Awake language mapping for cerebral glioma surgery

Abstract

This is a protocol for a Cochrane Review (Intervention). The objectives are as follows:

The aim of this study is to assess the reliability and effectiveness of intraoperative language mapping for glioma surgery by comparing glioma surgeries with and without language mapping.

Alternative language mapping techniques such as fMRI and PET scan will also be compared to intraoperative language mapping.

Background

Description of the condition

Gliomas are a heterogeneous group of neoplasms that account for 31% of all brain tumours and 80% of malignant central nervous system (CNS) tumours. The most common site of gliomas is the cerebrum. Based on the 2007 World Health Organization (WHO) classification of brain tumours (Louis 2007), the gliomas are classified by their cell types. The main types of gliomas include astrocytomas, oligodendrogliomas, ependymomas and mixed gliomas. Gliomas can be graded from I to IV, with grade I and II gliomas classified as low‐grade gliomas (LGGs) and grade III and IV gliomas as high‐grade gliomas (HGGs).

According to the data from the Surveillance, Epidemiology and End Results (SEER) program (Howlader 2003), the age‐adjusted incidence of all primary CNS tumours is 6.5 cases per 100,000 people per year in US. The incidence of brain tumours is higher in males than in females (7.7 versus 5.4 per 100,000 people per year). The onset of brain tumours peaks between 65 and 79 years of age.

The symptoms in people with gliomas are mainly headache and other neurological distortions, including cognitive changes, motor and language deficit. The symptoms progress with the advancement of the tumour. Patients with LGGs typically survive more than 5 years and those with HGGs survive 1 to 3 years. It is now widely accepted that the prognostic factors of gliomas include histopathological classification, malignant grade, the preoperative performance status (Karnofsky performance score (KPS) (Brem 2011) and the patient's age (Frenel 2009; Pignatti 2002). Despite controversies on the role or extent of tumour resection (Hart 2000; McGirt 2008; Tsitlakidis 2010; Whittle 1998), increasingly studies (McGirt 2008; Tsitlakidis 2010) have indicated its positive effect on overall survival (OS).

The treatment strategies of gliomas are highly individualized based on the WHO grading system (Louis 2007). For LGGs, maximal resection should be performed when appropriate and radiotherapy, chemotherapy or both delayed until the time of progression. For HGGs, the standard treatment is maximal safe resection followed by adjuvant combination of fractionated external beam radiation and chemotherapy.

However, resection of gliomas in or adjacent to language areas of the dominant hemisphere, such as Broca's area and Wernicke's area, may cause postoperative language dysfunctions presented as inability to comprehend or express language in its written or spoken form. Moreover, studies showed that language localization can be altered by reorganization of the brain and varies among people (Duffau 2003; Sanai 2008; Thulborn 1999).

Description of the intervention

The technique of direct electrical stimulation was first used to locate the sensory‐motor cortex during surgical removal of epileptic foci. In early 1940s, Wilder Penfield applied this technique in the identification of language areas (Penfield 1954).

Intraoperative language mapping, also known as language electrical stimulation under local anaesthesia, is a surgical procedure using electrical stimulation to identify the areas of the cortex that are essential for language functions during language tasks such as number counting, picture naming and word reading. A neuropsychologist is often needed to conduct preoperative and intraoperative language tests.

How the intervention might work

Due to the infiltrative nature of gliomas and the variability in localization of functional language areas, it is difficult for surgeons to perform radical resection without damaging the functional brain tissue. Language dysfunction is a possible consequence of gliomas located near or in eloquent areas of the dominant hemisphere. Intraoperative language mapping can help to identify essential language areas and preserve them during the course of tumour resection. It can minimize the postoperative language deficits and be compared with other functional mapping methods such as functional magnetic resonance imaging (fMRI) and position emission tomography (PET) scan.

Why it is important to do this review

The application of the intraoperative language mapping technique has been reported by many surgeons, yet most of the studies are retrospective case reports. There is a lack of strong and high‐level evidence to support the benefits of this procedure in the neurological outcomes after this surgery.

Moreover, alternative functional mapping methods such as PET scan and fMRI have been applied in the clinical setting for many years, yet their validity and effectiveness has also not been evaluated.

Therefore, a systematic review may provide a high level of clinical evidence for this surgical technique and even bring a new insight into the mechanism of the compensation of language functions in patients with cerebral glioma in eloquent areas.

Objectives

The aim of this study is to assess the reliability and effectiveness of intraoperative language mapping for glioma surgery by comparing glioma surgeries with and without language mapping.

Alternative language mapping techniques such as fMRI and PET scan will also be compared to intraoperative language mapping.

Methods

Criteria for considering studies for this review

Types of studies

Randomized controlled trials (RCTs) and controlled clinical trials (CCTs) will be included.

