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Subjective cognitive impairment and brain structural networks in Chinese gynaecological cancer survivors compared with age-matched controls: a cross-sectional study

Subjective cognitive impairment and brain structural networks in Chinese gynaecological cancer... Background: Subjective cognitive impairment can be a significant and prevalent problem for gynaecological cancer survivors. The aims of this study were to assess subjective cognitive functioning in gynaecological cancer survivors after primary cancer treatment, and to investigate the impact of cancer treatment on brain structural networks and its association with subjective cognitive impairment. Methods: This was a cross-sectional survey using a self-reported questionnaire by the Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) to assess subjective cognitive functioning, and applying DTI (diffusion tensor imaging) and graph theoretical analyses to investigate brain structural networks after primary cancer treatment. Results: A total of 158 patients with gynaecological cancer (mean age, 45.86 years) and 130 age-matched non- cancer controls (mean age, 44.55 years) were assessed. Patients reported significantly greater subjective cognitive functioning on the FACT-Cog total score and two subscales of perceived cognitive impairment and perceived cognitive ability (all p values <0.001). Compared with patients who had received surgery only and non-cancer controls, patients treated with chemotherapy indicated the most altered global brain structural networks, especially in one of properties of small-worldness (p = 0.004). Reduced small-worldness was significantly associated with a lower FACT-Cog total score (r = 0.412, p = 0.024). Increased characteristic path length was also significantly associated with more subjective cognitive impairment (r = −0.388, p = 0.034). (Continued on next page) * Correspondence: andy.cheng@polyu.edu.hk Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China Full list of author information is available at the end of the article © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Zeng et al. BMC Cancer (2017) 17:796 Page 2 of 10 (Continued from previous page) Conclusion: When compared with non-cancer controls, a considerable proportion of gynaecological cancer survivors may exhibit subjective cognitive impairment. This study provides the first evidence of brain structural network alteration in gynaecological cancer patients at post-treatment, and offers novel insights regarding the possible neurobiological mechanism of cancer-related cognitive impairment (CRCI) in gynaecological cancer patients. As primary cancer treatment can result in a more random organisation of structural brain networks, this may reduce brain functional specificity and segregation, and have implications for cognitive impairment. Future prospective and longitudinal studies are needed to build upon the study findings in order to assess potentially relevant clinical and psychosocial variables and brain network measures, so as to more accurately understand the specific risk factors related to subjective cognitive impairment in the gynaecological cancer population. Such knowledge could inform the development of appropriate treatment and rehabilitation efforts to ameliorate cognitive impairment in gynaecological cancer survivors. Keywords: Subjective cognitive impairment, Chemotherapy, Brain networks, Gynaecological cancer, China Background [10, 19, 20]”. “Cognitivefunctions arebelievedtobesup- Cognitive impairment can be a significant and prevalent ported by parallel neural networks that must balance the problem for survivors with gynaecological cancer [1, 2]. competing demands of segregation and integration [21].” Cognitive impairment often refers to cancer-related cogni- Observational studies have found that alterations in the tive impairment (CRCI), which can be related to the can- brain structural network have been demonstrated to have cer itself, as well as to its treatment, for example surgery, adverse effects on cognition in both female and male cancer chemotherapy, and radiation therapy [3, 4]. As CRCI can survivors [10, 22]. However, much remains unknown about negatively impact quality of life and daily life functioning the effects of cancer and its treatment on brain structural in cancer survivors [5, 6], it is important to investigate networks in gynaecological cancer populations. such late effects and to understand the course and causes In view of the poor understanding of the psychosocial of CRCI for guiding future treatment and rehabilitation impacts of cancer treatment on perceived cognitive impair- efforts [7–10]. ment and brain networks in gynaecological cancer survi- CRCI may be related to a number of psychological fac- vors, it is important to explore CRCI and its associated tors that are seldom investigated in the context of gynae- factors in this population. Therefore, this study aims to cological cancer, although gynaecological cancer is the assess subjective cognitive functioning in gynaecological second most prevalent form of cancer among women in cancer survivors after primary cancer treatment, and to China [11]. Psychological distress has been found to be investigate the impact of cancer treatment on brain struc- negatively associated with neuropsychological performance tural networks and cancer treatment’s association with in cancer patients [8, 12]. Research has also found that per- cognitive impairment. This study also aims to explore asso- ceived cancer-related fatigue and anxiety resulted in CRCI ciated predictors of subjective cognitive impairment in in cancer survivors [13, 14]. Furthermore, treatment-related order to gain a deeper understanding of potential factors of mood changes, such as depression, have also significantly importance to CRCI. influenced many cancer survivors’ cognitive functioning [13, 15–17]. Other research found that age and education Methods levels were also associated with changes in cognitive func- This cross-sectional study was conducted to assess research tion among gynaecological cancer survivors [6]. participants’ subjective cognitive functioning, psychological Self-reported cognitive impairment are also associated wellbeing and brain structural networks immediately after with structural and functional changes in the brain that can primary cancer treatment. Age-matched non-cancer con- be detected by magnetic resonance imaging (MRI) [10, 17]. trols were simultaneously assessed using these outcome Brain networks are organised such that specialised regions measures for direct comparison. or clusters of neurons are highly connected to their neigh- bours but sparsely connected to distant regions [18]. “Brain Subjects structural network that tends to display as a small-world Patients were recruited in South China, at a tumor hospital network organization, which is characterized by high clus- and at a general hospital’s gynaecological oncology unit. tering in local regions while retaining relatively short path This study obtained ethical approval from the ethics com- lengths across all brain regions, supporting the notion of mittees at both Hunan Cancer Hospital and The Third the brain in an optimal balance between segregation and in- Affiliated Hospital of Guangzhou Medical University. Sub- tegration in information processing between brain regions jects were Chinese females ages 18 to 60 