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Jaume Bordas-Martinez
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OA01 - Advanced Diagnostic Approaches for Intrathoracic Lymph Nodes and Peripheral Lung Tumors (ID 117)
- Event: WCLC 2019
- Type: Oral Session
- Track: Interventional Diagnostics/Pulmonology
- Presentations: 1
- Now Available
- Moderators:Marioara Simon, Tim Murgu
- Coordinates: 9/08/2019, 10:30 - 12:00, Melbourne (1991)
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OA01.03 - Probability Model for Malignancy in Hilar and Mediastinal Lymph Nodes in Lung Cancer Based on PET-CT and EBUS (Now Available) (ID 133)
10:30 - 12:00 | Presenting Author(s): Jaume Bordas-Martinez
- Abstract
- Presentation
Background
The mediastinal lymph nodes (LN) staging is routinely performed by PET-CT and EBUS- TBNA. Nevertheless, there are no studies that explore the diagnostic capacity of both techniques together. This study aims is to find an algorithm based on combined PET-CT and EBUS image variables together with clinical criteria that provides the most accurate probability of malignancy for each LN explored.
Method
Retrospective study of mediastinal staging of non-small cell lung cancer, based on PET-CT and EBUS-TBNA. The LN were identified by level (N1, N2 and N3) and by anatomical region (AR) (subcarinal, not subcarinal, and hilar). Standardized Uptake Value (SUV) was determined for each sampled LN (maximum, medium and peak) as well as for pulmonary mass, liver, and blood pool. The ultrasound features collected were: diameter in the short axis (DSA), morphology, border, ecogeneicity and presence of the vascular hilium. For the construction of the predictive algorithm a mixed model of logistic regression of Firth was used.
Result
116 consecutive patients were included and a total of 358 LN were evaluated. The set of variables that presented the best discrimination were: age, DSA, SUVmax and AR. The model determines the probability for malignancy for each LN, using the following formula = (-9.26) constant + (-0.21) Age + (4.29) SUVmax + (0.52) DSA + AR. The discrimination power of the model measured by the Area Under the Roc curve was = 0.95.
Conclusion
The model including age, DSA, SUVmax and AR provide the probability of malignancy for each LN with the highest accuracy. All other variables can be discarded when combining PET-CT and EBUS image features.
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P1.18 - Treatment of Locoregional Disease - NSCLC (ID 190)
- Event: WCLC 2019
- Type: Poster Viewing in the Exhibit Hall
- Track: Treatment of Locoregional Disease - NSCLC
- Presentations: 1
- Now Available
- Moderators:
- Coordinates: 9/08/2019, 09:45 - 18:00, Exhibit Hall
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P1.18-03 - How to Predict High Grade Radiation Pneumonitis in Non-Small Cell Lung Cancer Patients Treated with Thoracic Radiotherapy (Now Available) (ID 835)
09:45 - 18:00 | Presenting Author(s): Jaume Bordas-Martinez
- Abstract
Background
Predictive factors of radiation pneumonitis (RP) have been studied without conclusive results. The aim of this retrospective study was to identify clinical, inflammatory or dosimetric factors that could predict the development of high grade RP (HGRP).
Method
A retrospective analysis was conducted in patients with non-small cell lung cancer (NSCLC) treated with concurrent chemo- radiotherapy, secuential chemo-radiotherapy or radiotherapy (RT) alone at the Catalan Institute of Oncology from 2012 to 2016 who developed symptomatic RP. Collected variables were: anthropometric values, Neutrophil-Lymphocyte Ratio (NLR), Platelet-Lymphocyte Ratio, lung function, tumor features (histology, localization, staging) and treatment characteristics. RP was classified using RTOG scale. Patients were divided in 2 groups (low-grade [G1-G2], and HGRP [G3-G5]). Multivariate and regression tree analysis were performed.
Result
Sixty-seven patients were identified: 61% had low-grade RP and 39% HGRP. Development of HGRP was only associated with RT total dose (p=0.045). The most relevant predictive factors of HGRP were tumor location in lower lobes, high NLR values and the presence of peripheral vasculopathy. Figure 1 shows, when tumor is located in lower lobes and NLR is > 2.75, the probability of HGRP was 70% vs 50% when NLR <2.75. In other locations with NLR >4.56 the probability to develop a HGRP was 62%. But, when NLR<4.56, the presence of peripheral vasculopathy and its treatment determine the development of HGRP. When vasculopathy was not treated the probability to develop HGRP was 36% vs 0% when it was treated.61% had low-grade RP and 39% HGRP. Development of HGRP was only associated with RT total dose (p=0.045). When cancer is localized in lower lobes and NLR is > 2.75 the probability to develop HGRP was 70% vs 50% when NLR <2.75. In other locations with NLR >4.56 the probability to develop a HGRP was 62%. But, when NLR<4.56, the presence of vasculopathy and its treatment determine the development of HGRP. When vasculopathy was not treated the probability to develop HGRP was 36% vs 0% when it was treated.
Figure 1. Probability to develop HGRP (G3 –G5)
Conclusion
The probability of develop HGRP has been associated with RT dose and the association of cancer location, NLR, presence of vasculopathy and its treatment.
