Dataset Information

Estimating progression-free survival in patients with glioblastoma using routinely collected data.

ABSTRACT: Glioblastoma (GBM) represents 80% of all primary malignant brain tumours in adults. Prognosis is poor, and there is a clear correlation between disease progression and deterioration in functional status. In this pilot study we assess whether we can estimate disease progression and progression free survival (PFS) from routinely collected electronic healthcare data. We identified fifty patients with glioblastoma who had chemo-radiotherapy. For each patient we manually collected a reference data set recording demographics, surgery, radiotherapy, chemotherapy, follow-up and death. We also obtained an electronic routine data set for each patient by combining local data on chemotherapy/radiotherapy and hospital admissions. We calculated overall survival (OS) and PFS using the reference data set, and estimated them using the routine data sets using two different methods, and compared the estimated measures with the reference measures. Overall survival was 68% at 1 year and median OS was 12.8 months. The routine data correctly identified progressive disease in 37 of 40 patients and stable disease in 7 of 10 patients. PFS was 7.4 months and the estimated PFS using routine data was 9.1 and 7.8 months with methods 1 and 2 respectively. There was acceptable agreement between reference and routine data in 49 of 50 patients for OS and 35 of 50 patients for PFS. The event of progression, subsequent treatment and OS are well estimated using our approach, but PFS estimation is less accurate. Our approach could refine our understanding of the disease course and allow us to report PFS, OS and treatment nationally.

SUBMITTER: Kelly C

PROVIDER: S-EPMC5700233 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Estimating progression-free survival in patients with glioblastoma using routinely collected data.

Kelly Charlotte C Majewska Paulina P Ioannidis Stefanos S Raza Muhammad Hasan MH Williams Matt M

Journal of neuro-oncology 20170927 3

Glioblastoma (GBM) represents 80% of all primary malignant brain tumours in adults. Prognosis is poor, and there is a clear correlation between disease progression and deterioration in functional status. In this pilot study we assess whether we can estimate disease progression and progression free survival (PFS) from routinely collected electronic healthcare data. We identified fifty patients with glioblastoma who had chemo-radiotherapy. For each patient we manually collected a reference data se ...[more]

PMID: 28956223

Similar Datasets

Project description:Introduction: Achieving equity in health care remains a challenge for health care systems worldwide and marked inequities in access and quality of care persist. Identifying health care equity indicators is an important first step in integrating the concept of equity into assessments of health care system performance, particularly in emergency care. Methods: We conducted a systematic review of administrative data-derived health care equity indicators and their association with socioeconomic determinants of health (SEDH) in emergency care settings. Following PRISMA-Equity reporting guidelines, Ovid MEDLINE, EMBASE, PubMed, and Web of Science were searched for relevant studies. The outcomes of interest were indicators of health care equity and the associated SEDH they examine. Results: Among 29 studies identified, 14 equity indicators were identified and grouped into four categories that reflect the patient emergency care pathway. Total emergency department (ED) visits and ambulatory care-sensitive condition-related ED visits were the two most frequently used equity indicators. The studies analyzed equity based on seven SEDH: social deprivation, income, education level, social class, insurance coverage, health literacy, and financial and nonfinancial barriers. Despite some conflicting results, all identified SEDH are associated with inequalities in access to and use of emergency care. Conclusion: The use of administrative data-derived indicators in combination with identified SEDH could improve the measurement of health care equity in emergency care settings across health care systems worldwide. Using a combination of indicators is likely to lead to a more comprehensive, well-rounded measurement of health care equity than using any one indicator in isolation. Although studies analyzed focused on emergency care settings, it seems possible to extrapolate these indicators to measure equity in other areas of the health care system. Further studies elucidating root causes of health inequities in and outside the health care system are needed.

Dataset Information

Estimating progression-free survival in patients with glioblastoma using routinely collected data.

Publications

Estimating progression-free survival in patients with glioblastoma using routinely collected data.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure