Cognitive effects of chemotherapy in breast cancer patients: a dose–response study

Cognitive effects of chemotherapy in breast cancer patients:a dose–response study†

Barbara Collins1,2*, Joyce MacKenzie1, Giorgio A. Tasca1,2, Carole Scherling3 and Andra Smith21The Ottawa Hospital – Civic Campus, Ottawa, ON, Canada2School of Psychology, University of Ottawa, Ottawa, ON, Canada3Memory and Aging Centre, UCLA in San Francisco (UCSF), San Francisco, CA, USA

*Correspondence to:The Ottawa Hospital – CivicCampus, 1053 Carling Ave,Room A603, Ottawa, ON,Canada, K1Y 4E9. E-mail:[email protected]†Portions of the data werepresented in poster format at theInternational Cognition andCancer Conference in New YorkCity, USA in March 2010, at theMultinational Association ofSupportive Care in CancerConference in Athens, Greece inJune 2011 and at theInternational Cognition andCancer Conference in Paris,France in March 2012.

Received: 10 April 2012Revised: 24 July 2012Accepted: 24 July 2012

AbstractObjective: The purpose of this study was to determine if cognition progressively worsens with cumulativechemotherapy exposure. We reasoned that the demonstration of such a ‘dose–response’ relationshipwould help to establish whether cognitive changes are caused by neurotoxic effects of chemotherapy orwhether they are due to other confounding factors such as mood and pre-treatment differencesin cognition.

Methods: Sixty women with early stage breast cancer, aged 65 years or younger with noprevious history of cancer or chemotherapy, were matched to 60 healthy women on age andeducation. Neuropsychological assessment was conducted after surgery but prior to commencingchemotherapy and then again following each chemotherapy cycle in patients and at yokedintervals in healthy controls. We used multilevel modeling to assess change over time in an over-all cognitive summary score as well as domain-specific cognitive scores.

Results: After controlling for baseline performance, age, education, and mood, the chemotherapygroup showed a significant progressive decline over time relative to a matched healthy control groupin an overall cognitive summary score, as well as in working memory, processing speed, verbal memory,and visual memory scores. A linear model best fit the trajectory of cognitive change over the course oftreatment in the chemotherapy group supporting a dose–response hypothesis.

Conclusions: These results are in keeping with a dose–response relationship and provide the mostcompelling clinical evidence to date that cognitive decline is caused by chemotherapy exposure.Copyright © 2012 John Wiley & Sons, Ltd.

Introduction

Advances in the adjuvant treatment of breast cancer (BC)have resulted in a burgeoning number of BC survivors anda growing concern about the long-term adverse effects ofthese treatments on quality of life. Many BC patients experi-ence disturbances in cognitive function following diagnosis.Indeed, in a recent online survey conducted by HurricaneVoices, a BC advocacy group, 96% of the nearly 500 respon-dents reported cognitive changes, with some 50% of respon-dents rating them as moderate to severe [1]. Given that thesesymptoms typically arise during chemotherapy, patients referto them as ‘chemo fog’ or ‘chemobrain’ on the assumptionthat they are due to neurotoxic effects of cytostatic drugs.Numerous studies, both prospective and cross-sectional,

have now shown that BC patients who were exposed tochemotherapy are more likely to show signs or symptomsof cognitive disturbance than healthy or disease controls[2–39]. However, chemotherapy exposure is inextricablylinked to other factors that could cause cognitive distur-bances, such as stress and psychoactive palliative medica-tions. In fact, cancer patients have been shown to be atincreased risk for cognitive disturbances even in theabsence of chemotherapy [4,12,13,22,36,40–48], suggest-ing that the disease itself may be responsible.BC treatment regimens are contingent upon disease char-

acteristics and severity and therefore the use of a randomizedcontrolled trial is not ethically feasible. Because the cytotoxic

effects of many chemotherapeutic agents are known to becumulative [49], an alternative approach to establishingcausality would be to determine if there is a predictabledose–response relationship between the number of chemo-therapy cycles and severity of cognitive deficit [50].A few cohort studies in the extant literature have identified

duration of treatment and number of chemotherapy cycles asrisk factors for cognitive disturbance, hinting at such a dose–response relationship [2,13,38]. Notably, one cross-sectionalstudy of high-risk BC patients randomly allocated to receivestandard-dose or high-dose chemotherapy found that thehigh-dose group was significantly more likely to showcognitive impairment [32] and late electrophysiologicalabnormalities [51,52] than the control patients, with the risksin the standard-dose group falling somewhere in between.Similarly, in a prospective randomized controlled study, BCpatients receiving high-dose therapy were at a significantlyelevated risk for cognitive decline, whereas the standard-dosegroupwas not [26].Magnetic resonance spectroscopy studiesin BC patients [53–55] have shown white matter abnormali-ties following high-dose chemotherapy that were not detect-able following lower dose induction chemotherapy.In the current prospective, longitudinal study, we assessed

cognition in BC patients prior to their commencement of che-motherapy and at regular intervals throughout their treatment,allowing us to evaluate the cumulative toxicity of increasingexposure to chemotherapy. Our primary hypothesis was thatcognitive performance would decline as a linear function of

Copyright © 2012 John Wiley & Sons, Ltd.

Psycho-OncologyPsycho-Oncology (2012)Published online in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/pon.3163

number of chemotherapy cycles, independent of changes inmood, providing evidence for a direct causal relationshipbetween chemotherapy exposure and cognitive disturbance.

Methods

Participants

We studied a group of 60 patients with early stage BCfrom the Ottawa Hospital Regional Cancer Centre(TOHRCC). As the study has a within-subjects design,subjects served as their own controls in most respects.Nonetheless, a control group of 60 healthy women wasincluded to allow for correction of practice effects associ-ated with repeated testing. Controls were individuallymatched to patients on age (within five years) and, to theextent possible, on education (according to the categorieslisted in Table 1) and first language. Each patient wasasked to nominate her own control; when she was unableor disinclined to do so, a suitable control was recruitedthrough posters and website advertisements.All participants were required to be between the ages of

18 and 65 years (upper limit imposed to reduce the risk ofage-associated cognitive disorders), fluent in English withat least a grade-8 education living within a 30-mile radiusof Ottawa. Any history of previous cancer or chemother-apy, serious psychiatric or neurological illness, or signifi-cant substance abuse was grounds for exclusion.Additional exclusion criteria for the patient group in-cluded metastasis of disease beyond axillary lymph nodesand neo-adjuvant chemotherapy. Various chemotherapyregimens were acceptable. The majority of womenreceived FEC-T—three cycles of combined 5-fluorouracil,epirubicin and cyclophosphamide, followed by threecycles of taxotere (Table 1).

