Symptoms in primary care with time to diagnosis of brain tumours

The impact of sociodemographic background on clinical presentation of high-grade gliomas: a multi-institutional retrospective analysis

PURPOSE

High-grade gliomas (HGG; WHO III/IV) are among the most devastating intracranial malignancies, and outcomes may be associated with demographic, biological and environmental factors. Although research exists on the association of sociodemographic background with outcomes, the literature lacks data on the effect of sociodemographic background on clinical presentation. In this study, we aimed to examine race- and ethnicity-related differences in HGG presentation and diagnosis.

METHODS

We conducted a chart review of patients treated for HGG between 2015 and 2021 at three high-volume academic medical centers. A total of 314 patients were analyzed. 173 White patients were included along with 144 non-White patients, comprising of Asian (16%), Black (26%), Hispanic (9%), and other/declined (50%) race. Statistical analysis was carried out using GraphPad Prism.

RESULTS

On multivariate analysis, White race was significantly associated with a later age at diagnosis independent of IDH1 status. White patients were more likely to present with a cognitive deficit (42.3% vs. 21.1%; p = 0.02*), while less likely to present with midline shift (32.5% vs. 49.3%; p = 0.004**) and mass effect on imaging (59.8% vs. 76.1%; p = 0.003***). Additionally, Black patients were more likely to present with syncope (15.8% vs. 2.3% [n = 107]; p = 0.04*) and Hispanic patients were more likely to present with seizure (35.7% vs. 15.9% [n = 110]; p = 0.03*).

CONCLUSION

White race appears to be independently associated with a later age at diagnosis of HGG. Furthermore, Black and Hispanic patients are more likely to present with severe, life-threatening symptoms. Large-scale studies are needed to elucidate race-based differences in HGG presentation to effectively predict outcomes.

Nature and impact of symptoms at time of initial presentation for patients with glioblastoma

INTRODUCTION

In patients diagnosed with glioblastoma (GBM), minimal data exist on the pathway to presentation and the impact of symptoms on survival outcomes. This study aims to detail the symptoms that occur at time of initial presentation, the response to subsequent intervention, and the factors that predict survival in patients managed for GBM.

METHODS

A retrospective audit was performed from established prospective databases in patients managed consecutively with radiation therapy (RT) for GBM between 2016 and 2019. The major endpoint was median overall survival (mOS). Analysis was performed to determine associations with clinical factors including presenting symptom, performance status, tumour site and extent of resection. The level of carer support and objective perception of carer mastery was also assessed.

RESULTS

Overall, 182 patients with GBM were eligible for analysis. The majority of patients presented directly to Emergency (52%), with the most common initial presenting symptom being personality change in 23% of patients. The primary symptoms resolved pre-operatively in 47% of patients, with 9% having worse symptoms postoperatively. The mOS was 16.5 months (95% CI: 14.5-18.5). ECOG Scores 0-1 were associated with improved mOS at both initial ECOG (P < 0.001) and ECOG at 6 months (P = 0.006). Recognised Carer Mastery (P = 0.007) but not presence of carer (P = 0.35) was associated with improved mOS.

CONCLUSION

In patients with GBM initial presenting symptoms, level of performance status and role of carer influence clinical outcomes and survival. These findings can assist to guide clinicians and supportive care services to optimise future patient care.

Predictors of mortality at 3 months in patients with skull base tumor resections in a low-income setting

Objective

Globally, skull base tumors are among the most challenging tumors to treat and are known for their significant morbidity and mortality. Hence, this study aimed to identify robust associated factors that contribute to mortality of patients following surgical resection for a variety of skull base tumors at the 3-month follow-up period. This in turn helps devise an evidence-based meticulous treatment strategy and baseline input for quality improvement work.

Methodology

A retrospective cohort study of patients undergoing skull base tumor resection was conducted at two large-volume neurosurgery centers in Ethiopia. The categorical variables were expressed in frequencies and percentages. Normal distribution of continuous data was checked by histogram and the Shapiro-Wilk test. Median with interquartile range (IQR) was calculated for skewed data, while mean with standard deviation (SD) was used for normally distributed data. Odds ratio and adjusted odds ratio (AOR) were used to express the result of univariate and multivariate binary logistic analyses, respectively. A p-value <0.005 was considered statistically significant at 95% confidence interval (CI).

