Procarbazine, CCNU and vincristine (PCV) versus temozolomide chemotherapy for patients with low-grade glioma: a systematic review.

Low-grade gliomas (LGG) encompass a heterogeneous group of tumors that are clinically, histologically and molecularly diverse. Treatment decisions for patients with LGG are directed toward improving upon the natural history while limiting treatment-associated toxiceffects. Recent evidence has documented a utility for adjuvant chemotherapy with procarbazine, CCNU (lomustine), and vincristine (PCV) or temozolomide (TMZ). We sought to determine the comparative utility of PCV and TMZ for patients with LGG, particularly in context of molecular subtype. A literature search of PubMed was conducted to identify studies reporting patient response to PCV, TMZ, or a combination of chemotherapy and radiation therapy (RT). Eligibility criteria included patients 16 years of age and older, notation of LGG subtype, and report of progression-free survival (PFS), overall survival (OS), and treatment course. Level I, II, and III data were included. Adjuvant therapy with PCV resulted in prolonged PFS and OS in patients with newly diagnosed high-risk LGG. This benefit was accrued most significantly by patients with tumors harboring 1p/19q codeletion and IDH1 mutation. Adjuvant therapy with temozolomide was associated with lower toxicity than therapy with PCV. In patients with LGG with an unfavorable natural history, such as with intact 1p/19q and wild-type IDH1, RT/TMZ plus adjuvant TMZ may be the best option. Patients with biologically favorable high-risk LGG are likely to derive the most benefit from RT and adjuvant PCV

Rescue therapy for vasospasm following aneurysmal subarachnoid hemorrhage:a propensity score-matched analysis with machine learning

OBJECTIVE Rescue therapies have been recommended for patients with angiographic vasospasm (aVSP) and delayed cerebral ischemia (DCI) following subarachnoid hemorrhage (SAH). However, there is little evidence from randomized clinical trials that these therapies are safe and effective. The primary aim of this study was to apply game theory-based methods in explainable machine learning (ML) and propensity score matching to determine if rescue therapy was associated with better 3-month outcomes following post-SAH aVSP and DCI. The authors also sought to use these explainable ML methods to identify patient populations that were more likely to receive rescue therapy and factors associated with better outcomes after rescue therapy. METHODS Data for patients with aVSP or DCI after SAH were obtained from 8 clinical trials and 1 observational study in the Subarachnoid Hemorrhage International Trialists repository. Gradient boosting ML models were constructed for each patient to predict the probability of receiving rescue therapy and the 3-month Glasgow Outcome Scale (GOS) score. Favorable outcome was defined as a 3-month GOS score of 4 or 5. Shapley Additive Explanation (SNAP) values were calculated for each patient-derived model to quantify feature importance and interaction effects. Variables with high S HAP importance in predicting rescue therapy administration were used in a propensity score-matched analysis of rescue therapy and 3-month GOS scores. RESULTS The authors identified 1532 patients with aVSP or DCI. Predictive, explainable ML models revealed that aneurysm characteristics and neurological complications, but not admission neurological scores, carried the highest relative importance rankings in predicting whether rescue therapy was administered. Younger age and absence of cerebral ischemia/ infarction were invariably linked to better rescue outcomes, whereas the other important predictors of outcome varied by rescue type (interventional or noninterventional). In a propensity score-matched analysis guided by SHAP-based variable selection, rescue therapy was associated with higher odds of 3-month GOS scores of 4-5 (OR 1.63, 95% CI 1.22-2.17). CONCLUSIONS Rescue therapy may increase the odds of good outcome in patients with aVSP or DCI after SAH. Given the strong association between cerebral ischemia/infarction and poor outcome, trials focusing on preventative or therapeutic interventions in these patients may be most able to demonstrate improvements in clinical outcomes. Insights developed from these models may be helpful for improving patient selection and trial design

Development and validation of outcome prediction models for aneurysmal subarachnoid haemorrhage:the SAHIT multinational cohort study

