Stereotactic body radiation therapy for stage I non-small cell lung cancer: The importance of treatment planning algorithm and evaluation of a tumor control probability model

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Background: Stereotactic body radiation therapy (SBRT) is increasingly used to treat early-stage non-small cell lung cancer (NSCLC). A previous report introduced the term size-adjusted biologically effective dose (sBED), which accounts for tumor diameter and biologically effective dose (BED) and may be used to predict the likelihood of local control following SBRT. Here we seek to replicate those findings using a separate dataset. Methods and materials: We queried the RSSearch Patient Registry for patients treated with SBRT for stage I NSCLC. Kaplan-Meier survival curves, log-rank testing, and Cox proportional hazards modeling were used to evaluate tumor diameter, BED, and treatment planning algorithm as predictors of local control. sBED was defined as BED minus 10 times the tumor diameter (in centimeters). Tumor control probability (TCP) modeling was performed to characterize the relationship between sBED and the likelihood of local control 2 years after SBRT. Results: A total of 928 patients met inclusion criteria. Median BED was 115.5 Gy, and 59% of patients had T1 tumors. Local control rates following treatments planned using a pencil beam algorithm were inferior to those observed following treatments planned using a Monte Carlo algorithm (89% vs 96% at 2 years, log-rank P =.022). In a multivariable Cox model adjusted for tumor diameter and BED, the use of a pencil beam planning algorithm was associated with increased risk of local failure (hazard ratio, 2.39; 95% confidence interval, 1.08-5.29; P =.032). TCP modeling, restricted to patients treated using a Monte Carlo algorithm, demonstrated that sBED values of 60, 80, and 100 Gy yield predicted TCP rates of 91%, 95%, and 97%, respectively. Conclusions: Using a large, multi-institutional database, we found a strong association between treatment planning algorithm and local control rates following SBRT for early-stage NSCLC. sBED is a useful tool for predicting the likelihood of local control following SBRT in this setting.

Original languageEnglish (US)
Pages (from-to)e33-e39
JournalPractical Radiation Oncology
Volume8
Issue number2
DOIs
StatePublished - Mar 1 2018

Fingerprint

Non-Small Cell Lung Carcinoma
Radiotherapy
Neoplasms
Therapeutics
Kaplan-Meier Estimate
Proportional Hazards Models
Registries
Databases
Confidence Intervals

ASJC Scopus subject areas

  • Oncology
  • Radiology Nuclear Medicine and imaging

Cite this

@article{93667c1da69849a296b133300a40cab8,
title = "Stereotactic body radiation therapy for stage I non-small cell lung cancer: The importance of treatment planning algorithm and evaluation of a tumor control probability model",
abstract = "Background: Stereotactic body radiation therapy (SBRT) is increasingly used to treat early-stage non-small cell lung cancer (NSCLC). A previous report introduced the term size-adjusted biologically effective dose (sBED), which accounts for tumor diameter and biologically effective dose (BED) and may be used to predict the likelihood of local control following SBRT. Here we seek to replicate those findings using a separate dataset. Methods and materials: We queried the RSSearch Patient Registry for patients treated with SBRT for stage I NSCLC. Kaplan-Meier survival curves, log-rank testing, and Cox proportional hazards modeling were used to evaluate tumor diameter, BED, and treatment planning algorithm as predictors of local control. sBED was defined as BED minus 10 times the tumor diameter (in centimeters). Tumor control probability (TCP) modeling was performed to characterize the relationship between sBED and the likelihood of local control 2 years after SBRT. Results: A total of 928 patients met inclusion criteria. Median BED was 115.5 Gy, and 59{\%} of patients had T1 tumors. Local control rates following treatments planned using a pencil beam algorithm were inferior to those observed following treatments planned using a Monte Carlo algorithm (89{\%} vs 96{\%} at 2 years, log-rank P =.022). In a multivariable Cox model adjusted for tumor diameter and BED, the use of a pencil beam planning algorithm was associated with increased risk of local failure (hazard ratio, 2.39; 95{\%} confidence interval, 1.08-5.29; P =.032). TCP modeling, restricted to patients treated using a Monte Carlo algorithm, demonstrated that sBED values of 60, 80, and 100 Gy yield predicted TCP rates of 91{\%}, 95{\%}, and 97{\%}, respectively. Conclusions: Using a large, multi-institutional database, we found a strong association between treatment planning algorithm and local control rates following SBRT for early-stage NSCLC. sBED is a useful tool for predicting the likelihood of local control following SBRT in this setting.",
author = "Nitin Ohri and Tome, {Wolfgang A.} and Shalom Kalnicki and Garg, {Madhur K.}",
year = "2018",
month = "3",
day = "1",
doi = "10.1016/j.prro.2017.10.002",
language = "English (US)",
volume = "8",
pages = "e33--e39",
journal = "Practical Radiation Oncology",
issn = "1879-8500",
publisher = "Elsevier BV",
number = "2",

}

TY - JOUR

T1 - Stereotactic body radiation therapy for stage I non-small cell lung cancer

T2 - The importance of treatment planning algorithm and evaluation of a tumor control probability model

AU - Ohri, Nitin

AU - Tome, Wolfgang A.

