Journals of Gerontology: MEDICAL SCIENCES, 2015, 729–735 doi:10.1093/gerona/glt195 Research Article Advance Access publication December 24, 2013
Translational
Translational Article Special Section on Cancer and Aging Research article
Self-Reported History of Chemotherapy and Cognitive Decline in Adults Aged 60 and Older: The PATH Through Life Project Kaarin J. Anstey,1 Kerry Sargent-Cox,1 Nicolas Cherbuin,1 and Perminder S. Sachdev2 Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, Australia. Centre for Healthy Brain Ageing, The University of New South Wales, Sydney, Australia.
1 2
Address correspondence to Kaarin J. Anstey, PhD, Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra ACT 0200, Australia. Email: [email protected]
Abstract Background. There is a lack of data from cohort studies assessing cognitive function prior to and after chemotherapy. We evaluated the effect of self-reported cancer chemotherapy on cognitive function in a cohort assessed at baseline, 4 and 8 years. Methods. Participants were from the population-based PATH Through Life Study. Of the 2,551 participants aged 60–64 at baseline without cognitive impairment, 1,949 completed wave 3 and had data on cancer and chemotherapy and cognitive function. Linear mixed models were used to analyze the data. Results. At wave 3, participants reporting history of chemotherapy (n = 76) had lower scores on memory, processing speed, and executive function compared with those reporting cancer without chemotherapy (n = 289) and no cancer history (n = 1508). After adjustment for depression and disability, effects remained for processing speed and memory. Chemotherapy prior to the study commencement (n = 24), but not between waves 1 and 3 (n = 81), was associated with greater decline in delayed recall (β = −.21 [95% CI −0.38, −.03], p = .02) and digits backwards β = −.05 [95% CI −0.09, −.01], p = .02) over 8 years compared with those with no cancer history (n = 1562). Women reporting chemotherapy for breast cancer after wave 1 (n = 26) had slower choice reaction time (−0.81 (95% CI −1.28, −0.34), p = .001) but did not decline faster on this measure compared with those reporting no breast cancer history (n = 818). Conclusions. Results suggest chemotherapy prior to old age is associated with faster decline in memory in late life but that it does not affect decline in other domains of cognitive function. Key Words: Cancer—Mild cognitive impairment—Cognitive decline—Epidemiology—Longitudinal study. Decision Editor: Stephen Kritchevsky, PhD
The lifetime prevalence for cancer at any site for males is 44.81% and for females is 38.17% (1). In 2012, it was estimated that in
the United States alone there are approximately 9.7 million cancer survivors aged 60 and older, and a large proportion would have
© The Author 2013. Published by Oxford University Press on behalf of the Gerontological Society of America. All rights reserved. For permissions, please email: [email protected]
729
730
experienced chemotherapy (2). The long-term impact of chemotherapies on health and quality of life is an issue relevant to large numbers of aging adults. Cross-sectional and case–control studies have shown that patients receiving adjuvant chemotherapy for breast cancer and gynecologic cancer have poorer cognitive function (3–6) although some studies have reported effects to be subtle and more likely due to aspects of cancer diagnosis such as distress and physical disability (7). Only a few longitudinal cohort studies have evaluated the association between chemotherapy and dementia or cognitive decline. A recent report from the U.S. Health and Retirement Study using linked Medicare data found no cognitive decline associated with chemotherapy in patients with breast and colorectal cancer (8), but the only cognitive measure available in this study was the Telephone Interview for Cognitive Status, a brief screening instrument for dementia, which has ceiling effects and is not designed to measure cognitive decline. Another cohort study reported older women who received adjuvant chemotherapy for breast cancer were not at increased risk of dementia (9). Similar results were found in a large cohort (n = 72,374) of patients with history of chemotherapy for colorectal cancer. Using data linkage to establish future diagnosis of dementia, analyses showed that chemotherapy was associated with increased risk of Medicare claims for ICD-9-coded drug-induced persistent dementia but not with Medicare claims for other dementia types such as Alzheimer’s disease or vascular dementia (10). We identified no previous cohort studies evaluating cognitive function using psychometric measures likely to be more sensitive to cognitive change and that have been administered on multiple occasions. In this study, we evaluate the cognitive function cross-sectionally and longitudinally to determine whether self-report of receiving any type of chemotherapy for cancer was associated with poorer cognitive function and faster cognitive decline. Cancer subtype– specific analyses could only be conducted for breast cancer because of the low prevalence of other cancers within the sample. Analyses were adjusted for demographics, disability, and depression as these differed between the cancer and noncancer groups, and the effect of apolipoprotein E (APOE) was evaluated (11). Based on reviews of the literature (12), we hypothesized that history of chemotherapy would increase rate of cognitive decline in processing speed, memory, and reaction time and show effects on executive function (longitudinal data on executive function were not available).