Result

The study involved 266 patients. Of this, women accounted for 63.5% of patients. The median age of patients was 37 (±IQR = 17) years while the median size of the tumor in this study was 4.9 (±IQR 1.5) cm. The mean duration of symptoms at time of presentation was 17.3 (±SD = 11.1) months. Meningioma, pituitary adenoma, and craniopharyngioma contributed to 68.4%, 19.2%, and 9% of the skull-based tumors, respectively. Mortality following skull base tumor resection was 21.1%. On multivariable binary logistic regression analysis, intraoperative iatrogenic vascular insult (AOR = 28.76, 95% CI: 6.12-135.08, p = 0.000), intraventricular hemorrhage (AOR = 6.32, 95% CI: 1.19-33.63, p = 0.031), hospital-associated infection (AOR = 6.96, 95% CI: 2.04-23.67, p = 0.002), and extubation time exceeding 24 h (AOR = 12.89, 95% CI: 4.89-40.34, p = 0.000) were statistically significant with 3-month mortality.

Conclusion

Mortality from skull base tumor resection remains high in our setting. Holistic pre-operative surgical planning, meticulous intraoperative execution of procedures, and post-operative dedicated follow-up of patients in a neurointensive care unit alongside quality improvement works on identified risks of mortality are strongly recommended to improve patient outcomes. The urgent need for setup improvement and further training of neurosurgeons is also underscored.

Predictors of operative ischemic cerebrovascular complications in skull base tumor resections: Experience in low-resource setting

Background

Ischemic cerebrovascular complications following skull base tumor resections remain a significant factor impacting both short-term and long-term patient outcomes. This study aims to improve risk stratification, surgical decision-making, and postoperative care protocols.

Methods

A retrospective cohort study on predictors of ischemic cerebrovascular complications among patients who underwent skull base tumor resection was conducted at 2 high-volume neurosurgical centers in Ethiopia from 2018 to 2023. Binary logistic analysis was performed to see the association of each predictor variable.

Results

The study included 266 patients, with 65.5% being female. The median age and tumor size were 37 (± IQR = 17) years and 4.9 cm (± IQR 1.5), respectively. Ischemic cerebrovascular complications occurred in 19.9% of patients. Middle cranial fossa tumors and tumors spanning both anterior and middle cranial fossa (AOR = 6.75, 95% CI: 1.66-27.54, P < .008), grades 3-5 vascular encasement (AOR = 5.04, 95% CI: 1.79-14.12, P < .002), near-total resection and gross total resection (AOR = 2.89, 95% CI: 1.01-8.24, P < .048), and difficult hemostasis (AOR = 9.37, 95% CI: 3.19-27.52, P < .000) were significantly associated with iatrogenic vascular injury. Subarachnoid hemorrhage had a statistically significant association with vasospasm (AOR = 12.27, 95% CI: 1.99-75.37, P = .007).

Conclusions

Surgery-related ischemic cerebrovascular complications are common. Thorough perioperative risk stratification and proactive treatment planning are crucial to mitigate vascular insults associated with it. In low-resource settings, neurosurgical services are provided without advanced instruments, leading to more complications. Therefore, it is important to focus on improving neurosurgical setup to enhance patient outcomes.

The incidence and severity of symptoms similiar to peristing concussion symptoms in neurologically healthy individuals in aotearoa New Zealand

The non-specificity of persisting concussion symptoms (PCS) following concussion can make treatment and rehabilitation a complex and challenging endeavour for clinicians. International studies have demonstrated that in neurologically healthy individuals similar symptoms also exist. This study aimed to examine the presence and frequency of symptoms similar to PCS in neurologically healthy adults in Aotearoa New Zealand and compare these to PCS following concussion. 252 neurologically healthy adults (34.22 years); completed the Rivermead Post-Concussion Questionnaire (RPQ). Scores on this measure were evaluated and compared with 146 individuals who were at least three months post-injury (34.62 years). 25.79% (n = 65) of the neurologically healthy individuals had scores on the RPQ of ≥16. Fatigue was the most commonly endorsed symptom (67.9%), followed by sleep disturbances (59.9%). Certain demographic factors (age, education history and gender) were associated with higher endorsement but only on specific symptoms. The concussion group had significantly higher scores on the RPQ and significantly more individuals with PCS. However, at the individual item level, just over half of PCS symptoms were significantly higher in the concussion group. These symptoms were predominately neurological, with only forgetfulness and irritability significantly different between the concussion and neurologically healthy groups. Symptoms similar to PCS are prevalent in neurologically healthy individuals in Aotearoa New Zealand. The implications of these findings on the rehabilitation and management of PCS are discussed.

Recurrent neural networks for time domain modelling of FTIR spectra: application to brain tumour detection

A recurrent neural network trained on time domain data can accurately identify brain tumours from serum spectral data.

