Pretreatment Cancer-Related Cognitive Impairment in Hodgkin Lymphoma Patients

Background: Cancer-related cognitive impairment (CRCI) is one of the most serious side effects of cancer that negatively impact the quality of life of cancer patients and survivors. There is evidence of CRCI in Hodgkin lymphoma patients (HL); however, there is a lack of studies examining the presence of cognitive deficits before starting any treatment in HL patients. Methods: Forty patients (N=40) newly diagnosed with HL (with no previous cancer diagnoses) and 40 healthy controls (N=40) matched for age, sex, education, and premorbid intellect completed the neuropsychological battery and subjective and objective measures of affective distress and quality of life. Results: The results showed impairment in three out of six cognitive domains: verbal memory and learning, speed of processing/ psychomotor speed, and abstraction/executive functions in the HL patients before the initiation of any treatment. Speed of processing/psychomotor speed domain negatively correlated with depression. Conclusion: Impairment in verbal memory and learning and abstraction/executive functions domains in HL patients seems to occur before the initiation of treatment independently of anxiety, depression, or physical symptoms. This suggests that HL itself may cause cognitive deficits in these cognitive domains. However, the underlying causes of CRCI still remain unclear.

Keywords:

Subject: Medicine and Pharmacology - Hematology

1. Introduction

Cancer-related cognitive impairment (CRCI) is an important question related to decreased quality of life in oncological patients and survivors [1,2]. It is generally thought to have a typical frontal and subcortical cognitive profile and primarily involves the domains of memory, attention, executive functioning, and speed of processing [3]. These impairments are mild to moderate in severity [2], but they can have a significant impact on work capacity, ability to achieve work and educational goals, inability to drive or read, and decreased social connectedness, including occupational and social functioning, and can last for months or even years after treatment [1,4].

Persistent changes in cognitive function are frequently reported by lymphoma survivors [5,6,7], but only a few studies have focused on CRCI in Hodgkin lymphoma (HL) patients [8,9,10,11]. However, all these studies are focused on CRCI after chemotherapy or other adjuvant treatment in HL patients, reporting impairments in executive functions and memory [7], attention, working memory and planning, visual memory [8,9], verbal fluency, verbal and working memory, visual-motor coordination, problem-solving skills [6].

Despite, CRCI has been reported in up to 40 % of patients even prior to any treatment [12,13] and demonstrated in several cancer types, including some types of hematological malignancies [2,14,15,16]. In patients with acute myeloid leukemia/myelodysplastic syndrome (AML/MDS), lower than expected scores were found in tests of memory, verbal fluency, cognitive processing speed, executive function, and fine motor dexterity [15]. Analogously, a cognitive deficit in the executive and memory domains was reported for chronic myelogenous leukemia and myelodysplastic syndrome (CML/MDS) [16]. However, there is a complete lack of studies examining the presence of cognitive deficit in HL patients before starting any treatment.

To fill this gap, we conducted a neuropsychological study in a sample of HL patients before any treatment. We aimed to map the cognitive performance in adult HL patients upon the first detection of HL diagnosis with an extensive battery of objective neuropsychological tests. The HL patients were compared with healthy controls (HC), matched for age, sex, education (in years), and premorbid intellect. Owing to the previous findings of cognitive deficit before chemotherapy in other types of cancer [15,17,18], we expected worsen cognitive functioning in the HL group compared to HC before the initiation of any therapy. In addition, as the cognitive performance in the HL (and other oncological) patients may also be affected by psychological factors, such as anxiety, depression, or physical health, we included these potential affective confounds in the assessment and analytical procedures.

2. Materials and Methods

2.1. Procedures

The study was approved by the local ethics committees of the University Hospital Kralovske Vinohrady (UHKV; EK VP 16/0/2015) in Czech Republic. Ethical review committee: Cognitive impairment, structural and functional brain morphological sequelae of Hodgkin lymphoma treatment: Translational study; Approval number: EK VP 16/0/2015. All respondents signed an informed consent to participate in the study and to process the data for research purposes. Patients with HL were recruited from the Department of Internal Medicine and Hematology of UHKV. HC were recruited via advertising on social networks with a snowball sampling method. Participation in the research was voluntary without compensation. All participants underwent a neuropsychological examination at NIMH provided by a trained psychologist within a few days after establishing the diagnosis. The assessment required approximately 90-120 minutes (including breaks) to complete, and always began at the same time in the morning (due to possible influence of fatigue). Clinically significant symptoms of distress (i.e., depressive, or anxious symptoms) were operationally defined as ratings on the subjective and objective measures.