Procedures

The majority of the BC patients in our study were recruitedthrough their oncologists at TOHRCC. A clerk from themedical oncology clinic reviewed appointment schedulesfrom September 2008 to April 2010 to identify all new BCpatients meeting preliminary inclusion/exclusion criteria forthe study. Upon identifying a potential study candidate, theclerk placed a notice on the front of that patient’s chart,reminding the oncologist to introduce the study to the candi-date. If eligible and agreeable, the patient was then referredon to study personnel for further screening. In a small minor-ity of cases, women heard about the study through supportgroups or the hospital website, and they initiated contact withthe study coordinator directly. This study was approved bythe Ottawa Hospital Research Ethics Board, and informedconsent was obtained in all cases.All participants underwent a baseline assessment lasting 2

to 3 h that comprised a social and medical history, question-naires to assess mood, fatigue, and subjective cognitivefunction, a battery of pencil-and-paper neuropsychologicalmeasures, and a brief computerized cognitive test battery.In the case of the BC patients, this baseline assessment wascarried out following surgery but prior to commencementof chemotherapy (surgery-to-baseline interval ranged from9 to 89 days). All but three of our participants had had aminimum of 4 weeks to recover from surgery. The

exceptions were all self-referrals who indicated feeling welland ready to proceed at the time of assessment. The exami-ners attempted to be very sensitive to the needs of thepatients, and no woman was encouraged to continue if shewas too ill to do so comfortably. Any woman who couldnot tolerate baseline testing was dropped from the study.We did not find a significant correlation between days sincesurgery and any of the individual or composite cognitivescores at baseline testing.Most of the cognitive tests and questionnaires were

re-administered to the BC patients following each chemo-therapy cycle (in sessions lasting approximately 2 h), shortlybefore the next chemotherapy treatment to allow sufficienttime for any acute side effects to subside. The assessmentschedule for each control participant was matched to that ofher index patient with respect to both the number of testingsessions and the inter-test intervals. For example, if a patienthad four chemotherapy cycles, she and her matched controlwere assessed five times. The number of treatment cyclesvaried from four to eight, and the number of post-baselineassessment sessions ranged from four to six (AC-T was adose-dense regimen involving eight treatments 2 weeks

Table 1. Demographic and treatment characteristics of the sample

Characteristic

Groupp-

valuePatients Controls

Age at baseline — Mean (SD) 52.35 (7.93) 51.97 (7.86) 0.79Education — number (%)

<High school (HS) 2 (3) 3 (5) 0.40HS 12 (20) 10 (17)Some post-HS/community college 22 (37) 21 (35)Undergraduate degree 15 (25) 14 (23)Graduate degree 9 (15) 12 (20)

Chemotherapy regimen — number (%)FEC-T (with Herceptin in six cases) 42 (70)FEC 5 (8)CT (with Herceptin in one case) 7 (12)AC-T 3 (5)AC 2 (3)Other 1 (2)

Pre-tx menopausal status — number (%)Pre-menopausal 18 (30) 18 (30) 0.74Peri-menopausal 11 (18) 8 (13)Post-menopausal 31 (52) 34 (57)

BDI-II scores at baseline — Mean (SD) 8.09 (7.47) 4.05 (3.83) <0.001Days post surgery at T1 — Mean (SD) 45.72 (17.64)

[Range] [9–89]Inter-test interval in days — Mean (SD)

[Range]T1–T2 23.64 (7.52) 25.68 (7.72)

[12–48] [14–56]T2–T3 22.15 (3.34) 23.98 (4.92)

[14–35] [18–42]T3–T4 21.03 (3.12) 22.60 (4.07)

[14–29] [14–35]T4–T5 23.31 (6.75) 24.59 (6.61)

[13–58] [18–51]T5–T6 22.43 (4.33) 24.63 (6.70)

[14–42] [16–42]T6–T7 23.47 (5.53) 23.67 (5.05)

[13–41] [14–40]

SD, standard deviation; FEC, 5-fluorouracil, epirubicin, cyclophosphamide; FEC-T, FEC plustaxotere; CT, cyclophosphamide plus taxotere; AC, adriamycin and cyclophosphamide;AC-T, AC plus paclitaxel; Other, carboplatin, taxotere, Avastin and Herceptin; Pre-txmenopausal status, pre-treatment menopausal status; Pre-menopausal, still menstruatingregularly; Peri-menopausal, menstruated during past 12 months but experiencing irregulari-ties in menstrual cycle; Post-menopausal, amenhorrhea for at least 12 months; BDI-II, BeckDepression Inventory-II.

B. Collins et al.

Copyright © 2012 John Wiley & Sons, Ltd. Psycho-Oncology (2012)DOI: 10.1002/pon

apart, and assessments were conducted after every twocycles). All assessments were administered by one of twoexaminers with extensive training in neuropsychological test-ing. Any given participant was seen by the same examiner atevery study visit, usually in the participant’s home. Psycho-metric instruments were administered in a set order. Medicalrecords were reviewed periodically throughout the study.Approximately one-third of the sample participated in a com-panion functional magnetic resonance imaging study, theresults of which will be published separately. Women werepaid $30.00 for each study visit and were provided withindividual feedback on their cognitive test results at the endof the study.

Measures

Standard neuropsychological tests

The pencil-and-paper neuropsychological test battery wasabout 60 min in duration. The tests, listed in Table 2[56–65], were selected to focus on the areas of cognitionshown to be sensitive to the effects of cancer treatmentsin our previous research [30] and to correspond to thecognitive domains covered by the computerized testbattery. In our clinical experience, we have found thesemeasures to be sensitive to subtle cognitive impairment.The selected neuropsychological tests all have establishedreliability and validity [56,63–67] and conform to recentrecommendations of the International Cognition and CancerTask Force [68]. With the exception of theWAIS-III subtestsand Trail Making A and B, alternate forms were used asdescribed in Table 2.

Computerized cognitive tests

The computerized cognitive test, CNS-Vital Signs (CNS-VS)[58,59], was administered upon completion of the pencil-and-paper neuropsychological measures. We selected abattery of CNS-VS subtests measuring attention, reactiontime, working memory, executive function, and visual andverbal episodic memory that took approximately 30 min toadminister. CNS-VS is user friendly, has been validated ina cancer population, and has been proven sensitive in moni-toring an individual’s cognitive status over time. It hasnumerous parallel forms with established reliability for allof the core tasks. We administered the PC version of the teston an IBM laptop computer. Index scores were used in dataanalyses. These index scores and the subtests on which theyare based are described in Table 2.

