A prospective observational study assessing waiting times from diagnosis to treatment in brain tumor patients

INTRODUCTION

The global burden of brain tumors is substantial, brain and central nervous system cancers represent a significant public health concern globally due to their high mortality rates, substantial economic impact on individuals and society, low survival rates, and negative effects on patients’ quality of life.^[1,2] According to the global cancer observatory, tumors are the 10^th leading cause of cancer-related deaths, accounting for approximately 2.5% of all cancer deaths annually.^[3] An estimated 10–26% of patients who succumb to cancer will develop brain metastases during the course of their illness.^[4] Although most cancers that spread to the brain are challenging to cure with conventional therapies, long-term survival and effective palliation are achievable, often with minimal adverse effects on patients.^[5]

Brain tumors represent a significant public health challenge due to their complex management and profound impact on patients.^[6,7] Delays in treatment initiation can adversely affect outcomes, emphasizing the need to analyze waiting times systematically.^[8]

High-grade gliomas, in particular, progress rapidly and require urgent intervention to improve survival. These tumors are known for their aggressive nature, poor prognosis, and high recurrence rates. However, low-grade gliomas, although slower growing, also need timely treatment. If left untreated, they can progress to high-grade tumors and cause long-term complications such as seizures, cognitive impairment, or neurological deficits. Early surgical management and regular monitoring are therefore critical, even in patients with low-grade gliomas. Including both types of tumors in this study allows for a broader understanding of how delays impact patient care across the spectrum of brain tumor pathology.

However, timely initiation of treatment remains a challenge, especially in resource-limited settings where long waiting times for surgery, radiation therapy, and other interventions can adversely affect outcomes.^[9]

Delays in treatment are associated with poorer prognoses, especially for high-grade gliomas, where time to treatment can significantly influence survival rates.^[10] It has been reported that delays in the surgical treatment of glioblastoma were correlated with worse overall survival.^[11] In addition, high-grade brain tumors are known to progress rapidly, and any delay in initiating therapy may reduce the likelihood of positive outcomes. It has been reported that the high-grade brain tumors, a delay of more than 2 weeks between diagnosis and treatment initiation, were associated with reduced survival.^[12]

In India, the situation is compounded by the underdevelopment of healthcare infrastructure, particularly in public institutions, which often experience overcrowding and limited access to timely interventions.^[13,14]

This prospective observational study seeks to evaluate the waiting times from diagnosis to treatment for brain tumor patients at a Tertiary Care Center in India. By analyzing the demographic characteristics, tumor classifications, and hospitalization outcomes, the study aims to provide a comprehensive understanding of the critical delays in treatment initiation and offer recommendations for improving healthcare delivery.

MATERIALS AND METHODS

RESULTS

A total of 272 brain tumor patients (including Pediatric patients) were included in the study, with 166 males (61.0%) and 106 females (39.0%). Overall, 20.9% of the patients were pediatric cases [Figure 1a and 1b]. The analysis of treatment timelines revealed notable delays at multiple stages of care. The mean time from patient registration to surgery was 284 days (IQR: 182.5–366), suggesting a prolonged waiting period that could potentially affect disease progression. The average time between surgery and availability of biopsy report was 30 days (IQR: 18–42). The mean duration from availability of biopsy report to chemotherapy initiation was 52 days (IQR: 33.5–55), while the mean time from availability of biopsy report to radiation therapy initiation was 45 days (IQR: 27–56) [Table 1]. These delays, particularly in patients with high-grade tumors, highlight concerns about system inefficiencies and their potential impact on patient outcomes. The delays may be attributed to limited healthcare resources and the high number of patients in tertiary care centers, indicating the need for improved workflow management and resource optimization.

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Figure 1:

Distribution of gender and age among 272 brain tumor patients. Data on the demographic characteristics of the cohort, including gender and age distribution percentage, (a) Gender distribution and (b) Age distribution (adult vs pediatric).

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The analysis of intracranial tumor distribution in the studied cohort showed that low-grade gliomas were the most common intracranial tumors, representing 31.99% of cases. Meningiomas followed at 18.75%, while high-grade gliomas accounted for 14.71%. Pituitary tumors were observed in 10.29% of patients, whereas schwannomas and craniopharyngiomas comprised 7.72% and 7.35%, respectively. Rare brain tumors, encompassing less common histological subtypes, made up 2.94% of the cases, whereas medulloblastomas represented 2.21% [Figure 2].

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Figure 2:

The chart displays the percentage distribution of brain tumor patient cases. LGG: Low-grade gliomas, HGG: High-grade gliomas.

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Furthermore, among the 57 pediatric patients analyzed, low-grade gliomas were the most prevalent, constituting 35.09% of cases. Craniopharyngiomas accounted for 22.81%, in our study, craniopharyngiomas were the second most prevalent intracranial tumors in pediatric patients, followed by high-grade gliomas at 10.53%, meningiomas at 8.77% and medulloblastomas at 8.77%, and pituitary tumors at 5.26%. Schwannomas and rare tumors were identified in 3.51% of cases each [Figure 3].