2.2. Participants

The HL group consisted of 40 patients (55% women) with newly diagnosed Hodgkin lymphoma. HL patients of all histological subtypes (except lymphocyte predominance Hodgkin’s disease) were recruited prior to surgery, adjuvant chemotherapy and/or radiotherapy. HL patients were firstly diagnosed with C811 (n=30; 75%), C812 (n=5; 12.5%), C814 (n=3; 7.5%), and C819 (n=1; 2.5%); 1 data is missing (2.5%) according to ICD-10 classifications [19] and had no previous cancer diagnoses. Exclusion criteria for HL patients included age above 18, previous history of HL or other cancer or chemotherapy and a serious neurological or mental disorder.

HC group consisted of 40 volunteers (55% women) meeting the exclusion criteria. Exclusion criteria for the HC included age above 18, previous history of cancer or chemotherapy and a serious neurological or mental disorder. The HC and HL subjects were matched in sex, age, years of education, and estimated premorbid intelligence. All pairs were matched for age and education in the interval of ± 3 years. For more details, see Table 1.

2.3. Measurements

The study subjects were administered a standardized neurocognitive battery [20] consisting of the Czech version of 13 test indices (28 subtests) - Auditory Verbal Learning Test (AVLT), Rey-Osterrieth Complex Figure Test (ROCFT), Trail Making Test (TMT), Verbal Fluency Test (VFT; phonemic and semantic), Continuous Performance Test 3 (CPT-3), four subtests of the Wechsler Adult Intelligence Scale (WAIS-III): Digits Span, Similarities, Digit Symbols – Coding, Letter-Number Sequencing, Logical Memory from Wechsler Memory (WMS-IIIa) subtest, and the Stroop Test. The Czech Reading Test [21] was used as a measure of premorbid intelligence.

All tests were standardized and validated on a healthy Czech population, designed as a Matrics-like battery, and divided into six cognitive domains: attention/vigilance, memory and learning, working memory/flexibility, verbal memory and learning, speed of processing/psychomotor speed, and abstraction/executive functions [22]. All these domains have been found to be impaired in HL patients after chemotherapy [8,9,10,11]. Raw scores of the individual test methods transformed to z-scores were included as input variables for the Principal Component Analysis (PCA; rotation method: varimax with Kaiser normalization) using a limited number of six anticipated factors [22]. The results of the PCA were used to adjust the final composition of the cognitive domains. The reduction of 28 subtests scores to six major cognitive domains by PCA was applied to reduce the dimensionality (number of subtests) and to enable comparison with previous studies of CRCI. The composition and consistency of the cognitive domains are presented in Table 2.

To evaluate psychological distress in terms of depression and anxiety, the participants completed self-reported questionnaires; the Beck Depression Inventory (BDI-II) [23] and the Beck Anxiety Inventory (BAI-II) [24]. For complementary objective psychometrics, we applied the Hamilton Depression Rating Scale (HAM-D) [25] and the Hamilton Anxiety Rating Scale (HAM-A) [26]. Individual subjects’ quality of life was estimated using WHOQOL-BREF [27].

2.4. Data Processing and Statistical Analysis

Data processing and statistical analysis were processed using IBM SPSS Statistics 23 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to analyze the frequencies, means, and standard deviations of the study variables. The main analyses focused on the between-group differences in cognitive performance, clinical symptoms, and quality of life in the patients and controls. The normality of the score distribution was tested by the Shapiro-Wilk Test. Data were not normally distributed among several variables, so nonparametric statistical methods were used for further analysis. The statistical significance of group differences was tested with the Mann-Whitney U-Test, and the Chi-Square Test was used to test group differences in sex distribution. The raw scores of cognitive subtests of each participant were transformed to z-scores based on the normative data for the individual test methods [20]. Additionally, differences were also calculated for the z-scores of every cognitive domain. To indicate statistical significance, two-sided p-values of 0.05 were corrected using a flexible Bonferroni-Holm procedure for multiple comparison. The relationship between performance in cognitive domains and the subjective and objective measures of affective and physical distress in the HL sample was evaluated using Spearman correlations. Linear regression models with the enter method were used to predict the HL patients’ cognitive impairments based on anxiety, depression, and physical and psychological health as predictors.

3. Results

The final sample included 40 HL patients and 40 HC. The studied groups did not differ in sex, age, years of education, or mean estimated premorbid intelligence. The demographic data for both groups and their statistical comparisons are presented in Table 1.