Method Selection and Description of Participants The sample came from oldest cohort of the Personality and Health Through Life (PATH) Through Life Project, a large community survey of adults from Canberra and the neighboring town of Queanbeyan, New South Wales, Australia (13) that was established to evaluate mental health, cognition, and substance use. The sample aged 60–64 years at baseline was recruited from electoral rolls as electoral roll registration is compulsory for Australian citizens. At wave 1, 2,551 participants were assessed. Of those, 2,222 were reassessed 4 years later at wave 2 and 1,973 were reassessed after 8 years at wave 3. Participants were excluded from all analyses if they did not complete questionnaires on cancer and chemotherapy history. Cross-sectional models (wave 3) also excluded those with a MiniMental State Examination (MMSE) score less than 24 at wave 3 (n = 100), leaving a sample of 1,873. This comprised 1,508 participants without history of cancer, 289 reporting cancer and no chemotherapy, and 76 with cancer and chemotherapy. Participants were excluded from longitudinal analysis if MMSE at wave 1 was less than 24 (n = 24), leaving a sample of 1,949. This longitudinal sample consisted of 1,562 participants without history
Journals of Gerontology: MEDICAL SCIENCES, 2015, Vol. 70, No. 6
of cancer, 306 reporting history of cancer but not chemotherapy, and 81 reporting history of both cancer and chemotherapy. Most of the interview was self-completed on a laptop computer. A trained interviewer administered cognitive tests and physical tests, including a cheek swab from which DNA could be extracted. The study received approval from the Australian National University’s Human Research Ethics Committee.
Measures Components of the data collection relevant to the present article are described in the following sections. History of cancer and chemotherapy At each wave, participants were asked if they had ever been diagnosed with cancer (yes/no). At wave 3, a detailed questionnaire regarding cancer diagnosis and treatment was administered providing information on diagnosis of type of cancer including leukemia, melanoma, and lung, breast, uterus, ovary, stomach, colon, small bowel, lymph nodes, and other cancers. For each type of cancer, data were collected on type of treatment received including surgery (yes/ no), radiation (yes/no), and chemotherapy (yes/no). Finally the year of treatment was recorded. To establish reliability of the self-report cancer diagnoses, the distribution of total number of cancer diagnoses for the cohort was compared with de-identified data obtained from the Australian National Cancer registry. There was no difference in the frequency of cancer reported in the cohort with that recorded on official records χ2 (1) = 2.158, p = .142). Cognition Cognitive function was assessed using the following tasks at each wave. Spot-the-Word was used to assess verbal ability. Participants choose the real words from 60 pairs of words and nonsense words (14). Processing speed was assessed with the Symbol-Digit Modalities Test (SDMT) (15), which requires participants to find in a key the digit corresponding to a specific symbol and to complete as many symbol-digit pairs as possible in 90s. Episodic memory was assessed with the first trial of the California Verbal Learning Test (16), which involves recalling a list of 16 nouns. The interval between immediate and delayed recall was occupied by a test of grip strength. Working memory was assessed using the Digits Backwards subtest of the Wechsler Memory Scale (17). Simple and choice reaction time (SRT and CRT) were administered using a small box, with left and right buttons at the top to be depressed by the index fingers on appearance of a light. Mean SRT was the average of four blocks of 20 trials. Mean CRT