Predictors of survival in children with ependymoma from a singlecenter: using random survival forests

Francisco Hélder Cavalcante Félix1, Paula Maria PereiraFreire2, Kelly Kaliana dos Santos2, Juvenia Bezerra Fontenele2

1 - Hospital Infantil Albert Sabin, Secretaria de Saúde do Estado do Ceará2 - Curso de Farmácia, Faculdade de Farmácia Odontologia e Enfermagem, Universidade Federal do Ceará

helder.felix@hias.ce.gov.br

XIX Congresso Brasileiro de Oncologia Clínica — SBOC 2015

Introduction

Ependymoma accounts for 8–10% of all pediatric braintumors and constitutes the third most common brain

tumor in children. No robust molecular markers are yetin routine clinical use. Surgical resection and adjuvant ra-diotherapy cure approximately 40-70% of pediatric pati-ents with ependymoma. In our centre, we have been usingprophylactic valproic acid treatment for brain tumor pa-tients. Initial observations indicated that valproate couldhave a beneficial effect in the survival of patients. Recentobservations by other authors have shown that patientswith glioblastoma benefited from the treatment with val-proic acid, a histone deacetylase inhibitor.[1] Random sur-vival forests (RSF) modeling is a new statistical methodthat grows numerous mature trees with many branches,reducing variance and bias by using all variables collectedand by automatically assessing for nonlinear effects andcomplex interactions. [2]

MethodsThese results are part of a retrospective study approved by the institutional reviewboard of our institution (CAAE 26609514.4.0000.5042). We reviewed the charts ofpatients referred to our institution and diagnosed between January 2000 and De-cember 2010 with ependymoma, aged 0-17 years. Since January 2007, valproatesodium at doses 10-15mg/kg/day every 8-12h was routinely prescribed for all pe-diatric brain tumor patients in our institution as prophylactic anticonvulsant. Theprimary study endpoint was time to death from any cause, measured from the di-agnosis, from which overall survival (OS) percentage was computed. The primaryobjective of the statistical analysis was to determine the predictors of OS. Thefollowing variables were assessed for prognostic value: age, sex, metastasis at diag-nosis (metastasis), anaplasia, tumor site, treatment with chemotherapy, treatmentwith radiotherapy, extent of surgery, prophylatic treatment with valproate. Ran-dom survival analysis used all-cause mortality for the outcome. A survival forestof 1000 survival trees was constructed. Variables were selected with minimal depthmethod and the model was rerun, yielding another forest with only the selectedvariables. Prediction accuracy for RSF was assessed by Harrell C-index (C) usingout-of-bag (OOB) data. The error rate was computed as 1−C. A hundred replica-tions were run and the mean and standard deviation of the concordance error ratewere recorded (1000 trees in each replicated forest). Informativeness of each pre-dictor selected was assessed graphically by plotting importance values and partialpredicted survival time for a given predictor, after adjusting for all other predictors.Next, a nested analysis was done by sorting predictors by their importance values.The variation in error rate was checked for each nested model. Finally, a bootstra-ped Cox proportional hazards model was constructed and compared with the RSFmodel for predictive accuracy of the model and for selection of important risk fac-tors for all-cause mortality. Prediction accuracy for the Cox proportional hazardsmodel was assessed by Harrell C-index OOB data. OOB estimate of C-index forCox model was based on 100 bootstraps. Data descriptive statistics and statisti-cal calculations were performed on R for Mac OSX (R Foundation for StatisticalComputing, 2010). .

ResultsBetween 2000 and 2010, 27 patients were diagnosed withependymoma. There were seventeen males and 10 fema-les. Mean and median ages were 7.6 and 8.3 years.