Verbal fluency as a quick and simple tool to help in deciding when to refer patients with a possible brain tumour

Background

Patients with brain tumours often present with non-specific symptoms. Correctly identifying who to prioritise for urgent brain imaging is challenging. Brain tumours are amongst the commonest cancers diagnosed as an emergency presentation. A verbal fluency task (VFT) is a rapid triage test affected by disorders of executive function, language and processing speed. We tested whether a VFT could support identification of patients with a brain tumour.

Methods

This proof-of-concept study examined whether a VFT can help differentiate patients with a brain tumour from those with similar symptoms (i.e. headache) without a brain tumour. Two patient populations were recruited, (a) patients with known brain tumour, and (b) patients with headache referred for Direct-Access Computed-Tomography (DACT) from primary care with a suspicion of a brain tumour. Semantic and phonemic verbal fluency data were collected prospectively.

Results

180 brain tumour patients and 90 DACT patients were recruited. Semantic verbal fluency score was significantly worse for patients with a brain tumour than those without (P  <  0.001), whether comparing patients with headache, or patients without headache. Phonemic fluency showed a similar but weaker difference. Raw and incidence-weighted positive and negative predictive values were calculated.

Conclusion

We have demonstrated the potential role of adding semantic VFT score performance into clinical decision making to support triage of patients for urgent brain imaging. A relatively small improvement in the true positive rate in patients referred for DACT has the potential to increase the timeliness and efficiency of diagnosis and improve patient outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12883-022-02655-9.

Carbon dot-based fluorescent antibody nanoprobes as brain tumour glioblastoma diagnostics

The development of efficient and sensitive tools for the detection of brain cancer in patients is of the utmost importance particularly because many of these tumours go undiagnosed until the disease has advanced and when treatment is less effective. Current strategies employ antibodies (Abs) to detect Glial Fibrillary Acid Protein (GFAP) in tissue samples, since GFAP is unique to the brain and not present in normal peripheral blood, and it relies on fluorescent reporters. Herein we describe a low cost, practical and general method for the labelling of proteins and antibodies with fluorescent carbon dots (CD) to generate diagnostic probes that are robust, photostable and applicable to the clinical setting. The two-step protocol relies on the conjugation of a dibenzocyclooctyne (DBCO)-functionalised CD with azide functionalised proteins by combining amide conjugation and strain promoted alkyne-azide cycloaddition (SPAAC) ligation chemistry. The new class of Ab-CD conjugates developed using this strategy was successfully used for the immunohistochemical staining of human brain tissues of patients with glioblastoma (GBM) validating the approach. Overall, these novel fluorescent probes offer a promising and versatile strategy in terms of costs, photostability and applicability which can be extended to other Abs and protein systems.

Clinical validation of a spectroscopic liquid biopsy for earlier detection of brain cancer

Background

Diagnostic delays impact the quality of life and survival of patients with brain tumors. Earlier and expeditious diagnoses in these patients are crucial to reducing the morbidities and mortalities associated with brain tumors. A simple, rapid blood test that can be administered easily in a primary care setting to efficiently identify symptomatic patients who are most likely to have a brain tumor would enable quicker referral to brain imaging for those who need it most.

Methods

Blood serum samples from 603 patients were prospectively collected and analyzed. Patients either had non-specific symptoms that could be indicative of a brain tumor on presentation to the Emergency Department, or a new brain tumor diagnosis and referral to the neurosurgical unit, NHS Lothian, Scotland. Patient blood serum samples were analyzed using the Dxcover®Brain Cancer liquid biopsy. This technology utilizes infrared spectroscopy combined with a diagnostic algorithm to predict the presence of intracranial disease.

Results

Our liquid biopsy approach reported an area under the receiver operating characteristic curve of 0.8. The sensitivity-tuned model achieves a 96% sensitivity with 45% specificity (NPV 99.3%) and identified 100% of glioblastoma multiforme patients. When tuned for a higher specificity, the model yields sensitivity of 47% with 90% specificity (PPV 28.4%).

Conclusions

This simple, non-invasive blood test facilitates the triage and radiographic diagnosis of brain tumor patients, while providing reassurance to healthy patients. Minimizing time to diagnosis would facilitate identification of brain tumor patients at an earlier stage, enabling more effective, less morbid surgical and adjuvant care.

Artificial Intelligence in Brain Tumour Surgery-An Emerging Paradigm

Artificial intelligence (AI) platforms have the potential to cause a paradigm shift in brain tumour surgery. Brain tumour surgery augmented with AI can result in safer and more effective treatment. In this review article, we explore the current and future role of AI in patients undergoing brain tumour surgery, including aiding diagnosis, optimising the surgical plan, providing support during the operation, and better predicting the prognosis. Finally, we discuss barriers to the successful clinical implementation, the ethical concerns, and we provide our perspective on how the field could be advanced.