years; with a Zeng et al. BMC Cancer (2017) 17:796 Page 3 of 10 primary diagnosis of gynaecological cancer, without meta- score ≤ 85): ten out of 130 healthy controls had a FACT- static disease. Patient exclusion criteria were women who Cog summary score of less than 85, then 10 age-matched did not have a primary diagnosis of cancer, and/or who surgery patients and 10 age-matched patients with chemo- were in a terminal stage of cancer. Advertisements to re- therapy who also reported cognitive complaints were cruit non-cancer controls were posted in the hospitals’ included in brain MRI scanning.. This cut-off score common areas. Each non-cancer control subject was for the FACT-Cog was based on existing published within 2 years of the age of the patient. All participants had studies [17, 29]. DTI (diffusion tensor imaging) and to be without a diagnosis of a neurodegenerative disease or high-resolution structural T1-weighted brain scans any potential psychiatric disorder, and without the use of were obtained using single-shot echo-planar imaging psychotropic medication. All study participants provided (EPI) (acquisition matrix = 128 × 128; TE = Minimum; written informed consent to participate. TR = 16,000 ms; field of view = 256 mm × 256 mm; slice thickness/gap = 2.0 mm/0 mm; scanning time = 6 min Self-reported cognitive measures 56 s) with 32 distributed isotropic orientations for the Subjective cognitive functioning was assessed using the diffusion-sensitising gradients at a b-value of 1000 s/ Functional Assessment of Cancer Therapy-Cognitive mm and a b-value of 0. T1-weighted imaging was (FACT-Cog) scale. A self-report questionnaire measures achieved for morphometric (GM volume, cortical perceived cognitive impairment, comments from others, thickness and surface area) analysis using three- perceived cognitive ability, and impact of cognitive impair- dimensional fast spoiled-gradient recalled acquisition ment on quality of life [23]. The FACT-Cog consists of 37 in steady state in 166 coronal slices (acquisition matrix items and the overall cognitive function is the sum of the = 128 × 128; TE = 3.9 ms; TR = 9.6 ms; field of view = four subscales [23]. Higher scores indicate better cognitive 256 mm × 256 mm; slice thickness/gap = 2 mm/0 mm; function (i.e. lower subjective cognitive impairment). scanning time approximately 7 min). Psychological measures and general information sheet Statistical analysis Depression and anxiety were evaluated using the Chinese Data related to self-reported cognitive and psychological version of the Hospital Anxiety and Depression Scale measures were analysed using SPSS for Windows (ver- (HADS) [24]. The HADS is a 14-item self-assessment sion 21; IBM SPSS Statistics, Armonk, NY, USA). De- scale for a screening instrument to assess patients’ anxiety scriptive, comparison and regression analysis were used and depression levels. Each item is scored from 0 to 3. to analyse behavioural data. Descriptive statistics were The anxiety and depression sub-scores are both on scales used to describe sociodemographic and clinical charac- of 0 to 21. Higher total scores indicate higher levels of teristics of the sample. In comparing subject characteris- anxiety and depression [24]. The Chinese version of tics, cognitive and psychological measures between HADS has been reported to have acceptable internal patients and healthy controls used independent t-tests consistency and validity [25, 26], and is found to be a reli- for continuous variables, and chi-square or Fischer exact able tool for assessing psychological disturbances in can- tests were used for testing differences in categorical cer survivors [24]. The Brief Fatigue Inventory (BFI) has measures. To analyse the relationship between perceived been validated as a short and comprehensive instrument cognitive functioning and associated factors, a univariate to assess the severity of fatigue and fatigue-related impair- analysis was used followed by multiple regression ana- ment in cancer survivors [27, 28]. It consists of 10 items lysis. As sociodemographic factors, such as age and edu- and allows a basic assessment of the dimensions of activ- cation level, have been found to be associated with ity, ability to walk, mood, work, interpersonal relation- cognitive functioning in ovarian cancer survivors [6], it ships, and enjoyment of life [27]. Lower scores indicate is important to adjust for these factors, as they may less severity of fatigue [27]. A general information sheet potentially confound the relationship between subject- collected subjects’ demographic and clinical characteristics ive cognitive impairment and associated factors. The re- in terms of age, education level, employment, and marital siduals’ normality, linearity, and homoscedasticity were status. Patients’ clinical information included cancer checked to ensure the validity of the linear regression types, disease stage, and treatment received (e.g., Surgery, model [30]. Multiple linear regression analysis was per- Radiation, Chemotherapy). formed using a forward stepwise approach, in which vari- ables were significantly related to the total FACT-Cog MRI data acquisition score in the univariate analysis (it must be at a cutoff p The MRI data were acquired using a Philips 3 T Achieva value of 0.1 in the univariate analysis). Analysis of variance MRI scanner with an 8-channel head coil. Structural (ANOVA) was used to compare three participant groups brain networks were assessed in 30 participants who re- reported with subjective cognitive impairment and brain ported cognitive complaints (with the FACT-Cog summary structural network properties. Associations between brain Zeng et al. BMC Cancer (2017) 17:796 Page 4 of 10 network properties and subjective cognitive impairment Self-reported cognitive functioning were explored using Pearson’s correlation coefficient. From Table 2, gynaecological cancer survivors reported The threshold of P < 0.05 was used to assess statistical statistically higher subjective cognitive impairment than significance. healthy controls (p < 0.001), especially in the subscale scores of perceived cognitive impairment and perceived cognitive ability (all P values <0.001). Within the patient MRI data processing and analyses group, patients receiving chemotherapy scored lower in The DTI images were preprocessed using PANDA: a the FACT-Cog total scores and four subscale scores pipeline toolbox for analysing brain diffusion images (Table 3). According to Vardy et al. [17, 29], subjects (https://www.nitrc.org/projects/panda/). Each individual’s were categorised as having subjective cognitive impairment DTI dataset was registered to the same individual’shigh- with a FACT-Cog score of 85 or less. Of 158 patients, a resolution structural image and then into the standard total of 64 (40.51%) reported subjective cognitive impair- Montreal Neurological Institute (MNI) space using affine ment. Within the patient group, 16 subjects (10.13%) in transformations. Fractional Anisotropy (FA) images were the surgery group had subjective cognitive impairment and created from the pre-processed DTI data of all subjects. 48 subjects (30.38%) receiving chemotherapy had perceived All FA images were then non-linearly aligned to a common cognitive impairment. Of 130 healthy controls, a total of space. The mean FA image was used to represent the 10 subjects (7.69%) perceived cognitive impairment. centre of all tracts common to the group. Then, all sub- jects’ aligned FA data were projected onto the skeleton, Psychological measures and associated predictors of and the resulting data were subjected to voxelwise cross- FACT-cog outcomes subject statistics. Whole brain tractography was then per- While there were no statistically significant differences formed in the patient’s native space for each subject at between patients and healthy controls in terms of anx- each time point using a deterministic streamlined ap- iety, depression, and fatigue levels (Table 2), there were proach [31, 32], in which fibre pathways were recon- greater anxiety and fatigue levels in the subgroup of pa- structed by following the main diffusion tensor direction tients receiving chemotherapy (p = 0.014, and p < 0.001, as indicated by the principal eigenvector, until an FA value respectively) (Table 3). Associated predictors of cognitive of 0.20 or lower was reached, or until an angular turn of outcomes were explored using multivariate linear regres- 45 degrees or more was made [31, 32]. sion analysis (Table 4). Hierarchical multiple regression The assessment of brain network measures was per- analyses were performed to identify significant associated formed using the toolkit of graph theoretical network ana- factors for subjective cognitive impairment. A forward lysis (GRETNA) (https://www.nitrc.org/projects/gretna/). stepwise approach was used. There were no confounders The voxelwise brain structural network analyses were per- accounting for the association between associated predic- formed using the CPU-GUI platform of GRETNA [33]. tors and perceived cognitive functioning. The total The following characteristic graph metrics were estimated variance explained by the linear regression model was to describe the topological organisation of the whole 40.8%. Employment status, receipt of chemotherapy brain structural networks: global topological properties and depressive symptoms were statistically significant consist of small-world measures and global network ef- predictors of perceived cognitive functioning (standard- ficiency; local topological properties include local net- ized beta = −0.199, −0.129 and −0.331, respectively; all work efficiency, nodal clustering coefficient, and nodal p values <0.05). shortest path length. Brain structural networks and correlations with subjective Results cognitive impairment Research participant characteristics From Table 5, within global topological properties three Of the 288 participants, 158 patients with gynaecological groups had a small-world connectome organisation, as cancer had completed primary cancer treatment within the mean small-worldness index was greater than one. a week, and 130 noncancer controls were balanced in There were statistically significant differences in terms terms of age and marital status (Table 1). Nearly half of of small-worldness index (p = 0.004). Patients receiving patient participants (n = 81, 51.3%) were in the early stages chemotherapy had the lowest mean small-worldness of cancer, more than 60% of patients (n =98, 62.0%) index, compared with patients who received surgery only had a diagnosis of cervical cancer, and more than half and healthy controls. Lower small-worldness index of patients were receiving chemotherapy or a combin- was associated with more subjective cognitive impair- ation of chemotherapy and other cancer treatment. ment (r =0.412, p = 0.024) (Fig. 1). For the local topo- All research subjects’ demographic and clinical char- logical properties, there were no statistically significant acteristics are shown in Table 1. differences including nodal efficiency, nodal clustering Zeng et al. BMC Cancer (2017) 17:796 Page 5 of 10 Table 1 Demographic and clinical characteristics of participant groups Variables Mean (SD) / n (%) Patients (n = 158) Healthy controls (n = 130) p-Value Age (years) 45.86 (10.56) 44.55 (9.72) 0.157 Education levels <0.001 Primary school or below 103 (65.2) 65 (50.0) High school 34 (21.5) 15 (11.5) College or above 21 (13.3) 50 (38.5) Employment status <0.001 Employed but on medical leave 32 (20.3) 100 (76.9) Unemployed or retired 126 (79.7) 30 (23.1) Marital status 0.895 Single 9 (5.7) 8 (6.2) Married 142 (89.9) 117 (90.0) Divorced 6 (3.8) 5 (3.8) Widowed 1 (0.6) 0 (0.0) Disease stage Early stage 81 (51.3) Middle stage 57 (36.1) Advanced stage 20 (12.6) Disease diagnosis Cervical cancer 98 (62.0) Ovarian cancer 28 (17.7) Uterine cancer 14 (8.9) Other (e.g. GTN) 18 (11.4) Types of treatment Surgery 37 (23.4) Chemotherapy 14 (8.9) Surgery + chemotherapy 71 (44.9) Surgery + radiation + chemotherapy 21 (13.3) Radiation + chemotherapy 15 (9.5) Abbreviation: GTN Gestational Trophoblastic Neoplasia Table 2 Mean scores of cognitive and psychological measures in each group Measures Mean (SD) p-Value Patient (n = 158) Healthy controls (n = 130) FACT-Cog 99.80 (19.67) 112.33 (21.53) <0.001 Perceived cognitive impairment 57.38 (11.51) 65.21 (12.20) <0.001 Comments from others 14.51 (2.75) 14.37 (2.26) 0.658 Perceived cognitive ability 16.24 (6.81) 21.20 (8.02) <0.001 Impact on QOL 11.53 (3.54) 11.73 (4.05) 0.667 HADS Anxiety 5.86 (4.28) 5.40 (3.86) 0.352 Depression 5.17 (4.33) 4.52 (3.50) 0.171 BFI-total 32.52 (21.20) 27.25 (21.72) 0.062 Abbreviation: BFI Brief Fatigue Inventory, FACT-Cog Functional Assessment of Cancer Therapy-Cognition, HADS Hospital Anxiety and Depression Scale Bolded p values are statistically signifcant Zeng et al. BMC Cancer (2017) 17:796 Page 6 of 10 Table 3 Mean scores of cognitive and psychological measures in the patient group Measures Mean (SD) p-Value Surgery only (n = 37) Receiving CT (n = 121) FACT-Cog 108.25 (17.84) 97.28 (19.55) 0.003 Perceived cognitive impairment 61.76 (8.74) 56.04 (11.95) 0.002 Comments from others 15.24 (1.77) 14.29 (2.95) 0.019 Perceived cognitive ability 18.22 (7.71) 15.66 (6.44) 0.047 Impact on QOL 13.21 (3.12) 11.28 (4.20) 0.003 HADS Anxiety 4.35 (3.97) 6.32 (4.28) 0.014 Depression 4.00 (3.28) 5.52 (4.31) 0.060 BFI-total 19.08 (17.41) 34.33 (22.26) <0.001 Abbreviation: BFI Brief Fatigue Inventory, CT Chemothrapy, FACT-Cog Functional Assessment of Cancer Therapy-Cognition, HADS Hospital Anxiety and Depression Scale Bolded p values are statistically signifcant coefficient, and shortest path length (all p values >0.05). that CRCI could possibly be associated with chemotherapy Shorter characteristic path length, which indicates more rather than depressive symptoms. Previous research found efficient network organisation, was significantly associated that Chinese female cancer survivors reported higher levels with fewer subjective cognitive impairment (r = −0.388, of anxiety and depression, resulting in lower levels of work p = 0.034) (Fig. 2). productivity [35]. In consequence, employed cancer survi- vors experienced work limitations more frequently, leading Discussion to more cognitive impairment. This was a cross-sectional survey using a self-reported While there is a growing concern regarding possible questionnaire to assess subjective cognitive functioning, CRCI following primary cancer treatment [36], appropri- and applying DTI and graph theoretical analyses to in- ately assessing cognitive impairment in cancer survivors is vestigate brain structural networks after primary cancer an important aspect of CRCI [37]. “CRCI is usually subtle, treatment. Compared with non-cancer controls, patients and standard definitions of impairment on neuropsycho- reported