Objective To develop and validate a set of practical prediction tools that reliably estimate the outcome of subarachnoid haemorrhage from ruptured intracranial aneurysms (SAH). Design Cohort study with logistic regression analysis to combine predictors and treatment modality. Setting Subarachnoid Haemorrhage International Trialists' (SAHIT) data repository, including randomised clinical trials, prospective observational studies, and hospital registries. Participants Researchers collaborated to pool datasets of prospective observational studies, hospital registries, and randomised clinical trials of SAH from multiple geographical regions to develop and validate clinical predicti

Global burden and strength of evidence for 88 risk factors in 204 countries and 811 subnational locations, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

Background: Understanding the health consequences associated with exposure to risk factors is necessary to inform public health policy and practice. To systematically quantify the contributions of risk factor exposures to specific health outcomes, the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021 aims to provide comprehensive estimates of exposure levels, relative health risks, and attributable burden of disease for 88 risk factors in 204 countries and territories and 811 subnational locations, from 1990 to 2021. Methods: The GBD 2021 risk factor analysis used data from 54 561 total distinct sources to produce epidemiological estimates for 88 risk factors and their associated health outcomes for a total of 631 risk–outcome pairs. Pairs were included on the basis of data-driven determination of a risk–outcome association. Age-sex-location-year-specific estimates were generated at global, regional, and national levels. Our approach followed the comparative risk assessment framework predicated on a causal web of hierarchically organised, potentially combinative, modifiable risks. Relative risks (RRs) of a given outcome occurring as a function of risk factor exposure were estimated separately for each risk–outcome pair, and summary exposure values (SEVs), representing risk-weighted exposure prevalence, and theoretical minimum risk exposure levels (TMRELs) were estimated for each risk factor. These estimates were used to calculate the population attributable fraction (PAF; ie, the proportional change in health risk that would occur if exposure to a risk factor were reduced to the TMREL). The product of PAFs and disease burden associated with a given outcome, measured in disability-adjusted life-years (DALYs), yielded measures of attributable burden (ie, the proportion of total disease burden attributable to a particular risk factor or combination of risk factors). Adjustments for mediation were applied to account for relationships involving risk factors that act indirectly on outcomes via intermediate risks. Attributable burden estimates were stratified by Socio-demographic Index (SDI) quintile and presented as counts, age-standardised rates, and rankings. To complement estimates of RR and attributable burden, newly developed burden of proof risk function (BPRF) methods were applied to yield supplementary, conservative interpretations of risk–outcome associations based on the consistency of underlying evidence, accounting for unexplained heterogeneity between input data from different studies. Estimates reported represent the mean value across 500 draws from the estimate's distribution, with 95% uncertainty intervals (UIs) calculated as the 2·5th and 97·5th percentile values across the draws. Findings: Among the specific risk factors analysed for this study, particulate matter air pollution was the leading contributor to the global disease burden in 2021, contributing 8·0% (95% UI 6·7–9·4) of total DALYs, followed by high systolic blood pressure (SBP; 7·8% [6·4–9·2]), smoking (5·7% [4·7–6·8]), low birthweight and short gestation (5·6% [4·8–6·3]), and high fasting plasma glucose (FPG; 5·4% [4·8–6·0]). For younger demographics (ie, those aged 0–4 years and 5–14 years), risks such as low birthweight and short gestation and unsafe water, sanitation, and handwashing (WaSH) were among the leading risk factors, while for older age groups, metabolic risks such as high SBP, high body-mass index (BMI), high FPG, and high LDL cholesterol had a greater impact. From 2000 to 2021, there was an observable shift in global health challenges, marked by a decline in the number of all-age DALYs broadly attributable to behavioural risks (decrease of 20·7% [13·9–27·7]) and environmental and occupational risks (decrease of 22·0% [15·5–28·8]), coupled with a 49·4% (42·3–56·9) increase in DALYs attributable to metabolic risks, all reflecting ageing populations and changing lifestyles on a global scale. Age-standardised global DALY rates attributable to high BMI and high FPG rose considerably (15·7% [9·9–21·7] for high BMI and 7·9% [3·3–12·9] for high FPG) over this period, with exposure to these risks increasing annually at rates of 1·8% (1·6–1·9) for high BMI and 1·3% (1·1–1·5) for high FPG. By contrast, the global risk-attributable burden and exposure to many other risk factors declined, notably for risks such as child growth failure and unsafe water source, with age-standardised attributable DALYs decreasing by 71·5% (64·4–78·8) for child growth failure and 66·3% (60·2–72·0) for unsafe water source. We separated risk factors into three groups according to trajectory over time: those with a decreasing attributable burden, due largely to declining risk exposure (eg, diet high in trans-fat and household air pollution) but also to proportionally smaller child and youth populations (eg, child and maternal malnutrition); those for which the burden increased moderately in spite of declining risk exposure, due largely to population ageing (eg, smoking); and those for which the burden increased considerably due to both increasing risk exposure and population ageing (eg, ambient particulate matter air pollution, high BMI, high FPG, and high SBP). Interpretation: Substantial progress has been made in reducing the global disease burden attributable to a range of risk factors, particularly those related to maternal and child health, WaSH, and household air pollution. Maintaining efforts to minimise the impact of these risk factors, especially in low SDI locations, is necessary to sustain progress. Successes in moderating the smoking-related burden by reducing risk exposure highlight the need to advance policies that reduce exposure to other leading risk factors such as ambient particulate matter air pollution and high SBP. Troubling increases in high FPG, high BMI, and other risk factors related to obesity and metabolic syndrome indicate an urgent need to identify and implement interventions

Prognostic Factors in Aneurysmal Subarachnoid Hemorrhage: Pooled Analyses of Individual Patient Data and Development of Novel Risk Scores in Large Cohorts of International Patients

Primary studies reporting prognostic associations in aneurysmal subarachnoid hemorrhage (SAH) are often insufficiently powered, use data of limited representativeness and scarcely examine the added value of prognostic factors above those of other known factors. Hence, considerable knowledge gaps and conflicting results exist in the literature on the nature and extent of prognostic associations in SAH. Prognostic factors have been combined to develop prediction models and risk scores for early outcome prediction after SAH. None is routinely applied in clinical or research settings; some major constraints relate to lack of evidence on the predictive accuracy, reliability and generalizability of reported risk scores. The global aim of this research was to address these challenges and contribute to improved understanding of prognostic associations in SAH by analysing large cohorts of SAH patients reflecting a broad spectrum of settings. Pooled analyses of patient-level data from multiple randomized clinical trials and prospective hospital registries involving 10963 patients demonstrated a strong prognostic effect of admission neurologic status on 3-month outcome according to Glasgow outcome score. Age had a moderate effect on outcome; premorbid hypertension and subarachnoid clot burden on the Fisher scale were weak predictors of outcome. Patient's sex had no independent predictive value. Prognostic effect of aneurysm size and location depended on treatment modality. Novel prognostic scores were developed combining these predictors for early prediction of mortality and unfavorable outcomes at 3 months, and demonstrated adequate performance at bootstrap (AUC: 0.77 - 0.83) and at cross validation. Using 2 nationally representative administrative datasets, socioeconomic status and race/ethnicity were explored as latent prognostic factors in SAH. Multinomial logistic regression analysis demonstrated socioeconomic status, measured as neighborhood income status, was associated with inpatient mortality risk after admission for SAH. The extent of the association could be related to health care system under which treatment was provided. Race/ethnicity was independently associated with inpatient mortality. Patients of Hispanic ethnicity had the best outcomes and Asia/Pacific Islanders experienced the worst outcomes during the inpatient course. This research has provided higher level evidence than prior studies on studied prognostic factors and reliable tools for early prediction of outcome after hospitalization for SAH.Ph.D

Development and validation of outcome prediction models for aneurysmal subarachnoid haemorrhage: the SAHIT multinational cohort study