Rapid Spectroscopic Liquid Biopsy for the Universal Detection of Brain Tumours

Simple Summary

Due to the non-specific symptoms of brain cancer (e.g., headaches or memory changes), gliomas will often remain undetected until they are larger or at a higher grade, reducing the patient’s likelihood of a good clinical outcome. Earlier detection and diagnosis of brain tumours is vital to improve patient outcomes, leading to safer surgeries and earlier treatments. A liquid biopsy for brain tumour would prove revolutionary however in order to detect disease earlier the liquid biopsy needs to be able to detect smaller tumours; and current liquid biopsies perform worse when detecting smaller or earlier stage tumours. Here, for the first time, we confirm the applicability of a validated spectroscopic liquid biopsy approach to detect both small and low-grade gliomas proving that the spectroscopic liquid biopsy approach is insensitive to tumour volume unlike other liquid biopsies.

Abstract

Background: To support the early detection and diagnosis of brain tumours we have developed a rapid, cost-effective and easy to use spectroscopic liquid biopsy based on the absorbance of infrared radiation. We have previously reported highly sensitive results of our approach which can discriminate patients with a recent brain tumour diagnosis and asymptomatic controls. Other liquid biopsy approaches (e.g., based on tumour genetic material) report a lower classification accuracy for early-stage tumours. In this manuscript we present an investigation into the link between brain tumour volume and liquid biopsy test performance. Methods: In a cohort of 177 patients (90 patients with high-grade glioma (glioblastoma (GBM) or anaplastic astrocytoma), or low-grade glioma (astrocytoma, oligoastrocytoma and oligodendroglioma)) tumour volumes were calculated from magnetic resonance imaging (MRI) investigations and patients were split into two groups depending on MRI parameters (T1 with contrast enhancement or T2/FLAIR (fluid-attenuated inversion recovery)). Using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy coupled with supervised learning methods and machine learning algorithms, 90 tumour patients were stratified against 87 control patients who displayed no symptomatic indications of cancer, and were classified as either glioma or non-glioma. Results: Sensitivities, specificities and balanced accuracies were all greater than 88%, the area under the curve (AUC) was 0.98, and cancer patients with tumour volumes as small as 0.2 cm³ were correctly identified. Conclusions: Our spectroscopic liquid biopsy approach can identify gliomas that are both small and low-grade showing great promise for deployment of this technique for early detection and diagnosis.

Early diagnosis of brain tumours using a novel spectroscopic liquid biopsy

Early diagnosis of brain tumours is challenging and a major unmet need. Patients with brain tumours most often present with non-specific symptoms more commonly associated with less serious diagnoses, making it difficult to determine which patients to prioritize for brain imaging. Delays in diagnosis affect timely access to treatment, with potential impacts on quality of life and survival. A test to help identify which patients with non-specific symptoms are most likely to have a brain tumour at an earlier stage would dramatically impact on patients by prioritizing demand on diagnostic imaging facilities. This clinical feasibility study of brain tumour early diagnosis was aimed at determining the accuracy of our novel spectroscopic liquid biopsy test for the triage of patients with non-specific symptoms that might be indicative of a brain tumour, for brain imaging. Patients with a suspected brain tumour based on assessment of their symptoms in primary care can be referred for open access CT scanning. Blood samples were prospectively obtained from 385 of such patients, or patients with a new brain tumour diagnosis. Samples were analysed using our spectroscopic liquid biopsy test to predict presence of disease, blinded to the brain imaging findings. The results were compared to the patient’s index brain imaging delivered as per standard care. Our test predicted the presence of glioblastoma, the most common and aggressive brain tumour, with 91% sensitivity, and all brain tumours with 81% sensitivity, and 80% specificity. Negative predictive value was 95% and positive predictive value 45%. The reported levels of diagnostic accuracy presented here have the potential to improve current symptom-based referral guidelines, and streamline assessment and diagnosis of symptomatic patients with a suspected brain tumour.

Presenting Psychiatric and Neurological Symptoms and Signs of Brain Tumors before Diagnosis: A Systematic Review

Brain tumors can present with various psychiatric symptoms, with or without neurological symptoms, an aspect that complicates the clinical picture. However, no systematic description of symptoms that should prompt a neurological investigation has been provided. This review aims to summarize available case reports describing patients with brain tumors showing psychiatric symptoms before brain tumor diagnosis, in order to provide a comprehensive description of these symptoms as well as their potential relationship with delay in the diagnosis. A systematic literature review on case reports of brain tumors and psychiatric symptoms from 1970 to 2020 was conducted on PubMed, Ovid, Psych Info, and MEDLINE. Exclusion criteria comprised tumors not included in the World Health Organization (WHO) Classification 4th edition and cases in which psychiatric symptoms were absent or followed the diagnosis. A total of 165 case reports were analyzed. In a subset of patients with brain tumors, psychiatric symptoms can be the only manifestation or precede focal neurological signs by months or even years. The appearance of focal or generalized neurological symptoms after, rather than along with, psychiatric symptoms was associated with a significant delay in the diagnosis in adults. A timely assessment of psychiatric symptoms might help to improve early diagnosis of brain tumors.