a higher prevalence of subjective cognitive im- logical assessments may not formally identify these mild, pairment, especially in the subgroup of patients receiving but nonetheless functionally disruptive changes [12].” In chemotherapy. Regression analysis also confirmed that contrast, self-report methods may be more sensitive to receipt of chemotherapy was one of the significant predic- identify subtle changes, “because self-report taps a pa- tors of CRCI. Other risk factors related to CRCI in gynae- tient’s self-knowledge of their previous ability, whereas cological cancer survivors included employment status neuropsychological testing usually approximates premor- and depression. Consistent with previous studies, the bid functioning by using test-based norms [37]”.In prevalence of CRCI was significantly higher in survivors particular, self-reported cognitive measures also require with depression than in survivors without depression substantially fewer resources than do formal neurocogni- [15, 16, 34]. Yet at the same time, in the non-depressed tive tests, due to the lack of practice effects and clinical survivors, the severity CRCI was significantly higher in adaptability [16, 37]. While self-reported cognitive mea- survivors receiving chemotherapy than in survivors with- sures have several important strengths in research set- out receipt of chemotherapy. This study finding suggests tings, future studies should utilise both subjective and Table 4 Factors associated with cognitive complaints (FACT-Cog) in the patient group Variables Unstandardized Standard Standardized p-Value Coefficients (B) Error Coefficients Beta Age −0.129 0.123 −0.070 0.294 Employment status −9.884 3.336 −0.199 0.004 Receipt of chemotherapy −6.077 2.997 −0.129 0.044 Anxiety −0.935 0.515 −0.203 0.071 Depression −1.503 0.488 −0.331 0.002 BFI total score −0.127 0.065 −0.140 0.055 Abbreviation: BFI Brief Fatigue Inventory, FACT-Cog Functional Assessment of Cancer Therapy-Cognition Adjusted R = 0.408, p < 0.001 Bolded p values are statistically signifcant Zeng et al. BMC Cancer (2017) 17:796 Page 7 of 10 Table 5 Demographics, cognitive function and brain network measures in each group Mean (SD)/ n (%) p-Value Surgery only (n = 10) Receiving CT (n = 10) Healthy controls (n = 10) Age 50.50 (9.51) 50.90 (9.34) 50.50 (6.81) 0.993 Education levels 0.159 Primary school or below 8 (80.0) 9 (90.0) 7 (70.0) High school or above 2 (20.0) 1 (10.0) 3 (30.0) Employment status 0.329 Employed 1 (10.0) 0 (0) 10 (100) Unemployed or retired 9 (90.0) 10 (100) 0 (0) Marital status 0.355 Married 10 (100) 9 (90.0) 10 (100) Divorced 0 (0) 1 (10.0) 0 (0) FACT-Cog total score 77.50 (6.00) 59.40 (4.85) 78.60 (5.81) <0.001 Perceived cognitive impairment 43.70 (3.83) 31.90 (11.21) 46.50 (5.68) 0.046 Comments from others 13.90 (2.76) 9.30 (4.94) 11.60 (3.68) 0.070 Perceived cognitive ability 12.10 (2.02) 9.70 (4.69) 13.60 (3.65) 0.687 Impact on QOL 7.80 (3.64) 8.50 (4.19) 6.90 (4.45) <0.001 Graph metrics Small-worldness 1.276 (0.039) 1.191 (0.074) 1.290 (0.073) 0.004 Global efficiency 0.140 (0.002) 0.136 (0.004) 0.142 (0.005) 0.065 Local efficiency 0.199 (0.004) 0.199 (0.005) 0.201 (0.004) 0.697 Clustering coefficient 1.696 (0.296) 1.765 (0.314) 1.504 (0.261) 0.137 Characteristic path length 1.487 (0.099) 1.544 (0.139) 1.446 (0.094) 0.169 Abbreviation: CT Chemothrapy Bolded p values are statistically signifcant Fig. 1 Correlation of small-worldness properties with FACT-Cog total score Zeng et al. BMC Cancer (2017) 17:796 Page 8 of 10 Fig. 2 Correlation of characteristic path length with FACT-Cog total score objective neuropsychological assessments to quantify the be conducted to explore the causal associations be- prevalence, severity, and impact of CRCI in the Chinese tween CRCI and clinical factors, psychosocial variables, gynaecological cancer population, as few studies have been and brain networks. In addition, this study did not col- conducted to date on Chinese cancer survivors. lect details about patients’ chemotherapy regimens. This study found that patients after chemotherapy re- Hence, this study cannot discuss which chemotherapeutic ported the lowest level of small-worldness index and agents may influence cognition. Finally, heterogeneity of global and local network efficiency, compared with age- clinical variables, such as cancer type, disease stage, and matched non-cancer controls. Research evidence shows treatment modalities may have created sampling bias, that disrupted structural networks have been demon- which limits the generalisability of the results. While the strated to have detrimental effects on cognitive function- present study has limitations that need to be addressed in ing [10, 18, 22, 38]. Global and local network efficiency future studies, its findings are important to communicate has been demonstrated to be important for cognitive to patients and clinicians alike, especially due to the functioning, as global efficiency plays a key role in how increasing level of concern about subjective cognitive information may be efficiently exchanged across the impairment following cancer treatment. entire brain network [39]. In contract, local network efficiency measures the average of local subgraphs in a net- Conclusion work and indicates how tolerant a network is to local fail- When compared with non-cancer controls, a considerable ures [40]. Regarding the associations between structural proportion of gynaecological cancer survivors may exhibit network properties and subjective cognitive impairment, CRCI. After cancer treatment, 40.51% of Chinese gynaeco- this study found that higher values of small-worldness logical cancer patients perceived cognitive impairment. index and shorter characteristic path length were related to Moreover, cognitive impairment occurred not only in pa- higher FACT-Cog total scores (i.e. better cognitive func- tients who had received chemotherapy, but also in approxi- tioning). Study findings reveal that primary cancer treat- mately 10% of patients who were treated using surgery ment can result in a more random organisation of brain only. Lower cognitive functioning was associated with un- network changes, which contributed to reducing brain employment, receipt of chemotherapy, and depressive functional specificity and segregation, with implications for symptoms. This study provides the first evidence of brain cognitive functioning [10]. structural network alteration in gynaecological cancer pa- Limitations of the cross-sectional study design were tients post-treatment, and offers novel insights regarding the inability to explore the course of CRCI over time; the neurobiological change mechanisms of CRCI in gynae- additionally, the study could not provide causal infer- cological cancer patients. Primary cancer treatment can re- ences for factors associated with subjective cognitive im- sult in a more random organisation of structural brain pairment. Thus, future prospective cohort studies should networks, which may reduce brain functional specificity Zeng et al. BMC Cancer (2017) 17:796 Page 9 of 10 and segregation and have implications for cognitive impair- Received: 9 August 2017 Accepted: 16 November 2017 ment. 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Subjective cognitive impairment and brain structural networks in Chinese gynaecological cancer survivors compared with age-matched controls: a cross-sectional study

