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Analysis of early respiratory-related mortality after radiation therapy of non-small-cell lung cancer : feasibility of automatic data extraction for dose–response studies

Stervik, Louise ; Pettersson, Niclas ; Scherman, Jonas ; Behrens, Claus F. ; Ceberg, Crister LU ; Engelholm, Silke ; Gunnarsson, Kerstin ; Hallqvist, Andreas ; Nyman, Jan and Persson, Gitte F. , et al. (2020) In Acta Oncologica 59(6). p.628-635
Abstract

Purpose: To examine the feasibility of automatic data extraction from clinical radiation therapy (RT) databases at four hospitals to investigate the impact of mean lung dose (MLD) and age on the risk of early respiratory-related death and early overall death for patients treated with RT for non-small-cell lung cancer (NSCLC). Material and methods: We included adult patients with NSCLC receiving curatively intended RT between 2002 and 2017 at four hospitals. A script was developed to automatically extract RT-related data. The cause of death for patients deceased within 180 days of the start of RT was retrospectively assessed. Using logistic regression, the risks of respiratory-related death and of overall death within 90 and 180 days... (More)

Purpose: To examine the feasibility of automatic data extraction from clinical radiation therapy (RT) databases at four hospitals to investigate the impact of mean lung dose (MLD) and age on the risk of early respiratory-related death and early overall death for patients treated with RT for non-small-cell lung cancer (NSCLC). Material and methods: We included adult patients with NSCLC receiving curatively intended RT between 2002 and 2017 at four hospitals. A script was developed to automatically extract RT-related data. The cause of death for patients deceased within 180 days of the start of RT was retrospectively assessed. Using logistic regression, the risks of respiratory-related death and of overall death within 90 and 180 days were investigated using MLD and age as variables. Results: Altogether, 1785 patients were included in the analysis of early overall mortality and 1655 of early respiratory-related mortality. The respiratory-related mortalities within 90 and 180 days were 0.9% (15/1655) and 3.6% (60/1655). The overall mortalities within 90 and 180 days were 2.5% (45/1785) and 10.6% (190/1785). Higher MLD and older age were associated with an increased risk of respiratory-related death within 180 days and overall death within 90 and 180 days (all p<.05). For example, the risk of respiratory-related death within 180 days and their 95% confidence interval for patients aged 65 and 75 years with MLDs of 20 Gy was according to our logistic model 3.8% (2.6–5.0%) and 7.7% (5.5–10%), respectively. Conclusions: Automatic data extraction was successfully used to pool data from four hospitals. MLD and age were associated with the risk of respiratory-related death within 180 days of the start of RT and with overall death within 90 and 180 days. A model quantifying the risk of respiratory-related death within 180 days was formulated.

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Contribution to journal
publication status
published
subject
in
Acta Oncologica
volume
59
issue
6
pages
8 pages
publisher
Taylor & Francis
external identifiers
  • scopus:85082423238
  • pmid:32202189
ISSN
0284-186X
DOI
10.1080/0284186X.2020.1739331
language
English
LU publication?
yes
id
d2b7ac8c-7cdb-4b00-a367-c1ec85728733
date added to LUP
2021-01-11 15:33:22
date last changed
2021-02-17 06:29:28
@article{d2b7ac8c-7cdb-4b00-a367-c1ec85728733,
  abstract     = {<p>Purpose: To examine the feasibility of automatic data extraction from clinical radiation therapy (RT) databases at four hospitals to investigate the impact of mean lung dose (MLD) and age on the risk of early respiratory-related death and early overall death for patients treated with RT for non-small-cell lung cancer (NSCLC). Material and methods: We included adult patients with NSCLC receiving curatively intended RT between 2002 and 2017 at four hospitals. A script was developed to automatically extract RT-related data. The cause of death for patients deceased within 180 days of the start of RT was retrospectively assessed. Using logistic regression, the risks of respiratory-related death and of overall death within 90 and 180 days were investigated using MLD and age as variables. Results: Altogether, 1785 patients were included in the analysis of early overall mortality and 1655 of early respiratory-related mortality. The respiratory-related mortalities within 90 and 180 days were 0.9% (15/1655) and 3.6% (60/1655). The overall mortalities within 90 and 180 days were 2.5% (45/1785) and 10.6% (190/1785). Higher MLD and older age were associated with an increased risk of respiratory-related death within 180 days and overall death within 90 and 180 days (all p&lt;.05). For example, the risk of respiratory-related death within 180 days and their 95% confidence interval for patients aged 65 and 75 years with MLDs of 20 Gy was according to our logistic model 3.8% (2.6–5.0%) and 7.7% (5.5–10%), respectively. Conclusions: Automatic data extraction was successfully used to pool data from four hospitals. MLD and age were associated with the risk of respiratory-related death within 180 days of the start of RT and with overall death within 90 and 180 days. A model quantifying the risk of respiratory-related death within 180 days was formulated.</p>},
  author       = {Stervik, Louise and Pettersson, Niclas and Scherman, Jonas and Behrens, Claus F. and Ceberg, Crister and Engelholm, Silke and Gunnarsson, Kerstin and Hallqvist, Andreas and Nyman, Jan and Persson, Gitte F. and Pøhl, Mette and Wahlstedt, Isak and Vogelius, Ivan R. and Bäck, Anna},
  issn         = {0284-186X},
  language     = {eng},
  number       = {6},
  pages        = {628--635},
  publisher    = {Taylor & Francis},
  series       = {Acta Oncologica},
  title        = {Analysis of early respiratory-related mortality after radiation therapy of non-small-cell lung cancer : feasibility of automatic data extraction for dose–response studies},
  url          = {http://dx.doi.org/10.1080/0284186X.2020.1739331},
  doi          = {10.1080/0284186X.2020.1739331},
  volume       = {59},
  year         = {2020},
}