Prediction of cognitive outcome after surgery in patients with meningiomas and gliomas: A comparison with healthy controls using normative formulae and reliable change indices

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Tilburg University

Prediction of cognitive outcome after surgery in patients with meningiomas and

gliomas

Rijnen, Sophie

Publication date: 2019

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Publisher's PDF, also known as Version of record

Link to publication in Tilburg University Research Portal

Citation for published version (APA):

Rijnen, S. (2019). Prediction of cognitive outcome after surgery in patients with meningiomas and gliomas: A comparison with healthy controls using normative formulae and reliable change indices . [s.n.].

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Sophie Johanna Maria Rijnen

Prediction of cognitive outcome

after surgery in patients

with meningiomas and gliomas:

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Prediction of cognitive outcome after surgery in patients with meningiomas and gliomas: A comparison with healthy controls using normative formulae and reliable change indices. ISBN: 978-90-9032406-7

This PhD thesis was embedded within Experiment TopZorg, at the Department of Neurosurgery,

Elisabeth-TweeSteden hospital, Tilburg, the Netherlands, and the Department of Cognitive Neuropsychology, Tilburg University, Tilburg, the Netherlands.

The research was funded by a grant of ZonMw (Grant number 842003007). Financial support for this thesis was kindly given by STOPhersentumoren.nl. Cover design by Linda van Zijp || www.studiolin.nl

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PROEFSCHRIFT

ter verkrijging van de graad van doctor aan Tilburg University, op gezag van prof. dr. G.M. Duijsters, als tijdelijk waarnemer van de functie rector magnificus

en uit dien hoofde vervangend voorzitter van het College voor Promoties, in het openbaar te verdedigen ten overstaan van een

door het college van promoties aangewezen commissie in de Aula van de Universiteit op

woensdag 30 oktober 2019 om 16.00 uur

door

Sophie Johanna Maria Rijnen geboren op 15 maart 1991 te Tilburg

Prediction of cognitive outcome

after surgery in patients

with meningiomas and gliomas:

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Chapter 1

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General introduction | CHAPTER 1

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Primary brain tumors (PBT) constitute a heterogeneous set of tumors associated with variable origins, behaviors, malignancies, and symptoms.1,2_{They are characterized by the}

type of cell from which they arise – dominated by meningiomas and gliomas, respectively arising from the arachnoid layer covering the brain and the glial cells in the brain.2 In many cases, initial treatment comprises of maximal safe resection, followed by radio- and/ or chemotherapy if proved necessary based on the classification of tissue obtained during surgery. The decision whether to operate or not is largely based on clinical grounds and focuses on the patients’ general performance status: patients should be in a reasonable condition and the estimated risks of surgery should be acceptable in terms of postoperative neurological deficits. Yet, it has been demonstrated that the majority of meningioma and glioma patients already show cognitive deficits prior to surgical treatment – and although some improvements of cognitive functioning have been reported after surgery, postoperative cognitive deficits continue to exist.3-20_{Moreover, cognitive deficits have not}

only been found to be a valuable indicator of disease severity (and potentially even for tumor progression), but have also been demonstrated to contribute to a lower quality of life and to negatively affect the resumption of social and professional activities after brain tumor surgery.21-26_{Despite this, information on the patient’s cognitive status is currently}

seldom embedded in the clinical care of PBT patients.

This thesis addresses the incidence and severity of cognitive deficits in patients with meningiomas and gliomas before, and on the short- and long-term after surgery, both on the individual patient and the group level. Furthermore, models that address sociodemographic, clinical, neuro-anatomical, and (neuro)psychological risk factors that enable the pre-surgical identification of patients at risk for cognitive deficits after surgery are developed.

This first chapter starts with an elaboration on the characteristics of the types of brain tumors (and accompanying approaches of disease management) of the patients who were included in the studies in this thesis. Subsequently, neuropsychological assessment in neuro-oncological care is described. Lastly, an overview of the chapters is provided.

Figure 1. Illustrative cases of patients with a meningioma (A), low-grade glioma (B), and high-grade glioma (C) on T1 weighted contrast-enhanced magnetic resonance imaging (MRI) scans.

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CHAPTER 1 | General introduction

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Although there are about 130 different types of brain tumors, the focus of this thesis is on patients with meningiomas and patients with gliomas (see Figure 1), which together account for about two third of all patients with a PBT.1

Meningiomas

Meningiomas are the most common type of PBT, accounting for about one third of all brain tumors.1,27_{These tumors most likely originate from arachnoid cap cells – that lie within}

the inner membrane that covers the brain and spinal cord. Therefore, a meningioma is technically not a brain tumor (i.e., they do not grow from brain tissue itself), but is included in this category since it compresses adjacent brain tissue as they grow. Meningiomas are most common in women (with a female:male ratio of 2.27:1), and adults older than 65 years.1

Typically slow growing, meningiomas can reach a considerable size and may go unnoticed for many years due to the plastic potential of the brain (i.e., the potential of the brain to reshape itself during ontogeny, learning, or following injuries). However, perilesional edema or mass effect may eventually lead to symptoms such as seizures, focal neurological deficits (sensorimotor or visual disturbances), or changes in cognitive functioning (e.g., memory loss, problems with concentration and attention).

For those with a documented WHO grade, more than 81% of meningiomas are grade I and have a benign course and the most favorable long term prognosis.1_{Atypical meningiomas}

(WHO grade II) and malignant meningiomas (WHO grade III) comprise the remaining 19%. With more aggressively growing meningiomas invading the brain and likely to recur after treatment, these patients have a poorer prognosis than patients with benign WHO grade I meningiomas, in whom the ten-year relative survival comprises 81.5%.1,28_{The rates of tumor}

recurrence in grade II and grade III meningioma at 5 years are approximately 50% and 90%, respectively, accompanied by a lower ten-year relative survival rate of 53.5%.1,28

Disease management. With the wider use of computed tomography (CT) and magnetic resonance imaging (MRI) scans, the growing interest in health, and the increasing life expectancy, many meningiomas are discovered as incidental findings during investigations for unrelated symptoms.29-32_{If there are no symptoms, monitoring the meningioma}

with serial scans, or a ‘wait-and-scan’ approach, is a common clinical strategy.27,31_When

symptomatic, the age and general condition of the patient, as well as the location and size of the tumor determine which approach is most appropriate for the patient.29_Surgical

resection remains the most common and preferred treatment in many cases – radiotherapy or stereotactic radiosurgery is mostly reserved for meningioma that are surgically considered inoperable, small but growing, recurrent, or subtotal excised.27_{Yet, although surgery is the}

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General introduction | CHAPTER 1 13 Chap te r 1 Gliomas