Psychosocial measures

In order to better characterize our sample, we measureddepression symptoms at baseline using the Beck DepressionInventory-II (BDI-II) [69]. We administered the Profile ofMood States (POMS) [70] at baseline and at every subse-quent time point to measure change in mood over time. Weused the POMS rather than the BDI-II for this purpose, asit is more sensitive to normal fluctuations in mood, andfor the most part, our participants did not show signs of aclinical mood disorder.The POMS consists of 65 adjectivescorresponding to six dimensions reliably identified byfactor analytic studies: Tension–Anxiety, Depression–Dejection, Anger–Hostility, Vigor–Activity, Fatigue–Inertia,

and Confusion–Bewilderment. Respondents rated each ad-jective on a five-point scale with reference to their mood stateover the previous week. For the current analyses, we usedthe Total Mood Disturbance Score (POMS TMD), whichreflects the sum of scores on all dimensions. Note that POMSTMD reflects both mood state and fatigue. The POMShas also been shown to have satisfactory reliability andvalidity [66,70].

Data analysis

Calculation of cognitive summary scores

We combined the raw scores on the traditional neuropsycho-logical tests and the index scores from the computerizedcognitive tests into a limited number of cognitive summaryscores in order to reduce our risk of a Type I error. Raw testscores for each participant on each cognitive measure at eachtime point were standardized using the mean and standarddeviation on that variable in the control group. Thesestandardized scores were then averaged to compute anoverall cognitive summary score (COGSUM) for eachpatient at each time point, reversing the sign in the case ofTrails A and B and CNS-VS Reaction Time. When morethan one measure was taken from a single test, we used anaverage of the standardized scores in calculating COGSUMin order that one test would not disproportionately influencethe summary score.We used the same method to calculate summary scores for

more specific cognitive domains. In order to determine whichmeasures to assign to which domain, we conducted a seriesof principal components analyses, one for the data from eachtest session. Data from the chemotherapy and control groupswere pooled for this purpose. Some measures loaded consis-tently on the same factor from one time point to the next, andinterpretation of that factor was obvious. For example,WAIS-III Digit Symbol Coding, WAIS-III Symbol Search,and the CNS-VS Processing Speed Index always loadedmost highly on the same, common factor that clearly repre-sented processing speed. In those instances where a given testdid not consistently load on the same factor from one testingsession to the next, assignment of the measure to a particularcognitive domain was based on the modal factor loadingacross the seven testing sessions. By means of this process,we reduced the data to the following four specific cognitivesummary scores: Working Memory, Processing Speed,Visual Memory, and Verbal Memory.

Trajectory of change

Rate of change in the cognitive summary scores was assessedusing two-level multilevel growth models (MLM) for longi-tudinal data analysis [71]. MLM is a statistical method foranalyzing the trajectory of change over time that can accountfor the baseline status of an individual or group on the depen-dent variable of interest as well as the impact of clinicalcharacteristics that vary across individuals. Benefits ofMLM include its ability to reliably model varying numbersand spacing of assessments across respondents (because ituses maximum likelihood estimation for slopes and inter-cepts), its ability to model individual linear or non-linearchange, and its relative freedom (compared with analysis ofvariance, for example) from restrictive assumptions regard-ing issues such as sphericity and heteroscedasticity. Because

Cognitive effects of chemotherapy in breast cancer patients


Table 2. Cognitive test battery organized by cognitive domain

Tests (by cognitive domain) Description Variable(s)

Processing speedDigit Symbol Coding, WAIS-III [56] A timed pencil-and-paper test that requires the participant to

copy symbols to correspond with numbers, according to a key.Number correct in 120 s

Symbol Search, WAIS-III [56] A timed test requiring the participant to scan a group ofsymbols in search of target symbols.

Number correct in 120 s less errors

Trail Making Test A (Trail A) [57] A pencil-and-paper test of visuomotor tracking, requiringparticipants to connect, in sequence, numbers randomlydistributed on a page.

Completion time in seconds

Trail Making Test B (Trail B) [57] A pencil-and-paper test of visuomotor tracking, requiringparticipants to alternately connect, in sequence, numbers andletters randomly distributed on a page.

Completion time in seconds

CNS-VS Processing SpeedIndex [58,59]

Based on Digit Symbol Coding—a timed measure ofpsychomotor speed and visual-motor coordination requiringthe participant to key in numbers to correspond with symbolsby referring to a key at the top of the screen.

Number correct in 120 s less errors

CNS-VS Reaction TimeIndex [58,59]

Based on Stroop Test—a measure of processing speed,cognitive flexibility, and inhibition/disinhibition that requiresthe participant first to press a key when the color of a wordmatches the word (words are color names), then to pressonly when the words and colors do not match (i.e., toovercome a conditioned response tendency).

Mean reaction time for all responses for both the matchand mismatch conditions

Working memoryDigit Span, WAIS-III [56] Participants recite strings of random digits of increasing length,

first forward, then backward.Total raw score on forward and backward components

Letter Number Sequencing,WAIS-III [56]

Participants are required to re-order random alphanumericsequences presented orally.

Total raw score

Paced Auditory Serial AdditionTask (PASAT) [60,61]

Participants are required to add 60 pairs of randomized digitspresented orally at a fixed pace of one every 3 s so that eachdigit is added to the digit immediately preceding it. Theversion developed by Stephen Rao was used with one of twodifferent forms used at alternate testing sessions.

Total number correct

Auditory Consonant TrigramsTest (CCCs) [62]

Participants are instructed to remember orally presented lettertrigrams over 000 , 900 , or 1800 intervals while carrying out a serialsubtraction task. Six forms were used.

Total letters correctly recalled for all intervals

Controlled Oral WordAssociation Test (COWA) [63]

Scores on this test reflect the total number of words beginningwith designated letters generated orally in respective 1-minintervals. The two alternate forms (FAS and BHR) from theDelis–Kaplan Executive Function System Test were used.

Total number correct for all three letters

CNS-VS Flexibility Index [58,59] Based on the Stroop Test (described above) and the ShiftingAttention Test. The latter is a measure of executive controland set shifting requiring participants to match colored shapesto a target based on a randomly changing rule of either coloror shape.

Number of correct responses on the Shifting AttentionTest less errors on the Shifting Attention Test and lesscommission errors on the Stroop Test (all conditions)

CNS-VS Working MemoryIndex [58,59]

Based on the 2-back condition of the Continuous PerformanceTest that requires the participant to respond when a coloredshape on the screen matches the stimulus that was presentedtwo screens earlier.

Correct responses less incorrect responses

Verbal memoryHopkins Verbal LearningTest—Revised (HVLT-R) [64]

Assesses ability to learn a list of 12 words over three trials andto recall and recognize the list words after a 25-min delay. Sixalternate versions were used.