Early economic evaluation to guide the development of a spectroscopic liquid biopsy for the detection of brain cancer

OBJECTIVES

An early economic evaluation to inform the translation into clinical practice of a spectroscopic liquid biopsy for the detection of brain cancer. Two specific aims are (1) to update an existing economic model with results from a prospective study of diagnostic accuracy and (2) to explore the potential of brain tumor-type predictions to affect patient outcomes and healthcare costs.

METHODS

A cost-effectiveness analysis from a UK NHS perspective of the use of spectroscopic liquid biopsy in primary and secondary care settings, as well as a cost-consequence analysis of the addition of tumor-type predictions was conducted. Decision tree models were constructed to represent simplified diagnostic pathways. Test diagnostic accuracy parameters were based on a prospective validation study. Four price points (GBP 50-200, EUR 57-228) for the test were considered.

RESULTS

In both settings, the use of liquid biopsy produced QALY gains. In primary care, at test costs below GBP 100 (EUR 114), testing was cost saving. At GBP 100 (EUR 114) per test, the ICER was GBP 13,279 (EUR 15,145), whereas at GBP 200 (EUR 228), the ICER was GBP 78,300 (EUR 89,301). In secondary care, the ICER ranged from GBP 11,360 (EUR 12,956) to GBP 43,870 (EUR 50,034) across the range of test costs.

CONCLUSIONS

The results demonstrate the potential for the technology to be cost-effective in both primary and secondary care settings. Additional studies of test use in routine primary care practice are needed to resolve the remaining issues of uncertainty-prevalence in this patient population and referral behavior.

Atypical teratoid rhabdoid tumor in the cerebellum of a 7-year-old boy presenting with headache after a fall

A 7-year-old boy presented to a community emergency department (ED) after sustaining a minor fall. Although he was found to have a normal neurologic examination, additional history revealed the patient had been having mild intermittent headaches and dizziness in the months preceding the fall. The emergency clinicians ordered neuroimaging, which demonstrated a right cerebellar mass, ultimately diagnosed as atypical rhabdoid/teratoid tumor. Atypical rhabdoid/teratoid tumor is a rare, aggressive brain tumor with a poor prognosis. The objectives of this case report are to emphasize the importance of detailed history with pediatric head trauma, in particular on reassessment, and to discuss briefly the epidemiology and management of atypical teratoid rhabdoid tumor.

From first symptoms to diagnosis: Initial clinical presentation of primary brain tumors

Background:

Despite modern imaging methods, a long symptom-to-diagnosis interval can be observed in patients with primary brain tumors.

Objective:

The study evaluated the initial and subsequent clinical presentation of patients with brain tumors in the context of time to diagnosis, localization, histology, and tumor grading.

Methods:

In this retrospective analysis of 85 consecutive patients with primary brain tumors, we assessed the presenting symptoms and signs. The analyses were based on entries from medical records at the Department of Neurology of Zurich University Hospital between 2005 and 2010.

Results:

A total of 54 men and 31 women with a mean age at diagnosis of 48 years were included. 60% of the patients present with a malignant tumor (World Health Organization grading III–IV), 24.7% with a benign tumor (I–II), and 15.3% were not classified. The interval between symptom onset and diagnosis varied from 1 day to 96 months (median: 39 days). High-grade tumors (III–IV) were diagnosed significantly earlier than low-grade tumors (II) after the first symptoms occurred (median: 26 vs. 138 days; z = −3.847, p < 0.001).

Conclusions:

Symptoms with a short symptom-to-diagnosis interval such as nausea/vomiting, seizures, as well as of personality change are assumed to contribute to a faster diagnosis in high-grade tumors. Visual disturbances and headaches, although occurring relatively seldom, did not contribute to a decrease in time to diagnosis and should therefore be considered for further diagnostic workup.

Economic evaluation of GPs' direct access to computed tomography for identification of brain tumours

BACKGROUND

When GPs suspect a brain tumour, a referral for specialist assessment and subsequent brain imaging is generally the first option. NICE has recommended that GPs have rapid direct access to brain imaging for adults with progressive sub-acute loss of central nervous function; however, no studies have evaluated the cost-effectiveness.