was the average of two blocks of 20 trials. At wave 3, two tests were added. Trails B is a test of executive function involving cognitive-motor speed and task-switching ability. Participants are instructed to draw lines to connect an alternating sequence (1-A-2-B etc.) (18). For verbal fluency, participants were asked the name as many words as they could in 60 seconds starting with the letter “F” and again with “C” (19). Self-reported memory function At waves 1 and 2, participants were asked “Do you feel you can remember things as well as you used to? That is, is your memory the same as it was earlier in life? If no, then “Does this memory problem interfere in any way with your day to day life? And have you seen a doctor about your memory?” Covariates Education at baseline was constructed using a series of items that asked participants to indicate their highest level of completed education. Smoking status was derived from questions on current and
Journals of Gerontology: MEDICAL SCIENCES, 2015, Vol. 70, No. 6
past smoking habits. Depression was measured with the PRIME-MD Patient Health Questionnaire, which asks about DSM-IV major depressive symptoms in the past 2 weeks (20). This questionnaire was scored to give a continuous scale from 0 to 27. The SF-12 Physical Component Summary (PCS-12) was used to measure physical disability using the Research and Development scoring (RAND12) scoring (21,22). Apolipoprotein E e4 allele (APOE*E4) genotype was assessed by TaqMan assays (Applied Biosystems) from DNA extracted from buccal swabs (23).
Statistical Analysis Cross-sectional analyses at wave 3 comparing participants who had reported chemotherapy with participants who had not were conducted with generalized linear models that adjusted first for demographics and second for depression and disability. Linear mixed models were used to estimate the association between self-reported chemotherapy and cancer status and overall cognitive function at the three occasions of measurement, as well as decline in cognitive function. To examine the before and after effects of chemotherapy on trajectories of cognitive function, as well as the long-term effects of chemotherapy, chemotherapy and cancer status was coded: chemotherapy on or prior to wave 1 (n = 24), chemotherapy after wave 1, i.e., between wave 1 and 3 (n = 57, consisting of wave 1 to wave 2 [n = 47] + wave 2 to wave 3 [n = 10]), cancer with no chemotherapy treatment (n = 306), and no cancer reported (n = 1562). Subgroup mixed models analyses were conducted for breast cancer as this was the only cancer type with high enough prevalence. The effect of APOE genotype was evaluated despite small cell sizes. Analyses were conducted in IBMSPSS 20 and STATA 11.
Results Compared with those lost to follow-up or for whom self-reported chemotherapy data were not available at wave 3, the sample for this
731
study had lower levels of baseline depression (t (2,537) = −5.60, p < .001), higher MMSE scores (t (2,533) = 9.38, p < .001), and less disability (t (2,539) = 7.71, p < .001). No differences were found in years of education (t (2421) = −8.40, p = .061), or gender distribution (χ2 (1) = .018, p = .895). Table 1 shows descriptive characteristics at wave 3 assessment for those who reported a lifetime treatment of chemotherapy for cancer (n = 81), those reporting history of cancer but not chemotherapy (n = 306), and those reporting no history of chemotherapy or cancer (n = 1562). Those with history of chemotherapy had significantly higher levels of physical disability than those without chemotherapy exposure. Of the 306 individuals reporting some type of cancer history, the majority (79.1%) also reported not having chemotherapy as treatment (χ2 (1) = .296.71, p < .001). The different types of cancers reported are reported online (see Supplementary Table E1).