Average of the total raw score on the three learning trialsand the number correct on delayed free recall

CNS-VS Verbal MemoryIndex [58,59]

Participants are instructed to remember 15 words presentedon the screen, one at a time; they are then shown the 15target words interspersed randomly with 15 distracter wordsand asked to press for words that they recognize, bothimmediately and again after a 25-min delay.

Correct hits plus correct passes on both the immediateand delayed recognition trials to a maximum score of 60

Visual memoryBrief Visuospatial MemoryTest—Revised (BVMT-R) [65]

Participants are shown an array of six nonsense designs for 10 sand then asked to reproduce the designs in their respectivelocations. Scores are based on accuracy and location of thedesigns. There are three learning trials, as well as recall andrecognition trials after a 25-min delay. Six alternate formswere used.

Average of the total raw score on the three learning trialsand the number correct on delayed free recall

CNS-VS Visual MemoryIndex [58,59]

Participants are instructed to remember 15 geometric imagespresented on the screen, one at a time; they are then shownthe 15 images interspersed randomly with 15 distractorimages and asked to press for stimuli that they recognize,both immediately and again after a 25-min delay.

Correct hits plus correct passes on both the immediateand delayed recognition trials to a maximum score of 60

WAIS-III, Wechsler Adult Intelligence Scale-III; CNS-VS, CNS-Vital Signs.

B. Collins et al.


the cognitive summary scores are already corrected forpractice (they represent the average deviation of the chemo-therapy group mean from the control group mean), MLManalyses were carried out on the chemotherapy group only.To address the dose–response hypothesis, we assessed

whether a linear or quadratic model best fit the data: alinear fit would suggest fairly consistent decline acrosstesting sessions, whereas a quadratic fit would indicateearly decline that stabilized in later assessments. Model1 in Appendix A shows the full model used to test the timeparameters. The deviance statistic (D) for these nestedmodels was subtracted and evaluated against a chi-squaredistribution in which the degrees of freedom were basedon the difference in number of parameters estimated byeach model. We also assessed the linear and quadraticmodels separately and used the AIC statistic to assess rel-ative fit of the models [71].When assessing change in the cognitive summary scores,

baseline scores on that same measure were co-varied in theevent that initial cognitive status might influence the changeparameter. Eachmodel also controlled for other variables thatmight affect rate of change, specifically, participant age,education, and baseline depression scores on the BDI-II.We took a sequential model building approach such that abase model was run first, followed by a growth model, andthen covariates were added. Model 3 in Appendix A showsthe full model.To evaluate if change in COGSUM was associated with

change in mood state, we ran an MLM using the POMSTMD score as a time-varying covariate. Again, a sequentialmodel building approach was taken in which overall scoreson the covariate were associated with change in COGSUM,and then change in the covariate was added at level 1 of theMLM. Model 3 in Appendix A shows the full time-varyingcovariate model. For all MLM analyses, effect size wasassessed with pseudo (~) R2, in which ~R2≥ .13 indicates amedium effect and ~R2≥ .25 indicates a large effect [72].HLM software version 6.04 with full maximum likelihoodmethod of estimation was used for MLM analyses [73]. Pre-dictive Analytics SoftWare Statistics, version 18.0, was usedfor all other data analyses.

Frequency of impairment/superiority

Groups were compared in terms of the frequency of cognitiveimpairment at each time point. A given subject was deemedimpaired if she had two standard scores of less than or equalto �2.0 out of a total of 17 cognitive measures (standardscores were derived using the mean and standard deviationof the control group on the same measure at the same timepoint). The frequency of impaired individuals was comparedin the chemotherapy and control groups at each time pointusing the Chi-square statistic. In an analogous manner, anindividual with two standard scores of more than or equalto +2 at any given time point was considered to show cogni-tive superiority.

Missing values

Where a participant missed an entire testing session (therewere two instances of this), MLM was able to estimatereliable parameters by using the maximum likelihoodmethod. Where a participant was missing a value on a

particular neuropsychological measure for a given test ses-sion, it was replaced by the average of her scores on that samevariable from the preceding and subsequent sessions (e.g., ifthe value was missing for T3, the average of T2 and T4values was used to replace it).

Type I error rate

A Type 1 error rate of 0.05 (two-sided) was adopted for allanalyses.

Results

Sample characteristics

One hundred and twenty-six new BC patients passed pre-liminary screening and were approached regarding partic-ipation. It was decided in advance that any participant whodid not complete the study would be replaced in order tomeet recruitment targets of 60 women per group. Sixty-eight BC patients underwent baseline assessment, buteight of them quit because they found the assessmentstoo stressful. Two patients missed a single testing sessionbecause of acute illness or hospitalization, but we retainedthem in the sample and simply omitted that testing sessionfor their control participant as well. Most of the patientswho dropped out of the study did so early on before beingmatched to a control subject. A total of 64 healthy womenwere enrolled in the study, four of whom quit becausethey found it too stressful. Short-term retention rate was87% in the chemotherapy group, 94% in the controlgroup, and 90% overall.Table 1 lists demographic features of the groups. Not

surprisingly, given the individual matching of controls topatients, the groups did not differ with respect to age oreducation. The chemotherapy group ranged in age from35 to 65 years, and the healthy controls, from 31 to65 years. Seventy-seven percent of the chemotherapygroup, and seventy-eight percent of the control grouphad some post-secondary education. Baseline menopausalstatus was also the same in the two groups, with 70% ofparticipants in either group being peri-menopausal orpost-menopausal. The patients scored significantly higherthan the controls on the BDI-II at baseline, but the averagescore of the patient group was still well within normal lim-its [69]. Nine of the patient scores fell outside the normalrange, but in six cases, scores were only mildly elevated.Within the healthy control group, only one score fell out-side normal limits, in the moderate range.

Cognitive measures

Group means and standard deviations on the raw neuro-psychological test scores and the CNS-VS index scoresat each assessment are presented in Table 3. Table 3 alsoshows the means and standard deviations of the cognitivesummary scores at each assessment (note that the controlgroup means for these summary scores are de facto equalto 0). The summary scores, used as the primary dependentvariables for MLM analyses, were normally distributed,and there were no outliers at any time point.For the convenience of researchers in the field using Reli-

able Change Indexes, the practice effects and standard errorof the difference for all of the standard neuropsychological



Tab

le3.