0 20 40 60 80 100 120

0.0

0.2

0.4

0.6

0.8

1.0

Surgery extent

0 20 40 60 80 100 1200.0

0.2

0.4

0.6

0.8

1.0

Radiotherapy

0 20 40 60 80 100 120

0.0

0.2

0.4

0.6

0.8

1.0

Valproic acid

0 20 40 60 80 100 120

0.0

0.2

0.4

0.6

0.8

1.0

Tumor site

Figure 1: Patients with ependymoma diagnosed between 2000-2010.

Kaplan-Meier survival curves stratified by major variables.

Surg < 1.5

Age >= 11

>= 1.5

< 11

123 / 39100%

0.6810 / 2154%

0.492 / 718%

0.818 / 1436%

1.613 / 1846%

A VPA >= 0.5

Sex < 0.5

< 0.5

>= 0.5

123 / 39100%

0.6810 / 1949%

1.613 / 2051%

1.17 / 1333%

2.76 / 718%

B

VPA >= 0.5

Sex < 0.5

< 0.5

>= 0.5

123 / 39100%

0.6810 / 1949%

1.613 / 2051%

1.17 / 1333%

2.76 / 718%

C ana < 0.5

Topo = Spr

>= 0.5

P_F

123 / 39100%

0.8112 / 2359%

0.452 / 718%

1.110 / 1641%

1.311 / 1641%

D

5658

6062

64

Surg

1 2

5660

64

VPA

0 1

5660

64

RT

0 1

Figure 2: CART trees were plotted as example. Trees were modelled excluding

one or more variables. Boxplots of partial predicted values show the impact of

each of the predictor variables in the outcome (survival time), weighted by all

other variables.

0 200 400 600 800 1000

0.4

0.5

0.6

0.7

Number of Trees

Erro

r Rat

e

AgeanaMXSexTopochemoSurgVPART

−0.04 0.00 0.04

Variable Importance

0 200 400 600 800 1000

0.20

0.30

0.40

0.50

Number of Trees

Erro

r Rat

e

RT

VPA

Surg

0.02 0.04 0.06 0.08

Variable Importance

Figure 3: Aggregate variable importance (calculated from C-index) for each

variable. Using the minimum depth method, only the most strong variables were

selected (lower panel).

Seventeen had posterior fossa tumors, 6 had supratento-rial lesions. Eighteen were submitted to complete surgicalresection, whereas 9 had partial resection or biopsy. Nine-teen received radiotherapy. Seventeen received adjuvantchemotherapy. Simple Kaplan-Meier estimates were cal-culated. Univariate analysis with log-rank test indicatedthat surgical extent (p<0.01), radiotherapy (p<0.01) andvalproic acid therapy (p=0.01) modified survival, but nottumor site (p=0.5). RSF model indicated 6 variables aspredictors of OS: surgery extent, valproic acid treatment,radiotherapy treatment, anaplasia, topography and che-motherapy. After variable selection, 3 variables were left,in order of importance: valproic acid, surgery, and radi-otherapy. Mean concordance error rate for the final RSFmodel wa s 0.25(±0.016). Drop in concordance error ratewas 0.2365 for surgery extent, and 0.0166 for valproic acidtreatment. The concordance error rate for bootstrapedCox model was 0.28.

ConclusionThis analysis has confirmed surgery resection extent andtreatment with radiotherapy as independent predictors ofoverall survival. More data is needed about the possibleinfluence of histone deacetylase inhibition by valproic acidin the survival of patients with ependymoma.

References

[1] WELLER M, Gorlia T, Cairncross JG et al Prolonged survival with valproicacid use in the EORTC/NCIC temozolomide trial for glioblastoma. Neurology2011;77:1156–1164

[2] ISHWARAM H, Kogalur UB, Blackstone EH, Lauer MS. Random survivalforests (2008) Ann Appl Stat. 2:841– 860.

[3] KAPLAN EL, Meier P. Nonparametric estimation from incomplete observati-ons. J Amer Stat Assoc 1958;53(282):457-81.

Aknowledgements

SBOC 2015 - XIX Congresso Brasileiro de Oncologia Clínica