PMID- 31528230
OWN - NLM
STAT- PubMed-not-MEDLINE
LR  - 20200930
IS  - 1837-9664 (Print)
IS  - 1837-9664 (Electronic)
IS  - 1837-9664 (Linking)
VI  - 10
IP  - 19
DP  - 2019
TI  - Comparison of Three Radiobiological Models in Stereotactic Body Radiotherapy for 
      Non-Small Cell Lung Cancer.
PG  - 4655-4661
LID - 10.7150/jca.33001 [doi]
AB  - Objective: The applicability of the linear quadratic (LQ) model to local control 
      (LC) modeling after hypofractionated radiotherapy to treat lung cancer is highly 
      debated. To date, the differences in predicted outcomes between the LQ model and 
      other radiobiological models, which are characterized by additional dose 
      modification beyond a certain transitional dose (d(T)), have not been well 
      established. This study aims to compare the outcomes predicted by the LQ model 
      with those predicted by two other radiobiological models in stereotactic body 
      radiotherapy (SBRT) for non-small cell lung cancer (NSCLC). Methods: Computer 
      tomography (CT) simulation data sets for 20 patients diagnosed with stage Ⅰ 
      primary NSCLC were included in this study. Three radiobiological models, 
      including the LQ, the universal survival curve (USC) and the modified linear 
      quadratic and linear (mLQL) model were employed to predict the tumor control 
      probability (TCP) data. First, the d(T) values for the USC and mLQL models were 
      determined. Then, the biologically effective dose (BED) and the predicted TCP 
      values from the LQ model were compared with those calculated from the USC and 
      mLQL models. Results: The d(T) values from the USC model were 29.6 Gy, 33.8 Gy 
      and 44.5 Gy, whereas the values were 90.2 Gy, 84.0 Gy and 57.3 Gy for the mLQL 
      model for 1-year, 2-year and 3-year TCP prediction. The remarkable higher d(T) 
      values obtained from the mLQL model revealed the same dose-response relationship 
      as the LQ model in the low- and high-dose ranges. We also found that TCP 
      prediction from the LQ and USC models differed by less than 3%, although the BED 
      values for the two models were significantly different. Conclusion: 
      Radiobiological analysis reveals small differences between the models and 
      suggested that the LQ model is applicable for modeling LC using SBRT to treat 
      lung cancer, even when an extremely high fractional dose is used.
FAU - Lu, Jia-Yang
AU  - Lu JY
AD  - Department of Radiation Oncology, Cancer Hospital of Shantou University Medical 
      College, Shantou 515031, Guangdong, China.
FAU - Lin, Zhu
AU  - Lin Z
AD  - Department of Radiation Oncology, Cancer Hospital of Shantou University Medical 
      College, Shantou 515031, Guangdong, China.
FAU - Lin, Pei-Xian
AU  - Lin PX
AD  - Department of Nosocomial Infection Management, The Second Affiliated Hospital of 
      Shantou University Medical College, Shantou 515041, Guangdong, China.
FAU - Huang, Bao-Tian
AU  - Huang BT
AD  - Department of Radiation Oncology, Cancer Hospital of Shantou University Medical 
      College, Shantou 515031, Guangdong, China.
LA  - eng
PT  - Journal Article
DEP - 20190808
PL  - Australia
TA  - J Cancer
JT  - Journal of Cancer
JID - 101535920
PMC - PMC6746137
OTO - NOTNLM
OT  - non-small cell lung cancer
OT  - radiobiological models
OT  - stereotactic body radiotherapy
COIS- Competing Interests: The authors have declared that no competing interest exists.
EDAT- 2019/09/19 06:00
MHDA- 2019/09/19 06:01
PMCR- 2019/01/01
CRDT- 2019/09/19 06:00
PHST- 2019/01/10 00:00 [received]
PHST- 2019/06/06 00:00 [accepted]
PHST- 2019/09/19 06:00 [entrez]
PHST- 2019/09/19 06:00 [pubmed]
PHST- 2019/09/19 06:01 [medline]
PHST- 2019/01/01 00:00 [pmc-release]
AID - jcav10p4655 [pii]
AID - 10.7150/jca.33001 [doi]
PST - epublish
SO  - J Cancer. 2019 Aug 8;10(19):4655-4661. doi: 10.7150/jca.33001. eCollection 2019.