Gliomas make up about 30% of all brain and central nervous system (CNS) tumors, and about 80% of all malignant brain tumors.1 _{There are different types of gliomas, indicated by}

the type of glial cell in the supportive tissue of the brain they arise from: astrocytomas arise from astrocytes, oligodendrogliomas arise from cells called oligodendrocytes. Gliomas are classified into four grades, that help to determine on an appropriate treatment plan and the patient’s expected prognosis, according criteria of the World Health Organization (WHO).2

The WHO grades reflect how quickly and likely the tumor is expected to grow and invade nearby brain tissue: grade I and II tumors are generally called low grade, whereas grade III and IV tumors are often referred to as high grade. More specifically, grade I tumors comprise cells that have an almost normal appearance: they typically grow slowly and do not invade or infiltrate nearby tissue. As surgery can often cure these patients, grade I tumors are usually associated with long-term survival. Grade II tumors also tend to grow slowly, but its cells have a slightly abnormal appearance. These tumors can invade nearby brain tissue, are likely to recur after treatment, and are also likely to dedifferentiate over time and progress into a higher malignancy grade. Grade III lesions exhibit higher cellularity, more nuclear atypia as well as mitoses. Grade IV lesions comprise the fastest growing aggressive tumors: its cells have a very abnormal appearance, they reproduce rapidly, are likely to spread, and recur even if intensively treated.2_{For most tumors accounts that the lower the grade, the}

better the prognosis of the patient. Yet, important to mention is that all brain tumors (also the lower graded ones) can cause serious symptoms and can be life threatening: enclosed within the skull, the brain cannot expand to make room for a growing mass whereby normal brain tissue is infiltrated and displaced.36

In 2016, the WHO histological classification of PBT was revised to synthesize the growing understanding of the molecular basis of tumors.2_{The distinction between types of gliomas}

(and subsequent therapeutic considerations and expected prognosis) now hinges on tumor histology and on molecular genetic features, generating an ‘integrated diagnosis’. Examples of clinically relevant genotypic parameters are isocitrate dehydrogenase 1 and 2 (IDH1 and IDH2) mutations, 1p/19q co-deletion status, and 06-methylguanine-DNAmethyltransferase (MGMT) promotor mythylation (see Figure 2). IDH-mutated tumors exhibit better prognosis throughout every grade of gliomas. The MGMT promotor gene and 1p/19q codeletion status can predict sensitivity to radio- and chemotherapy in glioma patients.2_{As from this}

updated WHO classification, diffuse gliomas include WHO grade II and III astrocytoma, WHO grade II and III oligodendroglioma, and grade IV glioblastoma.2

Low-grade and anaplastic gliomas. The recent vision of the WHO classification of PBT and new epidemiologic data underscore the link between diffuse low-grade gliomas (WHO grade II; LGGs) and diffuse anaplastic gliomas (WHO grade III; AGs): comprising grade II and grade III astrocytomas and oligodendrogliomas.2_{IDH1 wild-type WHO II gliomas are, for example,}

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nowadays considered and treated as high-grade glioma. Together, LGGs and AGs represent 22.6% of all gliomas diagnosed.37_{LGGs grow relatively slow, yet, they are infiltrative, migrate}

along the white matter tracts, and anaplastic transformation over time is inevitable. In the presence of nuclear atypia and mitotic activity, such tumors are designated as AGs: growing faster and more aggressively than LGGs. The majority of LGG patients present with seizures, sometimes generalized tonic-clonic, but not uncommonly with a history of unrecognized partial seizures for several months or longer.38,39

LGGs most commonly occur in the second through fourth decades of life, whereas the median age at diagnosis for patients with an AG is around 40 years old.40,41_{A wide range of}

outcomes exists among LGG patients: subsets of patients can be identified with a median survival of as little as 2 years, or greater than a dozen years. The median overall survival for patients with an AG is around 3.5 years, but also being especially higher (i.e., up to 13 years) with favorable prognostic factors.41_{Among prognostic factors, age is powerful (younger}

patients do substantially better than older patients), tumor size matters (with larger tumors negatively affecting survival), preserved functional status with limited neurological deficits is favorable, and molecular markers (e.g., IDH1 status) are critical.39,41

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or via progression from primary LGG or AG (secondary GBM). Median age of diagnosis of primary GBMs is 62 years, whereas secondary GBMs are often diagnosed in younger patients with a median age of 44 years.1_{The incidence of GBM is somewhat higher in men}

as compared to in women (female:male ratio of 2:3).42_{The majority of patients with GBM}

present with a short clinical history (weeks to months), as symptoms develop rapidly as a result of the fast growing tumor. Despite aggressive treatments, outcomes after diagnosis with GBM are generally poor: the median survival of patients with GBM is three months if untreated, combined modality therapy with surgery, radio-, and chemotherapy has significantly improved the median survival of patients to 15 months.1,42,43 _{Only a few patients}

reach the long-term survival status of 2.5 years and less than 5% of the patients survive 5 years post diagnosis.1,42,43

Disease management. Approaches with regard to disease management and subsequently the survival of patients with glioma varies widely and depends on the WHO grade, molecular characteristics of the tumor, and surgical possibilities. As prevailing evidence suggests that maximal safe resection for gliomas (1) significantly improves overall as well progression-free survival, (2) assures histological diagnosis and molecular analysis, and (3) improves quality of life by relieving focal deficits and/or improving seizure control due to the amelioration of mass effects, surgery is usually considered the first step of treatment.44-48

The aim of surgery is therefore twofold: to increase overall survival, but also to prevent neurological worsening and deteriorations of quality of life, that is, to optimize the ‘onco-functional’ balance. The use of awake craniotomy (with the patient responding to cortical and subcortical electrical stimulation and continuous testing of functions during surgery) enables surgeons to pursue greater extent of resection of non-functional tissue with glioma invasion, as well as preserving neurological functions by avoiding the resection of brain tissue that is still functional. Awake surgery is mainly performed to remove tumors that have spread throughout eloquent brain tissue without clear borders, such as LGGs.47

Additional treatment options for glioma patients include the wait-and-scan approach, radiotherapy, chemotherapy, or concomitant radio- and chemotherapy, depending amongst others on clinical and molecular prognostic factors, and on the extent of symptoms.49_{Key treatment recommendations for LGG patients include wait-and-scan}

(which remains controversial) or radiotherapy followed by PCV (procarbazine, lomustine, and vincristine) chemotherapy, or temozolomide (TMZ) chemotherapy plus radiotherapy followed by TMZ.49_{Radiotherapy or concomitant radio- TMZ chemotherapy followed by}