Objective To develop and validate a set of practical prediction tools that reliably estimate the outcome of subarachnoid haemorrhage from ruptured intracranial aneurysms (SAH). Design Cohort study with logistic regression analysis to combine predictors and treatment modality. Setting Subarachnoid Haemorrhage International Trialists’ (SAHIT) data repository, including randomised clinical trials, prospective observational studies, and hospital registries. Participants Researchers collaborated to pool datasets of prospective observational studies, hospital registries, and randomised clinical trials of SAH from multiple geographical regions to develop and validate clinical prediction models. Main outcome measure Predicted risk of mortality or functional outcome at three months according to score on the Glasgow outcome scale. Results Clinical prediction models were developed with individual patient data from 10 936 patients and validated with data from 3355 patients after development of the model. In the validation cohort, a core model including patient age, premorbid hypertension, and neurological grade on admission to predict risk of functional outcome had good discrimination, with an area under the receiver operator characteristics curve (AUC) of 0.80 (95% confidence interval 0.78 to 0.82). When the core model was extended to a “neuroimaging model,” with inclusion of clot volume, aneurysm size, and location, the AUC improved to 0.81 (0.79 to 0.84). A full model that extended the neuroimaging model by including treatment modality had AUC of 0.81 (0.79 to 0.83). Discrimination was lower for a similar set of models to predict risk of mortality (AUC for full model 0.76, 0.69 to 0.82). All models showed satisfactory calibration in the validation cohort. Conclusion The prediction models reliably estimate the outcome of patients who were managed in various settings for ruptured intracranial aneurysms that caused subarachnoid haemorrhage. The predictor items are readily derived at hospital admission. The web based SAHIT prognostic calculator (http://sahitscore.com) and the related app could be adjunctive tools to support management of patients

Emotional expressions associated with therapeutic inertia in multiple sclerosis care

Background Emotions play a critical role in our daily decisions. However, it remains unclear how and what sort of emotional expressions are associated with therapeutic decisions in multiple sclerosis (MS) care. Our goal was to evaluate the relationship between emotions and affective states (as captured by muscle facial activity and emotional expressions) and TI amongst neurologists caring for MS patients when making therapeutic decisions. Methods 38 neurologists with expertise in MS were invited to participate in a face-to-face study across Canada. Participants answered questions regarding their clinical practice, aversion to ambiguity, and the management of 10 simulated case-scenarios. TI was defined as lack of treatment initiation or escalation when there was clear evidence of clinical and radiological disease activity. We recorded facial muscle activations and their associated emotional expressions during the study, while participants made therapeutic choices. We used a validated machine learning algorithm of the AFFDEX software to code for facial muscle activations and a predefined mapping to emotional expressions (disgust, fear, surprise, etc.). Mixed effects models and mediation analyses were used to evaluate the relationship between ambiguity aversion, facial muscle activity/emotional expressions and TI measured as a binary variable and a continuous score. Results 34 (89.4%) neurologists completed the study. The mean age [standard deviation (SD)] was 44.6 (11.5) years; 38.3% were female and 58.8% self-identified as MS specialists. Overall, 17 (50%) participants showed TI in at least one case-scenario and the mean (SD) TI score was 0.74 (0.90). Nineteen (55.9%) participants had aversion to ambiguity in the financial domain. The multivariate analysis adjusted for age, sex and MS expertise showed that aversion to ambiguity in the financial domain (OR 1.56, 95%CI 1.32–1.86) was associated with TI. Most common muscle activations included mouth open (23.4%), brow furrow (20.9%), brow raise (17.6%), and eye widening (13.1%). Most common emotional expressions included fear (5.1%), disgust (3.2%), sadness (2.9%), and surprise (2.8%). After adjustment for age, sex, and physicians’ expertise, the multivariate analysis revealed that brow furrow (OR 1.04; 95%CI 1.003–1.09) and lip suck (OR 1.06; 95%CI 1.01–1.11) were associated with an increase in TI prevalence, whereas upper lip raise (OR 0.30; 95%CI 0.15–0.59), and chin raise (OR 0.90; 95%CI 0.83–0.98) were associated with lower likelihood of TI. Disgust and surprise were associated with a lower TI score (disgust: p < 0.001; surprise: p = 0.008) and lower prevalence of TI (ORdisgust: 0.14, 95%CI 0.03–0.65; ORsurprise: 0.66, 94%CI 0.47–0.92) after adjusting for covariates. The mediation analysis showed that brow furrow was a partial mediator explaining 21.2% (95%CI 14.9%-38.9%) of the association between aversion to ambiguity and TI score, followed by nose wrinkle 12.8% (95%CI 8.9%-23.4%). Similarly, disgust was the single emotional expression (partial mediator) that attenuated (-13.2%, 95%CI -9.2% to -24.3%) the effect of aversion to ambiguity on TI. Conclusions TI was observed in half of participants in at least one case-scenario. Our data suggest that facial metrics (e.g. brow furrow, nose wrinkle) and emotional expressions (e.g. disgust) are associated with physicians’ choices and partially mediate the effect of aversion to ambiguity on TI