3.1. Neuropsychological Evaluations

Significant between-group differences were found in several subtests, i.e., the Auditory Verbal Learning Test- set VI and recognition; Verbal Fluency Test – semantic; Trail Making Test (part A and B); and Similarities (Table 2). Differences in AVLT set IV and VFT—semantic, on the other hand, were not considered significant because they did not pass the Bonferroni-Holm adjusted alpha threshold for multiple comparison. Other measures of the neurocognitive battery showed no significant differences between the studied groups. Analyses of the z-scores for the particular cognitive domains revealed significant differences in 3 out of 6 domains. We may consider cognitive impairment in HL patients in verbal memory and learning, speed of processing/psychomotor speed, and abstraction/executive functions (Table 3).

3.2. Subjective and Objective Measurement Outcomes

The HL patients scored significantly higher on both subjective and objective measures of anxiety (HAM-A, BAI-II) compared to HC (Table 4). A significantly higher score was also identified for the objective scale of depression (HAM-D) in the HL patients, but the patients did not report increased severity of depression in the self-reported inventory (BDI-II). Significant differences between the groups were found in the quality of life of the respondents. As expected, the HL patients scored significantly lower in the domain of physical health, but they perceived their social relationships as better than HC.

3.3. Correlates and Predictors of Cognitive Alterations in HL Patients

The domains of anxiety (BAI-II, HAM-A), depression (BDI-II, HAM-D), and quality of life (WHOQOL-BREF; physical and psychological health) may negatively influence cognitive performance. Spearman’s correlational analysis was used to evaluate their influence on impaired cognitive domains (Table 5). With a medium effect size, speed of processing/psychomotor speed domain was negatively correlated with BDI-II. Therefore, we may consider the influence of depression on this domain. Positive correlations were also found between speed of processing/psychomotor speed and physical health, but the result did not hold after multiple comparison correction.

The linear regression models with the enter method were calculated to identify possible predictors of cognitive impairments in HL patients, including anxiety and depression scales and physical and psychological health scales as predictors (Table 6). The linear regression models were estimated separately for each cognitive domain (dependent variable), in which we found significant impairments (between-group differences). The regression analyses showed no significant model (Table 6).

4. Discussion

The main finding of this study is the confirmation of decreased cognitive functions before any treatment in patients with HL. The neuropsychological examination identified impaired cognitive performance in three out of six cognitive domains, i.e., verbal memory and learning, speed of processing/ psychomotor speed, and abstraction/executive functions. In the working memory/flexibility domain, only one subtest was found to be impaired, but not the whole domain. On the contrary, our results suggest that HL patients do not have difficulty with attention/vigilance, and memory and learning (in the meaning of visuospatial modality). Performance in cognitive domains was further analyzed to eliminate the influence of physical and affective symptoms related to the distress of a recent cancer diagnosis. However, only one cognitive domain, speed of processing/ psychomotor speed, was found to be negatively influenced by depression. In contrast, our findings document that deterioration in the verbal memory and learning, and abstraction/executive functions domains are present in HL before the initiation of treatment and occur independently of anxiety, depression, or physical symptoms. This suggests that HL may cause cognitive deficits in these cognitive domains.

This finding is in line with memory and learning impairments identified before the initiation of therapy in breast [18,28], colorectal [29], and lung cancer patients [30,31]. Prior to treatment, patients with some hematological malignancies, such as AML/MDS and CML/MDS, have also been reported to have verbal memory and learning cognitive deficits [15,16]. The memory and learning domain deficits have also been previously identified in HL patients after treatment [8,9] but our study is the first to document them prior to treatment. Deficits in executive functions were also previously reported in HL survivors after chemotherapy [9], using the same subtest as in our study [6], so it is possible to hypothesize that some impairment was already present at the beginning of the disease and that it persists after chemotherapy. Analogously, an executive function deficit prior to treatment was also reported in AML/MDS [15] and CML/MDS [16].

Our findings of impaired speed of processing/psychomotor speed correspond with previous studies of HL patients after treatment [9,32]. We found decreased performance in both semantic verbal fluency and TMT-A subtests before treatment. Studies of HL patients have also shown impairments in TMT-A [9] and phonemic fluency [32] after treatment. Moreover, verbal fluency and cognitive processing speed in AML/MDS patients [15] and processing speed in colorectal cancer patients [29] have been shown to be affected before treatment. These findings may show evidence of a pre-treatment deficit that also persists. However, depression affected the performance in this domain in our sample. Some previous results also confirmed that fatigue, anxiety, and other emotional problems reported in HL patients negatively influence their cognitive performance [7]. Some studies, on the hand, did not associate the psychological or surgery factors with cognitive functions [1] before the initiation of therapies [4,33,34].