TMZ is recommended for patients with AG. For patients with GBM, TMZ plus radiotherapy followed by TMZ has become the standard of care for patients aged 70 years or younger. For patients older than 70 years, radiotherapy alone, or TMZ plus radiotherapy followed by TMZ, or TMZ alone is recommended.49 _{Yet, the various treatment modalities are handled}

differently across centers and countries.50

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Furthermore, several medications are used to relieve symptoms of the tumor. Steroids are used to decrease edema around the tumor and anti-epileptic drugs aim to control seizures, in addition, anti-depressants, anti-anxiety, or sleeping medications may also be considered to improve quality of life during or after glioma treatment.51

Cognitive functioning in patients with a primary brain tumor

Due to increasingly effective disease management, survival times in patients with meningiomas and LGGs have become better over the years. Unfortunately, prognosis remains poor for patients with higher grade glioma. Yet, longer overall survival in some patients as well as very poor prognoses in other patients highlight the importance of maximizing the quality of life of patients during the (limited) ‘disease-free’ period. Although the majority of PBT patients exhibit cognitive impairments at some point in the disease, deficits often remain unrecognized and underestimated in the clinical management of PBT patients.18,20,26,52,53_{This is remarkable given the negative impact of cognitive deficits}

on for example returning to social and professional activities, and quality of life after brain tumor surgery.22,24,26,52-54_{Taken together, this introduces and highlights the importance of}

recognizing and assessing cognitive functioning in the clinical management of PBT patients. A wide range of serious preoperative cognitive deficits have been documented in patients with meningioma (in more than 40% of the patients20,36_{) and glioma (in more than 80%}

of GBM patients18_{), and a number of studies demonstrated that patients also show}

postoperative impairments.17,18,20,36_{Deficits were found in several cognitive domains, most}

commonly involving attention and executive functioning, processing speed, and learning and memory.15,36_{Although surgical resection of the tumor has been found to improve}

cognitive performance in some patients, postoperative deficits seem to continue to exist, as significant cognitive impairments are reported up to four years after surgery.9,16,36

Furthermore, radiation- and/or chemotherapy-induced cognitive impairment (which is difficult to differentiate from each other, since patients treated with chemotherapy are often already treated with radiotherapy, or are treated with both concomitantly- and have also been treated with surgery) has been reported in PBT patients, resulting from multimodal mechanisms, including direct radiation injury to neural structures and indirect insults to blood vessels causing cognitive changes.55,56_{Yet, studies on cognitive functioning in PBT}

patients often include a relatively small number of patients with heterogeneous tumor types, and cognitive assessment often does not comprise routine formal neuropsychological testing.

Furthermore, when changes in cognitive performance over time are assessed, methodological issues related to repeated neuropsychological assessment (NPA) should be taken into account, such as practice effects (performance gain at retest due to familiarity with and recognition of test materials and procedures).57,58_{Interpreting performance}

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might result in underestimations of decline, or overestimations of improvement in cognitive performance. In addition, pre-surgical cognitive functioning is often not examined, limiting statements about changes in cognitive performance over time in patients. Furthermore, prior studies presented cognitive outcomes mostly on the level of the whole patient sample that was examined, however, group results may mask cognitive deficits and/or changes in individual patients (e.g., no significant changes in performance from pre- to post-surgery may be demonstrated when group means are analyzed, yet, improvements and declines in performance of individual patients may be masked). Information on (changes in) cognitive performance of individual patients, as well as sociodemographic, clinical, neuro-anatomical, psychological, or cognitive characteristics of patients who are at risk for cognitive impairment after surgery is important to inform individual patients and clinicians at an early stage, and facilitate timely referral to cognitive rehabilitation.

We aimed to evaluate cognitive functioning in patients with meningiomas and gliomas, and more specifically, to gain insight in individual performances and changes of performance from pre- to post-surgery both on the group and individual patient level. Furthermore, we sought to designate preoperatively known risk factors (i.e., sociodemographic, clinical, neuro-anatomical, psychological, and cognitive) that enable the identification of patients who are at risk for cognitive impairment after surgery.

NPA implemented into neuro-oncological clinical care

There are several ways to assess a patient’s cognitive status: ranging from fast (but unreliable) observations during mental status examinations, to a formal gold standard (but expensive and time consuming) neuropsychological evaluation. Such an examination comprises of a full battery of neuropsychological tests, that is administered by a neuropsychologist taking hours of face-to-face time – yet, the time needed for this examination is lacking in clinical practice.59 _{As from November 2010, the department of Neurosurgery of the}

Elisabeth-TweeSteden hospital (Tilburg, the Netherlands) and the department of Cognitive Neuropsychology of Tilburg University (Tilburg, the Netherlands) therefore developed a protocol for the implementation of computerized, standardized NPAs into the neuro-oncological clinical care of PBT patients undergoing surgery. Routine NPAs have been administered in patients one day before (T0) and three months after (T3) surgery, and cognitive performance of patients with low scores or who showed marked deteriorations over time were addressed in meetings of the multidisciplinary clinical team to facilitate proper referral and/or follow-up care. From upon respectively January 2014 and February 2016, a 12 and 24 months post-operative follow-up assessment was implemented for research purposes in order to explore long-term cognitive functioning as part of the

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ZonMw project ‘Experiment TopZorg’.a_{Setting up, implementing, and running this research}

project took a large amount of time and effort, yet, as the Elisabeth-TweeSteden hospital is one of the largest neurosurgical centers in the Netherlands, we have been able to collect neuropsychological data in a large number of PBT patients before and after surgery since 2010.

PBT patients who were neuropsychologically assessed in the context of the current thesis, were evaluated using the computerized battery Central Nervous System Vital Signs (CNS VS; https://www.cnsvs.com/_{). A major advantage of computerized assessment is the potential of}

having computers perform labor-intensive test administration, reaction time measurement and accurate as well as less time consuming scoring procedures. As a result, they can quickly provide an automated calculation, presentation, and summary of the test results, which is potentially helpful for clinical purposes in neuro-oncological care. CNS VS provides measures of performance on seven cognitive domains (i.e., Verbal Memory, Visual Memory, Processing Speed, Psychomotor Speed, Reaction Time, Complex Attention, and Cognitive Flexibility (see p.18 for supplementary material on CNS VS). Time needed to complete the total battery is approximately 30 to 40 minutes. CNS VS has been shown to be well suited for use as a brief clinical screening tool.12,60,61 _{However, in spite of their widespread use and}

clinical (research) utility, many computerized batteries, including CNS VS, are limited in terms of their psychometric development.62,63 _{Most of its normative data has been collected and}

described more than a decade ago and lacks adjustments for effects of sex and education, as normalized scores are solely age-corrected.64_{Yet, sex and education are also known to}

correlate with performance on various (computerized) neuropsychological tests.65-69 _The

representativeness and applicability of the original CNS VS norms to the Dutch setting is therefore questionable, and potentially even hinders proper interpretation of test results.