Means

andstandard

deviations

(inparentheses)

forpsycho

metricmeasuresandcognitive

summaryscores

atalltimepo

intsforchem

otherapy

andcontrolgroups

Testsession

T1

T2

T3

T4

T5

T6

T7

Che

mo

Hea

lthy

Che

mo

Hea

lthy

Che

mo

Hea

lthy

Che

mo

Hea

lthy

Che

mo

Hea

lthy

Che

mo

Hea

lthy

Che

mo

Hea

lthy

Gro

up(N

=60

)(N

=60

)(N

=59

)(N

=59

)(N

=60

)(N

=60

)(N

=60

)(N

=60

)(N

=59

)(N

=59

)(N

=48

)(N

=48

)(N

=46

)(N

=46

)

Measure

HVLT

-RTo

tal

28.73(3.19)

28.83(3.11)

28.88(3.71)

28.41(3.25)

28.93(2.99)

29.05(2.95)

29.82(3.44)*

31.23(2.82)

29.56(3.69)

29.85(3.52)

30.92(3.46)

31.42(2.87)

31.41(2.83)

31.43(2.60)

HVLT

-RDelayed

Recall

10.42(1.39)

10.47(1.43)

10.24(1.76)

9.95

(1.91)

10.07(1.76)

10.32(1.47)

10.33(1.74)

10.38(1.25)

10.42(1.52)

10.51(1.70)

11.00(1.20)

10.79(1.34)

10.89(1.45)

11.04(1.15)

BVMT-RTo

tal

24.68(6.00)

23.63(5.08)

26.95(5.60)

26.08(5.00)

25.32(5.37)

25.62(5.16)

24.38(5.76)

24.98(5.36)

27.81(5.05)

28.24(4.70)

25.10(5.29)

25.42(5.13)

28.17(5.02)

28.89(4.31)

BVMT-R

Delayed

Recall

9.73

(2.15)

9.38

(1.77)

9.88

(2.14)

9.69

(2.08)

9.67

(1.81)

9.28

(2.03)

9.13

(2.40)

9.55

(2.00)

10.34(1.69)

10.44(1.72)

9.31

(1.80)

9.42

(1.82)

10.46(1.66)

10.57(1.41)

DigitSpan

17.45(3.79)

17.30(4.19)

17.75(3.59)

18.49(4.24)

17.73(3.69)

18.78(3.84)

18.62(3.73)

19.52(4.30)

18.81(4.36)

19.69(4.34)

19.35(3.96)

20.04(3.91)

19.43(3.86)

20.46(3.98)

DigitSymbo

lCod

ing77.12(13.33)

78.77(13.36)79.31(13.88)*

85.12(13.34)82.17(15.56)

86.62(13.17)83.95(15.68)

88.45(14.31)83.24(17.12)**

90.93(14.00)82.92(16.22)**

92.52(15.00)84.43(14.87)**

92.87(15.23)

Symbo

lSearch

33.12(6.44)

34.02(5.99)

36.32(6.89)

37.92(6.26)

38.33(7.52)

39.08(6.18)

39.40(7.59)

40.20(6.70)

40.20(7.06)

42.29(7.09)

39.10(8.07)

41.83(6.93)

40.22(7.32)*

43.02(6.10)

Lette

rNum

ber

Sequencing

10.75(2.45)

11.00(2.61)

11.59(2.32)

11.34(2.68)

11.78(2.34)

11.90(2.66)

11.60(2.62)

11.78(2.57)

11.75(2.34)

12.22(2.86)

11.90(2.20)

12.46(2.74)

12.00(2.27)

12.91(2.37)

TrailA

25.13(7.81)

24.48(8.89)

24.10(8.70)

21.51(6.66)

22.08(6.65)

21.05(5.99)

21.23(6.97)

19.12(5.06)

21.66(6.81)*

18.98(4.80)

21.06(6.61)

19.23(4.96)

20.93(8.07)*

18.17(3.76)

TrailB

63.70(22.43)

59.05(17.16)58.08(21.90)

54.81(18.56)54.68(21.54)

50.65(14.29)52.08(22.26)

47.95(12.99)50.20(22.05)

46.22(14.08)51

.48(25.88)

45.83(14.72)50.43(25.31)

44.20(14.33)

CCCs

34.63(5.13)

36.33(4.48)

35.46(4.80)**

38.05(4.52)

34.53(5.38)***

37.60(4.31)

35.17(4.84)***

38.88(4.23)

35.14(5.85)***

38.80(4.39)

36.31(4.66)***

39.60(3.95)

35.70(5.29)***

39.54(3.78)

COW

A40.90(12.59)

41.43(11.52)41.02(11.48)

44.05(12.39)42.48(12.75)

45.32(13.64)43.20(11.93)

45.98(13.37)44.63(12.72)

47.59(12.91)42.10(12.41)*

47.96(12.51)43.43(12.51)**

50.93(13.27)

PASA

T47.64(9.02)

49.79(7.55)

50.55(7.45)

52.39(6.65)

53.13(7.26)

54.35(6.09)

53.29(7.52)

54.68(4.90)

53.33(7.92)

55.57(4.31)

54.20(5.45)*

56.22(3.94)

55.74(5.31)

56.57(3.19)

CNS-VSVerbal

Mem

ory

52.55(4.20)

52.32(4.32)

51.08(5.52)

52.15(3.94)

51.10*

(5.45)

53.07(4.63)

50.40(5.86)

51.22(5.31)

50.81(5.55)*

52.86(4.20)

51.21(5.61)

52.74(4.25)

50.17(6.10)*

52.70(5.05)

CNS-VSVisu

alMem

ory

45.53(4.43)

46.80(4.27)

45.25(4.80)

45.56(4.34)

44.00(4.78)

44.56(4.29)

43.63(6.32)

44.63(4.38)

43.78(5.45)

45.42(4.38)

45.17(4.59)

44.94(4.53)

44.73(6.56)

45.17(5.04)

CNS-VSProcessin

gSpeed

56.97(10.64)

56.22(8.51)

59.36(9.47)

59.83(8.56)

60.87(9.78)

59.35(9.02)

61.25(11.65)

60.90(9.16)

62.93(11.87)

62.12(9.64)

62.30(10.05)

62.55(8.92)

62.43(12.45)

62.63(8.74)

CNS-VSRe

actio

nTime

662.27

(91.13)

647.55

(73.45)643.59(79.02)

627.02

(63.32)632.93(71.87)

616.13

(69.02)630.50(78.30)

614.60

(67.38)632.19(95.55)

609.64

(71.69)637.11(93.26)*

599.04

(69.10)627.09(73.26)

607.15

(72.31)

CNS-VSFlexibility

44.85(11.01)*

48.48(9.02)

50.05(10.77)*

53.59(8.23)

53.07(11.54)

55.27(8.69)

53.98(10.13)*

57.80(7.25)