Clinical characteristics and outcome of aneurysmal subarachnoid hemorrhage with intracerebral hematoma

OBJECTIVE Intracerebral hematoma (ICH) with subarachnoid hemorrhage (SAH) indicates a unique feature of intracranial aneurysm rupture since the aneurysm is in the subarachnoid space and separated from the brain by pia mater. Broad consensus is lacking regarding the concept that ultra-early treatment improves outcome. The aim of this study is to determine the associative factors for ICH, ascertain the prognostic value of ICH, and investigate how the timing of treatment relates to the outcome of SAH with concurrent ICH. METHODS The study data were pooled from the SAH International Trialists repository. Logistic regression was applied to study the associations of clinical and aneurysm characteristics with ICH. Proportional odds models and dominance analysis were applied to study the effect of ICH on 3-month outcome (Glasgow Outcome Scale) and investigate the effect of time from ictus to treatment on outcome. RESULTS Of the 5362 SAH patients analyzed, 1120 (21%) had concurrent ICH. In order of importance, neurological status, aneurysm location, aneurysm size, and patient ethnicity were significantly associated with ICH. Patients with ICH experienced poorer outcome than those without ICH (OR 1.58; 95% CI 1.37-1.82). Treatment within 6 hours of SAH was associated with poorer outcome than treatment thereafter (adjusted OR 1.67; 95% CI 1.04-2.69). Subgroup analysis with adjustment for ICH volume, location, and midline shift resulted in no association between time from ictus to treatment and outcome (OR 0.99; 95% CI 0.94-1.07). CONCLUSIONS The most important associative factor for ICH is neurological status on admission. The finding regarding the value of ultra-early treatment suggests the need to more robustly reevaluate the concept that hematoma evacuation of an ICH and repair of a ruptured aneurysm within 6 hours of ictus is the most optimal treatment path

Predictors of Delayed Cerebral Ischemia in Patients with Aneurysmal Subarachnoid Hemorrhage with Asymptomatic Angiographic Vasospasm on Admission

Risk of delayed cerebral ischemia (DCI) in patients with aneurysmal subarachnoid hemorrhage (aSAH) with asymptomatic angiographic vasospasm on admission is unclear in the literature. The goal of this study is to identify predictors of clinical DCI in this group of patients

Sex differences in delayed cerebral ischemia after subarachnoid hemorrhage

OBJECTIVE In this study the authors sought to investigate the sex differences in the risk of delayed cerebral ischemia (DCI), delayed cerebral infarction, and the role of hormonal status. METHODS Ten studies included in the SAHIT (SAH International Trialists) repository were analyzed using a fitting logistic regression model. Heterogeneity between the studies was tested using I(2) statistics, and the results were pooled using a random-effects model. Multivariable analysis was adjusted for the effects of neurological status and fixed effect of study. An additional model was examined in which women and men were split into groups according to an age cut point of 55 years, as a surrogate to define hormonal status. RESULTS A pooled cohort of 6713 patients was analyzed. The risk of DCI was statistically significantly higher in women than in men (OR 1.29, 95% CI 1.12-1.48); no difference was found with respect to cerebral infarction (OR 1.17, 95% CI 0.98-1.40). No difference was found in the risk of DCI when comparing women ≤ 55 and > 55 years (OR 0.87, 95% CI 0.74-1.02; p = 0.08) or when comparing men ≤ 55 and > 55 years (p = 0.38). Independent predictors of DCI were World Federation of Neurosurgical Societies (WFNS) grade, Fisher grade, age, and sex. Independent predictors of infarction included WFNS grade, Fisher grade, and aneurysm size. CONCLUSIONS Female sex is associated with a higher risk of DCI. Sex differences may play a role in the pathogenesis of DCI but are not associated with menopausal status. The predictors of DCI and cerebral infarction were identified in a very large cohort and reflect experience from multiple institutions