CNS VS is suggested to be suitable for serial administration due to the generation of alternate forms through its random presentation of stimuli.64_{Yet, several studies that}

investigated the effects of retesting on CNS VS performance in the American population were largely consistent on the low test-retest correlation for scores on the memory measures, and adequate to high test-retest reliabilities for scores on measures of executive functioning, speed, and reaction time.62,70,71_{Furthermore, participants demonstrated}

significant practice effects between the first and second assessment with CNS VS on the majority of its cognitive domains.71_{Since the included sample sizes in these studies were}

small and characteristics were only described for the English version of CNS VS, these results do not necessarily generalize to non-American samples.72_{Moreover, methods to deal with}

the demonstrated imperfect test-retest reliabilities and practice effects for use of CNS VS in daily (clinical) practice have not been provided to date.

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We aimed to evaluate the performance of healthy Dutch participants assessed with the computerized neuropsychological battery CNS VS: to examine the applicability of the American CNS VS norms for the Dutch population and to establish regression- based normative formulae, to identify the impact of sociodemographic variables on performance, and to examine the psychometric properties of CNS VS when used repeatedly over time to provide individually tailored solutions for methodological issues related to repeated neuropsychological testing.

2. Outline of this thesis

In Part I of the current thesis I present an evaluation of the normative data of the computerized battery CNS VS, and subsequently, an evaluation of its psychometric properties related to repeated testing. Part II comprises studies that describe group as well as individual changes of cognitive functioning from pre- to post-surgery in PBT patients. Subsequently, Part III continues on cognitive performance of PBT patients and contains studies that evaluate pre-surgical predictors of cognitive outcome after surgery. In Part IV a summary and general discussion of the results described in this thesis is presented.

More specifically, in Part I, Chapter 2 we evaluate the applicability of the original American normative data of CNS VS to performance of a large sample of healthy Dutch participants (N = 158), and examine the effects of age, education, and sex on CNS VS performance. Moreover, we provide normative formulae for obtaining sociodemographically adjusted normed scores that facilitate proper interpretation of CNS VS test performances, which we applied in the patient studies described in the current thesis. In Part I, Chapter

3 we evaluate performance of the Dutch normative sample with regard to repeated NPA

over time (i.e., at baseline, and three- and twelve month follow-up) using the CNS VS, by examining test-retest reliabilities and practice effects. Furthermore, we establish formulae for addressing cognitive change over time while taking into account methodological issues: this provides a solution for the interpretation of performance of Dutch patients when CNS VS is used repeatedly over time. Part I, Appendix I describes concerns with regard to the interpretation of cognitive change in glioma patients following a recently published meta-analysis. Although attention for cognitive changes in PBT is growing, a few concerns, in line with the considerations that are described in Chapter 2 and 3, are at issue. In Part II, Chapter 4, we evaluate cognitive performance of patients with LGG, and specifically investigated effects of hemispheric tumor location and type of surgery (i.e., with or without intraoperative stimulation mapping [ISM] of motor and language functions under awake conditions). ISM is currently mostly reserved to patients with left-sided lesions (as the left hemisphere is usually dominant for language), but typically does not involve extensive neuropsychological testing. Therefore, the effects of lesion side and type of surgery on cognitive performance in our cohort of operated LGG patients are relevant to determine on future directions in awake surgery. In Part II, Chapter 5, we evaluate pre- and postoperative cognitive functioning of patients with glioblastoma using the CNS VS battery. We focus on

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Supplementary material on CNS Vital Signs

CNS VS is composed of seven neuropsychological tests - based on the performance on these tests, 11 cognitive domains scores are automatically generated. Yet, given the large similarity across some domains (due to the way they are computed), we consider only seven cognitive domains throughout the studies included in this thesis (see below).

Cognitive domain CNS VS test Description Domain score calculation Verbal Memory Verbal memory test (VEM)

Learning a list of 15 words, with direct recognition, and after 6 more tests a delayed recognition trial

VBM direct correct hits + VBM direct correct passes + VBM delayed correct hits + VBM delayed correct passes Visual

Memory

Visual memory test (VIM)

Learning a list of 15 geometric figures, with direct recognition, and after 6 more tests a delayed recognition trial

VIM direct correct hits + VIM direct correct passes + VIM delayed correct hits + VIM delayed correct passes Processing

Speed

Symbol digit coding test (SDC)

Number 1 to 9 correspond to different symbols. As many numbers as possible have to be filled out under the presented symbols in 90 seconds SDC correct responses – SDC errors Psychomotor Speed Finger-tapping test (FTT); Symbol digit coding test (SDC)

Pressing the space bar with the index finger as many times in 10s

Above mentioned

FTT taps right hand + FTT taps left hand + SDC correct responses

Reaction Time

Stroop test (ST) Part I: pressing the space bar as soon as the words RED/YELLOW/ BLUE/GREEN appear – Part II: pressing the bar as the color of the word matches what the word says – Part III: pressing the bar as the color of the word does not match what the word says

(ST part II reaction time on correct responses + ST part III reaction time on correct responses)/2 Complex Attention Continuous performance test (CPT); Shifting attention test (SAT); Stroop test

Responding to a target stimulus ‘B’ but no any other letter

Shifting from one instruction to another quickly and accurately (matching geometric objects either by shape or color)

Above mentioned

Stroop commission errors + SAT errors + CPT commission errors + CPT omission errors Cognitive Flexibility Shifting attention test (SAT); Stroop test

Above mentioned SAT correct – SAT errors –

ST commission errors

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25 Zamanipoor Najafabadi AH, Peeters MCM, Dirven L, Lobatto DJ, Groen JL, Broekman MLD. Impaired health-related quality of life in meningioma patients – a systematic review. Neuro Oncol. 2017;19(7):897-907.

26 Benz LS, Wrensch MR, Schildkraut JM, Bondy ML, Warren JL, Wiemels JL. Quality of life after surgery for intracranial meningiomas. Cancer. 2018;124(1):161-166.

27 Goldbrunner R, Minniti G, Preusser M, Jenkinson MD, Sallabanda K, Houdart E, et al. EANO guidelines for the diagnosis and treatment of meningiomas. Lancet Oncol. 2016;17(9):e383-391. 28 Buerki RA, Horbinski CM, Kruser T, Horowitz PM, James CD, Lukas RV. An overview of

meningiomas. Future Oncol. 2018;14(21):2161-2177.

29 Whittle IR, Smith C, Navoo P, Collie D. Meningiomas. Lancet. 2004;363:1535-1543.

30 Nakamura M, Roser F, Michel J, Jacobs C, Samii M. The natural history of incidental meningiomas. Neurosurgery. 2003;53:62-70.