Not surprisingly, HL patients scored significantly higher on subjective and objective measures of anxiety and the objective scale of depression. A cancer diagnosis is associated with a high level of psychological stress in patients [35]. Anxiety and/or depression in these patients are related to uncertainty about the prognosis, planned chemotherapy or radiotherapy treatment, progressive physical deterioration, or thoughts of possible death [35]. The HL patients in our sample also reported a decrease in quality of physical health, which may be a consequence of cancer symptoms. On the other hand, the HL patients reported better social relationships compared to HC, which may be caused by the greater need and awareness for social relations and social support in individuals facing a serious health crisis.

In conclusion, our findings of cognitive impairments in HL patients before initiation of treatment are fully consistent with the previously described pattern of cognitive impairment in CRCI (i.e., disruption of learning and memory, executive functions, and psychomotor speed). Our results suggest that cognitive impairment in HL patients could be associated with HL itself and its related symptoms. CRCI research focused on the HL population has evaluated post-chemotherapy cognitive functioning, but baseline data are completely lacking. The uniqueness of this study lies in the provision of missing pre-treatment data and in the confirmation of CRCI in HL patients. Despite that, a possible limitation of our study may be the small sample size. Our sample, on the other hand, was well-matched in terms of demographic data and corresponds to or exceeds the sample sizes of other previous studies. Moreover, we evaluated the physical health, but not the fatigue itself which was considered as possible influencing factor in CRCI in some studies [7,9,13]. Unfortunately, given the design of our study, the underlying mechanisms of CRCI in HL and other cancers remain unexplained.

Further research should elucidate whether the cognitive deficit is improved/mitigated, or, on the contrary, exacerbated by the subsequent course of HL and its treatment. In addition, longitudinal neuroimaging studies should address the structural and functional neuroanatomical changes related to cognitive deficits in HL. Clinically, further research should focus on new neuropsychological cognitive rehabilitations that may help to improve patients’ quality of life and functional and work capacities. Inspired by our results, we also suggest that cognitive functions should be monitored from the beginning of HL and complemented by cognitive training and remediation if affected. Healthcare professionals need to consider that memory impairment may interfere with a patient’s daily life functioning and may also affect their adherence to the treatment regimen. Therefore, healthcare professionals should also provide patients with remediation strategies to manage cognitive deficits if they occur at any stage of HL.

Author Contributions

Conceptualization, V.J., D.F., and J.H; Methodology, V.J., D.F., and J.H; Formal Analysis, V.J.; Investigation, V.J, D.F.; Data Curation, V.J., D.F.; Writing – Original Draft Preparation, V.J, D.F., and J.J; Writing – Review & Editing, I.F, J.J., and J.H; Visualization, V.J; Supervision, I.F, and J.H; Project Administration, V.J, and D.F.; Funding Acquisition, J.H.

Funding

This study is the result of the research project AZV MZ CR 16- 29857A, institutional programs of support MH CZ – DRO (NUDZ, 00023752) and COOPERATIO Neurosciences (038).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the research ethics committees of the National Institute of Mental Health (NIMH) and the University Hospital Kralovske Vinohrady (UHKV) in Czech Republic.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented are available on request from the corresponding author.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