Cross-Sectional Analysis of Cognitive Function and History of Chemotherapy There were no differences at wave 1 between participants with no history of cancer or chemotherapy, participants with history of chemotherapy prior to wave 1 or after wave 1, or participants with cancer but no chemotherapy after wave 1 on immediate recall, delayed recall, or digits backwards (Supplementary Table E2). Significant differences in baseline scores were found for SDMT (F (3,1963) = 4.466, p = .004), SRT (F (3,1935) = 3.938, p = .008), and CRT (F (3,1921) = 4.572, p = .003). Post hoc tests revealed that compared with those who did not have cancer at any time, those reporting chemotherapy and cancer prior to wave 1 had lower SDMT scores at baseline, and those reporting cancer and chemotherapy after wave 1 had slower CRT at baseline. For SRT, those reporting cancer with chemotherapy prior to wave 1 had slower baseline SRT than those reporting cancer with no chemotherapy. At wave 3, after adjusting for age, gender, education, and cancer history (Model 1, Table 2) participants reporting experience of any
Table 1. Characteristics of the Sample That Persisted to Wave 3 by Cancer and Chemotherapy Status (N = 1949)
Male Age (M, SD) Years education (M, SD) Diabetes Heart condition Hypertension Alcohol intake Abstain/occasional Light/medium Hazardous/harmful Smoking status Never smoked Past smoker Current smoker Waist circumference (M, SD) Depression (M, SD) SF-12 physical health (M, SD) Spot-the-word APOE genotype ɛ4−/ɛ4− ɛ4+/ɛ4− ɛ4+/ɛ4+
No Cancer; N = 1562
Cancer + Chemo; N = 81
Cancer No Chemo; N = 306
50.1% 70.58 (1.49) 14.03 (2.68) 12.9% 20.2% 62.5%
44.4% 70.58 (1.54) 13.95 (2.73) 18.5% 23.5% 61.2%
60.5% 70.75 (1.53) 14.38 (2.64) 15.0% 21.9% 62.7%
.002 .184 .116 .247 .655 .971
29.0% 66.9% 4.1%
27.2% 70.4% 2.5%
25.8% 69.0% 5.2%
.621
54.8% 39.8% 5.3% 95.98 (13.54) 2.30 (2.88) 47.33 (10.29) 53.27(4.96)
58.0% 38.3% 3.7% 95.51 (15.30) 3.68 (3.30) 42.04 (12.13) 52.25(4.66)
52.0% 42.5% 5.6% 97.86 (13.01) 2.48 (2.89) 46.73 (10.13) 53.74(4.66)
.822
73.5% 24.6% 1.9%
64.1% 32.1% 3.8%
73.6% 26.4% 0.0%
p Value
.087
Translational
Translational Article Special Section on Cancer and Aging Research article
Self-Reported History of Chemotherapy and Cognitive Decline in Adults Aged 60 and Older: The PATH Through Life Project Kaarin J. Anstey,1 Kerry Sargent-Cox,1 Nicolas Cherbuin,1 and Perminder S. Sachdev2 Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra, Australia. Centre for Healthy Brain Ageing, The University of New South Wales, Sydney, Australia.
1 2
Address correspondence to Kaarin J. Anstey, PhD, Centre for Research on Ageing, Health and Wellbeing, The Australian National University, Canberra ACT 0200, Australia. Email: [email protected]
Abstract Background. There is a lack of data from cohort studies assessing cognitive function prior to and after chemotherapy. We evaluated the effect of self-reported cancer chemotherapy on cognitive function in a cohort assessed at baseline, 4 and 8 years. Methods. Participants were from the population-based PATH Through Life Study. Of the 2,551 participants aged 60–64 at baseline without cognitive impairment, 1,949 completed wave 3 and had data on cancer and chemotherapy and cognitive function. Linear mixed models were used to analyze the data. Results. At wave 3, participants reporting history of chemotherapy (n = 76) had lower scores on memory, processing speed, and executive function compared with those reporting cancer without chemotherapy (n = 289) and no cancer history (n = 1508). After adjustment for depression and disability, effects remained for processing speed and memory. Chemotherapy prior to the study commencement (n = 24), but not between waves 1 and 3 (n = 81), was associated with greater decline in delayed recall (β = −.21 [95% CI −0.38, −.03], p = .02) and digits backwards β = −.05 [95% CI −0.09, −.01], p = .02) over 8 years compared with those with no cancer history (n = 1562). Women reporting chemotherapy for breast cancer after wave 1 (n = 26) had slower choice reaction time (−0.81 (95% CI −1.28, −0.34), p = .001) but did not decline faster on this measure compared with those reporting no breast cancer history (n = 818). Conclusions. Results suggest chemotherapy prior to old age is associated with faster decline in memory in late life but that it does not affect decline in other domains of cognitive function. Key Words: Cancer—Mild cognitive impairment—Cognitive decline—Epidemiology—Longitudinal study. Decision Editor: Stephen Kritchevsky, PhD
The lifetime prevalence for cancer at any site for males is 44.81% and for females is 38.17% (1). In 2012, it was estimated that in