53.27(10.56)***

59.36(7.00)

53.34(13.57)*

58.89(8.45)

55.72(7.88)

58.43(8.46)

CNS-VSW

orking

Mem

ory

10.81(3.38)

10.27(3.53)

10.76(3.59)

11.56(3.03)

10.68(3.89)

11.75(2.88)

11.05(3.88)

11.93(2.61)

11.60(3.74)

12.42(2.64)

11.80(3.50)

12.72(2.61)

12.49(2.91)

12.59(2.24)

POMSTM

D20.22(32.98)***

3.75

(18.36)15.80(29.69)**

1.95

(17.43)13.53(28.14)*

2.73

(19.16)18.72(29.92)***

2.45

(22.81)26.02(34.98)***

5.93

(24.14)27.21(32.57)***

3.04

(24.64)17.76(29.16)**

2.15

(22.28)

COGSU

M�0

.09(0.60)

0.00

(0.49)

�0.16(0.63)

0.00

(0.50)

�0.19(0.64)

0.00

(0.45)

�0.27(0.73)

0.00

(0.50)

�0.32(0.75)**

0.00

(0.47)

�0.30(0.64)**

0.00

(0.47)

�0.33(0.68)**

0.00

(0.50)

Processin

gSpeed

�0.12(0.91)

0.00

(0.74)

�0.25(0.88)

0.00

(0.73)

�0.17(0.93)

0.00

(0.70)

�0.23(1.03)

0.00

(0.77)

�0.31(1.05)

0.00

(0.73)

�0.39(1.00)*

0.00

(0.71)

�0.41(1.13)*

0.00

(0.69)

Working

Mem

ory

�0.15(0.63)

0.00

(0.61)

�0.26(0.68)*

0.00

(0.60)

�0.30(0.72)*

0.00

(0.59)

�0.36(0.76)**

0.00

(0.64)

�0.43(0.87)**

0.00

(0.60)

-.44(0.66)***

0.00

(0.62)

�0.41(0.71)**

0.00

(0.63)

VerbalM

emory

0.01

(0.80)

0.00

(0.82)

�0.05(1.03)

0.00

(0.82)

�0.26(0.98)

0.00

(0.78)

�0.28(1.06)

0.00

(0.80)

�0.31(1.05)

0.00

(0.78)

�0.19(1.09)

0.00

(0.78)

�0.27(1.01)

0.00

(0.76)

Visu

alMem

ory

0.05

(1.48)

0.00

(1.14)

0.10

(1.38)

0.00

(1.24)

0.01

(1.16)

0.00

(1.20)

�0.28(1.59)

0.00

(1.13)

�0.25(1.38)

0.00

(1.25)

�0.03(1.25)

0.00

(1.26)

�0.17(1.57)

0.00

(1.19)

Means

andstandard

deviations

basedon

rawscores

ontradition

alneurop

sychologicaltests,indexscores

ontheCNS-VS,andrawTMDscores

onPO

MS;COGSU

Mvalues

anddo

main-specificsummaryscores

representaverage

ofZ-scores

(referencedto

controlgroup

meanandstandard

deviationatsametim

epo

int)on

testscomprisingthatdo

main,as

describedintheMetho

dssection.T1refers

topre-treatm

entb

aselinetesting;T2–

T7referto

testingsessions

followingfirsttosixthchem

otherapy

treatm

ent;HVLT

-R,H

opkins

Verbal

Learning

Test—

Revised;B

VMT-R,B

riefVisuo

spatialM

emoryTest—

Revised;C

CCs,Audito

ryCon

sonant

Trigram

sTest;COW

A,C

ontrolledOralW

ordAssociatio

nTest;PA

SAT,Paced

Audito

rySerialAddition

Test;CNS-VS,CNS-VitalSigns;POMSTMD,Profileof

Moo

dStates

TotalMoo

dDisturbance

Score.

Asterisks

referto

significancevalues

asfollows:

*p≤.05;

**p≤.01;

***p

≤.001.

Inthecaseofrawtestscores,sign

ificance

refersto

independentt-te

stscom

parin

gthechem

otherapy

groupto

thehealthy

controlgroup

atsametim

epoint;inthecaseofthecognitive

summaryscores,sign

ificance

refersto

dependentt-te

stscom

parin

gscoresatT2

throughT7

,respective

ly,to

baseline(T1)

scores

forthechem

otherapy

group.

B. Collins et al.


measures are presented in Table 4. It should be noted thatwhen multiple forms were used, these ‘practice effects’ alsocapture differences in performance deriving from the use ofthe different forms.

Dose–response relationship

A linear model of change fit the data well, and there wasa significant linear slope parameter indicating a consistentdecrease over time in COGSUM, as well as in each ofthe domain-specific summary scores. The quadratic pa-rameter was not significant for any of the dependentvariables, and the addition of the quadratic parameter didnot significantly improve the fit of the models over andabove the respective linear models alone. AIC statisticsindicated that a linear model was a better fit than aquadratic model for each dependent variable when themodels were fit separately. Model 2 in Appendix A showsthe equations for these analyses.As can be seen from Table 3, the overall cognitive sum-

mary score for the chemotherapy group declined quiteconsistently from T1 to T7, with the difference from base-line reaching statistical significance at T5 (i.e., followingthe fourth chemotherapy cycle). It is further apparent fromTable 3 that the Working Memory score showed the great-est decline. In this case, there was a significant declinefrom baseline following the very first chemotherapy cycle,and the downward trajectory intensified thereafter.

Change in cognitive functioning over time

There was a significant main effect for change inCOGSUMover time in the chemotherapy group after con-trolling for baseline COGSUM scores, baseline BDI-IIscores, age, and education (b10 =�.05, t(55) =�8.77,p< .001). This effect of time was large (~R2 = .25)and indicated that, after removing positive practiceeffects, the COGSUM values in the chemotherapy groupdeclined significantly with successive treatments. Werepeated these analyses with each of the domain-specific

summary scores. The effect of time was large and signifi-cant for working memory (b10 =�.06, t(55) =�7.52,p< .001, ~R2 = .26) and processing speed (b10 =�.05,t(55) =�4.87,p< .001, ~R2 = .27),with the chemotherapygroupdecliningbyanaverageof .06 and .05 standardunits,respectively, at each assessment. Verbal memory(b10 =�.06, t(55) =�3.97, p< .001; ~R2 = .10) and visualmemory (b10 =�.06, t(55) =�2.82, p = .007; ~R2 = .05)also declined significantly over time, but the effect sizeswere small.