31 Lee EJ, Park JH, Park ES, Kim JH. ‘Wait-and-see; strategies for newly diagnosed intracranial meningiomas based on the risk of future observation failure. World Neurosurg. 2017;107:604-611.

32 Vernooij MW, Ikram MA, Tanghe HL, Vincent AJPE, Hofman A, Krestin GP, et al. Incidental findings on brain MRI in the general population. N Eng J Med. 2007;357:1821-1828.

33 Van Alkemade H, de Leau M, Dieleman EM, Kardaun JW, van Os R, Vandertop WP, et al. Impaired survival and long-term neurological problems in benign meningioma. Neuro Oncol. 2012;14(5);658-666.

34 Van der Vossen S, Schepers VP, Berkelbach van der Sprenkel JW, Visser-Meily JM, Post MW. Cognitive and emotional problems in patients after cerebral meningioma surgery. J Rehabil Med. 2014;46(5):430-470.

35 Meskal I, Gehring K, Rutten GJM, Sitskoorn MM. Cognitive functioning in meningioma patients: a systematic review. J Neurooncol. 2016;128:195-205

36 https://www.abta.org/, accessed April 30, 2019.

37 Bauchet L, Ostrom QT. Epidemiology and molecular epidemiology. Neurosurg Clin N Am. 2019;30(1):1-16.

38 Schiff D. Low-grade gliomas. Continuum (Minneap Minn). 2017;23(6):1564-1579.

39 Le Rhun E, Taillibert S, Chamerlain MC. Anaplastic glioma: current treatment and management. Expert Rev Neurother. 2015;15(6):601-620.

40 Diwanji TP, Engelman A, Snider JW, Mohindra P. Epidemiology, diagnosis, and optimal management of glioma in adolescents and young adults. Adolsc Health Med Ther. 2017;8:99-113.

41 Balañá C, Alonso M, Hernandez A, Perez-Segura P, Pineda E, Ramos A, et al. SEOM clinical guidelines for anaplastic gliomas (2017). Clin Transl Oncol. 2018;20:16-21.

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42 Thakkar JP, Dolecek TA, Horbinski C, Ostrom QT, Lightner DD, Barnholtz-Sloan JS, et al. Epidemiologic and molecular prognostic review of Glioblastoma. Cancer Epidemiol Biomarkers Prev. 2014;23(10):1985-1996.

43 Hanif F, Muzaffar K, Perveen K, Mahli S, Simsjee SU. Glioblastoma multiforme: a review of its epidemiology and pathogenesis through clinical presentation and treatment. Asian Pac J Cancer Prev. 2017;18(1):3-9.

44 Aghi MK, Nahed BV, Sloan AE, Ryken TC, Kalkanis SN, Olson JJ. The role of surgery in the management of patients with diffuse low grade glioma: a systematic review and evidence-based clinical practical guide. J Neurooncol. 2015;125(3):503-530.

45 Hollon T, Hervey-Jumper SL, Sagher O, Orringer DA. Advances in the surgical treatment of low-grade glioma. Semin Radiat Oncol. 2015;25(3):181-188.

46 Sepúlveda-Sánchez JM, Langa JM, Arráez MA, Fuster J, Laín AH, Rynés G. SEOM clinical guideline of diagnosis and management of low-grade glioma (2017). Clin Transl Oncol. 2018;20:3-15. 47 Duffau H. Is non-awake surgery for supratentorial adult low-grade glioma treatment still

feasible? Neurosurg Rev. 2018;41:133-139.

48 Hervey-Jumper SL, Berger MS. Evidence for improving outcome through extent of resection. Neurosurg Clin N Am. 2019;30(1):85-93.

49 Weller M, van den Bent M, Tonn JC, Stupp R, Preusser M, Cohen-Jonathan-Moyal E, et al. European association for Neuro-Oncology (EANO) guideline on the diagnosis and treatment of adult astrocytic and oligodendroglial gliomas. The Lancet Oncol. 2017;18(6):e315-e329. 50 Mandonnet E, Wager M, Almairac F, Baron MH, Blonski M, Freyschlag CF, et al. Survey on current

practice within the European Low-Grade Glioma Network: where do we stand and what is the next step? Neuro-Oncol P. 2017;4(4):241-247.

51 Liu R, Page M Solheim K, Fox S, Chang SM. Quality of life in adults with brain tumors: current knowledge and future directions. Neurooncol. 2009;11(3):330-339.

52 Zamipoor Najafabadi AH, Peeters MCM, Dirven L, et al. Impaired health-related quality of life in meningioma patients - a systematic review. Neuro Oncol. 2017;19(7):897-907.

53 Drewes C, Sagberg LM, Jakola AS, Solheim O. Perioperative and postoperative quality of life in patientswith glioma - a longitudinal cohort study. World Neurosurg. 2018;117:e465-e474. 54 Noll KR, Bradshaw ME, Weinberg JS, Wefel JS. Neurocognitive functioning is associated with

functional independence in newly diagnosed patients with temporal lobe glioma. Neuro Oncol Pract. 2017;5(3):184-193.

55 Schagen SB, Wefel JS. Chemotherapy-related changes in cognitive functioning. EJC Suppl. 2013;11(2):225-232.

56 Ali FS, Hussain MR, Gutiérrez C, Demireva P, Ballester LY, Zhu JJ, et al. Cognitive disability in adult patients with brain tumors. Cancer Treat Rev. 2018;65:33-40.

57 Calamia M, Markon K, Tranel D. Scoring higher the second time around: meta-analyses of practice effects in neuropsychological assessment. Clin Neuropsychol. 2012;26:543-570. 58 Wahlstrom M, Boersma FJ. The influence of test-wiseness upon achievement. Educ Psychol

Meas. 1968;28:413-420.

59 Casaletto KB, Heaton RK. Neuropsychological assessment: Past and future. J Int Neuropscyhol Soc. 2017;23(9-10):778-790.

60 Collins B, Mackenzie J, Tasca GA, Scherling C, Smith A. Persistent cognitive changes in breast cancer patients 1 year following completion of chemotherapy. J IntNeuropsychol Soc. 2014;20:370-390.

61 Gualtieri CT, Johnson LG, Benedict KB. Neurocognition in depression: patients on and of medication versus healthy comparison subjects. J Neuropsychiatry Clin Neurosci. 2006; 18:217-225.

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Neuropsychology and the National Academy of Neuropsychology. Clin Neuropsychol. 2012;26:177-196.

63 Arrieux JP, Cole WR, Ahrens AP. A review of the validity of computerized neuropsychological assessment tools in mild traumatic brain injury assessments. Concussion. 2017;2(1):CNC31. 64 Gualtieri CT, Johnson LG. Reliability and validity of a computerized neurocognitive test battery,

CNS Vital Signs. Arch of Clin Neuropsychol. 2006;21:623-643.