the United States alone there are approximately 9.7 million cancer survivors aged 60 and older, and a large proportion would have
© The Author 2013. Published by Oxford University Press on behalf of the Gerontological Society of America. All rights reserved. For permissions, please email: [email protected]
729
730
experienced chemotherapy (2). The long-term impact of chemotherapies on health and quality of life is an issue relevant to large numbers of aging adults. Cross-sectional and case–control studies have shown that patients receiving adjuvant chemotherapy for breast cancer and gynecologic cancer have poorer cognitive function (3–6) although some studies have reported effects to be subtle and more likely due to aspects of cancer diagnosis such as distress and physical disability (7). Only a few longitudinal cohort studies have evaluated the association between chemotherapy and dementia or cognitive decline. A recent report from the U.S. Health and Retirement Study using linked Medicare data found no cognitive decline associated with chemotherapy in patients with breast and colorectal cancer (8), but the only cognitive measure available in this study was the Telephone Interview for Cognitive Status, a brief screening instrument for dementia, which has ceiling effects and is not designed to measure cognitive decline. Another cohort study reported older women who received adjuvant chemotherapy for breast cancer were not at increased risk of dementia (9). Similar results were found in a large cohort (n = 72,374) of patients with history of chemotherapy for colorectal cancer. Using data linkage to establish future diagnosis of dementia, analyses showed that chemotherapy was associated with increased risk of Medicare claims for ICD-9-coded drug-induced persistent dementia but not with Medicare claims for other dementia types such as Alzheimer’s disease or vascular dementia (10). We identified no previous cohort studies evaluating cognitive function using psychometric measures likely to be more sensitive to cognitive change and that have been administered on multiple occasions. In this study, we evaluate the cognitive function cross-sectionally and longitudinally to determine whether self-report of receiving any type of chemotherapy for cancer was associated with poorer cognitive function and faster cognitive decline. Cancer subtype– specific analyses could only be conducted for breast cancer because of the low prevalence of other cancers within the sample. Analyses were adjusted for demographics, disability, and depression as these differed between the cancer and noncancer groups, and the effect of apolipoprotein E (APOE) was evaluated (11). Based on reviews of the literature (12), we hypothesized that history of chemotherapy would increase rate of cognitive decline in processing speed, memory, and reaction time and show effects on executive function (longitudinal data on executive function were not available).
Method Selection and Description of Participants The sample came from oldest cohort of the Personality and Health Through Life (PATH) Through Life Project, a large community survey of adults from Canberra and the neighboring town of Queanbeyan, New South Wales, Australia (13) that was established to evaluate mental health, cognition, and substance use. The sample aged 60–64 years at baseline was recruited from electoral rolls as electoral roll registration is compulsory for Australian citizens. At wave 1, 2,551 participants were assessed. Of those, 2,222 were reassessed 4 years later at wave 2 and 1,973 were reassessed after 8 years at wave 3. Participants were excluded from all analyses if they did not complete questionnaires on cancer and chemotherapy history. Cross-sectional models (wave 3) also excluded those with a MiniMental State Examination (MMSE) score less than 24 at wave 3 (n = 100), leaving a sample of 1,873. This comprised 1,508 participants without history of cancer, 289 reporting cancer and no chemotherapy, and 76 with cancer and chemotherapy. Participants were excluded from longitudinal analysis if MMSE at wave 1 was less than 24 (n = 24), leaving a sample of 1,949. This longitudinal sample consisted of 1,562 participants without history
Journals of Gerontology: MEDICAL SCIENCES, 2015, Vol. 70, No. 6
of cancer, 306 reporting history of cancer but not chemotherapy, and 81 reporting history of both cancer and chemotherapy. Most of the interview was self-completed on a laptop computer. A trained interviewer administered cognitive tests and physical tests, including a cheek swab from which DNA could be extracted. The study received approval from the Australian National University’s Human Research Ethics Committee.