Time-varying covariates

Higher POMS TMD scores were associated with greaterdecline in COGSUM scores (b20 =�.001, t(59) =�2.08,p= .04). However, even after controlling for the effects ofPOMS TMD, COGSUM declined significantly over time inthe chemotherapy group (b10 =�.05, t(58) =�8.10,p< .001). We then ran a model that included the effects ofchange in POMS TMD scores on change in COGSUMscores. As TMD scores increased, COGSUM scoresdecreased (b30 =�.0005, t(59) =�2.55, p= .014). Again,however, COGSUM scores still declined significantlyover time after controlling for the effects of decreasing mood,with an average rate of change of .04 standard units at eachassessment (b30 =�.04, t(58) =�5.41, p< .001). Model 3in Appendix A shows the equations for these analyses.

Sub-analysis for FEC-T patients

It is difficult to plot a true dose–response curve for these databecause the number of treatment cycles varied systematicallyas a function of treatment regimen. The preceding analyseswere based on all available data regardless of type of chemo-therapy or total number of treatment cycles. Thus, the resultsmay be subject to confounding by treatment type. To addressthis, we re-ran the MLM analyses using only the data fromthose 36 patients who received FEC-T (60% of the entiresample). The pattern of results was the same as with the entiresample, with respect to the following: (i) the fit of the linear

Table 4. Practice effects (PE) and standard error of the T1� Tn difference scores (SEdiff) in the control group for T2–T7 referenced to T1

Test interval T1–T2 T1–T3 T1–T4 T1–T5 T1–T6 T1–T7Days (Mean�SD) (25.7� 7.7) (49.5� 9.1) (72.1� 10.5) (96.9� 13.6) (118.1� 12.0) (141.1� 13.0)

N=59 N=60 N=60 N= 59 N=48 N=46

Measure PE SEdiff PE SEdiff PE SEdiff PE SEdiff PE SEdiff PE SEdiff

HVLT-R Total �0.36 2.85 0.22 3.10 2.40 2.73 1.05 3.21 2.56 3.36 2.59 2.54HVLT-R: Delayed Recall �0.49 1.77 �0.15 1.42 �0.08 1.23 0.07 1.52 0.31 1.70 0.59 1.36BVMT-R Total 2.39 4.53 1.87 4.77 1.23 4.65 4.59 4.53 1.40 4.23 4.87 4.83BVMT-R Delayed Recall 0.32 1.97 �0.10 2.04 0.17 2.17 1.09 2.01 0.04 1.99 1.13 1.54Digit Span 1.15 1.73 1.48 2.64 2.22 2.82 2.32 2.80 2.54 2.84 3.13 2.49Digit Symbol Coding 6.09 7.34 7.85 8.13 9.68 9.22 12.37 9.25 13.69 9.00 14.48 8.61Symbol Search 3.83 4.08 5.07 4.39 6.18 4.57 8.27 4.56 7.98 4.88 9.17 5.17Letter Number Sequencing 0.34 2.04 0.90 1.86 0.78 2.03 1.22 1.92 1.27 2.14 1.70 2.06Trail A �2.73 6.31 �3.43 6.21 �5.37 6.65 �5.49 7.21 �5.21 6.80 �6.54 7.18Trail B �3.90 16.52 �8.40 12.50 �11.10 14.73 �13.14 11.87 �13.25 14.83 �15.00 13.79CCCs 1.73 3.85 1.27 4.17 2.55 4.49 2.32 3.98 3.13 4.18 3.30 4.42COWA 2.71 8.17 3.88 8.21 4.55 8.03 5.88 7.94 5.38 8.48 8.61 8.46PASAT 2.52 5.33 4.56 7.12 4.90 6.92 5.91 6.83 6.33 6.76 6.93 8.00

SD, standard deviation.T1 refers to pre-treatment baseline testing; T2–T7 refer to testing sessions following first to sixth chemotherapy treatment; HVLT-R, Hopkins Verbal Learning Test—Revised;BVMT-R, Brief Visuospatial Memory Test—Revised; CCCs, Auditory Consonant Trigrams Test; COWA, Controlled Oral Word Association Test; PASAT, Paced Auditory SerialAddition Test.Note that alternate forms were used for most neuropsychological tests as described in Table 2.



model; (ii) the decline in cognitive test performance as a func-tion of number of chemotherapy cycles; (iii) the significantinverse relationship between change in POMS TMD andchange in COGSUM; and (iv) the fact that the decline inCOGSUM over time remained significant after controllingfor POMS TMD and for change in POMS TMD.

Frequency of impairment

Table 5 shows the frequency of impairment and superiority inthe chemotherapy and control groups at each of the seventesting sessions. There is no difference in frequency ofimpairment until after the third chemotherapy cycle(i.e., T4), when the risk becomes significantly greater amongthe chemotherapy patients. There is no difference betweenthe groups in the frequency of cognitive superiority at anytime point.

Discussion

These results indicate that cognitive function in BC patientsprogressively worsens over the course of chemotherapy treat-ment. Although mean raw scores of the patient group did notactually decline on most tests (indeed, they often improvedslightly from before to after treatment), the BC patients didnot benefit from practice to the same extent as a healthymatched control group such that the decline became evidentonce the expected positive practice effect was removed.One could argue that the cognitive changes observed in

the patient group are clinically insignificant because, onaverage, their test scores still fell within normal limits atthe end of treatment. However, the effect size of thedecline in COGSUM for the chemotherapy group, oncecorrected for practice, was large. Furthermore, even smalllosses may have a significant adverse impact on quality oflife for individuals who struggled to meet high intellectualdemands even prior to any loss of cognitive resources[19,74,75]. Many BC patients cite cognitive impairmentas their most troublesome long-term iatrogenic symptomand report that it affects their daily functioning and qualityof life [76]. Poorer neuropsychological performance hasbeen associated with reduced likelihood of return-to-workamong cancer survivors [19], and poorer executive func-tioning specifically has been associated with decreased

productivity, community involvement, and social rolefunctioning [24]. Thus, the cognitive changes detected instudies of cancer survivors do appear to have meaningfulfunctional implications.Although analyses with the various domain-specific

cognitive scores all yielded trends similar to thoseobserved with COGSUM, working memory and proces-sing speed appeared to be most sensitive to this chemo-therapy effect. This fits well with patients’ self-reports ofdiminished cognitive efficiency and difficulties withmulti-tasking [10,77]. It is also consistent with results ofrecent imaging [8,9,78–80] and animal studies [81,82],showing that the toxic effects of chemotherapy may havea predilection for white matter and for frontal–subcorticalcircuits in the brain. Alternatively, the working memoryand processing speed summary scores may have beenmore sensitive to change because they were composedof more measures than the other domain scores conferringupon them greater reliability of measurement. A thirdpossibility is that these factor scores were more sensitivebecause they were time dependent, and very subtle cogni-tive deficits may be better captured by speed than byaccuracy of response. Functional MRI studies have shownthat untimed accuracy-based scores on cognitive tasksmay not differ between chemotherapy and control groupsdespite significant differences in neural processingactivated by these tasks [80,83]. Inconsistencies amongprevious studies may be due to differential processingspeed demands of the tests used.Despite our careful attention to the design of this study,

