (LMS).

Cookie Settings
Accept Terms & all Cookies