References

Janelsins, M.C.; Kesler, S.R.; Ahles, T.A.; Morrow, G.R. Prevalence, mechanisms, and management of cancer-related cognitive impairment. Int Rev Psychiatry 2014, 26, 102–113. [Google Scholar] [CrossRef] [PubMed]
Olson, B.; Marks, D.L. Pretreatment Cancer-Related Cognitive Impairment-Mechanisms and Outlook. Cancers 2019, 11, 687. [Google Scholar] [CrossRef] [PubMed]
Wefel, J.S.; Vardy, J.; Ahles, T.; Schagen, S.B. International Cognition and Cancer Task Force recommendations to harmonise studies of cognitive function in patients with cancer. Lancet Oncol. 2011, 12, 703–708. [Google Scholar] [CrossRef]
Wefel, J.S.; Kesler, S.R.; Noll, K.R.; Schagen, S.B. Clinical characteristics, pathophysiology, and management of noncentral nervous system cancer-related cognitive impairment in adults. CA Cancer J Clin. 2015, 65, 123–138. [Google Scholar] [CrossRef]
Gates, P.; Krishnasamy, M.; Wilson, C.; Hawkes, E.A.; Doré, V.; Perchyonok, Y.; Rowe, C.C.; Walker, A.K.; Vardy, J.L.; de Ruiter, M.B.; Cushion, T.; Dhillon, H.M.; Gough, K. Cancer-related cognitive impairment in patients with newly diagnosed aggressive lymphoma undergoing standard chemotherapy: a longitudinal feasibility study. Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer 2022, 30, 7731–7743. [Google Scholar] [CrossRef]
Janelsins, M.C.; Mohamed, M.; Peppone, L.J.; Magnuson, A.; Belcher, E.K.; Melnik, M.; Dakhil, S.; Geer, J.; Kamen, C.; Minasian, L.; Reagan, P.M.; Mohile, S.G.; Morrow, G.R.; Ahles, T.A.; Heckler, C.E. Longitudinal Changes in Cognitive Function in a Nationwide Cohort Study of Patients With Lymphoma Treated With Chemotherapy. Journal of the National Cancer Institute 2022, 114, 47–59. [Google Scholar] [CrossRef] [PubMed]
Wouters, H.; Baars, J.W.; Schagen, S.B. Neurocognitive function of lymphoma patients after treatment with chemotherapy. Acta oncologica (Stockholm, Sweden) 2016, 55, 1121–1125. [Google Scholar] [CrossRef]
Vinokurova, E.G.; Marchenko, A.A.; Khrushchev, S.O.; Olexenko, L.V.; Rupchev, G.E.; Vybornykh, D.E.; Moiseeva, T.N. Cognitive impairments in patients with hodgkin’s lymphoma. HemaSphere 2018, 2, 22–23. [Google Scholar]
Trachtenberg, E.; Mashiach, T.; Ben Hayun, R.; Tadmor, T.; Fisher, T.; Aharon-Peretz, J.; Dann, E.J. Cognitive impairment in hodgkin lymphoma survivors. British journal of haematology 2018, 182, 670–678. [Google Scholar] [CrossRef]
Magyari, F.; Ivánka, T.; Égerházi, A.; Simon, Z.; Miltényi, Z.; Kósa, K.; Illés, Á. Cognitive dysfunction after treatment for hodgkin lymphoma. HemaSphere 2018, 2. [Google Scholar] [CrossRef]
Magyari, F.; Virga, I.; Simon, Z.; Miltényi, Z.; Illés, A.; Kósa, K.; Ivánka, T.; Berecz, R.; Égerházi, A.; Illés, Á. Assessment of cognitive function in long-term Hodgkin lymphoma survivors, results based on data from a major treatment center in Hungary. Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer 2022, 30, 5249–5258. [Google Scholar] [CrossRef] [PubMed]
Ahles, T.A.; Root, J.C.; Ryan. E.L. Cancer- and cancer treatment-associated cognitive change: an update on the state of the science. J Clin Oncol. 2012, 30, 3675–3686. [Google Scholar] [CrossRef] [PubMed]
Lange, M.; Joly, F.; Vardy, J.; Ahles, T.; Dubois, M.; Tron, L.; Winocur, G.; De Ruiter, M.B.; Castel, H. Cancer-related cognitive impairment: an update on state of the art, detection, and management strategies in cancer survivors. Annals of oncology : official journal of the European Society for Medical Oncology 2019, 30, 1925–1940. [Google Scholar] [CrossRef]
Ahles, T.A.; Saykin, A. Cognitive effects of standard-dose chemotherapy in patients with cancer. Cancer investigation 2001, 19, 812–820. [Google Scholar] [CrossRef]
Meyers, C.A.; Albitar, M.; Estey, E. Cognitive impairment, fatigue, and cytokine levels in patients with acute myelogenous leukemia or myelodysplastic syndrome. Cancer 2005, 104, 788–793. [Google Scholar] [CrossRef] [PubMed]
Meadows, M.E.; Chang, G.; Jones, J.A.; Antin, J.R.; Orav, E.J. Predictors of neuropsychological change in patients with chronic myelogenous leukemia and myelodysplastic syndrome. Archives of clinical neuropsychology: the official journal of the National Academy of Neuropsychologists 2013, 28, 363–374. [Google Scholar] [CrossRef]
Simó, M.; Root, J.C.; Vaquero, L.; Ripollés, P.; Jové, J.; Ahles, T.; Navarro, A.; Cardenal, F.; Bruna, J.; Rodríguez-Fornells, A. Cognitive and brain structural changes in a lung cancer population. Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer 2015, 10, 38–45. [Google Scholar] [CrossRef] [PubMed]