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Figure 3:

The chart illustrates the percentage distribution of brain tumor cases among 57 pediatric patients.

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The distribution shows that gliomas, both high-grade and low-grade, are the most common tumors. Hospitalization outcomes demonstrated that 14 patients (5.1%) died and the remaining 258 patients (94.9%) were discharged following treatment. Overcrowding in hospitals causes delays in patient care, making it critical to provide timely treatment. Especially for high-grade tumor patients, who need urgent care, may experience critical delays that affect their recovery.

DISCUSSION

The findings of this study shed light on the delays in the treatment pathways for brain tumor patients, particularly for those with high-grade malignancies, which may adversely affect clinical outcomes. High-grade tumors, such as glioblastomas and high-grade brain tumors, are characterized by aggressive progression, emphasizing the critical importance of timely intervention.^[15] Delays in surgical management and adjuvant therapies, including chemotherapy and radiation, have been associated with reduced overall survival.^[16]

It has been reported that the detrimental impact of treatment delays in high-grade brain tumors. For instance, a previous study demonstrated that longer intervals between diagnosis and surgery were associated with increased tumor burden and poorer surgical outcomes. Similarly, delays in initiating adjuvant therapy in high-grade glioma patients have been shown to result in diminished therapeutic efficacy and reduced overall survival.^[17] These findings recommend the importance of reducing waiting times to improve patient outcomes.

In resource-limited settings such as India, systemic barriers contribute significantly to treatment delays. Overburdened public healthcare facilities, limited availability of neurosurgeons, or insufficient infrastructure for advanced diagnostic and therapeutic interventions are the major challenges.^[18] Studies from other low- and middle-income countries have reported similar findings, where overcrowding and limited resources in government hospitals lead to prolonged waiting times and suboptimal care delivery.^[19,20]

The extended waiting times observed in this study, spanning registration to surgery and subsequent adjuvant therapies, are particularly concerning in the context of high-grade tumors. As per our findings, the IQRs show minor variations between the two groups. As, the IQR for registration to surgery was 180 days for adults and 185 days for pediatric patients. While pediatric patients are generally given priority due to the importance of early intervention in brain development, in our study, both groups experienced similarly long delays. This may reflect systemic challenges such as limited operating room availability and overall patient load, which affect all patients regardless of age. The delay in initiating chemotherapy and radiation therapy following surgery can contribute to tumor recurrence and progression. Stupp et al. emphasized that timely initiation of the Stupp protocol (surgical resection followed by radiotherapy and concomitant temozolomide), that is standard protocol for survival of high-grade glioma patients. Deviations from this protocol, particularly delays, are associated with reduced median survival rates.^[21,22]

To reduce these delays, several steps can be considered. Improving coordination between departments – such as neurosurgery, pathology, radiology, and oncology – can help streamline patient flow. Setting up fast-track pathways for high-grade tumors, increasing operation theater slots for urgent cases, and optimizing the scheduling process could significantly shorten waiting times.

We have also added a patient navigator to our team. This person helps patients and families move through the hospital system by guiding them on when and where to get tests such as magnetic resonance imaging’s and biopsy reports. The navigator also follows up with departments to avoid delays. This support has already started helping with better coordination. We plan to study its full impact in future work.

In addition, the use of digital tracking systems for scheduling and follow-ups may enhance workflow efficiency. These measures require institutional support, improved infrastructure, and adequate staffing to be effectively implemented. Although some of these steps are being gradually introduced at our center, a systematic and large-scale approach is needed to see measurable impact.

It is important to note that the waiting times reported in this study reflect the situation at a high-volume tertiary care public hospital, which experiences significant patient overcrowding and limited resources. These delays may not be fully representative of all neurosurgical centers in the government sector, as admission policies and patient loads can vary across institutions. Our primary aim was to highlight the delays in treatment faced by patients in such settings, which may serve as a reference point for addressing systemic inefficiencies and guiding improvements in care delivery. This limitation has been acknowledged in interpreting the generalizability of our findings.

This study was conducted at a single tertiary care government hospital, so the results may not represent all hospitals in the country. However, since this hospital sees a large number of brain tumor patients, it shows the kind of delays that can happen in busy public hospitals. We agree that including more centers would give a better overall picture, and we suggest that future studies should look at this on a larger scale.

CONCLUSION

This study identifies substantial delays in treatment timelines for brain tumor patients at a Tertiary Care Center in India. The extended waiting periods from registration to surgery and subsequent adjuvant therapies could be associated with adverse clinical outcomes and reduced survival rates. These delays reflect basic issues related to resource allocation and multidisciplinary coordination. Optimizing treatment pathways and reducing waiting times are critical for improving clinical outcomes, particularly for patients with aggressive malignancies.