Blinding is not feasible due to the obvious differences between surgical procedures with and without intraoperative language mapping.

Types of participants

People with suspected glioma from clinical examination and imaging (computerized tomography (CT), magnetic resonance imaging (MRI) or both) will be included. Participants will be over 18 years of age, have a preoperative Karnofsky performance score (KPS) score (Brem 2011) greater than 70 and subsequent histology confirming cerebral glioma. Patients with Grade I histology will be excluded, as will those with multifocal lesions or gliomatosis cerebri.

The histological types to be included can be found in Appendix 1

Types of interventions

Interventions will be surgical resection of cerebral glioma utilizing intraoperative language mapping versus surgical resection without additional intraoperative localization assistance. Studies using intraoperative commodities such as intraoperative MRI to achieve total resection can be included. Different postoperative treatment regimens of chemotherapy and radiotherapy will be included since they do not affect the primary outcome.

Studies comparing intraoperative language mapping with other functional mappings such as language functional MRI and intraoperative optical imaging will be excluded.

Types of outcome measures

Primary outcomes

Language functional assessments using aphasia batteries to assess language functions after surgery (e.g. at time intervals of 1 week, 1 month, 3 months, 6 months). Include the Boston Diagnostic Aphasia Examination (BDAE) and Western Aphasia Battery (WAB) and their translated versions or modified versions (e.g. Aphasia Batteries of Chinese (ABC)). We will carry out an analysis of heterogeneity for the different scales used. If two or more scales were used in one study, we will give priority to the one that indicated higher language dysfunctional rate.

Secondary outcomes

• Overall survival (OS): defined as survival from time of randomisation to death from any cause.

• Progression Free Survival (PFS): defined as time from randomisation to either death from any cause or disease progression. The updated McaDonald criteria (Wen 2010) will be used to assess tumour progression.

• Quality of life (QoL): measured using EORTC QLQ‐C30 (Aaronson 1993).

• Performance scales: measured using a validated scale, e.g., KPS (Brem 2011), ECOG (Oken 1982).

• Adverse events (AEs): according to the MedDRA® (Medical Dictionary for Regulatory Activities), we will collect the most relevant ADEs, e.g., nausea, vomiting, seizure, fatigue, infection, haemorrhage etc.

Search methods for identification of studies

No language restriction will be applied.

Electronic searches

The following electronic databases will be searched: the Cochrane Central Register of Controlled Trials (CENTRAL, current issue), MEDLINE (1970 to date), EMBASE (1970 to date), and Chinese Biomedical Literature Database (CBM, 1970 to date).

Searching other resources

We will search sources of grey literature.

• National Technical Information Service (NTIS, www.ntis.gov).

• Conference abstracts and proceedings will be searched through the American Society of Clinical Oncology (ASCO) (www.asco.org/ASCO/Meetings).

• Dissertations and theses will be searched through the ProQuest Dissertation & Theses Database (www.proquest.co.uk/en‐UK/catalogs/databases/detail/pqdt.shtml).

• Ongoing trials will be searched through the Current Controlled Trials metaRegister of Controlled Trials (mRCT) (www.controlled‐trials.com/mrct), the ClinicalTrials.gov website (clinicaltrials.gov) and the Chinese Clinical Trial Registry (www.chictr.org/Default.aspx)

• Handsearching of journals: Journal of Neuro‐Oncology, Journal of Neurosurgery and Neurosurgery from 1991 to 2011 to identify trials that may not be included in the electronic databases.

• Reference lists of existing systematic reviews and identified studies.

• Correspondence: the authors of identified trials and professionals in this field will be contacted via email to obtain further information of unpublished and ongoing trials.

Data collection and analysis

Selection of studies

Two review authors (Wu J‐S and Zhang J) will independently examine the titles and abstracts of studies retrieved from electronic searches. They will exclude duplicate and obviously irrelevant reports. Two review authors (Wu J‐S and Zhang J) will obtain the full texts of the identified eligible studies and further independent assessment using the established criteria of inclusion will be made. Disagreements will be resolved through discussion. If a study lacks information to be included, the study author will be contacted for further details.

Data extraction and management

Two reviews authors (Wu J‐S and Zhang J) will independently extract data from potential eligible reports using a data collection form that includes study type, participants, interventions and outcomes.

The review authors (Wu J‐S and Zhang J) will receive appropriate training and a pilot test will be conducted. Disagreements will be resolved by discussion and the consensus data will be recorded in a different ink colour on one of the authors' data collection form. Data from multiple reports of the same study will be extracted separately and combined.