AU - Kalnicki, Shalom

AU - Garg, Madhur K.

PY - 2018/3/1

Y1 - 2018/3/1

N2 - Background: Stereotactic body radiation therapy (SBRT) is increasingly used to treat early-stage non-small cell lung cancer (NSCLC). A previous report introduced the term size-adjusted biologically effective dose (sBED), which accounts for tumor diameter and biologically effective dose (BED) and may be used to predict the likelihood of local control following SBRT. Here we seek to replicate those findings using a separate dataset. Methods and materials: We queried the RSSearch Patient Registry for patients treated with SBRT for stage I NSCLC. Kaplan-Meier survival curves, log-rank testing, and Cox proportional hazards modeling were used to evaluate tumor diameter, BED, and treatment planning algorithm as predictors of local control. sBED was defined as BED minus 10 times the tumor diameter (in centimeters). Tumor control probability (TCP) modeling was performed to characterize the relationship between sBED and the likelihood of local control 2 years after SBRT. Results: A total of 928 patients met inclusion criteria. Median BED was 115.5 Gy, and 59% of patients had T1 tumors. Local control rates following treatments planned using a pencil beam algorithm were inferior to those observed following treatments planned using a Monte Carlo algorithm (89% vs 96% at 2 years, log-rank P =.022). In a multivariable Cox model adjusted for tumor diameter and BED, the use of a pencil beam planning algorithm was associated with increased risk of local failure (hazard ratio, 2.39; 95% confidence interval, 1.08-5.29; P =.032). TCP modeling, restricted to patients treated using a Monte Carlo algorithm, demonstrated that sBED values of 60, 80, and 100 Gy yield predicted TCP rates of 91%, 95%, and 97%, respectively. Conclusions: Using a large, multi-institutional database, we found a strong association between treatment planning algorithm and local control rates following SBRT for early-stage NSCLC. sBED is a useful tool for predicting the likelihood of local control following SBRT in this setting.

AB - Background: Stereotactic body radiation therapy (SBRT) is increasingly used to treat early-stage non-small cell lung cancer (NSCLC). A previous report introduced the term size-adjusted biologically effective dose (sBED), which accounts for tumor diameter and biologically effective dose (BED) and may be used to predict the likelihood of local control following SBRT. Here we seek to replicate those findings using a separate dataset. Methods and materials: We queried the RSSearch Patient Registry for patients treated with SBRT for stage I NSCLC. Kaplan-Meier survival curves, log-rank testing, and Cox proportional hazards modeling were used to evaluate tumor diameter, BED, and treatment planning algorithm as predictors of local control. sBED was defined as BED minus 10 times the tumor diameter (in centimeters). Tumor control probability (TCP) modeling was performed to characterize the relationship between sBED and the likelihood of local control 2 years after SBRT. Results: A total of 928 patients met inclusion criteria. Median BED was 115.5 Gy, and 59% of patients had T1 tumors. Local control rates following treatments planned using a pencil beam algorithm were inferior to those observed following treatments planned using a Monte Carlo algorithm (89% vs 96% at 2 years, log-rank P =.022). In a multivariable Cox model adjusted for tumor diameter and BED, the use of a pencil beam planning algorithm was associated with increased risk of local failure (hazard ratio, 2.39; 95% confidence interval, 1.08-5.29; P =.032). TCP modeling, restricted to patients treated using a Monte Carlo algorithm, demonstrated that sBED values of 60, 80, and 100 Gy yield predicted TCP rates of 91%, 95%, and 97%, respectively. Conclusions: Using a large, multi-institutional database, we found a strong association between treatment planning algorithm and local control rates following SBRT for early-stage NSCLC. sBED is a useful tool for predicting the likelihood of local control following SBRT in this setting.

UR - http://www.scopus.com/inward/record.url?scp=85043303650&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85043303650&partnerID=8YFLogxK

U2 - 10.1016/j.prro.2017.10.002

DO - 10.1016/j.prro.2017.10.002

M3 - Article

C2 - 29233523

AN - SCOPUS:85043303650

VL - 8

SP - e33-e39

JO - Practical Radiation Oncology

JF - Practical Radiation Oncology

SN - 1879-8500

IS - 2

ER -