METHODS

We developed a cost-effectiveness model based on data from one region of the UK with direct access computed tomography (DACT), routine data from GP records and the literature, to explore whether unrestricted DACT for patients with suspected brain tumour might be more cost-effective than criteria-based DACT or no DACT.

RESULTS

Although criteria-based DACT allows some patients without brain tumour to avoid imaging, our model suggests this may increase costs of diagnosis due to non-specific risk criteria and high costs of diagnosing or 'ruling out' brain tumours by other pathways. For patients diagnosed with tumours, differences in outcomes between the three diagnostic strategies are small.

CONCLUSIONS

Unrestricted DACT may reduce diagnostic costs; however, the evidence is not strong and further controlled studies are required. Criteria-based access to CT for GPs might reduce demand for DACT, but imperfect sensitivity and specificity of current risk stratification mean that it will not necessarily be cost-effective.

Impact of the updated NICE referral pathway for patients with suspected brain cancer on a neuroscience service

INTRODUCTION

The National Institute for Health and Clinical Excellence (NICE) publish guidelines to facilitate the referral of patients with suspected malignancies, including CNS tumours, from primary care to the appropriate hospital services. We aimed to assess the impact and utility of the most recently revised guidelines, published in 2015, on our neurosurgical service.

MATERIALS & METHODS

We performed a retrospective analysis of the 2-week wait (2WW) referrals received by the neurosurgery department at our institution over a 3 and a half year period between 2015 and 2019. Details pertaining to the patient's clinical condition and ultimate diagnosis were collected from their medical records and assessed to determine whether the referral criteria were fulfilled.

RESULTS

Referrals for 101 patients were received over the study period (mean 29/year). Of these, 82 patients (81.2%) were referred based on symptoms, whilst 19 patients (18.8%) were referred with an abnormal brain scan. Seventy-five referrals (74%) were deemed compliant with the guideline criteria. The sensitivity and specificity of the updated guidelines was 90% (73-98%, 95% CI) and 32.4% (22-45%, 95% CI) respectively. The commonest reason for a non-compliant referral, in 21 cases (81%), was headache disorder without neurological deficit. Overall, 30 patients (30%) referred via the 2WW rule were found to have a brain tumour. With guideline adherence, the brain tumour detection rate was 3-fold higher (36.0% vs 11.5%, p = 0.02).

CONCLUSIONS

An update to the NICE guidelines has coincided with an increase in the number of 2WW referrals received by our department, an increase in guideline compliant referrals and an improved rate of tumour detection, though a significant proportion of patients referred via this route ultimately do not require the services of a neurosurgeon. Greater provision of urgent imaging for general practitioners, in accordance with the current NICE guidelines, may reduce unnecessary neurosurgery consultations.

Interventions to reduce the time to diagnosis of brain tumours

BACKGROUND

Brain tumours are recognised as one of the most difficult cancers to diagnose because presenting symptoms, such as headache, cognitive symptoms, and seizures, may be more commonly attributable to other, more benign conditions. Interventions to reduce the time to diagnosis of brain tumours include national awareness initiatives, expedited pathways, and protocols to diagnose brain tumours, based on a person's presenting symptoms and signs; and interventions to reduce waiting times for brain imaging pathways. If such interventions reduce the time to diagnosis, it may make it less likely that people experience clinical deterioration, and different treatment options may be available.

OBJECTIVES

To systematically evaluate evidence on the effectiveness of interventions that may influence: symptomatic participants to present early (shortening the patient interval), thresholds for primary care referral (shortening the primary care interval), and time to imaging diagnosis (shortening the secondary care interval and diagnostic interval). To produce a brief economic commentary, summarising the economic evaluations relevant to these interventions.

SEARCH METHODS

For evidence on effectiveness, we searched CENTRAL, MEDLINE, and Embase from January 2000 to January 2020; Clinicaltrials.gov to May 2020, and conference proceedings from 2014 to 2018. For economic evidence, we searched the UK National Health Services Economic Evaluation Database from 2000 to December 2014.

SELECTION CRITERIA

We planned to include studies evaluating any active intervention that may influence the diagnostic pathway, e.g. clinical guidelines, direct access imaging, public health campaigns, educational initiatives, and other interventions that might lead to early identification of primary brain tumours. We planned to include randomised and non-randomised comparative studies. Included studies would include people of any age, with a presentation that might suggest a brain tumour.

DATA COLLECTION AND ANALYSIS

Two review authors independently assessed titles identified by the search strategy, and the full texts of potentially eligible studies. We resolved discrepancies through discussion or, if required, by consulting another review author.

MAIN RESULTS

We did not identify any studies for inclusion in this review. We excluded 115 studies. The main reason for exclusion of potentially eligible intervention studies was their study design, due to a lack of control groups. We found no economic evidence to inform a brief economic commentary on this topic.