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Pubmed Central
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© The Author(s). 2017
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1471-2407
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1471-2407
DOI
10.1186/s12885-017-3793-4
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Abstract

Background: Subjective cognitive impairment can be a significant and prevalent problem for gynaecological cancer survivors. The aims of this study were to assess subjective cognitive functioning in gynaecological cancer survivors after primary cancer treatment, and to investigate the impact of cancer treatment on brain structural networks and its association with subjective cognitive impairment. Methods: This was a cross-sectional survey using a self-reported questionnaire by the Functional Assessment of Cancer Therapy-Cognitive Function (FACT-Cog) to assess subjective cognitive functioning, and applying DTI (diffusion tensor imaging) and graph theoretical analyses to investigate brain structural networks after primary cancer treatment. Results: A total of 158 patients with gynaecological cancer (mean age, 45.86 years) and 130 age-matched non- cancer controls (mean age, 44.55 years) were assessed. Patients reported significantly greater subjective cognitive functioning on the FACT-Cog total score and two subscales of perceived cognitive impairment and perceived cognitive ability (all p values <0.001). Compared with patients who had received surgery only and non-cancer controls, patients treated with chemotherapy indicated the most altered global brain structural networks, especially in one of properties of small-worldness (p = 0.004). Reduced small-worldness was significantly associated with a lower FACT-Cog total score (r = 0.412, p = 0.024). Increased characteristic path length was also significantly associated with more subjective cognitive impairment (r = −0.388, p = 0.034). (Continued on next page) * Correspondence: andy.cheng@polyu.edu.hk Department of Rehabilitation Sciences, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, China Full list of author information is available at the end of the article © The Author(s). 2017 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Zeng et al. BMC Cancer (2017) 17:796 Page 2 of 10 (Continued from previous page) Conclusion: When compared with non-cancer controls, a considerable proportion of gynaecological cancer survivors may exhibit subjective cognitive impairment. This study provides the first evidence of brain structural network alteration in gynaecological cancer patients at post-treatment, and offers novel insights regarding the possible neurobiological mechanism of cancer-related cognitive impairment (CRCI) in gynaecological cancer patients. As primary cancer treatment can result in a more random organisation of structural brain networks, this may reduce brain functional specificity and segregation, and have implications for cognitive impairment. Future prospective and longitudinal studies are needed to build upon the study findings in order to assess potentially relevant clinical and psychosocial variables and brain network measures, so as to more accurately understand the specific risk factors related to subjective cognitive impairment in the gynaecological cancer population. Such knowledge could inform the development of appropriate treatment and rehabilitation efforts to ameliorate cognitive impairment in gynaecological cancer survivors. Keywords: Subjective cognitive impairment, Chemotherapy, Brain networks, Gynaecological cancer, China Background [10, 19, 20]”. “Cognitivefunctions arebelievedtobesup- Cognitive impairment can be a significant and prevalent ported by parallel neural networks that must balance the problem for survivors with gynaecological cancer [1, 2]. competing demands of segregation and integration [21].” Cognitive impairment often refers to cancer-related cogni- Observational studies have found that alterations in the tive impairment (CRCI), which can be related to the can- brain structural network have been demonstrated to have cer itself, as well as to its treatment, for example surgery, adverse effects on cognition in both female and male cancer chemotherapy, and radiation therapy [3, 4]. As CRCI can survivors [10, 22]. However, much remains unknown about negatively impact quality of life and daily life functioning the effects of cancer and its treatment on brain structural in cancer survivors [5, 6], it is important to investigate networks in gynaecological cancer populations. such late effects and to understand the course and causes In view of the poor understanding of the psychosocial of CRCI for guiding future treatment and rehabilitation impacts of cancer treatment on perceived cognitive impair- efforts [7–10]. ment and brain networks in gynaecological cancer survi- CRCI may be related to a number of psychological fac- vors, it is important to explore CRCI and its associated tors that are seldom investigated in the context of gynae- factors in this population. Therefore, this study aims to cological cancer, although gynaecological cancer is the assess subjective cognitive functioning in gynaecological second most prevalent form of cancer among women in cancer survivors after primary cancer treatment, and to China [11]. Psychological distress has been found to be investigate the impact of cancer treatment on brain struc- negatively associated with neuropsychological performance tural networks and cancer treatment’s association with in cancer patients [8, 12]. Research has also found that per- cognitive impairment. This study also aims to explore asso- ceived cancer-related fatigue and anxiety resulted in CRCI ciated predictors of subjective cognitive impairment in in cancer survivors [13, 14]. Furthermore, treatment-related order to gain a deeper understanding of potential factors of mood changes, such as depression, have also significantly importance to CRCI. influenced many cancer survivors’ cognitive functioning [13, 15–17]. Other research found that age and education Methods levels were also associated with changes in cognitive func- This cross-sectional study was conducted to assess research tion among gynaecological cancer survivors [6]. participants’ subjective cognitive functioning, psychological Self-reported cognitive impairment are also associated wellbeing and brain structural networks immediately after with structural and functional changes in the brain that can primary cancer treatment. Age-matched non-cancer con- be detected by magnetic resonance imaging (MRI) [10, 17]. trols were simultaneously assessed using these outcome Brain networks are organised such that specialised regions measures for direct comparison. or clusters of neurons are highly connected to their neigh- bours but sparsely connected to distant regions [18]. “Brain Subjects structural network that tends to display as a small-world Patients were recruited in South China, at a tumor hospital network organization, which is characterized by high clus- and at a general hospital’s gynaecological oncology unit. tering in local regions while retaining relatively short path This study obtained ethical approval from the ethics com- lengths across all brain regions, supporting the notion of mittees at both Hunan Cancer Hospital and The Third the brain in an optimal balance between segregation and in- Affiliated Hospital of Guangzhou Medical University. Sub- tegration