Wefel, J.S.; Lenzi, R.; Theriault, R.; Buzdar, A.U.; Cruickshank, S.; Meyers, C.A. (2004). ‘Chemobrain’ in breast carcinoma?: a prologue. Cancer 2004, 101, 466–475. [Google Scholar] [CrossRef] [PubMed]
19. World Health Organization (WHO). The ICD-10 classification of mental and behavioural disorders, 2016; -10.
Preiss, M.; Bartoš, A.; Čermáková, R.; Nondek, M.; Benešová, M. ; Rodriguez. M.; Raisová, M.; Laing, H.; Mačudová, G.; Bezdíček, O.; Nikolai, T. Neuropsychologická baterie Psychiatrického centra Praha: Klinické vyšet, P: kognitivních funkcí. Praha, 2012. [Google Scholar]
Krámská, L. Hodnocení premorbidního intelektu v neuropsychologii. Český test čtení slov. Otrokovice, Propsyco; 2014.
Rodriguez, M.; Fajnerová, I.; Sedláková, K.; Dorazilová, A.; Vorácková, V.; Paštrnák, M. Cluster analysis and correlations between cognitive domains: cognitive performance in a Czech sample of first episodes schizophrenia spectrum disorders - Preliminary results. Psychiatrie 2017, 21, 4–11. [Google Scholar]
Ptáček, R.; Raboch, J.; Vnukova, M.; Hlinka, J.; Cervenkova, M. (2017). Standardization of Czech version of beck depression inventory (BDI II). European Psychiatry 2017, 41, S539–S539. [Google Scholar] [CrossRef]
Kamaradova, D.; Prasko, J.; Latalova, K.; Panackova, L.; Svancara, J.; Grambal, A.; Sigmundova, Z.; Ociskova, M.; Bares, V.; Cakirpaloglu, S.; Jelenova, D.; Kasalova, P.; Kovacsova, A.; Vrbova, K. Psychometric properties of the Czech version of the Beck Anxiety Inventory - comparison between diagnostic groups. Neuro endocrinology letters 2015, 36, 706–712. [Google Scholar] [PubMed]
Hamilton, M. A rating scale for depression. J Neurol Neurosurg Psychiatry 1960, 23, 56–62. [Google Scholar] [CrossRef]
Hamilton, M. The assessment of anxiety states by rating. Br J Med Psychol 1959, 32, 50–55. [Google Scholar] [CrossRef] [PubMed]
27. World Health Organization. The world health organization quality of life (WHOQOL)-BREF, 2012.
Shilling, V.; Jenkins, V.; Morris, R.; Deutsch, G.; Bloomfield, D. The effects of adjuvant chemotherapy on cognition in women with breast cancer--preliminary results of an observational longitudinal study. Breast (Edinburgh, Scotland) 2005, 14, 142–150. [Google Scholar] [CrossRef]
Vardy, J.L.; Dhillon, H.M.; Pond, G.R.; Rourke, S.B.; Bekele, T.; Renton, C.; Dodd, A.; Zhang, H.; Beale, P.; Clarke, S.; Tannock, I.F. Cognitive Function in Patients With Colorectal Cancer Who Do and Do Not Receive Chemotherapy: A Prospective, Longitudinal, Controlled Study. Journal of clinical oncology: official journal of the American Society of Clinical Oncology 2015, 33, 4085–4092. [Google Scholar] [CrossRef]
Meyers, C.A.; Byrne, K.S.; Komaki, R. Cognitive deficits in patients with small cell lung cancer before and after chemotherapy. Lung cancer (Amsterdam, Netherlands) 1995, 12, 231–235. [Google Scholar] [CrossRef]
Simó, M.; Root, J.C.; Vaquero, L.; Ripollés, P.; Jové, J.; Ahles, T.; Navarro, A.; Cardenal, F.; Bruna, J.; Rodríguez-Fornells, A. Cognitive and brain structural changes in a lung cancer population. Journal of thoracic oncology: official publication of the International Association for the Study of Lung Cancer. [CrossRef]
Baudino, B.; D’agata, F.; Caroppo, P.; Castellano, G.; Cauda, S.; Manfredi, M.; Geda, E.; Castelli, L.; Mortara, P.; Orsi, L.; Cauda, F.; Sacco, K.; Ardito, R.B.; Pinessi, L.; Geminiani, G.; Torta, R.; Bisi, G. The chemotherapy long-term effect on cognitive functions and brain metabolism in lymphoma patients. Q J Nucl Med Mol Imaging. 2012, 56, 559–568. [Google Scholar]
Ahles, T.A.; Saykin, A.J.; Furstenberg, C.T.; Cole, B.; Mott, L.A.; Skalla, K.; Whedon, M.B.; Bivens, S.; Mitchell, T.; Greenberg, E.R.; Silberfarb, P.M. Neuropsychologic impact of standard-dose systemic chemotherapy in long-term survivors of breast cancer and lymphoma. Journal of clinical oncology: official journal of the American Society of Clinical Oncology 2002, 20, 485–493. [Google Scholar] [CrossRef]
Cimprich, B.; So, H.; Ronis, D.L.; Trask, C. Pre-treatment factors related to cognitive functioning in women newly diagnosed with breast cancer. Psycho-oncology 2005, 14, 70–78. [Google Scholar] [CrossRef]
Zabalegui, A.; Sanchez, S.; Sanchez, P.D.; Juando, C. Nursing and cancer support groups. Journal of advanced nursing 2005, 51, 369–381. [Google Scholar] [CrossRef]