AUTHORS' CONCLUSIONS

In this version of the review, we did not identify any studies that met the review inclusion criteria for either effectiveness or cost-effectiveness. Therefore, there is no evidence from good quality studies on the best strategies to reduce the time to diagnosis of brain tumours, despite the prioritisation of research on early diagnosis by the James Lind Alliance in 2015. This review highlights the need for research in this area.

Prediagnostic symptoms and signs of adult glioma: the patients' view

BACKGROUND

Little is known about the symptoms glioma patients experience in the year before diagnosis, either or not resulting in health care usage. This study aimed to determine the incidence of symptoms glioma patients experienced in the year prior to diagnosis, and subsequent visits to a general practitioner (GP).

METHODS

Glioma patients were asked to complete a 30-item study-specific questionnaire focusing on symptoms they experienced in the 12 months before diagnosis. For each indicated symptom, patients were asked whether they consulted the GP for this issue.

RESULTS

Fifty-nine patients completed the questionnaires, 54 (93%) with input of a proxy. The median time since diagnosis was 4 months (range 1-12). The median number of symptoms experienced in the year before diagnosis was similar between gliomas with favourable and poor prognosis, i.e. 6 (range 0-24), as were the five most frequently mentioned problems: fatigue (n = 34, 58%), mental tiredness (n = 30, 51%), sleeping disorder (n = 24, 41%), headache (n = 23, 39%) and stress (n = 20, 34%). Twenty-six (44%) patients visited the GP with at least one issue. Patients who did consult their GP reported significantly more often muscle weakness (11 vs 3, p = 0.003) than patients who did not, which remained significant after correction for multiple testing, which was not the case for paralysis in hand/leg (10 vs 4), focussing (11 vs 6) or a change in awareness (9 vs 4).

CONCLUSIONS

Glioma patients experience a range of non-specific problems in the year prior to diagnosis, but only patients who consult the GP report more often neurological problems.

How do patients with malignant brain tumors experience general practice care and support? Qualitative analysis of English Cancer Patient Experience Survey (CPES) data

Background

English Cancer Patient Experience Survey (CPES) data show patients with brain cancer report the least-positive experiences of general practice support. We aimed to understand these findings by identifying the issues described in qualitative survey feedback and suggest how care may be improved.

Methods

We reviewed 2699 qualitative comments made to open questions about what was good or might be improved about National Health Service care between 2010 and 2014. We identified 84 (3%) specific comments about general practice care and used open coding and framework analysis to develop a thematic framework.

Results

We identified 3 key themes and 12 subthemes: first, the experience of initial diagnosis by a general practitioner (GP), including apparent complexity of making the diagnosis, apparent slowness in referral for investigation, referral made by patient or family, delay in receiving scan results, and whether the GP quickly identified the problem and referred to a specialist; second, the experience of care and support from the general practice, including lack of supportive response from the GP, lack of follow-up care from the GP, lack of family involvement by the GP, lack of GP knowledge about management, and whether the GP responded in a supportive way to the diagnosis; and third, the experience of overall coordination in care, including lack of communication between the hospital and general practice and good communication about the care plan.

Conclusion

Qualitative responses from patients with brain cancer reveal their needs for better emotional and practical support within primary care. Suggestions include increasing the speed of initial referral for investigation, the depth of discussion about diagnostic difficulties, and developing coordinated care plans with cancer centers.

Development of high-throughput ATR-FTIR technology for rapid triage of brain cancer

Non-specific symptoms, as well as the lack of a cost-effective test to triage patients in primary care, has resulted in increased time-to-diagnosis and a poor prognosis for brain cancer patients. A rapid, cost-effective, triage test could significantly improve this patient pathway. A blood test using attenuated total reflection (ATR)-Fourier transform infrared (FTIR) spectroscopy for the detection of brain cancer, alongside machine learning technology, is advancing towards clinical translation. However, whilst the methodology is simple and does not require extensive sample preparation, the throughput of such an approach is limited. Here we describe the development of instrumentation for the analysis of serum that is able to differentiate cancer and control patients at a sensitivity and specificity of 93.2% and 92.8%. Furthermore, preliminary data from the first prospective clinical validation study of its kind are presented, demonstrating how this innovative technology can triage patients and allow rapid access to imaging.

The usefulness of symptoms alone or combined for general practitioners in considering the diagnosis of a brain tumour: a case-control study using the clinical practice research database (CPRD) (2000-2014)

OBJECTIVES

To evaluate the utility of different symptoms, alone or combined, presented to primary care for an adult brain tumour diagnosis.