certain limitations must be acknowledged. First, differentchemotherapy regimens were included, and the numberof treatment cycles varied as a function of treatment regi-men. To address this issue, we re-ran additional analyseswith a subgroup of 36 participants homogeneous withrespect to treatment regimen (FEC-T) and obtained thesame pattern of results. Even here, however, the treatmentin the first three cycles (FEC) differed from that in the lastthree (taxotere), and thus, any cognitive decrements in thelatter cycles may have been due to different drugs rather thanaccumulating exposure to cytostatic agents. A prospectivemulti-centre trial with sufficient numbers of participantsto explore the dose–response relationship within treatment-specific subgroups would allow us to better address this

Table 5. Number (and percentage) of chemotherapy patients and controls showing impairment and superiority at each testing session

Frequency impairment

Χ2 p

Frequency superiority

Χ2 pChemo Controls Chemo Controls

T1, n=60 7 (11.7%) 6 (10%) 0.09 0.77 3 (5.0%) 2 (3.3%) 0.21 0.65T2, n=59 13 (22.0%) 7 (11.9%) 2.17 0.14 2 (3.4%) 1 (1.7%) 0.34 0.56T3, n=60 14 (23.3%) 9 (15%) 1.35 0.25 2 (3.3%) 2 (3.3%) 0.00 1.00T4, n=60 19 (31.7%) 8 (13.3%) 5.78 0.02 2 (3.3%) 3 (3.3%) 0.21 0.65T5, n=59 20 (33.9%) 10 (16.9%) 4.47 0.04 1 (1.7%) 1 (1.7%) 0.00 1.00T6, n=48 15 (31.3%) 6 (12.5%) 4.94 0.03 0 (0.0%) 1 (2.1%) 1.01 0.32T7, n=46 17 (37.0%) 7 (15.2%) 5.64 0.02 2 (4.3%) 1 (2.2%) 0.35 0.56

n refers to the number of participants per group.Impairment is defined as having two standardized scores (standardized to the mean and the standard deviation of the control group on that measure at the same time point) of lessthan �2.0 out of a total of 17 scores.Superiority is defined as having two standardized scores (standardized to the mean and the standard deviation of the control group on that measure at the same time point) of morethan +2.0 out of a total of 17 scores.A single score was derived from each of the Hopkins Verbal Learning Test—Revised and the Brief Visuospatial Memory Test—Revised by averaging the cumulative score on trials1–3 and the delayed recall score.Signs were reversed for timed measures (Trail A, Trail B, and CNS-VS Reaction Time Index).

B. Collins et al.


potential confound. Finally, we cannot rule out the possibilitythat palliative medications given to treat side effects of che-motherapy in the BC patients contributed to the cognitive dis-turbances. We can, however, rule out confounding by otheradjuvant treatments as, unlike the majority of retrospectivecase–control studies, none of our patients had commencedhormonal therapy at the time of the post-chemotherapytesting and only two had begun radiotherapy.While it would be virtually impossible to unequivocally

prove by means of a clinical study that chemotherapy causescognitive dysfunction, we believe that this study provides themost compelling evidence to date of such a causal relation-ship. By including pre-treatment baseline testing andmeasur-ing change from baselinewithin the chemotherapy group, wehave largely controlled for fixed factors (including diseasestatus) that might otherwise account for cognitive dysfunc-tion. By testing participants repeatedly over the course ofchemotherapy, we were able to measure and statisticallyaccount for random or fluctuating effects, such as the effectsof mood and fatigue, that might confound the chemotherapy–cognition relationship. Finally, by including a healthy controlgroup, we were able to account for the effects of repeatedtesting that could easily mask subtle, treatment-related cogni-tive changes. What we observe using this within-betweendesign is an attenuation of the normal practice effect in thechemotherapy group that, in itself, is considered an indicationof cognitive dysfunction. We contend that the linear declinein cognitive function with increasing chemotherapy exposureeven after controlling for baseline performance, practiceeffects, and changes in mood does indicate a systematicdose–response relationship and hence strongly implicates acausal role for chemotherapy in cognitive disturbance.Future studies should aim to identify the adverse cogni-

tive effects of specific chemotherapy regimens so that thiscan be considered in prescribing treatment, in obtainingpatient consent, and in tailoring cognitive rehabilitationstrategies for affected individuals. This study protocolcalls for a final testing session 1 year following comple-tion of chemotherapy. It will be of interest to determineif the cognitive decline described herein persists over thelonger term and, if so, if the number of chemotherapycycles predicts later cognitive outcome.

AcknowledgementsThis research was made possible by the generous support of theCanadian Breast Cancer Foundation – Ontario Chapter. We wouldlike to thank the women who volunteered as participants, as wellas the oncologists, nurses, and support staff at the Ottawa HospitalCancer Centre for their support.

Conflict of interest

Authors have no conflicts of interest.

References

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Appendix A

Model 1 Full two-level multilevel model to assessaddition of quadratic parameter and best fitting timeparameters

Level 1:Yti =p0i + p1i(timeti) + p1i(timeti)2 + eti

Level 2: p0i ¼ b00 þ r0ip1i ¼ b10 þ r1i

Model 2 Full two-level multilevel model to assess changein cognitive functioning controlling for baseline andcovariates

Level 1:Yti =p0i + p1i(timeti) + eti

Level 2:p0i=b00+b01(age)+b02(education)+b03(depression)+b04(baseline)+r0i

p1i=b10+b11age+b12(education)+b13(depression)+b14(baseline)+r1i

Model 3 Full two-level multilevel model to assess POMStotal as a time-varying covariateLevel 1:Yti = p0i + p1i(time) +p2i(POMStot) +p3i(POMStot� time) + eti

Level 2:

p0i ¼ b00 þ b02 baselineð Þ þ r0ip1i ¼ b10 þ b12 baselineð Þ þ r1ip2i ¼ b20 þ r2ip3i ¼ b30 þ r3i



http://www.hurricanevoices.org/downloads/hv_cognitive_results.pdf

http://www.hurricanevoices.org/downloads/hv_cognitive_results.pdf

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Cognitive effects of chemotherapy in breast cancer patients: a dose–response study

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