Effects of Comorbid Disease on Pre-treatment Neurobehavioral Functioning. Sunita K. Patel, PhD Assistant Professor. City of Hope Medical Center

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1 Effects of Comorbid Disease on Pre-treatment Neurobehavioral Functioning. Sunita K. Patel, PhD Assistant Professor City of Hope Medical Center Duarte, California.

2 Pre-Chemotherapy e e apycognitive Functioning Neurocognitive dysfunction in survivors of breast cancer is primarily attributed to the effects of chemotherapy and/or hormonal therapy. However, more recent studies suggest these symptoms are present even prior to adjuvant treatments. Initially reported in the first prospective trial that assessed pts prior to chemo rather than only after treatment (Wefel et al., Cancer, 2004). In this study of breast cancer pts, 33% showed neurocognitive deficits prior to starting chemo. The presence of low scores in about 30% at pre-chemo has since been replicated with larger N = 101 (Hermelink et al., Cancer 2007). The reasons for cognitive problems in cancer patients prior to treatment are not known. Possible mechanisms underlying effects for both prior treatment, and for the dysfunction observed following treatment, have been postulated.

3 Proposed Mechanisms for Cognitive Changes. Blood-brain barrier integrity Genetic susceptibility Changes in cognition, and brain structure and function DNA damage and telomere length Oestrogen or testosterone reduction Cytokine deregulation Ahles and Saykin, Nature Reviews Cancer, 7, 2007

4 Study Objective and Background We hypothesized that comorbid health status at cancer diagnosis is associated with lowered neurocognitive and behavioral functioning prior to initiation of cancer treatment. This was based on the literature linking cognitive and behavioral dysfunction with various non-cancer health/disease conditions. Type 1 and Type 2 diabetes have been associated with neurocognitive compromise (Review article: Kodl et al., 2008). There is an increased incidence of dementia in pts with Type 2 (Cukierman et al., 2005) Elevated blood pressure is a risk factor for vascular dementia and decline of cognitive function in middle age and older patients (Papademetriou, 2005). Treating HTN lessens the cognitive complications only 34% of hypertensive Americans have their hypertension under control, despite widespread treatment (Papademetriou, 2005).

5 Methods Used data from an ongoing study tracking various outcomes in newly diagnosed breast cancer pts. across two years. In the larger study, post-menopausal women newly diagnosed with breast cancer are seen for neurobehavioral assessment prior to any treatment, including surgery. We used the baseline assessment data to evaluate the impact of a co- morbid health condition on neurobehavioral functioning i prior to any treatment. Results are based on 176 post-menopausal breast cancer patients for whom we have pre-treatment data.

6 Eligibility Criteria for the Larger Study Newly diagnosed breast cancer, stages 0-III (excludes stage IV) Post-menopausal status as defined by self-report of no menstruation for 12 months or longer No previous history of cancer diagnosis in the past 5 years. No neurological or severe psychiatric disorders. No use of substances known to be active in the CNS (e.g. narcotics, anti-emetics,) within 2 weeks of baseline data collection. Ability to read and/or comprehend English at a 3rd grade reading level No history of infection within past 2 weeks and no fever at evaluation No history of infection within past 2 weeks and no fever at evaluation time.

7 Study Measures Neurocognitive Self-report Other Objective i neurocognitive tests administered by a trained examiner. Tests selected from recommended battery to use in research with cancer patients (Vardy et al.) Brief Symptom Inventory (BSI; Derogatis, 2004). Behavior Rating Inventory of Executive Functioning (BRIEF; Roth et al., 2005) Fatigue Symptom Inventory (FSI; Moffitt Cancer Center, 1998) MOS-SF36 Physical Health and Social lsupport scales (Ware et al.1992) Functional Activities Questionnaire (FAQ; Pfeffer 1982) Demographic/Lifestyle Q Blood draw for biomarkers. Detailed review of patient s medical records. Charlson Comorbidity Index scale (Extermann 2000).

8 Charlson Comorbidity o Index (Extermann, 2000) Charlson Comorbidity Index Assigns point value to conditions depending on relative risk of death. Overall score is the sum of all the points assigned to a patient s comorbid health conditions. The original Charlson index did not assign any points to Hypertension. The augmented Charlson Index assigns 1 point to HTN (Braithwaite et al., 2009). Co-morbid Point Assignments Assigned Point Value 1 2 Condition History of myocardial infarction Congestive heart failure Peripheral vascular disease Cerebrovascular disease Dementia Chronic pulmonary disease Connective tissue disease Ulcer disease Mild liver disease Diabetes (without complications) Hypertension Diabetes (with end organ damage) Hemiplegia Moderate or severe renal disease Any solid tumor (non-metastatic) Leukemia Lymphoma For the current presentation, we used the HTN augmented Charlson Metastatic solid tumor Index 6 AIDS 3 Moderate or severe liver disease

9 Demographic Characteristics Age Mean=6059 =60.59, SD=71 =7.1, Range=4584yrs =45-84yrs % % % % % Education < High school 27.3% > High school 68.8% Income < $45, % $45,001 - $75, % > $75, % Race White/Caucasian 65% Other 35% Sample Characteristics (N = 176) Cancer Stage Cancer Characteristics O 12.5% I 41.5% II 26.2% III 91% 9.1% Estrogen Hormone Receptor Status Positive 72.2% Negative 18.8% Progesterone Hormone Receptor Status Positive 63.1% Negative 27.8% Body Mass Index (BMI) Underweight (<18.5) 0.6% Normal ( ) 30.1% Overweight (25-30) 29.5% Obese (>30) 34.1%

10 Methods The validated Charlson Comorbidity Index was calculated for each patient using medical records to represent baseline comorbid disease conditions. Statistical analyses were conducted using the presence versus absence of a qualifying comorbid condition as the independent variable, and neurobehavioral scores as dependent variables. A total t of 91(52%) women in our sample had at least one qualifying i comorbidity, while 85 women (48%) did not have a comorbid health condition. The comorbid and No comorbid groups were similar in education, social support, and cancer stage. The mean age in the comorbid group was 62 years vs. 59 years.