in information processing between brain regions jects were Chinese females ages 18 to 60 years; with a Zeng et al. BMC Cancer (2017) 17:796 Page 3 of 10 primary diagnosis of gynaecological cancer, without meta- score ≤ 85): ten out of 130 healthy controls had a FACT- static disease. Patient exclusion criteria were women who Cog summary score of less than 85, then 10 age-matched did not have a primary diagnosis of cancer, and/or who surgery patients and 10 age-matched patients with chemo- were in a terminal stage of cancer. Advertisements to re- therapy who also reported cognitive complaints were cruit non-cancer controls were posted in the hospitals’ included in brain MRI scanning.. This cut-off score common areas. Each non-cancer control subject was for the FACT-Cog was based on existing published within 2 years of the age of the patient. All participants had studies [17, 29]. DTI (diffusion tensor imaging) and to be without a diagnosis of a neurodegenerative disease or high-resolution structural T1-weighted brain scans any potential psychiatric disorder, and without the use of were obtained using single-shot echo-planar imaging psychotropic medication. All study participants provided (EPI) (acquisition matrix = 128 × 128; TE = Minimum; written informed consent to participate. TR = 16,000 ms; field of view = 256 mm × 256 mm; slice thickness/gap = 2.0 mm/0 mm; scanning time = 6 min Self-reported cognitive measures 56 s) with 32 distributed isotropic orientations for the Subjective cognitive functioning was assessed using the diffusion-sensitising gradients at a b-value of 1000 s/ Functional Assessment of Cancer Therapy-Cognitive mm and a b-value of 0. T1-weighted imaging was (FACT-Cog) scale. A self-report questionnaire measures achieved for morphometric (GM volume, cortical perceived cognitive impairment, comments from others, thickness and surface area) analysis using three- perceived cognitive ability, and impact of cognitive impair- dimensional fast spoiled-gradient recalled acquisition ment on quality of life [23]. The FACT-Cog consists of 37 in steady state in 166 coronal slices (acquisition matrix items and the overall cognitive function is the sum of the = 128 × 128; TE = 3.9 ms; TR = 9.6 ms; field of view = four subscales [23]. Higher scores indicate better cognitive 256 mm × 256 mm; slice thickness/gap = 2 mm/0 mm; function (i.e. lower subjective cognitive impairment). scanning time approximately 7 min). Psychological measures and general information sheet Statistical analysis Depression and anxiety were evaluated using the Chinese Data related to self-reported cognitive and psychological version of the Hospital Anxiety and Depression Scale measures were analysed using SPSS for Windows (ver- (HADS) [24]. The HADS is a 14-item self-assessment sion 21; IBM SPSS Statistics, Armonk, NY, USA). De- scale for a screening instrument to assess patients’ anxiety scriptive, comparison and regression analysis were used and depression levels. Each item is scored from 0 to 3. to analyse behavioural data. Descriptive statistics were The anxiety and depression sub-scores are both on scales used to describe sociodemographic and clinical charac- of 0 to 21. Higher total scores indicate higher levels of teristics of the sample. In comparing subject characteris- anxiety and depression [24]. The Chinese version of tics, cognitive and psychological measures between HADS has been reported to have acceptable internal patients and healthy controls used independent t-tests consistency and validity [25, 26], and is found to be a reli- for continuous variables, and chi-square or Fischer exact able tool for assessing psychological disturbances in can- tests were used for testing differences in categorical cer survivors [24]. The Brief Fatigue Inventory (BFI) has measures. To analyse the relationship between perceived been validated as a short and comprehensive instrument cognitive functioning and associated factors, a univariate to assess the severity of fatigue and fatigue-related impair- analysis was used followed by multiple regression ana- ment in cancer survivors [27, 28]. It consists of 10 items lysis. As sociodemographic factors, such as age and edu- and allows a basic assessment of the dimensions of activ- cation level, have been found to be associated with ity, ability to walk, mood, work, interpersonal relation- cognitive functioning in ovarian cancer survivors [6], it ships, and enjoyment of life [27]. Lower scores indicate is important to adjust for these factors, as they may less severity of fatigue [27]. A general information sheet potentially confound the relationship between subject- collected subjects’ demographic and clinical characteristics ive cognitive impairment and associated factors. The re- in terms of age, education level, employment, and marital siduals’ normality, linearity, and homoscedasticity were status. Patients’ clinical information included cancer checked to ensure the validity of the linear regression types, disease stage, and treatment received (e.g., Surgery, model [30]. Multiple linear regression analysis was per- Radiation, Chemotherapy). formed using a forward stepwise approach, in which vari- ables were significantly related to the total FACT-Cog MRI data acquisition score in the univariate analysis (it must be at a cutoff p The MRI data were acquired using a Philips 3 T Achieva value of 0.1 in the univariate analysis). Analysis of variance MRI scanner with an 8-channel head coil. Structural (ANOVA) was used to compare three participant groups brain networks were assessed in 30 participants who re- reported with subjective cognitive impairment and brain ported cognitive complaints (with the FACT-Cog summary structural network properties. Associations between brain Zeng et al. BMC Cancer (2017) 17:796 Page 4 of 10 network properties and subjective cognitive impairment Self-reported cognitive functioning were explored using Pearson’s correlation coefficient. From Table 2, gynaecological cancer survivors reported The threshold of P < 0.05 was used to assess statistical statistically higher subjective cognitive impairment than significance. healthy controls (p < 0.001), especially in the subscale scores of perceived cognitive impairment and perceived cognitive ability (all P values <0.001). Within the patient MRI data processing and analyses group, patients receiving chemotherapy scored lower in The DTI images were preprocessed using PANDA: a the FACT-Cog total scores and four subscale scores pipeline toolbox for analysing brain diffusion images (Table 3). According to Vardy et al. [17, 29], subjects (https://www.nitrc.org/projects/panda/). Each individual’s were categorised as having subjective cognitive impairment DTI dataset was registered to the same individual’shigh- with a FACT-Cog score of 85 or less. Of 158 patients, a resolution structural image and then into the standard total of 64 (40.51%) reported subjective cognitive impair- Montreal Neurological Institute (MNI) space using affine ment. Within the patient group, 16 subjects (10.13%) in transformations. Fractional Anisotropy (FA) images were the surgery group had subjective cognitive impairment and created from the pre-processed DTI data of all subjects. 