DESIGN AND SETTING

Matched case-control study, using the data from Clinical Practice Research Datalink (2000-2014) from primary care consultations in the UK.

METHOD

All presentations within 6 months of the index diagnosis date (cases) or equivalent (controls) were coded into 32 symptom groups. Sensitivity, specificity, positive predictive values (PPVs) and positive likelihood ratios were calculated for symptoms and combinations of symptoms with headache and cognitive features. Diagnostic odds ratios were calculated using conditional logistic regression, adjusted for age group, sex and Charlson comorbidity. Stratified analyses were performed for age group, sex and whether the tumour was of primary or secondary origin.

RESULTS

We included 8,184 cases and 28,110 controls. Seizure had the highest PPV of 1.6% (95% CI 1.4% to 1.7%) followed by weakness 1.5% (1.3 to 1.7) and confusion 1.4% (1.3 to 1.5). Combining headache with other symptoms increased the PPV. For example, headache plus combined cognitive symptoms PPV 7.2% (6.0 to 8.6); plus weakness 4.4% (3.2 to 6.2), compared with headache alone PPV 0.1%. The diagnostic ORs were generally larger for patients <70 years; this was most marked for confusion, seizure and visual symptoms.

CONCLUSION

We found seizure, weakness and confusion had relatively higher predictive values than many other symptoms. Headache on its own was a weak predictor but this was enhanced when combined with other symptoms especially in younger patients. Clinicians need to actively search for other neurological symptoms such as cognitive problems.

Direct access CT for suspicion of brain tumour: an analysis of referral pathways in a population-based patient group

BACKGROUND

Brain tumour patients see their primary care doctor on average three or more times before diagnosis, so there may be an opportunity to identify 'at risk' patients earlier. Suspecting a brain tumour diagnosis is difficult because brain tumour-related symptoms are typically non-specific.

METHODS

We explored the predictive value of referral guidelines (Kernick and NICE 2005) for brain imaging where a tumour is suspected, in a population-based patient group referred for direct access CT of the head. A consensus panel reviewed whether non-tumour findings were clinically important or whether further investigation was necessary.

RESULTS

Over a 5-year period, 3257 head scans were performed; 318 scans were excluded according to pre-specified criteria. 53 patients (1.8%) were reported to have intracranial tumours, of which 42 were significant (diagnostic yield of 1.43%). There were no false negative CT scans for tumour. With symptom-based referral guidelines primary care doctors can identify patients with a 3% positive predictive value (PPV). 559 patients had non-tumour findings, 31% of which were deemed clinically significant. In 34% of these 559 patients, referral for further imaging and/or specialist assessment from primary care was still thought warranted.

CONCLUSION

Existing referral guidelines are insufficient to stratify patients adequately based on their symptoms, according to the likelihood that a tumour will be found on brain imaging. Identification of non-tumour findings may be significant for patients and earlier specialist input into interpretation of these images may be beneficial. Improving guidelines to better identify patients at risk of a brain tumour should be a priority, to improve speed of diagnosis, and reduce unnecessary imaging and costs. Future guidelines may incorporate groups of symptoms, clinical signs and tests to improve the predictive value.

Missed opportunities for diagnosing brain tumours in primary care: a qualitative study of patient experiences

Background

Brain tumours are uncommon, and have extremely poor outcomes. Patients and GPs may find it difficult to recognise early symptoms because they are often non-specific and more likely due to other conditions.

Aim

To explore patients’ experiences of symptom appraisal, help seeking, and routes to diagnosis.

Design and setting

Qualitative study set in the East and North West of England.

Method

In-depth interviews with adult patients recently diagnosed with a primary brain tumour and their family members were analysed thematically, using the Model of Pathways to Treatment as a conceptual framework.

Results

Interviews were carried out with 39 patients. Few participants (n = 7; 18%) presented as an emergency without having had a previous GP consultation; most had had one (n = 15; 38%), two (n = 9; 23%), or more (n = 8; 21%) GP consultations. Participants experienced multiple subtle ‘changes’ rather than ‘symptoms’, often noticed by others rather than the patient, which frequently led to loss of interest or less ability to engage with daily living activities. The most common changes were in cognition (speaking, writing, comprehension, memory, concentration, and multitasking), sleep, and other ‘head feelings’ such as dizziness. Not all patients experienced a seizure, and few seizures were experienced ‘out of the blue’. Quality of communication in GP consultations played a key role in patients’ subsequent symptom appraisal and the timing of their decision to re-consult.

Conclusion

Multiple subtle changes and frequent GP visits often precede brain tumour diagnosis, giving possible diagnostic opportunities for GPs. Refined community symptom awareness and GP guidance could enable more direct pathways to diagnosis, and potentially improve patient experiences and outcomes.