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- Stervik, Louise, 1993, et al.
(författare)
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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
- 2020
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Ingår i: Acta Oncologica. - 0284-186X. ; 59:6, s. 628-635
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Tidskriftsartikel (refereegranskat)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 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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| 2. |
- Stervik, Louise, 1993, et al.
(författare)
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Modelling the risk of fatal acute toxicity following radiotherapy of lung cancer
- 2018
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Ingår i: Physica medica. Vol. 52, Suppl. 1, p. 30. 2nd European Congress of Medical Physics. - : Elsevier BV. - 1120-1797 .- 1724-191X.
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Konferensbidrag (refereegranskat)abstract
- Purpose:To model the risk of fatal acute toxicity after conventionally fractionated curative radiotherapy of patients with non-small-cell lung cancer (NSCLC). Methods:Scripting was used to automatically extract treatment-related data for all patients treated for NSCLC between 2008 and 2016 from three hospitals. Inclusion criteria were conventionally fractionated curative radiotherapy and no prior treatment in the thorax region. Maximum likelihood estimation and logistic regression (LR) were used to model the risk of fatal acute toxicity defined as death within 90 days from treatment start. Mean lung dose (MLD), patient age and the volume of the gross tumour volume (GTV) were investigated as predictors in a univariable LR analysis. We performed analysis on the data from the three hospitals separately and merged. Predictor variables were considered statistically significant if p < 0.05. All predictor variables with a p < 0.1 were further analysed in multivariable LR models. Confidence intervals (CIs) for the predictors were calculated using the likelihood ratio test. CIs for the multivariable models were calculated by bootstrapping. Results:Data was extracted for 848 patients. The incidence of death within 90 days from treatment start was 3.8% (32/848) for the merged data set and varied from 1.8% to 5.4% between hospitals. For the hospital with the highest incidence, a statistically significant relationship between MLD and the risk of fatal acute toxicity (p = 0.020) was found. The model parameters and their 95% CIs were D50=42.8 (31.4-167.7) Gy and γ50=1.20 (0.77-1.68). In the univariable LRs with patient age and GTV volume, patient age had p-values < 0.1 and GTV volume p-values > 0.2. Multivariable LR with MLD and patient age resulted in a statistically significant multivariable model (p = 0.005) for the merged data. The calculated risks and their 95% CIs for a patient with MLD = 20 Gy were 1.6% (0.5-3.3%), 2.8% (1.3-4.5%), 4.9% (3.1-6.8%), and 8.6% (4.8-13.5%) at 50, 60, 70, and 80 years of age, respectively. Conclusions:A statistically significant multivariable model quantifying the risk of fatal acute toxicity with MLD and patient age as predictor variables was found.
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