Dutch
Albanian
Arabic
Armenian
Azerbaijani
Belarusian
Bengali
Bosnian
Catalan
Czech
Danish
Deutsch
Dutch
English
Estonian
Finnish
Français
Greek
Haitian Creole
Hebrew
Hindi
Hungarian
Icelandic
Indonesian
Irish
Italian
Japanese
Korean
Latvian
Lithuanian
Macedonian
Mongolian
Norwegian
Persian
Polish
Portuguese
Romanian
Russian
Serbian
Slovak
Slovenian
Spanish
Swahili
Swedish
Turkish
Ukrainian
Vietnamese
Български
中文(简体)
中文(繁體)
Journal of Neuro-Oncology 2011-Aug

Radiotherapy and temozolomide for newly diagnosed glioblastoma and anaplastic astrocytoma: validation of Radiation Therapy Oncology Group-Recursive Partitioning Analysis in the IMRT and temozolomide era.

Alleen geregistreerde gebruikers kunnen artikelen vertalen
Log in Schrijf in
De link wordt op het klembord opgeslagen
Anthony J Paravati
Dwight E Heron
Douglas Landsittel
John C Flickinger
Arlan Mintz
Yi-Fan Chen
M Saiful Huq

Sleutelwoorden

Abstract

Since the development of the Radiation Therapy Oncology Group-Recursive Partitioning Analysis (RTOG-RPA) risk classes for high-grade glioma, radiation therapy in combination with temozolomide (TMZ) has become standard care. While this combination has improved survival, the prognosis remains poor in the majority of patients. Therefore, strong interest in high-grade gliomas from basic research to clinical trials persists. We sought to evaluate whether the current RTOG-RPA retains prognostic significance in the TMZ era or alternatively, if modifications better prognosticate the optimal selection of patients with similar baseline prognosis for future clinical protocols. The records of 159 patients with newly-diagnosed glioblastoma (GBM, WHO grade IV) or anaplastic astrocytoma (AA, WHO grade III) were reviewed. Patients were treated with intensity-modulated radiation therapy (IMRT) and concurrent followed by adjuvant TMZ (n = 154) or adjuvant TMZ only (n = 5). The primary endpoint was overall survival. Three separate analyses were performed: (1) application of RTOG-RPA to the study cohort and calculation of subsequent survival curves, (2) fit a new tree model with the same predictors in RTOG-RPA, and (3) fit a new tree model with an expanded predictor set. All analyses used a regression tree analysis with a survival outcome fit to formulate new risk classes. Overall median survival was 14.9 months. Using the RTOG-RPA, the six classes retained their relative prognostic significance and overall ordering, with the corresponding survival distributions significantly different from each other (P < 0.01, χ(2) statistic = 70). New recursive partitioning limited to the predictors in RTOG-RPA defined four risk groups based on Karnofsky Performance Status (KPS), histology, age, length of neurologic symptoms, and mental status. Analysis across the expanded predictors defined six risk classes, including the same five variables plus tumor location, tobacco use, and hospitalization during radiation therapy. Patients with excellent functional status, AA, and frontal lobe tumors had the best prognosis. For patients with newly-diagnosed high-grade gliomas, RTOG-RPA classes retained prognostic significance in patients treated with TMZ and IMRT. In contrast to RTOG-RPA, in our modified RPA model, KPS rather than age represented the initial split. New recursive partitioning identified potential modifications to RTOG-RPA that should be further explored with a larger data set.

Word lid van onze
facebookpagina

De meest complete database met geneeskrachtige kruiden, ondersteund door de wetenschap

  • Werkt in 55 talen
  • Kruidengeneesmiddelen gesteund door de wetenschap
  • Kruidenherkenning door beeld
  • Interactieve GPS-kaart - tag kruiden op locatie (binnenkort beschikbaar)
  • Lees wetenschappelijke publicaties met betrekking tot uw zoekopdracht
  • Zoek medicinale kruiden op hun effecten
  • Organiseer uw interesses en blijf op de hoogte van nieuwsonderzoek, klinische onderzoeken en patenten

Typ een symptoom of een ziekte en lees over kruiden die kunnen helpen, typ een kruid en zie ziekten en symptomen waartegen het wordt gebruikt.
* Alle informatie is gebaseerd op gepubliceerd wetenschappelijk onderzoek

Google Play badgeApp Store badge