48 subjects (30.38%) receiving chemotherapy had perceived All FA images were then non-linearly aligned to a common cognitive impairment. Of 130 healthy controls, a total of space. The mean FA image was used to represent the 10 subjects (7.69%) perceived cognitive impairment. centre of all tracts common to the group. Then, all sub- jects’ aligned FA data were projected onto the skeleton, Psychological measures and associated predictors of and the resulting data were subjected to voxelwise cross- FACT-cog outcomes subject statistics. Whole brain tractography was then per- While there were no statistically significant differences formed in the patient’s native space for each subject at between patients and healthy controls in terms of anx- each time point using a deterministic streamlined ap- iety, depression, and fatigue levels (Table 2), there were proach [31, 32], in which fibre pathways were recon- greater anxiety and fatigue levels in the subgroup of pa- structed by following the main diffusion tensor direction tients receiving chemotherapy (p = 0.014, and p < 0.001, as indicated by the principal eigenvector, until an FA value respectively) (Table 3). Associated predictors of cognitive of 0.20 or lower was reached, or until an angular turn of outcomes were explored using multivariate linear regres- 45 degrees or more was made [31, 32]. sion analysis (Table 4). Hierarchical multiple regression The assessment of brain network measures was per- analyses were performed to identify significant associated formed using the toolkit of graph theoretical network ana- factors for subjective cognitive impairment. A forward lysis (GRETNA) (https://www.nitrc.org/projects/gretna/). stepwise approach was used. There were no confounders The voxelwise brain structural network analyses were per- accounting for the association between associated predic- formed using the CPU-GUI platform of GRETNA [33]. tors and perceived cognitive functioning. The total The following characteristic graph metrics were estimated variance explained by the linear regression model was to describe the topological organisation of the whole 40.8%. Employment status, receipt of chemotherapy brain structural networks: global topological properties and depressive symptoms were statistically significant consist of small-world measures and global network ef- predictors of perceived cognitive functioning (standard- ficiency; local topological properties include local net- ized beta = −0.199, −0.129 and −0.331, respectively; all work efficiency, nodal clustering coefficient, and nodal p values <0.05). shortest path length. Brain structural networks and correlations with subjective Results cognitive impairment Research participant characteristics From Table 5, within global topological properties three Of the 288 participants, 158 patients with gynaecological groups had a small-world connectome organisation, as cancer had completed primary cancer treatment within the mean small-worldness index was greater than one. a week, and 130 noncancer controls were balanced in There were statistically significant differences in terms terms of age and marital status (Table 1). Nearly half of of small-worldness index (p = 0.004). Patients receiving patient participants (n = 81, 51.3%) were in the early stages chemotherapy had the lowest mean small-worldness of cancer, more than 60% of patients (n =98, 62.0%) index, compared with patients who received surgery only had a diagnosis of cervical cancer, and more than half and healthy controls. Lower small-worldness index of patients were receiving chemotherapy or a combin- was associated with more subjective cognitive impair- ation of chemotherapy and other cancer treatment. ment (r =0.412, p = 0.024) (Fig. 1). For the local topo- All research subjects’ demographic and clinical char- logical properties, there were no statistically significant acteristics are shown in Table 1. differences including nodal efficiency, nodal clustering Zeng et al. BMC Cancer (2017) 17:796 Page 5 of 10 Table 1 Demographic and clinical characteristics of participant groups Variables Mean (SD) / n (%) Patients (n = 158) Healthy controls (n = 130) p-Value Age (years) 45.86 (10.56) 44.55 (9.72) 0.157 Education levels <0.001 Primary school or below 103 (65.2) 65 (50.0) High school 34 (21.5) 15 (11.5) College or above 21 (13.3) 50 (38.5) Employment status <0.001 Employed but on medical leave 32 (20.3) 100 (76.9) Unemployed or retired 126 (79.7) 30 (23.1) Marital status 0.895 Single 9 (5.7) 8 (6.2) Married 142 (89.9) 117 (90.0) Divorced 6 (3.8) 5 (3.8) Widowed 1 (0.6) 0 (0.0) Disease stage Early stage 81 (51.3) Middle stage 57 (36.1) Advanced stage 20 (12.6) Disease diagnosis Cervical cancer 98 (62.0) Ovarian cancer 28 (17.7) Uterine cancer 14 (8.9) Other (e.g. GTN) 18 (11.4) Types of treatment Surgery 37 (23.4) Chemotherapy 14 (8.9) Surgery + chemotherapy 71 (44.9) Surgery + radiation + chemotherapy 21 (13.3) Radiation + chemotherapy 15 (9.5) Abbreviation: GTN Gestational Trophoblastic Neoplasia Table 2 Mean scores of cognitive and psychological measures in each group Measures Mean (SD) p-Value Patient (n = 158) Healthy controls (n = 130) FACT-Cog 99.80 (19.67) 112.33 (21.53) <0.001 Perceived cognitive impairment 57.38 (11.51) 65.21 (12.20) <0.001 Comments from others 14.51 (2.75) 14.37 (2.26) 0.658 Perceived cognitive ability 16.24 (6.81) 21.20 (8.02) <0.001 Impact on QOL 11.53 (3.54) 11.73 (4.05) 0.667 HADS Anxiety 5.86 (4.28) 5.40 (3.86) 0.352 Depression 5.17 (4.33) 4.52 (3.50) 0.171 BFI-total 32.52 (21.20) 27.25 (21.72) 0.062 Abbreviation: BFI Brief Fatigue Inventory, FACT-Cog Functional Assessment of Cancer Therapy-Cognition, HADS Hospital Anxiety and Depression Scale Bolded p values are statistically signifcant Zeng et al. BMC Cancer (2017) 17:796 Page 6 of 10 Table 3 Mean scores of cognitive and psychological measures in the patient group Measures Mean (SD) p-Value Surgery only (n = 37) Receiving CT (n = 121) FACT-Cog 108.25 (17.84) 97.28 (19.55) 0.003 Perceived cognitive impairment 61.76 (8.74) 56.04 (11.95) 0.002 Comments from others 15.24 (1.77) 14.29 (2.95) 0.019 Perceived cognitive ability 18.22 (7.71) 15.66 (6.44) 0.047 Impact on QOL 13.21 (3.12) 11.28 (4.20) 0.003 HADS Anxiety 4.35 (3.97) 6.32 (4.28) 0.014 Depression 4.00 (3.28) 5.52 (4.31) 0.060 BFI-total 19.08 (17.41) 34.33 (22.26) <0.001 Abbreviation: BFI Brief Fatigue Inventory, CT Chemothrapy, FACT-Cog Functional Assessment of Cancer Therapy-Cognition, HADS Hospital Anxiety and Depression Scale Bolded p values are statistically signifcant coefficient, and shortest path length (all p values >0.05). that CRCI could possibly be associated with chemotherapy Shorter characteristic path length, which indicates more rather than depressive symptoms. Previous research found efficient network organisation, was significantly associated that Chinese female cancer survivors reported higher levels with fewer subjective cognitive impairment (r = −0.388, of anxiety and depression, resulting in lower levels of work p = 0.034) (Fig. 2). productivity [35]. In consequence, employed cancer survi- vors experienced work limitations more frequently, leading Discussion to more cognitive impairment. This was a cross-sectional survey using a self-reported While there is a growing concern regarding possible questionnaire to assess subjective cognitive functioning, CRCI following primary cancer treatment [36], appropri- and applying DTI and graph theoretical analyses to in- ately assessing cognitive impairment in cancer survivors is vestigate brain structural networks after primary cancer an important aspect of CRCI [37]. “CRCI is usually subtle, treatment. Compared