65 Heaton RK, Grant I, Matthews CG. Differences in neuropsychological test performance associated with age, education, and sex. In Grant I, Adams KM (Eds). Neuropsychological assessment in neuropsychiatric disorders: clinical methods and empirical findings. (pp. 100-120). Oxford, England: Oxford University Press.

66 Seidenberg M, Gamache MP, Beck NC, Goirdane B, Berent S, Sackellares JC, et al. Subject variables and performance on the Halstead Neuropsychological Test Battery: a multivariate analysis. J Consult Clin Psychol. 1984;52:658-662.

67 Gualtieri CT, Hervey AS. The structure and meaning of a computerized neurocognitive battery. Front Psycholog Behav Sci. 2015;4(2):11-21.

68 Iverson GL, Brooks BL, Rennison VLA. Minimal gender differences on the CNS Vital Signs computerized neurocognitive battery. Appl Neuropsychol: adult. 2014;21:36-42.

69 Swagerman SC, de Geus EJC, Kan KJ, van Bergen E, Nieuwboer HA, Koenis MMG, et al. The computerized neurocognitive battery: validation, aging effects, and heritability across cognitive domains. Neuropsychol. 2016;30:53-64.

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PART I

Dutch normative data and

psychometric properties of the

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Chapter 2 Dutch normative data of a

computerized neuropsychological

battery: CNS Vital Signs

Assessment. 2017: 1-11.

Sophie JM Rijnen

1,2

Ikram Meskal

2

Wilco HM Emons

3

Carlijn CM Campman

2

Sophie D van der Linden

1,2

Karin Gehring

1,2

Margriet M Sitskoorn

2

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Dutch normative data of CNS VS | CHAPTER 2

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Evaluation of normative data of a widely used computerized neuropsychological battery: Applicability and effects of sociodemographic variables in a Dutch sample

ABSTRACT

Background: Central Nervous System Vital Signs (CNS VS) is a computerized

neuro-psychological battery that is translated into many languages. However, published CNS VS’ normative data were established over a decade ago, are solely age-corrected, and collected in an American population only.

Method: Mean performance of healthy Dutch participants on CNS VS was compared with

the original CNS VS norms (N = 1069), and effects of sociodemographic variables were examined.

Results: Z tests demonstrated no significant differences in performance on four out of

seven cognitive domains; however, Dutch participants (N = 158) showed higher scores on Processing and Psychomotor Speed, as well as on Cognitive Flexibility. Although the original CNS VS norms are solely age-corrected, effects of education and sex on CNS VS performance were also identified in the Dutch sample.

Discussion: Users should be cautious when interpreting CNS VS performance based on the

original American norms, and sociodemographic factors must also be considered.

Keywords: CNS Vital Signs, computerized neuropsychological testing, healthy participants,

normative data, sociodemographic variables, neuropsychological assessment

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CHAPTER 2 | Dutch normative data of CNS VS

32

INTRODUCTION

Computerized neuropsychological test (CNT) batteries have become increasingly popular in clinical and research settings over the past years. A major advantage of CNT’s is the potential of having computers perform labor-intensive test administration, and accurate as well as less time consuming scoring procedures. The Central Nervous System Vital Signs (CNS VS;1₎

is a battery composed of CNTs that are mostly based on well-established conventional paper-and-pencil tests. CNS VS has been shown to be well suited for use as a brief clinical screening tool for cognitive dysfunction in different patient groups.2-4

However, in spite of their widespread use and clinical utility, many CNT’s, including CNS VS, are limited in terms of their psychometric development, and stratified norms are often lacking.5,6_{Most of the normative data have been collected and described by Gualtieri}

and Johnson more than a decade ago based on a sample of 1069 volunteering American participants ranging in age from 7 to 90 years.1_{Since 2006, the normative database has}

been expanded to over 1900 participants (http://www.cnsvs.com), but unfortunately no information on the updated CNS VS normative database has been reported to date. As a result, there is no publically available description of the composition of the American sample regarding background characteristics, nor the basis on which participants were classified as “normal,” except that they had “no past or present neurological or psychiatric disorder, head injury, and learning disabilities” (1_{, p. 625). Hence, the representativeness of}

the norms for the American population cannot be evaluated and is uncertain. Moreover, although the CNS VS has been translated into over 50 languages, only normative data for the American version has been published. However, the performance on translated versions of the CNS VS could be affected by cultural influences rendering the norms for the American sample inapplicable to individuals in other countries. To the best of our knowledge, the applicability of the original norms to non-American samples has never been studied. In addition, the original CNS VS norms may be outdated, since norms were based on data that were collected over a decade ago. Ageing of norms is an important treat to the usefulness of normative data.(e.g., 7)

Another limitation of the original CNS VS’ normative data concerns the absence of adjustments for effects of education and sex, as normalized scores are solely age-corrected. All three sociodemographic variables (i.e., age, education, and to a lesser extent sex) have extensively been found to correlate with performance on various neuropsychological tests, including performance on computerized tests.8-12_{The absence of corrections for these}

variables when interpreting performance on neuropsychological tests hinders proper interpretation and comparison in terms of cognitive functioning.

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performance using a regression-based procedure. By using this approach, individual normed can be derived. Formulae for obtaining sociodemographically adjusted normed scores based on normative data from the Dutch population are presented as well.

MATERIALS AND METHODS

Participants and procedure

A total of 158 Dutch participants, recruited by convenience sampling from the broad network of the research group, volunteered to participate in the study. Participants were considered healthy if (a) there was no past or present psychiatric or neurologic disorder; (b) they had no other major medical illnesses in the past year prior to participation (e.g., cancer, myocard infarct); (c) they were free of use of any centrally acting psychotropic medication; and (d) did not have a history of or current alcohol or drug abuse. The computerized neuropsychological tests were, depending on participants’ preference, administered individually at Tilburg University (Tilburg, the Netherlands), Elisabeth-TweeSteden Hospital (Tilburg, The Netherlands), or at participants’ homes. Well-trained test technicians ensured appropriate conditions and remained present during the entire assessment. Participants provided written informed consent and filled out a questionnaire on health status.

The study was approved by the Medical Ethics Committee Brabant, the Netherlands (File number: NL41351.008.12).

Measures and normative data

Sociodemographic Characteristics. Number of years and completed level of education were self-reported by participants. Grade retention did not count as an extra year, neither did supplementary vocational courses that were attended after graduation. Actual number of years of education was verified (i.e., recalculated by the test technician together with the participant) during the assessment. To classify the level of education, the Dutch Verhage scale was used.13_{Its seven categories were merged into three ordinal categories: low educational}

level (Verhage 1 until 4), middle educational level (Verhage 5), and high educational level (Verhage 6 and 7; Table 1). Participants also rated their frequency of computer use on a 3-point scale with categories never, some, or frequent.

