Estimation of the α/β ratio of non-small cell lung cancer treated with stereotactic body radiotherapy.
Aged
Aged, 80 and over
Bayes Theorem
Carcinoma, Non-Small-Cell Lung
/ pathology
Cell Survival
/ radiation effects
Dose Fractionation, Radiation
Female
Humans
Logistic Models
Lung Neoplasms
/ pathology
Male
Middle Aged
Models, Statistical
Neoplasm Recurrence, Local
/ pathology
Radiation Dose Hypofractionation
Radiosurgery
/ methods
Retrospective Studies
Linear-quadratic model
NSCLC
Radiobiology
SBRT
Tumor control probability
Journal
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
ISSN: 1879-0887
Titre abrégé: Radiother Oncol
Pays: Ireland
ID NLM: 8407192
Informations de publication
Date de publication:
01 2020
01 2020
Historique:
received:
03
04
2019
revised:
11
06
2019
accepted:
04
07
2019
pubmed:
23
8
2019
medline:
13
8
2020
entrez:
22
8
2019
Statut:
ppublish
Résumé
High-dose hypofractionated radiotherapy should theoretically result in a deviation from the typical linear-quadratic shape of the cell survival curve beyond a certain threshold dose, yet no evidence for this hypothesis has so far been found in clinical data of stereotactic body radiotherapy treatment (SBRT) for early-stage non-small cell lung cancer (NSCLC). A pragmatic explanation is a larger α/β ratio than the conventionally assumed 10 Gy. We here attempted an estimation of the α/β ratio for NSCLC treated with SBRT using individual patient data. We combined two large retrospective datasets, yielding 1294 SBRTs (≤10 fractions) of early stage NSCLC. Cox proportional hazards regression, a logistic tumor control probability model and a biologically motivated Bayesian cure rate model were used to estimate the α/β ratio based on the observed number of local recurrences and accounting for tumor size. A total of 109 local progressions were observed after a median of 17.7 months (range 0.6-76.3 months). Cox regression, logistic regression of 3 year tumor control probability and the cure rate model yielded best-fit estimates of α/β = 12.8 Gy, 14.9 Gy and 12-16 Gy (depending on the prior for α/β), respectively, although with large uncertainties that did not rule out the conventional α/β = 10 Gy. Clinicians can continue to use the simple LQ formalism to compare different SBRT treatment schedules for NSCLC. While α/β = 10 Gy is not ruled out by our data, larger values in the range 12-16 Gy are more probable, consistent with recent meta-regression analyses.
Sections du résumé
BACKGROUND
High-dose hypofractionated radiotherapy should theoretically result in a deviation from the typical linear-quadratic shape of the cell survival curve beyond a certain threshold dose, yet no evidence for this hypothesis has so far been found in clinical data of stereotactic body radiotherapy treatment (SBRT) for early-stage non-small cell lung cancer (NSCLC). A pragmatic explanation is a larger α/β ratio than the conventionally assumed 10 Gy. We here attempted an estimation of the α/β ratio for NSCLC treated with SBRT using individual patient data.
MATERIALS AND METHODS
We combined two large retrospective datasets, yielding 1294 SBRTs (≤10 fractions) of early stage NSCLC. Cox proportional hazards regression, a logistic tumor control probability model and a biologically motivated Bayesian cure rate model were used to estimate the α/β ratio based on the observed number of local recurrences and accounting for tumor size.
RESULTS
A total of 109 local progressions were observed after a median of 17.7 months (range 0.6-76.3 months). Cox regression, logistic regression of 3 year tumor control probability and the cure rate model yielded best-fit estimates of α/β = 12.8 Gy, 14.9 Gy and 12-16 Gy (depending on the prior for α/β), respectively, although with large uncertainties that did not rule out the conventional α/β = 10 Gy.
CONCLUSIONS
Clinicians can continue to use the simple LQ formalism to compare different SBRT treatment schedules for NSCLC. While α/β = 10 Gy is not ruled out by our data, larger values in the range 12-16 Gy are more probable, consistent with recent meta-regression analyses.
Identifiants
pubmed: 31431371
pii: S0167-8140(19)32998-6
doi: 10.1016/j.radonc.2019.07.008
pii:
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
210-216Informations de copyright
Copyright © 2019 Elsevier B.V. All rights reserved.