Table 1. Demographic data of the study participants and between-group comparison results.

	HL patients (N= 40)	Healthy controls (N= 40)	Mann-Whitney U test/ Chi square
	Mean ± SD/Frequency	Mean ± SD/Frequency
Sex	55% women (n=22)	55% women (n=22)	χ² = 0.80; p = 0.371
Age (years)	39.14 ± 12.41 Range 19-67	38.41 ± 11.69 Range 18-65	U= 764.0; p = 0.729
Education (years)	14.29 ± 2.74 Range 11-21	14.74 ± 3.28 Range 11-25	U= 674.0; p = 0.614
Education (category) Elementary school Certificate of apprenticeship High school education University degree Postdoctoral education	2.5% (1) 20% (8) 47.5% (19) 27.5% (11) 2.5% (1)	5% (2) 17.5% (7) 45% (18) 30% (12) 2.5% (1)
The Czech Reading Test (Premorbid intellect measurement)	27.77 ± 12.33	30.33 ± 11.45	U= 480.0; p = 0.104

Table 2. Raw scores of the individual test results and between-group comparison of z-scores.

Domain	Subtests	HL patients Mean ± SD	HC group Mean ± SD	Mann-Whitney U test p-value
Attention/ vigilance	(CPT 3-com) (CPT 3-om) (CPT 3-var) (CPT 3-det) (CPT 3-per) (CPT 3-hitsebch)	51.10 ± 9.39 47.82 ± 6.36 46.42 ± 5.86 49.77 ± 9.16 48.59 ± 6.06 49.44 ± 8.82	48.03 ± 9.02 47.21 ± 4.49 47.23 ± 9.26 46.67 ± 8.73 49.51 ± 8.62 48.23 ± 8.61	U= 593.0; p= 0.094 U= 728.5; p= 0.744 U= 705.0; p= 0.713 U= 639.0; p= 0.224 U= 735.0; p= 0.792 U= 700.5; p= 0.548
Visuospatial memory and learning	(ROCFT-3) (ROCFT-30)	19.35 ± 6.70 19.56 ± 6.46	20.03 ± 6.03 20.05 ± 6.15	U= 761.0; p= 0.704 U= 728.0; p= 0.483
Working memory/ flexibility	(WAIS-III-DSp) (WAIS-III-LNS) (TMT-B) (ST-CW) (ST-IF)	15.6 ± 3.47 8.90 ± 2.69 86.30 ± 56.74 43.63 ± 10.64 5.25 ± 8.92	17.55 ± 5.41 10.33 ± 3.45 66.73 ± 28.77 43.70 ± 12.24 2.07 ± 11.93	U= 655.0; p= 0.163 U= 610.5; p= 0.095 U= 473.5; p= 0.006 U= 665.0; p= 0.553 U= 603.0; p= 0.159
Verbal memory and learning	(AVLT- I-V) (AVLT- B) (AVLT- VI) (AVLT- 30) (AVLT- rec) (WMSIII-LM-imm) (WMSIII-LM-del)	50.80 ± 8.88 5.58 ± 1.78 10.28 ± 2.73 10.50 ± 3.02 13.25 ± 1.72 42.03 ± 8.72 26.89 ± 6.98	54.10 ± 8.38 5.85 ± 1.82 11.83 ± 2.77 11.28 ± 2.94 14.23 ± 1.00 42.35 ± 10.60 27.77 ± 9.20	U= 596.0; p= 0.190 U= 759.5; p= 0.692 U= 532.5; p= 0.010* U= 156.5; p= 0.103 U= 526.0; p= 0.006 U= 599.0; p= 0.478 U= 578.0; p= 0.343
Speed of processing/ Psychomotor speed	(WAISIII-DS-C) (ST-W) (ST-C) (VFT-phonemic) (VFT-semantic) (TMT-A)	70.05 ± 17.81 84.76 ± 12.34 69.55 ± 10.24 41.08 ± 10.86 21.77 ± 5.65 35.55 ± 13.82	76.63 ± 15.47 88.25 ± 11.07 72.40 ± 11.49 44.00 ± 11.83 25.53 ± 6.28 27.15 ± 7.95	U= 610.0; p= 0.131 U= 603.5; p= 0.160 U= 638.0; p= 0.490 U= 633.0; p= 0.270 U= 542.0; p= 0.019* U= 421.5; p= 0.001
Abstraction/ Executive functions	(WAIS-III-Sim)	21.08 ± 4.29	23.97 ± 4.39	U= 489.0; p= 0.012