Central Nervous System Vital Signs. Cognitive functioning was assessed using the Dutch translation of the CNT battery CNS VS. It comprises seven neuropsychological tests, yielding measures of performance in 11 cognitive domains. Since some domains scores generated by CNS VS are very similar (i.e., mainly calculated based on components of the same tests), we chose to consider only 7 cognitive domains (see Supplementary material on CNS VS, Chapter 1, p.21). Time needed to complete the total battery is approximately 30 to 40

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minutes. Scoring is automated and scores are presented in raw and normed scores, as well as percentile ranks, generating a summary report for clinical interpretation or statistical analysis. Raw scores include the number of correct or incorrect responses, reflecting accuracy, and mean reaction times (in milliseconds) on individual tests and domains, reflecting speed. Normed scores are automatically generated by the CNS VS and represent the performance of an individual relative to the American normative sample controlled for age. In the population, CNS VS normed scores are assumed to have a mean of 100 and a standard deviation of 15; higher scores always indicate better performance.1_{The percentile}

rank of these scores refer to the proportion of scores in the normative sample that are equal to or lower than the score at hand. All testing was done using CNS VSX’ local software app, on the same type of laptop computers running Windows 7 Professional on 64-bit operating systems. Background programs were shut down at time of all assessments and laptops were disconnected from (wireless) internet resources.

There is not a large body of literature regarding the reliability and validity of CNS VS. In the original reliability and validity paper, Gualtieri and Johnson describe CNS VS’ psychometric characteristics to be very similar to the characteristics of the conventional neuropsychological tests on which the battery is based.1_{However, correlational studies}

suggest at best moderate correlations between CNS VS and traditional neuropsychological tests, and in addition, no consistent clear patterns of convergent or discriminant validity have been.1,10, 14-16_{As no two presentations of CNS VS are similar due to the random presentation}

of stimuli, the battery is assumed to be suitable for serial administration without inducing practice effects.

CNS VS American Normative Database. As stated before, CNS VS’ normative database has been expanded to over 1900 participants nowadays (http://www.cnsvs.com). However, we rely on information regarding the CNS VS’ normative sample described by Gualtieri and Johnson since detailed information (e.g., sociodemographic characteristics) about the enlarged normative sample is not available.1 _{One thousand sixty-nine normal participants}

were included in the normative database of CNS VS. Background characteristics (i.e., sex, ethnicity, handedness, and computer familiarity) and normative data are represented for 10

Table 1. Description of educational levels (Adapted from Verhage, 196413₎

Level Verhage categories

Low 1. Less than 6 years of primary education

2. Finished primary education

3. Primary education and less than 2 years of low-level secondary education 4. Finished low-level secondary education

Middle 5. Finished average-level secondary education

High 6. Finished high-level secondary education

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age groups: less than 10 years old, 10 to 14 years, 15 to 19 years, in deciles to 79 years, and finally, 80 years and older, with group sizes ranging from 25 to 212 participants.1_{In most age}

groups, there is a female predominance, ranging from 43% to 72%.

Characteristics are not presented for the sample as a whole — hindering proper comparisons between the total Dutch and American samples with respect to age and sex. Information about education (e.g., level, number of years) of the American sample is not described by Gualtieri and Johnson, or in the documentation of the CNS VS itself (http:// www.cnsvs.com).1_{Neither was such information available from any of CNS VS’ analyses}

regarding the establishment of the battery’s normative data.

Statistical analysis

Mean Domain and Test Performances. To explore whether mean CNS VS performance of the Dutch participants differed from the mean performance of the normative American sample, a series of two-tailed one-sample z tests was performed (test values: M = 100, SD = 15). CNS VS presents up to 10 different mean raw scores (i.e., for each of the 10 different age-groups of CNS VS’ normative sample) for each domain and test. Since adopting the same subgroups in the Dutch sample would dramatically decrease the sample size for these analyses, the automatically generated age corrected normed scores were used in all comparisons between the American and Dutch samples. In this way, we also account for effects of age in both groups. Effect sizes (ES) for potential differences between the American and the Dutch samples were calculated and expressed as Cohen’s d using pooled variance.1 ES between ≤0.20 and 0.49 were defined as small, between 0.50 and 0.79 as medium, and ≥0.80 represented large effects.17

Multiple Regression Analyses. To explore the effects of sociodemographic factors on CNS VS performance, a series of multiple linear regression analyses was conducted using raw CNS VS domain scores as the outcome variables and a predetermined list of sociodemographic predictors. Age (in years), education (dummy coded; middle education as reference category), and sex (coded as 0 = men, 1 = women) were predictor variables which were entered as a single block (“enter” method). Assumptions were evaluated as follows: independence of observations was evaluated by Durbin–Watson tests, and linearity and homoscedasticity were examined using scatter plots of residuals.18_{Potential multicollinearity between}

predictors was examined by inspecting Pearson’s correlation coefficients. By computing Cook’s distances, univariate influential cases were identified.19_{Normality of residuals was}

investigated by visual inspection of histograms. Alpha was set at .02 in order to prevent the problem of inflated Type I errors related to multiple comparisons. All statistical analyses were performed with SPSS 22.0.

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Normative Regression Formulae. The results of the regression models which regresses performance on age, sex, and educational level also provide the formulae for computing sociodemographically adjusted norms. Clinicians and researchers can use these formulae in future administrations of CNS VS to obtain normed scores for individuals on each cognitive domain, based on their age, educational level, and sex. In particular, all predictors were included in the normative formulae irrespective of the significance of the effects, as follows:

Ypdomain = α+ b1Age + b2Dlow education + b2Dhigh education + b3Sex

In this formula, Yp domain is the predicted raw domain score, α is the intercept, and b1 trough

b3 are the regression coefficients. Notice that educational level is a categorical variable with

three categories and therefore modelled by means of two dummy variables, one for low education and one for high education (i.e., middle education as reference category). Sex is also a dummy variable, with men as the reference category (i.e., for men: sex = 0 and for women: sex = 1). Application of these regression formulae is demonstrated in Box 1.