with non-cancer controls, patients and standard definitions of impairment on neuropsycho- reported a higher prevalence of subjective cognitive im- logical assessments may not formally identify these mild, pairment, especially in the subgroup of patients receiving but nonetheless functionally disruptive changes [12].” In chemotherapy. Regression analysis also confirmed that contrast, self-report methods may be more sensitive to receipt of chemotherapy was one of the significant predic- identify subtle changes, “because self-report taps a pa- tors of CRCI. Other risk factors related to CRCI in gynae- tient’s self-knowledge of their previous ability, whereas cological cancer survivors included employment status neuropsychological testing usually approximates premor- and depression. Consistent with previous studies, the bid functioning by using test-based norms [37]”.In prevalence of CRCI was significantly higher in survivors particular, self-reported cognitive measures also require with depression than in survivors without depression substantially fewer resources than do formal neurocogni- [15, 16, 34]. Yet at the same time, in the non-depressed tive tests, due to the lack of practice effects and clinical survivors, the severity CRCI was significantly higher in adaptability [16, 37]. While self-reported cognitive mea- survivors receiving chemotherapy than in survivors with- sures have several important strengths in research set- out receipt of chemotherapy. This study finding suggests tings, future studies should utilise both subjective and Table 4 Factors associated with cognitive complaints (FACT-Cog) in the patient group Variables Unstandardized Standard Standardized p-Value Coefficients (B) Error Coefficients Beta Age −0.129 0.123 −0.070 0.294 Employment status −9.884 3.336 −0.199 0.004 Receipt of chemotherapy −6.077 2.997 −0.129 0.044 Anxiety −0.935 0.515 −0.203 0.071 Depression −1.503 0.488 −0.331 0.002 BFI total score −0.127 0.065 −0.140 0.055 Abbreviation: BFI Brief Fatigue Inventory, FACT-Cog Functional Assessment of Cancer Therapy-Cognition Adjusted R = 0.408, p < 0.001 Bolded p values are statistically signifcant Zeng et al. BMC Cancer (2017) 17:796 Page 7 of 10 Table 5 Demographics, cognitive function and brain network measures in each group Mean (SD)/ n (%) p-Value Surgery only (n = 10) Receiving CT (n = 10) Healthy controls (n = 10) Age 50.50 (9.51) 50.90 (9.34) 50.50 (6.81) 0.993 Education levels 0.159 Primary school or below 8 (80.0) 9 (90.0) 7 (70.0) High school or above 2 (20.0) 1 (10.0) 3 (30.0) Employment status 0.329 Employed 1 (10.0) 0 (0) 10 (100) Unemployed or retired 9 (90.0) 10 (100) 0 (0) Marital status 0.355 Married 10 (100) 9 (90.0) 10 (100) Divorced 0 (0) 1 (10.0) 0 (0) FACT-Cog total score 77.50 (6.00) 59.40 (4.85) 78.60 (5.81) <0.001 Perceived cognitive impairment 43.70 (3.83) 31.90 (11.21) 46.50 (5.68) 0.046 Comments from others 13.90 (2.76) 9.30 (4.94) 11.60 (3.68) 0.070 Perceived cognitive ability 12.10 (2.02) 9.70 (4.69) 13.60 (3.65) 0.687 Impact on QOL 7.80 (3.64) 8.50 (4.19) 6.90 (4.45) <0.001 Graph metrics Small-worldness 1.276 (0.039) 1.191 (0.074) 1.290 (0.073) 0.004 Global efficiency 0.140 (0.002) 0.136 (0.004) 0.142 (0.005) 0.065 Local efficiency 0.199 (0.004) 0.199 (0.005) 0.201 (0.004) 0.697 Clustering coefficient 1.696 (0.296) 1.765 (0.314) 1.504 (0.261) 0.137 Characteristic path length 1.487 (0.099) 1.544 (0.139) 1.446 (0.094) 0.169 Abbreviation: CT Chemothrapy Bolded p values are statistically signifcant Fig. 1 Correlation of small-worldness properties with FACT-Cog total score Zeng et al. BMC Cancer (2017) 17:796 Page 8 of 10 Fig. 2 Correlation of characteristic path length with FACT-Cog total score objective neuropsychological assessments to quantify the be conducted to explore the causal associations be- prevalence, severity, and impact of CRCI in the Chinese tween CRCI and clinical factors, psychosocial variables, gynaecological cancer population, as few studies have been and brain networks. In addition, this study did not col- conducted to date on Chinese cancer survivors. lect details about patients’ chemotherapy regimens. This study found that patients after chemotherapy re- Hence, this study cannot discuss which chemotherapeutic ported the lowest level of small-worldness index and agents may influence cognition. Finally, heterogeneity of global and local network efficiency, compared with age- clinical variables, such as cancer type, disease stage, and matched non-cancer controls. Research evidence shows treatment modalities may have created sampling bias, that disrupted structural networks have been demon- which limits the generalisability of the results. While the strated to have detrimental effects on cognitive function- present study has limitations that need to be addressed in ing [10, 18, 22, 38]. Global and local network efficiency future studies, its findings are important to communicate has been demonstrated to be important for cognitive to patients and clinicians alike, especially due to the functioning, as global efficiency plays a key role in how increasing level of concern about subjective cognitive information may be efficiently exchanged across the impairment following cancer treatment. entire brain network [39]. In contract, local network efficiency measures the average of local subgraphs in a net- Conclusion work and indicates how tolerant a network is to local fail- When compared with non-cancer controls, a considerable ures [40]. Regarding the associations between structural proportion of gynaecological cancer survivors may exhibit network properties and subjective cognitive impairment, CRCI. After cancer treatment, 40.51% of Chinese gynaeco- this study found that higher values of small-worldness logical cancer patients perceived cognitive impairment. index and shorter characteristic path length were related to Moreover, cognitive impairment occurred not only in pa- higher FACT-Cog total scores (i.e. better cognitive func- tients who had received chemotherapy, but also in approxi- tioning). Study findings reveal that primary cancer treat- mately 10% of patients who were treated using surgery ment can result in a more random organisation of brain only. Lower cognitive functioning was associated with un- network changes, which contributed to reducing brain employment, receipt of chemotherapy, and depressive functional specificity and segregation, with implications for symptoms. This study provides the first evidence of brain cognitive functioning [10]. structural network alteration in gynaecological cancer pa- Limitations of the cross-sectional study design were tients post-treatment, and offers novel insights regarding the inability to explore the course of CRCI over time; the neurobiological change mechanisms of CRCI in gynae- additionally, the study could not provide causal infer- cological cancer patients. Primary cancer treatment can re- ences for factors associated with subjective cognitive im- sult in a more random organisation of structural brain pairment. Thus, future prospective cohort studies should networks, which may reduce brain functional specificity Zeng et al. BMC Cancer (2017) 17:796 Page 9 of 10 and segregation and have implications for cognitive impair- Received: 9 August 2017 Accepted: 16 November 2017 ment. 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BMC CancerPubmed Central

Published: Nov 28, 2017

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