The data collection form will include the following categories as recommended in the Cochrane Handbook for Systematic Reviews of Interventions (Higgins 2011):

• basic information: study ID, report ID, review author ID, citation of the report

• eligibility: reasons for exclusion

• study characteristics: study design, duration, sequence generation, allocation

• participants: total number, age, sex, country, setting, diagnostic criteria, tumour location and pathology, neurological deficits

• interventions: details of intraoperative language mapping and comparisons, co‐interventions

• outcomes: include language assessment score, QoL, overall survival and PFS

For continuous outcomes, the number of participants, the mean value and the standard deviation of outcome measurements in each intervention group will be extracted. For dichotomous outcomes, the total numbers and the number of participants who experienced the outcome in each group will be extracted. For time‐to‐event outcomes, the log hazard ratios (lgHRs) and their standard errors will be extracted. If they are not reported, they will be estimated from quoted statistics and survival curves using the method by Parmar 1998.

Assessment of risk of bias in included studies

We will assess the risk of bias in included studies using The Cochrane Collaboration's tool for assessing risk of bias (Higgins 2011), which includes seven domains as follows:

• random sequence generation

• allocation concealment

• blinding of participants and personnel

• blinding of outcome assessment

• incomplete outcome data

• selective reporting

• other sources of bias

The review authors' judgements of risk of bias in each entry will be categorized as follows:

• low risk

• high risk

• unclear risk

We will also quote verbatim in the 'Risk of bias' tables from reports or correspondence in support for judgements made. Two review authors (Wu J‐S and Zhang J) will assess the risk of bias of all the included studies independently. Disagreements will be resolved by discussion. The assessments will be presented in the 'Risk of bias' graph and the 'Risk of bias' summary figures generated using RevMan 5. The risk of bias in included trails will be discussed and incorporated in the interpretation of meta‐analysis.

Measures of treatment effect

Treatment effects for different types of data will be measured as follows:

• For continuous data (e.g. language assessment scores, QoL), we will use the mean value, the standard deviation and the total number of participants in each group to calculate the weighted mean difference (WMD) between treatment arms. If different measurement scales have been used among studies, then we will use the standardized mean difference (SMD) instead.

• For dichotomous data (e.g. number of patients experiencing aphasia, time‐to‐event data that cannot be measured by HRs), we will estimate the risk ratio (RR) with 95% confidence interval (CI).

• For time‐to‐event data, we will pool the HRs by using the generic inverse variance facility of RevMan 5. If the HRs cannot be extracted or estimated from the studies, we will measure the data as dichotomous.

Unit of analysis issues

We will review unit of analysis issues according to Higgins 2011 and differences will be resolved by discussion. These may include reports where:

• Groups of individuals were randomized together to the same intervention (i.e. cluster‐randomized trials);

• Individuals undergo more than one intervention (e.g. in a cross‐over trial, or simultaneous treatment of multiple sites on each individual); or

• There are multiple observations for the same outcome (e.g. repeated measurements, recurring events, measurements on different body parts).

Dealing with missing data

We will contact the study authors to obtain missing data. If no further information is available, we will assume that data are missing at random because short‐term postoperative language functions are the main outcome. We will also perform sensitivity analyses to exclude studies with poor follow‐up rates. The potential impact of missing data will be addressed in the Discussion section of the review.

Assessment of heterogeneity

We will assess heterogeneity by visual inspection of the overlap of CIs for the results of individual studies in the forest plot. We will also use the I² statistic to quantify inconsistencies among studies. If substantial heterogeneity (I² greater than 50%) is identified, we will explore the possible causes of heterogeneity:

• variable settings of participants (e.g. countries, language)

• different scales for language assessment

• incorrect data extracted or entered into RevMan 5

• mean differences used for continuous outcomes

If we cannot readily explain the heterogeneity, we will incorporate it into a random‐effects model.

Assessment of reporting biases

We will visually inspect funnel plots to assess reporting biases. We will use contour lines to identify asymmetry due to reporting bias from that due to other factors. If there are sufficient studies included (greater than 10) in the meta‐analysis, we will perform formal tests for tunnel plot asymmetry.

Data synthesis

With sufficient studies included, we will pool their results and perform meta‐analyses for various data types.

• For continuous data, we will pool the weighted mean difference (WMD). If different measurement scales have been used among studies, the standardized mean difference (SMD) will be pooled.

• For dichotomous data, we will pool the risk ratio (RR) with 95% CI.

• For time‐to‐event data, we will pool the HR by using the generic inverse variance facility of RevMan 5. If the HRs cannot be extracted or estimated from the studies, we will measure the data as dichotomous.

If there are insufficient studies to perform a meta‐analysis, we will perform a systematic review without meta‐analysis.

