Our results demonstrate that brain activity in glioma patients as measured by MEG is associated with PFS when adjusting for other known predictors (age, tumor grade, KPS, epilepsy and IDH/1p19q status). According to our results, assessment of broadband power could thus improve the current prognosis prediction. Although we did not directly measure tumor growth, these findings also support the hypothesis that higher levels of neuronal activity are associated with faster tumor growth. Activity recorded at the sensor-level did not predict PFS, emphasizing the importance of reconstructing activity at the source-level [31, 32].
Older age was associated with a slightly longer PFS (HR 0.93), whereas we expected age to predict a slightly shorter PFS (previously reported HR 1.02–1.06) . This could be due to our small sample size, or to a possible selection bias that resulted in above average vitality in our older patients.
Results from the post-hoc analyses also suggest a relationship between broadband power and overall survival. The univariate model showed broadband power to be predictive of OS, the multivariate model verified this connection. Even though this multivariate model was overfitted and thus had limited statistical power, it suggests that the predictive value of broadband power cannot be explained by other predictors and is an independent predictor of OS.
In our patients, broadband power was assessed after tumor resection, which is a relevant phase of the disease in terms of treatment strategy. Part of the current cohort has been reported on with respect to preoperative broadband power, showing that higher oscillatory activity before tumor resection significantly predicts PFS . Hazard ratios for broadband power were similar in the separate analyses of the previously analyzed cohort and the new cohort, suggesting that our findings are robust, both in terms of time point (before or after tumor resection) and cohorts. Although broadband power did not reach significance in predicting PFS in the two small subgroups (likely due to reduced statistical power), hazard ratios were comparable to those found for the entire cohort. This indicates that the current results were not driven by those patients already included in our previous study but may be seen as a replication and extension of those results.
Broadband power was based on all AAL regions, because Derks et al. showed similar results in the preoperative setting for tumor regions specifically and when including all AAL regions . From a brain network perspective, glioma and the resection of glioma affects the entire brain network and it is therefore reasonable to expect global alterations in broadband power [33, 34].
Glioma prognosis and treatment are determined preoperatively and confirmed or adapted postoperatively, based predominantly on histopathology, molecular tumor subtyping, radiological imaging and patient condition. Our results suggest that broadband power could contribute to assessment of prognosis in the postoperative disease phase.
Additionally, broadband power may speculatively be useful in dynamically monitoring disease course. If broadband power is indeed a valid proxy of the neuronal activity that leads to accelerated tumor growth, (forthcoming) tumor progression may conceivably be detected with broadband power before radiological or clinical progression is observable . If so, this would be particularly relevant in the context of pseudoprogression. Pseudoprogression occurs in approximately 10–30% of patients treated for gliomas, and is difficult to distinguish from real tumor progression . With conventional MRI, an estimated 37% of diagnosed progressive disease cases are actually (at least partly) pseudoprogression . Consequently, current guidelines discourage diagnosing tumor progression within the first 3 months posttreatment . Due to the aggressive nature of (in particular) glioblastomas, however, progression might very well be seen within these first months, underlining the need for better, non-invasive markers of (early) progression. Larger prospective studies are necessary to investigate the value of broadband power in this context.
A foreseen barrier towards clinical implementation of our current results is the fact that MEG is costly and not widely available in hospitals around the world, although new technical developments may change this situation rapidly . For now, a more feasible alternative could be to use EEG, as it is widely available and less costly. Although EEG is less accurate and more prone to artifacts than MEG, it might be worth investigating whether EEG also reliably measures broadband neuronal power and predicts PFS.
Even more valuable than improving survival prediction and monitoring, is the possibility of developing new treatment targets based on the mechanism hypothesized to underlie the predictive value of broadband power for PFS. NLGN3 has been suggested to play a key role in glioma growth and might therefore be a viable treatment target . Indeed, gliomas fail to grow in NLGN3 knockout mice, while blocking NLGN3 release prevents tumor growth in animals . However, these inhibitors are currently not suitable for human use. Therefore, a more feasible treatment target might be neuronal activity, which might be reduced through antiepileptic drugs (AEDs) as these could diminish neuronal activity, or through non-invasive inhibitory stimulation using transcranial magnetic stimulation (TMS) or transcranial direct/alternating current stimulation (tDCS/tACS) [35,36,37,38,39,40,41,42]. Clinical trials are necessary to further explore the therapeutic benefits of these targets.
First, although very well-characterized, the study cohort should be considered small, so caution must be applied when interpreting our results. The robustness of the results was evaluated with leave-one-out analyses, showing a 11–16% model instability, probably due to the low sample size. Nevertheless, our study results are in line with previous findings .
Furthermore, the study population does not accurately reflect the general diffuse glioma patient population: our patients generally had prognostically favorable tumors, were relatively young and had high performance status. This selection bias possibly resulted in the surprising finding that older age was associated with longer PFS. Although the effect was small (HR 0.95), it was significant, underlining that we should interpret our findings with caution when extrapolating to the general diffuse glioma population.
Most patients used an AED. Even though AED dosing was titrated in order to achieve seizure freedom and may thus not reach levels necessary for the dose-dependent lowering of neuronal activity, we cannot exclude the possibility that AED use influenced our results .
Last, we used broadband activity as a proxy of neuronal firing. Although we did not directly measure neuronal activity, assessment through MEG remains its most accurate non-invasive proxy [10, 12].