RESULTS

Sociodemographic characteristics

Table 2 shows participants’ sociodemographic characteristics. Mean age was 45.9 (SD = 14.4) years, ranging from 20.0 to 80.0. There was a female predominance (57%) in the Dutch sample, which appears comparable to the American normative database of CNS VS. The participants completed 16.9 years of education on average. Almost all participants (97%) indicated to use the computer frequently. Men and women did not differ in terms of mean age, t(156) = 0.48, p = .162, and educational level, χ2_{(2) = 1.20, p = .550, neither did men and}

women differ in frequency of computer use, χ2_{(2) = 1.42, p = .491. Likewise, no significant}

differences between groups based on the three educational levels were found concerning age, F(2, 155) = 1.04, p = .355, and frequency of computer use, χ2_{(4) = 8.79, p = .067.}

Mean domain and test performance

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At the level of normed individual test scores (e.g., representing reaction time, number of correct answers), the Dutch sample demonstrated significantly higher scores on 5 out of 17 measures compared with the American normative sample (see Table 3). The number of correct rejections in the delayed recognition Visual Memory Task was significantly higher in the Dutch sample, and Dutch participants performed significantly more taps on the Finger Tapping Test with both the right and the left hand. In addition, the numbers of correct responses on the Symbol Digit Coding task and Shifting Attention Task were higher in the Dutch compared with the original American normative group. A near-medium sized difference was found for the right hand Finger Tapping Test (Cohen’s d = 0.46), for the other tests, ES were small (Cohen’s d ranging from 0.20 to 0.36).

Multiple regression analyses

None of the assumptions regarding the regression analyses were violated. There was independence of residuals, with Durbin–Watson statistics ranging from 1.72 to 2.22. Scatter plots demonstrated linear relationships between the dependent and independent variables, and homoscedasticity. No problems with collinearity were identified, with correlations r between −0.01 and 0.38. No influential cases were identified (all Cook’s distances >1), and histograms demonstrated normally distributed standardized residuals for each cognitive domain. Table 4 shows the results of the regression analyses. Overall, significant effects of age were found on performance in four out of seven raw cognitive domain scores (i.e., for Processing Speed, Psychomotor Speed, Reaction Time, and Cognitive Flexibility). Higher age was consistently associated with lower scores. Educational level was significantly associated with performance on three out of seven domains: participants with a high educational level (i.e., compared with a middle and low educational level) obtained higher scores on Visual

Table 2. Sociodemographic characteristics of the Dutch sample (N = 158) and the American sample (N = 1069)

Dutch sample American samplea

Age; years, M±SD, range 45.94 ± 14.43, 20-80 Unknowna_{, 7-90}

Sex; women n (%) / men n (%) 90 (57.0) / 68 (43.0) 654 (61.2) / 415 (38.8)

Education Years, M±SD 16.88 ± 3.29 Unknowna

Level Low n (%) 19 (12.0) Unknowna Middle n (%) 57 (36.1) Unknowna High n (%) 82 (51.9) Unknowna Computer use Never n (%) 1 (0.6) 288 (26.9) Some n (%) 4 (2.5) 52 (4.9) Frequent n (%) 153 (96.8) 729 (68.2)

a_{Characteristics of the American sample were not presented for the sample as a whole (see Gualtieri and}

Johnson1_{for demographic characteristics across different age groups).}

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Memory, Processing Speed, and Cognitive Flexibility. Sex was found to be significantly associated with performance on the Verbal Memory domain, in favor of women, and the Psychomotor Speed domain, in favor of men. The proportions of explained variances (R2_{) by}

age, education, and sex ranged from 7.2% (for the Verbal Memory domain) up to 46.2% (for

Table 3. Mean CNS VS normed scores of Dutch participants (N = 158) compared with the American normative data (M = 100, SD = 15) M (SD)a _{Mean Δ} _{z test} _p _{ES d}b Domain Verbal Memory 98.66 (14.99) -1.34 -1.11 .268 -0.09 Visual Memory 101.81 (12.98) 1.81 1.50 .133 0.12 Processing Speed 104.52 (14.48) 4.52 3.77 <.001* 0.30 Psychomotor Speed 107.17 (12.87) 7.17 5.97 <.001* 0.49 Reaction Time 101.41 (11.13) 1.41 1.17 .242 0.09 Complex Attention 101.88 (11.66) 1.88 1.54 .124 0.13 Cognitive Flexibility 102.91 (12.94) 2.91 2.39 .017* 0.19 Test

Verbal memory test

Direct recognition correct hits 99.01 (14.66) -0.99 -0.79 .425 -0.07

Direct recognition direct rejections 100.94 (12.58) 0.94 0.76 .447 0.06

Delayed recognition correct hits 98.16 (14.86) -1.84 -1.48 .138 0.12

Delayed recognition correct passes 98.98 (14.07) -1.02 -0.89 .370 0.08

Visual memory test

Direct recognition correct hits 99.50 (13.97) -0.50 -0.40 .685 0.03

Direct recognition correct passes 102.53 (13.35) 2.53 2.05 .040 0.17

Delayed recognition correct hits 98.46 (12.06) -1.54 -1.25 .211 -0.10

Delayed recognition correct passes 103.86 (11.43) 3.86 3.13 .002* 0.26

Finger-tapping test

Number of taps right 106.79 (12.66) 6.79 5.52 <.001* 0.46

Number of taps left 104.81 (12.99) 4.81 3.92 <.001* 0.33

Symbol digit coding test

Number correct 105.37 (14.27) 5.37 4.39 <.001* 0.36

Stroop test

Reaction time Part I 101.11 (10.01) 1.11 0.91 .364 0.08

Reaction time Part II 100.48 (12.78) 0.48 0.39 .698 0.03

Reaction time part III 102.34 (10.48) 2.34 1.90 .057 0.16

Shifting attention test

Number correct 102.97 (14.16) 2.97 2.42 .016* 0.20

Reaction Time 100.51 (15.13) 0.51 0.42 .678 0.03

Continuous performance test

Number correct 101.67 (9.48) 1.67 1.37 .172 0.12

Note. CNS VS = Central Nervous System Vital Signs. a_{CNS VS normed scores based on the American normative}

sample have a mean of 100 and a standard deviation of 15; higher scores indicate better performance; positive

mean difference indicates better performance for the Dutch sample and vice versa. b_{Cohen’s d effect sizes:}

Prediction of cognitive outcome after surgery in patients with meningiomas and gliomas: A comparison with healthy controls using normative formulae and reliable change indices

Tilburg University

Prediction of cognitive outcome after surgery in patients with meningiomas and

gliomas

Rijnen, Sophie

Prediction of cognitive outcome

after surgery in patients

with meningiomas and gliomas:

Prediction of cognitive outcome

after surgery in patients

with meningiomas and gliomas:

Table of contents

Chapter 1

Supplementary material on CNS Vital Signs

REFERENCES

PART I

Dutch normative data and

psychometric properties of the

Chapter 2

Dutch normative data of a

computerized neuropsychological

battery: CNS Vital Signs

Assessment. 2017: 1-11.

Sophie JM Rijnen

Ikram Meskal

Wilco HM Emons

Carlijn CM Campman

Sophie D van der Linden

Karin Gehring

Margriet M Sitskoorn

ABSTRACT

INTRODUCTION

MATERIALS AND METHODS

RESULTS