Subgroup analysis and investigation of heterogeneity

We will perform the following subgroup analyses to investigate heterogeneity:

• different language branches of participants (e.g. English, French, Spanish, Chinese)

• different scales of language assessment (e.g. BDAE, WAB)

• alternative language mapping techniques (e.g. fMRI, PET scan)

Sensitivity analysis

If there are sufficient data, we will perform sensitivity analyses to assess the robustness of following decisions to:

• include studies with high risk of bias

• include studies with poor follow‐up rates

• use fixed‐effect or random‐effects methods for analyses

• analyse results of continuous outcomes as mean differences individually for each scale or as a SMD across all scales

Appendices

Appendix 1. Tumour type for inclusion

Astrocytic tumours

Pilocytic astrocytoma 9421/1¹ Pilomyxoid astrocytoma 9425/3^* Subependymal giant cell astrocytoma 9384/1 Pleomorphic xanthoastrocytoma 9424/3 Diffuse astrocytoma 9400/3 Fibrillary astrocytoma 9420/3 Gemistocytic astrocytoma 9411/3 Protoplasmic astrocytoma 9410/3 Anaplastic astrocytoma 9401/3 Glioblastoma 9440/3 Giant cell glioblastoma 9441/3 Gliosarcoma 9442/3 Gliomatosis cerebri 9381/3 Oligodendroglial tumours Oligodendroglioma 9450/3 Anaplastic oligodendroglioma 9451/3 Oligoastrocytic tumours Oligoastrocytoma 9382/3 Anaplastic oligoastrocytoma 9382/3

Ependymal tumours Subependymoma 9383/1 Myxopapillary ependymoma 9394/1 Ependymoma 9391/3 Cellular 9391/3 Papillary 9393/3 Clear cell 9391/3 Tanycytic 9391/3 Anaplastic ependymoma 9392/3

¹ Morphology code of the International Classification of Diseases for Oncology (ICD‐O) {614A} and the Systematized Nomenclature of Medicine (http://snomen.org). Behaviour is coded /0 for benign tumours, /3 for malignant tumours and /1 for borderline or uncertain behaviour.

Tumour grade: grade I to IV according to the latest WHO grading criteria;

*Tumour location: located in or close to areas of the dominant hemisphere that are associated with language functions, including:

1. Frontal lobe, which is divided into inferior frontal gyrus (BA44‐Pars opercularis, BA45‐Pars triangularis/Broca's area), middle frontal gyrus (BA9, BA46), superior frontal gyrus (BA4, BA6, BA8), primary motor cortex (BA4), premotor cortex (BA6) and supplementary motor area (BA6)

2. Parietal lobe, which is divided into inferior parietal lobule (BA40‐supramarginal gyrus, BA39‐angular gyrus), parietal operculum (BA43) and primary somatosensory cortex (BA1, BA2, BA3)

3. Temporal lobe, which is divided into transverse temporal gyrus (BA41, BA42), superior temporal gyrus (BA38, BA22/Wernicke's area) and middle temporal gyrus (BA21)

4. Insular lobe

Appendix 2. MEDLINE search strategy

The following MEDLINE Ovid search strategy will be applied:

1. exp Glioma/

2. glioma*.mp.

3. 1 or 2

4. Language/

5. Brain Mapping/

6. language*.mp.

7. map*.mp.

8. exp Aphasia/

9. (aphasia* or broca* or wernicke*).mp.

10. exp electric stimulation/

11. (electric* adj5 stimulat*).mp.

12. awake.mp.

13. 4 or 5 or 6 or 7 or 8 or 9 or 10 or 11 or 12

14. randomized controlled trial.pt.

15. controlled clinical trial.pt.

16. randomized.ab.

17. placebo.ab.

18. clinical trials as topic.sh.

19. randomly.ab.

20. trial.ti.

21. 14 or 15 or 16 or 17 or 18 or 19 or 20

22. 3 and 13 and 21

key: mp=protocol supplementary concept, rare disease supplementary concept, title, original title, abstract, name of substance word, subject heading word, unique identifier pt=publication type ab=abstract sh=subject heading ti=title

 

What's new

Date	Event	Description
15 December 2016	Amended	Withdrawn from Issue 12, 2016; editorial decision not to proceed with full review as author team unable to complete the review.

Contributions of authors

Wu J‐S designed this study. Wu J‐S and Zhang J are responsible for the execution, study coordination, manuscript writing, and data analysis. Song Y‐Y will be involved in data analysis. Lu J‐F, Yao C‐J, Zhuang D‐X and Qiu T‐M will be involved in data collection and analysis. Zhou L‐F will supervise the study design and data analysis, and will review the data and the paper.

Sources of support

Internal sources

• No sources of support supplied

External sources

• National Natural Science Foundation of China, China.

  No. 81071117

• China National Funds for Distinguished Young Scientists, China.

  No. 81025013

Declarations of interest

None known.

Notes

Withdrawn from Issue 12, 2016; editorial decision not to proceed with full review as author team unable to complete the review.

Withdrawn from publication for reasons stated in the review