Abbreviations: CPT - continuous performance test, com - commissions, om - omissions, var -variability, det - detectability, per - perseverations, hitsebch - hit reaction time block change; ROCFT - Rey Osterrieth complex figure, 3 - immediate recall after 3 minutes, 30 - delayed recall after 30 minutes; ST-W - Stroop test - words, ST-C - Stroop test – colors , ST-CW - Stroop test, colors words subtest, ST-IF - Stroop test, interference score; AVLT - auditory verbal learning test, I-V - trial 1 - 5, VI - trial 6, 30 - delayed recall after 30 minutes, rec - recognition; WMSIII - Wechsler memory scale, LM - logical memory , imm - immediate recall, del - delayed recall; WAIS-III – Wechsler adult intelligence scale, DSp – digits span, LNS – letter-number sequencing, DS-C – digit symbols-coding; * results did not pass the Bonferroni-Holm adjusted alpha threshold for multiple comparison.

Table 3. Results of between-group differences in domains expressed in z-scores.

Cognitive domain	HL patients Mean ± SD	HC group Mean ± SD	Mann-Whitney U test p-value
Attention/ vigilance	0.13 ± 0.42	0.17 ± 0.46	U= 710.5; p =0.617
Visuospatial memory and learning	0.23 ± 0.94	0.32 ± 0.93	U= 683.0; p = 0.437
Working memory/ flexibility	-0.37 ± 0.61	-0.15 ± 0.88	U= 664.5; p = 0.337
Verbal memory and learning	-0.27 ± 0.85	0.04 ± 0.75	U= 578.5; p = 0.048
Speed of processing/ Psychomotor speed	-0.54 ± 0.67	-0.19 ± 0.66	U= 553.0; p = 0.038
Abstraction/ Executive functions	-0.53 ± 0.64	-0.03 ± 0.84	U= 498.0; p = 0.012

Table 4. Descriptive statistics and statistical comparisons in the subjective and objective measures of clinical symptoms.

Measures	HL patients	HC group	Mann-Whitney U test
	Mean ± SD	Mean ± SD	p-value
BAI-II	8.92 ± 6.97	6.51 ± 8.23	U= 513.5; p= 0.030
BDI-II	4.26 ± 3.73	3.31 ± 3.47	U= 625.5; p= 0.173
HAM-D	8.77 ± 5.86	3.74 ± 4.13	U= 367.0; p< 0.001
HAM-A	8.67 ± 6.23	5.28 ± 5.58	U= 488.5; p= 0.006
WHOQOL-BREF
Physical health	15.2 ± 2.79	17.3 ± 1.49	U= 404.5; p< 0.001
Psychological health	15.9 ± 2.69	16.2 ± 1.99	U= 759.0; p= 0.988
Social relationships	16.8 ± 2.48	15.4 ± 2.44	U= 492.5; p= 0.007
Environmental Quality of Life	15.9 ± 2.08	16.5 ± 1.85	U= 650.5; p= 0.269

Table 5. Results of Spearman correlational analyses between subjective and objective measures of clinical symptoms and impaired cognitive domain in HL patients.

Cognitive domain	BAI	BDI	HAM-D	HAM-A	Physical health	Psychological health
Verbal memory and learning	r_s= -0.258 p= 0.117	r_s= -0.176 p= 0.290	r_s= -0.254 p= 0.123	r_s= -0.187 p= 0.261	r_s= 0.138 p= 0.409	r_s= 0.017 p= 0.919
Speed of processing/ Psychomotor speed	r_s= -0.253 p= 0.125	r_s= -0.115 p= 0.491	r_s= -0.436** p= 0.006	r_s= -0.268 p= 0.103	r_s= 0.349*# p= 0.032	r_s= 0.240 p= 0.147
Abstraction/ Executive functions	r_s= 0.045 p= 0.787	r_s= 0.134 p= 0.423	r_s= 0.038 p= 0.823	r_s= 0.093 p= 0.579	r_s= 0.084 p= 0.617	r_s= -0.155 p= 0.353

Note. * p < .05, ** p < .01, *** p < .001. # results did not pass the Bonferroni-Holm adjusted alpha threshold for multiple comparison.

Table 6. Linear regression model of cognitive impairment predictors.

Cognitive domain	N	R	R²	R²adj	F-value	p-value
Verbal memory and learning	38	0.415	0.172	0.012	1.076	0.398
Speed of processing/ Psychomotor speed	38	0.540	0.292	0.155	2.128	0.078
Abstraction/ Executive functions	38	0.391	0.153	-0.011	0.935	0.484

Note. R - simple correlation, R2 - R-square (proportion of variance in the dependent variable, which may be predicted from the independent variables), R2adj - adjusted R2, β- standardized coefficient.

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