J Cancer 2019; 10(25):6314-6326. doi:10.7150/jca.33463 This issue

Research Paper

Natural History of Pediatric Low-Grade Glioma Disease - First Multi-State Model Analysis

Anna-Maria Goebel1, Astrid K. Gnekow2, Daniela Kandels2, Olaf Witt3,4,5, Rene Schmidt6*, Pablo Hernáiz Driever1*✉

1. Charité-Universitätsmedizin Berlin, Corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Department of Pediatric Oncology/Hematology, Berlin, Germany
2. Augsburg University Hospital, SIOP-LGG central study registry, Swabian Children's Cancer Center, Augsburg, Germany
3. Heidelberg University Hospital, Department of Pediatric Hematology and Oncology, Heidelberg, Germany
4. German Cancer Research Center (DKFZ) and German Consortium for Translational Cancer Research (DKTK), Heidelberg, Germany
5. Hopp Children's Cancer Center at the NCT Heidelberg (KiTZ), Heidelberg, Germany
6. University of Muenster, Institute of Biostatistics and Clinical Research, Muenster, Germany
*Authors equally contributed to this work

This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/). See http://ivyspring.com/terms for full terms and conditions.
Goebel AM, Gnekow AK, Kandels D, Witt O, Schmidt R, Hernáiz Driever P. Natural History of Pediatric Low-Grade Glioma Disease - First Multi-State Model Analysis. J Cancer 2019; 10(25):6314-6326. doi:10.7150/jca.33463. Available from https://www.jcancer.org/v10p6314.htm

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Background: Pediatric low-grade glioma [PLGG] is often a chronic progressive disease requiring multiple treatments, i.e. surgery, chemotherapy and irradiation. The multi-state model [MSM] allows an extended analysis of disease-states, that patients may undergo, incorporating competing risks over the course of time.

Purpose: We studied disease-state-probabilities of the German SIOP-LGG 2004 cohort from the initial state “diagnosis” to the final state “death”. Transient “disease-states” incorporated successive surgical and non-surgical treatments. We evaluated clinical risk factors for highly progressive disease requiring multiple interventions and death.

Results: We identified 22 states within 1587 patients (median follow-up 6.3 years). For robust statistical calculation, we reduced the model to 7 states and eventually to three levels of disease-progressiveness: non, low and highly progressive. Five years after diagnosis state-probabilities were: 0.11 no therapy, 0.49 one and 0.11 two or more surgeries only, 0.19 one and 0.06 two or more non-surgical interventions with or without prior surgery. At this time point higher probability for highly progressive disease was found in infants (0.30), supratentorial-midline location (0.17) and diffuse astrocytoma WHO-grade II (0.12). Neurofibromatosis type-1 patients were most likely not to be treated (0.36) or to have received only non-surgical therapy (0.45). Two years after diagnosis 3-year predictions for highly progressive disease and death increased with the number of interventions patients underwent in the first 2 years after diagnosis.

Conclusion: In this first MSM analysis we delineated a refined description of PLGG disease course over time, identifying three levels of progressiveness. Growth behavior in the first two years predicted future progressiveness and death.

Keywords: pediatric low-grade glioma, multi-state model, survival, multiple interventions, chronic progressive disease