Measures Components of the data collection relevant to the present article are described in the following sections. History of cancer and chemotherapy At each wave, participants were asked if they had ever been diagnosed with cancer (yes/no). At wave 3, a detailed questionnaire regarding cancer diagnosis and treatment was administered providing information on diagnosis of type of cancer including leukemia, melanoma, and lung, breast, uterus, ovary, stomach, colon, small bowel, lymph nodes, and other cancers. For each type of cancer, data were collected on type of treatment received including surgery (yes/ no), radiation (yes/no), and chemotherapy (yes/no). Finally the year of treatment was recorded. To establish reliability of the self-report cancer diagnoses, the distribution of total number of cancer diagnoses for the cohort was compared with de-identified data obtained from the Australian National Cancer registry. There was no difference in the frequency of cancer reported in the cohort with that recorded on official records χ2 (1) = 2.158, p = .142). Cognition Cognitive function was assessed using the following tasks at each wave. Spot-the-Word was used to assess verbal ability. Participants choose the real words from 60 pairs of words and nonsense words (14). Processing speed was assessed with the Symbol-Digit Modalities Test (SDMT) (15), which requires participants to find in a key the digit corresponding to a specific symbol and to complete as many symbol-digit pairs as possible in 90s. Episodic memory was assessed with the first trial of the California Verbal Learning Test (16), which involves recalling a list of 16 nouns. The interval between immediate and delayed recall was occupied by a test of grip strength. Working memory was assessed using the Digits Backwards subtest of the Wechsler Memory Scale (17). Simple and choice reaction time (SRT and CRT) were administered using a small box, with left and right buttons at the top to be depressed by the index fingers on appearance of a light. Mean SRT was the average of four blocks of 20 trials. Mean CRT was the average of two blocks of 20 trials. At wave 3, two tests were added. Trails B is a test of executive function involving cognitive-motor speed and task-switching ability. Participants are instructed to draw lines to connect an alternating sequence (1-A-2-B etc.) (18). For verbal fluency, participants were asked the name as many words as they could in 60 seconds starting with the letter “F” and again with “C” (19). Self-reported memory function At waves 1 and 2, participants were asked “Do you feel you can remember things as well as you used to? That is, is your memory the same as it was earlier in life? If no, then “Does this memory problem interfere in any way with your day to day life? And have you seen a doctor about your memory?” Covariates Education at baseline was constructed using a series of items that asked participants to indicate their highest level of completed education. Smoking status was derived from questions on current and
Journals of Gerontology: MEDICAL SCIENCES, 2015, Vol. 70, No. 6
past smoking habits. Depression was measured with the PRIME-MD Patient Health Questionnaire, which asks about DSM-IV major depressive symptoms in the past 2 weeks (20). This questionnaire was scored to give a continuous scale from 0 to 27. The SF-12 Physical Component Summary (PCS-12) was used to measure physical disability using the Research and Development scoring (RAND12) scoring (21,22). Apolipoprotein E e4 allele (APOE*E4) genotype was assessed by TaqMan assays (Applied Biosystems) from DNA extracted from buccal swabs (23).
Statistical Analysis Cross-sectional analyses at wave 3 comparing participants who had reported chemotherapy with participants who had not were conducted with generalized linear models that adjusted first for demographics and second for depression and disability. Linear mixed models were used to estimate the association between self-reported chemotherapy and cancer status and overall cognitive function at the three occasions of measurement, as well as decline in cognitive function. To examine the before and after effects of chemotherapy on trajectories of cognitive function, as well as the long-term effects of chemotherapy, chemotherapy and cancer status was coded: chemotherapy on or prior to wave 1 (n = 24), chemotherapy after wave 1, i.e., between wave 1 and 3 (n = 57, consisting of wave 1 to wave 2 [n = 47] + wave 2 to wave 3 [n = 10]), cancer with no chemotherapy treatment (n = 306), and no cancer reported (n = 1562). Subgroup mixed models analyses were conducted for breast cancer as this was the only cancer type with high enough prevalence. The effect of APOE genotype was evaluated despite small cell sizes. Analyses were conducted in IBMSPSS 20 and STATA 11.
Results Compared with those lost to follow-up or for whom self-reported chemotherapy data were not available at wave 3, the sample for this
731
study had lower levels of baseline depression (t (2,537) = −5.60, p < .001), higher MMSE scores (t (2,533) = 9.38, p < .001), and less disability (t (2,539) = 7.71, p < .001). No differences were found in years of education (t (2421) = −8.40, p = .061), or gender distribution (χ2 (1) = .018, p = .895). Table 1 shows descriptive characteristics at wave 3 assessment for those who reported a lifetime treatment of chemotherapy for cancer (n = 81), those reporting history of cancer but not chemotherapy (n = 306), and those reporting no history of chemotherapy or cancer (n = 1562). Those with history of chemotherapy had significantly higher levels of physical disability than those without chemotherapy exposure. Of the 306 individuals reporting some type of cancer history, the majority (79.1%) also reported not having chemotherapy as treatment (χ2 (1) = .296.71, p < .001). The different types of cancers reported are reported online (see Supplementary Table E1).
Cross-Sectional Analysis of Cognitive Function and History of Chemotherapy There were no differences at wave 1 between participants with no history of cancer or chemotherapy, participants with history of chemotherapy prior to wave 1 or after wave 1, or participants with cancer but no chemotherapy after wave 1 on immediate recall, delayed recall, or digits backwards (Supplementary Table E2). Significant differences in baseline scores were found for SDMT (F (3,1963) = 4.466, p = .004), SRT (F (3,1935) = 3.938, p = .008), and CRT (F (3,1921) = 4.572, p = .003). Post hoc tests revealed that compared with those who did not have cancer at any time, those reporting chemotherapy and cancer prior to wave 1 had lower SDMT scores at baseline, and those reporting cancer and chemotherapy after wave 1 had slower CRT at baseline. For SRT, those reporting cancer with chemotherapy prior to wave 1 had slower baseline SRT than those reporting cancer with no chemotherapy. At wave 3, after adjusting for age, gender, education, and cancer history (Model 1, Table 2) participants reporting experience of any
Table 1. Characteristics of the Sample That Persisted to Wave 3 by Cancer and Chemotherapy Status (N = 1949)
Male Age (M, SD) Years education (M, SD) Diabetes Heart condition Hypertension Alcohol intake Abstain/occasional Light/medium Hazardous/harmful Smoking status Never smoked Past smoker Current smoker Waist circumference (M, SD) Depression (M, SD) SF-12 physical health (M, SD) Spot-the-word APOE genotype ɛ4−/ɛ4− ɛ4+/ɛ4− ɛ4+/ɛ4+
No Cancer; N = 1562
Cancer + Chemo; N = 81
Cancer No Chemo; N = 306
50.1% 70.58 (1.49) 14.03 (2.68) 12.9% 20.2% 62.5%
44.4% 70.58 (1.54) 13.95 (2.73) 18.5% 23.5% 61.2%
60.5% 70.75 (1.53) 14.38 (2.64) 15.0% 21.9% 62.7%
.002 .184 .116 .247 .655 .971
29.0% 66.9% 4.1%
27.2% 70.4% 2.5%
25.8% 69.0% 5.2%
.621
54.8% 39.8% 5.3% 95.98 (13.54) 2.30 (2.88) 47.33 (10.29) 53.27(4.96)
58.0% 38.3% 3.7% 95.51 (15.30) 3.68 (3.30) 42.04 (12.13) 52.25(4.66)
52.0% 42.5% 5.6% 97.86 (13.01) 2.48 (2.89) 46.73 (10.13) 53.74(4.66)
.822
73.5% 24.6% 1.9%
64.1% 32.1% 3.8%
73.6% 26.4% 0.0%
p Value
.087