11 Comorbidity Characteristics of the Study Sample Comorbidity in study sample N % Cardiovascular Dysfunction Peripheral Vascular Disease 0 0 Cerebrovascular Disease 0 0 Dementia 0 0 Chronic Pulmonary Disease Connective Tissue Disease Ulcer Disease Mild Liver Disease Diabetes Hemiplegia 0 0 Moderate or Severe Renal Disease Lymphoma Moderate or Severe Liver Disease AIDS 0 0 Hypertension Pervious Cancer 5 2.8

12 Cognitive Measures Verbal Learning and memory assessed by: Hopkins Verbal Learning Test (HVLT; Brandt, 1991). Attention/working memory assessed by: WAIS-IV (Pearson, 2008). Digit Span Sequencing subtests Executive functioning assessed by: D-KEFS subtests t (Pearson, 2001) Trails 4 Switching test Letter Fluency Category Switching Color Word Inhibition & Inhibition Switching Behavior Rating Inventory of Executive Functioning (Roth et al., 2005)

13 Cognitive Measures (continued) Processing Speed assessed by: WAIS-IV Processing Speed Index (Pearson, 2008) Delis-Kaplan Executive Functioning System (D-KEFS; Pearson, 2001) Trail Making Test 2 Color Word Naming Color Word dreading Fine motor coordination and speed is assessed by: Grooved Peg Board (Matthews & Klove, 1964) Estimate of pre-morbid IQ is assessed by: Wide Range Achievement Test-IV (WRAT4; Wilkinson & Robertson 2006) Reading subtest. t

14 ANCOVA Results: Significant Differences on Processing Speed (controlled for age and education) Processing Speed No Comorbidity Comorbidity WAIS Processing DKEFS Color Word Grooved Pegboard Speed Reading F(1, 142) = 9.30 F(1, 155) = 3.82 F(1, 122) = 6.81 p =.003 p =.05 p =.01 Performance scores presented in T-score measurement (M = 50, SD = 10)

15 ANCOVA results: Significant Differences on Executive Functioning (controlled for age and education) 12 Executive Functioning Trails 4 Inhibition Inhibition Switching No Comorbidity Comorbidity F(1, 149) = 6.33 F(1, 154) = 4.23 F(1, 154) = 4.26 p =.01 p =.04 p =.041 Performance scores presented in scaled score measurement (M = 10, SD = 3)

16 ANCOVA: Sig Differences on Self-report of Cognitive Dysfunction. 60 BRIEF No Comorbidity Comorbidity Global Executive Metacognition Behavioral Regulation F(1, 155) = F(1, 155) = F(1, 157) = p <.001 p <.001 p <.001 T-score measurement (M = 50, SD = 10)

17 ANCOVA Results: Sig. Differences on Brief Symptom Inventory 58 Brief Symptom Inventory No Comorbidity Comorbidity 46 BSI Somatic BSI Depression BSI Anxiety F(1, 158) = 5.73 F(1, 158) = 8.48 F(1, 158) = 2.72 p =.02 p =.004 p =.10

18 ANCOVA: Significant ifi Differences in Self-report of ffatigue Fatigue Symptom Inventory FSI Disruption Index No Comorbidity Comorbidity F(1, 137) = p =.001

19 ANCOVA: Sig Differences in Self-report of Functional Status. t Functional Activities Functional Activities No Comorbidity Comorbidity F(1, 161) = 8.78 p =.004

20 ANCOVA: Sig Differences in Self-report of Physical Health. SF36 Physical Health Scale Physical Health No Comorbidity Comorbidity F(1, 129) = 9.65 p =.002 Mean in the normative sample = 84.42, SD = 23.3

21 Sig. Differences in Interleukin log 6 in a subsample of 120 patients (controlled for age and education). IL IL No Comorbidity Comorbidity F(1, 114) = 9.15 p =.003

22 No sig. differences in IL6 when BMIh held as a covariate. No comorbidity group: BMI Mean = (SD: 5.17) Comorbidity group: BMI Mean = (SD: 6.85) IL IL No Comorbidity Comorbidity F(1, 110) = p =.10

23 Summary of findings Post-menopausal breast cancer patients with health comorbidies have lowered neurocognitive performance even prior to any cancer treatment compared to those without a comorbid health condition. Differences found on measures of executive functioning and processing speed, but not on tests of verbal learning and memory, working memory, language, or estimated intelligence. Breast cancer patients with at least one health comorbidity also self- reported greater behavioral symptoms/dysfunction. The majority of these differences are not of a magnitude to be viewed as clinically ca significant since mean scores for both groups were e mostly within normal limits. However, these findings do suggest comorbid health conditions impact neurobehavioral symptoms and should be methodologically considered in cognition-related cancer research. Certainly, the contribution of comorbidity in predicting treatment-related changes in cancer patients should ldbe considered. d

24 Acknowledgments Collaborators & Research Staff: Arpine Davtyan, Ellis Beier, Krystle Barrera, Andrew Wong, Adrienne Meier, Lennie Wong, Arti Hurria Elizabeth Breen Michael Irwin Smita Bhatia. Grant Funding: NCI R21CA ACS RSG CPPB

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